· PDF fileTABLE OF CONTENTS PREFACE OPENING ADDRESS BY PROF. E. VAN RANST, CHAIRMAN STEERING...

NNeeww wwaavveess iinn PPhhyyssiiccaall LLaanndd RReessoouurrcceess

Proceedings of the Workshop for Alumni of the M.Sc. programmes in Soil Science, Eremology and

Physical Land Resources

Refresher Course supported by the Flemish Interuniversity Council (VLIR-UOS)

Edited by Dominique Langouche & Eric Van Ranst

GHENT UNIVERSITY 3-9 SEPTEMBER 2006

New waves in Physical Land Resources

Proceedings of the Workshop for Alumni of the M.Sc. programmes in Soil Science, Eremology and Physical Land Resources ISBN 9789076769950 Edited by Eric Van Ranst & Dominique Langouche GHENT UNIVERSITY 3-9 SEPTEMBER 2006

TABLE OF CONTENTS

PREFACE OPENING ADDRESS BY PROF. E. VAN RANST, CHAIRMAN STEERING COMMITTEE PHYSICAL LAND RESOURCES AND PROMOTOR OF THE MASTER PROGRAMME (UGENT) OPENING ADDRESS BY RECTOR P. VAN CAUWENBERGHE (UGENT) OPENING ADDRESS BY MS. K. VERBRUGGHEN, DIRECTOR OF VLIR-UNIVERSITY DEVELOPMENT CO-OPERATION SECTION OPENING LECTURES ....................................................................................................................................... 1

SUSTAINABLE LAND MANAGEMENT IN THE ETHIOPIAN HIGHLANDS............................................ 2 MITIKU HAILE..................................................................................................................................................... 2 NEW CHALLENGES OF SOIL SCIENCE TO FOOD SECURITY WITH SPECIAL REFERENCE TO CHINA ............................................................................................................................................................. 14 TANG HUAJUN & ZHOU WEI............................................................................................................................. 14 WORKS ON EROSION PROCESSES UNDER WIND-DRIVEN RAIN CONDITIONS IN I.C.E ................ 24 GUNAY ERPUL1 & DONALD GABRIELS2 ............................................................................................................ 24

WORKSHOP THEME A – SOIL AND GROUNDWATER POLLUTION AND REMEDIATION.......... 36 SUB-THEME : MANAGING CONTAMINATED SOILS USING PHYTOREMEDIATION ................... 37 ERIK MEERS, FILIP M. G. TACK, MARC G. VERLOO ......................................................................................... 37

COMPARISON OF AMENDMENTS USED TO REMEDIATE ACID MINE TAILINGS: ENVIRONMENTAL AND AGRICULTURAL APPLICATIONS .................................................................. 39 Kelly A. Senkiw and Tee Boon Goh*............................................................................................................ 39 STUDY ON THE EFFECTS OF TRADE VILLAGE WASTE ON ACCUMULATION OF Cu, Pb, Zn AND Cd IN AGRICULTURAL SOILS OF PHUNG XA VILLAGE, THACH THANH DISTRICT, HA TAY PROVINCE.................................................................................................................................................. 49 Nguyen Huu Thanh1, Tran Thi Le Ha1 *, Nguyen Duc Hung1, Tran Duc Hai2 ............................................ 49 METAL CONTAMINATION IN IRRIGATED AGRICULTURAL LAND: CASE STUDY OF NAIROBI RIVER BASIN, KENYA................................................................................................................................ 60 P.N. Kamande1*, F.M.G. Tack2 ................................................................................................................... 60

SUB-THEME : MANAGING GROUNDWATER POLLUTION FROM WASTE DISPOSAL SITES .... 63 KRISTINE WALRAEVENS, MARLEEN COETSIERS, KRISTINE MARTENS, MARC VAN CAMP ............................... 63

CONTAMINATION OF THE MARIMBA RIVER TRIBUTARY, ZIMBABWE, WITH Cu, Pb, Zn AND P BY INDUSTRIAL EFFLUENT AND SEWER LINE DISCHARGE. .................................................................. 66 Bangira, C*.Wuta, M., Dube, H.M and Chipatiso, L. .................................................................................. 66 CONTROLLING PHOSPHORUS (P) MOBILITY IN POORLY P SORBING SOILS: DRINKING-WATER TREATMENT RESIDUALS (WTR) TO THE RESCUE ............................................................................... 75 S. Agyin-Birikorang1*, G.A. O’Connor1 and L.W. Jacobs2.......................................................................... 75 Effects of WTR on P losses .......................................................................................................................... 84 HEAVY METAL CONTAMINATION OF SOIL AND SURFACE WATER BY LEACHATES OF AN OPEN DUMP OF MUNICIPAL SOLID WASTE: A CASE STUDY OF OBLOGO LANDFILL IN THE GA WEST DISTRICT OF ACCRA, GHANA................................................................................................................. 87 Abuaku Ebenezer*....................................................................................................................................... 87

CONCLUSIONS.............................................................................................................................................. 89 WORKSHOP THEME B – INTEGRATED SOIL FERTILITY MANAGEMENT .................................... 92

SUB-THEME : USE OF ISOTOPE TECHNIQUES FOR ................................................................................... 93 NUTRIENT MANAGEMENT ........................................................................................................................ 93 P. BOECKX, K. DENEF, AND O. VAN CLEEMPUT ............................................................................................... 93

ENHANCING THE AGRONOMIC EFFECTIVENESS OF NATURAL PHOSPHATE ROCK WITH POULTRY MANURE: A WAY FORWARD TO SUSTAINABLE CROP PRODUCTION .................... 95 S. Agyin-Birikorang1*, M.K. Abekoe2, O.O. Oladeji1, S.K.A. Danso2 ......................................................... 95 THE EFFECT OF LIMING AN ACID NITISOL WITH EITHER CALCITE OR DOLOMITE ON TWO COMMON BEAN (Phaseolus vulgaris L.) VARIETIES DIFFERING IN ALUMINIUM TOLERANCE ........................................................................................................................................... 108

E .N Mugai1*, S.G Agong1 and H. Matsumoto2 ......................................................................................... 108 EFFECT OF P FERTILISERS AND WEED CONTROL ..................................................................... 117 ON THE FATE OF P FERTILISERS APPLIED TO SOILS................................................................ 117 UNDER SECOND-ROTATION PINUS RADIATA ............................................................................... 117 A. A. Rivaie1, P. Loganathan2, and R. W. Tillman2 ................................................................................... 117

SUB-THEME : ORGANIC FARMING IN THE TROPICS PRESENT SITUATION, POSSIBILITIES AND CHALLENGES................................................................................................................................... 120 STEFAAN DE NEVE.......................................................................................................................................... 120

LOW INPUT APPROACHES FOR SOIL FERTILITY MANAGEMENT VERIFIED FOR SEMI-ARID AREAS OF EASTERN UGANDA ................................................................................................ 123 Kayuki C.Kaizzi1, Byalebeka John1, Charles S. Wortmann2 and Martha Mamo2 ..................................... 123 AMELIORATION OF ACID SULFATE SOIL INFERTILITY IN MALAYSIA FOR RICE CULTIVATION................................................................................................................................................................... 133 J. Shamshuddin.......................................................................................................................................... 133

WORKSHOP THEME C – LAND EVALUATION AND LAND DEGRADATION................................. 144 SUB-THEME : LAND EVALUATION FOR SUSTAINABLE LAND MANAGEMENT & POLICY MAKING ................... 145 A. VERDOODT & E. VAN RANST..................................................................................................................... 145

OIL PALM AND RUBBER PRODUCTION MODEL FOR SUBSTITUING RUBBER WITH OIL PALM AND EVALUATING TO ESTABLISH OIL PALM INTO NORTHEAST THAILAND .......... 149 S. Pratummintra1, E.Van Ranst2, H.Verplancke2, A. Verdoodt2 ................................................................ 149 SOIL PROPERTIES AND BIOLOGICAL DIVERSITY OF UNDISTURBED AND DISTURBED FORESTS IN MT. MALINDANG, PHILIPPINES ............................................................................... 162 Renato D. Boniao1*, Rosa Villa B. Estoista2 , Carmelita G. Hansel2, Ron de Goede4, .............................. 162 Olga M. Nuneza3, Brigida A. Roscom3, Sam James5, Rhea Amor C. Lumactud1, ..................................... 162 Mae Yen O. Poblete1 and Nonillon Aspe3.................................................................................................. 162

SUB-THEME : LAND DEGRADATION : PRESSURES, INDICATORS AND RESPONSES ............... 173 VARIOUS APPROACHES FOR SOIL EROSION RISK ASSESSMENT .................................................................... 173 W. CORNELIS, D. GABRIELS, H. VERPLANCKE................................................................................................ 173

INDICATORS AND PARTICIPATORY METHODS FOR MONITORING LAND DEGRADATION. A CASE STUDY IN THE MIGORI DISTRICT OF KENYA. ................................................................... 175 Vincent de Paul Obade1*, Eva De Clercq2 ................................................................................................ 175 PROPOSED PLAN OF ACTION FOR RESEARCH ON DESERTIFICATION IN THE SUDAN:... 181 GEZIRA AND SENNAR STATES .......................................................................................................... 181 Kamal Elfadil Fadul and Fawzi Mohamed Salih ...................................................................................... 181 DIAGNOSTIC OF DEGRADATION PROCESSES OF SOILS FROM NORTHERN TOGO (WEST AFRICA) AS A TOOL FOR SOIL AND WATER MANAGEMENT..................................................... 187 Rosa M Poch*, Josep M Ubalde ............................................................................................................... 187

CONCLUSIONS............................................................................................................................................ 195 WORKSHOP THEME D – SOIL SURVEY AND INVENTORY TECHNIQUES.................................... 196

SUB-THEME : DEVELOPMENTS IN SOIL (ATTRIBUTE) MAPPING WITH AN APPLICATION IN MAPING GROUNDWATER DEPTH ....................................................................................................... 197 P.A. FINKE ...................................................................................................................................................... 197

USING GEOGRAPHIC INFORMATION SYSTEMS AND GLOBAL POSITIONING SYSTEM TO MAP SOIL CHARACTERISTICS FOR LAND EVALUATION........................................................................... 199 P. Wandahwa1* J. A. Rota1, and D. O. Sigunga2 ....................................................................................... 199

SUB-THEME : DEVELOPMENTS IN GIS AND REMOTE SENSING WITH EMPHASIS ON HIGH RESOLUTION IMAGERY AND 3-D PRESENTATION TECHNIQUES ............................................ 208 R. GOOSSENS .................................................................................................................................................. 208

GEOMORPHOLOGY AND CLASSIFICATION OF SOME PLAINES AND WADIES ADJACENT TO GABEL ELBA, SOUTH EAST OF EGYPT................................................................................................ 210 El-Badawi, M. and Abdel-Fattah, A. ......................................................................................................... 210 HIGH RESOLUTION TERRAIN MAPPING AND VISUALIZATION OF CHANNEL MORPHOLOGY USING LiDAR AND IFSAR DATA............................................................................................................ 225 Sudhir Raj Shrestha1*, Dr. Scott N. Miller2 ............................................................................................... 225

SUB-THEME : DEVELOPMENTS IN SOIL SAMPLING AND PROXIMAL SENSING WITH APPLICATIONS IN PRECISION AGRICULTURE .............................................................................. 226 M. VAN MEIRVENNE, U.W.A. VITHARANA L. COCKX ................................................................................... 226

ESTIMATING SPATIAL VARIABILITY OF SOIL SALINITY USING COKRIGING IN BAHARIYA OASIS, EGYPT....................................................................................................................................................... 228 Kh. M. Darwish*, M.M. Kotb and R. Ali ................................................................................................... 228 SPATIAL VARIABILITY OF DRAINAGE AND PHOSPHATE RETENTION AND THEIR INTER RELATIONSHIP IN SOILS OF THE SOUTH-WESTERN REGION OF THE NORTH ISLAND, NEW ZEALAND.................................................................................................................................................. 242 A.Senarath*, A.S.Palmer and R.W.Tillman ............................................................................................... 242

CONCLUSIONS........................................................................................................................................... 252 WORKSHOP THEME E – SOIL PROCESSES AND ANALYTICAL TECHNIQUES........................... 254

SUB-THEME : DEVELOPMENTS IN SOIL GENESIS AND MINERALOGY.............................................. 255 VAN RANST E. & MEES F. .............................................................................................................................. 255

IMPACT OF ACID DEPOSITION ON CATION LEACHING FROM...................................................... 258 Mt. TALANG AIRFALL ASH..................................................................................................................... 258 Fiantis, D., Nelson1, E. Van Ranst2 and J. Shamshuddin3 ......................................................................... 258 STONE LINES AND WEATHERING PROFILES OF FERRALLITIC SOILS IN NORTHEASTERN ARGENTINA ............................................................................................................................................. 269 Morrás, H.1*, Moretti, L.1, Píccolo, G.2, Zech,W.3..................................................................................... 269 PEDOGENESIS ALONG A HILLSLOPE TRAVERSE IN THE UPPER AFRAM BASIN, GHANA.......... 281 T. Adjei-Gyapong,1 E. Boateng,1* C. Dela Dedzoe,1 W.R. Effland,2 M.D. Mays2 and J.K. Seneya1 ......... 281 INFLUENCE OF TITANOMAGNETITE ON DITHIONITE-CITRATE-BICARBONATE (DCB) AND OXALATE EXTRACTIONS IN WEATHERED DOLERITE ...................................................................... 283 C. G. Algoe 1*, E. Van Ranst 2, G. Stoops 3................................................................................................ 283

SUB-THEME : DEVELOPMENTS IN SOIL MICROMORPHOLOGY .......................................................... 291 STOOPS, G., MARCELINO, V., MEES, F............................................................................................................ 291

SPHEROIDAL WEATHERING OF DOLERITE IN SURINAME: EVIDENCE FROM PHYSICAL, CHEMICAL AND MINERALOGICAL DATA ........................................................................................... 295 C. G. Algoe 1*, E. Van Ranst 2, G. Stoops 3................................................................................................ 295 MICROMORPHOLOGICAL CHARACTERISTICS OF ANDISOLS IN WEST JAVA, INDONESIA ........ 296 Mahfud Arifin*, Rina Devnita.................................................................................................................... 296 MICROMORPHOLOGICAL FEATURES OF SOME SOILS IN THE AFRAM PLAINS (GHANA, WEST AFRICA).................................................................................................................................................... 307 M.D. Mays1, W.R. Effland2, T. Adjei-Gyapong3, C.D. Dedzoe3 and E. Boateng4*................................... 307

CONCLUSIONS........................................................................................................................................... 308 CLOSING ADDRESS BY PROF. E. VAN RANST, CHAIRMAN STEERING COMMITTEE PHYSICAL LAND RESOURCES AND PROMOTOR OF THE MASTER PROGRAMME (UGENT) 311 AGENDA ........................................................................................................................................................... 314 LIST OF PARTICIPANTS .............................................................................................................................. 318

PREFACE

The 5th Refresher Course for alumni of our Master programmes is organised with the aim to point out needs for feedback, co-operation and support for alumni, and present information and means to fill gaps and remediate shortcomings. In addition, the objective is to brief the alumni on the latest developments in the field of Soil Science and Engineering Geology, within the expertise available at the International Centre for Physical Land Resources.

While in the former editions of the Refresher Course, which took place in South-East Asia, Africa and Latin America, there was a strong accent on transfer of knowledge from the International Training Centre for Pos-Graduate Soil Scientists (ITC-Ghent), towards alumni, now an overall exchange of knowledge and information from alumni to staff and vice versa, as well as amongst alumni is envisaged. It is the intention to create or improve channels of communication as an indispensable vehicle for co-operation.

This publication collects all contributions from alumni that were submitted for the different workshops organised in the frame of this Refresher Course. The contributions are arranged per workshop theme, and introduced by each scientific committee appointed for each workshop. Care is taken to add a selection of valuable references pertaining to each workshop theme.

Welcome

WELCOME

Opening Address by Prof. E. Van Ranst, Chairman Steering Committee Physical Land Resources and Promotor of the Master Programme (UGent)

Opening Address by Rector P. Van Cauwenberghe (UGent)

Opening Address by Ms. K. Verbrugghen, Director of VLIR-University Development

Co-operation Section

Welcome

Opening Address by Prof. E. Van Ranst, Chairman Steering Committee Physical Land Resources and Promotor of the Master

Programme (UGent)

Given at the occasion of the fifth refresher course for alumni of the Master of Science Programmes in Soil Science (UGent), Eremology (UGent) and Physical Land Resources (UGent-VUB)

4 September 2006

The Rector of Ghent University, The Director of the Secretariat for University Development Co-operation of the Flemish

Interuniversity Council, Esteemed Guests, Dear Alumni, Dear Colleagues, Welcome at our 5th refresher course for alumni. We are happy to be able to welcome today about 40 alumni. When we take into account all alumni who reacted to our call for participation, this number would have been around one hundred (100). However, financial constraints proved to be a stumbling stone for many. The 5th Refresher Course for Alumni of our Master programmes is organised with the aim to point out needs for feedback, co-operation and support for alumni, and to present information and means to fill gaps and remediate shortcomings. In addition, it is the objective to brief the alumni on the latest developments in the field of Soil Science and Engineering Geology, within the expertise available at the International Centre for Physical Land Resources. While in the former editions of the Refresher Course, which took place in South-East Asia, Africa and Latin America, there was a strong accent on transfer of knowledge from the International Training Centre for Post-Graduate Soil Scientists towards the alumni, now an overall exchange of knowledge and information from alumni to staff and vice versa, as well as amongst alumni is aimed at. It is the intention to create or improve channels of communication as an indispensable vehicle for co-operation. We, the programme organisers, are proud and honoured that Prof. Van Cauwenberge, the Rector of Ghent University, which is hosting this workshop, has committed himself to address this meeting at the occasion of the opening. We know that he has a full agenda. In fact, his secretariat informed us that he has to be in Brussels today at eleven (11) ‘o clock, and he will have to leave us shortly after his opening address. We are also pleased with the presence of Ms. Verbrugghen, Director of VLIR-University Development Co-operation Section, and sponsor of this workshop, who kindly accepted to welcome you here today.

Welcome

Since 1997, the financing and scholarships that "the International Course Programme's, including ours, receive from the Belgian Administration for Development Co-operation are being administered through the Flemish Interuniversity Council – or VLIR , and more in particular the department University Development Co-operation. VLIR is a familiar name for all our graduates since.

Both distinguished speakers are invited to welcome the audience

Prof. E. Van Ranst

Welcome

Opening Address by Rector P. Van Cauwenberghe (UGent)


4 September 2006

Dear Alumni, Dear Colleagues, Esteemed Guests, It is my great pleasure and honour to welcome you at Ghent University. Ghent University has a long standing tradition of internationally oriented education and research. In fact, the international course programme in Physical Land Resources, which has roots back to 1963, is the very proof of this. And you – its alumni – are the living testimony. Up to this day, Ghent University is involved in many international projects and maintains intensive contacts with research institutes and laboratories all over the world. This university’s concern for the world beyond the national borders manifests itself foremost in the education and training of foreign students. Since 1963, up to this day, about 1000 alumni from over 90 countries worldwide graduated from the Master programmes in Soil Science, Eremology and Physical Land Resources at Ghent University and, since 1997, also at the Free University of Brussels. In the present day meeting, I see faces from more than 20 different nations, a number that without any doubt would have been much higher were it not for budgetary constraints. While the international course programme would not be successful without the day-to-day dedication of its promoters and staff, the programme is also highly indebted to you, the alumni. You act as scientific ambassadors by disseminating your knowledge into your home institution and country and as key persons in forming a bridge between your institution and Ghent University. Indeed, many of the research projects that have been and are being carried out, were set up through co-operation with graduates from this university. All initiatives that foster communication and networking and which reinforce ties between the university and its former students deserve our highest consideration and support. Yet, when exchanging knowledge care has to be taken to consider the local cultural, social and material reality. While for a soil scientist, it is as clear as mud that it is important to find a common ground, collaboration should consist of support, encouragement, catalysation and help from the North to find that little bit extra, while the actual work has to be done in and by the South. The will has to exist, to have a relevant impact on the local community and to develop a clear vision of the future. Soil is a key natural resource which requires better management to support sustainable development and to preserve this basic commodity for future generations. There is a need for well trained soil professionals with a sound scientific understanding of soil systems, but who can also develop policy and provide practical advice and guidance.

Welcome

As soil experts, you are aware of the fact that to get off the ground – you have to know the ground you walk on, and you have to see what something is worth on the ground. In the course of this day, several speakers will take the word with no other purpose than to inform you about several existing possibilities to find support and to establish co-operation, and this at different levels and scales. In the course of this week, there will be plenty of occasions to meet and to refresh contacts, both with staff from the International Course Programme in Physical Land Resources and with your colleagues from the South. I hope that you will grasp this golden opportunity with both hands. I sincerely wish to thank here the Flemish Interuniversity Council, and in particular the University Development Cooperation Section, for its financial support to the promoters of the International Course Programme Physical Land Resources to organise an event like this. While the course programme provided you with the intellectual luggage, a workshop like this is intented to prospect channels for carrying that luggage to your targets, yet staying down to earth and touching ground. Above all, the International Centre for Physical Land Resources aims to act as a two-directional gateway for knowledge exchange. To conclude, I hope that you will leave no stone unturned and cover a lot of ground the coming days, so that you come in sight of fine land. I think this is the most I can wish to sons and daughters of the soil.

Prof. P. Van Cauwenberghe

Welcome

Opening Address by Ms. K. Verbrugghen, Director of VLIR-University Development Co-operation Section

Given at the occasion of the fifth refresher course for alumni of the Master of Science Programmes in

Soil Science (UGent), Eremology (UGent) and Physical Land Resources (UGent-VUB)

4 September 2006

Dear Alumni, Dear Colleagues, Esteemed Guests, It is my pleasure to be given the opportunity to say a few words to you. First of all, I want to congratulate you all, not only for the fact that quite years ago you were selected as VLIR scholar out of, in many cases, hundreds of quality applications, proving your quality standard already at that stage, but also for the fact that you all succeeded and obtained a Master degree, and indeed returned to your home countries. Now you have all been called back to Belgium, for a number of reasons. First of all, to update your scientific knowledge of the field of study, physical land resources, to exchange information and experience and specific cases. This will allow you to be better equipped for your own job back home, but this will also allow the course organisers in Belgium to further improve their training programme. We want to learn from you, on the basis of your experience, how the training programme can be improved in terms of quality as well as of development relevance. Furthermore, integrating your experiences and cases into the training programme will allow also the other students from Belgium or elsewhere to get access to this valuable information. So this will contribute to the quality and the relevance of the training programme, both for the southern but also the northern students. But your being here will also allow you to improve your own network, first of all with the course organisers in Belgium, but also with your colleague graduates. So do talk to one another. Exchange business cards. Initiate long-lasting partnerships across frontiers. Because academic cooperation consists of both north south but also south south cooperation. And then finally you will be given more information on the opportunities that VLIR is providing. I am proud to be able to announce that this refresher course, organised by Ghent University, is co-financed by VLIR. For us, the result of an international course is not obtained by you getting your Master degree. No, we want you to go back home, to your home institution, and to make the difference there, by applying the knowledge that you acquired here, by passing on the knowledge to colleagues and peers, by training others. Only then, the intervention by VLIR, our funding, will be a good investment from the perspective of development cooperation. Our baseline is : sharing minds, changing lives. It is our common responsibility, also yours, to join brains and forces to help and improve the quality of life in the south.

Welcome

This afternoon, my colleague Frank will elaborate more on the wide range of funding opportunities that VLIR is providing. Over the last years, we have added quite many new opportunities, so we will be happy to give you an overview. He will also briefly touch upon the opportunities offered by other institutions in Belgium that are involved in development cooperation. Maybe there is something in it for you! But please, remember one thing: VLIR does not directly fund individuals or organisations in the south. We fund cooperation between individuals and universities or research institutions in the south, and one or more Flemish universities. We want you to occupy and to continue to occupy a key or strategic position in your home country from where you can contribute to the development of your country, through science, and we want you to link up with our Flemish scientists. If those two conditions are fulfilled, we will happily look forward to receiving proposals from your side. I once again thank the organisers of this event, and prof. Van Ranst in particular, for the time given to me today, and I wish you all the best. Let’s keep in touch!

Ms. K. Verbrugghen

Welcome

Opening Lectures

1

OPENING LECTURES

Sustainable Land Management in Ethiopian Highlands Mitiku Haile New Challenges of Soil Science to Food Security with Special Reference to China Tang Huajun, Zhou Wei Works on Erosion Processes under Wind-Driven Rain Conditions in I.C.E Gunay Erpul, Donald Gabriels

Opening Lectures

2

SUSTAINABLE LAND MANAGEMENT IN THE ETHIOPIAN HIGHLANDS

Mitiku Haile

Mekelle University, Mekelle, Ethiopia

1. INTRODUCTION 1.1 Development situation and policy

1.1.1 General Ethiopia is an agrarian country with 85% of the population earning their livelihoods from agriculture. It is one of the poorest countries in the world with a GDP of US$110 per capita per annum and 45.5 % of the population is below the poverty line. The country has suffered repeated famines over the last half century, and agriculture has failed to generate capital for diversifying and transforming the country’s economy. Hence reducing poverty through improving rural production and livelihoods is central to the country’s development agenda.

There have been a number of policy initiatives since the present government which came to power in 1991 has sought to address these issues. The overall guiding framework initially developed and still adhered to is ADLI, Agricultural Development Led Industrialization . This sees increased production in the rural areas as critical for generating the materials, market base, surplus labor, export earnings and capital for industrialization. In 2002, along with most developing world countries and in response to the identification of poverty reduction as the key target in the millennium development goals, the government developed its own poverty reduction strategy paper (PRSP) entitled the “Sustainable Development and Poverty Reduction Programme” (SDPRP). In 2005 this was superseded by an updated SDPRP called the “Plan for Accelerated and Sustainable Development to End Poverty” (PASDEP). This provides guidance for the second five years of the PRSP process. The other guiding document is the Federal Government’s Rural Development Policy and Strategies launched in 2003.

The emphases in these three documents respectively are as follows: SDPRP seeks to:

support ADLI by generating a primary surplus to fuel growth in other sectors, use (option) menu-based extension packages to enhance farmer choice of technologies, undertake investment in education to overcome critical capacity constraints, increase from 4m to 6m the households covered by Extension Packages, and support agricultural research, water harvesting and small-scale irrigation.

Rural Development Policies includes: crop intensification in high rainfall areas, livestock improvement and water resource development in pastoral areas, water harvesting and lands conservation in drought-prone areas, and livestock improvement through improved breeds and technology.

Opening Lectures

3

PASDEP aims to: capture the private initiative of farmers and support a shift to diversification and

commercialization in agriculture, support pro-poor subsistence farming where the aim is to increase crop yields for

domestic use and to ensure food security, provide intensified extension support at the kebele level to facilitate innovation.

In all these policies the need for skilled staff and for innovations based on farm-tested research findings are present. It is in this way that higher education and research from the agricultural faculties of universities can contribute to rural development, poverty reduction and the country’s achievement of the Millennium Development Goals. To this end Faculties of Agriculture, Junior Colleges and Training and Vocational Education Centers are engaged in adressing issues of sustainable land management as a basis for increased productivity. 1.1.2 Higher Education's Role in Development Tertiary education plays a key role in the economic and social development of any nation. This is particularly the case in today's globalizing, information and knowledge-based economy. No country can expect to successfully integrate into, and benefit from, the 21st century economy without a well-educated workforce. The task of integration is particularly great for countries like Ethiopia given the low level of education attainment of the country’s labor force, and the urgent need for sustained economic growth in order to reduce poverty. Furthermore, there are few higher education institutions with the skills, equipment and mandate to generate new knowledge and to adapt knowledge developed elsewhere to the local context. 1.1.3 Education Policy Ethiopia adopted an Education and Training Policy in 1994. The policy encompasses general and specific objectives, as well as implementation strategies that include formal and non-formal education, from kindergarten to higher education. Emphasis is placed on the development of problem-solving capacities, with a particular focus on the acquisition of both theoretical and practical knowledge.

The long-term aim is to achieve the goal of universal primary education by the year 2015. The strategy developed to implement the policy calls for sustained public investment programme through the mobilization of national and international resources. The policy seeks to develop synergy between education, training, research and development through coordinated participation by relevant organizations.

One outcome of this policy was the formulation of a sector-wide approach. The first Education Sector Development Programme was launched in 1996/1997 and was completed five years later in 2001/2002. The second five year Education Sector Development Programme became operational in 2001/2002, overlapping slightly with the first one, and was concluded in 2005/2006. The major components of the programmes were to: (1) increase enrolment; (2) improve leadership and management; (3) ensure quality and relevance; (4) improve institutional efficiency; and (5) provide a logistic framework.

For about five decades the country had only two universities (Addis Ababa and Alemaya). As the primary and secondary education facilities increased, these institutions were unable to provide enough opportunities for quality higher education to the growing numbers of school leavers. In addition, the tremendous increase in the participation rate in primary and secondary education resulted in increased demands for qualified teachers at the various levels.

Opening Lectures

4

To partially meet these growing demands, the country was obliged to expand the higher education sector. As a result, the sector witnessed rapid expansion between 1997 and 2001 with the establishment of Bahir Dar, Debub (Awassa), Jimma, and Mekelle universities. This involved amalgating existing colleges in these towns. Further, to meet the growing need for qualified manpower by various sectors of the economy, professional programs were developed in business, education, engineering and health in Alemaya, Arba Minch, Dila, Jimma and Mekelle. The next five years saw the realization of three additional universities, namely Arba Minch, Gonder and Adama, by upgrading Arba Minch Institute of Water Technology, Gonder College of Health Sciences and Nazareth College of Technical Teacher Education, respectively. This brought the number of public sector universities to nine. At the present point in time, there are 12 new universities being established in Dessie, Debre Berhan, Debre Markos, Nekemt, Bale-Robe, Sodo, Dilla, Mizan Teferi/Tepi, Jigjiga, Semera, Dire Dawa and Axum.

Expansion is not limited to increasing the number of higher education institutions, but also involves enlarging the number of academic programs they offer and their student intake. This has resulted in a tremendous increase in the participation rate in higher education. Within nine years, higher education enrolment in regular programs has increased from about 42,100 in 1997 to 103,500 in 2005 - an increase of 146 percent.

In addition to the expansion in terms of institutions, programmes and student numbers, higher education is undergoing rapid transformation in other respects. Cognizant of the fact that expansion needs to be supported by improvements in the management and operation of the higher education system, the Government has embarked upon an overall reform programme. This is part and parcel of the Civil Service Reform Programme the country has been implementing over the last few years. This requires organizations to become result-orientated, rather than input-oriented. The most important components of this transformation for higher education are: improving leadership, governance and management, and creating an enabling culture to provide appropriate tertiary level education. Relevance of the programmes to the economic development priorities of the country, as well as efficiency and effectiveness in the delivery of education and the use of scarce resources, are core areas of concern in this transformation.

Experience shows that “massification” at an unprecedented scale can lead to deterioration in quality. Realizing this, the Government established, in 2003, an autonomous body called the Higher Education Relevance and Quality Assurance Agency to make sure that appropriate and effective teaching support and learning opportunities are provided for students. It is responsible for internal audit undertaken by the institutions themselves and external audits which the Agency itself carries out. The audits assess the institutions' system of accountability and internal review mechanisms to ensure that each institution's quality assurance process complies with accepted standards. In addition to this Agency, a Higher Education Strategy Centre was established in 2003 to formulate policies as well as devise strategic directions for the higher education sector.

Sustainable land management as a course is provided in the universities and other colleges to enable graduates perceive the processes of land degradation and also design mitigating solutions.Cognizant of the fact, the extension packages of the agricultural and natural resources management sector have been improved to incorporate soil and water conservation practicies not only as a community endeavour but also as a farm management tool within households.

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2. ENVIRONMENTAL CHARACTERISTICS

Ethiopia, with a population of 76 million people and annual growth rate of 2.36%, is the second largest country in sub-Saharan Africa. It has a surface area of 1.12 million km² and an average population density of 62 persons per km². The elevation of the country varies from 120 m below sea level at Dalool to 4620 m.a.s.l. at the Ras Dashen Mountain. As a consequence the country is endowed with diversified agro-ecologies, soil types and biodiversity.

The country is divided into two major physiographic regions, the highlands and the lowlands (Table1). This physiographic separation is based on the traditional altitudinal classification of the country ([20]). The lowlands which constitute more than 60% of the land mass are found in areas <1500 m.a.s.l. on the other hand the highlands constitute 35-40% of the land and inhabited with 85% percent of the human population and 70% of the livestock are found in areas lying above 1500 m.a.s.l. Zone Altitude(m) Mean Rainfall (mm) Temperature (oC)Bereha (dry-hot) <500 <300 >22 Kolla (dry- warm) 500-1500 300-900 18-20 Erteb Kola (sub-moist warm) 500-1,500 900-1,000 18-24 Weinadega (sub-moist cool) 1,500-2300 900-1,000 18-20 Erteb Weinadega (moist- cool) 1,500-2,300 >1,000 18-20 Dega 2,300-3,200 900-1,000 14-18 Wurch(cold) 3200-3700 >1,000 10-14 Kur (very cold or alpine) >3,700 >1,000 <10

Table 1. Traditional Agroecological zones of Ethiopia ([12]) The lowlands are arid to semiarid, with annual air temperatures above 20°C. The plateaus have a temperate climate with annual average temperatures ranging between 10°C and 20°C. Rainfall increases from 200 mm y-1 in the east to over 2000 mm y-1 in the southwest . Rainfall in the northern Ethiopian highlands in general is concentrated into a fairly short season which experiences short and intensive storms. In the southern and eastern highlands there is a pronounced bimodal rainfall distribution, with the first and generally smaller rainfall (belg) peaking in April and the second is the main rainy season that lasts from June to September. The dry season extends from October to February, being longer and drier in the north. Rainfall variability is generally greatest in the lower rainfall areas of the north and the north - east highlands. According to [16] and [17], the geology of Ethiopia can be grouped into the pre - Cambrian basement complex of various grades with unaltered sedimentary rocks and igneous intrusion; the Mesozoic mantle sediments, deposited during a transgression in the upper Jurassic; and the cover deposits. Another important event is the Trap Series molten lava outpour at the beginning of the Mesozoic era. The highlands are made up of folded and fractured crystalline rocks covered by sedimentary limestone and sandstone, and by thick layers of volcanic lava .

Agriculture is the mainstay of the Ethiopian economy, which accounts for 50% of the gross domestic product, 90% of export revenue, and 85% of employment. The agricultural sector is, however, highly underdeveloped and remains almost entirely dependent on rainfall. Practically all cropping is rainfed and confined to the highlands, where there is also a

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concentration of around two- thirds livestock herd of the total 78 million population - the largest in Africa. According to [4], the crops grown in the country are cereals (70%), pulses (10%), and perennials (20%). The specific crops include: tef (Eragrostis tef), maize , wheat, barley and , sorghum as well as coffee and enset (Enset ventricosum). The wide ranges of topographic and climatic factors, parent material and land use have resulted in extreme variability of soils in Ethiopia (Table 2). In different part of the country, different soil forming factors have taken place. Assessments of the nutrient status of Ethiopian soils indicate ranges of 0.9 -2.9 g nitrogen (N) and 0.4 -1.10 g phosphorus (P) per kg of soils ([7]).

Soil type Area (km2) Percent Acrisol 55,726.5 5.0 Cambisol 124,038 11.1 Chernozems 814 0.07 Rendzinas 16,348 1.5 Gleysols 5,273.5 0.47 Phaeozems 32,551 2.9 Lithosol (Leptosols) 163,185 14.7 Fluvisols 88,261.5 7.9 Luvisols 64,063.5 5.8 Nitosols 150,089.5 13.5 Histosols 4,719.5 0.42 Arenosols 9,024 0.81 Regosols 133,596 12.0 Solonetz 495 0.04 Andosols 13,556 1.2 Vertisols 116,785 10.5 Xarosols 53,171 4.8 Yermosols 34,95 3.1 Solonchaks 47,217.5 4.2

Table 2. Distribution of soil types in Ethiopia

Ethiopia is endowed with vast water resources with 12 major rivers and 22 natural lakes

([24]). Professional estimates indicate that the country has an annual surface runoff of about 110 billion cubic meters from 12 major drainage basins ([26]), only 4% of which is used ([5]). Groundwater resources, the true potential of the country are not clearly known. However, it is widely reported that Ethiopia possesses a groundwater resource potential of approximately of 2.6 billion cubic meters (m3) ([18]).

According to [1], of the country's estimated 112 million ha of land mass, about 66%, about 22% is under cultivation for production of annual and perennial crops. About 96% of the current cultivated areas are occupied by small holder subsistence farmers, while commercial farms cultivate the remaining ([3]). [26] reported that the total irrigable area from the 12 major basins of ca. 3 million ha.[18] estimated the potential irrigable land of ca. 3.7 to 4 million ha. The figure is still subject to change as more reliable data are being acquired through accomplishment of all river basins master plan studies and with the growing technology for water transfer exploitation. Nevertheless. the irrigated areas generate only 3 % of the total field crop production.

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Despite the country's huge water resources potential, there is high temporal and spatial variability: most of the rivers in Ethiopia are seasonal and about 70% of the runoff potential takes place during the months of June, July and August ([27]). There is uneven spatial distribution of river basins that between 80-90% of Ethiopia's water resources is found in four river basins, namely the Blue Nile, Tekeze, Baro - Akobo, and Gibe – Omo ([18]).

Land degradation by erosion is clearly evident throughout 7000 years of history in the world and it is the major cause of poverty in rural areas of developing countries.

Studies of the effect of erosion on early civilization have shown that one of the major causes of the downfall of many flourishing empires was soil degradation. [2] described soil degradation as one of the major causes of the downfall of the ancient Axumite Kingdom. [10] also described soil erosion as one of the elements in the decline of civilizations of Lalibela in the 14th century and Gondar in the 17th century.

Much of the land degradation is found in the highlands above 1500m (45% of the total country's total area) ([4]). These highlands, which are characterized by favorable environmental conditions, have been settled and cultivated for millennia ([13]). The Ethiopian highlands constitute one of the most degraded lands in Africa, if not in the world ([6]). These highlands are an ancient and conspicuously uplifted part of the earth's surface, which by virtue of their location have constantly been assailed by normal erosive forces ([4]). Morever, the highlands have long history of tectonic instability which has split the highland into two parts. [4] identified six categories of soil degradation in the Ethiopian highlands: water erosion, wind erosion, salinization /alkalization, and chemical, physical and biological degradations.

The degradation of resources is caused by heavy pressure from human and livestock population, coupled with many other physical, socioeconomic and political factors

The most pressing forms of resource degradation are the destruction of the natural vegetation and soil erosion by water. Deforestation has been occurring in Ethiopia for millennia and has accelerated during the last century ([15]). Rapid population growth, extensive forest clearing for cultivation, overgrazing, movement of political centers, and exploitation of forests for fuel wood and construction materials without replanting reduced Ethiopia's forest area to 16% in the 1950's and to 3.1 % by 1982 ([25]).

The water erosion includes sheet and rill erosion, gully erosion, tunneling and land slides. Sheet and rill erosion is the most important erosion form in all zones and altitudinal belts of the Ethiopian highlands ([20]). According to the 'Global Assessment of Soil Degradation' map ([23]), more than 50% of the northern Ethiopan highlands suffer from extreme loss of top soil due to sheet and rill erosion. On this map, gulling and mass movements are indicated as another major problem.

Biological degradation induced by man, such as removal of field crop residues and dung, overgrazing and deforestation, is widespread and severe in the highlands. However, the major force driving land degradation in Ethiopia is nutrient depletion of agricultural soils arising from complete removal of crop residues from crop fields, crop production with low levels of nutrient inputs and lack of adequate soil conservation practices. However, this argument seems to contradict with the findings of [4]. Although, [7] identified erosion as particular concern in the Ethiopian context as the major cause of land degradation which declines food crop production, [20] attribute land degradation to several interacting bio-physical social and political attributes that demand concerted interventions not only maintaining soil fertilitybut also farm management practices that take sustainable land management into concideration.

The physical degradation of soil throughout the highlands is commonly associated with the biological degradation and water erosion. It could arise from excessive tillage,

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particularly for tef and livestock trampling between grazing grounds and watering locations ([4]).

Serious chemical degradation is rarely found in actively eroding soils but more common in Nitosols at elevations over 2000 m a.s.l. (southwestern parts of the country). Excessive removal of plant nutrients can result from continuous annual crops of cereals, but is not significant in the highlands i.e. partly allows replacement by the arrival of nutrients in the groundwater moving down the landscape. The argument is that had the replenishing not been there, the Ethiopian highlands could have been more in a severe condition than it is now, after so many centuries of food production.

Soil at a given site can be formed by three processes: the deposition of sediment by runoff erosion, the natural weathering of rock beneath the soil and the formation of soil at the surface by decaying organic and inorganic minerals caused by both natural processes and by cropping. The deposition of sediment involves substantially larger quantities than the formation of soil at in situ. It is estimated that 90% of the total erosion is deposited annually in the lower lying areas of the Ethiopian highlands ([4]).

Internationally, the issue of in situ soil formation rate is controversial among scientists. However, the common estimates lie between 0.8 and 3 t ha-1 y-1. It is, however, agreed that soil formation rate under farming is faster, and that tillage operations probably increase the rate of top soil renewal to around 11 t ha -1 y-1 ([4]).

All these rates are considerably lower than the soil formation rates tentatively calculated for the Ethiopian highlands (from 2 to 22 t ha -1 y-1 ) from the data on temperature, rainfall, length of growing period, soil units, soil depth, slope gradient and land cover (FAO) working paper 2 (WP2) ([4]). These indicative soil formation rates increase from low levels in the north to high levels in the west and southwest and thereafter fall towards the boarder to Kenya. The patterns reflect rainfall and temperature. In other reports, a soil formation rate of about 10 t ha-1 y-1 is estimated for the Ethiopian highlands, depending on slope gradient and land use type ([21, 8]).

[9] extrapolated soil formation rates for the different agro-climatological zones of Ethiopia (Table 3). These soil formation rates are mean rates, taking into account rain and temperature conditions, however, it did not consider lithology. Over all, the data on soil formation rates in Ethiopia are inconsistent; on the other hand, those data are used for comparison with the soil loss rates. It is, however, suggested that those data should not be applied to the vast areas where the soil mantle results from sediment deposition rather than from pedogenesis ([8]).

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Agro-Climatogical zone Altitudinal limits (m a.s.l.) Soil formation rate (t ha-1 y-1)

High Wurch(Kur) >3700 2 Wet Wurch 3200 -3700 4

Moist Wurch 3200 -3700 3 Wet Dega 2300-3200 10

Moist Dega 2300 -3200 8 Wet Woina Dega 1500 – 2300 16

Moist Woina Dega 1500-2300 12 Dry Woina Dega 1500 -2300 6

Moist Kolla 500-1500 6 Dry Kolla 500 -1500 3

Berha, Desert <500 1

Table 3. Estimated soil formation rates Source: [9] and [20]

Soil erosion by water is by far the biggest land degradation problem in Ethiopia ([4] and [11]). However, the studies made to establish the sediment budget i.e. the detailed account of the sources and deposition of sediments as it travels from its point of origin to its eventual exit of a drainage basin are still tentative. [4] indicated the sediment budget for Ethiopia highlands. Gross erosion is estimated at 1.9 billon tons of which 80% comes from cropland, and 20% from grasslands and other land uses. Of what has been eroded, 90% will be re-deposited, while 10% is delivered to the rivers which is equivalent to 190 million tons from all the land uses (ca. 536000 km2).

This is equal to ca. 354 t km-2 y-1, including the Eritrean highlands, which was part of Ethiopia by that time. [4] compiled erosion data for low potential crop (LPC), high potential crop (HPC) and high potential perennial (HPP) agro - ecological zones of the Ethiopian highlands and found annual soil loss (t ha -1 y-1) ranges of 75-140, 65-170, 50-135, respectively. While the current rates of soil loss are generalized, however, they hide significant variations within each zone, especially for LPC.

[9] estimated mean soil loss rates for different types of land use (Table 4). The highest loss is from the crop land (42t ha-1y-1), which is estimated at 1.5 billion t y-1 for the whole country. This figure has been criticized by [22] arguing that the soil loss rates have been projected from runoff plot studies. They do not account sediment that inflow into it and also sediment deposition has been neglected in this study. It was argued that the figure has become an eyecatcher and is being used in reports and in scientific reports.This needs major revision to rectify the diverse discussion on the established rates ([20]).

On the other hand, it seems puzzling that the nation wide total annual soil loss estimate by [9] (i.e. 1.5. billion t) is less than the total annual soil loss given for the Ethiopian highlands by FAO factors: (1) low erosion rates in the lowlands and (2), conversely, the flat topography allows deposition of eroded and transported soil from the highlands and hence resulted in low total annual soil loss at country level. However, the second argument may seem contradicting with critics made by [22] who presented a tentative sediment budget for average catchements of different size in Ethiopia highlands. They took into account the different components contributing to sediment mobilization and deposition, employing a mass balance equation and estimated the net sediment yield for an average catchment of 10000 km2 at 1.83 106 t y-1 i.e. 183 t km-2 y-1, which is the same order of magnitude with the estimate by [9].

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The value reported by [22] is lower by a half than the estimate made for the Ethiopian highlands by [4]. The two studies are not only differing in the magnitude of the SSY but also in their approach and assumptions. The [4] approach was based on agro-ecologies and the contribution of gully erosion and other forms of erosion were ignored. On the other hand, the [22] approach was catchment - based and seems to over emphasize the contribution of gully erosion, as it is in the same order of magnitude to that of rill erosion. Moreover, [22] predicted solid sediment loss that took into account the catchment area as the only explanatory variable for sediment yield prediction, with an r3 (coefficient of determination) of 0.59.

Overall, the information on sediment budget in the Ethiopia highlands is not only inconsistent but also inadequate to represent all the components of the mass balance equation. Therefore, further research is needed to understand the sediment budget taking into account representative river basins in the highlands of Ethiopia.

Land cover Area(%)

Soil loss (tha-1y-1)

Grazing 47 5 Uncultivable 19 5

Crop land 13 42 Wood land/ bush land 8 5

Swampy land 4 0 Former crop land 4 70

Forests 4 1 Perennial crops 2 8

Total for the whole of Ethiopia 100 8

Table 4. Soil loss rates in Ethiopia(after [9] and [20]) Erosion impacts can be either on-site or off-site or both. Correspondingly, the impacts can be conceived as positive or negative. [4] has documented that positive and negative impacts are merely relative terms that mainly depend on the region of interest. For instance the eroded soil from the Ethiopian highlands that leaves via the Blue Nile can bee seen as a negative effect for Ethiopia but, on the other hand , the deposited sediment in the Egypt's valley had increased the fertility status of the in-situ soil, which might adversely affect the Aswam dam. In this study, on-site impacts are related to productivity of farms caused by loss of top soil (loss of nutrients and organic matter), reduction of soil depth, soil crusting and sealing and dissection of fields. In less developed countries, on-farm economic impacts of erosion tend to exceed off-site impacts. This reflects the lower level of downstream infrastructure development, less concern about water quality and the heavy dependence of small farmers on natural levels of soil fertility. [14] also noted that in less developed areas the onset of significant erosion can lead to a pattern of rapid land degradation with declining yields and vegetative covers that lead to shortened fallow periods, overgrazing for further erosion and land degradation.

Soil fertility depletion is developing into a major constraint to agricultural production in Ethiopia. The Ethiopian Highlands Reclamation Study ([4]) reported that about half of the Ethiopian highlands (27 million ha) was significantly degraded in 1984, out of which 2 million hectares of agricultural land have degraded to the extent that they will not be able to sustain crop production in the future. However, little information exists on the relationship between erosion, erosion hazard, and its impact on crop productivity and associated costs. [19] reported that a reduction of barley yield by 25 kg ha-1 for 1 cm of soil loss was observed

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in a Humic Andisol in the Debre Birhan area of Northen Showa. The same study for the area indicated that with the soil loss rate of 66t ha-1y-1, the shallow soil with an average depth of 45 cm will be completely eroded in about sixty years time while crop production will decrease by 35% during the first twenty years. [11] predicted that most of the cultivated land in the Ethiopian highlands would be entirely stripped of the soil mantel within 150 years, assuming an average soil depth of 60cm. In economic terms, soil erosion, which is based on the data provided by [4], is estimated to have cost 619 million Ethiopian Birr (ETB) by the year 1990.

[4], however, acknowledged that (1) the cost estimate has uncertainties in that the relationship between soil loss and yield reduction was not documented and (2) there was difficulty inherent in projecting soil loss. An alternative erosion-caused soil fertility degradation costs analysis can be applied using a 'replacement cost' approach. The logic behind this approach is to calculate the loss of nutrients and put a value on it using the equivalent value cost of commercial fertilizer. Despite the lack of data on erosion related productivity loss, however, productivity loss rather than replacement cost is the most theoretically correct way to value resource depletion.

In other studies, the effect of land management and land use conversion was found to have a significant impact on the spatial variability of soil nutrients. An improvement in soil physical (soil structure, soil depth) and chemical characteristics e.g. N, P and organic matter (OM) was observed as one is going from cultivated lands to grazing lands and then to forest and exclosures. The improved soil characteristics are due to a decreased erosion process along the same direction. These studies, however, do not to indicate the nutrient status and the overall nutrient balance of the soils under the different land uses. Nowadays, there is increasing interest on assessment of nutrient balance at field and regional scale levels. [7] assessed nutrient balance for N, Pav, and K at regional scale and country level using two different soil loss estimates by USLE and LAPSUS (landscape process Model). The values (in kg ha-1y-1) reported were: 37.7 and 6.0 for N. 7.8 and 3.0 for Pav; and 28.3 and 4.0 for K, for USLE and LAPSUS soil loss estimates, respectively. In both cases, soil erosion is found to be the prime responsible factor for nutrient depletion i.e. accounts for loss of 70%, 80% and 63% for N, Pav and K, respectively. In their calculation, however, they assume a constant enrichment ratio (ER) of 1.5 for all nutrients.

[8] studied the N balance in Gobo Deguat (within this study region) at farmers' field using the Nutrient Monitoring Model (NUTMON), and estimated N loss by erosion at 12.6 kg ha-1y-1 and the N balance is negative. However, an organic input from purchased manure and feeds that takes the highest proportion (34.2 kg ha-1y-1 ) seems exaggerated. Moreover, the role of erosion in nutrient outflow is in the fourth place after harvested products (22.9) kg ha -1y-1), crop residue in manure (13.2 kg ha-1y-1), gaseous losses (4.9) kg ha-1y-1), which seems contradicting with the work by [7] at national and Regional States level.

Nitrogen and phosphorus balances analyzed under five different land uses in southern Ethiopia were either in equilibrium or positive in most of the farm components which may seem opposing to the findings by [8] and [7] who found strong negative balances of the respective nutrients.

The information on the nutrient balance shows that there are uncertainties in the nutrient balance calculation which could be associated to lack of measured input and output data and, therefore, merits further study. Erosion and sedimentation estimates were rough in all cases as both were only estimated but not measured at the site. Therefore, detailed investigation of the erosion and sedimentation component is required in all scale of nutrient balance studies in Ethiopia.

Off-site impacts include higher turbidity in rivers, lakes, reservoirs and sediment deposition in these same environments and flood plains. Also increased downstream runoff and flooding as a result of reduction of soil infiltration by the on-site impacts. Sediment

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delivery to river channels is probably one of the most problematic off-site consequences of soil erosion and it is a disturbing problem in countries of northern Africa . The inputs of the sediment by erosion process into rivers, reservoirs and ponds results in high sediment deposition rates and frequent dredging operations.

In Ethiopia, scientific documents on the off-site impacts are very rare. [26] found that the increased abnormal flooding in the downstream position of the Baro Akobo river basin is associated with human interference within the catchment, which is due to absence of proper land use planning. The increased human activity is due to the increased population after the 1984 resettlement program. These days, the abnormal flooding has become frequent also in places of lower Awash and in Wabishebele River Valleys which has been displacing many inhabitants and damaged the surrounding land.

Efforts to rehabilitate the degraded highlands through soil and water conservation were going on in and promising results are being documented. Several hectares of farm lands are conserved and millions of tree seedlings have been planted. However a national scheme is not designed to measure in either biophysical and economic terms, the impact of such an effort. Fragmented and uncoordinated studies are undertaken with no standardized methods and with no possibilities to formulate a national or regional database. Policy and operational guidelines are required to document the scattered studies within a framework of integrating sustainable land management into the farm management practices by farmers.

REFERENCES [1] G. Bikora. "Food security challenges in Ethiopia. Unit Nations", African Institute for Economic Development and Planning, Dakar, Senegal, (2001). [2] K.W. Butzer. "Rise and Fall of Axum, Ethiopia: a geological interpretation", American antiquity, 46 (3), 471-495, (1981). [3] EPA. "National Action Programme to Combat Desertification", Environmental Protection Authority, Addis Ababa, November 1998, p. 158, (1998). [4] FAO. "Ethiopian Highlands Reclamation study", vols. 1 and 2. Food and Agricultural Organization of the United Nations, Rome, Italy, (1986). [5] FAO. "Small scale irrigation consolidation project preparation report", Food and Agricultural Organizations of the United Nations, Rome, Italy, (1994). [6] E. Feoli, Vuerich, L., Zerihun, W. "Evaluation of environmental geomorphological, erosion and socio-economic factors", Agriculture, Ecosystems and environment , 91 (1-3), 313-325, (2002). [7] A. Haileselassie, Priess J., Veldkamp, E., Teketay, D., Lesschen, J.P. "Assessment of soil nutrient depletion and its spatial variability on stallholder’s mixed farming systems in Ethiopia using partial versus full nutrient balances", Agriculture, Ecosystem and Environment, 108, 1-16, (2005). [8] H. Hengsdijk, Meijerink, G.W., Mosugu, M.E. "Modeling the effect of three soil and water conservation practices in Tigray, Ethiopia", Agriculture, Ecosystems and Environment, 105, 29-40, (2005). [9] H. Hurni. "Soil formation rates in Ethiopia", Addis Ababa, FAO/Ministry of Agriculture. Joint Project EHRS, working paper No. 2, (1983). [10] H. Hurni. "Options for steep land conservation in subsistence agriculture". In: subsistence agricultural systems. Workshop on soil and water conservation on steep lands, San. Jau, Paurto Rico, Marsh 22-27, p. 14, (1987). [11] H. Hurni. "Land degradation, famine and land resource scenarios in Ethiopia". In:D. Pimentel (ed.), World soil erosion and conservation, pp. 27-62. Cambridge University Press, Cambridge, UK, (1993). [12] IFPRI/CSA. "Atlas of the Ethiopian Rural Economy", International Food Policy Research Institute and Central Statistics Agency. Addis Ababa (2006). [13] J. McCann. "People of the plow: an agricultural history of Ethiopia, 1800-1900", University of Wisconsin Press, Madison, USA, (1995). [14] S. McIntyre. "Reservoir sedimentation rates linked to long term changes in agricultural land use", Water Resources Bulletin, 29 (3), 487-495, (1993). [15] J. Moeyersons, Nyssen, J., Poesen, J., Deckers, J., Haile, M. "Age and backfill/overfill stratigraphy of two tufa dams, Tigray Highlands, Ethiopia: Evidence for Late Pleistocene and Holocene wet conditions", Palaeography, Palaeoclimatology, Palaecology 230, 165-181, (2006). [16] P.A. Mohr. "The geology of Ethiopia", Univ. College Addis Ababa Press, (1962).

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[17] P.A. Mohr. "The geology of Ethiopia", Addis Ababa: Haileselassie-I University Press, (1971). [18] MoWR. "Abay River Basin Integrated Development Master Plan Project Phase II". Data collection site investigation survey and analysis. Section II. Sectorial studies Vol. V Water Resources Development. Part I irrigation and Drainage. Ministry of Water Resources, Addis Ababa, Ethiopia (1998). [19] T. Mulugeta. "Soil conservation experiments on cultivated land in Maybar area, Wollo region, Ethiopia". SCRP, Research Report 16, (1988). [20] H. Mitiku, Herweg K., Stillhardt, B. "Sustainable Land Management:New Approaches to Soil and Water Conservation In Ethiopia", Berhanena Selam Printing Enterprise. Addis Ababa, p. 304, (2006). [21] E.J. Mwendera, Saleem Mohammed, M.A. "Hydrologic response to cattle grazing in the Ethiopian Highlands", Agriculture, Ecosystem, Environment 64, 33-41, (1997). [22] J. Nyssen, Poesen, J., Moeyersons, J., Deckers, J., Mitiku Haile, Land, A. "Human impact on the environment in the Ethiopian and Eritrean highlands-a state of the art", Earth Science Reviews 64 (3-4), 273-320, (2004a). [23] L.R. Oldeman, Hakkeling, R.T.A., Sombroek, W.G. "World map of the status of human induced soil degradation": An explanatory note, 2nd ed., p 27. Wageningen and Nairobi: ISRIC and UNEP, (1991). [24] T. Tarekegn. "The role of water harvesting, small, medium and large scale irrigation in the overall agricultural production system and rural development", A paper presented on the first National Water Forum in Ethiopia October 23-24, Addis Ababa Ethiopia, (2004). [25] UNEP (United Nations environment Programme). "Ecology and Environment:What Do We Know About Desertification", Desertification Control, 3, 2-9, (1983). [26] M. Woube. "Flooding and sustainable land-water management in the lower Baro-Akobo river basin, Ethiopia", Applied geography, 19, 235-511, (1999). [27] E. Yazew. "Development and management of irrigated lands in Tigray". PhD Dissertation, UNESCO-IHE Institute for Water Education, Ethiopia, p. 284, (2005).

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NEW CHALLENGES OF SOIL SCIENCE TO FOOD SECURITY

WITH SPECIAL REFERENCE TO CHINA

Tang Huajun & Zhou Wei

Institute of Agricultural Resource and Regional Planning, Chinese Academy of Agricultural Sciences, Beijing-100081, China

Abstract As the main productive resource for agriculture, soil is one of the most basal factors consisting of comprehensive ability for food production, and the base and assurance for food security in China. In the situation that arable land is decreasing drastically, the protection of soil resource has become a major factor affecting sustainable development of the country. Preliminary investigations mainly focused on relationship between amount of arable land and food demand in China, but lack of systematic analysis on soil resource security associated with food demand and agricultural product quality. In this paper, based on investigation of the changes in quantity and quality of soil resource in China, the relationships between soil resource and food quantity security and quality safety were discussed, and policy options for keystone basic research tasks and engineering counter-measures were also proposed.

INTRODUCTION China has very abundant soil resource with many kinds of soil types. The total land area is 9.6 million km2. Climate types ranges from tropical zone to cold-temperate zone and from humid region to arid region. There are 14 soil orders, 39 suborders, 138 soil types and 588 subtypes in the whole country (Gong et al., 2005). The area of Cambosols and Aridosols occupies more than 20% of total soil area, that of Histosols, Ferralosols, Vertosols, Andepts and Spodosols accounts for 1%, the other includes Anthrosols, Halosols, Gleyosols, Isohumosols, Ferrosols, Argosols and Primosols (Table 1). Moreover, the absolute amount of cultivated land, woodland and grassland ranks number 4, 8 and 3 in the world, respectively. The data are based on 1:12,000,000 soil map, soil classification is from Chinese Soil Taxonomy.

Soil orders Percent total soil area

(%) Soil orders Percent total soil area

(%) Histosols 0.22 Isohumosols 8.67

Anthrosols 4.84 Ferrosols 8.89 Ferralosols 0.44 Argosols 7.42 Vertosols 0.30 Cambosols 21.51 Aridosols 23.01 Primosols 9.76 Halosols 3.64 Others 0.04

Gleyosols 1.24 Table 1: Soil resources inventory of different soil orders in China

The amount of arable land per capita in China is very limited. The total arable land area is

about 1.26×108 hm2, with arable land area per capita of 0.1 hm2, less than 40% of the average in the world (Zhao et al., 2006). Figure 1 shows that the amount of arable land resource has decreased dramatically since 1996, and this tendency will be continued. The main factors resulting in such a decrease of cultivated land include industrial construction, calamity damage, ecological returning and planting structure readjustment (Table 2), accounting for

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15.68%, 5.73%, 61.43% and 17.16% of the total loss of arable land, respectively. Thus, ecological returning among various factors dominates land loss. In addition, the uncultivated soil resource which can be available to agricultural production in China is about 0.133×108 hm2, less than 6% of the total arable land area, a serious shortage of farmland resource in China is coming (Smil, 1995; 1999).

11800

12000

12200

12400

12600

12800

13000

13200

1996 1997 1998 1999 2000 2001 2002 2003 2004 2005

Year

Are

a of

cul

tivat

ed la

nd (×

104 h

m2 )

3800

4000

4200

4400

4600

4800

5000

5200

Gra

in p

rodu

ctio

n ( 1

05 t)

Area of cultivated land

Grain production

Fig 1: Changes of the cultivated land and grain production from 1996 to 2005 in China

Year Construction Damage Returning Readjustment Sum ofdecrease 1997 1.930 0.470 1.630 0.590 4.620 1998 1.762 1.595 1.646 0.701 5.704 1999 2.053 1.347 3.946 1.071 8.417 2000 1.633 0.617 7.628 5.782 15.66 2001 1.637 0.306 5.907 1.083 8.933 2002 1.965 0.563 14.26 3.490 20.27 2003 2.610 0.500 22.37 3.310 29.79 2004 2.928 0.633 7.329 2.047 12.94 Sum 16.52 6.032 64.71 18.07 105.3 Average 2.065 0.754 8.089 2.259 13.17

Table 2: Structural analysis of changes in cultivated land in China from 1997 to 2004(×104 hm2)

The geographic distribution of soil resource, food production and population is uneven in

China (Gong et al., 2005). The southeast region with humid climate and 41.6% of the total land area, contains 81% of the population in China, 72.2% of the arable land, 81.5% of the total grain production of China, but with increasingly eminent problems such as people-land confliction and environment deterioration; Northwest region with arid climate and 35.7% of the total land area, contains 4%, 8.2% and 4.2%, respectively. Due to restriction of aridity and cold climate to agricultural production and life of human being, there is a sharp confliction in water and soil, a fragile environment, an undeveloped economy, and a less population and cultivated land in this region; Central region with semi-humid climate and 22.7% of the total land area, accounts for 15% of the population in China, 19.6% of the cultivated land, 14.8% of the total grain production in China (Table 3).

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Zones Percent total

population (%)

Percent total soil area (%)

Percent total land area (%)

Percent total grain production (%)

Total 100 100 100 100 I Humid zones of southeast China

81.0 41.6 72.2 81.5

1 Cold-temperate zone 0.04 1.2 0.1 0.1 2 Mid-temperate zone 6.96 8.6 16.3 13.7 3 Warm -temperate zone 19.7 5.2 15.7 20.5 4 North subtropical zone 15.7 4.3 11.5 15.2 5 Central subtropical zone 28.7 17.0 22.4 26.1 6 South subtropical zone 8.4 4.3 4.9 4.9 7 Tropical zone 1.6 1.0 1.3 1 II Semi-humid zones of central China

15 22.7 19.6 14.8

1 Mid-temperate zone 2.0 6.0 4.2 2.5 2 Warm-temperate zone 9.0 6.2 10.8 7.9 3 Plateau temperate zone 4.0 10.5 4.6 3.9 III Semiarid and arid zones of northwest China

4.0 35.7 8.2 4.2

III 1 Mid-temperate zone 1.1 8.2 2.9 1.5 III 2 Warm-temperate zone 2.22 12.4 4.4 2.2 III 3 Plateau temperate zone 0.49 5.0 0.7 0.5 III 4 Plateau temperate zone 0.08 2.0 0.11 0.0008 III 5 Plateau sub- frigid zone 0.05 5.3 0.06 0.0005 III 6 Plateau frigid zone 0 3.0 0 0

Table 3: Soil regionalization of China

CHANGES IN QUALITY OF SOIL RESOURCE IN CHINA Deterioration of soil resource Soil erosion leads to deterioration of arable land quality, such as reduction in the thickness of soil layer, damage of soil structure and loss of soil nutrients. According to estimation, due to water loss and soil erosion, annual loss of soil substance, organic matter, N, P and K is about 5.0×109t, 2.7×107 t, 5.5×106 t, 6.0×103 t and 5.0×106 t, respectively (Pan，2005).

Soil desertification and sandification occurs seriously. According to Station of Desertification Communique of China in 2005, the total area suffered from desertification is 2.64×106 km2 until 2004, accounting for 27.46% of the total land area; That suffered from sandification is 1.74×106 km2, accounting for 18.12% of the total land area; The amount of cultivated land suffered from sandification is 4.63×104 km2, of which occupies 2.66% of total sandification land (Ministry of Forestry P.R.C, 2005). Wind erosion of surface soil with abundant nutrients results in decline of soil fertility, damage of soil physical structure, decay of production ability and degeneration of farmland quality.

Arable land productivity is being degenerated. Among the existing arable land, high-productive land accounts for 21.5%, intermediate-productive land 37.2%, and low-productive land 41.2% (Table 4). Soils with the organic matter content of 1% to 2% and lower than 1% accounts for 38.3% and 26.0%, respectively. The situation of soil nitrogen content is similar

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to that of organic matter, and soils with total nitrogen content of 0.1 % to 0.075 % and lower than 0.075% accounts for 21.3% and 33.6%, respectively. As a whole, the total N content is relatively low. Cultivated land with phosphorous, potassium, sulfur and micronutrients deficiency accounts for 59%, 30%, 30% and 50%, respectively (Table 5). The soil physical properties tend to be deteriorated, 40%, 35% and 25% of low-productivity paddy field is Gleyed soil, illuvial hardened soils and heavy hardened soil, respectively.

High productive land Interm productive land Low productive land

Standard (t/hm2)

Percent distribution

Standard (t/hm2)


Standard (t/hm2)


Rice >6 3~6 <3 Wheat >5 2.5~5 <2.5 Maize >5.2

21.5%

2.3~5.2

37.2%

<2.3

41.3%

Table 4: Classification and percent distribution of cultivated land in China

Items % total land area Items % total land

area Organic matter content <2% 64.3 Potassium deficiency 30 Nitrogen deficiency <0.1% 54.9 Sulfur deficiency 30 Phosphorus deficiency 59 Micronutrient deficiency 50

Table 5: Soil fertility status in Chinese cultivated land

Soil is serious contaminated（Zhao et al.，2002）. The farmland area contaminated by

industry waste is about 587×104 hm2, and that polluted by Cd, Hg and F is estimated as 1.33×104, 3.2×104, and 67×104 hm2, respectively. Land seriously polluted by pesticides exceeds 0.13×104 hm2, land occupied by industry waste is about 1.5×104 hm2 (Table 6). The farmland area suffered from acid rain is 267×104 hm2 (Table 6).

Pollutants Area Pollutants Area

Cd 1.33 Pesticide 0.13 Hg 3.2 Industry solid waste 1.5 F 67 Acid rain 267

Table 6 Some cultivated land area affected by different pollutants in China（×104 hm2）

Regional features of soil quality degradation Due to differences in climate environment, social and economic factors, and human activities, there are great differences in quality of soil resource among various regions in China.

In Northeast China, water and soil loss and decline of soil fertility are the main problems existed in black soils. The thickness of black soil layer in the middle part of Jilin province was about 30 cm in 1983, while was merely 25 cm in 2002, that is, 5cm of black soil layer disappeared in the past 20 years（Liu et al.，2004）. According to the first extensive soil survey in Heilongjiang province in 1958, the organic matter content in black soil was 40 to 60 g kg-1, however, according to the second extensive soil survey in 1990, that was 30 to 50 g kg-

1or even less than 20 g kg-1 in the regions subjected to serious water and soil loss (Lu et al., 2005).

Soil pollution in the farmland in developed coastal region of southeast China is increasingly serious. DTT, hexachlorcyclonhexane, homolog of 15 polychlorinated biphenyls (PCBs) can be detected in all soil samples from drainage area of Taihu Lake （Luo et al.

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2005. The three-year-result of monitoring on agricultural soil quality in Zhujiang delta regions showed that the soils are contaminated by heavy metals such as Hg, Cd and As, and petroleum. The contaminated area accounts for about 50% of total soil area in these regions, of which light contaminated area is 32%, middle contaminated area is 8%, and heavy contaminated area is 10% (Wan et al., 2005).

Central China has a large proportion of low-productivity farmland, in which soils are relatively infertile. In the past 20 years, soil organic matter, N, and P content tended to increase, but the proportion of various nutrients was imbalance, and soil available K was seriously depleted. The ratio of soil productivity to application rate of chemical fertilizer tends to decrease with development of intensive cropping.

Semiarid region in Northwest China is seriously subjected to soil erosion. The land area with soil erosion in Loess Plateau is 1.13×107 hm2, accounting for 24.85% of the total area with soil erosion in China. The land area with sandification in the northwesten arid region and Loess Plateau accounts for 21.06% and 10.70% of the total soil area with sandification in China, respectively (Li, 2002). In addition, soil nutrients are generally found to be deficient in these regions.

In Central China and Southwest China, acid rain is always one of important factors resulting in soil acidification and degradation of soil quality. Acid rain not only directly influence crop adaptability to low soil pH, but also accelerate leaching and loss of soil nutrients, such as Cu and Zn, which lead to greatly decline of soil productivity and fertilizer use efficiency (Zhao, et al., 2002; Galloway, 2001).

SOIL RESOURCE AND FOOD SECURITY IN CHINA The decrease of cultivated land area in China greatly affects food production. Total food production tended to decline from 1998 to 2003, and began to ascend since 2004 (Fig 1). In order to ensure the country's security of grain supply, it is essential to increase production per unit area. It is estimated that the food deficit in the coming years 2010, 2030 and 2050 would be expanded to 5,127×104 t, 7,359×104 t and 1,354×104 t (Zhao et al., 2002), respectively. Difference between the present cultivated land area and the minimum requirement in these 3 phases will be over 900×104 hm2, and the pressure index of cultivated land will be more than 1.0 (Table 7). Thus, China will have a big challenge in feeding its growing population with a declined cultivated land area. Soil resource and food safety Due to excessive and improper application of fertilizer and pesticide as well as wastewater irrigation, poisonous substances increasingly accumulated in both soils and crops, situation of food quality safety become more and more serious. It was reported that 10% of grain, 24% of farm animal products, and 48% of vegetables have quality safety problems in some heavy contaminated region (Dong & Zhang, 2003). It is worried about that the residual effects of some low-concentration poisonous substance may last for several decades or even several generations.

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Year 2010 2030 2050

Population (100 million) 13.76 15.53 15.89 Food demand (104 t ) 59177 69907 71338

The minimum requirement of cultivated land (104 hm2 )

13426.2 12518 11673

The present cultivated land area (104 t) 12518.14 11600.33 10749.82 Grain production (104 t) 53486 61348 69684

Food deficit (104 t) -5127 -7359 -1354 The pressure index of cultivated land * 1.073 1.079 1.086

*The pressure index of cultivated land = the minimum requirement of cultivated land / present cultivated land area

Table 7: Estimation of food security and cultivated land change in China Pesticide residue in food Pesticide residue mainly occurs in grains, vegetables and fruits. According to the inspection results of 23 cities in China in the third quarter of 2001 issued by Quality Technology Supervisory Bureau of China, the pesticide residue in 47.5% of vegetables exceeded the maximum permitted value (Dong & Zhang, 2003). Although organochlorine pesticide have been prohibited for nearly 20 years, it can be detected in various crops, which is still a threat to human health through food chain. Investigations also demonstrated that the benzahex and DDT in tea and fruit could be detected, but the residual level was under standard limit (Fang, 1998). However, it was also found that the level of organochlorine residue in 40% of the tea were over maximum limit value (Hao, 2001). Heavy metal residue in food Heavy metal residue in agricultural products occurs in wastewater irrigated soil in suburb of large and middle cities or mining area. Especially vegetables grown in suburb soils are easily subjected to heavy metal contamination. According to the investigation on crop quality in suburb of 10 province capital cities in 2000, heavy metal residue in 30% of samples in 7 cities exceeded the limit value. The investigation of food quality in 300, 000 hm2 in basic protected farmland in China showed that heavy metal residue in 10% of samples was found to be over the limit value (Dong & Zhang, 2003); Vegetables grown in suburb in big cities of China have been contaminated by heavy metals to some extent, especially Cd, Hg and Pb. The standard-exceeding rate of Pb in vegetables in suburb of Xi-an is 48.0%, while that of Cd in Nanning is 91%, where the highest level of heavy metals in vegetables was found to be 6.2 times more than the limit of sanitation standard(Zhang & Bai, 2001). Nitrate residue in food Nitrate residue in food mainly arises in intensive cultivation regions, especially, nitrate and nitrite residues in vegetables grown in greenhouse generally occur. The nitrate content in 7 kinds of leafy vegetables in Zhujing delta area are more than 1,200 mg/kg with 100% of samples beyond the standard limit, and the highest level of nitrate is 5.35 times more than the limit value (Xie, 2000). In Xi-an, the nitrate residue in 32.5% of vegetable samples is over standard limit, and the highest level is 3.69 times more than the limit value (Wang, 2000).

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STRATEGIES FOR SUSTAINABLE UTILIZATION OF SOIL RESOURCE IN CHINA

Keystone basic research tasks Keystone basic researches on soil degradation should be carried out with respect to soil obstacle factors and main problems in sustainable utilization of soil resource (Yu, 2001). The feature of acidity and acidification mechanism in the soil of south China Great attention should be paid to probe the feature of acidity and acidification mechanism in the soil of south China with respect to differences in soil condition and constitution of acid rain. The main research tasks include: (1) Fate of H+ entering into soil; (2) Changes of Al3+

forms and chemical equilibrium of solid-liquid interface; (3) Effect of specific absorption of sulfate on soil acidification; (4) Effects of soil acidification on release of poisonous elements and leaching loss of nutrient elements; (5) Predication of soil acidification (sensitivity of the main soils types to acid deposition and its buffer capacity to acidification); (6) Acidification features in weakly acid soil in transition zone. Mechanism of genesis of gleyed soil The gleying process occurs in three types of soils: a swamp soil waterlogged for a long term, a paddy soil irrigated during growth period and bottom-gley soil with a certain height of groundwater level. Their common feature is that all layer or one layer of soil is saturated with water, and then reduction occurs to produce poisonous substance. It accounts for 1/5 of the soils in the world and more in China. The main research tasks include: (1) The relationship between intensity factors and quantity factors under reducing condition; (2) Development of determination method for distinguishing organic reduced substance using chemical and electrochemical method; (3) Reaction mechanism of organic reductive substance with Fe and Mn and its dynamics ; (4) Changes of Fe and Mn forms and their effects on plant growth; (5) Physical and chemical equilibrium among H2S—S2—FeS and their toxicology to organisms. Movement characteristic of salts and alkalization mechanism in saline-alkali soil There is a large scale of saline soil and alkali soil in China. Current researches emphasized on salt geochemistry, however, little information is available on mechanisms of physical chemistry of salinization and alkalization. The main research tasks include: (1) the effect of absorption-desorption on the movement of Na, K, Ca and Mg ions in soils; (2) the effect of complexation reaction on mobility of salt ions; (3) Differential movement of chlorine, nitrate, bicarbonate, and sulfate anions caused by absorption—negative adsorption—desorption process; (4) The osmotic potential of soil solution and its relationship to equilibrium of physical chemistry of various ions between solid phase and liquid phases; (5) Physical chemistry factors controlling pH of alkali soil. Transformation of poisonous elements in soil and their toxicology to organisms In the recent year, there have been growing concerns in China about inorganic contaminants in soils, such as Hg, Cd, Cr, Pb, Cu, As, F etc. The main research tasks include: (1) Relative importance of specific absorption and electrochemcial absorption of heavy metal ions in various types of soil; (2) Effect of precipitation, absorption and complexation reaction on

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distribution of heavy metal ions between solid phases and liquid phases; (3) Effect of heavy metal ions on characteristics of soil surface chemistry；(4) Effect of concomitant cations and anions on distribution of As and F between solid phase and liquid phase; (5) Forms and activities of variable valence elements (Cr and As) under different redox conditions. Migration of poisonous elements and nutrient elements and their effects on groundwater quality Nutrient element or poisonous element can affect plant growth through its movement to root surface. These elements can also influence the quality of groundwater through a series of reactions during their permeation in the soil. The main research tasks include: (1) Effect of absorption-desorption on migration of ions in soils and its mechanism; (2) Relationship between specific absorption and movement speed of heavy metal ions; (3) Effect of co-existing ions with different charge on the migration of ions; (4) Reaction dynamics of ions in the interfaces among soil colloid, soil solution and root or microorganism; (5) Relationship between the absorption of nitrate in variable-charge soils and nitrate contamination in groundwater. The renewal mechanism of soil organic matter Renewal mechanism of soil organic matter has received great concern due to rapid decline of organic matter in black soil. The main research tasks include: (1) Changes of components and characteristics of soil organic matter under different moisture and temperature conditions; (2) Factors affecting components, mineralization rate and humification coefficient of soil organic matter and their mechanisms; (3) Equilibrium models for describing dynamics of soil organic matter and their equilibrium points in soils with different fertility; (4) Effect of organic materials application (straw, green manure and animal manure) on the formation and characteristics of soil organic matter. Engineering counter-measures Balance fertilization and organic fertilizer application For a long time, intensive utilization of farmland and imbalance recovery of nutrients has resulted in great decline of soil fertility and fertilizer use efficiency. Fertilization and nutrient management need to be improved. Plentiful organic fertilizer resources in China have not been fully used yet. It is estimated that 4 billion tons of organic substances was produced in agricultural system every year, such as livestock manures, green manures, straws, etc., which can provide about 53.16 million tons of nutrients, including 21.76 million tons of N, 8.7 millions tons of P2O5 and 22.7 million tons of K2O. However, only 19.28 million tons of organic substances, or 36% of the total resources, are effectively used. The remainder enters into environment, and has a risk of contamination to ecological system. Therefore, it is very important to improve fertilizer application techniques such as balance fertilization with rational nutrients ratio, combined application of organic and inorganic fertilizers, to enhance soil fertility and ensure food security and food safety in China. Amelioration of soil and remediation of contaminated soil Since various adverse factors such as drought, sandification, salinization and acidification exist in cultivated lands of China, it was suggested to develop soil amelioration techniques,

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including increasing organic matter content of black soil, comprehensively ameliorating salt-alkali soil, improving soil structure, neutralizing acidic soil, and optimizing management of fertilizer and water.

With respect to contamination of pesticide, heavy metals and nitrate, both pollutant source and pollutant discharge should be controlled simultaneously. Great attention should be paid to both urban and rural environment protection, especially agricultural non-point source pollution. Studies on remediation of contaminated soils, regionally comprehensive ameliorating techniques, and developing patterns for sustainable utilization of cultivated land should be strengthened. Improvement of ecological environment High quality of farmland depends on improvement of ecological environment in China (Tang, 2000). Although a big net of protection forest of farmland had been established in China, it is not enough to protect all of cultivated land countrywide. The current pivotal works should be emphasized on remediation of soil sandification in semiarid and semi-humid regions, amelioration of soil secondary salinization and alkalization, and prevention of soil erosion. In addition, ecological returning of cultivated land to grassland or forestland is an absolutely necessary measure in interleaving zone in semiarid regions and in mountainous region of south China. Exploitation of uncultivated resource It is an important approach to exploit uncultivated resources for compensating deficit of farmland resource and ensuring food security. These approaches include improve of grassland to feed animal to increase meat, egg and milk products, utilization of some crops straw to feed household animals, utilization of water resource to develop aquaculture, and development of forest and fruit production (Gong et al., 2005).

REFERENCES

[1] Y.H. Dong, T.L. Zhang. "Sustainable management of soil resources for food safety" (In Chinese). Soils, 35 (3): 182-186, (2003). [2] L. Fang. "Assessment on the status of organochlorine pesticide residues in tea and surrounding environment" (In Chinese). Journal of Fujian Agriculture and Forestry University, 27(2): 211-215, (1998). [3] J.N. Galloway. "Acidification of the world: Nature and anthropogenic" (In Chinese). Water, Air, and Soil Pollution, 130: 17-24, (2001). [4] C. George, S. Lin, P. Samuel. "China’s land resources and land use change: Insights from the 1996 land survey". Land Use Policy, (20):87-107, (2003). [5] Z.T. Gong, H.Z. Chen, G.L. Zhang, Y.G. Zhao. "Characteristics of soil resources and problems of food security in China" (In Chinese). Ecology and Environment. 14(5): 783-788, (2005). [6] G.M. Hao, H.X. Li, C.J. Zhao. "Determination of organochlorine pesticide residues in tea" (In Chinese). Food Science, 22(11):73-75, (2001). [7] F.X. Li. "Degenerative reality and controlling countermeasure of cultivated land in west region of China" (In Chinese). Journal of Soil and Water Conservation, 16(1):1-10, (2002). [8] D.G. Liu, X.C. Zhang, Y. Cui. "Investigation report on the issue of black soil protection" (In Chinese). Journal of China Agricultural Resources and Regional Planning, 25(15):16-18, (2004). [9] C.Y. Lu, X. Chen, Y. Shi, J. Zheng, Q.L. Zhou. "Study on the change characters of black soil quality in Northeast China" (In Chinese). System Sciences and Comprehensive Studies in Agriculture. 21(3):182-184, (2005). [10] Y.M. Luo, Y. Teng, Q.B. Li, L.H. Wu, Z.G. Li, Q.H. Zhang. "Soil environmental quality and remediation in yangtze river delta region I. Composition and pollution of polychlorinated dibenzo-p-dioxins and dibenzofurans (pcdd/fs) in a typical farmland" (In Chinese). Acta Pedologica Sinica, 42(4):570-576, (2005). [11] Ministry of Forestry P.R.C. "Station of Desertification Communique" (In Chinese).

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[12] F. Pan. 2005. Science Times (In Chinese), (2005). [13] V. Smil. "Who will feed China ?" The China Quarterly, 143:801-813, (1995). [14] V. Smil. "China’s agricultural land". The China Quarterly, 158:414-429, (1999). [15] H.J. Tang. "Theory and Practice of Sustainable Land Use in China" (In Chinese). Beijing: China Agricultural Science and Technology Press, (2000). [16] H.Y. Wan, S.L.Zhou, Q.G. Zhao. "Spatial variation of content of soil heavy metals in metals in region with high economy development of South Jiangsu Province" (In Chinese). Scientia Geographica Sinica, 25(3):329-334, (2005). [17] L.P. Wang, C.P. Xiang, Y.H. Wang. "Nitrate content and its regulation in summer vegetables grown in Wuhan region" (In Chinese). Journal of Huazhong Agricultural University, 19 (5): 497-499, (2000). [18] H.S. Xie, Y.L. Wang, P. Cheng, B. Rong, Y.Y. Chen, S.M. Ren. "Nitrate pollution in leafy vegetables grown on Pearl River Delta: Problem and countermeasures" (In Chinese). Guongdong Agricultural Sciences, (5): 26-28, (2000). [19] T.R. Yu. "Chemical mechanisms for the occurrence of some major problems in sustainable agricultural development and ecological environment of China" (In Chinese). Soils, 33(3): 119 –121, (2001). [20] Z.G. Yu, X.P. Hu. "Research on the relation of food security and cultivated land’s quantity and quality in China" (In Chinese). Geography and Geo-information Science, 19(3): 45-49, (2003). [21] C.L. Zhang, H.Y. Bai. "Evaluating heavy metal contamination of soils and vegetables in suburb of Nanning" (In Chinese). Journal of Guangxi Agricultural and Biological Science, 20 (3): 186-205, (2001). [22] S.G. Zhang, J.J. Qiu, H.J. Tang. "Studies on recessive loss of amount of cultivated land in China" (In Chinese). Science & Technology Review, 24 (2 ):73-74, (2006). [23] Q.G. Zhao, B.Z. Zhou, H. Yang, S.L. Liu. "Some considerations on safety of arable land resources in China: problems and counter-measures" (In Chinese). Soils, 34(6): 293-302, (2002). [24] Q.G. Zhao, S.L. Zhou, S.H. Wu, K. Ren. "Cultivated land resources and strategies for its sustainable utilization and protection in China" (In Chinese). Acta Pedologica Sinica, 43(4):662-672, (2006).

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WORKS ON EROSION PROCESSES UNDER WIND-DRIVEN RAIN CONDITIONS IN I.C.E

Gunay Erpul1 & Donald Gabriels2

1 Faculty of Agriculture, Department of Soil Science, University of Ankara, 06110 Diskapi – Ankara, Turkey

2 Department of Soil Management and Soil Care, Ghent University, Coupure Links 653, B 9000 Ghent, Belgium. Abstract Soil erosion processes under wind-driven rains are important field of study for understanding the mechanism and developing prediction models. Clearly, the processes under conditions in which wind and rain act together differ significantly and conceptually from those under windless and rainless conditions. In this paper, wind-driven rain erosion research performed in I.C.E wind tunnel rainfall simulation facility was discussed and reviewed by analyzing the processes in place and methods to measure model parameters as influenced by horizontal wind currents. Additionally, concept and mechanism for rainsplash detachment and transport and sediment transport by raindrop-impacted shallow overland flow were given thoroughly.

INTRODUCTION The installation of a rainfall simulator inside the wind tunnel of I.C.E. (International Center for Eremology, Ghent, Belgium) enabled to study the combined effect of wind and rain on the erosion processes [11]. The simulated characteristics of wind-driven rains were assessed in the tunnel [1,3,4]. Kinetic energy of the simulated rainfalls of I.C.E. was determined by the splash cup technique [2,4]. Also, a two-dimensional numerical model and a kinetic energy sensor were used to estimate wind-driven raindrop trajectories [10,23].

After the mass and energy states of the simulated rainfalls of I.C.E. were described under windless and wind-driven conditions, rainsplash detachment studies were commenced [10]. On the other hand, a series of tests conducted to assess the effect of wind velocities on sand detachment from splash cups [6].

Along with on the rainsplash detachment process, the combined effect of rain and wind on the rainsplash transport process was examined in depth [7] Another paper presented experimental data on the effects of slope aspect, slope gradient, and horizontal wind velocity on the splash-saltation trajectories of soil particles under wind-driven rain [9].

Total interrill erosion under wind-driven rain was defined as a sum of wind-driven rainsplash and sediment transport by rain-impacted thin flow transport, which accounted for the transport processes occurred before and after runoff onset, respectively [8]. A quantification of wind and rain interactions and the effects of wind on both transport processes aimed to provide an opportunity for an erosion prediction technology to improve the estimation in situations where wind and rain occurred at the same time. Additionally, an I. C. E tunnel study under wind-driven rains was conducted to determine the effects of horizontal wind velocity and direction on sediment transport by the raindrop-impacted shallow flow [5]. Wind velocity and direction affected not only energy input of rains but also shallow flow hydraulics by changing roughness induced by raindrop impacts with an angle on flow and the unidirectional splashes in the wind direction. To particularly examine the roughness effect of impacting raindrops with an angle on sediment transport capacity of thin flow, KE was divided into its components and the partitioning of the KE into two components provided a better insight into the processes for which they independently played a role [20].

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This paper targets to give a review of wind-driven rain erosion research performed in I.C.E wind tunnel rainfall simulation facility. The review contains analyses of the processes in place and methods to measure wind and rain parameters in action. As well, concept and mechanism for rainsplash detachment and transport and sediment transport by raindrop-impacted shallow overland flow are reviewed by giving research results.

MATERIALS AND METHODS A description of the wind-tunnel research facility of International Center for Eremology (I.C.E.), Ghent University for wind, rain, and jointly wind and rain studies is given by Gabriels et al. (1997) [11] and Cornelis et al. (2004) [1]. Horizontal wind speeds were measured with a vane-type anemometer and associated recording equipment in the center of the wind tunnel. The reference wind velocities were determined up to 2 m and profiles for these velocities characterized by a logarithmic equation. In our studies, the boundary layer was mostly set at about 0.30 m, and subsequently, the reference wind shear velocities were derived from the logarithmic wind profiles by regression, assuming a fixed roughness height of 0.0001 for a bare and smoothed soil surface.

In studies, the central pipe line of rainulator on the ceiling of the I.C.E. wind tunnel along the working area was used, where downward oriented nozzles were installed at 2 m high and 1 m intervals. The nozzle employed was an axial-flow, wide angle, full cone type. A pumping unit supplies water from a tank to the pipe and accordingly to the nozzles. The lower and upper limits of the operating pressures were 0.75 and 1.50 bar, respectively. The spatial distribution of the intensity was measured with rain gauges with 11 cm in diameter and 13.5 cm in depth. When studies were done on inclined surfaces with different aspects, rainfall intensity was directly determined with the same slope degree and aspect as the sloping experimental set-ups. The drop size distribution was determined by an absorbent paper dyed with 1 M CuSO4. Colored paper was exposed to simulated rainfall in the tunnel after paper calibration was performed with drops of known size with known velocities.

The energy of the simulated rains was determined by the splash cup technique [2] and the kinetic energy sensor [23]. Also, an analytical calculation was made to approximate the kinetic energy of wind-driven rains taking forces that act on a raindrop falling through a wind profile into account. The splash cup technique involved exposure of a cup, 8-cm in diameter and 4-cm in depth, packed with standard sand of 200 - 300 µm particle size range, to the simulated rainfall. The amount of sand, which splashed out of the cup, was a measure of rainfall energy. A calibration study with vertically falling raindrops was previously performed to establish a linear relationship between the amount of the standard sand splash and the rain energy. Together with splash cups, the readings of the sensit kinetic energy sensor were taken during runs. Similar course of actions followed in the splash cup technique was used to acquire different energy levels. In addition, the two-dimensional analytical model was used to estimate the KE considering forces that act on a raindrop falling through a wind profile. In the analytical approach assumed was that the reference wind velocity was the x-component of the rain velocity vector at the nozzle height, and the z-component was the normal terminal velocity in still air.

Rainsplash detachment by windless and wind-driven rains were evaluated on the soil surfaces of three loess-derived agricultural soils packed into a 55-cm long and 20-cm wide pan placed at both windward and leeward slopes of 7%, 15%, and 20% (Figure 1). Soil detachment rates were determined by the amount of the splashed particles trapped at set distances on a 7-m uniform slope segment. For windless rain, splashboards were also

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26

positioned to collect side splash. Calculation of rainsplash detachment rate was based on the mathematical form of rainsplash erosion [19,21,25]:

∑=

=n

1iii xmq (1)

where, q (gm-1min-1) is the total rainsplash erosion, mi (g) is the mass of a particle, which is splashed over a distance xi (m) measured along the x-axis. Rainsplash detachment rate was estimated from the area under the curves of mass with distance by:

xxm

At1D

i

i

r

∂= ∫ (2)

where, D (gm-2min-1) is the rainsplash detachment rate, A is the surface area of soil pan ( )2m110.0m20.0m55.0 =× and tr (min) is the time during which rainsplash process occurred.

Additionally, a rainsplash detachment study was conducted with cohesionless sand surfaces. Windless rains and the rains driven by horizontal wind velocities of 6, 10, and 14 ms-1 were applied to the splash cups, 8 cm in diameter and 4 cm in depth, placed flat to the base of the tunnel (Figure 2a) [16]. The cups with a removable porous bottom to allow free drainage were filled at a full level with standard graded tertiary dune sand obtained as a sieve fraction of 100 – 200 µm (310 gram per cup). After manually compacted by tapping, the surface of the sand was smoothed exactly on a level with the rim of the cup. Each run was performed on a pre-wetted sand surface to prevent sand from lifting off due to the wind. For each intensity and wind velocity level, there were 30 splash cup measurements (a total of 360 splash cup measurements with 3 intensity and 4 wind velocity levels. Sand detachment rates were evaluated by the amount of sand splash out of the cup.

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Soil pan

7-m uniform slope segment

Sediment trapsW inddirection

a) T op view

W ind-driven rain

α

θ

α : rain inclination from verticalθ: slope degreeφ : angle of rainfall incidencecos φ = cos(α - θ)

W inddirection

W inddirection

W ind-driven rainα

θ

α : rain inclination from verticalθ: slope degreeφ : angle of rainfall incidencecos φ = cos(α + θ)

b) Side view of windward setup

c) Side view of leeward setup

Figure 1. Experimental set-up with soil pan and sediment traps for rainsplash measurements,

arranged on the slopes of windward and leeward in the I. C. E. wind tunnel.

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Figure 2. Splash cups used to evaluate the sand detachment rates (a), radial sand splashes by the vertical raindrop (b), and unidirectional sand splashes by the inclined raindrop (c).

AtmD = (3)

where, D is the sand detachment rate (g m-2 s-1); m is the mass of soil (g) splashed out of the cup. The product of At determines the number of sand particles per unit area per unit time, which are raindrop-induced and entrained in the splash droplets.

Similarly, rainsplash transport rates of soils were calculated using the amount of the splashed particles trapped at set distances on a 7 m uniform slope segment (Figure 1) and based on Eq. (1) by:

∫= dxmAt1Q i

rs (4)

where, Qs is in g m-1 min-1, A is the collecting trough area ( )2m168.0m14.0m20.1 =× , and tr is the time (min) during which rainsplash process occurred. Furthermore, using the exponential

porous cloth bottom

8 cm

4 cm

standard sand

Path of raindrop

Sand splashes in all directions

Path of raindrop

Unidirectional sand splashes

(b) (c)

(a)

α: Rain inclination from vertical

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29

relation between mass of soil particles and distance traveled, the average rainsplash trajectory was derived from the average value of the fitted function:

dxeab

1Xb

a

x∫ δ−

β−

= (5)

Eq. (5) gives an approximation of the average value of the mass distribution curves

over the interval a ≤ x ≤ b, where the lower limit a = 0. β and δ are coefficients that depend upon the physical properties of soil particles.

During each rainfall application and after runoff started sediment and runoff samples were collected at 5-min intervals at the bottom edge of the pan using wide-mouth bottles and were determined gravimetrically. Total sediment and runoff values, and the time during which the process occurred were used in calculation of sediment transport by rain-impacted thin flow (qs).

RESULTS AND DISCUSSION Assessment of drop size distribution of simulated rainfall in the I. C. E. wind tunnel by the logistic growth model given as Eq. (6) indicated that a distinct increase in D50 for all operating pressures was observed, and values were higher than 1.50 mm [2, 3, 4].

( ) γ−β−+= de1

100dN (6)

where, N(d) is the cumulative percentage of a given drop size by volume, d is drop diameter (mm), and β and γ are parameters of the logistic growth model. Indeed, the effects of wind on the drop size distribution of the simulated rains of the tunnel were rather different from its effects on that of natural rains. In other terms, its effect on large drop sizes would not be as great as those on small drops. Large drops are less stable, and wind may cause some of them to break up into smaller drops. Consequently, disintegration of large drops depending on wind may actually lead to a reduction in drop size. However, the wind caused the formation of larger drops in the tunnel since collisions between small drops happened more frequently as result of their greater number per unit volume of air. This accordingly brought about an increase in the median drop size. Assessment of the spatial distribution of the rain intensity in I.C.E. wind tunnel showed that wind-driven rain intensity was determined as a function of the angle of rain incidence, which was measured from the normal to the plane of incidence and given by the cosine law of spherical trigonometry [22]:

( ) ( )θαθα±θα=θα zzcossinsincoscoscos mm (7) where, α is the raindrop inclination from vertical, θ is the slope gradient, and zα and zθ are the azimuth from which rain is falling and the azimuth towards which the plane of surface is inclined, respectively. In the second term of Eq. (7), the positive sign indicates the windward-facing slope and the negative sign corresponds to the leeward-facing slope, implying the raindrop impact deficit with the same values of the slope degree and the raindrop inclination. Mainly, Eq. (7) implied that the wind-driven rain intensity varied with the raindrop inclination from vertical and slope degree and aspect.

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Splash cup technique, kinetic energy sensor, and analytical solution used to measure the kinetic energies of windless and wind-driven rains led to similar results for windless rains; unfortunately, the methods provided relatively different results for wind-driven rains. The discrepancy among the methods increased as the wind velocity increased (Table 1). The performance and accuracy of the techniques used were evaluated by considering the initial assumptions. It appeared that splash cup technique underestimated the kinetic energy. The reason for these relatively lesser values was the fact that the calibration study to establish a relationship between the amount of sand splashed and the rain energy was performed with vertically falling raindrops under windless conditions. It was apparent that at a given rainfall energy, there was a significant difference between the effectiveness of the vertical raindrops and the inclined raindrops in splashing sand out of the cups.

On the other hand, the analytical solution resulted in overestimation of the energy of wind-driven raindrops. This was because of the assumption that the wind velocity had a x-component of the raindrop velocity at the nozzle height. As anticipated, the raindrop horizontal velocities could not be attained because the horizontal wind velocities drifted only a few meters in the tunnel. For this reason, the rain energy measured by the kinetic energy sensor was found to be more reliable than those by the splash cup technique and the analytical solution. Although the calibration of the kinetic energy sensor was carried out with vertically falling raindrops, it did not involve in sand splash, which, we believe, differs significantly with wind-driven raindrops and directly relied on the amplitude of electrical pulses produced by the impact of raindrops on the surface of the sensor. The results of the rainsplash detachment rates from soil surfaces were analyzed for two cases of raindrop impact parameters, without angle of incidence and with angle of incidence. Fluxes of kinetic energy and momentum were used as rainfall parameters without angle of incidence:

= 2

Rar mV21ΞE (8)

( )Rar mVΞ=ϕ (9)

where, Ξa is the actual number of raindrops and calculated by ( )∀aI in # m-2 s-1, Er is kinetic energy flux in Wm-2, and ϕr is momentum flux in Nm-2. If rainsplash detachment was assumed to be related to the normal component of raindrop impact velocity ( )[ ]θα mcosRV [12,13,15,24], fluxes of kinetic energy and momentum, and raindrop impact pressure can, respectively, be calculated by:

( )θαcosmV21ΞE 22

Rarn m

= (10)

( ) ( )θαcosmVΞ Rarn m=ϕ (11)

( ) ( )θαcosVρΞΓ 22

Rwa m= (12) where, Ern (Wm-2) and ϕrn (Nm-2) are the kinetic energy flux and momentum flux, which are related to the normal component of resultant velocity, respectively, Γ (MPa) is the total raindrop impact pressure, and 222

xzR VVV += with tzVz ∂∂= and txVx ∂∂= .

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u

(m s-1) d50

(mm) KE (J)

VR (m s-1) KE = f (u)* R2

Splash Cup Technique 0 1.00 1.31E-06♣ (3.89E-07)♦ 2.22 (0.28) 6 1.63 1.04E-05 (3.26E-06) 3.00 (0.47)

10 1.53 2.45E-05 (4.06E-06) 5.09 (0.43) 14 1.54 4.02E-05 (9.02E-06) 6.38 (0.69)

KE = 2E-06e0.2473u 0.9555

Kinetic Energy Sensor 0 1.00 5.11E-06 (1.25E-06) 4.38 (0.58) 6 1.63 2.47E-05 (5.99E-06) 4.64 (0.56)

10 1.53 5.51E-05 (8.50E-06) 7.64 (0.60) 14 1.54 1.07E-04 (1.15E-05) 10.48 (0.57)

KE = 6E-06e0.2184u 0.9887

Analytical Solution 0 1.00 1.73E-05 4.10 6 1.63 6.05E-05 7.31

10 1.53 1.03E-04 10.47 14 1.54 1.95E-04 14.13

KE = 2E-05e0.1712u 0.9902

VR: resultant raindrop velocity at impact; *this illustrates a functional relationship which exists between the impact energy and the horizontal wind velocity obtained by the corresponding method in the form of KE = aebu with a and b showing the model parameters; ♣the E notation means "times 10 to the power"; ♦standard deviation is given inside the parentheses for the kinetic energy and the resultant impact velocity.

Table 1. The kinetic energies (J) and the resultant impact velocities (m s-1) of windless and wind-driven rains measured by both splash cup technique and kinetic energy sensor and estimated by the

analytical solution. Statistical analyses between rainsplash detachment rate and the rainfall parameters showed that Er and ϕr had low correlation coefficients with the detachment rate. This occurred because they were unable to account for the changes in raindrop trajectory. Even Ia alone led to a much greater correlation coefficient in each case. Very significantly, the introduction of angle of rain incidence into parameters produced improvements in the coefficients, and each of the parameters, Ern, ϕrn, and Γ, could account for more than 82% of the variation in the detachment rates. This suggested that the angle of rain incidence accounted for the differences in raindrop fall trajectory in connection with the rain inclination and slope gradient and aspect. On the other hand, the results of sand detachment by wind-driven rain showed that the tangential stress controlled the process rather than compressive stress or the normal component of resultant velocity. Kinetic energy flux (Erax) calculated using the horizontal component of wind-driven raindrops, [VRsinα], had a greater correlation coefficient than the kinetic energy flux (Eray) calculated using the normal velocity component, [VRcosα], with the sand detachment rates from the cups. Correlation coefficients with D were 0.96 and 0.54, respectively for Erax and Eray at the significance level of P = 0.0001 (Table 2). The reason for this might be that the vertical compressive stress of a wind-driven raindrop at impact weakens as the raindrop deviates from the vertical and the tangential shear stress becomes stronger. Our experimental study demonstrated that tangential jetting of raindrops mainly caused the sand detachment from the splash cups by the wind-driven raindrops. Openly, the soil material behaved differently from the sand surface, and as wind velocity and angle of rain incidence increased, the rate of sand detachment increased even though the rate of soil detachment decreased. These findings also indicated that the strength of the surface, such as interparticle friction and cohesion, significantly affected the detachment rate and determined the

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differential contribution of the compressive and tangential stress to the process under wind-driven raindrops.

Eray

Erax

D

Eray 1.00

(0.0000)† 0.53

(0.0001) 0.54

(0.0001)

Erax 1.00 (0.0000)

0.96 (0.0001)

D 1.00 (0.0000)

* ( )αcosEE 2raray = ; ** ( )αsinEE 2

rarax = ; †Numbers in parantheses are significance levels. Table 2. Pearson correlation coefficients between the sand detachment rate, D, (g m-2 s-1) and the the

kinetic energy flux related to both normal component, Eray*, (J m-2 s-1) and horizontal component,

Erax**, (J m-2 s-1) of the raindrop impact velocity.

On the other hand, measured rainsplash transport rates varied in close relationship to the raindrop impact parameter (Θ) and wind shear velocity. Therefore, the process was successfully modeled under the approach that once lifted off by the raindrop impact, the soil particles entrained into the splash droplets traveled some distance, which varied directly with the wind shear velocity. The raindrop impacts induced the process that would otherwise be incapable of transporting. At last, the wind-driven rainsplash process was related to the rainfall parameter and the wind shear velocity and analyzed using a log-linear regression technique:

11 b*

a1s ukQ Θ= (13)

where, k1 is the relative soil transport parameter for the wind-driven rainsplash process, u* is the wind shear velocity (ms-1), and a1 and b1 are the regression coefficients. Eq. (13) incorporated the dynamic effects of physical raindrop impact and wind action on the process, therefore, provided a basis for modeling interrill rainsplash transport under wind-driven rains. Additionally, the results of the study to determine the effects of slope aspect, slope gradient, and wind shear velocity on the trajectories of the raindrop-induced and wind-driven soil particles indicated that neither slope aspect nor slope gradient significantly predicted the splash-saltation trajectory. As a result, we conducted a statistical analysis to fit the average trajectories of the process into nonlinear regression model of:

( )guCX 2*1

_= (14)

where _X is in m, u* is in ms-1, and g is in ms-2. C1 is a model parameter. These results also

contradicted the previous approach of the splash-saltation transport based on only the slope aspect and gradient for defining the process.

Along with the substantial effects of the wind on raindrop impact parameter and rainsplash detachment and transport processes, there were significant wind effects on sediment transport by raindrop-impacted shallow flow. This process was modeled based on interrill erosion mechanics [13,14,17,18,26]:

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co

barns SqkEq = (15)

where, k is soil transport parameter for the sediment transport by raindrop-impacted shallow flow and , a, b, and c are regression coefficients to which kinetic energy flux (Ern), unit discharge (q) and slope (So) are raised, respectively. Flux of rain energy computed by combining the effects of wind on the velocity, frequency, and angle of raindrop impact and unit discharge and slope adequately described the characteristics of wind-driven rains and significantly explained the variations in sediment delivery rates to the shallow flow transport (R2 ≥ 0.91). Analyses of the Pearson correlation coefficients additionally showed that a significant difference occurred in shallow flow hydraulics with different aspects under the impacts of wind-driven raindrops. The reverse / advance particle splashes and the lateral stress of impacting raindrops at angle with respect to the shallow flow direction were concluded to have significant effects on the shallow flow hydraulics under wind-driven rains. Further analyses to understand the effects of roughness elements on the sediment transport capacity of raindrop-impacted shallow flow were conducted by partitioning the resultant kinetic energy into its vertical and horizontal components since the magnitude of those significantly changed with wind velocity, slope aspect and gradient and accordingly their effects on thin flow hydraulics.

)(sinKEKE 2x β±α= (16)

)(cosKEKE 2y β±α= (17)

0qSγ=Ω (18) cb

yaxs KEkKEq Ω= (19)

where, Ω is the stream power as a flow parameter (kg s-3).

CONCLUSIONS This paper aims to give a review of wind-driven rain erosion research performed in I.C.E wind tunnel rainfall simulation facility giving the principal discrepancies obtained in water erosion sub-processes when wind came into play during rains. Concepts and mechanisms were discussed giving experimental results on the effects of wind on the drop size distribution, rain intensity and energy, rainsplash detachment and transport, and thin flow transport capacity.

REFERENCES [1] Cornelis, W., Erpul, G., D. Gabriels. The I.C.E. Wind Tunnel for Wind and Water Interaction Research. Wind and Rain Interaction in Erosion, Visser, S. and Cornelis, W. (Eds.), Tropical Resource Management Papers, Chapter 13, p (195 - 224). Wageningen University and Research Centre (2004). [2] Ellison, W. D. Soil erosion studies (7 parts). Agr. Eng. 28: 145-146; 197-201; 245-248; 297-300; 349-351; 407-408; 447-450 (1947). [3] Erpul, G., D. Gabriels, D. Janssens. “Assessing the Drop Size Distribution of Simulated Rainfall in a Wind Tunnel,” Soil & Tillage Research, 45, 455-463 (1998). [4] Erpul, G., D. Gabriels, D. Janssens. “Effect of Wind on Size and Energy of Small Simulated Raindrops: A Wind Tunnel Study,” Int. Agrophysics, 14, 1-7 (2000).

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[5] Erpul, G., D. Gabriels, L. D. Norton,. “Wind effects on sediment transport by raindrop-impacted shallow flow”, Earth Surface Processes and Landforms, 29: 955-967 (2004). [6] Erpul, G., D. Gabriels, L. D. Norton. “Sand Detachment by Wind-driven Raindrops”. Earth Surface Processes and Landforms, 30: 241-250 (2005). [7] Erpul, G., L. D. Norton, D. Gabriels. “Raindrop-Induced and Wind-Driven Particle Transport,” Catena, 47, 227-243 (2002). [8] Erpul, G., L. D. Norton, D. Gabriels. “Sediment Transport From Interrill Areas under Wind-Driven Rain”, Journal of Hydrology, 276 (1-4), 184-197 (2003). [9] Erpul, G., L. D. Norton, D. Gabriels. “Splash – saltation trajectories of soil particles under wind-driven rain”, Geomorphology. 59: 31-42 (2004). [10] Erpul, G., L. D. Norton, D. Gabriels. “The Effect of Wind on Raindrop Impact and Rainsplash Detachment”, Transactions of American Society of Agricultural Engineering. Vol. 45(6): 51-62 (2003). [11] Gabriels, D., Cornelis, W., Pollet, I., Van Coillie, T., Quessar, M. The I. C. E. wind tunnel for wind and water erosion studies. Soil Technology. 10: 1-8 (1997). [12] Gilley, J. E. & Finkner, S. C. Estimating soil detachment caused by raindrop impact. Transactions of the American Society of Agricultural Engineering, 28, 140-146 (1985). [13] Gilley, J. E., Woolhiser, D. A. & McWhorter, D. B. Interrill soil erosion. Part I: Development of model equations. Transactions of the American Society of Agricultural Engineering, 28, 147-153 and 159 (1985). [14] Guy, B. T., W. T. Dickinson and R. P. Rudra. The roles of rainfall and runoff in the sediment transport capacity of interrill flow. Transactions of the ASAE 30(5): 1378-1386 (1987). [15] Heymann, F. J. A survey of clues to the relation between erosion rate and impact parameters. In: Proceedings of International Conference on Rain Erosion and Allied Phenomena. Second Rain Erosion Conference, The Royal Aircraft Establishment, Farnborough, England, 2, pp. 683-760 (1967). [16] Hudson, N. W. The influence of rainfall mechanics on soil erosion. M. Sc. Thesis, University of Cape Town (1965). [17] Julien, P. Y. and D. B. Simons. Sediment transport capacity of overland flow. Transactions of the ASAE 28: 755-762 (1985). [18] Parsons, A. J., S. G. L. Stromberg and M. Greener. Sediment-transport competence of rain-impacted interrill overland flow. Earth Surf. Processes and Landforms, 23: 365-375 (1998). [19] Poesen, J. An improved splash transport model. Z. Geomorph. N. F., 29: 193-221. 69-74 (1985). [20] Samray, H., Erpul, G., Gabriels D. The effect of slope aspect on sediment transport by shallow overland flow under wind-driven rain. 18th International Soil Meeting (ISM) on “Soil Sustaining Life on Earth, Managing Soil and Technology”, May 22 – 26, 2006 Şanlıurfa – Turkey, Proceedings, Volume 1: 459 – 464 (2006). [21] Savat, J. and J. Poesen. Detachment and transportation of loose sediments by raindrop splash. Part I: The calculation of absolute data on detachability and transportability. Catena 8: 1-18 (1981). [22] Sellers, W. D. Physical Climatology. University of Chicago Press, Chicago, Ill. pp. 33-35 (1965). [23] Sensit. Model V04 Kinetic Energy of Rain Sensor. Portland, N. D.: Sensit Company (2000). [24] Springer, G. S. Erosion by liquid impact. John Wiley and Sons, Inc., New York (1976). [25] Van Heerden, W. M. An analysis of soil transportation by raindrop splash. Trans. ASAE, 10:166-169 (1967). [26] Zhang, X. C., M. A. Nearing, W. P. Miller, L. D. Norton and L. T. West. Modeling interrill sediment delivery. Soil Sci. Soc. Am. J. 62: 438-444 (1998).

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Workshop IC-PLR 2006 – Theme A – Soil and groundwater pollution and remediation

36

WORKSHOP THEME A – SOIL AND GROUNDWATER POLLUTION AND REMEDIATION

Sub-theme : Managing contaminated soils using phytoremediation Erik Meers, Filip M.G. Tack, Marc G. Verloo

Paper/poster : Comparison of amendments used to remediate acid mine tailings: Environmental and Agricultural Applications - Kelly A. Senkiw, Tee Boon Goh Paper/poster : Study on the effects of trade village waste on accumulation of Cu, Pb, Zn and Cd in agricultural soils of Phung Xa Village, Thach Thanh District, Ha Tay Province - Nguyen Huu Thanh, Tran Thi Le Ha, Nguyen Duc Hung, Tran Duc Hai Paper/poster : Metal contamination in irrigated agricultural land : case study of Nairobi River basin, Kenya – P.N. Kamande, F.M.G. Tack

Sub-theme : Managing groundwater pollution from waste disposal sites Kristine Walraevens, Marleen Coetsiers, Kristine Martens, Marc Van Camp

Paper/poster : Contamination of the Marimba River Tributary, Zimbabwe, with Cu, Pb, Zn and P by industrial effluent and sewer line discharge – Bangira C., Wuta, M. Dube, H.M., Chipatso, L. Paper/poster : Controlling phosphorus (P) mobility in poorly P sorbing soils : drinking-water treatment residuals (WTR) to the rescue – S. Agyin-Birikorang, G.A. O'Connor, L.W. Jacobs Paper/poster : Heavy metal contamination of soil and surface water by leachates of an open dump of municipal solid waste : a case study of oblogo landfill in the Ga West District of Accra, Ghana – Abuaku Ebenezer

Conclusions


37

Sub-theme : MANAGING CONTAMINATED SOILS USING PHYTOREMEDIATION

Erik Meers, Filip M. G. Tack, Marc G. Verloo

Laboratory of Analytical Chemistry and Applied Ecochemistry, Ghent University, Ghent, Belgium

Abstract Soil contamination with heavy metals is a widespread environmental issue, remediation of which is hampered by excessive economic costs. Phytoremediation is the use of plant based techniques for soil remediation. This technology can help to solve some of the environmental issues involved, yet only under certain conditions. Some of the do’s and don’t of phytoremediation applications will be discussed during the oral presentation.

SOIL CONTAMINATION

An unfortunate byproduct of industrialization has been the contamination of soil and water resources with heavy metals, metalloids and other harmful substances. Over the last decades, awareness of the problem has grown considerably, as has the insight that the problem is more widespread than was initially assumed [1]. Conventional soil remediation techniques fall short of expectation to tackle the overwhelming task at hand due to their high cost: engineering techniques cost between €40 - €400 per m3 of soil treated [2]. In Flanders (Belgium, Europe) average soil remediation costs are estimated at €310 per ton (based on [3]). The estimated total cost for remediation of historically polluted soils is estimated at 7 billion euro [4]. In Europe, overall cleanup costs for historic pollution are estimated to run into the 100 billion euro range [5, 1]. Budget estimates for soil remediation generally exclude the necessity to remediate light to moderately contaminated sites due to low priority and already high cost involved in cleaning the heavily polluted sites.

PHYTOREMEDIATION Phytoremediation has been proposed as an economic alternative for some of the environmental issues involved in heavy metal pollution [6, 7]. Phytoextraction is a plant based technique aimed at removing inorganic contaminants from the soil matrix by plant absorption and translocation to harvestable plant parts. By subsequently removing the metal-enriched biomass from the site, a gradual attenuation of the contamination in the top soil layer is achieved.

As a soil remediation technique, it offers the following advantages over conventional remediation techniques: as an in situ technique, it is less invasive and more economic than civil-engineering earth moving techniques. Also, it can be applied over extended surface areas and targets the “bioavailable” soil fraction of heavy metals, which is the most relevant fraction from an environmental risk assessment perspective. The most important drawback is the long required remediation period (years to decades). The sense of uncertainty in regards to system consistency and performance predictability of biological remediation systems can also be perceived as a drawback. The use of soil amendments to increase accumulation of heavy metals in harvestable plant parts can also increase the risk of leaching. In addition, elevated


38

aboveground plant concentrations also run the risk of entering the foodchain through herbivory of the phytoextraction crops.

RESEARCH FINDINGS Phytoextraction research at our laboratory [8] revealed several important findings:

Firstly, phytoextraction as a soil remediation technique can only be applied on lightly to moderately contaminated soils. This not only for plant tolerance reasons, but also because reducing metal concentrations in more heavily polluted soils to levels below legal soil sanitation criteria would take excessively long periods of time (in the order of centuries).

Secondly, phytoextraction is not equally applicable for all heavy metals as plants have a different affinity for uptake of the various metals. Particularly for Cd and Zn the technique appears to be suitable, and to a lesser extent also for Cu.

Thirdly, since the technique is slow working (order of years and decades) it is considered a vital prerequisite to economically re-valorize the produced biomass for industrial applications. A viable approach is to employ bio-energy crops with affinity for metal removal. These energy crops can be converted into electrical and thermal energy. However, the fate of the accumulated metals in the phytoremediation biomass needs to be monitored closely during the conversion processes. Other industrial applications can be found in the paper industry, fibre industry, wood industry and so on. During the presentation, several field studies will be presented in which phytoextraction of heavy metals is examined.

REFERENCES

[1] C. Ferguson, H. Kasamas. “Risk assessment for contaminated sites in Europe”. CARACAS publication. LQM Press, Nottingham (UK), 223 p. (1999) [2] S.D. Cunningham, D.W. Ow. “Promises and prospects of phytoremediation”. Plant Physiology, 110, 715-719. (1996) [3] F. De Naeyer. “Soil Remediation Projects: the new guidelines and daily practice”. Studyday TI-KVIV (30/3), Technological Institute. (Translated from dutch). (2000) [4] Ecolas. “Financial cost estimation in regards with soil sanitation”. OVAM (Public Waste Agency of Flanders), Mechelen, Belgium. (Translated from Dutch). (2001) [5] D.J. Glass. “U.S. and international markets for phytoremediation”, 1999-2000. D. Glass Associates Inc., Needham (USA), 266 p. (1999) [6] A.J.M. Baker, R.R. Brooks. “Terrestrial higher plants which hyperaccumulate metallic elements – a review of their distribution, ecology and phytochemistry”. Biorecovery, 1, 81-126. (1989) [7] A.J.M. Baker, S.P. McGrath, R.D. Reeves, J.A.C. Smith. “A review of the biological resource for possible exploitation in the phytoremediation of metal-polluted soils”. In: Terry, N. & Bañuelos, G.S. (Eds.), Phytoremediation of Contaminated Soil and Water. CRC Press LLC, Boca Raton, FL, 85-107. (1999) [8] E. Meers. “Phytoextraction of heavy metals from contaminated dredged sediments”. ISBN 90-5989-053-1, 341 pp., Ghent University, Ghent, Belgium. (2005)


39

COMPARISON OF AMENDMENTS USED TO REMEDIATE ACID MINE TAILINGS: ENVIRONMENTAL AND AGRICULTURAL APPLICATIONS

Kelly A. Senkiw and Tee Boon Goh*

Department of Soil Science, University of Manitoba, Winnipeg, Canada R3T 2N2

Abstract In environments with low pH, a large portion of the total copper can exist in the labile and potentially toxic water-soluble form, while the rest is distributed among chemical forms that are less bioavailable. Copper was sequentially extracted from acid mine tailings, in order to assess the potential lability and availability of the metal. Four amendments were applied to the tailings in an incubation study, and sequential extraction was used to examine the distribution of copper among six fractions. The control was highly contaminated with copper, containing 564 mg kg-1 of water-soluble copper. The addition of wheat straw (WS) reduced this form to 305 mg kg-1. The addition of an alkaline extract of humic substances from leonardite (HS) decreased the free copper to 72 mg kg-1, while the combination of HS+WS reduced it to 30 mg kg-1. The CaCO3 amendment reduced free copper to near zero. The amendments increased the pH of the tailings in the order of Lime > HS+WS > HS > WS. Total copper in the tailings ranged from 1816-2275 mg kg-1 by summation of copper in the six fractions. Total copper by acid digestion was 2257-2360 mg kg-1. The efficiency of the sequential extraction method varied from 75 to 96%. Lime was the most effective at reducing the potential availability of copper, followed by HS+WS, then HS.

INTRODUCTION

Many regions in Canada have been mined for natural resources such as coal and industrial metals. The aboveground storage of mine tailings exposes previously buried minerals to the surface environment. Here, accelerated chemical and biological weathering can occur, with the associated risk of contamination by heavy metals (Barnhisel et al. 1982, Amacher et al. 1995). The presence of sulphur-containing minerals at mine sites is a precursor to the production of sulphuric acid by the process of oxidation, resulting in a pH as low as 3.5 (Dixon et al. 1982). Heavy metals such as Cu, Ni, Zn, Mn and Fe are often present in mine spoils, and their mobility and toxicity may be increased in acidic environments (Barnhisel et al. 1982). The potentially toxic combination of a low pH and dissolution of heavy metals are hazardous to vegetation and habitats bordering mine tailings. Hence the reclamation of mine spoils or tailings must involve a neutralization of pH, as well as a reduction of lability, availability and toxicity of free metal ionic contaminants. Several mines operated within Manitoba in the early twentieth century, in the region that is now Nopiming Provincial Park. Today, the tailings of a former gold mine cover an area of approximately 5400 m2 and have remained virtually barren since the mine’s closure, in 1937, despite several recent attempts at revegetation on site. It is believed that revegetation has been limited by the acidity and extremely high concentrations of copper and other metals in the tailings (Renault et al. 2000). The acid portion of the tailings have a pH of 3 to 5, and contain, on average, 2300 mg kg-1 total copper (by digestion) (Ibrahim and Goh 2004). Merely knowing the total contents of heavy metals (such as copper) in a soil provides limited information about the potential behaviour and bioavailability of the metals. Soil texture, pH, organic matter content, and Fe/Mn oxides also influence the lability and bioavailability of copper. A heavy metal in soil can be associated with many of these soil components. Sequential extraction techniques have been employed to examine the


40

distribution of metals, such as copper, among soil micronutrient pools (Shuman 1985; Sims 1986; Alva et al. 2000; Kabala and Singh 2001). Shuman (1991) describes six conceptual micronutrient pools in soils: water-soluble; exchangeable; precipitated as carbonate; associated with Fe, Mn, and Al-oxides; organically-bound; and residual (hereafter referred to as fractions F1 to F6). The water-soluble and exchangeable forms of metals are considered readily labile and available to plants, while the other forms can be considered relatively inactive or strongly bound (Alva et al. 2000).

Copper is a trace element that is essential to the nutrition of plants and animals. The average Cu content in soils is around 30 ppm with a range from 2-100 ppm (Aubert and Pinta 1977) and it is well-documented that excessive bioavailability of copper is toxic. In fact, the soil-plant continuum functions as a natural barrier against toxicity to animals. Plant growth (e.g. revegetation of copper-contaminated tailings) will either be greatly reduced or will cease before a dangerously toxic amount would be accumulated and transferred to animals via the food chain.

Organic matter accounts for many useful functions in soils, sediments and natural waters (Aiken 1985). Studies using humic substances obtained from lignite as a soil conditioner or amendment are rare. Whiteley and Williams (1993) investigated a metal-contaminated mine spoil (pH = 5.1) after amendment with three forms of lignite: untreated lignite; and the insoluble and soluble extracts obtained after an oxidation treatment. The authors concluded that the lignite treatment may be a valuable reclamation tool, as it improved the survival of non-tolerant cultivars in a Cd-, Pb-, Zn-contaminated mine spoil. However, the composition of the lignite was not known with certainty. Preliminary investigations in our laboratory revealed that humic substances constitute most of the organic matter in leonardite, a coal mine overburden material that is rich in carbon, but is usually discarded because it does not burn like coal. It was of interest to investigate if the humic substances that can be obtained following alkaline chemical extraction of leonardite was of benefit in the reclamation of copper-contaminated mine spoils.

The objectives of this study were to assess the copper distribution among six defined fractions, and thereby approximate the lability and the bioavailability of copper, within the mine tailings; and, further, to investigate the potential of alkaline humic substances from leonardite, lime, and wheat straw amendments to reduce the lability and bioavailability of copper after incubation for 24 weeks.

MATERIALS AND METHODS Acid mine tailings were collected from the surface of the Central Manitoba Mine site. The tailings were then stored at room temperature in a covered, five-gallon plastic pail.

The mine tailings have a sandy loam texture, with 48.5% sand, 47.2% silt, and 4.3% clay. Their organic matter content is very low (2.1 g kg-1), and total copper contents are extremely high (≥2000 mg kg-1) (Renault et al. 2000; Ibrahim and Goh 2004).

The experiment was designed to compare the effects of different organic amendments on the distribution of copper in the mine tailings. Humic substances (HS), fresh wheat straw (WS), and lime (CaCO3) were mixed with the mine tailings in four combinations. All experimental units were 200 g of mine tailings. For the HS treatment, 14 mL of liquid HS, (5.62% Organic Carbon), pH = 10.5, was added. The WS, containing 65.5% carbon, was ground by hand and 2.29 g was added to the tailings. The amounts of HS and WS applied corresponded to 4.0 and 7.5 g C kg-1 tailings, respectively. The third treatment was the combined addition of HS+WS, at the same rates. The lime was applied at a rate of 4 g CaCO3


41

kg-1 tailings. Nitrogen (N) was added to all samples except the Control at the rate of 50 mg N kg-1 tailings. All samples were prepared in triplicate and placed in 500 mL plastic containers with lids. The samples were incubated at 20°C for 24 weeks and their moisture was maintained at 60% of the water holding capacity throughout the incubation period. Fractionation of Copper Total copper concentration of the tailings was determined following digestion of a sample with aqua regia. In addition, six fractions of copper (labeled F1 to F6) were extracted according to the procedure of Salbu et al. (1998). After each step, the supernatant was separated by high-speed centrifugation for 30 min at 10,000 x g. The residue was washed with 10 mL of deionized water and the wash was combined with the supernatant. All supernatants were refrigerated until analysis for copper content by graphite furnace atomic absorption spectrophotometry. The sequential extraction was conducted in the following manner:

A two-gram subsample of tailings and 20 mL of deionized water were combined in a 50 mL polycarbonate centrifuge tube and shaken for 1 hour at 20°C. The supernatant containing the water-soluble copper, denoted Fraction 1 (F1), was collected and stored. The F1 residue (i.e. the soil following F1 extraction) was extracted for 2 hours with 20 mL of 1 mol L-1 ammonium acetate, pH 7 to obtain the exchangeable copper (F2) from the mine tailings. To obtain Fraction 3 (F3), the F2 residue was extracted for 2 hours on a shaker with 20 mL of 1 mol L-1 ammonium acetate, pH 5. Fraction 4 (F4), the metal-associated (or specifically-sorbed) copper, was collected by combining the F3 residue with 20 mL of 0.04 mol L-1 NH2OH-HCl solution for 6 h in a 60°C water bath. To collect Fraction 5 (F5), the organically complexed copper, the F4 residue was extracted for 5.5 h in an 80°C water bath with 15 mL of 30% H2O2, pH 2. After cooling, 5 mL of 3.2 mol L-1 ammonium acetate was added and the sample was shaken for 30 minutes. The solution was brought up to 20 mL with deionized water. Finally, all of the remaining copper in the sample was extracted into Fraction 6 (F6). The residue from F5 was allowed to dry for a few minutes. One gram of the residue was placed into an Erlenmeyer flask and digested with 10 mL of 7 mol L-1 HNO3 on a hotplate for 6 hours. After dissolution with 1 mL of 2 mol L-1 HNO3, the contents were made up to 10 mL. Analysis for Copper Concentration The copper concentration of all extracts was determined by graphite furnace atomic absorption spectrophotometry (AAS). Standard copper solutions were prepared in each of the matrices utilized in the sequential extraction procedure. Data Analysis The experiment was carried out as completely randomized design (CRD). The copper fractions (F1-F6), and total copper (by sum of fractions, and by digestion), were randomized among the treatments (Control, HS, HS+WS, WS, and Lime). Analysis of variance (ANOVA) was performed using Statistical Analysis Software (SAS Institute 2000).


42

RESULTS AND DISCUSSION Effect of Amendments on pH of the Tailings The pH measurements (1:1; soil:water) of the tailings after the incubation period of 24 weeks are listed in Table 1. The pH of the control tailings was 3.32. As expected, lime was the most effective treatment, raising the pH to 5.59. The HS alone augmented the tailings’ pH to 4.5, whereas the WS alone increased the pH by a slight 0.6 units compared to the control. In comparison, the combined HS+WS treatment raised the pH to 5.02. The combination of HS+WS caused a 50-fold reduction in the acidity (i.e. 1.7 pH units), compared to the control.

Despite the fact that all four treatments were able to increase the pH of the mine tailings above the initial value of 3.32, the pH still remained in the acidic range. This means that following the application of the amendments containing HS at the rate used in this experiment, site rehabilitation by revegetation may still not be possible since the availability of heavy metals is expected to be high in acidic environments. Some plants may be able to tolerate the slightly acidic pH in the lime- and HS+WS- amended tailings, but further investigation will be necessary to identify these plant species. Effects of Amendments on the Distribution of Copper The total copper measured by fractionation in the control tailings was 1816 mg kg-1 (Table 1). Of this total, 31% or 564 mg kg-1 of Cu was found in F1, the water-soluble fraction. This is an extremely high amount, and is expected to be very toxic to organisms. The organically-complexed fraction (F5) contains the largest portion of copper in the untreated tailings (34%) (Table 1 and Fig. 1). The total copper extracted from the tailings treated with alkaline HS was 1824 mg kg-1 This was very similar to the amount of total copper obtained from the control. The water-soluble copper was drastically reduced from 564 to 72 mg kg-1 (Table 1). The copper was redistributed into the other fractions, i.e. F2 to F6. The largest increase was observed in F5, which rose to 872 mg kg-1 compared to 618 mg kg-1 in the control, although this difference is not significant. However, the observed increases in the copper content of the F2 and F3 fractions were significant compared to the control. Furthermore, if fractions F1 (water-soluble) and F2 (exchangeable) are indicative of the most available fractions of Cu, it is observed that the HS treatment may greatly reduce the availability of Cu to plants. The size of the residual copper pool (F6) in the HS treated tailings was the largest of all amendments, at 23%.

The fractionation procedure extracted almost 2300 mg kg-1 of total copper from the tailings treated with HS+WS. The soluble, toxic form of copper was reduced to 1% of the total copper extracted, or 30 mg kg-1 (Table 1 and Fig. 1). The organically bound copper comprised 52% of the distribution, and was significantly higher than the F5 of all other treatments. A total of 11.5 g C was added per kg tailings, which is the highest of all the treatments. Because organic matter provides surface sites for adsorption and complexation of copper, it is expected that increasing additions of carbon residues will correspondingly raise the copper in F5. The HS+WS amendment was very effective at reducing the toxic forms of copper, while redistributing the copper to fractions where it is strongly held (F4, F5, F6) and thus considered to be less bioavailable.

When applied alone, the WS did not reduce the free copper as much as the amendments containing the alkaline HS. The water-soluble copper was reduced from 30% in the control, to 15% in the WS-treated tailings (Fig. 1). However, the 305 mg kg-1 of free copper (Table 1) was still extremely high, and poses a toxicity hazard to organisms. It is


43

possible that the low pH of the WS-amended tailings may have limited microbial activity and the ability of WS carbon to play a role in immobilizing copper. In contrast, when WS was added in combination with HS, the water-soluble copper was reduced to 30 mg kg-1. The slightly higher pH observed in the tailings that received the HS+WS treatment may have contributed to the reduction in F1, compared to the control. The pH of 5.02 was probably more favourable for the carbon of the WS to be used by microbes, and thus through decomposition, the WS may have contributed some active surface sites to which Cu could be adsorbed or chelated.

A total of 1989 mg kg-1 of copper was extracted from the tailings treated with Lime. The water-soluble copper was negligible, at only 7 mg kg-1. This is a reduction of 80 times compared to the control. The copper was redistributed to all other fractions, with greatest gains in F4 and F6. The lime treated tailings had the largest increase in F4 of all the treatments, at 22% of the total distribution, compared to 11% in the control. This provides evidence that the F4 fraction obtained by this fractionation scheme extracts some carbonate bound copper, in addition to metal-oxide bound copper.

In this study, an amendment was considered effective based on several observations. Firstly, if it elevated the pH of the tailings, then the lability of copper would be reduced (Sims 1986; Alva et al. 2000). The water-soluble copper is the most toxic form, followed by the adsorbed and exchangeable forms. Thus, if an amendment reduced the copper in these fractions, it was considered beneficial in decreasing the potential for mobility and toxicity. A corresponding increase of copper in fractions where it is tightly bound or unavailable (i.e. F4, F5, and F6), was also considered a benefit. There is some uncertainty as to whether the carbonate-bound fraction (F3) is labile and available. This would depend on the pH, since the Cu sorbed by carbonates may have a transient existence in carbonate minerals. In an acidic environment the Cu may be released upon dissolution of the carbonate. Thus, fraction F3 represents a potentially mobile and available pool among the total copper.

The treatments HS, HS+WS, and Lime, all drastically reduced the F1 fraction of copper in the tailings (Table 1). The amount of water-soluble copper in the tailings amended with Lime plunged to a nearly negligible amount of 7 mg kg-1. The treatments containing modified leonardite (HS and HS+WS) were both highly effective compared to the control, with HS+WS outperforming HS alone (30 and 72 mg kg-1, respectively).

The amount of free copper in soil solution is very important because this form is readily absorbed by plant roots. In soil solutions with pH < 6.0, the dominant species of copper is the divalent cation, Cu2+ (Harter 1991). As the pH increases, two hydrolysis reactions occur fairly quickly.

Cu2+ + H2O Cu(OH)+ + H+ log K = -7.70 [1] Cu(OH)+ + H2O Cu(OH)2 + H+ log K = -6.08 [2] If an amendment was able to increase the pH, the more unavailable chemical forms of copper such as Cu(OH)+, Cu(OH)2, and even CuO would be formed.

The results show that all treatments caused some of the water-soluble copper to be redistributed from F1 to F2. However, the copper in F2 is still relatively labile, and still poses a toxicity threat because it may be released into solution via cation exchange, or may be subject to plant uptake. In a practical sense, it must also be noted that the quantities of copper held in the exchangeable fraction are very small when compared to the total copper in the tailings. For the Control and WS treatments, where F1 is very large, exchangeable copper contributes very little to the potentially toxic copper in the tailings. But, for treatments with small amounts of Cu in F1, namely HS, HS+WS, and Lime, F2 values are approximately


44

equal to the amount of water- soluble copper, and thus they contribute more to potential toxicity or bioavailability.

All treatments significantly increased the amount of copper in the carbonate-associated fraction, F3 (Table 1). Despite the statistical differences between treatments, the relative size of the F3 fraction only varied from 8.7 to 9.9% in all of the amended tailings (Fig. 1). There is some uncertainty concerning the classification of F3 as carbonate-bound Cu (Shuman 1991). We doubt that in this instance, that F3 represents carbonate bound Cu, since, in the acid pH conditions of the mine tailings, free calcium carbonate was non-existent.

Examination of the organically-complexed fraction, F5, reveals several interesting observations. This was the largest pool of copper in all treatments, comprising 34 to 52% of the total copper (Fig. 1). The amount of organically-complexed copper ranged from 618 to 1185 mg kg-1 across all treatments, and the differences were found to be statistically significant at p < 0.10 (Table 1). As anticipated, the treatment that added the most organic material to the tailings, HS+WS, was the most successful at raising the copper in F5.

Copper ions in soil solution are often complexed with various inorganic or organic ligands. Complexation with organic acids or low molecular weight organic matter may solubilize copper and render it available for plant uptake or leaching (van der Watt 1991 et al.; Merritt and Erich 2003). On the other hand, complexation followed by precipitation with complex humic substances may immobilize the copper (Stevenson 1982). Effect of Amendments on Potential Lability and Plant Availability of Copper The water-soluble and exchangeable forms of metals in soils are considered to be plant-available (Shuman 1991; Alva et al. 2000). The free copper cation or its complexed species may be adsorbed to the negatively charged colloids within the soil. Attraction due to electrostatic forces is referred to as non-specific or outer-sphere adsorption. This copper is exchangeable using salt solutions because of its relatively weak adsorption onto non-specific exchange sites (Shuman, 1991). The F3 fraction, considered to be carbonate-bound, is sometimes included in this estimate, as metals in this fraction can become available under altered environmental conditions (Kabala and Singh 2001). Alternately, copper may form covalent bonds with an OH- ligand on a soil colloid, such as Fe, Mn, or Al oxides. If the copper forms two covalent bonds with the exchanger, the copper is strongly retained by the soil. This is termed specific adsorption. In this case, the copper is not salt-exchangeable.

The Lability Factor (LF) was employed as an aid in assessing the plant-availability of copper in the mine tailings. It is a relative index to compare metal lability among treatments. When F1+F2 are the only fractions considered to be labile at the time of fractionation, the control tailings have the highest lability, with an LF of 32% (Table 2). The Lability Factors for the HS and HS+WS treatments are 6.3 and 4%, respectively. The Lime treatment was more effective at reducing the F1 and F2 fractions of copper, resulting in a low LF of 2.4%.

If fraction F3 is also considered labile, then 37% of the relative distribution of copper in the control tailings is potentially toxic. Regardless, the resulting lability factors, Lability Factor 2, present the same pattern as described for Lability Factor 1 (Table 2). Hence, the treatments containing the alkaline organic amendment (HS and HS+WS) decreased the copper LF to less than half of its original value, and the Lime is slightly more effective than the HS+WS.

Caution must be taken when using a Lability Factor to interpret the potential movement or availability of metals in soil. It is useful as a discussion tool, but the mobility of copper in individual fractions is only assumed, and not measured. Moreover, the values are in percentage of the total Cu and not in actual concentration in the soil. The copper extracted


45

into each fraction, and its lability, will depend upon the individual soil and the metal fractionation procedure employed.

CONCLUSIONS The study confirmed that the tailings from the Central Manitoba Mine site are highly contaminated with copper, containing approximately 2300 mg Cu kg-1. The control tailings contained 564 mg kg-1 of water-soluble copper, which is readily labile and toxic. Approximately one-third of the total copper in the acid tailings is considered potentially toxic.

All amendments altered the distribution of copper. The Lime was the most effective at increasing pH, and decreasing soluble copper. The two treatments containing alkaline, humic substances extracted from leonardite were also effective at reducing water-soluble copper. The addition of WS with the HS further reduced the water-soluble fraction. The treatment HS+WS also had the highest amount of copper in the organically-complexed fraction.

In conclusion, the alkaline humic substances extract used in this research may be a valuable addition to a reclamation strategy for acid, copper-contaminated mine tailings.

ACKNOWLEDGEMENTS

This study was supported by a research grant from LUSCAR Ltd. to TBG and the James Gordon Fletcher Graduate Fellowship in Agricultural and Food Sciences to KAS.

REFERENCES [1] Aiken, G.R. 1985. Isolation and concentration techniques for aquatic humic substances. Pages 363-385. in Aiken, G.R., McKnight, D.M., Wershaw, R.I. and MacCarthy, P. (Eds). Humus Substances in Soil, Sediment and Water: Geochemistry, Isolation and Characterization. John Wiley, New York.. [2] Alva A.K., Huang, B. and Paramasivam, S. 2000. Soil pH affects copper fractionation and phytotoxicity. Soil Sci. Soc. Am. J. 64:955-962. [3] Amacher, M.C., Brown, R.W., Sidle, R.C. and Kotuby-Amacher, J. 1995. Effect of mine waste on element speciation in headwater streams. In: Allen, H., Huang, C.P., Bailey, G.W. and Bowers, A.R. (Eds.). Metal Speciation and Contamination of Soil. Lewis Pub. Boca Raton. [4] Aubert, H. and Pinta, M. 1977. Trace Elements in Soils. Elsevier, Amsterdam. [5] Barnhisel, R.I., Powell, J.L., Akin, G.W. and Ebelhar, M.W. 1982. Characteristics and reclamation of “acid sulfate” mine spoils. Pages 225-232. in J.A. Kittrick et al. (Eds.) Acid Sulfate Seathering. SSSA Spec. Publ. 10. SSSA, Madison, WI. [6] Dixon, J.B., Hossner, L.R., Senkayi, A.L. and Egashira, K. 1982. Mineralogical properties of lignite overburden as they relate to mine spoil reclamation. Pages 169-191. in J.A. Kittrick et al. (Eds.). Acid Sulfate Weathering. SSSA Spec. Publ. 10. SSSA, Madison, WI. [7] Ibrahim, S.M. and Goh, T.B. 2004. Changes in macroaggregation and associated characteristics in mine tailings amended with humic substances. Comm. Soil Sci. Plant Anal. 35:1905-1922. [8] Kabala, C. and Singh, B.R. 2001. Fractionation and mobility of copper, lead, and zinc in soil profiles in the vicinity of a copper smelter. J. Environ. Qual. 30:485-492. [9] Merritt, K.A. and Erich, M.S. 2003. Influence of organic matter decomposition on soluble carbon and its copper-binding capacity. J. Environ. Qual. 32:2122-2131. [10] Renault, S., Sailerova, E., and Fedikow, M.A.F. 2000. Phytoremediation and phytomining in Manitoba: preliminary observations from an orientation survey at the Central Manitoba (Au) Minesite (NTS 52L13); in Report of Activities 2000, Manitoba Industry, Trade and Mines, Manitoba Geological Survey, p. 179-188. [11] Salbu, B., Krekling T. and Oughton, D.H. 1998. Characterisation of radioactive particles in the environment. Analyst. 123:843-849.


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[12] SAS Institute. 2000. SAS User’s Guide: Statistics. Version 8. SAS Institute Inc., Cary, N.C., U.S.A. [13] Shuman, L.M. 1985. Fractionation method for soil microelements. Soil Science. 140:11-22. [14] Shuman, L.M. 1991. Chemical forms of micronutrients in soils. Pages 113-144. in J.J. Mortvedt et al. (Eds.) Micronutrients in Agriculture. 2nd ed. SSSA. Madison, WI, U.S.A. [15] Sims, J.T. 1986. Soil pH effects on the distribution and plant availability of manganese, copper and zinc. Soil Sci. Soc. Am. J. 50:367-373. [16] van der Watt, H.v.H., Barnard, R.O., Cronje, I.J., Dekker, J., Croft, G.J.B. and van der Walt, M.M. 1991. Amelioration of subsoil acidity by application of a coal-derived calcium fulvate to the soil surface. Nature. 350:146-148. [17] Whiteley, G.M. and Williams, S. 1993. Effects of treatment of metalliferous mine spoil with lignite derived humic substances on the growth responses of metal tolerant and non metal tolerant cultivars of Agrostis capillaris L. Soil Technol. 6:163-171.


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Treatmentz pHControl 3.32 564 ± 151 a 16 ± 2.6 c 90 ± 1.1 d 207 ± 13 d 618 ± 199 c 321 ± 73HS 4.5 72 ± 36 c 44 ± 6.8 b 171 ± 15 c 237 ± 21 cd 872 ± 240 bc 428 ± 38HS+WSy 5.02 30 ± 0.8 c 63 ± 8.7 a 217 ± 31 a 334 ± 12 b 1185 ± 30 a 446 ± 11WS 3.95 305 ± 6.3 b 45 ± 1.9 b 174 ± 3.9 bc 273 ± 6 cd 863 ± 102 bc 341 ± 62Lime 5.59 7 ± 0.9 c 40 ± 3.8 b 197 ± 1.3 ab 430 ± 33 a 909 ± 179 ab 405 ± 68

ANOVA df Pr > FTrt 4

a-d Mean values followed by the same letter (within columns) are not significantly different.z Treatments: Control, HS = Humic Substances, WS = Wheat Straw, Lime = CaCO3.y For HS+WS, all Cu fractions are means of 2 replications.* significant at p < 0.10** significant at p < 0.05

Copper in each fraction (mg kg-1)F 1 F 4F 3F 2

< .0001** < .0001** < .0001** < .0001** 0.0701* 0.1300

F 5 F 6

Table 1. pH of tailings and mean copper content in each fraction


48

Treatment Lability Factor 1z Lability Factor 2y

Control

HS

HS+WS

WS

Lime

31.92

6.33

4.09

17.50

2.39

36.88

15.72

13.62

26.21

12.31

zLability Factor 1 = [(F1 + F2) / (Total Cu by Sum)] x 100

yLability Factor 2 = [(F1 + F2 + F3) / (Total Cu by Sum)] x 100

Table 2. Copper Lability Factors for each treatment

0%

20%

40%

60%

80%

100%

Control HS HS+WS WS Lime

Treatment

Cop

per

cont

ent

(% o

f Tot

al b

y Σ F

1-F6

) F 6

F 5

F 4

F 3

F 2

F 1

Figure 1. Relative distribution of copper among fractions after 24 weeks.


49

STUDY ON THE EFFECTS OF TRADE VILLAGE WASTE ON ACCUMULATION OF CU, PB, ZN AND CD IN

AGRICULTURAL SOILS OF PHUNG XA VILLAGE, THACH THANH DISTRICT, HA TAY PROVINCE

Nguyen Huu Thanh1, Tran Thi Le Ha1 *, Nguyen Duc Hung1, Tran Duc Hai2

1 Hanoi Agricultural University, Hanoi, Vietnam, 2 Postgraduate student, Hanoi Agricultural University,

Hanoi, Vietnam Abstract Waste materials from Vinh Loc trade village affected greatly the accumulation of Cu, Pb, Zn and Cd in agricultural soil. Seventeen soil samples were taken for analysis. Soil was polluted locally with Zn and Cd. The Zn concentrations in 2 samples exceeded the standard and were in a polluted level. The Cd concentration of one sample exceeded the standard by 22% with regarding the soil as polluted. Among 17 soil samples, the percentage of samples contaminated with different heavy metals was 100% for Cu, 59% for Pb, 35% for Cd, and 24% for Zn. Over 80% of Pb and Cd in soil was extractable by salt solution or diluted acid. This indicates a great potential of the soil to cause Pb and Cd toxicity to environment in this village. Fe and Mn oxides had the stronger affinity to heavy metals than did organic matter and carbonates. The exchangeable form of heavy metals was in the low proportion in soil.

1. INTRODUCTION Metal recycle trade village (metal ware-mechanical trade village) is one of the typical features of rural Vietnam in general and particularly in Ha Tay. These trade villages have participated greatly in the multi-component economy in the doi-moi period [3, 4].

Like other trade villages, metal ware-mechanical trade villages are typical with unprompted development of trade villages without planning, the low technical level with simple works and relying mainly on experience, and lack of basic training.

Small scale and scattered production all over the area constitute numerous small waste sources. It is difficult to gather the waste material and to treat it in a central facility. Evaluation the effects of metal ware-mechanical trade villages on the accumulation of heavy metals in agricultural land is to guarantee the sustainable agriculture.

2. MATERIALS AND METHODS 2.1. Location and sampling Phung Xa commune is situated in Red River delta (Figure 1) with the area of agricultural land is 307.1 ha. Residential area and trade village are intermixed.


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commune.shpaquaculturecemetrycontruction areairrigation landpastureresident arearice fieldunused water

# sampling_site.shproad.shp

# household.shp

N

EW

S

Sampling diagram

Figure 1. Sampling diagram

Seventeen soil samples (Table 1) were sampled at the surface horizon with a depth from 0 to 15 cm and were indicated on the sampling diagram in Figure 1. The nearer to waste sources, the more densely samples were taken..

Sam-ple Location

Distance to sources (m)

Altitude Vegeta-tion

Sam-ple Location

Distance to sources (m)

Altitude Vegeta-tion

1 Dong Man 1500 Medium Rice 9 Dong

Khoai 1250 Medium Rice

2 Dong Sau 500 Medium Rice 10 Dong

Mo 1000 Medium Rice

3 Ben Hiep 500 High Rice 11 Dong Lac 300 Medium Rice

4 Ben Hiep 300 Low Rice 12 Dong Lac 100 Medium Rice

5 Cua Lo 100 Medium Rice 13 Dong Mo 50 Medium Rice

6 Ben Hiep 250 Medium Rice 14 Cong Dinh 50 Medium Rice

7 Dong Nuong 200 Medium Rice 15 Cong

Dinh 50 Medium Coriander

8 Dong Sau 750 Medium Rice 16 Cong

Dinh 50 Medium Rice

17 Cong Dinh 150 Low Rice

Table 1. Main information on soil samples


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One waste water sample and one domestic waste water sample was taken in the trade village at a distance of 10 m from waste sources to determine their properties. 2.2. Analytical procedures The following procedures were used for analyses.

Total Cu, Zn, Pb, and Cd were determined after digestion the samples by HF, HNO3, and HClO4 [6].

Fractionation of heavy metals was done by sequential extraction with following solutions [5]: 1M MgCl2 (pH=7), 1M CH3COONa (pH=5), 0.3M Na2S2O4 , 0.175M sodium citrate, 0.025M citric acid, and mixture of 0.02M HNO3, 30%H2O2, 3.2M CH3COONH4 in 30%HNO3.

Concentrations of Cu, Pb, Zn, and Cd in the digested solution or extracted solution were determined by an atomic absorption spectrophotometer ANA182. Cu, Zn, Pb, and Cd was determination at the wave length of 324.8nm; 307.6nm; 283.3nm; 228.8nm respectively.

3. RESULTS AND DISCUSION 3.1. Soil properties

Soil texture ranged from loamy sand to clay (Table 2). The clay percentage of the surface horizon was mostly greater than 16%. It related to soil properties, fertility, and heavy metal absorption ability of soil.

Almost all samples had a pH higher than 5.6 (medium and light acid). The pH values are in harmony with Eutric Fluvisols of the Red River delta with long duration of cultivation, together with tropical environment. Furthermore, trade village activities might cause a more or less strong change of pH.

Soil was quite rich in organic matter. The total organic carbon concentration (OC) was in a range between 1.47% and 3.15%. Some samples with low altitude or near residential area had OC greater than 2%.

Cation exchange capacity (CEC) varied from 10.2 to 15.4 cmol+/kg soil and was in the average to high level. In the study of the relationship of pH, OC, and clay content with CEC, as shown later, a correlation coefficient between CEC and OC was 0.66. The high OC and CEC are closely related to the existence of heavy metals in soils.


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Sam-ple

Texture (FAO-UNESCO)

pH OC (%)

CEC (meq/100g soil)

Sam-ple

Texture (FAO-UNESCO)

pH OC (%)

CEC (meq/100g soil)

1 Sandy clay 6.18 1.77 10.56 9 Loam 5.32 1.47 10.55 2 Sandy clay 5.78 1.73 11.65 10 Sandy loam 6.08 1.98 10.95 3 Sandy clay 5.21 1.95 10.98 11 Clay loam 6.96 2.91 14.37 4 Sandy clay 6.12 2.80 12.78 12 Sandy clay 5.97 3.15 13.20 5 Sandy clay 6.49 2.03 14.33 13 Sandy loam 4.76 2.52 11.12 6 Clay loam 5.66 1.99 10.16 14 Clay loam 6.31 3.09 15.38 7 Sandy clay 5.97 2.58 12.13 15 Clay loam 6.69 2.25 12.61 8 Loamy

d6.31 1.73 12.97 16 Clay 4.91 2.73 13.39

17 Clay 5.41 2.56 13.08

Table 2. Some physical and chemical characteristics of soils 3.2. Possible factors in the trade village affecting the heavy metal concentration of

soil 3.2.1. Exhausted fumes According to the research of Ministry of National Defense in 2002, the hanging dust concentration in air ranged from 0.26 to 0.31 mg.m-3 while Vietnam standard TCVN 5937-1995 is 0.3 mg.m-3. The Pb was detectable in air. The SO2 concentration ranged from 0.01 to 0.61 mg m-3 (Vietnam standard TCVN 5937-1995 is 0.3 mg m-3) and the NOx concentration was in a range between 0.004 and 2.12 mg m-3 (Vietnam standard TCVN 5937-1995 is 0.1 mg m-3) [2]. Therefore, the exhausted fumes of Vinh Loc trade village were regarded having no affect to the heavy metal accumulation in soil. 3.2.2. Waste water Waste water from rolling and plating steel comes to the drainage system. One waste water sample collected at a site 10 m distant from the drainage system was analyzed.


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Permissible levels in TCVN 5949-1995 Item Unit Value A B C

pH 4.2 6 – 9 5.5 - 9 5 – 9 Suspended solids mg/l 725 50 100 200 Cu mg/l 0.178 0.2 1 5 Zn mg/l 7.92 1 2 5 Pb mg/l 0.65 1 2 2 Cd mg/l 0.02 0.01 0.02 0.5

Table 3. Some properties of waste water collected at trade village in Phung Xa Note: Waste water having values and concentrations: o value in column A can be discharged to domestic waterways, o value in column B can only be discharged to waterways used for hydro-traffic, aquaculture,

and cultivation. o ranged from value in column B to value in column C can only be discharged to defined places. o value column C can not be discharged to any environment. Table 3 showed that the concentrations of Cu, Pb and Cd were lower than or equal to the permissible level of waste water used for aquaculture and cultivation. However, other items of pH, suspended solids and Zn concentration were higher than the permissible level. From the criteria of pH and suspended solids, the waste water was not allowed to be discharged without treatment. Discharge of such waste water to environment without treatment affects soil quality badly.

According to the field observations, waste water was discharged one part to surrounding ponds, lakes and one part directly to agricultural land near the trade village. Because ponds and lake around Vinh Loc trade village are not connected with irrigation channels of the commune, the pollution of heavy metals in Vinh village is difficult to take place in samples 1, 2, 8-11. Heavy metal pollution can only occur in surrounding samples as 3-7, 12, 14-17.

Table 5 showed that the concentrations of Cu, Zn, Pb and Cd in the above samples were considerably higher than those of other samples. This proves that waste materials from trade village raises heavy metal concentrations in the soil. The concentrations of Cu, Pb, Zn and Pb were highest in sample 17. Because this sample site is in a depression with stagnant water coming from the village, heavy metals might have accumulated. Similarly, sample 4 had higher concentrations of heavy metals and was at the contaminated level. This is due to its low altitude compared to samples 3 and 6. 3.2.3. Others Domestic waste rubbish is collected to a designated place and doesn’t considerably affect the accumulation of heavy metals in soil.

Domestic waste water is discarded directly to drainage channels. The results of the domestic waste water analysis are presented in Table 4. Table 4 showed that the concentrations of Zn, Cu, Pb and Cd in the domestic waste water did not exceed the permissible level of the Vietnam standard. Therefore, the accumulation of Zn, Cu, Pb and Cd in agricultural land is not affected by the domestic waste water more than by the


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waste water from the trade village. However, suspension solid and the NH4+-N

concentration in the waste water were very high and even exceeded the standard C level, suggesting that the domestic waste water is not allowed to be discarded to the environment.

Permissible levels in TCVN 5949-1995 Item Unit Value A B C

pH 6.98 6 - 9 5.5 - 9 5 – 9 Suspension solid mg/l 409 20 50 100 Cu mg/l 0.01 0.2 1 5 Zn mg/l 0.087 1 2 5 Pb mg/l 0.33 1 2 2 Cd mg/l 0.008 0.01 0.02 0.5 NH4

+-N mg/l 15.36 0.1 1 10

Table 4. Some characteristics of domestic waste water Furthermore, the accumulation of heavy metals in soil can be influenced by irrigation water, fertilizer, and agricultural chemicals. Irrigation water of Phung Xa is taken from the Red River and the Dong Mo River and it can be considered that it does not affect seriously the heavy metal accumulation in soil. As mentioned above, the main crop in Phung Xa is paddy rice. This crop is planted over 96% of the total area for annual crops. This indicates that the difference in the influence of fertilizers and agricultural chemicals between samples is not great. 3.3. Total concentrations of Cu, Pb, Zn and Cd in soil Most of soil samples were found to have total concentrations of Cu, Pb, Zn and Cd below the permissible level in Vietnam standard TCVN 7209-2002.

The analytical results of heavy metal in agricultural soils are shown in Table 5.

Sample Cu Pb Zn Cd Sample Cu Pb Zn Cd 1 39.68* 10 39.33* 2 43.61* 60.04* 11 43.38* 51.52* 1.45* 3 42.14* 12 47.79* 53.21* 4 47.06* 58.94* 142.49* 1.52* 13 39.05* 50.25* 248.36** 2.44** 5 41.80* 14 42.83* 54.26* 142.00* 1.49* 6 41.66* 15 40.47* 50.33* 157.23* 1.62* 7 41.42* 16 47.08* 57.85* 242.70** 1.52* 8 46.17* 51.39* 17 43.54* 68.24* 155.64* 1.57* 9 39.44* TCVN 7209-2002 50.00 70.00 200.00 2.00

Note: *, contaminated; **, polluted.

Table 5. Total concentrations of some heavy metals in agricultural soils in Phung Xa (unit: mg kg-1).


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To evaluate the pollution level in heavy metals of soil, the total concentrations of heavy metals were divided into the following three categories: - No contamination: heavy metal concentration below 70% of the Vietnam standard. - Contaminated: heavy metal concentration in between 70% and 99% of the

Vietnam standard. - Polluted: heavy metal concentration over the Vietnam standard. 3.3.1. Cu Table 5 showed that the total Cu concentrations ranged from 39.05 to 47.79 mg kg-1 and were lower than the permissible level (50.0 mg kg-1 in TCVN 7209-2002). Although the total Cu concentrations did not exceed the permissible level, every sample was contaminated with Cu (more than 35 mg kg-1). Samples 4, 12 and 16, which were taken from the village border and the waste water receiver from Vinh village, showed the total concentration of Cu nearly reaching the permissible level. Other samples taken far from Vinh village were less affected by trade village’s activities and had the lower Cu concentration. 3.3.2. Pb The total Pb concentrations in soil were from 39.66 to 68.24 mg kg-1 and were below the permissible level (72.0 mg kg-1 in TCVN 7209-2002). However, ten samples (59% of total samples) were at the contaminated level. The total Pb concentration of sample 17 was noted to be close to the permissible level; this sample was taken from the receiver of village’s waste water in a low altitude. Like Cu, the total Pb concentrations of samples 4, 11, 12, 14- 17, which were taken from the area bordering on Vinh village, were higher than those of other samples. 3.3.3. Zn The Zn concentration in soil was mostly affected by the waste from the trade village. The total Zn concentrations of samples 13 and 16 exceeded the Zn permissible level in soil (200.0 mg kg-1 in TCVN 7209-2002). In addition, samples 4, 14, 15 and 17 were in the category of the contaminated level. Production installations and plating pools in Vinh Loc trade village, mainly zinc plating, probably lead to the local pollution and contamination of Zn in agricultural soil. 3.3.4. Cd The total Cd concentrations varied from 1.16 to 2.44 mg kg-1, and sample 13’s Cd concentration is higher than TCVN 7209-2002. The total Cd concentrations of the remaining samples were below the Vietnam standard but still in the high level. Especially those of samples 4, 11, 14-17 were at the contaminated level. These samples located at the border on Vinh village were directly affected from exhausted fumes, dust, and waste water from the village, leading to the high total Cd concentration.


56

3.3.5. Evaluation the heavy metal pollution in agricultural soil The total Cu concentrations of all samples were at the contaminated level (70 to 99% of TCVN 7209-2002). The total Pb concentrations of samples near Vinh Loc trade village were at the contaminated level. Sample 17 had the total Pb concentration close to the Vietnam standard. It is worthwhile to pay attention to that agricultural soil in Phung Xa was locally polluted by Zn and Cd. The total Zn concentrations in sample 13 and 16 exceeded the permissible level and at the polluted level. The total Cd concentration of sample 13 exceeded the permissible level by 22% and polluted the soil. Some other samples around the waste source were in the category of the contaminated level.

Sample 13 was influenced by some production installations along the road and was the most polluted one. This sample was at the polluted level in the total Zn and Cd concentrations and at the contaminated level in the total Cu and Pb concentrations, compared to the Vietnam standard. 3.4. Fractionation of heavy metals in soil 3.4.1. Cu Analytical results of fractionation of Cu are shown in Table 7. The data pointed out that Cu existed mainly in the form of bonding to Fe and Mn oxides and the residual form which is not extractable with salt solution or diluted acid (Cu in crystal network of primary and secondary minerals or other forms). In average, the Cu concentration in the form bonding to Fe and Mn oxides was 15.46 mg kg-1, making up 36.18% of total Cu, and the Cu in the residual form was 23.10 mg kg-1, with occupation of 54.06% of total Cu.

On the other hand, exchangeable Cu, and Cu bonded to carbonates and to organic matter were in a low concentration. It was as low as 1.08 mg kg-1 in average for the exchangeable form, 1.74 mg kg-1 for the bonding-to-carbonates form, and 1.35 mg kg-1 for the bonding-to-organic matter form, making up 2.53%, 4.07%, and 3.16% of total Cu, respectively.

The solubility of Cu decreases in the following order: exchangeable, bonding to carbonate, bonding to Fe oxides, bonding to Mn oxides, bonding to organic matter, and residual forms. In Phung Xa, the concentrations of exchangeable Cu and Cu bonded to carbonates were low. As a result, it is evaluated that Cu is less toxic to crops and environment, even when the total Cu concentration is high.

3.4.2. Pb Analytical results of fractionation of Pb are presented in Table 8. It showed that approximately 50% of total Pb existed in the form of bonding to Fe and Mn oxides. The average concentration of this form was 25.35 mg kg-1. The Pb concentration was lowest in the form of bonding to organic matter (average concentration is 4.49 mg kg-1, making up 8.81% of total Pb) and the residual form (average concentration is 4.77 mg kg-1 or


57

9.36% of total Pb). The concentrations of exchangeable Pb and Pb bonding to carbonates were in an intermediate level with averages of 7.57 and 8.78 mg kg-1, respectively.

Total of the extractable Pb (exchangeable, and bonding to carbonates, Fe and Mn oxides, and organic matter) was 46.19 mg kg-1 in average (nearly reaching the contaminated level of 49 mgkg-1) and made up 90.64% of total Pb. Total of the extractable Pb concentrations of samples 2, 4, 16 and 17 exceeded 49 mg kg-1. It means that the potential Pb toxicity in agricultural soil is high, because Pb easily changes to the available form in soil and affects crops, animals, and human being.

3.4.3. Zn Analytical results of fractionation of Zn are presented in Table 9. Different from Cu, the concentration of extractable Zn increased from the exchangeable form to the bonding-to-organic matter form. In this sequence, the concentration of Zn bonding to carbonates was 18.81 mg kg-1and made up 13.09% of total Zn; exchangeable Zn was 20.10 mg kg-1 or 13.99% of total Zn; Zn bonding to Fe and Mn oxides was 23.84 mg kg-1 or 16.59% of total Zn; and Zn bonding to organic matter was 27.16 mg kg-1 or 18.90% of total Zn. The rest of Zn is kept in minerals’ crystal structure. The average concentration of this residual form was 53.79 mg kg-1 or 37.43% of total Zn. Although the proportion of the extractable forms is not so high, it is necessary to pay a great attention to Zn in Phung Xa due to the high Zn concentration in waste sources. When Zn comes into soil, 63% of total Zn will exist in the extractable forms which easily transform into the available form and affect creatures and environment.


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0

5

10

15

20

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 0

5

10

15

20

25

30

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17

Figure 2. Fractionation of Cu (mg.kg-1) Figure 3. Fractionation of Pb (mg.kg-1)

0

10

20

30

40

50

60

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0.1

0.2

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1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 Figure 3. Fractionation of Zn (mg.kg-1) Figure 3. Fractionation of Cd (mg.kg-1)

Exchange-able

Bonding to carbonates

Bonding to Fe & Mn oxides

Bonding to organic matter

3.4.4. Cd Cd is a very toxic element in soil and can cause toxicity at low concentrations (TCVN 7209-2002 is 2 mg kg-1). Analytical results of fractionation of Cd are presented in Table 10. It showed that the distribution tendency of Cd in soil was similar to that of Pb and that Cd bonding to Fe and Mn oxides occupied the highest proportion in total Cd. The average concentration of Cd bonding to Fe and Mn oxides was 0.41 mg kg-1 or 28.47% of total Cd. The problem is that extractable Cd occupies the very high proportion in total Cd (1.16 mg kg-1 or 80.55% of total Cd). Therefore, the risk for Cd toxicity in the soil is very high, because Cd easily changes to the available form from the extractable forms, when conditions of soil like pH, moisture, and oxidation-reduction potential change naturally or caused by fertilizer application.


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4. CONCLUSIONS AND PROPOSALS

4.1. Concusions From the study on the effects of the trade village waste on the pollution of agricultural soil by heavy metals in Phung Xa, Thach That, Ha Tay, the following conclusions are drawn: 1. The target soil belonged to Eutric Fluvisols with loamy sand to clay texture, quite high

organic matter concentration, and medium to high CEC. 2. Waste materials from Vinh Loc trade village affected greatly the accumulation of Cu,

Zn, Pb and Cd in agricultural soil. Soil was polluted locally with Zn and Cd (samples 13 and 16 were polluted with Zn and sample 13 with Cd). Furthermore, the ratio of the contaminated to total soil samples was 100% for Cu, 59% for Pb, 35% for Cd, and 24% for Zn.

3. Over 80% of Pb and Cd in soil was extractable by salt solution or diluted acid. It made great potentiality for causing toxicity to environment.

4. Fe and Mn oxides showed the stronger affinity to heavy metals than did organic matter and carbonates. Exchangeable heavy metals were of low proportion (less than 16% of total heavy metal).

4.2. Proposals

1. The Phung Xa People Committee is requested to research into the closed production technology, to change machines to modern ones, and to control and treat waste water and waste solid. Industrial waste water from industrial sites or production installations must be treated according to the Vietnam standard before discharge to common drainage canals.

2. Application of lime or phosphate alkali, together with organic fertilizer, to soil in order to transform most of heavy metals into hardly soluble forms.

3. Establishment of the environment management board in commune. 4. Raising of the environment protection awareness by propaganda and education on

environment protection to people.

6. REFERENCES [1] “Committee of Soil Standard Methods for Analyses and Measurements (ed.)” Soil Standard Methods for Analyses and Measurements, Hakuyusha, Tokyo (1986). [2] Hoang Minh Dao. “Current Vietnam Environment”. Industrial Magazine, No. 2, pp. 13, (2004). [3] “Land Use Planning Program in Phung Xa, Thach That, Ha Tay from 2001 to 2010. 2004”. [4] Le Duc, Le Van Khoa. “Effect of trade villages' activities for handicraft copper recycle in Dai Dong commune, Van Lam district, Hung Yen province to local soil environment”, Soil Science Magazine, No 14: 48-52, (2001) [5] Tessier, A., Campbel, P. G. C. and M. Bisson. “Sequential extraction procedure for the speciation of particulate. Analytical Chemistry, No. 51, pp. 844-851, (1979). [6] Vietnam standard TCVN 5949-1995 for water, (1995). [7] Vietnam standard TCVN 7209-2002 for soil, (2002).


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METAL CONTAMINATION IN IRRIGATED AGRICULTURAL LAND: CASE STUDY OF NAIROBI RIVER BASIN, KENYA

P.N. Kamande1*, F.M.G. Tack2

1University of Nairobi, Department of Land Resources Management and Agricultural Technology,

P.O. Box 29053-00625, Nairobi, Kenya. Tel: +254.725.371.498. E-mail: [email protected], 2Ghent University, Laboratory for Analytical Chemistry and Applied Ecochemistry, B-9000 Ghent,

Belgium Poster Extended Abstract

INTRODUCTION Farming in Kenya has increased in reaction to the increased population and the concomitant demand for food. River water is used for irrigation. In Nairobi river basin, industrial effluents and untreated sewage from the Nairobi city council are directly discharged into the rivers. In spite of this, farmers continue to use this water for irrigation. A recent study by UNEP revealed that Ngong/Motoine River water was significantly contaminated with Cr, Cd, Cu, Zn, Pb and Ni [1]. The use of this water for irrigation is likely to cause accumulation of significant amounts of metals in agricultural soils. This may lead to the accumulation of unacceptably high metal concentrations in plants grown on these soils. In this study, metal concentrations and contamination levels in agricultural soils of this area were assessed using different chemical extraction procedures.

MATERIALS AND METHODS This study focussed on the areas irrigated with water from the heavily polluted Ngong River. Four sampling sites were selected in the farmlands of “Mukuru kwa Njenga” slums, within a stretch of about 300 m. Sites 1, 2 and 3 were agricultural sites irrigated with river water while site 4 was a non-irrigated (reference) site. The sites were situated within 5, 17, 15 and 20 meters from the river, respectively. Sites 1, 2 and 3 were at a lower and plain position with respect to river. The reference site was selected on an elevated area that was unlikely to have been flooded by the river; it had similar soil properties as the test sites and was presumably not predisposed to other sources of contamination. At each site, soil was sampled from two points 10 m apart, at 0-20 cm, 20-40 cm and 40-60 cm depth. In this study, it was assumed doubtful whether the farmers were aware of the impending environmental and health risks in using polluted river water for growing crops. To assess their knowledge base about pollution, a brief interview was conducted on farmers, using a simple questionnaire with pointed questions.


61

Different chemical extraction methods were applied to the soils. These include aqua regia extraction for pseudo-total analysis, extraction with 0.5 M HCl for extracting a non lithogenic metal fraction, extractions with EDTA and acetic acid, and extraction with dilute CaCl2 to determine a highly soluble fraction [2, 3, 4, 5 and 2 respectively]. Surface layer samples analysis was triplicated to ascertain the reproducibility of the extraction procedures used. To check analytical accuracy, certified reference materials for certification of total contents in a calcareous soil (CRM 141) and in a light sandy soil (CRM 142 R) were analyzed.

RESULTS AND DISCUSSION Most farmers were aware that polluted water affected crop quality. Their awareness and innovativeness was evidenced in one case where the farmer tried to purify industrial wastewater by allowing it to percolate through the ground and collecting it in a shallow well for irrigation. Though the concentration may have been reduced by sorption to soil, it is not excluded that the water was still contaminated with soluble elements. Farmers defied their knowledge and used the water due to lack of an alternative source of good quality water for irrigation. The pseudo-total metal contents in the irrigated sites were at least five times higher than in the non-irrigated site, with sites 1 and 3 leading. The metal contents (except Ni) exceeded normal contents found in most unpolluted soils in the world and were in the order Zn>Cr>Pb>Cu>Ni>Cd. The major contaminants were Zn (300-1000 mg/kg), Cr (28.5 - 749 mg/kg) and Pb (300 mg/kg). This could possibly be due their extensive use in the industries, car garages and informal industries located near the river. Cd in sites 1 and 3 was slightly elevated compared to normal ranges in soils worldwide (0.07 – 1.1 mg/kg) and were in the range 0.94 to 1.37 mg/kg. Significant amount of metals were removed by 0.5 M HCl, suggesting their association with various more labile fractions in the soil. For sites 1 and 3, median HCl-extractable contents of Cd, Cu, Pb and Zn were between 65 – 80% of the total content. For the non-irrigated site, this percentage was between 7 and 18%. The extractability of Ni was between 13 – 27%, and only 3% for the non-irrigated site. Despite elevated total contents of Cr in the irrigated sites, extractability in HCl remained low in the irrigated soils. EDTA extracted high contents of Zn (200-700 mg/kg), Pb (35-200 mg/kg) and Cu (20-85 mg/kg). In contaminated areas, fractions of the total amount for Cd, Cr and Zn were markedly higher than in the reference soil. High EDTA extractable contents in the contaminated profiles point to the likelihood that plants grown on these soils would accumulate metals in levels above contents in plants growing on uncontaminated sites. Except for Zn (200-500 mg/kg) and Ni (3 mg/kg), the metal contents extracted by 0.11 M acetic acid were below the detection limit of ICP-OES in some profiles. A high percentage of Pb (50% of the samples) and Cu (40% of the samples) were also below the detection limit. Nevertheless, Cd and Cr recorded measurable amounts in the test sites but were below detection in the reference site. These results would suggest that the metals are withheld in rather strong complexes, specifically sorbed or occluded in solid soil phase.


62

The metal content removed with CaCl2 generally fell below the detection limit of the ICP-OES. However, there were detectable levels of Zn (0.30±0.14 to 10.2±0.39 mg/kg) in the surface layers. CaCl2 is a weak extractant, which consists of a neutral salt at an ionic strength in the range of typical soil solutions. Low metal levels would indicate that metals in the soil are not highly soluble and hence not immediately available for uptake by plants.

CONCLUSION The farmers were aware of pollution of Ngong River. However, their knowledge was limited to crop quality and did not encompass the degradation of soil quality and health hazards related to possible accumulation of heavy metals. With appropriate information, farmers may appreciate these hazards

The metal content of the soils revealed that the use of polluted water for irrigation had significantly contributed to contamination of the soils with Cr, Cu and Zn. Although chemical extraction suggested that the mobility of the contaminants in these soils is rather limited, more general surveys and further investigations of metal uptake by crops are needed to evaluate the extent of current hazards.

This issue indicates the need for implementing management strategies in Kenya to prevent and abate soil contamination. To aid in the development of reference values, background concentrations of trace elements in Kenyan soils should be established.

REFERENCES [1] UNEP. Outputs of phase I, Nairobi River Basin Project, (1999). (URL:http://www.unep.org/roa/Nairobi_River/Webpages/pictures.map7.htm) (24th July, 2005). [2] E.Van Ranst, M. Verloo, A. Demeyer, J.M. Pauwels. Manual for the soil chemistry and fertility laboratory. Gent University, Faculty of Agricultural and Applied Biological Sciences, Belgium. Pp. 243, (1999). [3] R.A. Sutherland. Comparison between non-residual Al, Co, Cu, Fe, Mn, Ni, Pb and Zn released by a three step sequential extraction procedure and a dilute hydrochloric acid leach for soil and road deposited sediment. Applied Geochemistry, Volume 17, pp. 353-365, (2002). [4] G. Rauret, J.F. Lopez-Sanchez, A. Sahuquillo, R. Rubio, C. Davidson, A. Ure, Ph. Quevauviller. Improvement of the BCR three step sequential extraction procedure prior to the certification of new sediment and soil reference materials. Journal of Environmental Monitor, Volume 1, pp. 57-61, (1999). [5] Ph. Quevauviller, M. Lachica, E. Barahona, G. Rauret, A. Ure, A. Gomez, H. Mintau. Interlaboratory comparison of EDTA and DPTA procedures prior to certification of extractable trace elements in calcareous soils. The Science of The Total Environment, Volume 178, pp. 127-132, (1996a).


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Sub-theme : MANAGING GROUNDWATER POLLUTION FROM WASTE DISPOSAL SITES

Kristine Walraevens, Marleen Coetsiers, Kristine Martens, Marc Van Camp

Laboratory for Applied Geology and Hydrogeology, Department of Geology and Soil Science, Ghent

University, Ghent, Belgium

INTRODUCTION: THE WASTE PROBLEM

Waste constitutes a problem which increasingly demands the attention of scientists, engineers, policy makers and the general public. This is partly because the volumes of waste are increasing at an alarming rate (due to population growth, but even more to our changing life style), and partly because our understanding and appreciation of the hazards associated with improperly handled wastes are growing [3].

WASTE MANAGEMENT

In Flanders [8], the strategy to deal with waste consists in the following hierarchy: 1. waste prevention 2. waste reuse 3. waste recycling 4. waste incineration 5. waste disposal in controlled dumps. Dumping has thus become the last resort, only to be appealed to for waste which cannot be managed at lower steps of this ladder. This is in sharp contrast with the past, when the usual fate of waste was uncontrolled dumping. The former practice has resulted in wide-spread pollution of soil and groundwater. Industrial dump sites have often caused major cases of pollution, but mostly restricted to a select group of chemicals. Yet, municipal household-refuse landfill sites contribute to pollution of groundwater to a large extent [4], by a wide variety of chemicals.

GROUNDWATER POLLUTION FROM WASTE DISPOSAL Rainwater percolating through the waste material in open dumps dissolves soluble matter in the waste, becoming more concentrated on its way down. This leachate may leave the dump site and contaminate the surrounding soil and groundwater, depending on different factors [3]: - climatic factors (dry versus humid) - depth to the water table and thickness of the unsaturated zone


64

- the characteristics of the rocks: hydraulic conductivity, potential for adsorption or degradation of contaminants

- type and composition of the waste. Interaction of the leachate with the solid soil results mainly in the in-situ pollution of the affected soil, whereas groundwater is a mobile medium, transporting and spreading the contaminants. Leachate plumes may show lengths of several kilometers [1].

MANAGING GROUNDWATER POLLUTION FROM WASTE DISPOSAL

Future waste disposal should be managed in an appropriate way, preventing leachate to be produced and to leave the dump. Current practices implemented to reach this objective will be discussed. Existing cases of groundwater pollution resulting from waste disposal must be handled carefully, in order to control the risks and, if possible, restore the area to its original state. Different steps are required: 1. characterization of the groundwater reservoir 2. characterization and mapping of the pollution plume; geophysical measurements may be very helpful [5, 7] 3. simulation of the groundwater pollution [2, 6] 4. conception and simulation of remediation schemes [2, 6] 5. actual remediation 6. monitoring and follow-up. In very specific cases, the actual remediation step may be replaced by natural attenuation [4], but then the monitoring and follow-up require double attention.

Case-studies of groundwater pollution from dump sites will be discussed.

REFERENCES

[1] T.H. Christensen, P. Kjeldsen, H.-J. Albrechtsen, G. Heron, P.H. Nielsen, P.L. Bjerg, P.E. Holm. “Biogeochemistry of landfill leachate plumes.” Appl. Geochem., 16(7-8), pp. 659-718, (2001). [2] K. Martens, K. Walraevens. “Pollution at a dry cleaning site: Modelling of the movement of the pollution in groundwater by VOCl with RBCA Tier 2 Analyzer.” ConSoil 2003, Gent. Eight International FZK/TNO Conference on Contaminated Soil. Conference Proceedings. Theme B: Identification of Risks, pp. 1197-1205, (2003). [3] B.W. Murck, B.J. Skinner, S.C. Porter. “Environmental Geology”. John Wiley & Sons, New York (ISBN 0-471-30356-9). 535 p., (1996). [4] B.M. Van Breukelen. “Natural attenuation of landfill leachate: a combined biogeochemical process analysis and microbial ecology approach.” PhD Dissertation, Free University of Amsterdam (ISBN 90-9016928-8), 140p., (2003). [5] K. Walraevens, E. Beeuwsaert, W. De Breuck. “Geophysical methods for prospecting industrial pollution: A case-study.” European Journal of Environmental and Engineering Geophysics, 2, pp. 95-108, (1997). [6] K. Walraevens, E. Beeuwsaert, M. Van Camp, W. De Breuck. “Groundwater pollution by industrial waste disposal: geophysical and hydrogeological case-study.” In: MARINOS, P.G., KOUKIS, G.C.,


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TSIAMBAOS, G.C. & STOURNARAS, G.C. (eds.). Engineering Geology and the Environment. pp. 2243-2248. Rotterdam: A.A. BALKEMA Publishers (ISBN 90-5410-879-7), (1997). [7] K. Walraevens, M. Coetsiers, K. Martens. “Large-scale mapping of soil and groundwater pollution to quantify pollution spreading.” In: LENS, P., GROTENHUIS, T., MALINA, G. & TABAK, H. (eds.). Soil and Sediment Remediation. Mechanisms, technologies and applications. pp. 37-48. Integrated Environmental Technology Series. IWA Publishing, London (ISBN 1-84339-100-7), (2005). [8] http://www.ovam.be (in Dutch)


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CONTAMINATION OF THE MARIMBA RIVER TRIBUTARY, ZIMBABWE, WITH CU, PB, ZN AND P BY INDUSTRIAL

EFFLUENT AND SEWER LINE DISCHARGE.

Bangira, C*.Wuta, M., Dube, H.M and Chipatiso, L.

*University of Zimbabwe, Department of Soil Science & Agricultural Engineering, P.O. Box MP167, Mount Pleasant, Harare, Zimbabwe

Tel: +263 4 303211/+263 4 307304 Fax: +263 4 307304

Correspondence: Email: [email protected] Abstract The rate of industrialization in developing countries is often mismatched with the provision of solid and liquid waste disposal and other requisite infrastructural facilities. Consequently, facilities such as sewer lines and sewage treatment works become overloaded resulting in frequent pipe bursts and inadequate sewage treatment. A study was conducted in Marimba River tributary to assess the contribution of industrial effluent and sewer line discharge on the total concentration of Cu, Pb, Zn and P in sediment and water. Sediment and water samples were collected at specific points in the tributary during the dry season. Heavy metals and P in sediments and water were determined by spectroscopic and colorimetric methods respectively. Electrical conductivity and pH were determined using their respective meters. The results showed elevated levels of Cu and Zn in sediments immediately after industrial effluent discharge points. However, concentrations of Cu, Zn and Pb in water were all below 0.5 mgl-1. The pH ranged from 7.3 - 8.0 and 6.2 – 7.4 in water and sediment respectively. Lower concentrations of heavy metals in water were attributed to the low insolubility of these metals due to high pH. Significantly higher concentrations of Cu and Zn in sediments immediately after the industries were due to industrial effluent discharge that was not adequately pre-treated. Phosphates concentration in water exceeded the Standards Association of Zimbabwe (1999) limit of 0.5mgl-1. It was concluded that industrial effluent discharge and burst or leaking sewer lines were contributing to the pollution of Manyame River tributary which feeds into Harare’s main drinking water source. KEY WORDS: Heavy metals, P, industrial effluent, water, sediment, Marimba River

INTRODUCTION In recent years, developing countries have been experiencing rapid industrial growth and urbanisation. Such processes bring with it a plethora of social and economic challenges. The provision of accommodation to the urban population and the subsequent solid and liquid waste disposal facilities are probably some of the major problems faced by cities in most developing countries. In Harare, Zimbabwe’s capital city, a phenomenal population increase from 310 360 people in 1961, 658 400 people in 1982 to 1 896134 in 2002 (CSO, 1982; 2002) occurred following the end of the liberation war mainly due to a search for employment and partly due to high birth rates. High demand for accommodation was then created. The Municipality responded to the housing shortage by opening up more residential areas adjacent to the existing ones as in-fill type or on agricultural land. People already allocated houses started extending them or constructing


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backyard cottages. On one hand small-scale industrial parks built in these areas have their liquid waste disposed of in streams. Although the Municipality sanctioned these developments, most of them took place illegally. These developments took place without or with little upgrading of the sewer reticulation system. Consequently, facilities such as sewer lines and sewage treatment facilities became overloaded resulting in frequent pipe bursts and inadequate sewage and industrial effluent treatment. Old suburbs such as Mabelreign, Greencroft and Bluffhill that were built in the late 1940s and 1950s for smaller population have been severely affected by the overloading of the sewer system resulting from the increased population and aging sewer reticulation system. Due to non-prohibitive fines and the incapacity of the Municipality to regularly monitor effluent discharge into water bodies, most industries directly discharge their untreated effluent into streams. This study aimed at assessing the contribution of industrial effluent and sewer line discharge on the total concentration of Cu, Pb, Zn and P in sediment and water in Marimba River tributary. Materials and Methods The study area is located about 10 km the north west of Harare City and covers the Bloomingdale, Bluffhill, Greencroft and Mabelreign residential areas. The Marimba tributary passes through the medium and low density residential areas of Bloomingdale, Bluffhill, Cotswold Hills and Mabelreign in Harare (Figure 1). In between the tributaries is an industrial zone. The main industries in this zone include vehicle servicing and repairs, panel beating and spray painting, fuel stations, paint manufacturing, road construction and welding. Effluent from these industries is directly discharged into the northern sub-tributary. The southern sub-tributary receives mainly domestic effluent from the leaking or burst sewer lines and manholes located along the course of the sewer line. Manholes serve as relief ponds in case of blockages. Both streams are lined with Typha latifolia aquatic plants from the discharge points. The tributaries later converge to form one major stream that drains into Marimba River that in turn drains into Lake


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N

Built up area.

Main Road.

LEGEND

Industrial area.

HARARE

Zimbabwe

AngolaZambia

Namibia

South Africa

Tanzania

Democratic Republic of Congo

Mozambiq

ue

SOUTHERN AFRICA

Botswana

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300 0 300 600 Meters

Marbelreign

Bluff Hill

Tynwald

Greencroft

12

345

6

7

8 9 10

1112

HARAREHARARE

#

Marimba

500 0 500 1000 Meters

Figure 1. Location map of the study area.

Chivero. Lake Chivero is the main source of drinking water for the City of Harare, Norton and Chitungwiza.

The residential areas of Mabelreign, Greencroft and Bluffhill, from where most of the sewerage comes from, were constructed in the post World War II era between 1949 and early 1970s to accommodate an increased number of immigrants from Europe (Zinyama, 1993). As such, these areas were for the more privileged and relatively small population (Colquhoun, 1993). Their sizes range from 1000-2000m2

and were thus stipulated to have reticulated sewerage system by the urban by-laws. Sampling Sediment River sediments were collected from 12 sites using augers to a depth of 0.1 (refer to figure 1). Site 1, 11 and 12 were control sites. At each site three composite sediment samples were taken. One sample was composed of 9 sub-samples randomly selected from the streambed. The three samples from each site were placed in polythene bags and taken to the laboratory for air-drying before chemical analyses.


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Water Water samples were collected using 1 L plastic bottles previously soaked in 10% HNO3 to remove any traces of heavy metals. Prior to sampling the bottles were rinsed three times with de-ionised water and then stream water. Sampling was done with the bottle mouth facing the opposite direction to water flow. A total of three composite water samples resulting from the combination of 9 sub-samples were collected from three randomly selected positions in the stream. Immediately after sampling, the bottles were tightly closed, put in cooler boxes and taken to the laboratory for analyses. Laboratory Analyses The electrical conductivity and pH of water samples were determined immediately on arrival to the laboratory using an Orion pH and electrical conductivity meter respectively. About 0.5 L of the water samples were then acidified with 5 drops of concentrated nitric acid, filtered with Whatman No. 42 filter paper and the concentration of Cu, Pb and Zn in the filtrate was determined using an atomic absorption spectrophotometer. The other 0.5 L water was analysed for P. Total P in water was measured colorimetrically [Murphy and Riley, 1962] after digestion with the aqua-regia. The electrical conductivity was measured in a suspension of 1:5 sediment : water. The pH was measured in a 1:5 sediment: 0.01 M CaCl2 suspension. Total heavy metals in sediments were extracted with aqua-regia and then determined using an atomic absorption spectrophotometer.

RESULTS AND DISCUSSION Water Water pH at the sites affected by contamination was lower than the control sites (sites 1, 11 and 12). Lower pH is attributed to the discharge of domestic and industrial effluent into the stream. Moreover, there was a marked increase in the electrical conductivity of water at the industrial sites (sites 4, 5 and 6). Due to high pH of water that precipitates heavy metals, the concentration of Cu, Pb and Zn in water at all the sites were below 0.5 mg l-1 and thus comply with the Standards Association of Zimbabwe [1999] regulations for wastewater.

The P concentration in water (Figure 1) reveals elevated levels of this element compared to most natural surface water P concentration of 0.005-0.020 mg l-1 P [Chapman, 1998]. Highest values were also recorded at the industrial sites. Although the P concentration at other sites were lower than the recommended value of 0.5mg l-1 [Standards Association of Zimbabwe, 1999] there was a significant difference between the control sites (sites 1, 11 and 12) with the other sites that were affected by domestic (sewer line discharge) and industrial effluent. Downstream Marimba River total P values between 1.67-5.42 ppm have been recorded in water [Hranova and Manjonjo, 2006]. Detergents and soaps, which are commonly used for both domestic and industrial purposes, contain at least one functional group such as sulphate, sulphonate or phosphate groups [Kirsner and Froelich, 1998] and are therefore likely sources of phosphates in


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water in this study area. High P concentration in water may also be contributing to the growth of aquatic plant, Typha latifolia that starts growing from areas with burst or leaking sewer manhole and pipe. Boyd and Hess [1970] found that standing crops of Typha latifolia were positively correlated with concentrations of dilute acid soluble P (1.0-116 ppm) in hydrosoils and dissolved P (0.02-0.32 ppm) in the waters.

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

1 2 3 4 5 6 7 8 9 10 11 12

Sampling site

P co

ncen

tratio

n (m

g l

-1)

Figure 2. P concentration in water at different sites. Sediments Total P concentration in sediments was significantly higher (Figure 3) at sites that received mainly domestic effluent from the leaking manhole of sewer lines or burst pipes. This trend implicates detergents and soaps that are widely used for domestic purposes as the main sources of P enrichment in the stream. Lower levels of P at site 6 were attributed to the low sediment accumulation due to the erosive power of the water from all the industries. Earlier studies by Thornton and Nduku [1982] in some Zimbabwean lakes showed non-eutrophic lakes to have sediment P concentration of about 0.3ppm whilst eutrophic lakes had P concentration greater than 1.0 ppm. The growth of Typha latifolia in sections of the stream that were affected by effluent could therefore be a result of P enrichment.

The pH of sediments (Table 1) was in the slightly alkaline range. A significant increase in electrical conductivity, however, occurred at the industrial sites and was attributed to the direct discharge of soluble salts from industrial chemicals and detergents that became associated with sediment particles. Heavy metals (Cu and Zn) in sediments showed increased concentration up to 170 mg kg-1 (Figure 3) compared to the control sites with less than 60 mg kg-1. Sediments are good nutrient sinks in rivers. High levels of heavy metals in sediments were attributed to the discharge of effluent into the stream


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by the electrical, welding, paint and vehicle services industries located along this part of the stream. Industrial effluent and sludge are known to contain heavy metals [Alloway, 1990; McBride, 1995; Nyamangara and Mzezewa, 1999; Zaranyika et al., 1993] The concentration of the heavy metals in sediments in a stream that received domestic effluent was also less than 50mg kg-1 indicating no enrichment of heavy metals. Pb concentration in sediments at all the sites was below 70mg kg-1 and there was no particular trend. The use of heavy metals for domestic use is rather limited hence lower levels in the sediments. No standard values for heavy metals in sediments exist in Zimbabwe.

0

50

100

150

200

250

300

350

400

450

500

1 2 3 4 5 6 7 8 9 10 11 12Sampling site

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g kg

-1)

Figure 3. Mean total P concentration in sediments at different sites.


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0

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160

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1 2 3 4 5 6 7 8 9 10 11 12

Sampling site

Met

al c

once

ntra

tion

(mg

kg-1

) Cu Pb Zn

Figure 4. Mean heavy metal concentration in sediment at different sites. Conclusion The direct discharge of industrial effluent into the Marimba tributary contributed to the enrichment of Cu, P and Zn in sediments. Sewer line leaks and bursts as a result of increased population and the discharge of industrial effluent are also enriching the water and sediments with P and are polluting Marimba River tributary that feeds into Harare’s main drinking water source. Higher P levels in water and sediments may also have contributed to the growth of Typha latifolia in the tributary. Regular monitoring of industrial effluent and the upgrading of the sewer reticulation system are recommended.

ACKNOWLEDGEMENTS This research was funded by the University of Zimbabwe Research Board fund (3YSL10/0004) for which the authors are very grateful.

REFERENCE B.J. Alloway. Heavy Metals in Soils. Wiley, New York. (1990) C.E. Boyd and L.W. Hess. Factors Influencing shoot production and mineral nutrient levels in Typha latifolia. Ecology 51 (2): (1970). Central Statistics Office. 2002 Census Report. Government of Zimbabwe. (2002)


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D. Chapman. Water Quality Assessment: A Guide to use of Biota, Sediments and Water in Environmental Monitoring (1998). 2nd Ed, London. SPON Press S. Colquhoun. Present problems facing the harare city council. IN: Zinyama, L., Tevera, D. and Cumming, S.(eds) 1993. Harare: the growth and problems of the city. University of zimbabwe publishers. R. Hranova and M. Manjonjo. Sewage sludge disposal on land-impacts on surface water quality (2006). In: r. Hranova (ed.) Diffuse pollution of water resources: pricinciples and case studies in the southern africa region.p272. Taylor & francis group plc, london. R.S. Kirsner and C.W. Froelich. Soaps and Detergents: Understanding their composition and effect. Ostomy Wound Management 44 (4): 393-397. (1998). M.B. mcbride. Toxic metal accumulation from agricultural use of sludge: are USEPA regulations protective? Journal of Environmental Quality 24: 5-18. (1995). J. Murphy and J. P. Riley. A modified single solution method for determination of phosphate in natural waters. Anal. Chim.Acta 27: 31-36. (1962) Cited in: Page, A.L., Miller, R.H., and Keeney, D.R.(eds). 1982. Methods of Soil Analysis Part 2. Chemical and Microbiological Properties. Agronomy Series 9. America Society of Agronomy, Inc. Madison, USA. J. Nyamangara and J. Mzezewa . The effect of long-term sludge application on Zn, Cu, Ni and Pb levels in a clay loam soil under pasture grass in Zimbabwe. Agric. Ecosy. Environ. 73: 199-204 (1999) Standards Association of Zimbabwe. Zimbabwe standard specification for waste water. Zimbabwe Standard No.558:1999. (1999). Thornton, J.A. and Nduku, W.K.K. Sediment Chemistry. In: Thornton, J.A. and Nduku, W.K.K. (eds), Lake Macllwaine-the Eutrophication and Recovery of a Tropical African Man-made Lake. 1982. P59-65, London: Dr W. Junk Publishers M.F. Zaranyika, L. Mtetwa, S. Zvomuya, G. Gongoraand and A.S Mathuthu,. The effect of industrial effluent and leachate from landfills on the levels of selected trace heavy metals in the waters of upper and middle Mukuvisi river in Harare, Zimbabwe. Bull. Chem. Soc. Ethiopia 7 (1) :1-10 (1993) Zinyama, L. The evolution of the spatial structure of greater Harare: 1890-1990. (1993). IN: Zinyama, L., Tevera, D. and Cumming, S.(Eds) 1993. Harare: the growth and problems of the city. University of Zimbabwe publishers.


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Site Number 1 2 3 4 5 6 7 8 9 10 11 12 WATER pH 7.9±0.03 7.8±0.03 NSa 7.5±0.01 7.7±0.0 7.7±0.07 7.7±0.08 7.3±0.01 7.6±0.07 7.4±0.02 7.5±0.01 8.0±0.05 Conductivity (µS cm-1) 521±7 542±10 NS 930±74 929±60 887±60 731±27 491.0±22 446±44 507±28 408±25 287±12 Cu (mgl-1) 0.1 0.2 NS 0.2 0.3 0.3 0.3 0.3 0.3 0.2 0.3 0.2 Pb (mgl-1) 0.2 0.2 NS 0.2 0.3 0.2 0.3 0.3 0.3 0.4 0.4 0.3 Zn (mgl-1) 0.1 0.1 NS 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 SEDIMENT pH (CaCl2) 6.7±0.02 6.7±0.03 6.8±0.02 7.3±0.01 6.8±0.05 7.0±0.02 6.2±0.03 7.2 ±0.02 7.4 ±0.03 6.7 ±0.02 6.7 ±0.02 6.6±0.02 Conductivity (µScm-1) 451±10 1631±21 2000±51 2116±63 193±15 467±27 375±197 193±7. 1464±34 1630±40 342±9. 320±12 Nsa- Not sampled because stream section dry

Table 1. Mean values (± standard error) of selected parameters for water and sediment in Marimba tributary


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CONTROLLING PHOSPHORUS (P) MOBILITY IN POORLY P SORBING SOILS: DRINKING-WATER TREATMENT

RESIDUALS (WTR) TO THE RESCUE

S. Agyin-Birikorang1*, G.A. O’Connor1 and L.W. Jacobs2

1 Soil and Water Science Department, University of Florida, Gainesville, FL 32611, USA, 2 Department of Crop Science, Michigan State University, East Lansing, MI 48824, USA

* Corresponding author (E-mail: [email protected]; Tel.: 1-352-846-5770)

Abstract Surface runoff of nutrients nitrogen (N) and phosphorus (P) from manured agricultural land can be an important source of water quality impairment in surface waters worldwide. Excessive concentration of soluble P is the most common source of eutrophication in fresh waters. Addition of amendments to reduce P solubility is one of the most effective in-situ technologies for remediating P contaminated soils. Abundant evidence indicates that drinking water treatment residuals (WTR) are effective amendments. However, little information is available concerning the longevity of WTR immobilization. A modified isotopic (32P) dilution technique was used to monitor the lability of P in a one-time WTR (114 Mg dry WTR ha-1) treated, P-impacted plots in two sites in Western Michigan (USA) for seven–and-a-half (7.5) years. At the end of the monitoring period, we conducted a runoff study, using rainfall simulation technique on the soils from both sites to assess the long-term effectiveness of WTR in reducing dissolved P in runoff and leachate from the soils. Labile P concentrations of the WTR-amended soil samples were reduced to ≤ 46 % of the soil samples without WTR amendment, 6 months after WTR amendment and the reduction persisted for 7.5 years. Application with WTR reduced the flow-weighted soluble reactive P concentrations in runoff and leachate in soils from both sites by ~ 60 % and dissolved organic P by ~ 45%. Overall, WTR amendment decreased flow-weighted dissolved P concentrations by ~ 55 %. We concluded that WTR is an effective amendment to control labile P in P-impacted soils and that the WTR immobilized P will remain fixed for a long time. Thus amendment of P-impacted soils with WTR can help minimize eutrophication in fresh surface waters.

INTRODUCTION

Clean water is a crucial resource for drinking, irrigation, industry, transportation, recreation, fishing, hunting, support of biodiversity, and sheer esthetic enjoyment. Eutrophication caused by excessive inputs of phosphorus (P) and nitrogen (N) is the most common impairment of surface waters worldwide. Eutrophication has many negative effects on aquatic ecosystems. Perhaps the most obvious consequence is the increased growth of algae and aquatic weeds that interfere with use of the water for fisheries, recreation, industry, agriculture, and drinking.

Application of animal manure in amounts that exceed agronomic P rates often results in increased loss of P from agricultural land in surface runoff and potential eutrophication of surface waters [21]. Reversal of eutrophication requires the reduction of P and N inputs into surface waters. Current strategies used to reduce P transport to surface water include conservation tillage, crop residue management, cover crops, buffer strips, contour tillage, runoff water impoundment, and terracing. These strategies are effective in controlling particulate P but not dissolved P in runoff [21]. Drinking water treatment residuals (WTR) that contain Al or Fe oxides can be beneficially used as a best management practice (BMP) to protect surface water quality by removing dissolved P from agricultural runoff water. Thus, excessive soluble P concentrations can be controlled through the additions of environmentally-benign and cost-effective P-sorbing amendments, such as WTRs [5].


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Drinking water treatment residuals are by-products of the drinking water treatment process and are physical mixtures of Al or Fe hydr(oxides) that originate from flocculant (Al, or Fe salts) additions made during the drinking water treatment [17]. Drinking water treatment residuals are usually disposed of in landfills, and can be obtained at minimal or no cost from drinking-water treatment facilities. Studies have shown that incorporating WTRs into soil reduces excessive soluble P resulting from manure application [3]. Similar studies showed that phosphorus solubility in biosolids was reduced by co-application with WTRs [5]. O'Connor et al. [17] showed that P movement from P-enriched soils to freshwater supplies was reduced when the soils were treated with WTRs. The primary purpose of their study was to investigate the ability of three WTRs produced in Florida to reduce soluble P levels in Florida soils amended with fertilizer, manure, and biosolids-P sources. Gallimore et al. [7] utilized WTRs as a buffer strip (44.8 Mg WTR ha-1) applied to a portion of a pasture treated with poultry litter. Surface runoff P was reduced by WTR from an average of 15 to 8.1 mg L-1. The authors [7] concluded that the most effective surface application of WTR was as a buffer strip.

Data from various studies suggest that WTRs could be effective amendments to improve P retention in poorly P-sorbing soils. Short-term laboratory, greenhouse, and rainfall simulation studies have demonstrated WTR efficacy in reducing soluble P concentrations in runoff [3], and leaching [5] from areas amended with animal wastes. The long-term stability of sorbed P by WTRs has only been qualitatively inferred from lab experiments [12]. Time constraints associated with conducting long-term field experiments are the major drawbacks in evaluating the long-term fate of sorbed P in WTR-amended soils, and few researchers have attempted such studies. The objective of this study was to assess the long-term effectiveness of alum WTR (Al-WTR) in reducing dissolved P in runoff and leachate from field soils with long histories of poultry manure applications.

MATERIALS AND METHODS Field layout and amendments application Two field sites (sites 1 and 2) located in Western Michigan were selected in 1998 for evaluation of WTR effects on P extractability in soils having “very high” soil test P concentrations. Both soils have a long-term (> 10 yr) history of heavy chicken manure applications (actual application rates unknown). Soil at site 1 was a Granby fine sandy loam (sandy, mixed, mesic Typic Endoaquolls) with Bray P1 test levels (265 mg P kg-1). Soil at the second site was Granby loamy sand (sandy, mixed, mesic Typic Endoaquolls) with Bray P1 test values of 655 mg P kg-1.

A randomized, complete block design was established at each site with four replications per treatment and a plot size of 14 m x 30 m. The WTR used in this study was removed from lagoon storage, and stockpiled for drying. The dried Al-WTR was applied (114 dry Mg ha-1) to plots using a Knight ProTwin Slinger, model 8030 V-box spreader, by making three passes on each side of the plot, or three round trips. All plots, including the untreated controls, were disked (~30 cm) twice following WTR application. Additionally, site 1 was chisel-plowed and field cultivated prior to planting on May 5, 1998. Site 2 was moldboard plowed before planting on May 4, 1998. Subsequently, both sites were rototilled in April/May, 2000 prior to planting to promote more thorough mixing of WTR. Field corn (Zea mays L.) was planted each year at both sites. Herbicides and insecticides for weed and pest control typically used by cooperating farmers were applied at planting. Fertilizer nitrogen and potash were applied


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as needed. The study continued for more than 7 years, but the WTR amendment was applied only in 1998. Soil sampling Surface soils of control and WTR-amended plots from both of the Michigan field study sites were first sampled in spring 1998 (time zero) by compositing 20 cores (2.54 cm diameter) from the top 30 cm depth of each plot. Additional soil surface samples were similarly collected each fall in 1998, 1999, 2000, 2001, 2002, 2003, 2004 and 2005 for analyses to monitor changes in labile pools of P following the WTR application. At the end of the monitoring period (Fall 2005), surface soils of the control and the WTR amended plots from both sites were sampled (~ 20 kg) from the top 30 cm depth of each plot to undertake the rainfall simulation study. Soil and WTR characterization Samples were air-dried and passed through a 2 mm sieve before analyses. Particle size distribution was determined by the pipette method [2]. The pH was determined in a 1:2 WTR to 0.01 M CaCI2 solution using a glass electrode [13]. Electrical conductivity (EC) was determined in a 1:2 WTR to deionized water solution [18]. Soluble reactive P of WTRs was measured in a 0.01 M KCl solution at a 1: 10 solid: solution ratio, after 40 d reaction. Total C and N were determined by combustion at 1010 C using a Carlo Erba NA-1500 CNS analyzer. Total recoverable P, Fe, and Al were determined by ICP-AES (Perkin-Elmer Plasma 3200) following digestion according to the EPA Method 3050A [23]. Oxalate extractable P, Fe, and Al were determined by the ICP after extraction at a 1: 60 solid: solution ratio, following the procedures of [20]. Oxalate-extractable Fe and Al represents noncrystalline and organically complexed Fe and Al present in the solid [20]. Determination of labile pools of P Two grams of each soil sample was placed in centrifuge tubes to which 20 mL of deionized water was added, giving a solid-to-solution ratio of 1:10. Two drops of toluene were added to each suspension and equilibrated for 4 days in an end-over-end shaker. The samples were then spiked with 50 µL of a solution containing 32P (5 MBq/mL) and returned to the shaker to equilibrate for 3 days. At the end of the equilibration period, samples were centrifuged at 4200 g for 10 min and filtered through 0.2-µm filters (Sartorius). Activities of radioactive P in the filtrates were assessed using liquid scintillation counter (Beckman LS 5801). All analyses were performed in triplicate and included blanks. The total activity introduced in each sample was determined by analyzing spiked solutions, without soil, in parallel with the soil suspensions as suggested by [10]. The labile pools (E) of P were determined as reported in [8].

E = (Csol/C†sol) R * (V/W) -----------------------[1]

where Csol is the concentration of water extractable P in solution (µg/mL), C†

sol is the activity of radioisotope remaining in solution after equilibration (Bq/mL), R is the total activity of radioisotope added to each sample (Bq/mL), and V/W is the ratio of solution to sample, which in this case was 10 mL/g.


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Rainfall simulation experiment The rainfall simulation was carried out as prescribed in the U.S. National Phosphorus Research Project indoor runoff box protocol [16]. However, the design of wooden runoff boxes (100 cm long, 20 cm wide, and 7.5 cm deep) was modified to quantify leaching of P in addition to runoff P by adding a second box under the first in a double-decker design. This design allows collection of runoff and leachate simultaneously. The boxes were packed with 5 cm of soils to a bulk density of 1.4 g cm-3. Soils collected from the Michigan study sites (7.5 y after WTR amendment) were pre-wetted to near saturation to control for antecedent moisture and to promote runoff in subsequent rainfall simulation. Rainfall simulations were conducted three times, at one-day intervals between rainfall events. Boxes were sloped at 3 % and rainfall was delivered at 7.1 cm hr-1 from a height of 3 m above the boxes. For each rainfall event, the 30 min of runoff, and leachate generated during the entire rainfall was collected from each box and the volumes recorded. Subsamples of the runoff were immediately filtered (0.45 µm) for analysis. A representative well-mixed sample of the unfiltered runoff (~ 250 mL) was also taken from each replicate for analysis.

Leachate and runoff pH and EC was determined on each sample. Soluble reactive P (SRP) was determined on the filtered runoff and the leachate samples colorimetrically [14]. Total dissolved phosphorus (TDP) was measured on the filtered runoff and the leachate samples after digesting 10 mL of the samples with 0.5 mL 11 N H2S04 and 0.15g of potassium persulfate in an autoclave for 1 hr [4]. Total P in the unfiltered runoff sample was determined by digesting 5 mL of the samples with 1 mL of 11 N H2S04 and 0.3g of potassium persulfate on the digestion block and then diluted by adding 10 ml of water [4]. All digested samples were analyzed for P colorimetrically [14]. The iron-oxide impregnated paper strip method [15] was used to estimate bioavailable P in runoff waters.

Particulate phosphorus (PP) was calculated by subtracting TDP from the TP of each sample. Dissolved organic P (DOP) was assumed to be the difference between SRP and TDP. Flow-weighted P concentrations were determined for the runoff and the leachate by summing the product of the P concentrations and volumes for the three runs (P load) and dividing the P load by the total volume of the runs. The mass of runoff and leachate P losses (mg) were calculated as the product of flow-weighted concentrations (mg L-1) and the runoff and leachate volume (L) respectively. Total P losses were determined by summing the masses of runoff and the leachate P loss. Statistical analyses Differences among treatments were statistically analyzed as a factorial experiment with a randomized complete block design (RCBD), using the general linear model (GLM) of the SAS software [19] The means of the various treatments were separated using a single degree of freedom orthogonal contrast procedure.

The data collected from the rainfall simulation study showed great variation about the means with coefficient of variation > 60 %. This prompted us to test for normal distribution of the data using the Kolmogorov-Smirnov Procedure and the normal probability plots of the Statistical Analysis System [19]. The P concentration data were not normally distributed, so typical analysis of variance could not be used. Instead, the NPAR1WAY procedure of the SAS software with the Kruskal-Wallis test was used. The NPARIWAY procedure is a nonparametric procedure that tests whether the distribution of a variable has the same location parameter across different groups. The Kruskal-Wallis procedure tests the null hypothesis that the groups are not different from each other by testing whether the rank sums


79

are different based on a Chi-square distribution [9]. This is a powerful and robust test that is insensitive to variation among data and the presence of outliers [9].

RESULTS AND DISCUSSION Chemical properties of the WTR and soils used The WTR and soils were analyzed for selected chemical properties (Table 1). The pH of WTR was near neutral (7.4), and may have resulted from pH adjustment with alkaline materials (i.e., calcium hydroxide) during drinking water treatment.

WTR Site 1 Site 2

pH 7.4 ± 0.1 6.4 ± 0.2 6.8 ± 0.2

Sand nd† 60 ± 3.0 % 76 ± 4.5 %

Silt nd 28 ± 2.2 % 16 ± 2.0 %

Clay nd 12 ± 1.4 % 8 ± 0.9 %

Total C 34,000 ± 200

nd nd

KCl-P 4.0 ± 0.1 22.1 ± 2.3 58.1 ± 5.1

Bray P1 nd 265 ± 45 655 ± 90

Oxalate P 570 ± 96 790 ± 7.5 970 ± 8.3

Oxalate Al 29700 ± 3603

2400 ± 21.3 710 ± 8.5

Oxalate Fe 2300 ± 310 730 ± 8.3 290 ± 0.8

Total P 800 ± 78 970 ± 47.1 1100 ± 4.3

Total Al 39700 ± 5650

7000 ± 35.2

3400 ± 32.5

Total Fe 9200 ± 545 2700 ± 98.3 1800 ± 6.7

†not determined Table 1: Some characteristics of the WTR and soils used. Values are averages of six replicates ± one

standard deviation. Values are in mg kg-1, except pH values

The EC ranged from 1.21 dS m-1, well below the 4.0 dS m-1 associated with salinity problems [1]. The KCl-P represented only a small fraction of total P, with a mean value of 4 mg kg-1. The very low amount of KCl-P in the WTR implies that it would be poor not be source of P in soils. Total C value for the WTR was 3.4 %. Total C measured value agreed with the range C found for Al-WTRs (2.3- to 20.5 %; [3,12]. Total C determinations may overestimate organic C content since the combustion method (temperature 1010 C) measures both organic and inorganic C. The high total C levels found in many WTRs may be attributed to carbonate additions for pH adjustment during water treatment or additions of activated


80

carbon, which is used to remove taste and odor from source water. The WTR had C: N ratio less than 25, indicating that there was a significant N pool that could be used by plants, if WTRs were land applied. A C: N ratio of ~25 is commonly used as the value where mineralization and immobilization of an organic amendment are in balance. Total P of the WTR was 800 mg P kg-1, typical of Al-WTRs (300 to 4000 mg P kg-1; [3,12] Total P in WTRs comes from the raw water purified in drinking water treatment plants and becomes a part of the WTR structure. The relatively high total P content of the WTRs is probably due to concentration in the WTR after removal from contaminated raw water during treatment. Total Al was ~ 40 g Al kg-1, within normal ranges reported by others (15- to 177 g Al kg-1; [3,12]. Aluminum (hydr)oxides are sorbents for oxyanions such as phosphate, thus the high Al content of the WTR suggests that they will be major sorbents for P. Oxalate extractable P, Fe, and Al are usually associated with the amorphous phase of the particles. Oxalate-extractable Al values were close to total Al (84 % of the total), suggesting an amorphous nature of the WTR. This is consistent with the findings of O’Connor et al. [17] that the traditional 200 mM oxalate-extractable P, Al and Fe concentrations are typically 80-90 % of the respective WTRs’ total elemental concentrations. Gallimore et al. [17] concluded that the amorphous, rather than the total, Al content determines WTR effectiveness in reducing runoff-P.

The soil samples collected at both sites of the Michigan field have near neutral pH. Soils from both sites have very high soil test P (STP) values, but the soil collected from site 2 had greater soil test P. The high STP values reflect the long history of chicken manure application to the fields. The KCl-P accounted for 3.3 and 4.2 %, respectively, of the total P contents at site 1 and site 2. The high soluble reactive P concentration at both sites suggests that the soil can contribute significantly to P loss in runoff. The soil from site 1 had greater total Fe and Al than site 2, suggesting that site 1 had greater potential to sorb excess soil P than the soil at site 2. Changes in labile pools of P with time The isotopic dilution technique has been used to successfully describe P phytoavailability and mobility (labile pools of P) in soils [8]. Measured labile P levels in the control plots did not change significantly with time in the field, and were ~100 and 220 mg P kg-1

for site 1 and 2 (Fig. 1), respectively. Site 2 had significantly greater amounts of labile P, consistent with greater soil test P levels and coarser texture (Table 1). The high, and nearly constant, labile P levels in the control plots reflect the history of heavy manure applications to these soils, and portend that soils from both sites could continuously supply large amounts of soluble P in runoff over many years.


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0

50

100

150

200

250

300

t(0) 1998 1999 2000 2001 2002 2003 2004 2005

Year of sampling

labi

le P

con

c. (

mg

kg-1

)

Site1 controlSite 1 WTRSite 2 controlSite 2 WTR

Figure 1: Changes in labile P concentrations with time for the Michigan field samples taken from both the control and WTR amended plots at site1 and 2

Amendment with the WTR significantly (p = 0.015) reduced labile P concentrations at

both sites (Fig. 1). At site 1, WTR application reduced labile P values from ~ 100 to 50 mg P kg-1

6 months after WTR application, and labile P levels continued to decline for another 2 years. Time series analysis suggests that an equilibrium labile P level (~ 30 mg P kg-1) was reached around 2.5 years after WTR application. Similar WTR effects were obtained for site 2. Amendment with WTR significantly (p < 0.001) reduced labile P values within 6 months, and the reduction continued for another 4 years. Time series analysis suggested that an equilibrium labile P level (~ 75 mg P kg-1) was reached around 4.5 years after WTR application. The greater time (4.5 years) required at site 2 for the equilibration of WTR effect on labile P probably reflects the greater soil test P level, compared to site 1. Nevertheless, WTR amendment of either manure-impacted site significantly reduced labile P levels (at all times) below the higher levels in the control soils. The reduction in labile P due to WTR application is expected to reduce P loss and P pollution potential for these soils. Notable also is the longevity of the WTR effect. There was no evidence of release of WTR-immobilized P over time as measured by the labile P values. The labile P data demonstrate delayed, but steady, reduction in soluble P with time and ultimate reductions of ~ 65 to 70 % relative to the control soils.

The reduction of labile pools of P with time from the WTR-amended plots prompted us to assess the changes in Fe and Al concentrations with time. Iron and Al hydroxides, especially Al forms in Al WTR, can be major sorbents for oxyanions in soils, such as P. Changes in the magnitude of the sorbent pool with time are expected to influence the P sorption capacity of the amended soil. For both sites, there was an increase in the concentration of oxalate (200 mM)-extractable soil Al and Fe concentrations (Fig. 2) in the WTR amended plots, although the concentrations showed great variability over time. The WTR amended plots of site 2 exhibited a greater increase in oxalate (200 mM)-extractable Al and Fe concentrations, possibly due to the soil’s lower native Al and Fe concentrations (Table 1). The variability in oxalate extractable- Al and Fe, concentrations over time is attributed to sampling variability. Variability in the sorbent (200 mM oxalate-extractable Fe and Al) pool, observed with time at both sites (Fig. 25) prompted normalizing the data by dividing oxalate (200 mM)-extractable P by the corresponding oxalate Fe and Al concentrations in moles. This normalization yields a term, the P saturation ratio (PSR) [11], similar to the degree of P saturation (DPS) index, but omits the α factor (α = 0.3-0.5) in the ratio [20]. Small PSR values (< 0.1) suggest excess P sorption capacity and limited P lability. The PSR values for


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both sites were calculated and statistically analyzed to evaluate subtle differences between treatments over time.

0

20

40

60

80

100

t (0) 1.5 3.5 5.5 7.5Years after WTR application

Fe+A

l con

c. (m

mol

kg-1

)

Site 2 controlSite 2 WTRSite 1 controlSite 1 WTR

Figure 2: Changes in oxalate extractable Fe+Al with time from both the control and WTR amended

plots at sites 1 and 2.

0.00.20.40.60.81.01.21.41.6

t (0) 1.5 3.5 5.5 7.5Years after WTR application

PSR

Site 2 controlSite 2 WTRSite 1 controlSite 1 WTR

Figure 3: Changes in P saturation ratios with time from both the control and WTR amended plots at

sites 1 and 2.

For site 1, PSR values of the WTR-amended plots did not significantly differ at the 95

% confidence level from the control (no WTR) plots (Fig. 3). Similarly, aging in the field had no significant effect on the PSR values for WTR-amended plots even 7.5 years after WTR application; the PSR values remained low and relatively constant (~ 0.3) throughout the monitoring period. For site 2 (Fig. 3), PSR values were at least double those of site 1 for both control and WTR-amended plots because site 2 had about twice the soil test P and one-half the total Fe and Al concentrations (Table 1). Control plots of site 2 had relatively high PSR values (> 1), which suggest that site 2 could contribute significant amounts of P in surface runoff. Amendment with the WTR significantly (p = 0.015) decreased PSR values 6 months after application and, thereafter, remained relatively constant (Fig. 3) at PSR values < 50 % of the PSR values of the control samples. There was no significant effect of time, suggesting little potential for time-dependent P release from WTR-amended plots. Low native total soil Al and Fe concentrations in site 2 soil (Table 1) may have contributed to the positive WTR effect on reducing P extractability, as expressed by the PSR concept. In contrast, site 1 soil had relatively high amounts of native total Al and Fe concentrations; thus, the WTR application rate used was not sufficient to significantly increase total soil Al levels or change PSR values. Rainfall simulation study This study was conducted to confirm WTR effects on WEP and labile P measurements via rainfall simulation. Soils used represented samples from one-time WTR-amended fields in Western Michigan, 7.5 years after WTR amendment. The masses (mg) of the various forms of P lost in runoff and leachate from soil samples collected from both sites are given in Table 2.

Generally, there were significantly greater P losses from the soil samples collected from site 2 (both the control and the WTR-amended soils), than those collected from site 1 (Table 2). Results are consistent with the greater soil test P values and greater labile P values for soil


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at site 2 than at site 1. Most of the P loss from both sites occurred through surface runoff, rather than through leaching (Table 2).

RUNOFF

TREATMENT TDP‡ SRP†† DOP†‡ PP‡‡ BAP‡‡† Total Runoff

P CTRL 43.6 ± 31.6 40.6 ± 31.2 3.01 ± 2.2 51.9 ± 43.6 52.4 ± 21.4 95.5 ± 52.1

Site 1 WTR 17.9 ± 8.32 16.0 ± 11.3 1.94 ± 1.37 83.7 ± 77.8 22.5 ± 10.9 102 ± 66.3

CTRL 65.5 ± 47.3 60.6 ± 46.1 4.85 ±2.99 87.4 ±53.6 76.7 ± 41.6 153 ± 101

Site 2 WTR 34.1 ± 26.9 31.3 ± 19.8 2.85 ± 2.04 158 ± 112 39.2 ± 24.7 193 ± 89.6

LEACHATE

TREATMENT TDP SRP DOP Total

Leachate P TOTAL P LOSS

(Runoff + Leachate) CTRL 29.0 ± 14.9 12.7 ± 9.32 16.3 ± 11.5 29.0 ± 14.9 124 ± 88.9

Site 1 WTR 13.3 ± 8.65 5.82 ± 3.96 7.49 ± 5.48 13.3 ± 8.65 115 ± 79.9

CTRL 44.5 ± 29.5 20.4 ± 16.7 24.1 ± 18.9 44.5 ± 29.5 197 ± 131

Site 2 WTR 18.7 ± 11.2 7.12 ± 5.34 11.6 ± 8.74 18.7 ± 11.2

211 ± 156

† Numbers are flow-weighted means of 4 replicates in 3 rainfall events ± one standard deviation ‡ Total dissolved P †† Soluble reactive P †‡ Dissolved organic P ‡‡ Particulate P ‡‡† Bioavailable P

Table 1: Maases† of the various P forms measured in runoff and leachates from both sites of the

Michigan field study. All values are expressed in mg.

The total runoff P losses of the samples taken from both sites were dominated by particulate P, and greater particulate P loads came from the WTR-amended plots than the control plots. The runoff dissolved P at both sites was dominated by soluble reactive P (SRP), with dissolved organic P (DOP) occurring in small proportions (< 7 % of TDP). Contrary to the runoff dissolved P, the total dissolved P in the leachate had greater absolute values of DOP than the SRP. An independent determination of the total dissolved P was carried out on the undigested leachate samples using ICP-AES. The values obtained from this independent determination were similar to those obtained from the digested leachate samples determined colorimetrically. We, therefore, concluded that particulate P loads in the leachate samples were negligible and were consequently not determined. The high particulate P concentrations observed in the runoff from the soil samples, prompted estimation of ‘bioavailable’ P levels in the runoff water, using the iron-oxide impregnated paper strip method [15]. Sharpley [21] reported that the transport of BAP in agricultural runoff can stimulate freshwater eutrophication Total bioavailable P (BAP) loss was calculated by summing the BAP loads from the runoff and the TDP loads from the leachate. Total dissolved P loads were used to represent the BAP loads in the leachate on the assumption that the dissolved organic P will mineralize and eventually become bioavailable.

As expected, the total BAP loss from the soil samples taken from site 2 were significantly greater than those taken from site 1 (Table 1), consistent with the higher STP and labile P values of the site 2 soil. For site 1, the total BAP of the control soils accounted for > 60 % of the total P loss, whereas total BAP loss from the WTR-amended plots accounted for ~ 25 % of the total P loss (Table 1). Similar behavior was observed for the samples taken from site 2, with the total BAP accounting for ~ 55 % in the control and ~25 % for the WTR-amended soils (Table 2). The runoff pH and the EC were similar for both the


84

WTR-amended and the control plots at the respective sites. Runoff pH and EC values were similar to those observed for the leachates (data not presented). Effects of WTR on P losses There were no significant differences between the flow-weighted total P masses of the WTR-amended plots and the control plots at either site (Table 2). However, the flow-weighted TDP, SRP and DOP masses were significantly reduced at both sites in the presence of WTR. Conversely, the flow-weighted particulate P masses were significantly greater in the WTR amended plots at both sites than the control plots (Table 2). Possibly, the particles detached by the rain drops from the WTR-amended plots had greater P enrichment due to the WTR immobilization than the soil particles detached from the control plots. Furthermore, the greater particulate P masses may be due to the presence of WTR contained in the eroded particles, which also contains some P.

For site 1, application of WTR reduced the flow-weighted SRP masses by ~60 % and DOP by ~35% (Fig. 4). Overall, amendment with Al-WTR decreased flow-weighted dissolved P mass by ~59 %. Similar results were obtained for site 2. Amendment with Al-WTR reduced SRP masses by ~53 % and DOP by ~50 % (Fig. 4), resulting in an overall reduction of flow-weighted dissolved P by ~52 %. Earlier studies have shown that WTR amendment increased the content of P-fixing Al and Fe concentrations in the soils at both sites (Fig. 3). The increased P-fixing capacity of the soils resulted in the decreased TDP content. This is consistent with the observation of Elliott et al. [6] that, as the content of P-fixing Al and Fe in soils and P sources increases, TDP concentration decreases. The authors [6] determined P levels in runoff from soils amended with biosolids and dairy manure, under simulated rainfall and concluded that TDP concentrations in runoff can be reduced by adding Al and Fe salts to P sources that have high concentrations of water soluble P.

Amendment with WTR decreased the total (runoff + leachate) flow-weighted TDP concentrations from ~ 2.5 mg L-1 to ~ 0.86 mg L-1 at site 1 and from ~ 3.2 mg L-1 to ~ 0.94 mg L-1 at site 2. The reduced values exceed values (0.01-0.05 mg L-1) usually associated with eutrophication of surface waters [23], but are below a solution concentration of 1.0 mg L-1 (3.2 * 10-5 M) occasionally used as a benchmark. The 1.0 mg L-1 concentration is a common goal for wastewater discharges to rivers and streams and has been applied to soils on the premise that the discharge of P from soils to water should be held to the same standard [22]. Greater single amendment rates (> 114 Mg ha-1), or a multiple (yearly) WTR applications are likely necessary to reduce TDP concentration to the 0.01-0.05 mg L-1 target concentration range. The single application of 114 Mg ha-1, however, significantly reduced runoff and leachate P impacts on water quality.

A large proportion of the total P load loss in runoff was particulate P (45-73 % of the total P losses). Compared to the control plots, greater particulate P losses were found in the WTR-amended plots at both sites (Fig. 4). Despite the greater particulate P loads in runoff from the WTR-amended plots, flow-weighted ‘bioavailable’ P loads in runoff were significantly smaller than those of the control plots (Fig. 32), suggesting that much of the particulate P was not bioavailable. Thus, even if WTR-P erodes to surface waters, there should be minimal adverse effects on water quality.


85

0%

20%

40%

60%

80%

100%

Site1CTRL

Site 1WTR

Site 2CTRL

Site 2WTR

Treatments

perc

enta

ge o

d to

tal P

mas

s lo

ss

PP

DOP

SRP

Figure 4: Percentages of total P mass loss represented by the various P forms.

0

20

40

60

80

100

120

140

Site1 CTRL Site 1 WTR Site 2 CTRL Site 2 WTR

Treatments

Mas

s of

bio

avai

labl

e P

(mg)

Figure 5: Flow-weighted bioavailable P loads in runoff from sites 1 and 2.

SUMMARY AND CONCLUSIONS

The study was conducted to assess the longevity of WTR immobilization. Results from this study also showed that amendment with WTR reduced labile P concentration by ≥ 60 % of those of the control plots and that 7.5 yr after WTR application, the WTR immobilized P remained stable. The data suggest that WTR amendment should reduce P losses from soils, and do so for a long time. To confirm this, we utilized rainfall simulation techniques to investigate P losses in runoff and leachates 7.5 yr after one-time WTR amendment. Amendment with WTR reduced dissolved P and bioavailable P (BAP) by > 50 % from both sites, showing that even 7.5 yr after WTR amendment of the sites, the WTR-immobilized P remained non-labile. Thus, there is little fear that WTR-immobilized P will be dissolved into runoff and leachates to contaminate surface and ground water. The data suggest that WTR can be relied upon to control P losses in runoff and leachates, and that even if WTR-P erodes to surface waters, the bioavailability of the immobilized P is minimal and will cause no adverse effects on the water quality.

ACKNOWLEDGEMENT

This study was funded by United States Environmental Protection Agency (EPA Project CP-82963801). We wish to express our appreciation to Drs. Hector Castro, John Thomas and Mr. Scott R. Brinton (Soil and Water Sci. Dept., Univ. of Florida) for their technical assistance.

REFERENCES

[1] N.C. Brady, R.R. Weil. “The Nature and Properties of soils (13th ed)”, Prentice Hall, NJ, pp. 430-432, (2002). [2] P.R. Day. “Particle fractionation and particle size analysis”, In Methods of soil analysis, Part 1, C.A Black (Ed), American Society of Agronomy, Inc., Madison, WI, pp. 545-567, (1965).


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[3] E.A. Dayton, N.T. Basta, C.A Jakober, J.A. Hattey. “Using treatment residuals to reduce phosphorus in agricultural runoff”, Journal of American Water Works Association, 95, pp. 151-158, (2003). [4] T.C. Daniel, D.H. Pote. “Analyzing for total phosphorus and total dissolved phosphorus in water samples”, In: G.M. Pierzynski (Ed) “Methods of phosphorus analysis for soils, sediments residuals and waters”, Southern Corp. Series Bull. 396. Cooperative Extension Service, North Carolina State University, Raleigh, NC, pp 91-93, (2000). [5] H.A. Elliott, G.A. O’Connor, P. Lu, S. Brinton. “Influence of water treatment residuals on phosphorus solubility and leaching”, Journal of Environmental Quality, 31, pp. 681-689, (2002). [6] H.A. Elliott, R.C. Brandt, G.A O'Connor. “Runoff phosphorus losses from surface-applied biosolids”, Journal of Environmental Quality, 34, pp. 1632-1639, (2005). [7] L.E. Gallimore, N.T. Basta, D.E. Storm, M.E. Payton, R.H. Huhnke, M.D. Smolen. “Water treatment residual to reduce nutrients in surface runoff from agricultural land” Journal Environmental Quality 28, pp. 1474-1478, (1999). [8] R.E. Hamon, I. Bertrand, M.J. McLaughlin. “Use and abuse of isotopic exchange data in soil chemistry”, Australian Journal of Soil Research, 40, pp. 1371-1381, (2002). [9] M. Hollander, D.A. Wolfe. “Nonparametric statistical methods” 2nd ed. Wiley-Interscience Publications, NY, pp. 787, (1999). [10] E. Lombi, R.E. Hamon, S.P. McGrath, M.J. McLaughlin. “Lability of Cd, Cu, and Zn in polluted soils treated with lime, beringite, and red mud and identification of a non-labile colloidal fraction of metals using isotopic techniques”, Environmental Science and Technology, 37, pp. 979-984, (2003). [11] R.O. Maguire, J.T. Sims, S.K. Dentel, F.J. Coale, J.T. Mah. “Relationships between biosolids treatment processes and soil phosphorus availability”, Journal of Environmental Quality, 37, pp. 979-984, (2001). [12] K.C. Makris, 2004. Long-term stability of sorbed phosphorus by drinking water treatment residuals: mechanisms and implications. PhD dissertation, University of Florida, Gainesville, FL, (2002). [13] E.O. McLean. “Soil pH and Lime Requirement”, In: Methods of Soil Analysis. 2nd Ed., A.L. Page et al. (Eds.), Soil Science Society of America, Madison, WI, pp. 687-683, (1982). [14] J. Murphy, J.P. Riley. “A modified single solution method for the determination of phosphate in natural waters”, Analytica Chimica Acta, 27, pp. 31-36, (1962). [15] R.G. Myers, G.M. Pierzynski. “Using the iron oxide method to estimate biovailable phosphorus in runoff”, In: G.M. Pierzynski (Ed) “Methods of phosphorus analysis for soils, sediments residuals and waters”, Southern Corp. Series Bull. 396. Cooperative Extension Service, North Carolina State University, Raleigh, NC, pp 98-102, (2000). [16] National Phosphorus Research Project. National research project for simulated rainfall surface runoff studies [Online]. Available at http://www.sera17.ext.vt.edu/Documents/National_P_protocol.pdf (verified May 12 2006). North Carolina State University, Raleigh, (2001). [17] G.A. O’Connor, H.A Elliott, P. Lu. “Characterizing water treatment residuals phosphorus retention”, Soil and Crop science Society of Florida Proceedings 61, pp. 67-73, (2002). [18] J.D. Rhoades. “Electrical Conductivity and Total Dissolved Solids”, In: Methods of soil Analysis 2nd Ed., A.L. Page et al. (Eds.), Soil Science Society of America, Madison, WI pp. 365 – 372, (1996). [19] SAS Institute. “SAS online document”, version 8, SAS Institute Inc., Cary, NC, (1999). [20] O.F. Schoumans. “Determining the degree of phosphate saturation in non-calcareous soils”, In: G.M. Pierzynski (Ed) “Methods of phosphorus analysis for soils, sediments residuals and waters”, Southern Corp. Series Bull. 396. Cooperative Extension Service, North Carolina State University, Raleigh, NC, pp 31-34, (2000). [21] A.N. Sharpley, S.C. Chapra, R. Wedepohl, J.T. Sims, T.C. Daniel, K.R. Reddy. “Managing agricultural phosphorus for protection of surface waters - issues and options”, Journal of Environmental Quality 23, pp. 437-451 (1994). [22] J.T. Sims, G.M. Pierzynski. “Chemistry of phosphorus in soils”, In. Chemical processes in soils, M.A Tabatabai and D.L Sparks (Eds). SSSA Book Series 8, Soil Science Society of America, Inc., Madison, WI, (2005). [23] USEPA. “Acid digestion of sediments, sludges, and soils”, Section A, Part I, Chapter Three – Metallic analytes. Method 3050, SW-846, test methods for evaluating solid waste, USEPA, Washington, DC, (1986).


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HEAVY METAL CONTAMINATION OF SOIL AND SURFACE

WATER BY LEACHATES OF AN OPEN DUMP OF MUNICIPAL SOLID WASTE: A CASE STUDY OF OBLOGO LANDFILL IN

THE GA WEST DISTRICT OF ACCRA, GHANA.

Abuaku Ebenezer*

Department of Soil Science, School of Agriculture, University of Cape Coast, Cape Coast, Ghana. E-mail: [email protected]; Tel.: + 233 244 73 60 51; Fax: + 233 21 85 03 85

Poster Extended Abstract

BACKGROUND Municipal Solid Waste (MSW) management constitutes one of the challenging environmental problems facing many countries in the developing world in recent times. In Ghana, the problem is particularly worrying in the big cities like Accra where an increase in population tends to aggravate the situation. Open dumping is the most common method of solid waste disposal in most communities in Ghana. However, this presents numerous health and environmental problems for communities in which the landfills are located. Leachate from the landfill pollutes nearby streams and groundwater and in addition the piles act as breeding grounds for rodents and insects which are vectors of human diseases (Rushbrook and Dugh, 1999)

Leachate from these MSW landfills has very high contents of a range of organic and inorganic substances including heavy metals due to the heterogeneous nature of the waste stream reaching the landfill. In mixed (unseparated) MSW, there is a diverse range of other materials, some of which are potentially hazardous. Heavy metals in MSW originate from a variety of sources such as batteries, consumer electronics, used motor oils, plastics, ink and glass products, etc. When present in ground or surface waters, metals may constitute a significant hazard for public health and ecosystems.

The site chosen for the study is important because of its proximity to the Densu River which serves as a source of treated water for Accra, the capital City of Ghana. It is also located in the catchment of one of the country’s most important Ramsar site.

OBJECTIVES The study is broadly carried out to ascertain the impact of the landfill and its environmental pollution on the Oblogo community and its environment in the Ga West District of Accra, Ghana. This will involve the determination of heavy metals contained in the leachates coming from the landfill and explore the extent to which the leachate has negatively affected the quality of Densu River and other aquatic life such as fish. The study also aims at assessing the levels of soil contamination due to the landfill and to investigate the effect of the leachate-polluted water on the quality of vegetables produced.


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HYPOTHESES The study is based on the hypotheses that the leachate coming from the landfill contains high levels of heavy metals and other contaminants which have affected negatively the quality of Densu River and that the quality of both the soil and vegetables irrigated with the leachate-polluted river has also been affected significantly.

MATERIALS AND METHODS The fieldwork involved sampling of leachates, surface water, soil, fish, and vegetables from the study site. Measurements which were monitored in the field included temperature, pH, and conductivity. Laboratory analyses were also carried out to determine the presences and/or levels of heavy metals such as Mercury (Hg), Cadmium (Cd), Copper (Cu), Arsenic (As), Silver (Ag) etc using the Nuclear Activation Analysis (NAA) technique. Other physico-chemical parameters analysed included the Total Dissolved Solid (TDS), Chemical Oxygen Demand (COD), and Biological Oxygen Demand (BOD). Questionnaires were designed to ascertain the impact of the landfill on the health and socio-economic life of the Oblogo community.

EXPECTED OUTCOME It is envisaged that the study will help establish the critical levels of heavy metal contaminants in the soil and vegetables irrigated with the leachate-polluted river. The presence and/or critical levels of heavy metal contamination of the Densu River and other aquatic life such as fish will be known. The effect of the presence of the landfill on the health aspects such respiratory diseases, cholera, typhoid etc and the socio-economic life of the inhabitants of Oblogo will be ascertained. Recommendations will therefore be made to the appropriate governmental agencies for policy formulation and immediate interventions.


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WORKSHOP Theme: Soil and Groundwater Pollution and Remediation

Convenors: M. Verloo, K. Walraevens, J. Van De Steene, F. Tack

CONCLUSIONS The workshop consisted of two sub-themes:

- Managing contaminated soils using phytoremediation - Managing groundwater pollution from waste disposal sites

Sub-theme: Managing contaminated soils using phytoremediation Soil contamination is widespread in inhabited areas. Because effective cleanup by pollutant removal is financially prohibitive, there is a need to develop alternative affordable strategies to manage the contamination. Phytoremediation may prove a valuable option in dealing with contaminated land, especially if it can be combined with economic uses such as wood production for bioenergy. Erik Meers in his keynote presentation outlined the principles of phytoremediation and highlighted recent scientific developments. Acid mine tailings may benefit from phytoremediation approaches for long term stabilization of the site. However, plant growth may only be realized on these sites after amelioration of the physico-chemical parameters using amendments. Tee Boon Goh (Canada) presented experiences with various low cost amendments for stabilizing these sites. In a next contribution, Tran Thi Le Ha outlined the issue of contamination of agricultural land in Vietnam due to various sources of trade village waste. Conclusion Existing contaminated sites should be managed accounting for the contamination present. This management should be designed to prevent any significant hazards to ecosystems or to the food web. Phytoremediation is promising in this context provided it can be combined with beneficial or economic uses. Appropriate management strategies are extremely site specific and additionally depend on economical and sociological aspects. Prevention of new soil pollution should be an utmost priority in a country’s policy with respect to soil contamination. Sub-theme: Managing groundwater pollution from waste disposal sites A keynote presentation on this sub-theme was presented by Kristine Walraevens. Peter Kamande made an oral presentation on metal contamination in irrigated agricultural land in Kenya. River water used for irrigation of fields at the river-side is contaminated by various pollutants. The study was focusing on heavy metals in the soil.


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Abuaku Ebenezer presented both orally and in a poster a case study of Oblogo municipal landfill in the Ga West District of Accra, Ghana. This ongoing study is also focusing on heavy metal contamination. Leachates flow overland towards the nearby Densu River, which is used for food-supply (fish) and irrigation of vegetable fields. Conclusion Uncontrolled dumping in open dumps is still common practice in developing countries, both for industrial and municipal solid waste. Ensuing contamination problems are affecting the local environment and are threatening food quality, and ultimately people’s health. Adoption of proper waste management strategies, and of measures for controlling pollution caused by the existing open dumps, are highly needed. These require characterization of the siting conditions and of the pollution case.


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Workshop IC-PLR 2006 – Theme B – Integrated soil fertility management

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WORKSHOP THEME B – INTEGRATED SOIL FERTILITY MANAGEMENT

Sub-theme : Use of isotope techniques for nutrient management – Isotope biochemistry P. Boeckx, K. Denef, O. Van Cleemput

Paper/poster : Enhancing the agronomic effectiveness of natural phosphate rock with poultry manure : a way forward to sustainable crop production – S. Agyin-Birikorang, M.K. Akekoe, O.O. Oladeji, S.K.A. Danso Paper/poster : The effect of liming an acid nitisol with either calcite or dolomite on two common bean (Phaseolus vulgaris L.) varieties differing in aluminium tolerance – E.N. Mugai, S.G. Agong, H. Matsumoto Paper/poster : Effect of P fertilisers and weed control on the fate of P fertilizers applied to soils under second-rotation Pinus radiata – A.A. Rivaie, P. Loganathan, R.W. Tillman

Sub-theme : Organic farming in the tropics present situation, possibilities and challenges – Current research at the research group of soil fertility and nutrient management Stefaan De Neve

Paper/poster : Low input approaches for soil fertility management verified for semi-arid areas of Eastern Uganda – Kayuki C. Kaizzi, Byalebeka John, Charles S. Wortmann, Martha Mamo Paper/poster : Amelioration of acid sulfate soil infertility in Malaysia for rice cultivation – J. Shamshuddin

Conclusions


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Sub-theme : USE OF ISOTOPE TECHNIQUES FOR NUTRIENT MANAGEMENT

P. Boeckx, K. Denef, and O. Van Cleemput

1Laboratory of Applied Physical Chemistry (ISOFYS), Ghent University, Gent, Belgium

www.isofys.ugent.be, [email protected], Phone: +32 9 264 60 00

ISOTOPE BIOGEOCHEMISTRY

One of the research lines developed at the ISOFYS laboratory is Isotope Biogeochemistry. Herein we use advanced, state of the art stable isotope techniques to study processes of C and N cycling in terrestrial and aquatic ecosystems. In the following two paragraphs we present a summary of our scientific activities and the analytical equipment related to stable isotope analysis we have available.

A first research line deals with N cycling studies. Nitrogen cycling is studied in natural and agricultural ecosystems. In natural ecosystems we use natural abundance measurements of 15N in soil profiles and leaf material to develop ecosystem indicators for N-cycling (e.g. N openness of ecosystems). Next to that we use 15N isotope dilution techniques in combination with 15N tracing models to unravel N cycling processes in soil systems. Both natural abundance techniques and tracer techniques are also applied to study BNF in tropical agriculture. A second research line deals with the use if 13C in combination with physical fractionation techniques for soil organic matter. These studies are carried out on a variety of land use systems, going from forest soils over grasslands to no-till systems to study C turnover in these systems. A third Isotope Biogeochemistry research line deals with the identification of nitrate sources in surface water using stable isotope signatures and machine learning techniques. Finally, a fourth axis of expertise we develop is the use of biomarkers to assess the link between, on the one hand above ground biodiversity or land use, and on the other the microbial community structure in the soil and the biogeochemical process they carry out.

To perform the above mentioned research lines ISOFYS is equipped with state of the art advanced mass spectrometry devices. ISOFYS has three Continuous Flow Isotope Ratio Mass Spectrometer (CF-IRMS) systems. This equipment is coupled to different sample preparation units such as an elemental analyzer, a high temperature elemental analyzer, TOC/TN analyzer, trace gas unit, gas chromatograph (GC) and HPLC. The combination of three IRMS systems in continuous flow with six sample preparation units enables ISOFYS to analyze 15N, 13C and 18O in bulk solid samples; 15N and 13C in TOC and TN from liquid samples; 15N, 13C and 18O in CO2, CH4, N2O and N2; 15N, 13C, 18O and D in specific compounds that can be separated through; and finally 13C in specific compounds that can be separated via HPLC.


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SELECTED REFERENCES

[1] P. Boeckx, O. Van Cleemput. "Methane oxidation in a neutral landfill cover soil: influence of temperature, moisture content and N-turnover", Journal of Environmental Quality 25: 178-183, (1996). [2] P. Boeckx, O. Van Cleemput. "Methane emission from a freshwater wetland in Belgium", Soil Science Society of America Journal 61: 1250-1256, (1997). [3] Goossens, A. De Visscher, P. Boeckx, O. Van Cleemput. "Two-year field study on the emission of N2O from coarse and middle-textured Belgian soils with different land use", Nutrient Cycling in Agroecosystems 60: 23-34, (2001). [4] L. Kravchenko, P. Boeckx, V. Galchenko, O. Van Cleemput. "Short-term and long-term effects of NH4

+ on CH4 and N2O fluxes in arable soils", Soil Biology and Biochemistry 34: 669-678, (2002). [5] H. Vervaet, P. Boeckx, V. Unamuno, O. Van Cleemput, G. Hofman. "Can δ15N profiles in forest soils predict NO3

- loss and net N mineralization rates ?", Biology and Fertility of Soils 36: 143-150, (2002). [6] F. Accoe, P. Boeckx, O.Van Cleemput, G. Hofman, H. Xu, B. Huang, G. Chen. "Characterization of soil organic matter fractions from grassland and cultivated soils via C content and δ13C signature", Rapid Communications in Mass Spectrometry 16: 2157-2164, (2002). [7] X. Xu, P. Boeckx, L. Zhou, O.Van Cleemput. "Inhibition experiments on nitrous oxide emission from paddy soils", Global Biogeochemical Cycles 16 (3), DOI. 10.1029/2001GB001397, (2002). [8] D. Seghers, E.M. Top, D. Reheul, R. Bulcke, P. Boeckx, W. Verstraete, S.D. Siciliano. "Long-term effects of mineral versus organic fertilizers on activity and structure of the methanotrophic community in agricultural soils", Environmental Microbiology 5: 867-877, (2003). [9] K. Dhondt, P. Boeckx, O. Van Cleemput, G. Hofman. "Quantifying nitrate retention processes in a riparian buffer zone using the natural abundance of 15N in NO3

-", Rapid Communications in Mass Spectrometry 17: 2597-2604, (2003). [10] F. Accoe, P. Boeckx, J. Busschaert, G. Hofman, O. Van Cleemput. "Gross N transformation rates and net N mineralisation rates related to C and N content of soil organic matter fractions in grassland soils of different age", Soil Biology & Biochemistry 36: 2075-2087, (2004). [11] H. Vervaet, P. Boeckx, A.M.C. Boko, O. Van Cleemput, G. Hofman. "Gross and net N transformation processes in a temperate forest soil: the role of NH4

+ and NO3- immobilization", Plant and Soil 264: 349-

357, (2004). [12] S. De Smet, A. Balcaen, E. Claeys, P. Boeckx, O. Van Cleemput. "Stable carbon isotope analysis of different tissues of beef animals in relation to their diet". Rapid Communications in Mass Spectrometry 18:1227-1232, (2004). [13] P. Boeckx, L. Paulino, C. Oyarzún, O. Van Cleemput, R. Godoy. "Soil δ15N patterns in old-growth forests of southern Chile as integrator for N cycling Isotopes", in Environmental and Health Studies 41: 249-259, (2005). [14] D. Huygens, P. Boeckx, R. Godoy, C. Oyarzún, O. Van Cleemput. "Aggregate and soil organic carbon dynamics in south Chilean Andisols", Biogeosciences 2: 159-174, (2005). [15] K. Dhondt, P. Boeckx, N. Verhoest, O. Hofman, O. Van Cleemput. "Assessment of temporal and spatial efficiency of three adjacent vegetated riparian buffer zones for groundwater nitrate retention". Environmental Monitoring and Assessment 116: 197-215, (2005) [16] Y. Kewei, R.D. DeLaune, P. Boeckx. "Direct measurement of denitrification activity in a Gulf coast freshwater marsh receiving diverted Mississippi water". Chemosphere (accepted), (2006).


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ENHANCING THE AGRONOMIC EFFECTIVENESS OF NATURAL PHOSPHATE ROCK WITH POULTRY MANURE: A WAY FORWARD TO SUSTAINABLE CROP PRODUCTION

S. Agyin-Birikorang1*, M.K. Abekoe2, O.O. Oladeji1, S.K.A. Danso2

1 Soil and Water Science Department, University of Florida, Gainesville, FL 32611, USA; 2 Department of

Soil Science, University of Ghana, P. O. Box 125, Legon, Accra, Ghana * Corresponding author (E-mail: [email protected] Tel.: 1-352-392-1804 ext. 328)

Abstract Phosphorus is one of the main limiting nutrients for agricultural production in highly weathered soils worldwide. Addition of P inputs is thus required for sustainable crop production. However, high cost and limited access to mineral P fertilizers limit their use by resource-poor farmers in West Africa. Direct application of finely ground phosphate rock is a promising alternative but its low solubility hampers its use. There is therefore the need to look into low cost means of improving the solubility of natural phosphate rock to improve their agronomic effectiveness. The objective of this study was to quantitatively estimate the enhancement effect of poultry manure on P availability applied from low reactive phosphate rock (Togo phosphate rock) to maize grown on highly weathered soils. We utilized two highly weathered soils from Ghana and Brazil for this study. In a greenhouse experiment, using 32P isotopic tracers, the agronomic effectiveness of poultry-manure-amended Togo rock phosphate (PR) was compared with partially acidulated Togo rock phosphate (PAPR) and triple super phosphate (TSP). Four rates of poultry manure: 0, low (30 mg P kg-1), high (60 mg P kg-1) and very high (120 mg P kg-1) were respectively added to a constant amendment (60 mg P kg-1) of the P sources and applied to each pot of 4 kg soil. A Randomized Complete Block Design (RCBD) was used for the experiment in a greenhouse setting and Maize (Zea mays) was used as a test crop. The plants were allowed to grow for 42 days after which the above ground portion was harvested for analysis. Without poultry manure addition, the agronomic effectiveness, represented by the relative agronomic effectiveness (RAE) and proportion of P derived from fertilizer (% Pdff) was in the order TSP > PAPR > PR = control (P0). In the presence of low rate poultry manure addition, the agronomic effectiveness followed the order TSP > PAPR = PR > P0. However, at the high and very high rates of poultry manure addition, no significant differences in agronomic effectiveness were observed among the P sources, suggesting that at this rate of poultry manure addition, PR was equally as effective as TSP. The study showed that direct application of PR will be a viable option for P replenishment when combined with poultry manure at a 1:1 P ratio. Thus a combination of PR and poultry manure can be a cost-effective means of ensuring sustainable agricultural production in P-deficient, highly weathered tropical soils.

INTRODUCTION Highly weathered tropical soils are often very infertile and exhibit high acidity, which are severe constraints for optimum plant growth and crop yields. A very low P status is the main limiting factor for sustainable crop production, which is exacerbated through the so called ‘‘soil mining’’, i.e. continuous cultivation without addition of P inputs [13]. A sustainable management of these soils to increase and sustain crop yields requires a proper land use such as long fallows and/or integrated management of organic and inorganic inputs [13]. Options for P inputs are organic materials and water-soluble mineral P fertilizers like triple superphosphate and diammonium phosphate.


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Unfortunately, the use of water-soluble mineral (nearly all imported) P fertilizers by the resource-poor farmers in West Africa is limited by their relatively high cost, and supplies often unavailable, when needed. Their use has become even more limited due to the withdrawal of subsidies on agricultural imports by most governments of developing countries, including Ghana. This situation has created a need to consider other alternative P sources for sustainable crop production especially in the developing countries.

Direct application of finely ground phosphate rock (PR), which is locally available or imported from neighbouring countries has been suggested as an alternative to the use of more expensive imported water-soluble P fertilizers for some crops grown in tropical acid soils [10a]. In recent years attention has been focused on the direct use of PRs in developing countries, and a number of trials have been conducted under greenhouse and field settings [1,2,10a,10b,20,21, 29, 30,31]. The main interest in the use of PR is due to its relatively low cost compared to the processed water-soluble fertilizers, and to its effect both in supplying P and liming soils in the long-term [10a,15]. Utilization of local PR deposits minimizes importation costs and hence saves on foreign exchange. In addition, other elements in PR, such as Ca, can improve the soil chemical and physical characteristics and contribute to plant nutrition [10a]. These advantages notwithstanding, the low solubility of PRs has discouraged its recommendation for direct use as a source of P for crops. Most of the P dissolved from PR undergoes immediate adsorption and immobilization reactions, whereas only a fraction (30–50% of dissolved P from PR) becomes available for plant uptake [8,21].

A method to improve the effectiveness of PR such as partial acid treatment with H2SO4 or H3PO4 has been suggested. Chien and Menon [10a] reported that partially acidified phosphate rocks can be as effective as superphosphate for certain crops and soils. Although partially acidified phosphate rocks are considerably cheaper than the imported water-soluble P fertilizer, the cost is still beyond the reach of the resource-poor small-holder farmers of the developing world. Another method that has been suggested is the compaction of PR with water-soluble P fertilizers [11,20,29]. Again, this process is slightly expensive to the resource-poor small-holder farmers. One of the cost effective options to increase PR solubility that has not been fully exploited is to combine it with on-farm organic materials such as farmyard manure (FYM) and crop residues, which farmers, particularly resource-poor smallholders, can access easily. Considering the hypothetical PR dissolution reaction, resulting in the release of H2PO4

- and Ca2+ [Ca10(PO4)6F2 + 12H+ ⇔ 10Ca2+ + 6H2PO4

- + 2F-], the dissolution of PR can be increased by increasing the supply of protons (H+) or by the continuous removal of the dissolved Ca and P from the dissolution zone [5]. Both of these expected processes have been shown to increase the dissolution of PR when acidic soil is amended with organic materials [5,18,21, 23,30]. With this amendment, protons are supplied by organic acids produced during composting and by the oxidation of ammonium to nitrate in the organic material. Thus depending on the amount and quality of the material used, it can influence P availability by stimulating microbial activity that can, in turn, increase mineralization of soil organic P, produce organic acids that may help to acidify and dissolve PR, and reduce P sorption [18]. Although organic amendments cannot usually provide sufficient P for optimum crop productivity because


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of its low P content, it can increase P availability in high P-fixing soils [18]. Increases in P availability are usually attributed firstly to an increase in net negative charges on soil colloids that reduce adsorption of applied P, and secondly to organic anions formed by decomposing organic manure that can compete with P for the same adsorption sites in the soil [18].

In addition to providing all the enumerated benefits with regard to organic matter in enhancing P phytoavailability from PR, poultry manure, generally, containing high P content, which can supply the early P requirement of the crop. By so doing, the plant would have better root development to deplete P and Ca in the dissolution zones of the PR, and thus enhance further dissolution of the PR. However, quantitative estimation of P availability from PR in soil as enhanced by poultry manure has not been reported. Because of possible interactions (priming effect) among poultry manure, PR, and soil P, use of radioactive 32P as a tracer is essential to distinguish P availability from soil P, PR, or poultry manure. The objective of this study was to use 32P as a tracer to estimate quantitatively the enhancement effect of poultry manure on P availability applied from a low-reactivity PR to maize grown on highly weathered tropical soils.

MATERIALS AND METHODS Site and soil description Two highly weathered soil types (from Ghana and Brazil) were collected and utilized for the study. The soil from Ghana was a well-drained savanna ochrosol (Ferric Acrisol, [14]), obtained from an uncultivated field at the University of Ghana Farm, Legon, near Accra. The soil was derived from quartzite schist. The sampling area receives an annual rainfall of between 635-1145 mm. The vegetation is mainly grassland with clusters of shrubs and grasses which include Panicum maximum, Andropogon gayallus, Sporobolus pyramidalis and Cynodon plectoatachus. The soil from Brazil was a clay-textured, typic Haplustox [27], with natural vegetation. The soil was obtained from Planaltina de Goiás, State of Goiás, Brazil, an area within the Brazilian central "Cerrado" (15o 14' S, 47o 42' W, altitude 826 m). The soils were collected at the 0-20 cm layer, air-dried, homogenized and sieved through a 4 mm screen for pot experiments, and 2 mm screen for laboratory analysis. Laboratory analysis Selected physicochemical properties of the soils used are given in Table 1. Particle size distribution analysis was performed using the modified Bouyoucos method as described by Day [12]. Soil pH was measured in 1:2 soil: 0.01M CaCl2. Organic carbon was analysed following the Walkley and Black oxidation procedure [4]. Total N was determined using the Kjeldahl method. Exchangeable basic cations were determined from ammonium acetate leachates while exchangeable Al and H were determined from KCl leachates as described by Thomas [28]. The effective cation exchange capacity (ECEC) was calculated by summing the above exchangeable cations. Extractable P was determined by the Bray-1 method and total P content of the soil by digestion with


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concentrated sulphuric acid and hydrogen peroxide [9]. In all cases P concentration was measured on neutralized extracts by colour development performed by the ammonium molybdate-ascorbic acid blue method [24].

Selected chemical and mineralogical properties of the PR used are given in Table 2. Total P was determined as described in AOAC [6]. The fluoride content was determined by means of the F- selective electrode as described by Evans et al. [13]. The PR dissolution in neutral ammonium citrate (NAC) and water was carried out as described in AOAC (1990) measuring dissolved phosphate by means of the molybdenum blue method [24]. Calcium carbonate equivalent and pH were determined as described in ISRIC [17]. The mineral composition of the PR was assessed by X-ray diffraction analysis using unoriented mounts and Co-Ka radiation on a Siemens D500 diffractometer equipped with a graphite crystal monochromator. The CO2-index, i.e. the ratio of intensities of the C–O and P–O absorptions, was determined from Fourier Transform Infrared (FTIR) spectra using the KBr pellet method (0.35 mg PR and 300 mg KBr compressed at 150 MPa in an evacuated die) and a Perkin-Elmer FT-IR2000 instrument. Scanning electron microscopy (SEM) using a microprobe technique with energy dispersive X-ray (EDX) was used to obtain information about arrangement, composition, size, shape and texture of mineral constituents. Greenhouse experiment Soil amendments used Well decomposed poultry manure was obtained from University of Ghana Agricultural Research Station, Nungua, near Accra. It was air-dried and crushed to pass through a 2-mm sieve. The nutrient concentration in the poultry manure was as follows: P, 0.59% N, 2.3%; and Ca, 3.1 %. The P sources utilized for the study in a finely ground form (100 mesh) were: Togo phosphate rock (PR), triple superphosphate (TSP) and partially acidified Togo phosphate rock (PAPR). The PR was obtained from Hahotoe (Togo) and contained 16 % total P with 1.3 % of neutral ammonium citrate-soluble P [2]. The total P content of the P sources was determined by dissolving each of them in concentrated HCl on a hot sandbath at 80°C and then determining the concentration colorimetrically on Philips PU 8620 spectrophotometer. The total P contents were: 11.87% for PAPR and 19.4 % for TSP. Design of the experiment Sixty (60) mg P kg-1 of the three inorganic P sources, together with a control [no P addition (P0)], were utilized for the study. Four application rates of poultry manure were utilized as follows: no poultry manure (M0), poultry manure to supply 30 mg P (M30), 60 mg P (M60) and 120 mg P (M120) kg-1 of soil calculated on the basis of the total P content of the poultry manure. Each of the 16 P source x poultry manure application rate combination was randomly assigned to a pot containing 4 kg of the 2 soil types respectively. Thus a 3-way mixed factorial experiment with two fixed factors (P source and Poultry manure rate) and one random factor (soil type) were combined to yield a total of 32 treatments. The pots were arranged n a randomized complete block design (RCBD)


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in a greenhouse setting with 3 replicates for each treatment. The isotopic dilution technique [32] was then used for the study.

An aliquot containing 1850 kBq 32P pot-1 was added to obtain sufficient activity in the plant material. To prepare the 32P-labelled carrier solution, the total activity required for the experiments was added as 32P carrier-free to a known volume of KH2PO4 carrier solution with 10 ppm P. Labelling was done by mixing the soil thoroughly with 10 ml of the solution containing 32P phosphate ions. The soils were allowed to equilibrate for 1 week before adding the unlabelled P fertilizers uniformly to the soil. A control [without P fertilizer and poultry manure addition (P0M0)], where only the 32P carrier solution was added was included as reference for the isotopic method.

Five maize (Zea mays var. Toxipino) seeds were sown in each pot and thinned to two after emergence. Pots were watered to 70% of the water holding capacity of the soil. Nitrogen, K, Ca, Mg and micronutrients were supplied as P-free Hoagland solution to each pot at every 2-weeks interval. The maize plants were allowed to grow for 42 days after which the above-ground plant material of each pot was cut into small pieces and the shoot dry matter yield was recorded after oven drying at 70 oC to a constant mass. The plant samples were burned at 450 oC for 5 h in a muffle furnace and the ashes were dissolved in 20 ml of 2 M HCl and filtered. Total P content of the filtered solution was determined colorimetrically using the Murphy and Riley [24] method. The 32P activity in the filtered solution was measured by liquid scintillation (Beckman LS 5801) counting of the 32P, by the Cerenkov Effect. Counts were corrected for isotope decay and counting efficiency (50%), and expressed in Bq. The specific activity (S.A.) of P was then calculated by considering the radioactivity per amount of total P content in the plant and expressed in Bq mg-1 P [32]. The percentage of plant P derived from the labeled source, and that derived from the soil alone, were calculated according to the 32P isotopic dilution method [32]. Similarly, the proportion (%) and amount (mg P pot-1) of P in the plants derived from the various P sources, with and without poultry manure treatments was obtained directly or indirectly using isotope dilution concepts [32]. Total P uptake from the individual P sources alone, and in combination with poultry manure was calculated based on the principles followed in Chien et al. [11]. The indices of relative agronomic effectiveness (RAE) were estimated based on the shoot dry weight (DMY), and total P uptake (Chien et al., 1996) as follows:.

RAE (%) = [(Y1 – Y0) / (Y2 – Y0)] * 100 where Y1 = yield or P uptake obtained from the P source or its combination, Y2 = yield or P uptake obtained from TSP source or its combination, Y0 = yield or P uptake obtained from the control

Statistical analyses Differences among treatments were statistically analyzed as a factorial experiment with a randomized complete block design (RCBD), using the PROC GLM procedure of general linear model (GLM) of the SAS software [26]. The means of the various treatments were separated using a single degree of freedom orthogonal contrast procedure. The


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relationship between P uptake and rate of poultry manure applied for the P sources was determined using a logarithmic function as follows:

ln Yi = βo + βi ln χ + εi where Yi was the P uptake obtained with P source i, χ was the rate of poultry manure applied, βi was the slope of the response function of P source i, βo was the intercept, and εi was the random error of the fitted model.

The ratio of any two of the regression coefficients (βi), that describes a Relative Crop Response Index (RCRI) [11,25] was estimated as follows: RCRI = βi/βTSP where βi is the regression estimate of the tested P source (PR or PAPR) and βTSP is the regression estimate of the standard fertilizer used (TSP). This ratio represents the marginal increase in P uptake, in proportion of a P source compared with a standard source, when a unit of poultry manure is applied.

RESULTS AND DISCUSSIONS

Properties of the soils The soil obtained from Ghana was a sandy clay loam soil and slightly acid in reaction (Table 1). The clay (27.5 %) and sand (51 %) contents were similar to those obtained by Acquaye and Oteng [3] for some savanna Ochrosols in Ghana. It was characterized by low organic matter, total nitrogen, available P and exchangeable basic cations. The low nutrient content of the soil may be due to little nutrient element cycling through plants in soils of the savanna zone.

The soil obtained from Brazil on the other hand was a clay soil and acid in reaction with comparatively high organic matter content (Table 1). Consistent with highly weathered soils, the soil had very low exchangeable basic cations and low nutrient (N and P) content.


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Soil properties Ghana soil

Brazil soil

Sand (g kg-1) 510 296 Silt (g kg-1) 215 324 Clay (g kg-1) 275 390 pH 6.1 4.2 Organic carbon (g kg-1) 10.6 22.6 Total Nitrogen (%) 0.10 0.32 Total P (mg kg-1) 91 103 Bray P-1 (mg kg-1) 7.49 6.98 Exchangeable basic cations (cmol (+) kg-1) Ca 2.27 1.49 Mg 1.05 1.05 K 0.85 0.16 Na 0.34 0.10 Exchangeable acidity (cmol (+) kg-1) 1.45 6.58

Table 1: Some physical and chemical properties of the soils used

pHH2O 7.4 Total P (%) 16.1 Ca (%) 33.2 F (%) 1.6 Ca:P-ratio 2.1 F:P-ratio 0.16 CaCO3 (%) 5.4 Si (%) 5.2 NAC-P† (%) 1.3 WS-P‡ (%) 0.02 a-cell (nm) 0.938 c-cell (nm) 0.692 Crystal size (nm) 400 CO2-index 0.29

Table 2: Selected chemical and mineralogical the phosphate rock used

† Neutral ammonium citrate-soluble phosphate.

‡ Water-soluble phosphate.

Characteristics of the Phosphate Rock Chemical, mineralogical and reactivity characteristics of the PR used are shown in Table 2. The data suggests that PR is a carbonate substituted fluorine deficient francolite. The low CO2-index corresponding to a low degree of carbonate substitution is consistent with the a-cell values, which indicate very low carbonate substitution. Moreover, the high a-cell values indicate very low reactivity, which is consistent with the measured low Neutral ammonium citrate (NAC) solubility. The large crystal size of the PR is also noteworthy in relation to reactivity [10b]. The low reactivity of Togo PR, and hence its unsuitability for direct application as P fertilizer, has been confirmed in numerous laboratory and greenhouse studies [1,2,21,25]. Effects of the P sources Despite the variation among the soils used in terms of differences in texture, pH, organic carbon content, etc; the effect of poultry manure on PR availability followed similar trends. Therefore only the data obtained from the soil of the Savanna zone of Ghana (Ferric Acrisol) are presented here. This soil was selected for explanation purposes because it showed the clearest trends.

The shoot dry matter yield (DMY), total P uptake, P derived from the applied P source (Pdff), obtained from the applied P sources, without poultry manure addition are presented in Table 3. The relative agronomic effectiveness (RAE) values calculated, based on DMY and total P-uptake from the applied P sources are also included in Table 3. Without P addition (P0), DMY and P uptake for the crop were low, consistent with the low bioavailable P content of the soil. Addition of TSP and PAPR significantly increased DMY and P uptake over the P0 and PR treatments. No significant difference was


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observed between the PR and P0, suggesting that the PR did not release adequate P to increase yield over the P0. Similar results have been previously reported when PR was utilized in some acid to near-neutral soils of the interior savanna and forest zones of Ghana [1,2,25].

The Pdff, which is estimated by isotope dilution technique, was also used to evaluate P uptake from the applied P sources. This technique is reported to be the most sensitive method for P uptake assessment from applied P fertilizers [32]. Similar to the DMY and P uptake, the percentage Pdff of the P sources followed the order: TSP > PAPR > PR (Table 3). As expected, the RAE values calculated based on total P uptake also showed, clearly, highest effectiveness of TSP followed by PAPR. This index was found to be a good parameter to compare differences in effectiveness between P sources [11,25]. The RAE calculated based on DMY indicated that PAPR was ~ 55 % as effective as the water soluble TSP in increasing yield of the maize crop while PR was only ~ 9 % (Table 3). Thus, the untreated PR was far inferior to the TSP and PAPR in increasing dry matter yield and P uptake of the crop.

Treatment DMY P uptake Pdff % RAE based on g pot-1 mg pot-1 % DMY P-uptake M0P0 3.1 ± 0.7 13.4 ± 2.4 0 0 0 M0PR 3.7 ± 1.1 14.5 ± 2.7 4.3 8.8 5.7 M0PAPR 7.0 ± 1.4 19.5 ± 2.0 35.3 54.6 31.6 M0TSP 10.8 ± 1.8 32.7 ± 4.2 72.6 100 100 M30P0 5.1 ± 0.4 27.6 ± 3.4 0 0 0 M30PR 7.5 ± 1.6 38.7 ±4.6 38.9 40.1 38.7 M30PAPR 7.9 ± 2.1 40.2 ± 5.7 53.2 46.8 43.9 M30TSP 11.2 ± 2.4 56.3 ± 5.3 73.2 100 100 M60P0 7.9 ± 1.3 34.9 ± 4.2 0 0 0 M60PR 11.3 ± 1.8 70.5 ± 8.1 72.7 84.4 85.4 M60PAPR 11.4 ± 2.1 72.7 ± 6.5 70.9 86.3 91.0 M60TSP 12.1 ± 2.4 76.1 ± 7.2 74.4 100 100 M120P0 8.1 ± 1.6 53.4 ± 6.2 0 0 0 M120PR 11.6 ± 1.9 73.1 ± 5.7 74.1 80.4 64.6 M120PAPR 11.7 ± 2.2 74.1 ± 8.2 73.8 83.7 67.9 M120TSP 12.2 ± 2.1 83.9 ± 7.6 75.6 100 100

Table 3: Dry matter yield, P uptake, Pdff and RAE of the maize plant fertilized with the P

sources, with and without manure addition. Values are average of three samples ± one standard deviation

Effect of poultry manure addition Mixing the various P sources with poultry manure significantly increased the DMY, P uptake and Pdff (Table 3) over those applied without poultry manure addition (M0) (Table 3). In the presence of low rate (M30 = 30 mg P kg-1) poultry manure addition, the DMY of the maize shoot of the PR treated plots increased from 3.8 to 7.5 mg pot-1, while the total P uptake increased from 14.5 to 38 mg pot-1. The percent P derived from the PR increased by nearly 10-fold (Table 3). Thus in the presence of M30, RAE calculated from


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both DMY and P-uptake followed the order TSP > PAPR = PR > P0 (Table 3). At the high (M60 = 60 mg P kg-1) and the very high (M120 = 120 mg P kg-1) rates of poultry manure incorporation, about 4-fold increase in DMY of the maize shoot over those of the PR treatment without poultry manure addition was observed (Table 3). Nearly 5-fold increase in total P uptake over the PR plots without manure addition was also observed. At these rates of manure application (M60 and M120), no significant differences in agronomic effectiveness were observed among the P sources, suggesting that at this rate of poultry manure addition, PR was equally as effective as TSP (Table 3). The PR mixed with poultry manure at a ratio of 1:1 increased the Pdff of the maize shoot from ~ 4 to ~ 73 % and DMY also increased from ~ 4 to 11.3 g, and gave RAE (calculated from P uptake) of ~ 84 %, which was similar to that of PAPR-poultry manure treatment and significantly greater than the PAPR treatment that received no poultry manure incorporation (Table 3). The high Pdff obtained from the PR-poultry manure mixture suggested an increased release of P from an otherwise unreactive PR. The DMY and P uptake by the maize shoot in the PR-poultry manure treatment were significantly greater than those obtained for the poultry manure applied alone (Table 3). This suggested that P availability from the PR-poultry manure to the maize crop was derived from the two materials. A two-way analysis of variance (ANOVA) showed a significant interaction between the PR and poultry manure.

The calculated values of P uptake using the isotopic dilution principles [11], presented in Fig. 1, were used to derive the regression coefficients (β) needed to calculate the relative crop response index (RCRI) for the various P sources. The estimated regression coefficients and RCRI for P uptake obtained for the various P sources are presented in Table 4. The RCRI represents the marginal increase in P uptake in proportion of a source compared with a standard source (TSP), when a unit of poultry manure is applied.

Source β1 RCRI (%) TSP 0.12 100 PAPR 0.21 175 PR 0.37 308

Table 4: Calculated values of the semi-log regression coefficient (β1) and the relative crop

response index (RCRI) of the P sources as a function of manure addition.

The RCRI vales indicated that the increase in P uptake as enhanced by poultry manure was ~ 3 times that of TSP and ~ 2 times that of PAPR (Table 4). The enhancing effect of poultry manure on P availability was thus greatest on the PR and that the effect decreased with increasing water-soluble P contents of the P sources. In the case of the TSP and PAPR, the lower influence of the poultry manure than the PR-poultry mixture may be due to the high water soluble P content (50% and 80% respectively for PAPR and TSP), which, possibly, already had priming effect of supplying P for early development and growth of the maize crop [7]. This is consistent with the results of Zaharah and Bah [31] who reported that green manure (organic matter) generally increased the solubility of less reactive PRs and depressed that of the more reactive ones. The greater enhancement effect of the poultry manure on the PR than on the PAPR and TSP may be explained by two possible mechanisms. Firstly, the release of organic acids such as citric and oxalic


104

acids during hydrolytic decomposition of the poultry manure may effectively chelate Ca2+ ion and lower its activity in the solution [15], or the organic acids so produced may solubilize the PR and render the P available to the maize plant. Secondly, the effect of the poultry manure may also be due to self-liming caused by mineralization and subsequent release of basic cations [23] and/or a release of OH- ions which may raise the pH of the soil-poultry manure system and facilitate the release of P [18].

To test which one of these processes was responsible for the interaction, the soil was mixed with PR and poultry manure in a ratio of 1:1, maintained at 60% water holding capacity and incubated for 6 weeks. A control treatment in which the soil was mixed with PR but without poultry manure was also included. At the end of the incubation period, the pH of the incubated samples was determined. The pH dropped from 6.2 in the soil mixed with PR alone (control) to pH 5.1 in the soil-poultry manure mixture. A drop in pH suggested a release of organic acids which rules out the possibility of self-liming due to the presence of the poultry manure.

We also hypothesized that P contained in the poultry manure will supply the early P requirement of the crop, which will enhance root development of the crop to deplete P and Ca2+ in the dissolution zone. Such reaction is expected to increase P availability from the PR. The result of the study shows that poultry manure addition to the soil alone, enabled the crop to significantly increase P uptake by the crop (Table 3). This observation supports the hypothesis that P availability from the manure also enhanced the efficiency of PR in increasing P uptake.

Differences between P uptake from the PR applied alone and P uptake from PR amended with different rates of poultry manure represented a quantitative estimation of the contribution of the poultry manure to the PR. In spite of the geometric increase of the P rate of the poultry manure mixed with the PR, the corresponding contribution to P availability from the PR was rather more of an exponential increase. For example, the increase in P uptake from the PR due to the poultry manure was 56 mg pot-l for M60 and 59 mg pot-1 for the MI20 treatment. Thus, doubling the P rate of the poultry manure mixed with PR did not result in corresponding contribution to P uptake. This may be attributed to common Ca2+ ion since, both PR and poultry manure contain some amounts of Ca which may increase the Ca2+ ion content in the soil solution and prevent dissolution of the rock phosphate [23]. It is therefore, uneconomical to mix very large amounts of the poultry manure, with the PR.

The marginal increase in P uptake (Fig. 2) was calculated as the derivative of the total P uptake with respect to P application rate of the poultry manure mixed with the PR. The maximum increase in P uptake was observed at M60 (1:1 PR manure ratio), after rate diminishing returns in P uptake was observed. The result suggest that the most economical returns in terms of P-uptake and possibly DMY is achieved when unreactive Togo PR is mixed with poultry manure at 1:1 P ratio.


105

0

1

2

3

4

5

0 1 2 3 4 5 6

Manure rate (log mg P kg-1)

P up

take

(log

mg

pot-1

)

TSPPAPR

PRP0

TSP: LN Y = 3.7 + 0.12 LN (X) R2 = 1.0PAPR: LN Y = 3.2 + 0.21 LN (X) R2 = 1.0PR: LN Y = 2.6 + 0.37 LN (X) R2 = 0.99

Figure 1: Linearized relationship between the manure application rates and P uptake from the P sources

0.000.200.400.600.801.001.201.401.601.80

0 50 100 150

Manure rate (mg P kg-1)

Mar

gina

l P u

ptak

e (k

g so

il po

t-1)

60

Figure 2: Increase in P uptake from PR per unit increase in manure added

SUMMARY AND CONCLUSIONS The 32P isotope dilution technique was an efficient tool to provide quantitative measurements of P uptake from the P sources studied for assessing the enhancement effect of poultry manure on P availability from PR. Unreactive Togo PR was found to be an ineffective P source for the 6-week-old maize plants grown on highly weathered acid to near-neutral soils. Addition of poultry manure to PR enhanced P uptake from the PR under the experimental conditions. Mixing an unreactive Togo rock phosphate with poultry manure in a 1:1 P ratio and applied to some highly weathered acid to near-neutral soils was more efficient in increasing DMY and P uptake of the maize shoot than using PAPR, and comparable to TSP (TSP = M60PR = M60PAPR > PAPR > PR). This finding is of relevance to local agriculture where a low input technology such as mixing unreactive PR with poultry manure can increase crop yield. The cost of mixing poultry manure with Togo PR is likely to be far lower than partial acidification since H3PO4 and H2SO4 needed for the process are imported and are extra cost to crop production. With the improvement of the poultry industry in most developing countries, including Ghana, disposal of poultry manure will sooner than later become a major environmental issue. Thus the beneficial use of poultry manure to improve the P status of the cropland will solve the anticipated disposal problem as well.

Further field trials under a variety of soil, climatic and agronomic management are needed to test further the hypothesis of the enhancement of P uptake in PR-manure mixture. Also, field-grown plant species may differ widely in their abilities to access poorly available soil phosphorus, thus plant species’ effect is worthy of investigation.


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ACKNOWLEDGMENTS This study was funded in part by the Ministry of Food and Agriculture, Ghana, through the National Agric. Research Programme (NARP). We wish to express appreciation to Profs. E. Owusu-Bennoah (CSIR, Ghana) and L.R.F. Alleoni (Univ. de Sao Paulo, Brazil) for their collaboration, and to Mr. Victor O. Edusei (Soil Sci. Dept., Univ. of Ghana), and Mr. Jeff Said (Agronomy Dept., Univ. of Florida) for their technical support.

REFERENCES

[1] M.K. Abekoe, S. Agyin-Birikorang “Greenhouse study on enhancement of availability of phosphorus from Togo rock phosphate using poultry manure”, Proceedings of Soil Science Society of Ghana, 16, pp.19-26, (1999). [2] M.K. Abekoe, H. Tiessen. “Fertilizer P transformations and P availability in hill slope soils of northern Ghana”, Nutrient Cycling in Agroecosystems, 52, pp.45-54, (1998). [3] D.K. Acquaye, J.W. Oteng. “Factors influencing the status of phosphorus in surface soils of Ghana”, Ghana journal of Agricultural Science, 5, pp. 221-228, (1972). [4] L.E. Allison, W.B. Bollen, C.D. Moodie. “Total Carbon”, In: Methods of Soil Analysis, Black CA et al. (Eds), Agronomy Monograph 9, Madison, WI, Part 2, pp. 1346–1365, (1965). [5] G.A. Alloush. “Dissolution and effectiveness of phosphate rock in acidic soil amended with cattle manure”, Plant and Soil 251, pp. 37-46 (2003). [6] AOAC 1990. “Official Methods of Analysis”, 5th Edition. Association of Official Analytical Chemists, VI. [7] T. Binh, C. Fayard. “Small-scale fertilizer production units using raw and partially solubilized phosphate”, In: Use of phosphate rock for sustainable agriculture in West Africa, H. Gerner and A.U. Mokwunye (Eds.), IFDC-Africa V series: Miscellaneous fertilizer studies No II, pp. 181-197, (1995). [8] N.S. Bolan, R.E. White, M.J. Hedley. “A review of the use of phosphate rocks as fertilizers for direct application in Australia and New Zealand”, Australian Journal of Experimental Agriculture, 30, pp. 297-313, (1990). [9] R.H Bray, L.T. Kurtz. “Determination of total, organic, and available forms of phosphorus in soils” Soil Science, 59, pp. 39-45, (1945). [10a] S.H. Chien, R.G. Menon. “Agronomic evaluation of modified phosphate rock products: IFDC’s experience”, Fertilizer Research 41, pp. 197- 209, (1995). [10b] S.H. Chien, R.G. Menon. “Factors affecting the agronomic effectiveness of phosphate rock for direct application”, Fertilizer Research 41, pp. 227-234, (1995). [11] S.H Chien, R.G. Menon, K.S. Billingham. “Estimation of phosphorus availability to maize and cowpea from phosphate rock as enhanced by water-soluble phosphorus”, Soil Science Society of America Journal, 60, pp. 1173-1177, (1996). [12] P.R. Day. “Particle fractionation and particle-size analysis”, In: Methods of Soil Analysis, Black CA et al. (Eds), ASA Monography, 9, American Society of Agronomy, Madison, WI, Part 1, pp. 545–567 (1965). [13] L. Evans, R.G. Hoyle, J.B. Macaskill. “An accurate and rapid method of analysis of fluorine in phosphate rocks”, New Zealand Journal of Science, 13 pp. 143-48, (1970). [14] FAO FAO/UNESCO. “Soil Map of the World, Revised Legend”, World Resources Report 60. Rome: FAO, (1994). [15] L.L. Hammond, S.H. Chien, A.H. Roy, A.U. Mokwunye. “Agronomic value of unacidulated and partially acidulated phosphate rocks indigenous to the tropics”, Advances in Agronomy, 40, pp. 89–140, (1986). [16] IFDC. “African Fertilizer Market”, Special Issue on Soil Fertility, Vol. 12, no. 12. IFDC Africa, Lome, Togo, (1999). [17] ISRIC. “Procedures for Soil Analysis”, International Soil Reference and Information Centre, Wageningen, (1995).


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[18] F. Iyamuremye, R.P Dick, J. Graham. “Organic amendments and phosphorus dynamics 1: Phosphorus chemistry and sorption”, Soil science, 161, pp. 426-453, (1996). [19] I.A.K. Kanabo, R.J. Gilkes. “The role of soil pH in the dissolution of phosphate rock fertilizers”, Fertilizer Research, 12, pp. 165-179, (1987). [20] K.A. Kpomblekou, M.A. Tabatabai. “Effect of organic acids on the release of phosphorus from phosphate rocks”, Soil Science, 158, pp. 442-453, (1994). [21] K.A. Kpomblekou, S.H. Chien, J. Henao, W.A. Hill. “Greenhouse evaluation of phosphate fertilisers produced from Togo phosphate rocks”, Communications in Soil Science and Plant Analysis, 22, pp. 63-73, (1991). [22] M.M Msolla, J.M.R. Semoka, O.K. Borggaard. “Hard Minjingu phosphate rock: an alternative P source for maize production on acid soils in Tanzania”, Nutrient Cycling in Agroecosystems, 72, pp. 299-308, (2005). [23] S. Mahimairaja, N.S Bolan, M.J. Hediey. “Dissolution of phosphate rock during the composting of poultry manure: An incubation experiment”, Fertilizer Research, 40, pp. 93-104, (1995). [24] J. Murphy, J.P. Riley. “A modified single solution method for the determination of phosphate in natural waters”, Analytica Chimica Acta, 27, pp. 31-36, (1962). [25] E. Owusu-Bennoah, F. Zapata, J.C. Fardeau. “Comparison of greenhouse and P-32 isotopic laboratory methods for evaluating the agronomic effectiveness of natural and modified rock phosphates in some acid soils of Ghana”, Nutrient Cycling in Agroecosystems 63, pp. 1-12, (2002). [26] SAS Institute. SAS online document Version 8, SAS Institute Inc., Cary, NC, (1999). [27] Soil Survey Staff. “Keys to Soil Taxonomy”, 8th Edition, United States Department of Agriculture, Soil Conservation Service, Pocahontas Press, Blacksburg, VI, (1999). [28] G.W. Thomas. “Exchangeable cations”, In: Methods of Soil Analysis, Page AL, Miller RH & Keeney SR (Eds), ASA Monography 9, American Society of Agronomy, Madison, WI, Part 2, pp 159–166, (1982). [29] F.C.A. Villanueva, T. Muraoka, A.R. Trevizam, V.I. Franzini, A.P. Rocha. “Improving phosphorus availability from Patos phosphate rock for Eucalyptus: A study with P-32 radiotracer”, Scientia Agricola 63, pp. 65-69, (2006). [30] M.W. Waigwa, C.O. Othieno, J.R. Okalebo. “Phosphorus availability as affected by the application of phosphate rock combined with organic materials to acid soils in western Kenya”, Experimental Agriculture, 39, pp. 395-407, (2003). [31] A.R. Zaharah, A.R Bah. “Effect of green manures on P solubilization and P uptake from phosphate rock”, Nutrient Cycling in Agroecosystems, 48, pp. 247-255 (1997). [32] F. Zapata, H. Axmann. “32P isotopic techniques for evaluating the agronomic effectiveness of rock phosphate materials”, Fertilizer Research, 41 pp. 189–195 (1995).


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THE EFFECT OF LIMING AN ACID NITISOL WITH EITHER

CALCITE OR DOLOMITE ON TWO COMMON BEAN (Phaseolus vulgaris L.) VARIETIES DIFFERING IN

ALUMINIUM TOLERANCE

E .N Mugai1*, S.G Agong1 and H. Matsumoto2

1Horticulture Department, Jomo Kenyatta University of Agriculture and Technology, P.O Box 62000

Nairobi, Kenya, 3Research Institute for Bioresources, Okayama University, Chuo Kurashiki 710, Japan Email: [email protected] or [email protected] Tel.+254 -722-337605

Abstract Two common bean (Phaseolus vulgaris) varieties, Rosecoco (GLP 2) and French bean (cultivar ‘Amy’), previously shown to differ in Al tolerance were tested for their response to liming with either calcite or dolomite in potted strongly acid, low fertility humic Nitisol. Dry matter yield, as a response to liming was highest at liming pH 5.6 for both varieties and lime types. However, French bean responded more to liming than Rosecoco at 102% and 102% (calcite), 129 %and 102 % (dolomite) of control respectively. Higher calcite liming (pH 6.8) reduced growth and was attributed to Mg deficiency by competition during uptake of Ca. Differential Al accumulation in the two varieties was higher in shoots of French bean but lower in roots an indication that one of the possible mechanisms of Rosecoco’s Al tolerance is confining Al to roots other than in shoots. However, Al uptake decreased in roots and shoots of both varieties with increasing levels of liming. Ca in the shoots increased with increasing liming levels but was higher in calcite than in dolomite treatments. Mg contents did not show any significant increases with liming with calcite but increased with dolomite liming levels. Rosecoco was more efficient in the uptake of Ca and Mg than the French bean. Therefore, it is concluded that there exists a varietal difference in Phaseolus vulgaris response to soil acidity and associated hazards and is therefore possible to select and breed/introduce Al tolerant cultivars for the acid soils of Kenya and that although both types of limes can be used to reduce the hazardous effect of acidity, dolomitic limes have an advantage in due to the additional Mg nutrition. It is therefore recommended that to achieve the highest crop yield on acid Nitisols, only dolomitic limes should be applied to a pH of around 5.6.

INTRODUCTION

In Kenya, acid soils with a pH of 5.0 or less comprise some or all Nitisols, Acrisols, Ferralsols, Cambisols and Andisols [3, 16]. These soils are estimated to cover an area of about 5 million hectares [16]. They are located in the Highlands where the climate is suitable for the intensive cultivation of many crops including the main source of protein to majority of Kenyans, the common bean. Continuous cultivation and use of soil acidifying fertilisers especially those containing ammonium has contributed to further acidification of these soils.

Although the hazard of soil acidity is obvious, the small-scale farmers have not adapted the culture of ameliorating it through liming, nor is the information available regarding relevant soil properties and the liming requirements for a particular crop. In Kenya, two cheap types of lime are available - calcite (CaCO3) and dolomite


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(CaMg(CO3)2. There are no comparative studies yet done to test the efficacy of the two lime types in the management of specific acid soils of Kenya.

The objectives of this research were to: (i) Characterise the acidity and related fertility properties of the acid humic Nitisol, (ii) Determine the optimum liming requirement by either calcite or dolomite and (iii) Determine the differential effect of liming with either calcite or dolomite on the growth and nutrition aspects of the common bean.

MATERIALS AND METHODS

Soil sampling and analysis Soil (0-15cm) was obtained from a humic Nitisol [3,14], in the tea-growing zone (altitude 2150m, Agro-climatic zone I-6) of Gatundu division, Thika District, Kenya. The soil was air dried, sieved through 2 mm and mixed. A sub-sample of the soil was analysed for pH (1:2.5 soil/water; 1:2.5 soil/0.01 CaCl2 solution); extractable Al (1N KCl) [2]; available phosphorus (P), potassium (K), calcium (Ca) and magnesium (Mg) [8]. P was determined by the molybdate blue method and measured by spectrophotometry, K by flame photometry and Ca and Mg by the atomic absorption spectrophotometry (AAS). Organic carbon was determined by the wet oxidation method [7]. Cation exchange capacity was determined by ammonium acetate method [2] and effective cation exchange capacity (ECEC) by sum of cations (including Al) extracted by unbuffered 1N KCl.

The summary results of the soil analysis are presented in Table 1. The soil is strongly acidic. The Al content is high reaching a saturation of about 50%. The high organic carbon is an indication of a lower rate of humification due to high acidity of the soil and the cool climate of the area. The chemical soil fertility is low except for K. Mapping unit (FAO)

pH water

pH CaCl2

CECac (cmole (+)/kg

ECEC (cmole (+)/kg

Organic Carbon %

Available nutrients (cmole (+)/kg

Extractable Al (cmole (+)/kg

humic Nitisol

K Ca Mg P (ppm)

3.95 3.4 24.8 11.4 1.9 1.6

0.67

0.25

11.0 5.11

Table 1: Selected soil properties of the test soil Neutralizing equivalence of limes The neutralizing equivalence of both calcite and dolomite as calculated for pure calcium carbonate was assessed by the method of Jackson [2]. Briefly, 1g of the lime were reacted with 1N HCl. After dilution, to 100 ml and boiling, the mixture was cooled and back-titrated with 1N NaOH using phenol-phthalein as indicator and calcium carbonate equivalence calculated accordingly. Calcite and dolomite were found to have a neutralizing equivalence values of 91.6 and 87 respectively.


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Estimation of liming requirements and plant culture Liming materials were local merchants. Estimation of liming requirements was from a calibration curve of pH against lime after incubating wet soil (1: 2.5 soil: water) with the varying amounts of liming materials (calcite and dolomite) for seven days [1]. Liming levels were 0, 6.0, 16.0 and 32 and 0, 6.0, 17, and 34 g/4 Kg soil of calcite and dolomite respectively, to attain pH levels 3.95, 5.1, 5.6 and 6.8. The liming materials were thoroughly mixed with the soil before potting. 1.32 g of diammonium phosphate (DAP) fertiliser equivalent to 200Kg (DAP) per hectare was mixed with top 5cm potted soil before planting. Three uniform 2-leaf seedlings previously pre-germinated in sterile sand were planted per pot. After a week of growth thinning was done to leave one seedling per pot. The liming treatments including the control were replicated three times and randomly placed on raised bench in greenhouse. Distilled water was used for basal irrigation. After one month the plants were harvested, washed off the soil with running tap water and rinsed with distilled water. The plants were then dried for 24 hours at 80 0C in a blow oven. The dry shoot and root were then weights were then weighed separately. 0.5g of each was then ground in a plant mill and ashed in a furnace at 550 0C. The ash was dissolved in 5 ml of 6N HCl, dehydrated, then dissolved again in 2 ml of 6N HCl and diluted to 100ml. Total Al, Ca and Mg in both shoots and roots and were then analysed by same methods as for the soil.

RESULTS Plant growth versus liming Table 2 presents the shoot and root dry weights of the two bean varieties against liming type and levels. The shoot and root dry biomass of the two bean varieties was significantly improved under liming irrespective of the lime type. The highest growth in both shoots and roots was attained at pH 5.6 across the varieties. In the un-limed soil the French bean variety exhibited a significant suppression of growth as compared with Rosecoco. Liming with calcite produced significantly less growth compared to that of dolomite across the two varieties and at the various levels of liming. In both types of liming, growth increase declined for both varieties at pH 6.8 although it was higher in French bean than in Rosecoco. The differential variety response to the two types of lime was also assessed by computing the relative whole plant growth against the un-limed control and expressed as a percentage (Fig.1). At maximum growth (pH 5.6) the growth response to calcite liming was similar in both varieties (102 %). However, dolomite liming resulted into higher growth response in French bean than in Rosecoco. At liming pH 5.1, 5.6, and 6.8 growth increase in calcite and dolomite liming was 112 %, 129 %, 78 % and 86 %, 119 %, 94 % respectively.


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Uptake of Al Al contents in both shoots and roots are presented in Table 3. Both varieties accumulated less Al in shoots than in roots. French bean concentrated a higher amount of Al in shoots than Rosecoco while Rosecoco accumulated more Al in roots. As liming increased, the content of Al in both roots and shoots of both varieties decreased. However the concentration of Al in the roots at calcite liming of pH 5.1 contained the highest levels of Al, higher than even in the control plants. Generally the Al uptake in the dolomite-limed plants contained less Al than in calcite limed ones in both shoots and roots in both varieties. Uptake of Ca and Mg The contents of Ca and Mg in dry shoots and roots in both varieties are presented in Table 4. Ca concentration in both shoots and roots of control plants was higher in Rosecoco than in French bean. The calcite-limed plants had the highest Ca concentration in both shoots and roots at pH 5.6 while dolomite limed plants had their peak at pH 6.8. The Ca concentration in both shoots and roots in the calcite and dolomite-limed plants was higher in Rosecoco than in French bean. Mg accumulation in shoots of control plants was also higher in Rosecoco than in French bean. It increased with liming with calcite to reach a peak at pH 5.6. In the dolomite-limed plants, Mg increased with liming to reach a peak at pH 6.8. Mg accumulation in the roots of control plants was higher in Rosecoco than in French bean. In calcite limed plants the Mg accumulation in the roots increased with increasing liming to reach a peak at pH 6.8 in both varieties. Mg accumulation in the roots was higher in Rosecoco than in French bean for both types of limes.

The Ca concentration in both shoots and roots was higher in calcite-limed plants than in dolomite limed ones. Mg accumulation in both shoots and roots of the dolomite-limed plants was much higher than in calcite treatments. The control plants showed clear deficiency symptoms of Ca deficiency, among others were severe stunted growth; crinkled, curled leaves and abnormally green first leaves; and some patchy interveinal chlorosis in the middle leaves. In the plants limed with calcite to pH 6.8, symptoms of Mg deficiency mainly interveinal chlorosis occurred in older leaves, while those treated at same pH level with dolomite were normal.


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1Means within columns ( plus/minus one standard deviation) with similar letters do not differ significantly (p < 0.05) by Duncan’s multiple range test (n = 4) **, *** Significantly different at p = 0.01 and 0.001 respectively

Table 2: The effect of liming with either calcite or dolomite on the growth of two Phaseolus vulgaries varieties, Rosecoco (R) and French bean cv. Amy (F).

Liming pH

Calcite Dolomite

3.95 5.1 5.6 6.8 3.95 5.1 5.6 6.8 Rosecoco Shoot 0.45 0.36 0.29 0.24 0.46 0.36 0.18 0.17 Root 6.1 12.0 8.8 6.6 6.1 6.1 2.9 2.5 French bean Shoot 0.82 0.45 0.3 0.29 0.82 0.29 0.19 0.17 Root 3.9 5.8 5.0 3.6 3.9 3.2 2.95 2.5

Table 3 : Uptake of aluminium (mg/g) in dry matter of shoots and roots of Rosecoco and French

bean in response to liming with either calcite or dolomite

Calcite Dolomite Variety and Liming level (pH)

Shoot dry weight (g)

Root dry weight (g)

Shoot dry weight (g)

Root dry weight (g)

R 3.95 0.4142 ± .027 c1

0.1713 ± 0.023 b

0.4142 ± 0.027de 0.1713 ± 0.023 c

R 5.1 0.6854 ± 0.043 b 0.2222 ± 0.017 a 0.855 ± 0.021 b 0.2433 ± 0.029 b

R 5.6 0.9011 ± 0.041 a 0.2817 ± 0.0021 a 0.995 ± 0.052 a 0.2967 ± 0.012 a

R 6.8 0.6185 ± 0.14 b 0.2583 ± 0.0164a 0.9133 ± 0.025 b 0.225 ± 0.0071 b

F 3.95 0.1917± 0.016 e

0.0783 ± 0.0153 d 0.1917 ± 0.016 e 0.0783 ± 0.0153 e

F 5.1 0.3733 ± 0.038 c 0.095 ± 0.00 d 0.4325 ± 0.062 e

0.1405 ± 0.0076 d

F 5.6 0.4433 ± 0.034 c 0.1033 ± 0.0153 d 0.4583 ± 0.04 d 0.159 ± 0.025 cd

F 6.8 0.2867± 0.0058 d 0.0783 ± 0.0153 e 0.3925 ± 0.0035 e 0.0875 ± 0.035 e

Significance2

Liming *** *** *** *** Variety *** ** *** *** Liming x variety ** *** ** ***


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DISCUSSION

The humic Nitisol [3] for which the experiment was conducted is strongly acid with very low nutrient content. Therefore the problem of this acid soil is not only the hazards associated with acidity like high Al but also quite low levels of P, Ca and Mg. Liming soil has the primary objective of raising the pH in order to decrease the soluble amounts of Al, Mn and Fe which not only may cause toxicity to plants but also immobilise P. The solubility of Mn and Fe is more controlled by soil redox than by pH and therefore in well drained soils like in Kenya Highlands where acid soils dominate, Al toxicity and soil infertility are the main hindrance to crop cultivation.

In this study phosphorus and nitrogen were supplied to the plant through diammonium phosphate fertilizer as is the custom in the small-scale cultivation of beans. The higher growth exhibited in limed plants as compared with control plants is an indication of detoxification of Al and increased Ca, and, Mg and Ca nutrition in calcite and dolomite limed plants respectively. These soils are low in both Ca and Mg and therefore a liming material like dolomite, which contains both of the elements, is bound to increase more the yield of crops than calcite, which contains only Ca.

The differences in acidity tolerance of the two bean varieties fits fairly well with the results earlier obtained [12] where root elongation in three day - old seedlings of Rosecoco and French bean was depressed by 38 % and 78 % respectively in nutrient solution containing 5 mM Al. Earlier work [10] showed that Al-sensitive plants respond more to decreased Al than Al-tolerant ones. The results of this study more or less agree with this principle (Fig. 1). The reason is that growth stimulation of root growth upon liming is more pronounced in Al – sensitive plants than Al-tolerant ones. However the depression of growth upon over-liming in French bean was greater than in Rosecoco. Under excessive calcite liming, Rosecoco was probably able to take up more Mg from the soil because of its more developed root system while under dolomite liming it was able to take up more elements including trace elements, which might have been unavailable due to immobilization (high pH) or competition by Ca and Mg. The higher response to liming with dolomite than with calcite is easily explained by the presence of Mg in the former because of the low Mg content in the test soil. The higher response to liming by French bean was not correlated with either Ca and Mg concentration and this may probably be Al toxicity was more critical than Ca or Mg nutrition in this particular soil. Barley grown in hydroponics had roots with higher contents of Al than in shoots [4]. This is in conformity with the results in this work (Table 3).

In control plants the shoots of Rosecoco contained less Al than the Al-sensitive French bean. Therefore the sensitivity of French bean to Al may be its inability to exclude Al to roots but also to the tops. There is therefore a need to also study the toxicity effects of Al in tops, which has hitherto been neglected. However roots of Rosecoco contained more Al in roots than those of French bean. If tolerance were achieved by Al immobilization in the cell wall, a reduction in membrane transport would be balanced by increase binding of Al in the apoplasm [15]. Thus, Al tolerant plants may have more or less Al as Al-sensitive ones. However this contradicted earlier results [12] where 3 day-old seedlings of Rosecoco had less Al in roots. Probably the accumulation of Al in cell wall through binding to cell walls after apoplasm immobilization increases with age of


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the plants. In this earlier work, Rosecoco’s tolerance was mainly due to Al immobilization by citric acid excreted by roots.

The Al concentration in both varieties and in both types of liming declined as liming was increased. This is expected because as pH is increased the toxic monomeric species of Al also decreased. However concentration of Al in calcite treatment of pH 5.1 is higher than that in controls in the roots of all varieties. This may be explained by the very poor growth in the controls, which reduces the uptake of all elements including Al.

Calcite Dolomite Liming pH

3.95 5.1 5.6 6.8 3.95 5.1 5.6 6.8

Rosecoco

Shoot

Ca 2.7 16.2 24.2 18.7 2.7 11.8 14.4 18.5

Mg 1.1 1.2 1.4 1.2 1.1 4.9 6.0 7.5

Root

Ca 2.2 7.8 17.1 18.5 2.2 7.4 8.8 9.3

Mg 0.9 1.6 2.4 3.3 0.9 5.3 8.5 11.1

French bean

Shoot

Ca 2.7 18.7 19.3 18.8 2.7 8.8 11.0 15.5

Mg 1.0 1.2 1.7 1.7 1.0 5.1 5.7 6.9 Root

Ca 1.3 4.3 8.7 10.3 1.3 4.0 7.5 8.3

Mg 0.8 1.2 2.5 2.2 0.8 3.0 5.6 5.9

Table 4 : Uptake of Ca and Mg (mg/g) by the dry shoots and roots of Rosecoco (R) and French

bean (F) upon liming with either calcite or dolomite The lower concentration of Al in dolomite treated plants implies that Mg just like Ca has Al-toxicity ameliorating role [9].


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Many studies have shown the role played by Ca in reduction of Al toxicity in plants. Al reduced Ca uptake in Al-sensitive wheat cultivars [9] while Al-tolerant Dade Snap bean cultivar contained more Ca in its exudate than that of Al-sensitive Romano cultivar [5]. Higher Ca concentrations in nutrient solution decreased Al-tolerance differences among maize inbred lines [13]. In this study (Table 4), the Ca in shoots agrees very well with other work [6] where the tolerant Dayton barley cultivar accumulated more Ca than the Al-sensitive Kearney when Al was added into the nutrient solution. In this study the Rosecoco plants had a higher Ca concentration than French bean irrespective of liming level and type, indicating its higher capacity to take Ca due to its better root development even at acid soil conditions.

The peak Ca uptake was arrived at pH 5.6 in calcite limed plants and at pH 6.8 in dolomite limed ones. The reason may be that in calcite limed plants Mg deficiency reduces growth so much at pH 6.8 as reduce Ca uptake. The content of Ca in shoots of control plants is less than 1.5% the minimum for optimal growth [7] and this explains the Ca deficiency symptoms mentioned earlier.

The Mg concentration in shoots was higher in the more Al- tolerant Rosecoco than in the French bean in both calcite limed probably due to its better-developed root system even in very acid conditions.

The Mg concentration rises with liming in the shoots and roots of calcite limed plants to reach a peak at liming pH 5.6; declining at pH 6.8 due to reduced growth associated with Mg deficiency. In dolomite limed plants, the peak is reached at liming pH 6.8. This may be due to factors associated with over liming like trace element deficiency though no deficiency symptoms were observed.

The content of Mg in control plants and in all calcite limed plants is less than 0.5% of dry weight which is necessary for optimal growth [11], thus the cause of the Mg deficiency symptoms mentioned above.

CONCLUSIONS

The study has conclusively shown the beneficial benefits of liming a low fertility, acid soil. Dolomite liming gave better growth than calcite and therefore the former should berecommeded as the type of liming material for acid soils of the tea zones of Kenya. The increase in the dry weight of the whole plant is well related to Al – tolerance; the more the response to dolomite liming the more sensitive the bean variety.

Al accumulation in the shoots of un-limed plants is a good indicator of acidity tolerance just like in young plants [12] but not so for Al in roots which seem to accumulate more in Al tolerant Phaseolus vulgaries. Al accumulation in roots of Phaseolus vulgaries grown in soil to near maturity gives contradictory result to that found in young plants and therefore use of Al contents in screening plants in soil grown to near maturity can only be done in combination with other techniques. Both Ca and Mg accumulation can be used to assess Al-tolerance in the common bean (Phaseolus vulgaris) grown in soil.

The most ideal liming pH level for maximum growth is 5.6 in this strongly acid soil irrespective of the liming material.


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ACKNOWLEDGEMENTS

The authors wish to thank the Japanese Co-operation Agency (JICA) for funding this study, and also the Jomo Kenyatta University of Agriculture and Technology for the provision of laboratory facilities.

REFERENCES

[1] M. M. Alley, L.W. Zelazny. “Soil acidity: Soil pH and lime needs. In Soil Testing: Sampling, Correlation, Calibration and Interpretation”, Ed. J.R Brown. pp.65-72. Soil science Society of America, Madison, Wisconsin, U.S.A, (1987). [2] H. D. Chapman, P. F. Platt. Methods of Analysis for Plants, Soils and Waters. Univ. California. 309 p., (1961) [3] FAO - UNESCO. Soil map of the world, Rome, (1988). [4] C. D. Foy, A.L. Fleming, W.H. Arminger, “Characterization of differential Al tolerance amongst varieties of wheat and barley”, Soil Sci. Soc. Am. Proc., 31, 513 -521, (1967). [5] C. D. Foy, A. L. Fleming, G. Gerloff. “Differential aluminium tolerance of soybean varieties”, Agro. J. 64: 815 -18, (1972). [6] C. D. Foy, A. L. Fleming, J.W. Schwartz. “Opposite and aluminium and manganese tolerance in two wheat varieties”, Agro. J. 65: 123-26, (1973). [7] A. D. M. Glass. Plant nutrition-An Introduction to Current Concepts, Jones and Bartlet Publishers, inc. 234 p. (1989). [8] G. Hinga, F. N. Muchena, C. M. Njihia. Physical and Chemical Methods of Soil Analysis, NAL-MoA, Kenya. (1980). [9] J. W. Huang, J.E. Shaff, D.L. Grunes, L.V. Kochian.. “Aluminium effects on calcium fluxes at the root apex of aluminium-sensitive wheat cultivars”, Plant Physiol., 98: 230-37, (1992b) [10] J. F. Ma, S. J. Zheng, X. F. Li, K. Takenda, H. Matsumoto. “A rapid hydroponic screening for aluminium tolerance in barley”, Plant and Soil. 191: 133-37, (1997a). [11] H. Marschner. Mineral Nutrition of higher plants, Inst. of plants Nutrition.Univ. Hohenheim, Germany. 889p., (1986). [12] E. N. Mugai, S. G Agong, H. Matsumoto. “Aluminium tolerance mechanisms in Phaeolus vulgaris L.: Citrate synthase activity and TTC reduction are well correlated with citrate secretion”, Soil Sci. Plant Nutr., 46, 939-950, (2000). [13] R. D. Rhue, C. O. Grogan. “Screening corn for aluminium tolerance”. Agron. J. 69,755 - 760, (1977). [14] W. G. Sombroek, H. M. H. Braun, B. J. A. van der Pouw. Exploratory Soil map and Agro-Climatic Zone Map of Kenya. Kenya Soil Survey. MoA. (1980) [15] G. J. Taylor. “Current views of the aluminium stress response; the physiological basis of tolerance”. Curr. Top. Plant Biochem. Physiol., 10, 57-93, (1991). [16] S.M Wokabi. “The distribution, characterization and some management aspects of acid soils of Kenya”, Paper presented at IBSRAM’S 2nd Regional Workshop in Land Development, Lusaka, Zambia. Kenya Soil Survey, (1987).


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EFFECT OF P FERTILISERS AND WEED CONTROL ON THE FATE OF P FERTILISERS APPLIED TO SOILS

UNDER SECOND-ROTATION PINUS RADIATA

A. A. Rivaie1, P. Loganathan2, and R. W. Tillman2

1Indonesian Center for Estate Crops R & D, Jl. Tentara Pelajar No.1, Bogor, Indonesia

([email protected]). Telp/Fax: 62 0251 336194; 2Soil Science, Massey University, Private Bag 11222, Palmerston North, New Zealand ([email protected]; [email protected])

Poster Extended Abstract

Phosphorus is an important nutrient in New Zealand forest plantations as most of the soils are P deficient or marginally deficient, and this element has been routinely applied since the 1960’s where appropriate. However, most of the information available on the P fertiliser requirements of radiata pine was obtained from trials on first-rotation forests that were managed under silvicultural regimes which were quite different from today. The current silvicultural regimes of Pinus radiata plantations with wider initial tree spacings have created the potential for increased growth of understorey vegetation. A consequence of this is that the response of P. radiata to P fertiliser is expected to be more influenced by the interaction between the P fertiliser, the tree and the understorey vegetation than was the case in the past.

The objectives of this study were to determine the effect of application of different rates of two P fertilisers (Triple superphosphate (TSP) and Ben Guerir phosphate rock (BGPR)) and weed control, and their interactions on P fractions and downward movement of P, in an Allophanic Soil (at the Kaweka forest) and a Pumice Soil (at the Kinleith forest) under 4-5-year-old second-rotation P. radiata plantations.

The results showed that P fraction containing the largest percentage of soil P was the 0.1 M NaOH extractable Po, in the surface soils (0-10 cm soil depth) at the two second-rotation forests. In the Allophanic Soil, NaOH-Po concentration was 196 µg P g-1

soil, which was 41% of the total P, and in the Pumice Soil it was 253 µg P g-1 soil which was 64% of total P. Therefore, the long-term P supplying power of the soil largely depends on the mineralisation of this organic P.

The NaOH-Pi and the H2SO4-Pi concentrations in the soils had increased at both forests two years after P fertiliser application, whereas, the largest pool of P, NaOH-Po, and residual-P were unaffected by the P fertiliser application. Changes in the concentration of P fraction as a result of P fertiliser application depend on the P fertiliser type. When increased rates of TSP were applied, the NaOH-Pi fraction (averaged over weed and weed-free treatments) increased at a faster rate than the other P fractions and the rate of increase was more marked at the Kaweka forest (an Allophanic Soil) than at the Kinleith forest (a Pumice Soil). This suggested that the proportion of TSP applied to the soil that was adsorbed to allophane and Fe+Al oxides was more than that converted to any of the other P fractions. The higher rate of increase of NaOH-Pi concentrations at the Kaweka forest than at the Kinleith forest is probably due to the higher P fixation capacity of the Kaweka soil compared to that of the Kinleith soil.


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When increased rates of BGPR were added, the H2SO4-Pi fraction (averaged over weed and weed-free treatments) increased at a faster rate compared with the other P fractions and the rate of increase was also more marked at the Kaweka forest than at the Kinleith forest. This is due to the high concentration of undissolved PR (P associated with Ca) remaining in the soils, which was extracted by H2SO4. In comparison, the addition of TSP increased the H2SO4-Pi concentrations only at 100 and 200 kg P ha-1 in the Kaweka soil and at 200 kg P ha-1 in the Kinleith soil. While, the increase in H2SO4-Pi concentrations resulting from the increase in BGPR rates of application is due to an increase in concentration of undissolved PR, the increase in H2SO4-Pi with an increase in TSP rates is due to the increase in concentrations of dicalcium phosphate resulting from the conversion of MCP in TSP to dicalcium phosphate.

In general, the magnitude of the increase in H2SO4-Pi concentrations per unit weight of BGPR addition at the Kaweka forest was greater than that at the Kinleith forest. This may be due to the higher rate of dissolution of BGPR in the Kinleith soil than in the Kaweka soil, as the former was more acidic than the latter (pH 5.1 and pH 5.7, respectively). The supply of H+ is a driving force for the dissolution of PR, along with the removal of the dissolution reaction products Ca2+, H2PO4

- and F- from the site of dissolution.

Rainfall at the Kinleith forest during the trial period was higher than at the Kaweka forest (annual rainfall for 2001 at Kinleith was 1491 mm and at Kaweka was 1285 mm; for 2002 they were 1702 and 1280 mm, respectively). It is possible that this would have resulted in a higher soil moisture regime at the Kinleith forest to help further the dissolution of BGPR. But the Kaweka soil had lower exchangeable Ca and resin-Pi concentrations and higher P fixing capacity compared to the Kinleith soil, therefore, based on these properties PR dissolution would have been expected to be higher at Kaweka soil. The fact that the observed dissolution was lower in the Kaweka soil indicates that the effect of the higher acidity and moisture content in the Kinleith soil overrides the influences of P fixing capacity, P concentration and exchangeable Ca in the soils in promoting a higher rate of BGPR dissolution in the Kinleith soil.

The effect of weeds on plant-available soil P concentration (resin-Pi) depends on the type of weeds and the degree of P deficiency in the soil. The deeper root systems of the weeds (Himalayan honeysuckle, buddleia and some toetoe) at the Kinleith forest enhanced the plant-available P concentrations in soil surface probably by removing P from the subsoils and returning it in the form of litter to the soil surface (pumping mechanism). At the P-deficient Kaweka forest soils, however, the weeds (bracken fern and manuka) reduced resin-Pi concentration. This suggests that when plant-available P is very low, the weeds tend to compete with radiata for P.

At both forests, the application of 200 kg P ha-1 as TSP and BGPR increased Bray-2 P at the 0-10 cm soil depth. At the 10-20 cm soil depth, however, the application of any of the two P fertilisers at the rate of 200 kg P ha-1 had no effect on Bray-2 P concentration at the Kaweka forest, while at the Kinleith forest the two P fertilisers increased Bray-2 P concentration. There was no fertiliser effect on Bray-2 P concentration at the 20-30 cm soil depth at both sites. This suggested that in the Pumice Soil at the Kinleith forest, P from both TSP and BGPR has leached to the lower depth. In the less porous and higher P fixing Allophanic Soil at the Kaweka forest it might have been difficult for the fertiliser P


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to have moved to below 10 cm depth. The movement of P in Kinleith forest was higher for TSP than BGPR because of higher solubility of TSP.


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Sub-theme : ORGANIC FARMING IN THE TROPICS PRESENT SITUATION, POSSIBILITIES AND CHALLENGES

Current research at the research group of soil fertility and nutrient management

Stefaan De Neve

Department of Soil Management and Soil Care, University of Gent, Gent, Belgium The research group on Soil Fertility and Nutrient Management is part of the department of Soil Management and Soil Care, which does research on all aspects of applied soil science, including soil fertility, soil organic matter, soil physics, soil erosion and soil conservation, soil pollution and its remediation, and soil data processing.

The research focus in the Soil Fertility and Nutrient Management group has gradually shifted from soil fertility related to maximising plant production towards environmental aspects related to fertilization and soil organic matter management. The main focus of the department is at present on the cycles of carbon and nitrogen in soil, and is reflected in a number of research topics that are briefly outlined below.

Fundamental research is going on about soil organic carbon (SOC) along different lines. A first line is the determination in soil of a passive SOC pool, i.e. a SOC pool that is by definition not affected by management but remains constant in size over centuries. This research uses a combination of physical fractionation methods (size and density fractionation) and chemical fractionation, in order to isolate silt and clay associated SOC and further subdivide this in biochemically and non-biochemically resistant SOC. The fractionations are combined with advanced mass spectrometrical analyses.

A second line is the visualization of physically protected SOC within micro-aggregates and the relationship between soil micro-architecture and SOC partitioning using X-ray computed nano tomography. This research should help to improve our understanding of mechanisms of physical protection of SOC, including the improvement of existing SOC models.

With regard to nitrogen, a more fundamental line of research is about the dynamics of dissolved organic nitrogen (DON) in forest soils in Flanders. Over the last decades, research on DON has received increasing attention as a possible important loss mechanism for N and as a biologically active component in the N cycle. We are looking at the importance of DON losses in forest soils in comparison to overall N leaching losses, and will try to model DON dynamics in these soils, based on laboratory measurements of the mineralization, sorption and desorption, chemical composition and transport in the vadose zone.

Another research line is the interaction between exogenous organic matter (EOM) that is applied to agricultural soil, the soil structure and soil physical properties, and soil foodweb dynamics, and how this interaction influences C and N cycling in soil. To this end, a field experiment was started where different qualities of EOM are applied in controlled quantities and where we monitor changes in soil physical properties/soil structure, changes in foodweb dynamics (notably microfauna, nematodes and earthworms) and associated C and N dynamics.


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Applied lines of research included research on alternative agricultural production systems such as reduced tillage agriculture/conservation agriculture and organic farming. Our research on reduced tillage is focussed on how this type of agriculture influences soil structure and soil physical properties, crop yields, and C and N dynamics from soil organic matter (SOM), including C storage, C and N mineralization, N2O emissions, nitrate leaching and overall nitrogen use efficiency. Research is also going on about the dynamics of crop residues under reduced tillage agriculture, namely C and N mineralization, NH3 and N2O emission and soil quality parameters including enzyme activities, microbial biomass, earthworms, … The organic farming systems research in our department until now has focussed on nutrient use efficiency compared to conventional agriculture, with emphasis on nitrate leaching losses and phosphorus saturation. An important part of the research is focussed on field grown vegetable crops, because in that particular sector many problems of over-fertilization and excessive nutrient losses are concentrated.

Finally, we are conducting research on nutrient balances and nutrient efficiencies of all kinds of organic manures and wastes to provide scientific support for new legislation concerning nutrient management in Flanders and in Europe.

REFERENCES [1] Coleman D, Fu SL, Hendrix P & Crossley D. 2002. Soil foodwebs in agroecosystems: impacts of herbivory and tillage management. European Journal of Soil Biology 38, 21-28. [2] De Neve S., Pannier J. and Hofman G. 1996. Temperature effects on C and N mineralization from vegetable crop residues. Plant and Soil, 181, 25-30. [3] Ferris H, Bongers T, de Goede RGM 2001. A framework for soil food web diagnostics: extension of the nematode faunal analysis concept. Applied Soil Ecology 18, 13-29. [4] D’Haene K., Moreels, E., De Neve S., Chaves Daguilar B., Boeckx P., Hofman G., Van Cleemput O. 2003. Soil properties influencing the denitrification potential of Flemish agricultural soils. Biology and Fertility of Soils, 38, 358-366. [5] Karlen, D.L., Mausbach, M.J., Doran, J.W., Cline, R.G., Harris, R.F. & Schuman, G.E. (1997). Soil quality: a concept, definition and framework for evaluation. Soil Science Society of America Journal, 61, 4-10. [6] Lenz R & Eisenbeis G. 2000. Short-term effects of different tillage in a sustainable farming system on nematode community structure. Biology and Fertility of Soils 31, 237-244. [7] Nunan N, Ritz K, Rivers M, Feeney DS, Young IM 2006. Investigating microbial micro-habitat structure using X-ray computed tomography. Geoderma 133, 398-407. [8] Schulten HR & Leinweber P (2000) New insights into organic-mineral particles: composition, properties and models of molecular structure. Biology and Fertility of Soils, 30, 399-432. [9] Six J, Conant RT, Paul EA, Paustian K 2002. Stabilization mechanisms of soil organic matter: Implications for C-saturation of soils. Plant and Soil 241, 155-176. [10] Sleutel S, De Neve S, Singier B, Hofman G 2006. Organic C levels in intensively managed arable soils - long-term regional trends and characterization of fractions. Soil Use and Management 22, 188-196. [11] Sleutel S., De Neve S., Hofman G., Boeckx P., Beheydt D., Van Cleemput O., Mestdagh I., Lootens P., Carlier L., Van Camp N., Verbeeck H., Van De Walle I., Samson R., Lust N. & Lemeur R. 2003. Carbon stock changes and carbon sequestration potential of Flemish cropland soils. Global Change Biology, 9, 1193-1203. [12] Van Den Bossche A., De Neve S. & Hofman G. 2005. Soil phosphorus status of organic farming in Flanders: an overview and a comparison with the conventional situation. Soil Use and Management, 21, 415-421. [13] Young IM, Crawford JW 2005. Interactions and self-organization in the soil-microbe complex. Science 304, 1634-1637.


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[14] Zelles L 1999. Fatty acid patterns of phospholipids and lipopolysaccharides in the characterisation of microbial communities in soil: a review. Biology and Fertility of Soils 29, 111-129.


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LOW INPUT APPROACHES FOR SOIL FERTILITY MANAGEMENT VERIFIED FOR SEMI-ARID AREAS OF

EASTERN UGANDA

Kayuki C.Kaizzi1, Byalebeka John1, Charles S. Wortmann2 and Martha Mamo2

1Kawanda Agricultural Research Institute (KARI), National Agricultural Research Organization (NARO), Box 7065 Kampala, Uganda; [email protected], 2University of Nebraska Lincoln, IANR, Department

of Agronomy and Horticulture, 154 Keim Hall, Lincoln, NE 68583-0915; [email protected]

Abstract Grain sorghum [Sorghum bicolor (L.) Moenich] is an important food crop in the semi-arid areas of Sub-Saharan Africa. Crop yields are generally low and declining partly due to low soil fertility. In an attempt to address the problem, 148 on-farm trials were conducted at three sites over three years in the drought prone parts of eastern Uganda. The aim of this research was to evaluate, with farmer participation, alternative low-input strategies for soil fertility improvement in sorghum based cropping systems. The strategies were: use of herbaceous legume (Mucuna pruriens) in improved fallow; a grain legume (Vigna unguiculata) in rotation with sorghum; use of cattle manure; application of low levels of N and P fertilizers. Mucuna (Mucuna pruriens) on average produced 7 t ha-1 of above ground dry matter containing 160 kg N ha-1 across the three sites. There was an increase in sorghum grain yield in response to the alternative strategies. Application of 2.5 t ha-1 of kraal manure and the application of 30 kg N plus 10 kg P ha-1 both increased grain yield by a mean of 1.15 t ha-1. A combination of 2.5 t ha-1 manure with 30 kg N ha-1 increased grain yield by 1.40 tha-1 above the farmer practice (1.1 t ha-1 grain). The increase in sorghum grain yields in response to 30 kg N ha-1 alone, to a mucuna fallow, and to a rotation with cowpea (Vigna unguiculata) was 1.0, 1.4 and 0.7 t ha-1, respectively. These alternative strategies were found to be cost-effective in increasing sorghum yield in the predominantly smallholder agriculture where inorganic fertilizer is not used. On-farm profitability and food security for sorghum production systems can be improved by use of inorganic fertilizers, manure, mucuna fallow, and sorghum-cowpea rotation. Key words: cowpea, low input, Mucuna pruriens, opportunity cost, resource poor, semi-arid, smallholder agriculture

INTRODUCTION Grain sorghum is an important crop for smallholder farmers in the drier areas of sub-Saharan Africa (SSA) but crop yields are low, and declining in some places [10, 22]. Low inherent soil N and P availability are major constraints [1] that are exacerbated by soil fertility depletion through nutrient removal in harvest and losses with runoff and soil erosion [21,30]. Many farmers are unable to compensate for these losses, resulting in negative nutrient balances at the national level for sub-Saharan Africa countries [26] and at the farm level in Eastern and Central Uganda [34]

Nutrient availability can be improved through application of inorganic or organic nutrient sources. The profitability of fertilizer use depends on agro-climatic and economic conditions at local and regional levels [31]. Infra structural and other marketing constraints, lack of agricultural subsidies, and high opportunity costs on available money makes the use of inorganic fertilizers very costly in SSA, and real costs to farmers are two to six times as


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much as in Europe [20]. Resource-poor farmers need large returns on the small investments that they can make, often require a 75% return within a six to 12 month period to make an investment competitive [32]

Use of organic nutrient sources is constrained by labor availability for collecting and applying the materials [19], limited quantities and variation in quality [17], and the demand for crop residues as fuel and fodder [16] Green manure production requires land that could often be used for food or cash crops [6]. Farmyard manure is available to many smallholder farmers but generally in small quantities [15]. Transfer of plant materials from field boundary areas, or near-by fallow or grazing areas, often has potential in sub-humid areas but less potential in semi-arid areas [14,32].

Biological nitrogen fixation (BNF) may contribute much N through better integration of legumes in farming systems. Biologically fixed atmospheric nitrogen contributes to productivity both directly, when the fixed N is harvested in protein of grain or other food for human or animal consumption, or indirectly by adding N to the soil for the maintenance or enhancement of soil fertility [8]. Under favorable environmental conditions, BNF can meet the N requirements of tropical agriculture [6,7,18]. Economic constraints make BNF an attractive N source for resource-poor farmers in sub-Saharan Africa [9,28].

Several promising low input approaches to soil fertility management for sorghum production in the drought-prone areas of eastern Uganda were evaluated to verify and fine-tune them for the production systems in four related studies. The objectives of these studies were to determine sorghum grain yield response to application of inorganic and organic N and P sources, mucuna fallow, and cowpea rotation.

MATERIALS AND METHODS Site characteristics Farmer-managed trials were conducted at Kadesok and Opwatetta parishes (approximately 33 45’ E and 1 12’N) in the Southern and Eastern Lake Kyoga Basin of eastern Uganda and Kapolin parish in the Usuk Sandy Farm-Grasslands (34 0’ E and 1 40’N) [33]. The altitude ranges from 1050 to 1150 m asl. The trials were part of a larger process of participatory research with these communities that began with participatory exercises in farming system characterization and diagnosis, identification of potential solutions to soil fertility problems, and development of research plans. The process lead to farmer participation in the dissemination of research results to other farmers.

The rainfall at the research sites allows for two cropping seasons per year with an annual mean of approximately 1150 mm for Kadesok and Opwatetta and 1000 mm for Kapolin. About 25-30% of the rainfall falls outside the crop seasons and is used by naturally growing annual or perennial vegetation and unavailable to the planted crops. Soil samples for the 0- to 20-cm depth were collected for each trial site, air-dried, ground to pass through a 2-mm sieve, and analyzed according to [6]. Extractable P, K and Ca were measured in a single ammonium lactate/acetic acid extract buffered at pH 3.8. Soil pH was measured using a soil to water ratio of 1:2.5. Soil organic matter was determined


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according to the Walkley – Black method, modified according to [5]. The dominant soil types in the area are petric plinthosols [3]. Sets of trials Two sets of trials were conducted. Each farm was a replication to minimize the probability of Type I error in extrapolating results throughout eastern Uganda. The plot size was 100 m2 for all trials. Trial 1 Use of the herbaceous legume (Mucuna pruriens), in improved fallow and cowpea (Vigna unguiculata) in rotation with sorghum were evaluated on 39 farms. The treatments were: continuous sorghum; sorghum following cowpea which was produced during the August to November short rains; continuous sorghum with 30 kg N ha-1 applied to the second sorghum crop; and mucuna fallow during the short rains followed by sorghum. Sorghum, cowpeas and mucuna were planted in the respective plots during the short rains. Sorghum was planted in all plots during the subsequent long rains period. No nutrients were applied except for the +N treatment. Trial 2 Sorghum response to applied inorganic fertilizers and manure was evaluated on 64 farms during the long rain season. The treatments were: no nutrients applied; 30 kg N ha-1; 30 kg N plus 10 kg P ha-1; 2.5 t manure ha-1; and 30 kg N plus 2.5 t manure ha-1. The manure was collected from open pens where farmers kept their cattle and goats at night. Cowpea was planted on all plots during the previous short rains season. Crop management practices, application of manure and inorganic fertilizers Manure and P fertilizers were applied at planting. Nitrogen was applied in two splits with 5 kg N ha-1 at planting and the remaining 25 kg N ha-1 six weeks later. Sorghum (cv. “Sekedo” and “Epurpur”) was planted at 60 x 20 cm during the long rains of 2004 (season 2004A) and 2005 (2005A). Mucuna was planted at a spacing of 75 x 60 cm and cowpea at 45 x 20 cm during the short rains of 2003 (2003B) and 2004 (2004B). In-season weed control was with hand hoes. Beta-cyfluthrin was applied 3 to 4 weeks after sorghum had germinated to prevent damage by stem borers and chloropyrifos 5% was applied for termite control.

Sorghum and cowpea stover were left in the field. The mucuna that remained after biomass measurements continued to grow until the soil water was depleted. Some of the mucuna, as well as some of the stover of sorghum and cowpea, was grazed by livestock during the dry season as livestock generally graze freely in the fields after harvest of the crops. Mucuna seeds remained in the field and germinated during the subsequent long rains, the volunteer plants were controlled until the second weeding after which emerging mucuna was allowed to grow in competition with the sorghum crop.


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Data collection and analysis Sorghum grain yield was determined by harvesting the whole plot at maturity. The grain was weighed after air-drying and threshing. Sub-samples were collected for moisture determination and the grain yield was adjusted to 14% water content. Mucuna biomass production was determined at 22 weeks after planting by harvesting an area equivalent to 3 m2 using a 1 m2 quadrant placed randomly at three different places within a plot. All the materials within the quadrant including litter were collected and weighed. A sub-sample was dried in an oven at 70˚C, ground to pass a 0.5 mm sieve and analyzed for total N, P and K by Kjeldahl digestion with concentrated sulphuric acid [1]. P was determined calorimetrically, and K by flame photometry.

Cowpea grain yield was determined at physiological maturity by picking pods only, a common practice in the area. Harvested grain was weighed after air-drying. Sub-samples were collected for moisture determination and the grain yield was adjusted to 14% water content.Analyses of variance were conducted by site and season for all sets of trials using Statistix V. 8.0 [25]. Differences were considered significant at the P ≤ 0.05 level.

ECONOMIC ANALYSIS

The profitability of alternative practices was assessed. The analysis for fertilizer use was based on the following assumptions [32]:

1. Opportunity cost, including risk allowance, was assumed to add 25, 50, and 75% to the cost of using fertilizer for the undefined categories of less poor, poor and very poor farmers, respectively;

2. Farm gate crop prices were reduced by 10% to cover the cost of harvesting, processing, and marketing;

3. Fertilizer costs were increased by 10% to cover transport and application costs; 4. Plot yields were assumed to be high relative to yields that small-scale farmers

can achieve at a farm-level and were reduced by 10% in the economic analysis. 5. Prices in Uganda shillings (UgSh 1,800/- = US $1) were assumed to be 200/- and

300/- kg-1 for sorghum and cowpea, respectively, at the farm-gate, and 40,000/- for 50-kg bags of urea and triple super phosphate.

RESULTS AND DISCUSSIONS Soil characteristics During the characterization and diagnosis process, farmers named different soils in the area and described these for their location on the landscape, associated problems, and soil-specific coping mechanisms. The major constraints mentioned by farmers include low soil fertility, low water holding capacity for sandy soils, water logging for clayey soils, and weeds. Researchers and farmers discussed possible solutions to the problems and farmers then agreed to participate in their evaluation.


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Soil texture class for the experimental sites ranged from sandy clay loam to sand with sand contents of 58 to 92% (Table 1). The pre-dominant texture classes were sandy loam and loamy sand, and of low water holding capacity. The soils for most trial sites had chemical values below the critical low levels estimated for Uganda soils [5]. Soil organic matter varied widely but was often low. Available P was below the critical level in most fields. Extractable K and Ca levels were low in 24 – 33% and 10-16% of the fields, respectively. Depletion of soil K probably occurred partly due to past harvests of cassava and sweet potato. The soil test results were typical for the area [23].

Soil property Kadesok Opwatetta Kapolin Critical

valuesa pH1:2.5

6.1 (5.4 – 6.6) 6.0 (5.2 – 7.2) 6.1 (5.3 – 7.5) 5.2 SOM (mg kg-1) 28 (19 – 42) 28 (26 – 41) 22 (17 – 35) 30 Extractable P (mg kg-1) 1.3 (1 – 6) 1.3 (1 – 5) 2.80 (1 – 9) 5.0 Extractable K (cmolc kg-1) 5.1 (2 – 10) 6.2 (3 – 10) 5.4 (2 – 10) 0.4 Extractable Ca (cmolc kg-1) 41 (8 – 45) 36 (5 – 54) 31 (5 – 68) 0.9 Sand (%) 71 (66 – 88) 76 (58 – 82) 84 (62 – 92) na Silt (%) 7 (2.6 – 13) 5 (1.3 – 15) 5. (3 - 11) na Clay (%) 2 (6.5 – 27) 19 (14 – 29) 11 (5 – 29) na aBelow these values, soils are deficient or poor [5]; na = not applicable.

Table 1: The median values and ranges for soil properties for the on-farm trial field in three communities

Trial 1: Sorghum response to improved fallow and rotation with cowpea The mean above-ground dry matter production by mucuna across the three sites was 7 t ha-1 containing 160 kg N ha-1, 14 kg P ha-1, and 94 kg K ha-1 This agrees with other findings in the region where mean dry matter production was 7.3 t ha-1, containing 180 kg N ha-1 with 103 kg N ha-1 derived from the atmosphere [11,13]. Farmers usually fallow their fields or grow cowpeas rather than sorghum during the short rain season (season B) due to the uncertainty of the rains and heavy feeding by birds. The mean cowpea grain yield during the short rains was 0.82 t ha-1, and the mean sorghum grain yield for the few farmers who harvested a short-season crop at Opwatetta and Kadesok was 1.05 t ha-1; these short season yields were used in the economic analysis.


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Treatment Kadesok Opwatetta Kapolin 2004A 2005A 2004A 2004B 2005A 2004A 2005A

Number of on-farm trials 5 8 5 3 7 6 5 Previous sorghum 1.03 1.76 1.17 1.00 1.39 0.67 0.96 Previous cowpea 1.84 3.19 1.61 2.00 2.17 1.43 1.18 Previous sorghum, 30 kg N ha-1

2.30 3.49 1.65 2.50 2.43 2.05 1.36

Previous mucuna 2.64 3.98 1.76 2.67 3.00 2.81 1.47 LSD0.05 0.27 0.27 0.29 0.56 0.39 0.53 0.15

Table 2 : Sorghum grain yield (t ha-1) during the long rains of 2004 and 2005 in three

communities

All treatments resulted in increased sorghum grain yield at all sites in both years relative to continuous sorghum with no fertilizer applied (Table 2). The overall mean increase in sorghum grain yield due to the effect of rotation with cowpea as compared to continuous sorghum was 0.72 t ha-1 with a range of 0.2 to 1.4 t ha-1 for the means of sites and years. The effect of applying 30 kg N ha-1 to sorghum following sorghum was an overall mean increase in sorghum yield of 1.03 tha-1 with a range 0.4 to 1.7 t ha-1. The effect of mucuna grown during the previous short rain season was an overall mean increase in sorghum yield of 1.43 t ha-1 with a range 0.5 to 2.2 t ha-1. Thus, inorganic N fertilizer, cowpea rotation, and mucuna fallow served as effective N sources for sorghum at the three sites. The relatively greater increase in sorghum grain yield due to the improved fallow with mucuna is in agreement with results reported for maize [3,11,26,28]. The higher mean response for sorghum following mucuna as compared to cowpea is expected as a large amount of fixed N was removed in the harvest of cowpea grain while most mucuna biomass was left in the field.

Treatment Gross returns

(,000 UgSh ha-1) Previous sorghum 371.2 Previous cowpea 535.7 Previous sorghum, 30 kg N ha-1 488.7 (25)b, 474.3 (50), 460.0 (75) Previous mucunac 453.7

bValues in parenthesis are opportunity costs

Table 3: The gross returns, excluding fertilizer costs at 25, 50 & 75% opportunity costs, for sorghum produced in the long rainy season following either sorghum, cowpea or mucuna

produced in the short rainy season. The most economical cropping system was the cowpea-sorghum rotation followed

by continuous sorghum with 30 kg N ha-1 fertilizer and the mucuna rotation (Table 3). Least profitable was the continuous sorghum without N. However, production costs were assumed to be similar for the previous crops while the cost of producing mucuna was undoubtedly less than for sorghum and cowpea due to easier planting, weed control and no harvest. The value of grazing of the mucuna during the dry season was not estimated but was probably greater than the value of grazing sorghum and cowpea stover. Accurate


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estimation of the true costs and benefits would improve the estimated profitability for the mucuna treatment to the extent that it may be the most profitable practice. Trial 2: Sorghum response to application of manure and inorganic fertilizer All manure and fertilizer treatments resulted in increased sorghum grain yield at all sites in all years relative to the control treatment with no nutrients applied (Table 4). The mean increases in sorghum grain yield, across sites and years, due to application of 30 kg N ha-

1 and 2.5 t ha-1 manure was 1.3 and 1.2 t ha-1, respectively. Application of 10 kg P ha-1 in addition to the 30 kg N ha-1 resulted in a mean additional yield increase of 0.27 t ha-1 with site-year mean increases ranging from <0.1to 1.32 t ha-1.

Application of 2.5 t ha-1 of manure in combination with 30 kg N ha-1 resulted in a mean yield increase of 1.08 t ha-1 compared to N and manure used alone with community-year mean increases ranging from <0.30 to 1.47 t ha-1. It is likely that manure supplied P and other nutrients required by sorghum. There was, however, no increase in the mean grain yield when P or manure was applied in addition to N during 2003A and 2004A at Kapolin and Opwatetta, respectively.

The net returns to application of low levels of N plus P, and of manure, are sufficient for these practices to be profitable (Table 5). The use of animal manure, assuming that it could be obtained and applied for Ug Shs 20,000/- t-1, was the most profitable soil fertility management practice. The least profitable practice was the application of N fertilizer in combination with manure. The application of inorganic P fertilizer in addition to N is profitable only when the opportunity cost of money is 25%, but the benefit to cost ratio was only 1.08 and therefore a relatively poor investment compared to N alone or manure alone. Kadesok Opwatetta Kapolin Treatment 2004A 2005A 2004A 2004B 2005A 2003A 2004A 2005A Number of on-trials conducted

5 9 5 3 17 6 7 12

Control 0.98 1.66 0.61 1.50 1.39 1.15 0.79 0.98 30 kg N + 10 kg P ha-1

2.62 3.78 1.74 2.92 2.69 2.15 2.50 1.48

30 kg N + 2.5 t manure ha-1

3.02 3.93 1.60 3.80 2.85 2.26 2.47 1.88

30 kg N ha-1 2.54 3.23 1.46 2.13 2.46 Na 1.43 1.40 2.5 t manure ha-1 2.06 3.51 1.44 2.25 2.41 1.74 2.04 1.74 LSD0.05 0.50 0.25 0.34 0.61 0.31 0.57 0.44 0.15

Table 4: Effects of nutrient application on sorghum grain yield (t ha-1) in three communities.


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Treatment Increase in grain yield (t

ha-1)

Net returns to input use

(,000 UgSh ha-1)a Benefit:cost ratio

25% 50% 75% 25% 50% 75% 30 kg N + 10 kg P ha-1 1.27 83.3 58.8 34.3 1.68 1.40 1.20 30 kg N + 2.5 t manure ha-

1 b 1.40 54.4 29.9 5.4 1.32 1.15 1.02

30 kg N ha-1 0.93 78.9 64.6 50.2 2.10 1.75 1.50 2.5 t manure ha-1 1.02 115.2 115.2 115.2 3.30 3.30 3.30

Table 5: Increase in sorghum grain yield (t ha-1) and net returns and benefit:cost ratios for

opportunity costs of money of 25, 50, and 75%, averaged across all location/years

DISCUSSION

The results presented in Tables 2, 4 and 5 show that sorghum yield is most constrained by soil N. However, soil tests results show that the availability of P and other nutrients is often low. Crop yield may therefore be limited by deficiency of one or more of these nutrients if crop yields are increased due to improved N availability. Application of a wide range of nutrients and organic matter with manure may contribute to the sustainability of the higher yield levels. The nutrient content of the manure on a dry matter basis was in the range 0.7 – 1.8%, 0.1 - 0.2% and 0.8 - 2.4% for N, P and K, respectively. The manure was from open pens and a large proportion of the manure N was probably in organic rather than ammonium form. Much of the organic N was probably not mineralized during the season and may benefit subsequent crops.

Manure use, however, is a process of transfer of nutrients from one part of the farming system to another rather than a replacement of nutrients exported in marketed harvest resulting in a negative farm level nutrient balance in the long run. Eventually, there will be a need to bring nutrients to the farm to sustain the higher levels of productivity and marketing of grain. Also, there is insufficient manure to apply 2.5 t ha-1

yr-1 to most of the cropland although manure is currently an under-utilized resource. Including legumes in the rotation apparently improved N availability. The cowpea-

sorghum rotation resulted in a significant increase in sorghum yield while providing a cowpea grain harvest the previous season. Using the short rain season to produce a mucuna fallow resulted in the greatest increase in sorghum yield. This is in agreement with the results reported for maize in eastern and central Uganda [4,11,12,13]. Furthermore, mucuna itself has some economic value as livestock grazed it during the dry season when fodder was scarce. Application of N fertilizer resulted in a mean sorghum grain yield that was intermediate relative to the yields following the legumes. The use of N fertilizer means a cash expense to the farmer but allows more choice in land use during the short rain season. The results of the economic analysis show that fertilizer use is profitable for all the farmers but less so for the poorest farmers with the greatest opportunity cost.

Several of the practices tested were verified as promising and a strategy is needed to achieve widespread adoption. Some of these practices had sufficient effect on crop performance that field demonstrations should be very effective if conducted throughout


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the semi-arid sorghum production areas of eastern and northern Uganda. Farmer involvement in the full research process ensured that the practices are compatible with their farming systems. Also, the practices are easily testable by adopting farmers.

Extension staff working in the target areas need to be enabled to conduct and effectively use demonstrations to inform farmers of the benefits of these practices. The participating farmers, who were involved from the characterization and diagnosis exercises through the implementation of trials and assessment of the results, are a potential resource for an organized farmer to farmer dissemination of the information.

CONCLUSIONS

Inorganic fertilizers, animal manure, N fertilizer combined with manure, mucuna fallow and cowpea rotation enable profitable increases in sorghum yield on the sandy loam and loamy sand soils of eastern Uganda. Inadequate N availability is the most limiting nutrient in the traditional production systems in this area. Application of a small amount of P in inorganic fertilizer or manure, in addition to N, is also profitable at three opportunity costs for money. The cowpea-sorghum rotation is a relatively profitable cropping system, especially if fertilizer N or manure is applied to the sorghum crop. The use of mucuna as a short rain season fallow crop is a promising source of N and organic material, as well as dry season fodder, for the resource-poor smallholder farmers of eastern Uganda. Available manure needs to be used efficiently as it supplies some of all soil nutrients essential to crop growth, some of which are likely to become more limiting with increased crop yields. Longer-term on-station research is needed to determine the sustainability of these low input approaches to soil fertility management.

ACKNOWLEDGEMENTS

The authors are grateful to the participating farmers and to Mr. Dennis Odelle, Mr. Bazil Kadiba, Mr. Patrick Odongo and Mr. William Acoda, the field assistants at the research sites. The research was made possible by the National Agricultural Research Organization (NARO), the International Sorghum/Millet Collaborative Research Support Program (INTSORMIL) and by funding from the U.S. Agency for International Development under the terms of Grant No. LAG-G-00-96-900009-00.

REFERENCES [1] J. M. Anderson, S. J. Ingram Tropical Soil Biology and Fertility: A Handbook of Methods. CAB Int. Wallingford, England. 221 p (1993). [2] M. A. Bekunda, A. Bationo, , H. Ssali. Soil Fertility Management in Africa. A review of selected research trials, pp 63 –79. In: Buresh, R.J., Sanchez, P.A., Calhoun, F. (eds) Replenishing soil fertility in Africa. SSSA spec. Publ. 51 SSA, Madison WI (1997). [3] FAO/ISRIC – ISSS. World Reference Base for Soil Resources. World Soil Resources. Report No. 84. Food and Agricultural Organization, Rome (1998).


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[4] M. Fischler, C. S. Wortmann. Green manures maize-bean systems in eastern Uganda: Agronomic performance and farmers’ perceptions. Agrofor. Syst., Volume 47, pp.123-138 (1999). [5]. H. L. Foster. Rapid routine soil and plant analysis without automatic equipment. I. Routine Soil analysis. E. Afric. Agric. For. J., Volume 37, pp. 160 – 170 (1971). [6] K.E. Giller, G. Cadisch, C. Ehakuitusm, E. Adams, W. D. Sakala, P.L. Mafongoya. Building soil nitrogen capital in Africa. In: R. J. Buresh, P. A. Sanchez, F. Calhoun, (eds.), Replenishing soil fertility in Africa. p 151-192. SSSA spec. Publ. 51 SSSA, Madison, EI (1997). [7] K. E. Giller, J. F. McDonagh, G. Cadisch. Can biological nitrogen fixation sustain agriculture in the tropics? p 173-191. In: J. K. Syers, D. L. Rimmer (eds.) Soil Science and sustainable land management in the tropics. CAB Int., Wallingford, England (1994). [8] K. E. Giller, G. Cadisch Future benefits from biological nitrogen fixation: An ecological approach to agriculture. Plant and Soil, Volume 174, pp.255-277 (1995). [9] K. E. Giller, K. J. Wilson. Nitrogen Fixation in Tropical Cropping Systems. CAB International, Wallingford, 313p, (1991). [10] IBSRAM. IBSRAM position paper. In: D. J. Greenland, G. D. Bowen, H. Eswaran, R. Rhoades, C. Valentin, (eds). Soil, Water and Nutrient Management Research - A new Agenda. Bangkok, Thailand (1994). [11] C. K. Kaizzi. The potential benefit of green manures and inorganic fertilizers in cereal production on contrasting soils in eastern Uganda. Ecology and Development series No. 4. Cuviller Verlag Göttigen, German, 102p (2002). [12] C. K. Kaizzi, H. Ssali, P. L. G. Vlek. Differential use and benefits of Velvet bean (Mucuna pruriens) and N fertilizers in maize production in contrasting agro-ecological zones of E. Uganda. Agricultural Systems, Volume 88, pp. 44 – 60 (2006). [13] C. K. Kaizzi, H. Ssali, P. L. G. Vlek. The potential of Velvet bean (Mucuna pruriens) and N fertilizers in maize production on contrasting soils and agro-ecological zones of East Uganda. Nutrient Cycling in Agro ecosystems,Volume 68 pp.59-73 (2004). [14] C. K. Kaizzi, C. S. Wortmann. Plant Materials for Soil Fertility Management in Subhumid Tropical Areas. Agron. J., Volume 93 pp.929-935 (2001). [15] J. K. Lekasi, J. C. Tanner, S. K. Kimani, P. J. C. Harris. Managing Manure to Sustain Smallholder Livelihoods in the East African Highlands. HDRA Publications, Coventry, UK. 32pp. (2001). [16] C. A. Palm. Contribution of Agro forestry trees to nutrient requirements of intercropped plants. Agrofor. Syst., Volume 30, pp.105-124 (1995)[. [17] C. A. Palm, R. J. K. Myers, S. M. Nandwa. Combined use of Organic and inorganic nutrient sources for soil fertility maintenance and replenishment. In: R. J. Buresh, P. A. Sanchez, F. Calhoun, (eds.), Replenishing soil fertility in Africa. pp 193 -217. SSSA spec. Publ. 51 SSSA, Madison, EI (1997). [18] M. B. Peoples, D. F. Herridge, J. K. Ladha. Biological nitrogen fixation: an efficient source of nitrogen for sustainable agriculture? Plant and Soil, Volume 174, pp. 3-28 (1995).


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AMELIORATION OF ACID SULFATE SOIL INFERTILITY IN MALAYSIA FOR RICE CULTIVATION

J. Shamshuddin

Department of Land Management, Faculty of Agriculture, Universiti Putra Malaysia, 43400 Serdang,

Selangor Malaysia

Abstract

Normally, acid sulfate soils are not suitable for crop production. Unless they are properly ameliorated using appropriate technology in agronomic practices, the soils are not put to agriculture production. The objective of this study was to ameliorate an acid sulfate soil in Malaysia using dolomitic limestone (GML) and an organic-based fertilizer for rice cultivation. The soils at the experimental plots belong to the Nipis-Bakri Associations (organic soils underlain by sulfidic materials with 50 cm depth), which can be classified as Typic Sulfosaprists. The rice (Oryza sativa) variety used in the trial was MR 219. The treatment included a control (T1, no lime), 2 t GML/ha (T2), 4 t GML/ha (T3), 6 t GML/ha (T4), 8 t GML/ha (T5), 4 t GML/ha + organic fertilizer (T6) and 4 t GML/ha + fused magnesium phosphate (T7). The result showed that the initial topsoil pH was low. At the depth of 45-60 cm, the pH values were lower than 3.5. The initial topsoil exchangeable Ca ranged from 1.17 to 1.68 cmolc/kg soil, lower than the required level for rice of 2 cmolc/kg soil. The initial exchangeable Mg was only 0.50-0.53, but Mg requirement is 1 cmolc/kg soil. The highest rice yield for the 2nd season was 7.5 t/ha obtained by T6. For this treatment, 4 t GML/ha were applied in combination with the organic fertilizer. This yield is comparable to the yield of rice grown on good soils in the granary areas of the west coast of the Peninsular Malaysia. The national average for Malaysia is 3.8 t/ha. It was observed that the yield obtained by T6 was not significantly different from that of T3, T4 and T5. This trial showed that applying 2 t GML/ha (T2) is not enough to ameliorate these soils for rice cultivation. For the T2, the pH was still low (3.99) and Al was very high (10.22 cmolc/kg soil). For T7, where 4 t GML/ha were applied in combination with fused magnesium phosphate, the yield was not significantly different from that of T6. It means instead of using organic fertilizer, farmers in that area can apply lime together with fused magnesium phosphate. The Malaysian government gives farmers in the area this phosphate fertilizer as a subsidy to increase rice production.

INTRODUCTION The Kemasin-Semerak Integrated Agriculture Development Project was launched by the Ministry of Agriculture Malaysia in 1982. The project area is located in the Kelantan Plain, an east coast state of Peninsular Malaysia. The Kelantan Plain is in the tropical wet climatic zone, with a mean daily temperature of 32o C and a mean annual rainfall of 2290-2540 mm [13]. The climate of the area is influenced by the South China Sea during the Northeast Monsoon, which is from November to January.

The Kelantan Plain consists of a mixture of riverine and marine alluvial soils, formed as a result of the rise and fall in sea level since the Quaternary [4]. Peaty materials sometimes overlain by mixed clayey-sandy sediments occasionally with variable amounts of pyrite are scattered all over the plain, especially along the coastline. This eventually gives rise to development of acid sulfate soil conditions, which are harmful to rice.

About 80 % of the people in the area involve in farming activities, particularly rice production. Unfortunately, some of the soils in the rice farms are too acidic for rice cultivation, having a pH value of less than 3.5. They are called acid sulfate soils. Under this condition, Al and Fe contents in the solutions are usually very high. Rice yield for


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these soils is very low (ranging from 1.29 to 3.06 t/ha). Among the agronomic problems common to acid sulfate soils are toxicity due to the presence of Al, decrease on P availability, nutrient deficiency, Fe(II) toxicity and plant stress due to the presence of sulfuric horizon [3].

The activities of Al3+ in the soil solution are controlled by Al(OH)3 (gibbsite), but only at high pH. Thus, raising the pH would render the Al inactive, as gibbsite is inert. Al in soil solution at 1-2 mg/kg can be toxic to rice [5].

With organic material, Fe(II) toxicity may occur due to reduction of Fe(III) under flooded soil conditions [20]. According to Moore and Patrick [9], Fe(II) activities were seldom equilibrium with iron solid phases in acid sulfate soils. Ponnamperuma et al. [15] reported values of 5000 mg/kg Fe(II) within 2 weeks of flooding. Iron uptake by rice is correlated with Fe2+ activities in soil solution [9]. Concentration above 500 mg/kg Fe(II) is considered toxic to rice plants planted on acid sulfate soils [12].

Some areas of acid sulfate soils in Malaysia have been reclaimed for rice cultivation using ground magnesium limestone (GML). In the acid sulfate soils of the Muda Agricultural Development Authority (MADA) granary areas in Kedah-Perlis coastal plains (northwest coast of Peninsular Malaysia), for instance, rice yield improved significantly after applying 2.5 tonnes of ground magnesium limestone per ha [2]. In another area called Merbok Scheme (also in the Kedah-Perlis coastal plains), rice yield increased from 1.4 t/ha (in 1974) to 4.5 t/ha (in 1990) after yearly application of 2 t GML/ha [19].

Acid sulfate soils can also be ameliorated by application of organic materials [10]. Application of organic matter in Al-toxic soils increases yield by detoxification of Al through pH increase and complexation of Al by organic matter [7]. The slight increase in soil pH can be due in part to release of NH3 during decomposition of organic matter as being reported for green manure [6].

The objective of this study was to ameliorate an acid sulfate soil using ground magnesium limestone and an organic-based fertilizer for rice cultivation.


The soils The soils in the experimental plots belong to the Nipis-Bakri Associations (organic soils underlain by sulfidic materials with 50 cm depth), which can be classified as Typic Sulfosaprists. The peaty materials have been degraded as a result of a long history of rice cultivation. In the soil profile, the sulfuric layer occurs below the depth of 45 cm. Prior to treatment, soil samples were collected at 15 cm interval to the depth of 75 cm at selected locations in the experimental plots (T1, T3, T5) in order to determine the initial chemical properties of the soils. Further soil samplings were carried out after every rice harvest for every treatment in the trial, but only for the topsoil. The crop tested The rice (Oryza sativa) variety used in the trial was MR 219. This is the most common rice variety planted by Malaysian rice growers in the Kelantan Plain. The past harvest


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showed that this rice variety yields about 2 t/ha using farmer’s practice, which is below the national average of 3.8 t/ha. Experimental The experiment was laid out in the field using Completely Randomized Design, with five replications. Each experimental plot size was 3X3 meters. There were altogether seven treatments. The treatment for the trial included a control (no lime, T1); the rest of the treatments are given in Table 1. The amount of organic fertilizer applied was 0.25 t/ha.

Symbol Treatment T1 Control (0 t GML/ha) T2 2 t GML+/ha T3 4 t GML/ha T4 6 t GML/ha T5 8 t GML/ha T6 4 t GML/ha + JITU* T7 4 t GML/ha + FMP#

+ GML – Ground Magnesium Limestone * JITU – Sugar cane-based organic fertilizer (0.25 t/ha)

# FMP – Fused Magnesium Phosphate

Table 1: Treatment in the field

The main rice season in the Kelantan Plain is November-April, while the off-

season is May-September. For this trial, two successive crops of rice were planted, during the main season. Ground magnesium limestone (GML) was applied once in mid-October 2002 and the seeding was done two weeks later, just before irrigation water was allowed to flow into the experimental plots.

Standard fertilizer rates were give to the growing rice plants in the field (90-120 kg N/ha, 12-18 kg P/ha, 90-120 kg K/ha), using urea, NPK Blue (12:12:17+TE) and NPK Green (15:15:15+TE) as the sources of the nutrients. This rate was for optimal rice growth, which was slightly higher than that using farmer’s practice. The organic fertilizer used was sugar cane-based compost. Soil analysis The soil pH (1:2.5) was determined in water. The cation exchange capacity (CEC) was determined using NH4OAc, buffered at pH 7. Exchangeable Ca, Mg, and K in the NH4OAc extract were determined by atomic absorption spectrometry (AAS). Exchangeable Al was extracted by I M KCl and determined by AAS. The organic carbon was determined by the standard Walkley-Black method [21].


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Iron in the soils was determined by double acid method (henceforth referred to as acid-extractable Fe). It was extracted using 0.05 M HCl in 0.0125 M H2SO4. A five-gram sample of the soil was mixed with 25 mL of the extracting solution and shaken for 15 minutes. The solution was then filtered through Whatman filter paper number 42 before determining the Fe it contained by AAS.

RESULTS AND DISCUSSION

The initial soil chemical properties

The chemical characteristics by depth of the soils at selected locations of the experimental plots in the trial before treatment are given in Table 2. The topsoil pH was low; the values were even lower at the depth below 50 cm. At the depth of 45-60 cm, the pH values were lower than 3.5 in all the three locations in the experimental plot (Table 2). This low pH coinciding with the presence of jarositic mottles in the soils at that depth qualifies them to be classified as acid sulfate soils. According to a study conducted in Vietnam, the depth of jarositic layer in an acid sulfate soil is not related with rice productivity [8]

The low pH was consistent with the presence of high exchangeable Al, especially at depth below 45 cm, which were the sulfuric layers. But in the Kelantan Plain, the exchangeable Ca and Mg were very low [18]. Hence, liming is necessary to supplement the macronutrients.

It was found that the peaty materials were completely decomposed. The CEC (data not shown) of less than 20 cmolc/kg soil further proves that the organic had broken down and completely mixed with mineral sediments. The CEC of normal organic matter is very high, having a value more than 200 cmolc/kg. According to the soil taxonomy [17], these soils can be classified as Typic Sulfosaprists due to the presence of peaty materials and sulfuric horizon within the depth of 50 cm.

The initial topsoil exchangeable Ca ranged from 1.17 to 1.68 cmolc/kg soil, lower than the required level for rice of 2 cmolc/kg soil [14]. The initial exchangeable Mg was only 0.50-0.53, but Mg requirement is 1 cmolc/kg soil [5]. According to these researchers also, Al concentration of 1-2 mg/kg in the soil solution would cause toxicity to the growing rice plants. Potassium contents seemed to be moderately high and thus would be sufficient for rice growth.

Based on the presence of deficient amounts of the two macronutrients (Ca and Mg), it is appropriate that the infertility of the soils can in part be ameliorated by application of dolomitic limestone, which contains both elements. The effects of treatment on soils Flood occurred twice in late November 2002. It is not possible to estimate how much damage the flood had caused to the rice production. The soil analyses carried out on the soil samples after the first rice harvest (sampled in April 2003) showed unexpected results. For instance, in T1, the topsoil pH, exchangeable Al, exchangeable Ca and


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T1 T3 T5

pH Al Ca Mg K O.C pH Al Ca Mg K O.C pH Al Ca Mg K O.C Depth (cm) air-

dried 1:2.5

fresh 1:2.5

--------------(cmolc/kg)-------------- %

air-dried 1:2.5

------------(cmolc/kg)------------ %

air-dried 1:2.5

-----------(cmolc/kg)----------- %

0-15 4.1 4.7 4.46 0.36 0.18 1.21 10.4 4.2 3.35 0.27 0.13 0.88 21.5 4.4 2.72 0.46 0.18 2.20 25.6

15-30 4.0 4.5 4.84 0.22 0.14 1.30 - 4.0 4.81 0.36 0.18 0.86 - 3.8 5.94 0.23 0.12 0.41 -

30-45 3.6 4.4 8.29 0.20 0.52 1.81 - 3.7 8.74 0.32 0.47 1.23 - 3.5 8.82 0.16 0.39 1.32 -

45-60 2.9 3.9 12.54 0.08 0.33 0.61 - 3.3 8.76 0.31 0.54 1.09 - 3.1 13.54 0.27 0.65 0.99 -

60-75 2.5 4.1 15.10 0.05 0.15 0.13 - 2.5 32.43 0.07 0.37 0.76 - 2.5 26.73 0.25 0.68 0.75 -

Table 2: Relevant chemical properties of the soil

Al Ca Mg K Treatment

pH water 1:2.5 ----------------------(cmolc/kg)----------------------

T1 3.95e 12.75a 1.58e 0.48f 0.41a T2 3.99e 10.22ab 1.99de 0.57e 0.24bc T3 4.06de 9.45ab 2.22cd 0.70d 0.15d T4 4.35b 3.13c 2.81b 0.93b 0.19bcd T5 4.52a 2.37c 3.74a 1.10a 0.17cd T6 4.21bc 8.79ab 2.57bc 0.79c 0.27b T7 4.16cd 7.46bc 2.47bc 0.78cd 0.21bcd LSD0.05 0.14 5.15 0.47 0.08 0.08

Table 3: Topsoil pH and exchangeable cations after 2nd harvest


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exchangeable Mg were 3.95, 5.83, 1.06 and 0.46 cmolc/kg soil, respectively (data not shown). In the T5, where 8 tonnes/ha of GML were applied, the corresponding values were 4.38, 2.64, 2.86 and 1.21 cmolc/kg soil. Ironically, the respective values for T7 were higher than those of the T5, where only 4 tonnes/ha of GML were applied. The corresponding values for this treatment were 4.93, 0.12, 8.60, 3.37 cmolc/kg soil. All these would be seen in the response of the rice plants shown by the yield of rice in this trial in the 1st season. However, the effect of this flood on rice yield was less remarkable in the 2nd season.

The results of the soil analyses for the second season (sampled on May 1, 2004) were according to expectation. The lowest pH with a value of 3.95 was reported for the control. The highest pH, being 4.52, was reported for T5, where the most amount of GML was applied (Table 3). Consistent with the lowest pH, the control treatment had the highest value of exchangeable Al, with a value of 12.75 cmolc/kg soil. As a result of the GML application, soil pH slowly but surely increased, culminating in the T5. In this treatment, the exchangeable Ca and Mg were the highest in the trials, having values of 3.74 and 1.10 cmolc/kg soil, respectively. The increase in pH was concomitantly followed by the lowering of exchangeable Al in the soil, the value of Al being 2.37 cmolc/kg soil. This was the lowest value of exchangeable recorded for this trial. Rice yield in the 1st season

The two floods of November of 2002 had affected the growing rice seedlings. After the floods, some plots needed to be reseeded (by transplanting). There could also be removal of the some liming materials by the running water during the height of the flood period; each flood lasted for about a week. The effect of the flood is clearly seen in the erratic values of the rice yield (Table 4). There seemed to be no real difference in rice yield between treatments. Note that the highest yield was seen on T2, where 2 t GML/ha was applied. But this yield was not significantly different from the control. The result of the trial for the 2nd would be presented later.

Treatment First harvest

April 26, 2003 (t/ha)

Second harvest May 1, 2004

(t/ha)

T1 4.5ab 5.1bc T2 5.0a 4.5c T3 3.5bc 6.3abc T4 4.4abc 6.6ab T5 4.2abc 7.2a T6 3.7bc 7.5a T7 3.1c 6.8ab LSD0.05 1.4 2.0

Table 4: The rice yield at the first and second harvest

Seeding of the 1st planting season was done two weeks after lime treatment. This is

considered a long enough time for the lime to react with soil, given the acid soil conditions at the site. The rice yield for the recommended rate (T6) was 3t/ha; this was lower than that of the control though it was not significantly different.


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Rice yield in the 2nd season The highest rice yield for the 2nd season was 7.5 t/ha obtained by T6 (Table 4). For this treatment, 4 t GML/ha were applied in combination with 0.25 t/ha sugarcane-based organic fertilizer (JITU). This yield is comparable to the yield of rice grown on good soils in the granary areas of the west coast of the peninsula.

It was observed that the yield obtained by T6 was not significantly different from that of the T3, T4 and T5. There was indication that applying 2 t GML/ha (T2) is not enough to ameliorate the soil for rice cultivation. As Table 3 shows, for the T2, the pH was still low (3.99) and Al was very high (10.22 cmolc/kg soil). For T7, where 4 t GML/ha were applied in combination with fused magnesium phosphate, the yield was not significantly different from that of the T6. It means that instead of using organic fertilizer, farmers in that area can apply lime together with fused magnesium phosphate. General discussion Ca present in soils is good in itself. Ca is, to a certain extent, able to reduce the toxic effect of Al [1,16]. This would happen from T3 right to T7 (Table 3). The amelioration of Al toxicity, should there be any, would be shown by the increase in rice yield (Table 4). The presence of extra Mg could also contribute to alleviation of Al toxicity as had been shown by Shamshuddin et al. [16] for maize.

Aluminum is toxic to plant. High exchangeable Al in soil is usually associated with low pH. This is clearly shown by the data given in Table 3; the lowest pH coincides with the highest Al (T5). It shows the opposite in T1. As seen in Table 1, the initial exchangeable Al was extremely high in some samples, reaching a value of 32.43 cmolc/kg soil in the subsoil of T3. The lowest value was 2.72, in the topsoil of T5. In the water in the vicinity of the experimental plots, Al would certainly exceed the critical value for rice production of 1-2 mg/kg. This high Al in the solution can be reduced to an accepted level by applying GML at an appropriate rate. This study suggested that GML application at 4 t/ha would be appropriate.

Fe toxicity is one of the most important problems facing production of rice on acid sulfate soils. In the abandoned rice fields, the water was reddish in color, indicating the presence of high amounts of soluble iron. In this study, acid-extractable Fe in the soils was slightly above the critical level, ranging from 0.07 to 0.81 cmolc/kg soil (data not shown). Critical Fe concentration varies from 0.05 to 5.37 cmolc/kg soil [5] implying that Fe may not be the only source of soil toxicity that causes reduction in yield.

A major problem of cultivated rice on acid sulfate soils is P-deficiency. This is caused by high P-fixation capacity of the soil due to the presence of high amounts of Al and/or Fe. P is unavailable to the rice and will remain in place where it is applied due to its immobilization. So, once soluble phosphate fertilizer is applied, it will revert to its less or insoluble form. Lack of P in the soil can be alleviated by applying fused magnesium phosphate (T7).

P-deficiency in the soil would cause stunted growth, reduced tillering and reduction in the number of panicles. In the 2nd season, the available P was about 4 ppm (data not shown), and there was no significant difference between treatments. But the rice yield did not seem to be affected significantly by the possible lack of available P in the soils, as the yield in T6 and T7 had shown. The required soil available P for rice production is 7-20 ppm [5].

Adding organic fertilizer into a flooded acid sulfate soil would intensify reducing condition, resulting in release of Fe2+, which is toxic to rice plants [20]. Putting organic fertilizer at the rate applied in the current study did not show any effect on rice yield.


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Treatment T6 in which GML applied together with organic fertilizer gave the highest rice yield of 7.5 t/ha in 2nd season (Table 4). On the contrary, high quality organic matter, like organic fertilizer used in the current study, would hasten reduction of Fe that result in pH increase [11].

The lime (GML) used in this study was dolomitic limestone [(Ca,Mg) (CO3)2 ]. Adding this lime would increase soil pH accordingly, with concomitant addition of Ca and Mg into the soil. For 2nd season of the trial, soil pH increased linearly with increasing exchangeable Ca (Figure 1A), with R2 = 0.73. Likewise, pH increased linearly with increasing exchangeable Mg (Figure 1B; R2 = 0.78).

y = 0.26x + 3.54R2 = 0.73

3.60

3.80

4.00

4.20

4.40

4.60

4.80

- 1.00 2.00 3.00 4.00 5.00

exchangeable Ca

pH

y = 0.26x + 3.54R2 = 0.73

3.60

3.80

4.00

4.20

4.40

4.60

4.80

- 1.00 2.00 3.00 4.00 5.00

exchangeable Ca

pH

A B Figure 1. Relationship between pH and exchangeable Ca (A) and exchangeable Mg (B)

GML ameliorated in the soil according to the following reactions: (Ca,Mg)(CO3)2 Ca2+ + Mg2+ + CO3

2- (equation 1) CO3

2- + H2O HCO3- + OH- (equation 2)

Al3+ + 3OH- Al(OH)3 (equation 3) The GML dissolved readily on applying it into the acidic soil, releasing Ca and Mg (equation 1), and these macronutrients could be taken up the growing rice plants. Subsequently, hydrolysis of CO3

- (equation 2) would produce hydroxyls that neutralized Al by forming inert gibbsite (equation 3). Soil pH increased significantly following reduction of exchangeable Al (Figure 2A).


141

y = -0.23Ln(x) + 4.59R2 = 0.59

3.60

3.80

4.00

4.20

4.40

4.60

4.80

- 5.00 10.00 15.00 20.00

exchangeable Al

pH y = 0.19Ln(x) + 4.36R2 = 0.71

3.60

3.80

4.00

4.20

4.40

4.60

4.80

- 1.00 2.00 3.00 4.00 5.00

Ca/Al ratio

pH

A B Figure 2: Relationship between pH and Al(A) and Ca/Al ratio (B)

Calcium is able to detoxify Al to certain extent [1]. Hence, Ca/Al ratio can be used as

an index of soil acidity [16]. Unfortunately, there was no correlation between rice and Ca/Al ratio in this study. Neither was there a correlation between relative yield and Ca/Al ratio. However, there was an excellent correlation between pH and Ca/Al ratio. This is shown by the equation in Figure 2B: pH = 0.19Ln(x) + 4.36 (R2 = 0.71)

Figure 3 depicts the relationship between yield and relative yield with either exchangeable Ca or Mg in the acid sulfate soil. The correlation between yield and exchangeable Ca was poor, with low R2 value (Figure 3A). The Pearson Correlation Coefficient was 0.32 with probability of 0.058. Thus, the relationship between the two parameters was significant at 5 % level. The same is true for the correlation between relative yield and exchangeable Ca (Figure 3B). As the relationship is poor, it is unable to determine the critical exchangeable Ca for rice cultivation on this particular acid sulfate soil. There is indication that rice yield improves on GML application.


142

A

y = 0.78x + 4.35

-

2

4

6

8

10

12

- 1.00 2.00 3.00 4.00 5.00

exchangeable Ca

Yiel

d (t/

ha)

C

y = 3.44x + 3.65

-

2

4

6

8

10

12

0.20 0.40 0.60 0.80 1.00 1.20

exchangeable Mg

Yiel

d (t/

ha)

B

y = 7.86x + 43.84

-

20

40

60

80

100

120

- 1.00 2.00 3.00 4.00 5.00

exchangeable Ca

Rela

tive

Yiel

d (%

)

D

y = 34.65x + 36.84

-

20

40

60

80

100

120

0.20 0.40 0.60 0.80 1.00 1.20

exchangeable Mg

Rela

tive

Yie

ld (%

)

Figure 3. Relationship between rice yield and exchangeable Ca (A), relative yield and exchangeable Ca (B), yield and exchangeable Mg (C) and relative yield with exchangeable Mg (D) for the second

season. (R2 < 0.01)

Further indication of the improvement of rice yield due to GML application is shown in Figure 3C and 3D, where yield and relative yield, respectively when exchangeable Mg was increased.

CONCLUSIONS Ground magnesium limestone and organic fertilizer applied at appropriate rates on acid sulfate soils can produce rice yield comparable to that of the granary areas of Malaysia. The result of this study showed that rice yield could be as high as 7.5 t/ha using current technology, applying 4 t GML/ha in combination with an organic fertilizer.


143

ACKNOWLEDGENTS The authors would like to thank Universiti Putra Malaysia and the Ministry of Science, Technology and Innovation Malaysia for financial and technical support.

REFERENCES

[1] A.K. Alva, C.J. Asher, D.G. Edwards. The role of calcium in alleviating aluminum toxicity. Aust. J. Soil Res., 37, pp. 375-383, (1986). [2) X. Arulando, S.P. Kam. Management of acid sulfate soils in the Muda Irrigation Scheme, Kedah, Peninsular Malaysia. In International Institute for Land Reclamation and Improvement; Dosh, H., Breemenr N., Eds.; Publ. 31, Wageningen, The Netherlands, pp: 195-212, (1982). [3] D.L. Dent. Acid Sulfate Soil: A Baseline for Research and Development; International Institute for Land Reclamation and Improvement: Wageningen, The Netherlands, Publ. 39, (1986). [4] H.D. Djia. Geomorphology. In Geology of the Malay Peninsula; Gobbet D.S., Hutchison, C.H., Eds.; John Wiley & Sons, New York, pp: 13-24, (1973). [5] A. Dobermann, T. Fairhurst. Rice: Nutrient Disorders and Nutrient Management; Phosphate Institute of Canada and International Rice Research Institute, Los Banos, The Philippines, (2000). [6] P.B. Hoyt, R.C. Turner. Effects of organic materials added to very acid soil on pH, aluminum, exchangeable bases, ammonium, and crop yield. Soil Sci., 119, pp. 227-237, (1975). [7] N.V. Hue, I. Amien. Aluminum detoxification with green manures. Commun. Soil Sci. & Plant Anal., 20, pp. 1499-1511, (1989). [8] O. Husson, P.H. Verburg, Mai Thanh Phunh. Special variability of acid sulfate soils in the Plain of Reeds, Mekong Delta, Vietnam. Geoderma, 97, pp.1-19, (2000). [9] P.A. Moore, W.H. Patrick. Metal availability and uptake by rice in acid sulfate soils. In International Institute for Land Reclamation and Improvement; Dent, D.L, Mensvoort, M.E.F., Eds.; Publ. 53, Wageningen, The Netherlands, pp: 205-224, (1993). [10] S. Muhrizal, J. Shamshuddin, I. Fauziah, M.H.A. Husni. Alleviation of aluminum toxicity in acid sulfate soils in Malaysia using organic materials. Commun. Soil Sci. & Plant Anal., 34, pp. 2999-3017, (2003). [11] S. Muhrizal, J. Shamshuddin, I. Fauziah, and M.H.A. Husni. Changes in an iron-poor acid sulfate soil upon submergence. Geoderma, 131, pp. 110-122, (2006). [12] M.M Nhung, F.N. Ponnamperuma. Effects of calcium carbonate, manganese dioxide, ferric hydroxide and prolonged flooding and electrochemical changes and growth of rice on a flooded acid sulfate soil. Soil Sci., 102, pp. 29-41, (1966). [13] J.B. Ooi. Land, People and Economy of Malaya. Longmans; London, (1964). [14] M. Palhares. Recommendation for fertilizer application for soils via qualitative reasoning. J. Agric. Sys., 67, pp. 21-30, (2000). [15] F.N.Ponnaperuma, T. Attanandana, G. Beye. Amelioration of three acid sulfate soils for lowland rice. In International Institute for Land Reclamation and Improvement; Dosh, H., Ed.; Publ.18, Wageningen, The Netherlands, pp: 391-406, (1973). [16] J. Shamshuddin, I. Che Fauziah, H.A.H. Sharifuddin. Effects of limestone and gypsum application to a Malaysian Ultisol on soil solution and yields of maize and groundnut. Plant and Soil, 137, pp. 45-52 (1991). ]17] Soil Survey Staff. Soil Taxonomy: A Basic Soil Classification for Making and interpreting Soil Surveys. USDA, Natural Resources Conservation Services, Washington, DC, (1999). [18] S.W. Soo,. Semi-detailed Soil Survey of Kelantan Plain. Ministry of Agriculture & Rural Development, Kuala Lumpur, (1975). [19] C.C. Ting, S. Rohani, W. S. Diemont, B.Y Aminuddin. The development of an acid sulfate soil in former mangroves in Merbok, Kedah, Malaysia. In International Institute for Land Reclamation and Improvement; Dent, D.L., Mensvoort, M.E.F., Eds.; Publ. 53, Wageningen, The Netherlands, pp: 95-101, (1993). [20] K.T. Tran, T.G. Vo. Effects of mixed organic and inorganic fertilizers on rice yield and soil chemistry of the 8th crop on heavy acid sulfate soil (Hydraquentic Sulfaquepts) in the Mekong Delta of Vietnam. A paper presented at the 6th International Symposium on Plant-Soil at Low pH. August 1-5, 2004; Sendai: Japan, (2004). [21] A.Wakley, I.A. Black. An examination of the Degtjrref Method for determining organic matter, and a proposed modification of chromic acid titration method. Soil Sci., 37, pp. 29-38, (1934).

Workshop IC-PLR 2006 – Theme C – Land Evaluation and Land Degradation

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WORKSHOP THEME C – LAND EVALUATION AND LAND DEGRADATION

Sub-theme : Land evaluation for sustainable land management & policy making A. Verdoodt, E. Van Ranst

Paper/poster : Oil palm and rubber production model for substituting rubber with oil palm and evaluating to establish oil palm into Northeast Thailand – S. Pratummintra, E. Van Ranst, H. Verplancke Paper/poster : Soil properties and biological diversity of undisturbed and disturbed forests in Mt. Malingdan, Philipines - Renato D. Boniao, Rosa Villa B. Estoista, Carmelita G. Hansel, Ron de Goede, Olga M. Nuneza, Brigida A. Roscom, Sam James, Rhea Amor C. Lumactud, Mae Yen O. Poblete, Nonillon Aspe

Sub-theme : Land degradation : pressures, indicators and responses W. Cornelis, D. Gabriels, H. Verplancke

Paper/poster : Indicators and participatory methods for monitoring land degradation. A case study in the Migori district of Kenya – Vincent de Paul Obade, Eva De Clercq Paper/poster : Proposed plan of action for research on desertification in the Sudan : Gezira and Sennar States – Kamal Elfadil Fadul, Fawzi Mohamed Salih Paper/poster : Diagnostic of degradation processes of soils from Northern Togo (West Africa) as a tool for soil and water management – Rosa M. Poch, Josep M. Ubalde

Conclusions


145

Sub-theme : LAND EVALUATION FOR SUSTAINABLE LAND MANAGEMENT & POLICY MAKING

Overview of the latest research in land evaluation at the Laboratory of Soil Science

A. Verdoodt & E. Van Ranst

Laboratory for Soil Science, Ghent University, Gent, Belgium

New paradigms interpret soil as a habitat for living systems, delivering a wide range of hugely valuable ecosystem functions such as food security, clean air and water, biodiversity, and cultural heritage. Soil erosion, contamination, and organic matter decline, are only a few examples of threats that hypothecate soil functioning all over the world. Although there is good agreement on the importance that should be given to sustainable land management, understanding about how the principal drivers and configurations of the soil system differ between ‘land-use-soil-climate’ combinations is still incomplete and hampers the development of scientifically sound land use policies. In response to these new demands, the research in land evaluation conducted at our laboratory focuses on three major aspects : (1) design of soil/land information systems providing georeferenced climate, landscape and

soil data; (2) design of land evaluation tools for specific land uses, making full use of the increased

availability of soil data; and (3) identification of soil quality indicators, baselines and thresholds for monitoring soil

quality and designing soil protection policies. In the first research aspect, land and soil information systems, together with the new

techniques of data gathering based on remote sensing, have become indispensable tools for the presentation and analysis of soil characteristics. Geographic information science and relational database software were combined to capture the spatial as well as the numerical and descriptive data gathered during the traditional soil surveys organised in Rwanda and the Democratic Republic of Congo. The soil information system of Rwanda, comprising 43 soil maps and 43 digital terrain models at a scale of 1:50,000, was further extended with climatic records at monthly and daily temporal resolutions. Additionally, the generation of simplified soil maps at scale 1:250,000, revealed the diversity in land resources at national level. With the creation of a soil profile database, containing 1,834 described and analysed soil profiles, the soil information system is a powerful tool for agricultural and land use planning purposes in Rwanda. A similar soil information system is being created for the Democratic Republic of Congo. In addition, the detailed, semi-detailed and reconnaissance soil maps and the abundant morphological and analytical soil profile data gathered in Rwanda, Burundi and the DR of Congo, enabled us to develop a scientifically sound Great Lakes Area SOTER (Soil and Terrain) Database. SOTER mapping is similar to physiographic soil mapping but with stronger emphasis on the terrain-soil relationship. A SOTER unit represents a unique combination of terrain and soil characteristics. The methodology focuses on the identification of areas of land with a distinctive pattern of landform, lithology, surface form, slope, parent material and soil. During the design of the SOTER database of Central Africa, a physiographic map has been derived after analysis of SRTM satellite data of the region. Geological maps at different scales were translated into lithological maps. These thematic maps were combined to give the SOTER unit maps at scale 1:1M for Rwanda and Burundi


146

and at scale 1:2M for the Democratic Republic of Congo. Much more additional information characterising the non-mappable terrain and soil components has been selected, harmonised and inserted in a large relational database containing a wealth of descriptive and analytical soil profile data.

The second research aspect comprises the development of (1) a spatially and temporally explicit multi-scale decision support system that reveals the biophysical indicators affecting land use choices of different stakeholders, and (2) a web-based land evaluation system to perform agricultural productivity assessments in developing countries. The multi-scale decision support system comprises three different environmental assessment tools, designed to run with data supplied by traditional soil surveys and organised into a land information system. A qualitative land suitability classification procedure is adapted to translate the large-scale biophysical data, into five suitability classes. At local scale, the productivity of the soil units is estimated using a three-level hierarchical crop productivity estimator. At the smallest spatial and temporal resolution, a daily water balance approach is linked to a crop growth model. The decision support system was applied and validated using the land information system of Rwanda. It revealed the biophysical properties affecting national crop regionalisation, regional crop productivity differences, and local intensification options. The Web-based land evaluation system (WLES) is designed in such a way that the system operates either as a Web Application or as a Web Service via the Internet. Implemented on top of the .NET platform, the WLES has a loosely coupled multi-tier structure which seamlessly integrates the land evaluation knowledge engine and the spatial database. The WLES not only provides productivity assessment service in a user-friendly way to agricultural researchers, engineers, farm managers, policy makers and planners but also acts as a building block of a larger system such as that of land taxation, impact of climate change on agriculture, population carrying capacity, and so forth.

The third research aspect merely focuses on the assessment of the overall soil quality, reflecting the capacity of the soil to function sustainably. This encompasses the identification and selection of scientifically sound soil quality indicators to monitor the changes in the soil quality status. These changes are determined relative to a baseline value and are also compared to a threshold value, indicating a critical soil status limiting or threatening the sustainable functioning of the soil. The ongoing ENVASSO (ENVironmental ASsessment for SOil monitoring) project reviews and defines indicators that encompass the main threats to soil degradation in Europe. Identification of the soil quality indicators for each threat is based on an extensive literature review with the reports of technical working groups within the development of the EU Thematic Strategy on Soil Protection as main source documents. Selection criteria for each indicator are based on its significance, analytical soundness, measurability, policy relevance, geographical coverage, availability of baselines and thresholds and its comprehensibility. Protocols and procedures for data collection, sampling, storage, manipulation, interpretation and reporting will be developed. The project will report the current monitoring of the soil quality indicators, will identify gaps in the national and European wide monitoring systems and will provide guidelines for the development of a soil policy. Soil mapping and identification of sound soil quality indicators can also be realised through the incorporation of ethnopedological knowledge. In Mexico, a local soil classification scheme was formalised and compared to the international USDA soil classification system. Both similarities and differences, revealing complementarities, were identified. Critical is the evaluation of the topsoil characteristics, as the monitoring of the topsoil dynamics is fundamental to sustainable land management. In a study for sustainable land management of mountain karst areas in Vietnam, local inhabitants are also participating in the generation of soil maps and the identification and classification of local indicators of soil quality. Laboratory results confirmed the validity of vernacular knowledge for


147

identifying and classifying local indicators of soil quality and soil fertility, compared to scientific standards applied in Vietnam and in the international community.

REFERENCES

Research papers, Laboratory of Soil Science

[15] N. Barrera-Bassols, J.A. Zinck, E. Van Ranst. Symbolism, knowledge and management of soil and land resources in indigenous communities : ethnopedology at global, regional and local scales. Catena 65, pp. 118-137 (2006). [16] N. Barrera-Bassols, J.A. Zinck, E. Van Ranst. Local soil classification and comparison of indigenous and technical soil maps in a Mesoamerican community using spatial analysis. Geoderma (in press, 2006). [17] B. Mintesenot, H. Verplancke, E. Van Ranst, H. Mitiku. Examining traditional irrigation methods, irrigation scheduling and alternate furrows irrigation on Vertisols in Northern Ethiopia. Agricultural Water Management 64, pp. 17-27 (2004). [18] D. P. Shrestha, J. A. Zinck, E. Van Ranst. Modelling land degradation in the Nepalese Himalaya. Catena 57, pp. 135-156 (2004). [19] H. Tang, E. Van Ranst. Is highly intensive agriculture environmentally sustainable? A case study from Fugou county, China. Journal of Sustainable Agriculture 25 (3), pp. 91-102 (2005). [20] H. Tang, J. Qiu, E. Van Ranst, C. Li. Estimations of soil organic carbon storage in cropland of China based on DNDC model. Geoderma 134, pp. 200-206 (2006). [21] E. Van Ranst, F. O. Nachtergaele, A. Verdoodt. Evolution and availability of geographic databases. In : Innovative techniques in soil survey : “Developing the foundation for a new generation of soil resource inventories and their utilisation”. H. Eswaran, P. Vijarnsorn, T. Vearasilp, E. Padmanabhan (eds.). Land Development Department, Chattuchak, Bangkok, Thailand, pp. 223-236 (2004). [22] Van Vosselen, H. Verplancke, E. Van Ranst. Assessing water consumption of banana : traditional versus modelling approach. Agricultural Water Management 74, pp. 201-218 (2005). [23] Verdoodt, E. Van Ranst, W. Van Averbeke. Modelling crop production potentials for yield gap analysis under semi-arid conditions in Guquka, South Africa. Soil Use and Management 19, pp. 372-380 (2003). [24] Verdoodt, E. Van Ranst, H. Verplancke. Integration of soil survey data, Geographic Information Science and land evaluation technology for land use optimisation in Rwanda. In : Innovative techniques in soil survey : “Developing the foundation for a new generation of soil resource inventories and their utilisation”. H. Eswaran, P. Vijarnsorn, T. Vearasilp, E. Padmanabhan (eds.). Land Development Department, Chattuchak, Bangkok, Thailand, pp. 365-380 (2004). [25] Verdoodt, E. Van Ranst, L. Ye. Daily simulation of potential dry matter production of annual field crops in tropical environments. Agronomy Journal 96, pp. 1739-1753 (2004). [26] Verdoodt, E. Van Ranst, L. Ye, H. Verplancke. A daily multi-layered water balance to predict water and oxygen availability in tropical cropping systems. Soil Use and Management 21, pp. 312-321 (2005). [27] Verdoodt, E. Van Ranst. Environmental assessment tools for multi-scale natural resources information systems. A case study of Rwanda. Agriculture, Ecosystems and Environment 114, pp. 170-184 (2006). [28] L. Ye, E. Van Ranst. Population carrying capacity and sustainable agricultural use of land resources in Caoxian County (N. China). Journal of Sustainable Agriculture 19 (4), pp. 75-94 (2002). [29] L. Ye, E. Van Ranst, A. Verdoodt. Design and implementation of a Web-based land evaluation system and its application to land value tax assessment using .NET technology. In : Innovative techniques in soil survey : “Developing the foundation for a new generation of soil resource inventories and their utilisation”. H. Eswaran, P. Vijarnsorn, T. Vearasilp, E. Padmanabhan (eds.). Land Development Department, Chattuchak, Bangkok, Thailand, pp. 183-196 (2004). [30] L. Ye, E. Van Ranst. Development of a Web-based land evaluation system and its application to population carrying capacity assessment using .NET technology. In : Proc. of the AFITA/WCCA 2004 Joint Congress on IT in Agriculture. F. Zazueta, S. Ninomiya, R. Chitradon (eds.). National Science and Technology Development Agency, Pathumthani 12120, Thailand, pp. 409-414. [31] J.A. Zinck, J.L. Berroteran, A. Farshad, A. Moameni, S. Wokabi, E. Van Ranst. Approaches to assessing sustainable agriculture. Journal of Sustainable Agriculture 23, pp. 87-109 (2004).


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Other interesting papers

[32] S. S. Andrews, D. L. Karlen, C. A. Cambardella. The soil management assessment framework : a quantitative soil quality evaluation method. Soil Science Society of America Journal 68, pp. 1945-1962 (2004). [33] M.A. Arshad, S. Martin. Identifying critical limits for soil quality indicators in agro-ecosystems. Agriculture, Ecosystems and Environment 88, pp. 153-160 (2002). [34] P. S. Bindraban, J. J. Stoorvogel, D. M. Jansen, J. Vlaming, J. J. R. Groot. Land quality indicators for sustainable land management : proposed method for yield gap and soil nutrient balance. Agriculture, Ecosystems and Environment 81 (2), pp. 103-112 (2000). [35] M. R. Carter. Soil quality for sustainable land management : organic matter and aggregation interactions that maintain soil functions. Agronomy Journal 94, pp. 38-47 (2002). [36] B. Govaerts, K. D. Sayre, J. Deckers. A minimum data set for soil quality assessment of wheat and maize cropping in the highlands of Mexico. Soil and Tillage Research 87, pp. 163-174 (2006). [37] J. E. Herrick. Soil quality : an indicator of sustainable land management? Applied Soil Ecology 15, pp. 75-83 (2000). [38] E. M. Hillyer, J. F. McDonagh, A. Verlinden. Land-use and legumes in northern Namibia – The value of a local classification system. Agriculture, Ecosystems and Environment (in press, 2006). [39] M. Igué, T. Gaiser, K. Stahr. A soil and terrain digital database (SOTER) for improved land use planning in Central Benin. European Journal of Agronomy 21, pp. 41-52 (2004). [40] R. Mermut, H. Eswaran. Some major developments in soil science since the mid-1960s. Geoderma 100, pp. 403-426 (2001). [41] E. W. Murage, N. K. Karanja, P. C. Smithson, P.L. Woomer. Diagnostic indicators of soil quality in productive and non-productive smallholders’fields of Kenya’s Central Highlands. Agriculture, Ecosystems and Environment 79, pp. 1-8 (2000). [42] S. A. Rezaei, R. J. Gilkes, S. S. Andrews, H. Arzani. Soil quality assessment in semi-arid rangeland in Iran. Soil Use and Management 21, 402-409 (2005). [43] R. Ryder. Local soil knowledge and site suitability evaluation in the Dominican Republic. Geoderma 111, pp. 289-305 (2003). [44] D. Wu, Q. Yu, C. Lu, H. Hengsdijk. Quantifying production potentials of winter wheat in the North China Plain. European Journal of Agronomy 24, pp. 226-235 (2006).


149

OIL PALM AND RUBBER PRODUCTION MODEL FOR SUBSTITUING RUBBER WITH OIL PALM AND EVALUATING

TO ESTABLISH OIL PALM INTO NORTHEAST THAILAND

S. Pratummintra1, E.Van Ranst2, H.Verplancke2, A. Verdoodt2

1Department of Agriculture, Bangkok, Thailand. 2Ghent University, Ghent, Belgium.

Abstract Oil palm (Elaeis guineensis Jacq.) is a cash crop that can be exploited all the year round. However, up to now, oil palm production in Thailand has been very low because of some limiting climatic, edaphic, crop-specific and management parameters. Especially the soil water deficit reported is restricting oil palm yields. The crop evapo-transpiration in an immature state (1-7 years) was about 4.5-5.0 mm.d-1, while the mature palm need more amounting to about 5.0-5.5 mm.d-1. These requirements further increase from 6.5-7.5 mm.d-1 in drought period, depending on soil texture and soil water content. An area of about 2.012 million rais (0.32 million hectare ) of oil palm plantation was identified from the LANDSAT 5 TM image data (date in 2004) and mapped using ARCVIEW ver.3.2 a. Land evaluation techniques were designed to classify the plantations based on their production potential. They were grouped into 4 potential production classes: (1) higher than 25 ton.ha-1.yr-1

(80,708 ha); (2) between 16-25 ton.ha-1.yr-1 (113,956 ha); (3) between 10-16 ton.ha-1.yr-1 (125,931 ha) and (4) lower than 10 ton.ha-1.yr-1 being land classified as unsuitable for oil palm (68 ha). Rubber plantation occupying about 1.6 million ha in East and South Thailand were identified from the same satellite image data. In addition, the rubber planting areas were classified by using the Rubber Production Model. Comparison of the productivity of both cash crops resulted in the identification of areas with a rubber productivity less than 1,500 kg.ha-1.yr-1 that could be profitably substituted by oil palm, giving a production exceeding 16 ton.ha-1.yr-1. Finally, the oil palm production model was integrated with a soil water balance model and applied to evaluate the water-limited production potential in Thabor, Nongkai Province, where the annual rainfall averaged less than 1,500 mm. One found that oil palm should be planted in an area about 20,000 ha and that expected yields are high enough for setting-up the bio-diesel project.

INTRODUCTION

Oil palm (Elaeis guineensis Jacq.) is one of an economic crop in the southern part of Thailand that can be exploited the whole year. However, the production in is limited by many parameters related to climate, soil fertility, oil palm variety and management technology. An optimized field management is required to continuously maintain a minimum bunch production, as oil palm production will be reduced when it is subjected to water stress [1,3,6,8,9,11,15]. The optimum average annual rainfall for oil palm is about 2,000 mm with a monthly distribution of about 120 mm [5,6]. In Malaysia, the water requirement of oil palm were determined by using a lysimeter filled with soil of the Munchong Soil Series (Tropeptic Haplorthoxs). One found that the daily potential evapo-transpiration (ETp) during the immature stage (1-7 year after planting (YAP)) is about 4.5-5.0 mm, and increased to 5.0-5.5 mm in a mature stage (more than 8 YAP). In the dry season, the daily ETP increased up to 6.5-7.5 mm, while it decreased in the rainy season at about 3.0-3.5 mm [4, 12].

The drought period affects the physiological process and stomatal resistance of oil palm, triggering the closure of the stomata. Consequently, the leaf temperature increases, while the rate of photosynthesis was decreased [10]. Upon the decrease in photosynthetic assimilates, the rate of female inflorescence abortion increases, while the sex ratio decreases, reducing oil palm production [2]. Caliman found that the stomatal resistance of oil palm decreased when available soil water content. It mean that the stomatal resistant decreased when the soil moisture content decreased. Further research is required to identify the


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appropriate management techniques for oil palm plantation in stress area such as Northeast Thailand [1].

In Thailand, oil palm plantation are extending very quickly, with an estimated area of 320,000 that will be exploited at the end of 2006. Some of the new plantation areas face strong limitations due to low rainfall and high water deficiencies. In these areas, the annual water deficit is about 208 to 675 mm within a period of 2-6 months [7,16,17]. Mapping the potential production and simulating soil water balance are important tools for guiding the farmers in their management strategies, oriented to a maintenance of high yield.

On the other hand, the Thai government policy has been assigned to control the rubber plantation at about 2 million ha in order to maintain a balanced world demand and supply, and to stabilize the rubber price. Rubber production area, with a productivity less than 1,500 kg.ha-1, will therefore be converted to other economic crops such as oil palm.

This study objectives are; 1. To locate the oil palm plantation and organize this information to GIS database; 2. To evaluate and map the production potential of oil palm and rubber; and 3. To determine the area of rubber that should be substituted with oil palm.


Materials Digital Images Data and Image Analysis Module The Image Analysis is an extension module within ARCVIEW GIS ver. 3.2a. This module is use to allocate and map the actual extension of rubber plantations and oil palm orchards from the false color composite image by using the visualized technique. The false color composite was formulated from 3 bands (5, 3, 2) of the following LANDSAT 5 TM digital data:

1. Path 127 Row 48, Digital Band 5 3 2, date 26 January, 2005. 2. Path 127 Row 49, Digital Band 5 3 2, date 20 April, 2004. 3. Path 127 Row 50, Digital Band 5 3 2, date 7 March, 2004. 4. Path 128 Row 47, Digital Band 5 3 2, date 16 February, 2004. 5. Path 128 Row 48, Digital Band 5 3 2, date 2 February, 2005. 6. Path 128 Row 50, Digital Band 5 3 2, date 6 March, 2005.

Climate Digital Database Climatic data reported during the last twenty years (1986-2005) in the nearby meteorological stations were used to run the land suitability model for oil palm. Required input data were maps of monthly rainfall, temperature and evaporation. Soil survey and analytical data The provincial soil maps at a scale of 1:50,000 was used as a basal map for soil surveying. Soil sample in each depth were brought up by Edelman Auger and determined moist soil color by using Monsel Soil Color Chart, texture by feeling method, structure and clay coating by eye lens, pH with soil pH kit. Then, the soil series was determined by comparing the field characteristics with the typical soil profile characteristics. On the other hand, a composite


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sample of each soil horizon was prepared from 25 sampling pit and use for phisico-chemical analysis such as particle size, CEC, available P, %O.C etc. The analytical data of each soil were stored in the database. Methods The procedures in this study were applied from: 1. The land evaluation technique [18] 2. The yield gap analysis [19] 3. The Rubber Production Model [13,14] 4. The soil water balance [20, 21] The environmental crop requirements that need to considered to asses the suitability area for oil palm are related to climate and soil as shown in Table 1. The steps of working (Fig. 1) started from collecting a climatic and soil data. The parametric approach , which mentioned in land evaluation technique, was used to calculate the land index by scoring the parameter with the crop requirement table 1). Field surveying was done for collecting the field soil data and oil palm yield. Together with the field data and land index, the production potential model was classified to 4 classes, named as;

1. L1 or very suitable (Land index is higher than 76), the production potential is more than 25 ton.ha-1.yr-1.

2. L2 or suitable (Land index is 51-75), the production potential is between 13.1-25 ton.ha-1.yr-1.

3. L3 or marginal area (Land index is 26-50), the production potential is 9.5-13.0 ton.ha-1.yr-1.

4. L4 is not recommended (Land index is lower than 25). The production potential is less than 9.5 ton.ha-1.y-1.

The result of the model was projected in the map with the GIS working scheme (Fig. 2). For rubber, plantations with a potential yield exceeding 1,500 kg dry rubber.0ha-1.yr-1 were classified as suitable. All others with a lower production potential should be substituted with oil palm to get a better benefit.


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Limitation classes and Indexes Class S1 S2 S3 N Limitation 0 1 2 3 4

Characteristics

Index 100 95 85 60 40 25 0 Rainfall and Distribution

Average annual Rainfall (mm) (p) 25003500

2000 3700

1700 4000

1450 5000

1350 5500

1250 6000

600 7000

Drought period (months p<1/2 ETc) 0 1 2 3 4 6 8

Mean maximum temperature ( °C) 25 29

22 27

20 29

18 32

16 35

14 37

10 40

Mean minimum temperature ( °C) >20 20 18 16 14 12 10 Annual mean temperature ( °C) >25 25 22 20 18 16 10

Average annual wind speed (m.s-1) 5 8

4 9

3 10

2 12

1 15

0 20

25

Sunshine radiation (MJ.m2) 13 15

11 16

9 17

8 19

7 21

5 23

3 25

Sunshine ratio (n/N) >0.75 0.75 0.60 0.45 Topology (%slope) 0 4 8 16 30 50 80 Wetness (w) Flood Duration Drainage classes

F0 Mod. Imp.

Well

F1

s. poor

F2

Poor&aeric

Poor but drain

F3

v.poor,excess.

Physical Properties (s) Soil texture and structure

C>60sC<60s, SiCs

SiCL, SC CL, L

SCL, Si

SiL, SL, LcS, C>60v C<60v

fS

Ls, Lcs,fs,s,Cs

Cm,

SiCm

Gravels (%) 0 3 15 35 55 75 100 Soil depth (cm) >150 150 100 50 25 15 5 CaCO3 (%) 0 1 5 10 15 20 30 Gypsum (%) 0 0.5 2 3 5 7 10 Soil fertility (f) Ex. CEC) (cmol (+) kg clay-1) >16 16 10 8 6 4 1

pH 1:1 H2O 5.8 6.0 5.5

6.5 4.5

7.0 3.5

7.5 2.5

8.0 2.0

9.0 1.5

O.M (%) >1.2 1.0 0.8 0.6 0.4 0.2 0.1 ECe (dS m-1) 0 1 2 3 4 5 6

After: [13, 18]

Table 1 (Cont) : Soil characteristics requirement for evaluating for land suitability for oil palm


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Figure 1 : Working scheme for Land Evaluation for Rubber and Oil Palm

Figure 2 : Working scheme for GIS

Climatic data- Rainfall- Temperature- Relative humidity

Crop Requirement Table - Climatic characteristics - Soil characteristics (Table 1)

Symbols and Suitability Class CI = Climatic indexes CI1 = Very suitable, index >75 CI2 = Suitable, index 51-75 CI3 = Marginal, index 25-20 CI4 = Non-suitable, index <25

Parametric Approach

2210....321

−= n

AnxAxAACI

A = index of parametersn = number of parameters

Workai = Working ability index Ferai = Soil Fertility index Saltai = Soil Salinity Index Physi = Phisico-chemical index (pH, CEC, %O.M)

Soil Characteristics

610aixPaiWaixFaixPSSI =

A = index of parametersn = number of parameters

Land suitability index (LI)

210CIxSILI =

Field study - Actual Yield - Field management

Production Potential Y = a + b(LI) a = intersect b = Slope

Physical data

-Administration Boundary

- Climatic Database

- Soil Database

LANDSAT 5 TM 2005

-Rubber existing area- Oil palm existing area

- Rubber (Pratummntra,et al. 2000)

- Oil palm (Pratummntra,et al. 2005)

Map of Production Potential

-Rubber - Oil palm


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Production potential modeling in a pilot area The Thai government designed a policy that favors the bio-energy to substitute the petroleum energy. Oil palm is one of the oil crops that will be used to produce bio-diesel (B100). The target for new oil palm plantings is about 1 million ha. This means that the government needs to know which areas are most suitable to establish the new oil palm plantations.

In Northeast Thailand, a pilot project for oil palm cultivation has been set up. However, this area is characterized by low rainfall, high evaporation rates, and high light intensities that are serious limitations for oil palm. Therefore, land evaluation models were designed and applied to analyse the problem. Soil water balances were studied. Based on that information, the area of the Tharbor Irrigation Project was selected for the pilot project.

The LANDSAT images were use to analyze land cover type and water system (Fig. 4a). The flooding areas were determined by comparing the GIS data with the image data. The ground control points were located with the GPS GARMIN GPS 12 Model. A soil survey was performed around the area, and the soil texture was mapped. The irrigation canals were also drawn on the map. Fig 4b shows the spatial distribution of soil texture and the irrigation system.

The soil water balance, based on Sys et al. [18] Verplancke [20], was then simulated to calculate the soil water deficit or water needs according to soil texture. Finally the production potential was mapped (Fig. 4C).

RESULTS

Oil palm production potential The first step of the land evaluation consisted of an analysis of the climatic data (Fig.3 A-E). The suitability classes of climate (Fig.3 F) show that the highly suitable areas are found in the South and some regions of East Thailand. Extension of Oil Palm Plantations The oil palm plantations identified from the LANDSAT images are located in the southern provinces occupying an area of 320,138 ha, and in the eastern provinces, occupying an area of 1,889 ha.

The maps of the plantations were overlaid with the production potential maps by using the Geoprocessing Module in GIS ARCVIEW 3.2a. Then, the existing area of oil palm plantation were classified into the 4 suitability classes (Table 2). The results have been shown inTable 2. About 70.0 ha of oilpalm plantations, almost entirely situated in the south were classified as “not recommendable”. Next, 124,912.2 ha in the southern and 1,019.5 ha in the eastern coast, were classified as marginal for oil palm production. The suitable lands occupy 113,086.4 ha in South and 869.4 ha in East. And finally, very suitable land was only found in the south, with an extension of about 82,071.5 ha.


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A Min. Temperature index B Max. Temperature index C Mean temperature index

D Rainfall index E Drought period index F Climatic index

Figure 3 : The Result of Climate Classification for Oil Palm by using Parametric Approach

Production Potential (ton.Ha-1.year-1) Province Name <9.5 9.5-13.0 13.1-25.0 >25.0 Total Southern Provinces 68.8 124,912.2 113,086.4 82,071.5 320,138.7 Chumporn - 22,694.9 33,346.9 2,090.1 58,131.7 Krabi - 45,872.0 38,531.2 59,846.2 144,249.3 Nakorn Srithammarat - 995.5 177.0 9.4 1,181.9 Naratiwat 35.7 19.5 510.1 - 565.3 Pang-nga - 5,450.7 2,522.2 1,759.4 9,732.3 Pattalung 25.8 - - - 25.8 Ranong - 1,696.6 - - 1,696.6 Songkhla - 582.7 3,652.0 - 4,234.7 Satun - 10,145.9 4,176.6 10,719.0 25,041.6 Surat Thani - 34,249.9 27,073.8 3,539.2 64,863.0 Trang - 3,204.3 3,096.8 4,108.2 10,409.1 Yala 7.2 - - - 7.2

East Provinces 0.2 1,019.5 869.4 - 1,889.0 Chonburi - 424.6 814.7 - 1,239.4 Rayong - 582.4 - - 582.4 Trad 0.2 12.5 54.6 - 65.6

Total Area 70.0 125,931.7 113,955.8 82,071.5 322,028.0

Table 2 : The production potential classification for an existing oil palm plantation


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Area of Rubber Plantation Analysis of the same LANDSAT images revealed that the total area of rubber is about 1.969 million ha, mainly located in the south for more than 85% (Table 3).

Unit : ha Low Production Potential Province Name Low land High land High Production Total

Southern Provinces 278,102.6 422,726.2 998,552.0 1,699,381.0 Chumporn 43,490.7 0.0 20,601.9 64,092.6 Krabi 4,865.0 11,689.4 77,253.9 93,808.3 Nakorn Srithammarat 13,415.8 47,092.8 145,306.1 205,814.7 Naratiwat 15,845.9 234.9 140,748.0 156,828.8 Pattani 6,990.7 13,181.3 24,377.4 44,549.4 Pang-nga 32,302.9 39,542.6 30,449.8 102,295.2 Pattalung 17,919.4 16,975.4 47,015.8 81,910.6 Phukhet 216.8 8,559.7 8,817.9 17,594.4 Ranong 457.6 8,819.4 7,793.9 17,070.9 Songkhla 58,736.6 77,858.9 85,462.2 222,057.8 Satun 5,671.7 6,859.5 30,101.1 42,632.3 Surat Thani 31,421.4 29,519.4 219,858.6 280,799.4 Trang 38,497.0 34,684.6 133,339.5 206,521.1 Yala 8,271.2 127,708.5 27,425.8 163,405.4 East Provinces 45,852.3 23,363.5 140,753.6 209,969.6 Chanthaburi 14,303.0 5,110.2 33,265.1 52,678.4 Chonburi 6,998.9 1,189.8 13,432.6 21,621.3 Chachoengsao 3,591.5 11.4 8,705.8 12,308.6 Rayong 8,941.9 15,624.2 65,098.2 89,664.3 Trad 10,942.2 1,396.6 19,338.7 31,677.6 Prachinburi 0.0 0.0 408.2 408.2 Srakaew 1,074.9 31.4 505.0 1,611.2 Total Area 323,954.9 446,089.9 1,139,305.8 1,909,350.6

Table 3 : An existing area of rubber plantation Establishing oil palm in northeast Thailand The area of Huimong Irrigation project is about 133,944 ha. An overview of the soils identified in the area has been giving in Table 4, summarising the soil series together with their national and international classification names.


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Soil Series USDA-1975 National Borabu fine loamy, mixed, Aquic Plinthustults Red-Yellow Podzolic Soils Korat fine loamy, siliceous, Oxic Paleustults Gray Podzolic Soils Roiet fine loamy, kaolinitic, Aeric Paleaquults Low Humic Grey Soils Renu fine loamy, mixed, Plinthic Paleaquults Hydromorphic Gray Podzolic Soils Sanpaya fine loamy, mixed, Typic Ustifluevents AlluvialSoils Siton fine loamy, mixed, Aeric Tropaquepts Low Humic Grey Soils Satuk fine loamy, kaolinitic, Typic Paleustults Red-Yellow Podzolic Soils Tatphanom fine loamy, mixed, Ustic Haplustalfs Non Clacic Brown Soils Warin fine loamy, siliceous, OxicPaleustults Red-Yellow Podzolic Soils Nakornpanom fine clayey, mixed, Aeric Paleaquults Low Humic Grey Soils Pimai fine clayey, mixed, Vertic Tropaquepts Hydromorphic Alluvial Soils Phen clayey skeletal, mixed, Typic Plinthaquults Low Humic Grey Soils Phonpisai clayey skeletal, mixed, Typic Plinthustults Red-Yellow Podzolic Soils Ratburi fine clayey, mixed, Aeric Tropaquepts Hydromorphic Alluvial Soils Srisongkham fine clayey, mixed, Vertic Tropaquepts Hydromorphic Alluvial Soils

Table 4 : Soil Taxonomy in the Study area

An area of about 30,169 ha has a clayey texture while the sandy soils cover about 96,420 ha. In sandy soil, the production potential is higher because these areas are located in the low terraces, which are flat and have a high level of ground water. An overview on the spatial distribution of these results has been shown in Figure 4, while more detailed data are provided in Table 5.

A

B

C

Figure 4 : The Result LANDSAT Image, Determine the Water Body, Irrigation system, and Production potential in the study area

Irrigation line Huimong Administration Boundary Reservoir Flooding area Sandy soil Clayey soil

<9.5 t ha-1 y-1 9.5-15.0 t ha-1 y-1 15.1-20.0 t ha-1 y-1 >20.0 t ha-1 y-1


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Soil Type Soil series Symbol Production Potential Area Clayey 30,169 Alluvium complex AC 15.1-20.0 6,256 Nakornpanom Nn 13.0-15.0 7,464 Pimai Pm 15.1-20.0 2,870 Phen Pn 13.0-15.0 4,871 Phonpisai Pp 13.0-15.0 8,490 Ratburi Rb 15.1-20.0 218 Sandy 96,420 Korat Kt >20.0 21,683 Roiet Re 13.0-15.0 33,995 Sanpaya Sa >20.0 10,307 Srisongkham Ss 13.0-15.0 22,875 Sithon St 13.0-15.0 5,490 Warin Wn >20.0 2,070 Flooding Area 7,355 Total Area 133,944

Table 5 : Area and production potential in Huimong Irrigation Project

The soil water balance model runs revealed that the water deficit starts from the first decade of November in sandy soils, while it starts only in the second decade in clayey soils (Table 6).

Decade P ETc STL-1 ETa STL ST.d ETad Water Deficiency

Jan1 1.52 33.85 2.19 2.2 1.2 3.40 2.19 29.3 Jan2 1.57 35.86 1.21 1.7 0.8 2.47 1.65 30.3 Jan3 1.92 23.29 0.82 1.2 1.2 2.35 1.20 30.4 Feb1 1.67 35.58 1.15 1.7 0.8 2.49 1.65 30.2 Feb2 3.28 37.14 0.84 2.4 1.1 3.46 2.35 29.3 Feb3 5.85 21.93 1.11 2.8 3.0 5.79 2.82 26.9 Mar1 11.72 46.49 2.97 9.4 3.0 12.34 9.36 20.4 Mar2 14.46 48.40 2.98 11.2 3.3 14.56 11.24 18.2 Mar3 16.42 32.36 3.32 10.3 6.1 16.45 10.34 16.3 Apr1 9.03 46.06 6.11 10.1 3.3 13.34 10.08 19.4 Apr2 15.82 44.42 3.26 11.8 4.1 15.92 11.82 16.8 Apr3 28.24 28.74 4.10 15.6 11.1 26.69 15.59 6.0

May1 58.86 39.76 11.10 37.1 21.1 34.31 13.22 0.00 May2 73.10 36.84 21.09 36.8 42.8 42.77 - - May3 83.54 24.06 42.77 24.1 85.0 85.50 - -

Table 6 : The example of some result of Soil Water Balance calculation

In table 7, the calculation of the water needs of oil palm in every soil type show that the maximum requirements amount to about 438,000 m3.ha-1 in sandy soils and to 175,000 m3.ha-1 in clayey soils.


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Decade Rainfall ETc S LS SL SCL LC CL C Jan1 2 36 34 33 30 27 21 13 3 Jan2 2 38 36 35 34 32 28 22 16 Jan3 2 25 22 21 20 19 16 12 6 Feb1 2 37 36 35 34 33 31 28 24 Feb2 3 39 35 35 34 33 32 30 27 Feb3 6 23 16 14 13 12 11 9 7 Mar1 12 49 36 34 32 31 29 28 26 Mar2 14 51 36 33 30 29 27 26 24 Mar3 16 34 15 12 8 6 4 2 0 Apr1 9 48 39 36 33 31 29 27 26 Apr2 16 47 30 27 23 22 19 17 16 Apr3 28 30 - - - - - - -

May1 59 42 - - - - - - - May2 73 39 - - - - - - - Oct33 9 20 - - - - - - - Nov1 6 31 21 0 0 0 0 0 0 Nov2 2 31 28 17 0 0 0 0 0 Nov3 0 20 19 13 0 0 0 0 0 Dec1 2 32 30 26 14 4 0 0 0 Dec2 2 30 27 25 17 11 1 0 0 Dec3 2 22 19 17 12 7 0 0 0

Total (1000 m3 ha-1) 478 414 334 295 248 215 175

Table 7 : The comparison of soil water balance in different texture

PRESENTING AUTHOR Somjate Pratummintra*, Senior Expert in Rubber, Department of Agriculture, Ministry of Agriculture and Cooperative, Thailand, is an alumnus of Ghent University in 1994. He studied Master Degree in the program of Soil Survey and Land Use Planning. After that, he got the scholarship from ABOS and He finished Ph.D. in the Twining Program between Ghent University and Universiti Putra Malaysia in 2000 in Physical Land Management. Email address: [email protected]

Prof. Dr. Eric .Van Ranst, Department of Geology and Soil Science, Faculty of Science, Ghent University. He set the standard template for this work and gave an advisory in Land Evaluation Technique and the Yield Gap Analysis. Email address: [email protected]

Prof. Dr. Hubert .Verplancke, Department of Soil Management and Soil Care, Faculty of Bioscience Engineering. He set the template study in soil water balance and gave an advisory in Soil physics, and calculating on soil water flux and actual evapo-transpiration from Soil Water Balance Equations. Email address: [email protected]

Dr. Ann Verdoodt, Department of Geology and Soil Science, Faculty of Science, Ghent University. She works in Land Evaluation Technique and the Yield Gap Analysis. Email address: [email protected]

SUMMARY The GIS software such as ARCVIEW ver. 3.2 a and remote sensing technique can be applied for mapping on an existing area of rubber and oil palm. Land evaluation technique together with GIS software could produce a map of production potential of oil palm and rubber. Then,


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the result from intercepting both two maps yielded the map of rubber plantation that should be substitutes with oil palm base on the crop production. It means that the rubber plantation, which a production was lower than 950 kg Ha-1, should be substituted with oil palm that give the production higher than 16 ton FFB Ha-1year-1. At last, the same procedures such as parametric approach for evaluating the land index of oil palm, a calculation of soil water balance were applied to study the area in Northeast Thailand. Then the yield gap analyses [20], especially the calculation of soil water balance, can predict a production of oil palm in Northeast Thailand for establishing oil palm in this area that will have a production higher than 16 ton FFB Ha-1 year-1.

ACKNOWLEDGEMENTS The authors wish to express their gratitude to Dr. Somchai Baimuang, Senior Expert, Department of Meteorology, who has consistently contributed in making essential metrological data available. He also help me to convert each climate data to a digital map.

Special thanks go to Department of Land Development, furthered contributed in providing me all the digital LANDSAT TM 5, and help me to train my colleague for analyzing a digital map of land use.

Special thanks their respective institutions, the Chachoengsao Rubber Research Centre, Surat Thani Rubber Research Centre and Surat Thani Oil Palm Research Centre, for the generous support staff services during the field survey in their responsibility area.

REFERENCES

[1] Caliman, J.P., 1992. Oil Palm and water deficit production adapted cropping techniques. Oleagineux; 47(5):205-216.

[2] Corley, R.H.V. 1976. Inflorescence abortion and sex differentiation. In Oil Palm Research (ed. R.H.V. Corley, J.J. Hardon and B.J. Wood). Amsterdam Elsevier. pp. 37-54.

[3] Corley, R.H.V. and T.K. Hong. 1982. Irrigation of oil palm in Malaysia. In The Oil Palm in Agriculture in Eighties. E. Pushparajah and P.S.Chew (eds.) vol.2. pp. 343-356.

[4] Cornaire, B.,C. Daniel, Y. Zuily-Fodil and E. Lamade. 1994. Oil palm performance under water stress. Background to the problem, first results and research approaches. Oleagineux; 49(1):1-12.

[5] Foong, S.F. 1991. Potential evapo-transpiration potential yield and leaching losses of oil palm. PORIM Intl. Palm Oil Conf-Agriculture. p.105-118.

[6] Foong, S.F. 1999. Impact of moisture on potential evapo-transpiration, growth and yield of oil palm. 1999 PORIM Int. Palm Oil Congress. PORIM p.64-86.

[7] Guha, M.M. 1986. Agro-climatic and soil factors in land use planning for oilpalm development in Thailand. Consultant Report to UNDP/FAO/THA/84/007. project.

[8] Hartley, C.W.S. 1977. The Oil Palm. 2nd Longmans , London. 706 pp. [9] Hartley, C.W.S. 1988. The Oil Palm. 2nd Longmans, London. 706pp. [10]Hong, T.K. and R.H.V. Corley. 1976. Leaf temperature and photosynthesis of atropical C3 plant,

Elaeisguineensis. MARDIRes. Bull.4 (1):16-20. [11]Kee, K.K. and P.S. Chew. 1991. Oil palm response to nitrogen and drip irrigation in a wet monsoonal

climate in Peninsular Malaysia. PORIM Int. Palm Oil Conf-Agriculture. pp. 321-339. [12]Ochs, R. and C. Daniel. 1976. Research on techniques adapted to dry regions. In Oil Palm Research (ed.

R.H.V. Corley, J.J. Hardon and B.J. Wood) Amsterdam Elsevier. pp. 315-330. [13]Paramathan, S. 2003. Land Selection for Oil Palm. In Oil Palm: Management for Large and Sustainable

Yield (ed. Fairhurst, T. And Härdter, R. Potash&Phosphate Institute of Canada. pp:27-57. [14]Pratummintra, S., Van Ranst, E., Verplancke, H., Shamshuddin, J., Theeravatanasuk, K., and Kesawapituk

P. 2002. Quantifying Parameters for the Maximum Rubber Production Potential Model in East Thailand. The 17th World Congress of Soil Science. 14-21 Septemper, Sirigit National Concerence Cemtre. Bangkok.


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[15]Pratummintra, S., Verplancke, H., Van Ranst, E., Shamshuddin, J., Zauyah, S., Yew, F.K. 2000. Maximum Production Potential Model for Evaluating Land Suitability for Rubber in THAILAND. The International Symposium on Suitable Land management, 8-10 August 2000. Kuala Lumpur, Malaysia.

[16]Prioux, J.,J. C. Jacquemard, H. de Franqueville and J.P. Caliman. 1992. Oil palm irrigation. Initial results obtained by PHCI (IvoryCoast). Oleagineux. 47(8-9):497-509.

[17]Sarakhun, N., Sinthurahut, S. and Dansakoonphon, S. 1998.Analytical for Oil Palm Plantation in South Thailand. Department of Agriculture, Ministry of Agriculture and Cooporation. Thailand. 266 pp. (Thai Version)

[18]Sys, C., Van Ranst, E. and Debaveye, J. and Beernaert, F. 1993. Land Evaluation Part I: Principles in Land Evaluation and Crop Production Calculations. Agricultural Publication No. 7. General Administration for Development Cooperation. Brussel. Belgium. 274 pp.

[19]Vanranst, E. 1998. Estimation of Rubber Yields Using Readily Available Climatic Data and Soil Characteristics. University of Gent, Laboratory of Soil Science. Gent Belgium. pp 6.

[20]Verdoodt, A. and Van Ranst, E. 2003. A Two Level Crop Growth Model for Annual Crop. Ghent University. Belgium. 258 pp.

[21]Verplancke H. 1998. Applied Soil Physics. Department of Soil Management and Soil Care-Division Soil Physics. Faculty of Agriculture and Applied Biological Sciences. University of Gent. Gent, Belgium. 450 pp.


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SOIL PROPERTIES AND BIOLOGICAL DIVERSITY OF UNDISTURBED AND DISTURBED FORESTS IN MT.

MALINDANG, PHILIPPINES

Renato D. Boniao1*, Rosa Villa B. Estoista2 , Carmelita G. Hansel2, Ron de Goede4, Olga M. Nuneza3, Brigida A. Roscom3, Sam James5, Rhea Amor C. Lumactud1,

Mae Yen O. Poblete1 and Nonillon Aspe3

1Mindanao State University at Naawan, Naawan, Philippines, 2Mindanao State University-Marawi, Philippines,

3Mindanao State University-Iligan Institute of Technology, Iligan City, Philippines, 4Wageningen University, The Netherlands, 5Kansas University, USA.

Abstract Mt. Malindang, a natural park in the southern Philippines faces serious problems of biodiversity loss and soil degradation. Scarce information on the drastic effects of forest cover loss and any form of disturbance keeps the forest denudation and soil loss unabated. Therefore, this study was conducted to assess the soil physicochemical and biological properties, and the change of such properties with disturbance in Mt Malindang. Undisturbed and disturbed forests and agro- and grassland ecosystems of the range, located at altitudes above and below the 1000 m asl contourline, were sampled. Results showed that in forest areas where human intrusion was less, highest amount of O.M. (20.2%), highest CEC (43 to 57 cmolc kg-1 soil) and lowest bulk density (0.4 Mg m-3) were obtained. The soil was relatively fertile. There were also more earthworm species (at least four) in contrast to only one species (Pontoscolex corethrurus) in agricultural land and grassland. Activities of living organisms (soil respiration rate) in grassland were significantly lower than those of natural ecosystems. Root hair plant-feeding nematodes are abundant in all sites except in arable corn and grassland below 1000 m asl where semi-endoparasitic species associated with crops dominate. Thus, in any human-induced forest disturbance, it is not only the forest cover that is lost, but the soil as well. Earthworms and nematodes species composition and a number of bio-physicochemical soil properties served well as indicators of this disturbance.

INTRODUCTION Soil is an essential part of the biosphere and is vital for the continued existence of life on Earth. It is a crucial component of terrestrial ecosystems and a determinant of their capacity to produce goods and services. Unfortunately, despite the role they played in protecting our natural ecosystems, the soil and the soil communities and the vital functions they perform are still poorly understood. Lack of knowledge on the incredible complexity of soils and the organisms that made them their home is probably the singular reason that there is a seemingly continued disregard of this vital component of the natural ecosystems. Such a disregard is true in the Mt. Malindang range ecosystems, the research site.

Mt. Malindang range is one of the ecologically valuable areas in Mindanao and is an important biodiversity refuge. Yet, the whole range with its varied ecosystems from the mossy forest (its highest point) down to the coastal areas is, in fact, ecologically threatened. The pressures come from many fronts: subsistence farmers living and encroaching inside the Park [5] and farming on steep slopes; logging, either commercial or at small scale, denuding the formerly thickly forested lands; and political and economic power holders, and other


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interested groups (military or insurgent) [11] within the range who would probably risk a fortune just to claim a stake on the land. All these pressures led to soil degradation, followed by loss of biodiversity, and the repercussion goes beyond local boundaries. Among people dependent on such resources, soil degradation is simply understood as depletion or loss of a natural productive resource. Biodiversity and its key function in maintaining the stability of (soil) ecosystems are hardly understood [11]. Studies, therefore, on soil properties and their relationship to soil biodiversity are expected to address the inadequacy of information for conservation needs and for truly sustainable land use plans that ultimately protect Mt. Malindang and its natural ecosystems. Objectives Given the need to save Mt. Malindang Natural Park from the inevitable degradation, the study was, therefore, conducted to assess the soil physicochemical and biological properties of the range, and to study the changes of such properties with increasing ecosystem disturbance.

REVIEW OF RELATED LITERATURE Mt. Malindang is located in the Province of Misamis Occidental, the Philippines. It is a watershed and a catchment area. In 1971 it officially proclaimed as a National Park and Watershed Reserve through Republic Act 6266. In August 2002, through proclamation No. 228, the range was proclaimed as Natural Park, which made it, at the same time, a protected area. With 78 rivers emerging from the mountain's rugged volcanic landscape [11] and with about 15 major catchment basins [5], the range is undeniably the lifeblood of the neighboring provinces of Misamis Occidental, Zamboanga del Norte, and Zamboanga del Sur. DENR [5] noted that the range or particularly the park is an important biodiversity refuge. Diverse endemic faunal and floral species are found in the old-growth and mossy forests, several more other species have yet to be identified or discovered. Still others may already be threatened or endangered and some may no longer exist.

The park occupies a total land area of 53,262 hectares, consisting of 24,511 hectares forest land, 13,320 hectares shrub lands of open and denuded land and 14,297.25 hectares open and cultivated land. The soils are mostly undifferentiated except in the buffer zones and down to the lowlands.

The remaining forest cover, approximately 23,000 ha, has been declining fast especially over the last decade, due to some logging and timber poaching activities. Eventually, the lush forest is converted to agricultural land and human settlements. Such demand for the biological resources has, of course, resulted in high rates of biodiversity loss making Mt. Malindang as one of the “hotspots” in the Philippines needing high priority for protection and conservation [8].

Earthworms, one of the groups of organisms studied, are considered as ecosystem engineers. Sensitive to low soil moisture and soil management practices such as soil tillage, application of organic matter, pesticides and inorganic fertilizer, the earthworm population density tends to increase with increasing organic matter inputs and decrease with soil disturbance, e.g., tillage [3].

Another group of organisms is the Nematodes. They are microscopic, unsegmented, threadlike worms that can be found in soils and sediments of all terrestrial and aquatic ecosystems. Nematodes, both free-living and plant-parasitic, possess several attributes that make them useful ecological indicators [6].


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MATERIALS AND METHODS Participatory approach Series of consultation with the local communities, from the local government units and line agencies down to the barangay levels, were conducted during the preparation of the proposed study and their participation and commitment to the study and to the eventual conservation and protection of the Park, was enlisted. Incorporated in some of these meetings were capacity-building trainings, particularly on field sampling, which resulted in developing a number of ‘local researchers’. They also became an important source of information in the selection of sampling sites. Sampling sites and soil sampling Sixteen (16) sites (Fig.1) within the Mt. Malindang Protected Area, spread over 8 barangays in 4 municipalities, were selected for the study. These sites were grouped according to elevation (above and below 1000 m asl) and into four different ecosystems based on the degree of disturbance (Table 1).

In each site at least three plots of 20 x 20 meters were established within which composite soil samples were collected for chemical and physical analyses. A sub-sample of about 700 g was separated for nematode extraction. The remaining soil (for chemical/physical analyses) was air-dried and stored at room temperature. On the same plots, 3 replicates of an undisturbed sample at 0-10 cm and at 20-30 cm depths, using a core sampler with known volume were collected for bulk density. Pits were dug, described and sampled for soil classification. The routine physicochemical analyses all follow the standard accepted laboratory procedures Earthworm sampling and identification Within each 20 x 20m plot, 10 subplots measuring 50 cm x 50 cm and 30 cm deep were dug. The soil block was put on a plastic sheet and all earthworms present were collected by hand. The earthworms were killed in a 70-90% ethanol and stored in 10% formaldehyde and the total number and species composition were counted and identified by plot. Species new to science were stored for further taxonomic description. Soil respiration determination In a randomly selected spots of each field plot, soil respiration was measured using the closed chamber–Draeger Tube-syringe method described by Parkin and Doran [10]. Each measurement was replicated twice. Nematode analyses Nematodes were extracted from a 100 g fresh weight soil sample stored at 4oC, using the Oostenbrink elutriator technique [9]. Total numbers of nematodes were counted and then stored in 4% formaldehyde until identification. Nematodes were identified to family and genus level. Next, they were assigned to trophic groups according to Yeates et al. [15].


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Figure 1. Location of Mt. Malindang Protected Area and the sampling sites within four municipalities


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Elevation Ecosystems Undisturbed

(Primary) forest

Disturbed Forest

Agroecosystem

Grassland

> 1000 masl

Mt. Guinlajan (6)* North Peak (6)

Small-scale timber extraction: a. Mt. Ulo sa Dapitan (6) b. Mt. Capole (6) c. Old Liboron (3) Logged-over- Pongol (3) Secondary Growth Forest - North Peak (1)

1st arable: a. Lake Gandawan/ Cabbage (3) 2nd Arable: a. Lake Gandawan- Agro (3) b. Gandawan - Agro (3)

Lake Duminagat (1) b. Gandawan (2)

< 1000 masl

Small-scale timber extraction: Mialen (3) Logged-over: Peniel (3) Agroforestry: Mamalad (3)

Coco a. Mialen (3) Corn a. Bunga (3) b. Mamalad (3)

a. Peniel (3)

Table 1. Sampling sites at different ecosystems in Mt. *Malindang. Numbers in parenthesis are the

total no. of sampling plots of the site specified

RESULTS AND DISCUSSION Soil morphology and classification The Mt. Malindang soils were relatively young. Two soil orders, Inceptisols and Entisols were reported (Descriptions of 9 profiles not shown). The studied soils, except one Profile (Brgy. Peniel), may have andic properties as shown by the bulk density values (Table 2) and the nature of the parent material. Such soils have good physical properties and essentially are fertile when first cleared for cultivation. However, they deteriorate fast with continued use over time, particularly because these soils were concentrated mostly on sloping areas. Physico-chemical Properties Primary data on the chemical and physical properties of the soils were given in Tables 2 and 3. It was shown that in a number of parameters, i.e. pH, available phosphorus (P), total nitrogen (N), exchangeable potassium (K) and texture, most of the ecosystems studied were similar, and if there were any seeming dissimilarities, these were not statistically significant.

There were, however, soil properties that reflected a higher soil quality in the undisturbed ecosystem than in the disturbed ecosystems, such as percent organic matter (%O.M.), CEC, and bulk density (Db).

Organic matter (% O.M.) The organic matter contents ranged from 8.5 to 20.2 % (Table 2). These values were relatively higher than an ideal soil was supposed to contain [1] and very much higher than most of the soils across the Philippines [2]. Comparison of the samples indicated that the undisturbed (primary) forests were richer in O.M. than the other ecosystems studied.


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ECOSYSTEMS BD Mg m-3

OM %

pH 1:1 H2O

Avail P ppm

Total N %

Exch K cmolc/kg

soil

CEC cmolc/kg

soil Undisturbed Forest 0.4a* 20.2 c 4.9 a 2.1 0.5 b 0.2 57.0 c Disturbed Forest 0.7b 15.0 b 5.4 b 1.4 0.5 ab 0.5 40.1 b Agroecosystem 0.9bc 10.3ab 5.2 ab 1.3 0.4 ab 0.5 27.5 a Grassland 1.1c 8.5 a 5.3 ab 1.0 0.3 a 0.3 23.6 a

Table 2. Soil chemical properties of the different ecosystems. *Means with same letter are not

significantly different at 5% level (Duncan) using SPSS Among disturbed ecosystems, the amount of O.M. went down with their degree or state of disturbance. Comparison by land use types (Table 3), reflecting varying degrees of disturbance, confirmed that more O.M. is lost as disturbance progresses into grassland (Peniel). Not even reforestation, as was the case of plantation forest in Peniel (6.6 %), can raise O.M. content approximately as high as the North Peak level (24.9 %), the undisturbed ecosystem. The consequential loss or decline of the natural levels of soil organic matter following cultivation is well established in literature. According to Syers and Craswell [12] soils under agriculture inevitably show a decline in organic matter because (1) tillage and other agricultural practices increase the soil organic matter decomposition rate by mixing the surface soil and increasing the number and intensity of wetting and drying cycles; and (2) the inputs of plant C are generally less in a disturbed or cultivated system than in natural environment. The reduction in return of organic residues to the soil is as much as ten-fold [7].

Land Use Types OM (%)

pH (1:1 H2O)

Total N%

Avail P ppm

Exch K cmolc/kg soil

CEC cmolc/kg

soil Small scale timber extraction 16.0 cd* 5.5 bc

0.51abc 1.6 ab 0.54 ab 43.16 d

Logged-over 11.98 abcd 4.9 ab 0.45abc 0.8 a 0.18 a 30.96bcd Agroforestry 4.9 a 4.6 a 0.2a 0.5 a 0.20 a 20.48 ab First arable 14.8bcd 5.4 bc 0.69c 1.9 ab 0.73b 43.15 d Last arable 14.3 bcd 5.4 bc 0.57bc 2.6 b 0.28 a 29.77 ab Coco 10.6 abc 5.7 c 0.35ab 0.5 a 1.16 c 34.87 bc Corn 6.6 ab 4.8 ab 0.19a 0.5 a 0.30 a 17.14 a Grassland 8.5 abc 5.3 bc 0.29a 1.0 ab 0.38 a 23.58 abc

Table 3. Soil chemical properties at different land use types. *Means with same letter are not

significantly different at 5% level (Duncan) using SPSS Cation Exchange Capacity (CEC) The CEC values of the ecosystems regardless of elevation were given in Table 2. These values were all above the adequate level (20 cmolc kg-1 soil) for plant growth set by the BSWM [4]. The undisturbed forest was observed to have the highest CEC value (57.0 cmolc kg-1 soil). Grassland, on the other hand, had the lowest CEC (23.6 cmolc kg-1 soil), followed by the agricultural and the disturbed forest ecosystems. The CEC difference between undisturbed and disturbed forest was quite significant and both had CECs significantly higher than those of the agricultural and grassland ecosystems. Obviously, CEC decreases with ecosystem disturbance.


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Incidentally, ecosystems with high CECs were the ecosystems with high O.M contents. Figure 2 shows the trend and the relationship having a high R2 value (R2=0.998). CEC coming from humus (O.M.) seemed to play a prominent role. Thus, the importance of organic matter to the cation exchange capacity of the soils was once again demonstrated above. The organic matter content is in equilibrium with climate, vegetation and other environmental conditions. It depletes rapidly if this equilibrium is disturbed by inappropriate management practices [13]. It is, therefore, a must that the management of these soils is oriented in maintaining sufficient amounts of organic matter.

y = 2.8461x - 0.8821R2 = 0.9987

0

10

20

30

40

50

60

0 5 10 15 20 25

% OM

CEC

(cm

olc/

kg s

oil)

Figure 2. Relationship between OM and CEC of the different ecosystems Bulk Density (Db) The bulk densities of the studied soils in each ecosystem were presented in Table 2. The values were unusually low for mineral soils, ranging from 0.4 to 1.1 at 0-20 cm depth or 0.43 – 1.03 Mg m-3 at 20-30 cm (not shown). However, against the backdrop of high O.M. content of most soils, these Db values seemed plausible. Mineral particle densities (Dp) usually range from 2.5 to 2.8 Mg m-3, while organic particles are usually less than 1.0 Mg m-3. Thus, where O.M. was observed to be comparatively high, bulk density was also relatively low. Undisturbed forest, significantly had the lowest Db value. This was also the ecosystem with the highest O.M. Soils in the disturbed ecosystems, grassland and agro ecosystems in particular, on the other hand, which may have lost much of their O.M. from human activities as presented earlier, had much higher bulk densities. Biological components Soil Respiration Soil respiration values were given in Table 4, all of which were less than the range of 40-72 CO2-C ha-1 d-1 based on the soil respiration class ratings of Words End Research [14]. Tillage, which was known to bring in more oxygen to the soil and expose organic matter to organisms, had obviously contributed to the increase of CO2 evolution from the soil. Comparatively, although the difference was not statistically significant, the undisturbed ecosystem had lower respiration rate than that of the disturbed or agro-ecosystem. The grassland ecosystem seemed to be an exception. It had the lowest respiration value among


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ecosystems when, in fact, it was the most disturbed albeit quite recently. The reason, maybe, was the amount of organic matter available for decomposition. Grassland incidentally (Tables 2, 3) had the lowest O.M.

As indicator of biological activity, soil respiration is usually regarded as a positive indicator of soil quality. A higher respiration rate results in more nutrients released from organic matter and improved soil structure, among others. In this perspective, the agro-ecosystem would have the highest quality soil. High respiration, however, does not always indicate good soil quality. It is understood that biological activity is also a direct reflection of the degradation of organic C compounds in soil [10]. It indicates loss of carbon from the soil system. Viewed from this perspective, the agro-ecosystem in this study must have retained less organic matter than the forest ecosystems. Indeed, based on the amount of organic matter present in these ecosystems (Table 2) the observation was true. All, except grassland, had high O.M. contents and the undisturbed ecosystem had more compared to other ecosystems. Earthworms Pontoscolex corethrurus, an exotic species introduced from Brazil, was the earthworm type that inhabited grassland and agro-ecosystems. It was the only species found in those ecosystems. In other ecosystems, varied species, possibly some would be new to science, were found. The undisturbed mossy forest had a notably higher number of species per unit area than the disturbed forest. Forest ecosystems, disturbed or not, had much more diverse species of worms than grasslands and agro-ecosystems (Table 4). In terms of the number of individuals, however, the latter two gave the greater numbers at both elevations (below or above 1000 masl). The species presence, however, was limited to one, P. corethrurus. It was well to note that, in forests, particularly the undisturbed ecosystems, where bigger and more colorful species were found, organic matter and surface litters were abundant. This may explain why the latter species of earthworms were mostly present.

Type of ecosystem

Earthworm (Ind. per 2.5 m2 at

0.30 m depth)

Earthworm (No. of sp per

2.5m2 at 0.30 m depth)

Nematode (No. of Ind. per

100 g soil)

Soil respiration (CO2 -C kg ha-1d-

1)

Primary forest 9.5a* 3.8b 583.3a 41.34b Disturbed forest 74.6ab 3.4b 921.7a 41.49b Agroeco 113.8b 1.0a 910.7a 43.16b

Grassland 111.0b 1.0a 805.0a 21.59a

Table 4. Soil nematode and earthworm abundance and soil respiration in different ecosystems.

*Means with same letter are not significantly different at 5% level (Duncan) using SPSS. Nematodes

Table 4 showed that the number of individual nematodes per 100 g soil was not significantly different among ecosystems and was rather low compared with soils in the temperate regions. But when grouped according to feeding habits, plant-feeders came out most abundant in all sites studied. And among this group, root-hair feeders dominate except in arable corn and grassland below 1000 m asl. In the grassland ecosystem, it was the semi-endoparasitic group which was abundant in both elevation classes, while the ectoparasitic plant-feeding nematodes were most abundant in forest ecosystems at more than 1000 m asl. When the relative abundance of nematodes were subjected to principal component analyses


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(PCA) with some environmental parameters as passive variables, the result showed that the forest ecosystems, located in the upper part of the ordination plot (Fig. 3) and characterized by low bulk density, and high organic matter and CEC, have relatively high abundance of nematodes.

Figure 3. PCA of nematodes showing the position of the10 sampling sites (o) and some soil physical

and chemical properties.

Further ordination analyses (redundancy analysis, RDA) on the 10 sites with nematode data showed that 58% of the variation in the nematode population can be described by the environmental variables. In fact, all variables together can explain 84% of the variation within the nematode dataset (Table 5).

Axes 1 2 3 4 Total variance

Eigenvalues 0.305 0.185 0.112 0.072 1.000 Species-environment correlations 0.993 0.997 0.959 0.929 Cumulative percentage variance of species data 30.5 49.0 60.2 67.4 of species-environment relation 36.4 58.4 71.7 80.3 Sum of all eigenvalues 1.000 Sum of all canonical eigenvalues 0.840

Table 5. Results of a RDA on the 10 sites with nematode data. Total-N was not included because data were missing for two sites; CEC and bulk density were excluded from the analyses because of strong

autocorrelation with other parameters.

PRESENTING AUTHOR *Renato D. Boniao, Mindanao State University-Naawan, Naawan, Misamis Oriental, Philippines. E-mail: [email protected] or [email protected] .


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CONCLUSION The soil characteristics, both physical and chemical properties, all pointed out that they are at their optimum or best levels in ecosystems where human activities occurrence is almost absent or none at all. These ecosystems kept the organic matter values high, pH levels acceptable and retained relatively good amounts of N or P in the soils. These are also the ecosystems that have loamy textural classes and low bulk densities, indicative of good structural aggregation, presumably because of, but for one, the high amount of O.M. In contrast, forests converted into agricultural lands and later abandoned into grasslands have much poorer soil properties. As shown, a good quality of the soil is in part maintained by the integrity of the forest cover, and forest or soil disturbance in any form without mitigating measures, can ultimately compromise soil quality. As is the case in Mt. Malindang, in time, grassland or waste land areas increase while forestlands decrease correspondingly.

The best way to break the cycle of abandoning old farms and opening new ones is to select areas on which, by necessity and social consideration, a certain degree of sustainable cultivation is allowable.

ACKNOWLEDGEMENT

We wish to thank The Netherlands Ministry of Development (DGIS) for the research grant through SEAMEO-SEARCA for the Philippine-Netherlands Biodiversity Research for Development in Mindanao: Focus on Mt. Malindang (BRP)

REFERENCES [1] Brady, N.C and R. R. Weil. 1999. The Nature and Properties of Soils. 12th Ed. Prentice Hall International, Inc. [2] Badayos, R. B. 1996. Soils and Agriculture in the Philippines. Seminar paper presented at Tsukuba, Ibaraki, Japan, October 1996 [3] Blair, J.M., P.J. Bohlen and D.W. Freckman. 1996. Soil Invertebrates as Indicators of Soil Quality. In: J.W. Doran & A.J. Jones (Eds.) Methods for Assessing Soil Quality. SSSA special publication number 49, Madison, Wisconsin, USA: 273-287. [4] CARE-BSWM. 2002. Soil and Land Resources Evaluation. Mt. Malindang National Park Buffer Zone, Province of Misamis Occidental Vol. 1, The Bio-physical Resources. BSWM and CARE Philippines. [5] DENR, 1999. Management Strategy for Mt. Malindang. DENR, National Integrated Protected Areas Program. p. 22. [6] Freckman, D.W. 1988. Bacterivorous nematodes and organic –matter decomposition. Agriculture, Ecosystems and Environment 24:195-217. [7] Goh, K.M. 1980. Dynamics and Stability of Organic Matter. In: B.K. Theng, (ed), Soils with Variable Charge. New Zealand Society of Soil Science. pp 373-393. [8] Ong, P.S., L.E. Afuang, and R.G. Rose-Amball (eds). 2002. Philippine Bidiversity Conservation Priorities: A Second Iteration of the National Biodiversity Strategy and Action Plan. Department of Environment and Natural Resources-Protected Areas and Wildlife Bureau, Conservation International Philippines, Biodiversity conservation program. UPCIDS and FPE, Philippines. [9] Oostenbrink, M. 1960. Estimating Nematode Populations by Some Selected Methods. In: Sasser J.N. & W.R. Jenkins (Eds.) Nematology. Chapel Hill, Univ. N. Carolina Press: 85-102. [10] Parkin, T.B. & J.W. Doran. 1996. Field and Laboratory Tests of Soil Respiration. In: J.W. Doran & A.J. Jones (Eds.) Methods for assessing soil quality. SSSA special publication number 49, Madison, Wisconsin, USA: 231-246. [11] SEAMEO-SEARCA. 2002. Biodiversity Research Programme for Development in Mindanao: Focus on Mt Malindang. SEAMEO-SEARCA, College, Los Banos, Laguna, Philippines.


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[12] Syers, J.K. and E.T. Craswell. 1995. Role of Soil Organic Matter in Sustainable Agricultural Systems. In: R.D.B. Lefroy, G.J. Blair and E.T. Craswell (Eds.) Soil Organic Matter Management for Sustainable Agriculture A workshop held in Ubon, Thailand, 24-26 August 1994. ACIAR, Canberra. [13] Van Wambeke, A. 1992. Soils of the Tropics, Properties and Appraisal. McGraw-Hill, Inc. New York. 343p. [14] Woods End Research. 1997. Guide to Solvita Testing and Managing your Soil. Woods End Research Laboratory, Inc., Mt., ME. [15] Yeates G.W., T. Bongers, R.G.M. de Goede, D.W. Freckman & S.S. Georgieva, 1993. Feeding Habits in Soil Nematode Families and Genera – An Outline for Soil Ecologists. J. Nematology 25: 315-331.


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Sub-theme : LAND DEGRADATION : PRESSURES, INDICATORS AND RESPONSES

Various approaches for soil erosion risk assessment

W. Cornelis, D. Gabriels, H. Verplancke

Soil Physics and Soil Erosion Unit, Department Soil Management and Soil Care, Ghent University, Gent, Belgium

According to GLASOD (Global Assessment of Degradation), erosion by water and wind is, on a global scale, considered as the major cause of soil degradation. The detrimental effects of soil erosion are particularly manifest in many tropical rural areas, where farmers are highly dependent on the intrinsic land properties and are lacking the means to improve the quality of their soils. There is, therefore, an urgent need for policy interventions to arrest soil degradation, and erosion in particular, and rehabilitate degraded areas. Erosion risk assessment methods offer a vital tool in the planning of such interventions.

The early erosion models such as the widely adopted USLE (Universal Soil Loss Equation) or WEQ (Wind Erosion eQuation) consisted of relatively simple response functions that were calibrated to fit a limited number of (regional) observations. Despite our progress in understanding soil erosion over the past years and the resulting attempts to introduce physically-based deterministic models of varying level of sophistication (e.g. WEPP, EUROSEM, WEPS), those ‘good old’ empirical models, though now improved and often incorporated into a Geographical Information System, are still very popular and most widely used. This was one of the outcomes of the International Symposium on ’25 Years of Assessment of Erosion’ held in September 2003 at Ghent University. The empirical models have generally a much simpler structure, require less input parameters and show often similar performance in terms of prediction accuracy than deterministic models when considering yearly averages. Reducing model complexity will generally lead to a minimization of the error propagation of erosion models, a topic that should be given much more attention than it has now in the future.

Besides the model-based and strictly quantitative approach, more attention has been given in recent years to expert-based methods. These methods use qualitative (categorical) or quantitative (numerical) data, or a combination of both, be it in a parametric or non-parametric way. An example of a parametric approach is factorial scoring. In this approach, scores are given to various indicators of soil erosion and then multiplied giving a combined score that represents erosion risk. Non-parametric methods can be based on regression techniques such as e.g. kernel density regression or a classification tree. They have the advantage that they do not require any assumption about the functional relationships between independent (e.g. erosion factor/indicator) and dependent variables (e.g. erosion risk). This, however, also implies that the resulting regression is shaped according to the data only, and not according to theoretical functions. Expert-based methods in general are further rather subjective as they depend on judgment of erosion indicators which can vary substantially among experts. Notwithstanding these short-comings, expert-based methods have shown to be promising. They are very attractive in those tropical rural areas where numerical data are scarce, but where categorical data such as erosion indicators can be relatively easily collected by scientists, extensionists or farmers. Integration of the broader scientific knowledge and experience of scientists and extensionists with the ‘grass-rooted’ local knowledge can become a key factor for successful interventions, and can stimulate the participation of local farmers in conservation practices to arrest and combat land degradation.


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We finally believe that techniques enabling to identify computer models on the basis of expert knowledge of the process of soil erosion, such as e.g. fuzzy methods, should be further explored in the context of erosion risk assessment. Fuzzy-based modeling can also been applied to improve the empirical or deterministic model-based methods.

REFERENCES

[45] W.M. Cornelis, D. Gabriels (eds). “25 Years of Assessment of Erosion”. Catena Special Issue, 64, pp.139-364, (2005). [46] M. Grimm, R. Jones L. Montanarella. Soil Erosion Risk in Europe. European Soil Bureau. Institute for Environment & Sustainability. JRC Ispra. 40 p. (2002). [47] V. Jetten, A. de Roo, D. Favis-Mortlock. “Evaluation of field-scale and catchment-scale soil erosion models”. Catena, 37, pp. 521-541, (1999). [48] G. Metternicht, S. Gonzalez. “FUERO: foundations of a fuzzy exploratory model for soil erosion hazard prediction”. Environmental Modelling & Software, 20, pp. 715-728, (2005). [49] B.G.J.S. Sonneveld, M.Q. Keyzer, P.J. Albersen. “A non-parametric analysis of qualitative and quantitative data for erosion modeling: a case study for Ethiopia”. In: D.E. Stoot, R.H. Mohtar and G.C. Steinhardt (eds.). Sustaining the Global Farm. Selected papers from the 10th International Soil Conservation Organization Meeting, May 24-29, 1999, Purdue University and USDA-ARS National Soil Erosion Research Laboratory. pp. 979-993. (2001). [50] L.T. Tran, M.A. Ridgley, M.A. Nearing, L. Duckstein, R. Sutherland. “Using fuzzy logic-based modeling to improve the performance of the Revised Universal Soil Loss Equation”. In: D.E. Stoot, R.H. Mohtar and G.C. Steinhardt (eds.). Sustaining the Global Farm. Selected papers from the 10th International Soil Conservation Organization Meeting, May 24-29, 1999, Purdue University and USDA-ARS National Soil Erosion Research Laboratory. pp. 979-993. (2001). [51] G. Verstraeten, J. Poesen, J. de Vente, X. Koninckx. “Sediment yield variability in Spain: a quantitative and semiqualitative analysis using reservoir sedimentation rates”. Geomorphology, 50, pp. 327-348, (2003). [52] O. Vigiak, B.O. Okoba, G. Sterk, L. Stroosnijder. “Water erosion assessment using farmers’ indicators in the West Usambara Mountains, Tanzania”. Catena, 64, pp. 307-320, (2005).


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INDICATORS AND PARTICIPATORY METHODS FOR MONITORING LAND DEGRADATION. A CASE STUDY IN THE

MIGORI DISTRICT OF KENYA.

Vincent de Paul Obade1*, Eva De Clercq2

1*United States International University, Nairobi, Kenya, 2Ghent University, Ghent, Belgium.

Abstract "Knowledge is power" is a common term in development research. The two sides of the same coin, "sharing knowledge" and "power sharing", however, lie at the root of problems like desertification and drought. Traditionally, farmers have used local knowledge to understand weather and climate patterns in order to make decisions about planting and harvesting. This knowledge, which has been passed on from previous generations, is adapted to local conditions and has been gained through many decades of experience. The potential of identifying the corresponding "grassroots (local) indicators" offers possibilities to design new and more accurate approaches to indicators selection, planning and monitoring processes for development. This approach would also facilitate local control over the generation and use of knowledge. This paper gives an overview of local-grassroots and scientific indicators of land degradation, which could be useful in providing information oriented towards reducing poverty and combating desertification in Kenya. The study area is Migori district in Nyanza province inhabited mostly by the Luo community of Kenya.

INTRODUCTION

Unpredictable rains and long periods without rains may result in crop failure and drought. Local people, in response to continuing poverty develop approaches to cope with unfavorable environmental conditions. These coping mechanisms can include career change, migrations, intensive agriculture etc. To counter drought, the Luo are increasingly applying irrigation in addition to using fertilizers and pesticides whenever possible to plant crops like vegetables, maize, and sugarcane. Furthermore, the lake region has had a rapid population growth, with a 13% growth rate [10]. It is not uncommon for the Luo people to have large families of 3-4 wives and 15-20 children in total. The combinations of all these factors are at the origin of land degradation in Migori, Kenya.

Desertification is "land degradation in arid, semi-arid and dry sub-humid areas resulting from various factors, including climatic variations and human activities [8]." Degradation of soil, decreasing water resources and changes in the climate are the three main obstacles to sustainable agricultural development in Kenya [2, 6, and 7]. The current debate on desertification has tended to focus on alarming data and trends in climatology and ecological change, to the neglect of the influence of and impact on, social conditions [5].

Participatory methods give outsiders a chance to learn how the local people live, what signs or signals they look for, and how they sustain their everyday lives. Before the advent of modern scientific methods, the local communities in Kenya must have realized that some animals, birds, insects and plants had the capacity to monitor and detect the changes in climatic conditions. However, research on these techniques continues most commonly to be an isolated process. The question then is: if local people's knowledge is to be used for monitoring natural resources, how can it be used and how useful and accurate is it for decision-makers, planners or implementers?


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Objectives The objectives of this study are: 1. Outline and briefly compare various indicators (scientific and grassroots-traditional) and

the participatory methodologies for monitoring climate, land degradation and land cover changes and

2. Identify indicators perceived by rural communities as affecting their Food Security (FS) and the changes (or indicators of change) in the environment that are used by local communities to monitor the environmental resources and make decisions about the adequacy of their future food supply.

INDICATORS Different approaches to understanding land degradation suggest differences in indicators. Scientists' explanations of degradation are derived from conclusions based on scientific data sets [2, 3 and 7]. Local perceptions-"grassroots indicators”, on the contrary, are mostly derived from the experience gained by the local people from the observable changes on the environment over time. This article outlines the factors considered when developing scientific and grassroots indicators. Scientific Indicators Determination of the extent of land degradation can be achieved through the use of indicators, including [7 and 9]: topography, soil depth, drainage, nutrient retention, vegetation, traffic, level of aluminium toxicity and soil acidity, vertic properties, soil erosion potential, flood risk, calcium carbonate, soil salinity etc. Table 1 shows the types of indicators and specific factors considered in measuring land degradation [9, 11, and 12]. Among the problems facing the development of scientific indicators of land degradation in Kenya are: the lack of coordinated data systems between the various stakeholders, poor methodologies and inaccuracies in data collection and analysis. As an example one can mention the heavy reliance on questionnaires to assess socio-economic conditions, or the conflicts in legislation, standards and specifications as given in the “Registration of Titles Act” (RTA) of 1919 (Cap. 281), the “Survey Act” of 1923 (Cap.299), and the “Registered Lands Act” (RLA) of 1963 (Cap 300) that are used for survey and mapping of land etc. In addition, scientific indicators have the weakness of the giving less importance to the effects of plant diseases that are soil borne (or perceived to be), as well as pests that live in the soil or crop residue.


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Type and subtype of indicator Factors

Climatic a. Rainfall b. Temperature c. Rain erosion potential (calculated) d. Sunlight duration e. Potential evapotranspiration — PET (calculated)

Soils a. Texture b. Fertility (organic matter) c. Structure d. Permeability e. Erosion potential (calculated) f. Alkalinization/Salinization

Physical

Topography a. Slope

Vegetation a. Canopy cover of herbaceous and woody plants (%) b. Plant composition and desirable or key species c. Potential herbaceous production (calculated)

Biological

Animals a. Animal population estimates and distribution b. Herd composition c. Herbaceous consumption (calculated)

Land and water use a. Land use b. Water availability and requirements

Settlement patterns a. Settlements and infrastructure.

Human biological parameters

a. Population structure and growth rate b. Measures of nutritional status and Feeding habits

Socioeconomic

Social process parameters a. Conflicts and Migration

Table 1: shows the scientific parameters considered in land degradation [9, 11 and 12].

Grassroots Indicators

Traditional knowledge is generally defined as the “knowledge of the people of a particular area based on their interactions and experiences within that area, their traditions and economic systems”. There has been an increasing interest in indigenous knowledge in the science of climatology and agriculture [2]. Local climate can be predicted and interpreted by locally observed variables and experiences; using combinations of plant, animal, insects and astronomical indicators. Table 2 shows grassroots (local) indicators of the people of Migori district. In designing grassroots’ indicators, one could ask the elders to explain how they predict coming events, rains, etc. What is it that they look for? What enables them to see trends? Future possibilities can also be probed by asking questions such as: What happens if nothing is done? Or if something is done? The impact of this technique is that most of the outsiders and local community end up with some understanding of their land resources, forest resources, village boundaries etc.


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Issue Indicators Indicator Meaning Expected action by community

Flowering and shading of various species of plants

When the Kayongo plant flowers, long rains are about to start. The onyiego plant shades its leaves and produces fresh buds just before the rain. (March and April). The modhno plant produces fruit in September and turns reddish just before the short rains in October-December.

Advanced stages of land preparation and manure application. Decisions and consultations within households on what to plant and where to plant

Bird behaviour The osogo (weaver) birds make noises continuously during the day and night, Magungu, Ang’etho and Agak fly across the sky

Continue land preparation. Preparation of seeds

Insect behaviour

Ong’ino, Onyoso and Ngwen insects (ants /termites) jump up and down imitating the way the women plant with a kwer (farm implement), Grasshoppers chirp continuously

Continue land preparation.

Start of rains

Animal and human behaviour

Cows and goats jump about excitedly. Elders and rain-makers (nganyi) determine the coming of rains for example by appearance of ayila-plant and gwer-gwer birds. Frogs croak.

Farmers take risk in Planting suitable crops.

Stars, Lightening and Thunderstorms

Appearance of yugni mammon (the sisters) female constellation of stars indicate wet season. Rains begin Farmers Plant and Cultivate suitable crops.

Flowering of Otho tree, which usually never buds. Mabinju, ochok, and ali plant flowers before any other plant. Strong easterly winds (Komadhi) marks dry spell. Ober and Saye plants shed off their leaves indicating drought. Deterioration of the health and productivity of crops.

Start storing food. Migrate to empty government lands (lop serikal) or employ herdsmen, send them with cattle to these lands, and check on them frequently; (however, those who settle on these lands retain previous homes)

Unthatched rooftops for cattle feed. Sell cattle and farms to buy food

Drought

Plant and animal behaviour

Appearance of numerous insects which destroy crops. Absence of frogs. Snakes and other reptiles begin straying into peoples houses searching for food.

Stars Appearance of yugni-machwo (orion).-male constellation of stars indicate dry season

Men migrate to seek employment elsewhere to feed families. Women engage more in fish business and feed on osuga, awayo, apoth, odielo etc Group formations increase, kinship affiliations and friendships are strengthened, as people grapple with problem of survival. Some men run away, leaving wives and children behind

Fertile soils Soil red, heavy and sticky. Insects such as ants around anthills, earthworms, snakes and rats found here

In kitchen gardens where debris and other rubbish are thrown away daily, Maize, beans and other legumes planted. Sorghum, pigeon peas, cowpeas, sweet potatoes and cassava planted.

Soil types and changes

Infertile soils Formerly heavy, sticky soil becomes loose and coarse. Weeds such as akech, mabinju, kayongo grow

Manure is added as soil nutrient, crop rotation, grow drought resistant crops

Table 2: Grassroots Indicators of land degradation for Migori district, Kenya.


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The weakness of the migori-luo grassroots indicators is that they are subjective in that they do not consider the effect of population change, landslides, soil erosion, texture, landform type and organic matter content. Furthermore, the appearance of rains is at times believed to be influenced by rain-makers, leading to further uncertainty on the reliability of the luo indicators.

HISTORICAL TRENDS Historical profiles and time trends are useful in understanding important events or key changes between years. As such, they also help to focus on the future in terms of land use, climate change, soil erosion, population, tree cover and common property resources etc [1].

PARTICIPATORY MAPPING

Maps are important for communicating land use changes especially where monitoring and evaluation are required. The people of the local community can do mapping of the land-use/change since they know most about the area under study. Maps are valuable for exploring land-use patterns, changes in farming practices, constraints, depletion trends of forest cover, land deterioration, water, and crops [9]. The key informants in this process will be the elderly, both men and women. The maps can be drawn on paper or on the ground i.e. “on-ground” digitizing whereby maps are sketched on the ground by people of various age groups. Secondary data and records can also be brought in for comparative information. As postulated by [4], satellite imagery and Global Positioning Systems (GPS) can also be used to validate the data.

CONCLUSION

In order to improve land management and climate forecasting, the gap between the local and scientific indicators needs to be assessed and bridged for the benefit of the rural communities who form the largest percentage of the population in Kenya. Neither the scientist nor the local-farmer views consider all factors responsible for land degradation. There is need for further investigations on grassroots and scientific indicators, to determine the most useful soil quality indicators oriented towards sustainable land management. In addition, it is important to select indicators that are easy and inexpensive to measure or monitor. Identification of grassroots indicators is a complicated process, and there is a need for more examination and documentation of this information. Most communities in Kenya have their own "grassroots indicators" based on knowledge and practical experience gained over time. The indicators differ by area according to environmental conditions and people's activities. However, the real challenge will be to evolve hybrid indicator systems bringing together the different relevant traditional and scientific, historical and actual perspectives and knowledge systems.


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ACKNOWLEDGEMENTS I wish to thank Dr-ir. Wim Cornelis and Dr. Ann Verdoodt of Ghent University in Belgium, Katsuji Nakamura and Professor Bob Kio Manuel both of the United States International University-Africa for their critical comments and contributions towards improving this article. I am also grateful to Professors Hubert Verplancke and Eric Van Ranst of Ghent University, Belgium for their advice.

REFERENCES [1] Anthony, G.Y., Xia, L. Urban Growth management in the Pearl river delta: an integrated remote sensing and GIS approach, ITC Journal 1996-1, pp. 77-86, 1996. [2] Coppin, N.J., Richards, I.G. Use of Vegetation in Civil Engineering. CIRIA/ Butterworths, London, 1990. [3] De jong, S.M., Paracchini, M.L., Bertolo, F., Folving, S., Megier, J., De Roo, A.P.J. Regional Assessment of Soil Erosion using the distributed model SEMMED and remotely sensed data. Catena 37, 291-308, 1999. [4] Dymond, J.R., Bẻgue, A., Loseen, D. Monitoring Land at Regional and National Scales and the role of remote sensing, ITC Journal 2001-2, pp. 162-175, 2001. [5] Evers, Y.D. Dealing with risk and uncertainty in Africa's dry lands: The social dimensions of desertification. International Institute of Environment and Development, Issue Paper No. 48, London, UK, 1994. [6] GoK (Government of Kenya). Royal Netherlands Government and United Nations Environment Programme. National Land Degradation and Mapping in Kenya. United Nations Office, Nairobi, 1997 [7] Morgan, R.P.C. A Simple approach to soil loss prediction: a revised Morgan-Morgan-Finley model. Catena 44, 305-322, 2001. [8] UNEP. The United Nations Environmental Programme’s (UNEP) Millennium Report on the Environment. Global Environment Outlook 2000. Nairobi: UNEP, 1999. [9] Van Ranst, E., Verplancke, H. Land Evaluation. Lecture notes. Laboratory of Soil Science, Faculty of Science, Ghent University, Belgium, 2003. [10] http://www.cbs.go.ke/census1999.html, Accessed online 12th November 2005. [11] http://www.idrc.ca/en/ev-30796-201-1-DO_TOPIC.html, Accessed online 6th July, 2006. [12] http://www.fao.org/ag/agl/agll/lada/emailconf.stm, Accessed online 6th July, 2006.


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PROPOSED PLAN OF ACTION FOR RESEARCH ON DESERTIFICATION IN THE SUDAN:

GEZIRA AND SENNAR STATES

Kamal Elfadil Fadul and Fawzi Mohamed Salih

Land and Waterr Research Center, AgriculturalResearch Corporation, Wad Medani. Sudan

Abstract The proposed plan of action for research on desertification in both Gezira and Sennar states includes an overall review of the previous and present activities innovated along his aspect. Both protective and preventive measures are required to combat desertification. Proper management of the cultivated lands, controlled use of the natural forests and rangelands, improvement of the standards of living for the inhabitants and the level of awareness pertaining to the problem are all factors of impact on the desertification in both states. Accordingly, the proposed plan addresses two experimental sites, one in the natural vegetation zone and the other in the irrigated area. The former site involves the cultivation of environmentally adapted plant species, where as the latter site caters for the management practices of the crops grown in the cultivated lands. Such a research program needs a multidisplinary effort of the specialties concerned together with the provision of funding estimated to implementation and follow up.

INTRODUCTION

Desertification as a land degradational process is encountered in Sudan at varying levels of intensity. It is mostly active in the northern and western regions. Nevertheless, Gezira and Sennar states, as parts of the central region, are susceptible to this phenomenon in the near future, especially in the northwestern parts of both states. The western part of Gezira state lies at he fringes of the degradated area of the northern and western regions, whereas the north-western part of Sennar state borders the tongues of the lighter-textured soils of Managil ridge. To illustrate the danger of sand encroachment as a sign of desertification of the northwest part of Gezira state, an area of 34 km2 of alluvial clay plain has been invaded and covered by sands from the surrounding sand dunes (Fig1). However there is hardly any effective research done to monitor or combat the approaching danger of desertification. The only effort implemented in this respect was the ‘Green belt’ of Eucalyptus species grown north of Gezira state and more Mesquit trees east of the White Nile at Hashaba area. Previously “Forest” plots existed within the Gezira irrigated scheme; also reclamation trials have been carried out in north Gezira salt-affected part (Mustafa,H.F., 1998). A plan of action has to be drawn for Gezira and Sennar states following an overall study of the problem of desertification. Such mode of scientific investigation can be justified by threatening of the sand creep from the two bordering directions towards the northern and western regions. The increasingly expected hazard of desertification includes even the irrigated tracts of lands, save the bare and seasonally rainfed fields, where proper management of cultivated crops is envisaged. However this effort requires the collaboration of research units, universities, local government and land users as guided and supervised by the Desertification and Desert Cultivation Studies Institute in Khartoum University.


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Monitoring of Sand Dune Movement at North-West Gezira Landsat image for (1985,1975,1949)

Scale 1:400,000 ´

Fig. 1 : Monitoring of Sand Dune Movement at North-West Gezira Landsat image for (1985, 1975,

1949)


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PLAN OF WORK

Objectives The main objective of this proposed plan of action is to promote the process of combating desertification through feasible preventive and protective measures, where a comprehensive technological program will be established for the development and management of the agro forestry. Specific objectives for Gezira and Sennar states endorse the control measures of sand movement along their northwestern fringes by shelterbelts of environmentally adapted tree and grass species, the recommended management practices of the cultivated tracts and the reclamation of Gezira and low-fertility parts of northwest Sennar. Basic data for both states is to be acquired. Strategy This plan aims at the preservation of the natural ecosystem of Gezira and Sennar states including the future projection of the growing population and the diminishing returns of the environmental inputs (Purnell,M.F. and Venema,J.H., 1976). Priority research themes These themes may involve the improvement of degraded cultivated lands (both irrigated and rainfed) and the conservation of the susceptible erodable lands (either by water, wind or mismanagement). Although all parts of the two states are at stake, still the northwestern parts of the Gezira and Sennar states represent priority research areas due to their proximity to the invading desert. In addition to these experimental sites, other susceptible parts to desertification could be included in the overall plan i.e. Abu Guta, Butana, Tahamid, Rahad, Guneid, North-West Sennar and Kenana schemes. Research plan To set an actual plan of action fulfilling the objectives of combating desertification in Gezira and Sennar states, a number of steps have to be considered: - Collection of data, including maps of location, hydrology, vegetation, soils and land use.

Also all relevant literature of research and control efforts is to be compiled as well. - Formation of a specialized cadre to review the prevailing biophysical socio-economic and

political conditions related to the two states. - Conducting a comparative study between the past and present situation of the fore-

mentioned aspects so as to evaluate the magnitude of the problem. - Selection of two experimental sites (e.g. north-west of the two states) for planting

environmentally adapted species. - Follow-up of results of the experimental sites prior to the evaluation of the effects of

control measures applied against the hazard. - Monitoring the trend of desertification through time by integrated information system will

be of high need (using landsat images and/or maps of similar landuse and crop yield potentials)(Imad,A.A., etal, 2000).

- Monitoring of all other aspects of land degradation (e.g. erosion salinization, pollution, etc.) for their potential impact on land utilization productivity both in irrigated and rainfed areas i.e. by measuring environmental stability index.


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- Undertaking a feasibility study prior to the implementation of the research plan for provision of necessary funds. Thus a scheduled plan of action is proposed for each state.

- Inclusion of land dune stabilization as integral activity of the overall research program (Table1).

Activities Area feddans 1 1.1 1.2 2 2.1 3 3.1 4 5 6

Two planting (Irrigated & Rainfed) Front rows (Laot, Kitir, Turfa, Tundub) Back rows (Eucalyptus, Seyal, Sidir, Sunut) Ranges: Grass-seedlings Dune stabilization Mesquite and/or Petro-chemicals Extension services (T.V, Radio, Leaflets, Seminars, etc) Alternative energy sources Ohers (Experimentation, Scholarships, Training Administration, etc)

200,000 200,000 400,000 200,000

Table 1. A scheduled plan of action for each proposed research site in Gezira and Sennar states.

PROPOSED RESEARCH PROGRAM

This program aims at establishing comprehensive technologies for the management and development of agroforestry. Natural vegetation zones Acacia seyal (Talh) belt This belt lies between 400 to 800 mm isohyets. Experimental sites are selected and reserved in agricultural schemes to: 1. Study and monitor flowering and seeding of Acacia trees. 2. Specify the critical moisture content necessary for growth (including water conservational

measures). 3. Specify methods, rate and timing of planting seeds and young trees. 4. Specify lateral position of tillers and the suitable time for cutting and activating the trees

(including natural or agronomic biofactors influencing heir growth). 5. Specify research site (size 625m2) for data collection, i.e.: a) Survey of land use resources, including type and density of vegetation (Van der kevie,W.,

1976). b) Comparing local sites with similar international sites (IUFRO). c) Correlating product versus factors of production (climate, etc). d) Experimenting on agronomic production factors. Acacia mellifera (Kitir) belt This belt is north of the Talh belt with less than 400 mm isohyets. Experimental sites are selected and reserved in agricultural schemes to:


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1. Study and monitor flowering and seeding of Acacia trees. 2. Specify the critical moisture content necessary for growth (including water conservational measures). 3. Specify methods, rate and time of planting seeds and young trees. 4. Specify lateral position of tillers and the suitable time for cutting and activating the trees (including natural or agronomic biofactors influencing their growth). 5. Specify research site (size 625 cm2) for data collection, i.e.: a) Survey of land use resource, including type and density of vegetation (Van der kevie,W., 1976). b) Comparing local sites similar international sites (IUFRO). c) Correlating product versus factors of production (climate, etc.). d) Experimenting on agronomic production factors. Acacia nilotica (Sunut) belt This belt lies on both banks of Blue Nile, where, death of old trees due to silting-up in low-lying sites and difficulty of regenerating new trees occur. The foreseen activities aim at 1. Studying the factors affecting silting up. 2. Estimating the amount of yearly silting up. 3. Studying the characteristics of soil deposits. 4. Studying the effect of silting up on establishment of tree roots. Irrigation zones Eucalyptus plantation The foreseen activities include 1. Genetic improvement of eucalyptus species. 2. Agronomic studies related to productivity. 3. Ecological and silvicultural studies as related to productivity. Shelterbelts for agricultural schemes A shelterbelt model will be made for each scheme. Irrigation canals shelterbelts The foreseen activities include 1. Selection of suitable species. 2. Study of suitable technologies to grow these species. Other relevant investigations 1. The mismanagement of the agricultural schemes (both rainfed or irrigated) leads to deterioration of the cultivated lands as reflected by less productivity due to poor physiochemical properties of the soils. Such tracts of land may be deserted and hence become susceptible to desertification especially after their natural flora has been removed. Also some


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of these traces may undergo salinization and/or sodication (e.g. north Gezira, which requires reclamation to improve its productivity). 2. Water harvesting is an important practice in arid areas where the rainwater is collected and stored for use during the critical time. Both climate and soils have an effective role in the system of water harvesting (Amer,N.M., 1993). The role of climate is through precipitation and evapotranspiration (Farah,S.M., etal, 1996). Effective soil factors include texture, depth, infiltration rate, water availability, slope and salinity. The study of all these factors (climate and soil) will help in the establishment of pasture and forages thus reducing the hazard of desertification by vegetation cover and stabilizing the bare land surface. 3. Some tree species are capable of N-fixation. Such trees may be identified so as to observe how much of this nutrient is added to the soil per growing season. 4. Seed propagation and breeding of selected tree species may be incorporated during the research program. 5. A socio-economic study of all the research program localities may be developed as related to the welfare of the people. Nevertheless, the implementation of this research plan of action is a multi-disciplinary project involving almost all the sectors of the society i.e. government, research centers, universities, specialized organizations and the users.

REFERENCES

[1] N.M. Amer(1993). "Water harvesting for supplementary irrigation. Regional Seminar on Cereal Production", Damascus, Syria, (1993). [2] S.M. Farah, I.A. Ali, S. Inanaga. "The role of climate and cultural practices on land degradation and desertification with reference to rain-fed agriculture in Sudan". Proceedings of the Fifth Int. Conference on Desert Development. Taxas Tch. University, USA, (1996). [3] A.A. Imad, M.F. Hassan, A.S. Ahmed. "Importance of information system for progress of research into desertification and sustainable development of the natural resources", LWRC, ARC, Medani, Sudan, (2000). [4] H.F. Mustafa. "Forestry Research Program During (1998-2000)". Forestry Research Centre, ARC, Sudan, (1998). [5] M.F. Purnell, J.H. Venema. "Agricultural Potential Regions of Sudan". UNDP project working paper. Soil Survey Administration, Medani, Sudan, (1976). [6] W. Van der Kevie. "Climatic Zones in the Sudan". Bulletin No. 27, SSA. Wad Medani, Sudan, (1973).


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DIAGNOSTIC OF DEGRADATION PROCESSES OF SOILS FROM NORTHERN TOGO (WEST AFRICA) AS A TOOL FOR

SOIL AND WATER MANAGEMENT

Rosa M Poch*, Josep M Ubalde

Department of Environment and Soil Sciences, Universitat de Lleida, Catalonia, Spain

Abstract In order to carry out a conservation project in Northern Togo, a survey was conducted to identify soil and water degradation processes. The model area occupies 100 ha and is representative of the Savannah Region of northern Togo (West Africa). This area belongs to the Centre de Formation Rurale de Tami, where several problems due to sheet and gully erosion, overgrazing, waterlogging and trafficability were identified. Parent materials are Precambrian granites and gneisses with granodioritic composition. The soil moisture and temperature regime are ustic and isohyperthermic respectively (SSS 1999). The vegetation type is a woody savannah, with a marked agricultural influence. A soil survey of the model area at a scale 1:5000 (1 observation / 10 ha) showed several mapping units classified as Geric Plinthosol, Orthiplinthic and Arenic Acrisol, Arenic Gleysol, Stagnic, Endoeutric Plinthosol (agricultural soils) and Pachic and Gleyic Phaeozem (natural soil) (FAO 1998). Physical, hydrological, chemical and micromorphological analyses showed that the main problems related to the agricultural soils were waterlogging in microdepressions due to saturated flow during the wet season, shallowness due to sheet erosion, soil acidity, lack of nutrients and organic matter, and low water holding capacities. On the contrary, undisturbed forest soils show very favourable physical and chemical properties for root development. The results were used to design soil and water conservation works as drainage ditches, zonation of crops and recommendation of management practices for each unit, as well as to assess the potential of the soils of the region to improve their quality with appropriate management. The practices are recommended not only to improve agricultural production, but also as mechanisms to use soils as carbon sinks in the frame of global climatic change policies.

INTRODUCTION AND OBJECTIVES

Degradation of soils due to human activity, mainly as soil erosion, is one of the factors affecting the future land use of the Savannah region in West Africa. In this region, an increase of the population (locally exceeding 300 inhabitants km-2) and a decline in the agricultural yield has already been recorded [1].

The recovery or maintenance of the soil quality requires a diagnostic of the degradation processes, and establishing a hierarchy of the soils to manage and the measures to apply in order to optimize the economical and human resources. The objectives of this research were to carry out the diagnosis of degradation processes through gathering of soil morphological and analytical information that are easy to collect, and to assess the type and severity of soil degradation and recovering possibilities.

MATERIAL AND METHODS

The physical environment This work was carried out in a model area of 100 ha located in the Savannah Region of northern Togo (West Africa). This area belongs to the Centre de Formation Rurale de Tami,


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where peasants of the region are trained on agriculture and husbandry during two years. This centre is located 20 km east from Dapaong, the capital of the region.

The climatic data was taken from a series of 19 years from the meteorological station of Dapaong. The climate is sudano-guinean, characterized by a dry season from October to April and a rainy season from May to end of September. During January and February a strong dusty wind from the NE (harmattan) reinforces the dryness of the season. Annual precipitation is 1001 mm, with a maximum in August (266 mm) and a minimum in January (0 mm). Interannual variability is high: within the studied series, annual rainfall ranges from 649 to 1370 mm. The maximum precipitation values in 24 h are 62, 86 and 107 mm for recurrence periods of 2, 10 and 100 years. Mean annual temperature is 28.1ºC, ranging from 25.2 ºC (August) to 31.8 ºC (May). The difference between the average of the maxima (33.6 ºC) and the average of the minima (22.5 ºC) is higher than the annual variation of the monthly mean, characteristic of a iso-temperature regime. Potential evapotranspiration according to Thornthwaite is 2057 mm, with a maximum in April (280.8 mm) and a minimum in August (106.7 mm). The soil moisture and temperature regime are ustic and isohyperthermic respectively [8].

Geologically the region belongs to the sedimentary or epimetamorphic cover formations from the Voltaian. The study area is found on the birrimian (Precambrian) basement consisting on granites and gneiss with granodioritic composition. The rock presents abundant large plagioclase crystals slightly oriented. Locally, quartz and pegmatite veins are found [2].

The savannah region is characterised by a rolling landscape consisting of sequences of platforms, valleys and slopes without precise limits but with a great relevance in soil forming and soil erosion processes. These units are found in the model area, at altitudes from 250 to 270 m asl.

The vegetation type is a woody savannah, with a marked agricultural influence. The dominant species are Parkia biglobosa and Butyrospermum parkii as trees and Acacia sieberiana as bush. Riparian and ruderal vegetation are also present. A small remnant of dry sudanian forest vegetation consisting of Anogeissus leiocarpus, Butyrospermum parkii, Bauhinia thonningii and Ziziphus mauritiaca as main species has been preserved as ‘sacred forest’ (fôret sacrée). The main land uses of the region are represented in the study area: 60% of the area is devoted to rainfed crops, mainly for self consumption (peanuts, soja, corn, sorghum, millet, rice) but also cash crops as cotton, occupying 8% of the area. The rest are pastures (30%), forest or abandoned cropland. The crop yields are low due to low fertility of the soils and a lack of fertilisation: 1850 kg ha-1 for corn and 1500 kg ha-1 for rice.

Methods

The soils of the model area were surveyed at a scale 1:5000 (1 observation/10 ha). Profile description was carried out in the main geomorphological and vegetation units previously defined. Chemical and physico-chemical characterisation was done in some of the profiles according to Porta et al. [5].

Tests of infiltration by a double-ring infiltrometer and permeability by the inverse Auger-hole method were performed in the main soil units of the study area.

Three of the profiles were sampled for the micromorphological study. Ten thin sections were made according to Guilloré [4] and described following the guidelines of Stoops [6].


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RESULTS AND DISCUSSION The soils: formation and characteristics The soils are developed either on saprolites of igneous rocks, on coarse colluvia of sands and petroplinthite gravels. Table 1 presents the main soils related with the geomorphological unit, the landuse/vegetation and the parent material. They classify as Ultisols, Vertisols and Mollisols, depending on the degree of stability and lack of soil erosion. The morphology and micromorphology of the representative soils are found in Table 2 and 3. The soil formation processes on the saprolite is fully displayed in Profile 9, who has the most complete sequence of horizons. According to this sequence, the alteration of the saprolite consists in the weathering of the plagioclases to kaolinite or 2:1 clays, depending on the drainage class of the soils. Profile 9 and 7 correspond to a vertic horizon, with frequent slickensides and striated b-fabrics. The clay has later been dispersed and illuviated, as it is shown by the microlaminated clay coatings in these horizons and in the saprolite itself. Formation of plinthic horizons would proceed from the more sandy horizons, with Fe-oxides accumulation, either absolute accumulation by direct release from mineral weathering, or residual accumulation after clay illuviation. This accumulation is strong enough for an incipient cementation in the walls of Profile 9, and is generalized in the platform soils of the region.

Tentative classification Position FAO 1998 [3] SSS 1999 [8]

Landuse / vegetation

Parent material Modal profile

Platforms Geric Plinthosol

Haplic Plinthustult cotton, corn, peanuts

Saprolite of syenites and gneiss

1,3

Upslope Orthiplinthic Acrisol or Lixisol

Plinthic Kanhaplustult


8

Footslope Arenic Acrisol or Lixisol

Arenic Kanhaplustult

Colluvium of quartzitic sands with petroplinthitic gravels

4

Slopes

Eroded slope Hypereutric Vertisol

Chromic Haplustert

soja, corn, peanuts, cotton, millet, sorghum, pastures Saprolite of syenites and

gneiss 7

Arenic Gleysol Aquic Quartzipsamment

Pastures, rice

Colluvium of quartzitic sands with petroplinthitic gravels

6 Strong accumulation

Pachic Phaeozem

Pachic Vermustoll Sacred forest


5

Valley bottoms

Slight accumulation

Stagnic, Endoeutric Plinthosol (inc. Gleyic Phaeozem)

Oxyaquic Argiustoll (inc. Oxyaquic Haplustoll)

Pastures, rice

Saprolite of gneiss and sandy colluvium on top

9,2

Table 1 : Classification, geomorphology and landuse of the soil mapping units in the study area

The evolution from this model produces different soil patterns depending on the local

conditions: - Soils on stable positions, not disturbed nor cultivated, under a dense vegetation cover (Profile 5) undergo an intense OM accumulation. The relatively high base content of the saprolite allows even the formation and accumulation of calcite coatings and nodules, caused by root and microbial activity. - Soils with different degrees of erosion lack this organic-rich top horizon and have sandy surface horizons instead, sometimes overlying the plinthic horizon (profiles 1,3). In the most severe cases, a slight acidification of the topsoil is proceeding (Profile 1). - Redoximorphic features are generalized in the soils of the area, as Fe oxi-hydroxide accumulation as concentric nodules, hypocoatings around pores and impregnative nodules, either orthic or anorthic. The high permeability of surface horizons in contrast to the


190

impervious vertic or plinthic horizons allows for subsurface saturated flow to occur, which is also the cause of erosion of the surface sands which are accumulated on the slopes (Profile 6) and in the valley bottoms (Profile 2)

Pro-file

Horizons

Depth (cm) Colour (moist)

Structure (primary, secondary)

Texture Coarse fragments

Consistence

Roots Mottles Accumulations/surfaces Diagnostic horizon [3]

1 Ap Bt1 Bts2 Bts3

0-20 20-33 33-55 55->60

7.5YR4/4 10YR6/3 7.5YR5/6 10R4/6

vw-sab-c - - -

LS SL SCL SCL

16-35% gr >70%gr >70% >70%

l-vf c-fm vc vc

f abs abs abs

abs abs abs abs

Abs silt cutans silt cutans, soft iron concretions silt cutans, soft iron matrix

ochric argic plinthic plinthic

2 Apg1 Ag2 Bs 2C 3C

0-10 10-25 25-63 63-100 >100

10YR3/3 10YR3/3 10YR4/6 7.5YR4/6 -

m-sab-m w-sab-m - - -

LS LS CS CS -

abs fr-gr vfr-gr vfr-gr >70%

vc-fm vc-fm c-vf s c

f f abs abs abs

fr-ox fr-ox ab-ox abs -

Abs abs iron coatings on coarse fragments abs Abs

mollic mollic - - -

3 Ap1 Ap2 Bw 2Bts

0-10 10-19/25 19/25-40 40->70

5YR2/3 5YR2/3 7.5YR4/6 5YR3/6

vw-c-m vw-sab-c - -

LS CL CS -

fr-gr vfr-gr ab-gr ab-gr

l-s c-f c vc

f f abs abs

abs abs abs abs

Abs abs abs iron impregnations on soil mass

ochric ochric - plinthic

4 Ap1 Ap2 Ap3 Bw Bts1 Bts2

0-10 10-20 20-26/43 26/43-50 50-68 68->90

5YR4/6 5YR4/8 5YR3/6 5YR3/6 5YR4/6 5YR4/6

abs abs abs abs abs abs

mS mS mS mS CS CS

f-gr f-gr f-gr f-gr f-gr f-gr

l c s s s l

f f abs abs abs abs

abs abs abs abs abs f-red

Abs abs abs abs few clay cutans few clay cutans

ochric ochric - - argic argic

5 Oa Oi A1 Bw1 Bw2 Bwg3

-5 - -3 -3-0 0-16/19 16/19-43 43-75/85 75/85->90

- 7.5YR1.7/1 7.5YR2/1 10YR3/2 10YR2/3 10YR4/3

abs abs vw-c-m,w-sab-m w-sab-c m-sab-m s-sab-m

- - CS CS CS CS

- - vf-gr vf-gr vf-gr f-gr

- - l-vf c-vf c-f c-fm

- - ab ab ab fr

- - abs abs abs ab-red

- - abs abs abs pressure faces

- - mollic mollic mollic -

6 Ap Bg1 Bg2 Bs3

0-15/21 15/21-37 37-65 65->80

10YR3/3 10YR4/6 10YR5/6 10YR5/6

vw-sab-f vw-sab-m w-sab-m -

LS SL CS CS

abs f-gr f-gr >70% gr

l-vf l c-f vc

f f vf abs

abs fr-ox ab-ox abs

abs few skeletans on root channels few skeletans on root channels abs

ochric - - -

7 Ap 2Apg2 2Bssg 2Bt

0-2 2-17 17-35 35->55

10YR4/6 2.5Y4/6 2.5Y6/4 2.5Y6/5

abs m-sab-m s-sab-m -

S C C SC

ab-gr abs abs abs

l vc vc vc

abs f f abs

abs fr-ox fr-ox abs

abs abs frequent slickensides frequent silt coatings on sands

ochric ochric vertic -

8 Ap Bw1 Bt1 Bt2

0-18 18-33 33-53 53->70

7.5YR4/6 7.5YR4/6 7.5YR4/6 10YR5/6

abs abs abs abs

mS LS SC C

f-gr v-gr vf-gr f-gr

l c c vc

f f vf abs

abs abs abs abs

abs Fe-Mn nodules, soft id, silt coatings, vertical cracks Fe-Mn nodules

ochric - argic argic

9 Apg Bg1 Bst2 Bsm3 Bssg4 C

0-20 20-28 28-60 60-73 73-150 >150

10YR3/3 10YR4/6 10YR6/6 10YR5/6 2.5Y6/6 2.5Y7/2

w-sab-m vw-sab-m vw-sab-f abs vs-sab-f, m-p-c parent material

S S LS – C -

fr-gr fr-gr fr-gr vfr-gr f-gr ab

l c c vc vc vc

f f abs abs abs abs

fr-ox fr-ox abs abs fr-ox abs

abs abs few clay cutans, Fe-Mn nodules weak Fe cementation abundant slickensides few silt coatings

mollic - argic plinthic vertic -

structure: s: strong, m: moderate, w: weak; sab: subangular blocky, g: granular; f: fine, m: medium, c: coarse, vc: very coarse, abundance: abs: absent, c: common, fr: frequent, vfr: very frequent, ab: abundant, coarse fragments: gr: gravels, consistence: l: loose, vf: very friable, f: friable, fm: firm, s: soft, c: compact: vc: very compact, size f: fine, c: coarse, vc: very coarse, roots: f: few, fr: frequent, ab: abundant, mottles: abs: absent, f: few, fr: frequent, ox: oxidation, red: reduction

Table 2 : Field description of the modal profiles


191

Microstructure and porosity Micromass Pedofeatures PROFILE 1 Bt1 25-35 cm Apedal, vughy, 30%, vughs, vesicles, biopores, planar.

Brownish mixture of clay and silt, mosaic and nodulostriated b-fabric

Intra-aggregate impregations of Fe-oxi-hydroxides, halo, very coarse sand size. Few silt and clay intercalations around some vughs, moderately oriented, laminated, mottled. Few clay coatings, around fissure walls, limpid, microlaminated, medium sand size, stained with

fe-oxides. Nodules of Fe-oxi-hydroxides, very coarse sand and gravel size, rounded, concentric, with

inclusions of runiquartz, anorthic, with higher quartz content than the groundmass. Bts2, 30-40 cm Pedal, subangular blocky, very coarse sand size. 25%, planar voids and vughs

Id before Nodules of Fe-oxi-hydroxides, very coarse sand and gravel size, rounded, concentric, with inclusions of runiquartz, anorthic, with higher quartz content than the groundmass.

General impregnation of Fe-oxi-hydroxides, with different degrees of intensity. Clay intercalations along walls of planar voids, probably kaolinite

Bts3, 60-73 cm Apedal, vughy, 20%, vughs and planar voids

Id before Clay coatings and infillings around pores, occupying 30% of the soil. Nodules of Fe-oxi-hydroxides, very coarse sand and gravel size, rounded, concentric, with

inclusions of runiquartz, anorthic, with higher quartz content than the groundmass. Orthic nodules of Fe-oxi-hydroxides, aggregate, diffuse, halo, intra-aggregate.

PROFILE 5 A1, 0-15 cm Pedal, granular, coarse sand size, well developed. 40%, compound packing pores, biopores, accomodated planar voids

Dark brown mixture of silt, clay and organic pigment, mosaic striated b-fabric

Passage features as infilled channels Coatings of acicular CaCO3 crystals in some biopores, apparently associated to organic remains. Rounded nodules of Fe-oxi-hydroxides. Few micritic nodules of CaCO3, medium sand size.

Bw1, 20-30 cm Pedal; Primary: subangular blocky, 1 cm, well developed; Secondary: channel. 30%, planar pores, biopores.

Light brown mixture of silt, and clay, mottled; mosaic-, cross- and nodulostriated b-fabric

Concentric nodules of Fe oxi-hydroxides, very coarse sand and gravels, granostriated. Few diffuse nodules of Fe oxi-hydroxides, impregnated, orthic, coarse and very coarse sand size. Coatings of acicular and microsparitic CaCO3 in some pores

Bw1, 30-43 cm Pedal. Primary: subangular blocky, 3 cm, well developed; Secondary: channel. 35%, planar voids, biopores.

Yellowish brown mixture of clay and silt, grano- and porostriated b-fabric

Passage features as infilled channels Coatings of acicular and microsparitic CaCO3 in some pores Kaolinite coatings around a planar void and around anorthic nodules Nodules of Fe oxi-hydroxides, impregnated, orthic (diffuse) and anorthic, very coarse sand size. Impregnations of Fe oxi-hydroxides intra-aggregate, very coarse sand size

Bw2, 50-60 cm Pedal, Primary: subangular blocky, 4 cm, moderately developed; Secondary: channel. 30%, planar voids and biopores

Yellowish brown mixture of clay and silt, mosaic- granostriated and slightly cross striated b-fabric

Coatings of acicular CaCO3 in biopores, crystals 0.3 mm long and 0.1 mm thick. Impregnative hypocoatings of microsparite in biopores, 0.25 to 0.5 mm in diameter Rounded nodules of microsparite, medium sand. Microsparite and needles of CaCO3 dispersed in the groundmass.

PROFILE 9 Ap, 0-13 cm Apedal, vughy. 20%, vesicules, biopores

Brownish mixture of clay, silt and organic pigment, undifferenciated b-fabric, locally mosaic striated.

Coatings and infillings of mottled clay, microlaminated, colours of 1st and 2nd order, around channels, 0.1 to 0.25 mm thick.

Frequent hypocoatings of Fe oxi-hydroxides, impregnative, around channels Rounded nodules of Fe oxi-hydroxides, medium sand, orthic and anorthic

Bst2, 33-43 cm Pedal. Primary: subangular blocky (3-4 cm in diameter), weakly developed; Secondary: vughy; 30%, planar voids, vesicles

Yellowish brow mixture of clay and silt, mottled, mosaic striated b-fabric, locally nodulostriated

Frequent intercalations of limpid clay, microlaminated, 1st order colours, up ot 2 mm thick. Clay coatings and infillings in channels, < 0.25 mm thick Rounded nodules of Fe oxi-hydroxides, with quartz inclusions, sharp boundary. Rounded nodules of Fe oxi-hydroxides, impregnative, diffuse boundary. Impregnative Fe hypocoatings along channels.

Bts2, 43-60 cm Pedal. Primary: subangular blocky (1-2 cm in diameter), moderately developed; Secondary: channel. 30%, planar voids, channels, vughs and vesicles.

Id before Rounded nodules of Fe oxi-hydroxides, with quartz inclusions, sharp boundary, very coarse sand, granostriated, porous.

Rounded nodules of Fe oxi-hydroxides, impregnative, diffuse boundary. Impregnative Fe hypocoatings along channels Clay coatings, infillings and intercalations, limpid, microlaminated, kaolinitic, <0.5 mm thick,

associated to the previous Fe-hypocoatings. Cemented areas of Fe oxi-hydroxides, associated to clay coatings and infillings.

Bssg4, 80-85 cm Apedal, channel. 20%, vughs and vesicles

Id before Few nodules of Fe oxi-hydroxides, with quartz inclusions, sharp boundary, very coarse sand, granostriated, porous.

Rounded nodules of Fe oxi-hydroxides, impregnative, diffuse boundary. Impregnative Fe hypocoatings along channels Clay coatings, infillings and intercalations, limpid, microlaminated, kaolinitic, <0.5 mm thick,

associated to the previous Fe-hypocoatings. Bssg4, 140-155 cm Pedal, subangular blocky, 1 cm in diameter, moderately developed, 20%, planar voids, vughs, biopores.

Light yellow mixture of clay, silt and Fe oxides, poro- and granostriated b-fabric, very frequent slickensides

Clay coatings and infillings, limpid or mottled, microlaminated, coarse to very coarse sand size, broken, some included in the groundmass, possibly kaolinite.

Impregnative nodules of Fe oxi-hydroxides, aggregate, intra-aggregate. Halo nodules of Fe-oxi-hydroxides intra-aggregate. Impregnative Fe hypocoatings along channels

C, 160-165 cm Apedal, granite saprolite, 10% Microlaminated clay infillings and coatings in planar voids

Newformed clay masses including quartz grains

Table 3 : Summary of the micromorphology of profiles 1,5 and 9


192

Degradation processes Soil erosion is one of the main problems, mainly as splash and sheet erosion. The most affected soils are those on the platforms and slopes. Soil erosion also occurs by concentrated runoff, as rills and gullies. Retreats of 2 m of the gully heads have been observed after a single storm event.

The erosion is due to intense rainfalls during the wet season, low structural stability, crops with low coverage and fields with an excessive length with low runoff control. In the case of the gullies, saturation flow in the sand colluvia runs along the slopes over the more clayey horizons and concentrates at the gully head. The low cohesion of the saturated sands at this point is the responsible of the collapse and retreat of the gully heads. Regarding the chemical and physical fertility (Table 4), the main problems are the low OM contents (<1%), except in the forest soil (10%). The sandy soils are moderately acidic, due to base leaching, but without reaching pH values less than 5.5. Acidification is not very intense in the soils of the area.

Profile

Horizons pH H2O, 1:2.5 OM %

Coarse sand %

Fine sand %

Total sand %

Coarse silt %

Fine silt %

Total silt %

Clay %

CEC cmol+/kg

V (%) total Fe (g/kg)

P ppm K ppm

1 Ap Bt1 Bts2 Bts3

5.8 6.3 6.2 6

0.6 0.5 0.3 0.2

61.2 41.8

16.6 13.0

77.8 54.8 41.3 36.7

7.6 8.7 8.8 7.9

3.8 10.6 8.8 11.4

11.4 19.3 17.6 18.3

10.8 25.9 41.1 44.0

5 26.9 - 38.8 73.0 71.0

8 37

2 Apg1 Ag2 Bs 2C 3C

6.2 6.6 7.4 7.4

1.6 0.6 0.1 0.1

42.4 52.1

15.3 8.3

57.7 60.4 91.1 92.7

9.3 5.0 1.5 1.5

16.7 16.1 1.8 2.3

26.0 21.1 3.3 3.8

16.3 18.5 5.6 3.5

8.9 74.1 - 11.7 8.8

6 47

4 Ap1 6.1 0.4 58.1 23.0 81.1 11.0 3.1 14.1 4.8 7 22 5 Oi

A1 Bw1 Bw2 Bwg3

7.7 7.9 8.2 8.5 8.6

13.1 9.7 1.6 1.6 0.7

- 25.7 27.9

- 11.1 11.7

- 36.8 29.6 37.0 38.7

- 10.7 9.6 9.2 9.4

- 14.8 13.9 14.1 12.8

- 25.3 23.3 23.3 22.2

- 37.7 36.9 39.7 39.1

- 39.1

- 100

15 15 3 2 2

>600 >600

7 Ap 2Apg2 2Bssg 2Bt

- 7.6

- 0.3

- 21.5

- 8.6

- 30.1

- 5.5

- 9.0

- 14.5

- 55.4

- 21.8

- 83.1

- 10

- 86

9 Apg Bg1 Bst2 Bsm3 Bssg4 C

6.8 7.7 7.8 7.7 6.5 8.8

0.9 0.3 0.3 0.2 0.1 0.0

50.6 20.3 70.9 73.1 61.3 51.7 27.4 86.2

9.1 8.2 5.4 3.8 8.7 4.0

6.4 5.5 5.7 5.6 16.7 3.8

15.5 13.7 11.1 9.4 25.4 7.8

13.6 13.2 27.6 38.9 47.2 6.0

4.7 3.3 6.0 7.8 3.9 15.0

60.7 70.1 65.3 73.2 100 22.2

8.2 9.5 17.6 31.4 36.1 3.3

3 18 <10 19 28 69 23

Table 4 : Physico-chemical characteristics of the modal profiles

Table 5 shows that infiltration capacity values range from moderate (valley bottoms) to very fast (platforms). Bulk density values are high, between 1450 (valley bottoms) to 1750 kg m-3 (sands of the platforms). Permeability is low (valley bottoms) to moderate (rest). All these properties indicate a larger probability of erosion and flooding by intense rains at the valley bottoms; and by long and high volume rains at the platforms. The main limitations for the platforms are low AWC, lack of nutrients, flooding. For the slopes, we differenciate the high areas, with problems of lack of rooting depth, flooding, lack of nutrients and erosion. In the lower part, one has to add low AWC. The valley bottoms are mainly affected by flooding.


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Modal profile Infiltration capacity (mm h-1)

Bulk density of the surface horizon (kg m-3)

Permeability class Available water capacity AWC (mm)

1 3

100 250

1708 1770

- -

40

2 9 6

75 60 50

1418 1480 1440

- Moderate

Slow

48 100 88

5 100 1195 Moderate 200 7 60

70 1369 1306

Moderate -

110

8 4

170 320 50

1612 1670 1560

Moderate - -

94 50

Table 5 : Hydrological properties of the modal profiles

CONCLUSIONS

The results show a very strong influence of human activity in soil formation and distribution. Erosion, either geological or human-driven (deforestation, fires) has acted in all soils except the undisturbed one under a permanent forest (Profile 5). Its properties show as well a high potential quality of the soils of the region, both regarding agricultural yields and also as carbon sink in the frame of global change policies.

The fertility of the most degraded soils cannot be improved significantly unless large inputs of organic matter and strict conservation management practices are applied, which are not possible given the availability of organic residues and the socio-economical characteristics of the region [9]. Instead, the application of good management practices that can be adapted to the conventional agricultural systems in the moderately degraded soils -as the ultisols-, would optimize the resources, keeping or improving soil quality and leading to higher yields.

In this sense, the management recommendations have been the control of surface runoff by a new outline of the fields and a network of contour drainage ditches, the control of gully erosion by permeable stone dams, and the management of organic matter: composting, crop residue management and bush fences. A new land use redistribution made from soil quality and soil erosion maps was also proposed [9].

ACKNOWLEDGEMENTS

We acknowledge the inconditional help, willigness and enthusiasm of Felipe García (CTFC), and the funding of Diputació de Lleida, Proide and Centre de Cooperació Internacional - Universitat de Lleida.

REFERENCES [1] P. Brabant, S. Darracq, K Egue, V. Simonneaux. “Togo. État de degradation des terres resultant des activités humaines. Notice explicative de la carte des indices de degradation”, Éditions de l’ORSTOM, Paris, 57 pp. (1996)


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[2] J. Collart, I. Ouassane, J.P. Sylvain. “Notice explicative de la carte géologique à 1/200 000. Feuille Dapaong, 1e Édition” Mémoire n. 2. République Togolaise, Ministère de l’Équipement, des Mines et des Postes et Télécommunications, DG Mines, Géologie et du Bureau National des Recherches Minières. (1985) [3] FAO. "World reference base for soil resources (WRB)", World Soil Resources Report No. 84 , FAO/ ISSS/AISS/IBG/ISRIC, Rome, (1998). [4] P. Guilloré. “Méthode de fabrication mécanique et en série de lames minces”. CNRS and INA-Paris-Grignon. Dep. Sols. Thiverval.Grignon. 22p. (1980) [5] J. Porta, M. López-Acevedo, R. Rodríguez. “Laboratori d’Edafologia”. Universitat Politècnica de Catalunya. 193 pp. (1993) [6] G. Stoops. “Guidelines for analysis and description of soil and regolith thin sections”, Soil Science Society of America, Madison, Wisconsin. 184 pp. (2003) [7] R.M. Rochette. “Le Sahel en lutte contre la desertification: leçons d’expériences”. Weikersheim, Margraf. 592 pp (1989). [8] SSS-Soil Survey Staff. "Soil Taxonomy. A Basic System of Classification for Making and Interpreting Soil Surveys ", USDA, Washington. (1999). [9] J.M. Ubalde, R.M. Poch. “Projet de conservation des sols et des eaux dans la zone soudano-guinéene au Centre de Formation Rurale de Tami (Togo)”, Bulletin du reséau erosion 20, pp 485-495, (2000)


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WORKSHOP Theme: Land Evaluation and Land Degradation

Convenors: A.; Verdoodt, W. Cornelis, E. Van Ranst, H. Verplancke, D. Gabriëls

CONCLUSIONS

This workshop focussed on two themes: «Land Evaluation» and «Land Degradation». The objectives were (1) to give an overview of the latest developments in both disciplines, (2) to review the current activities of our alumni within these fields of expertise and (3) to hold a round table discussion on the issues raised, on new research questions and changing needs. Although both themes were addressed separately, striking similarities and crosscutting issues could be identified throughout the workshop. Both sciences evolved from experimental modelling, over process-based modelling, towards more participatory approaches, making full use of the local knowledge on land suitability and risks for land degradation. Recent research topics in both disciplines focus on identifying soil quality indicators. The research topics presented by the 3 alumni illustrated these developments very well. Dr. Pratummintra explored the possibilities for oil palm production in Thailand using land suitability classification and crop modelling techniques. Dr. Boniao on the other hand, identified bio-indicators of soil degradation following forest to agricultural land conversion in the Philippines; a presentation touching both land evaluation and land degradation issues. And finally, within the «Land Degradation» theme, Dr. Poch illustrated how one combats soil degradation in Togo making use of soil quality maps and local capacity building. Each presentation was followed by a short discussion with the alumni attending the workshop. The most important overall conclusion of the workshop was that current methodologies in both disciplines integrate – using a sound scientific approach - traditional models building on expert knowledge with more recent process-based models and strongly valuable grass-roots knowledge.

Workshop IC-PLR 2006 – Theme D – Soil survey and inventory techniques

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WORKSHOP THEME D – SOIL SURVEY AND INVENTORY TECHNIQUES

Sub-theme : Developments in soil (attribute) mapping with a application in mapping groundwater depth P.A. Finke

Paper/poster : Using geographic information systems and global positioning system to map soil characteristics for land evaluation – P. Wandahwa, J.A. Rota, D.O. Sigunga

Sub-theme : Developments in GIS and remote sensing with emphasis on high resolution imagery and 3-D presentation techniques R. Goossens

Paper/poster : Geomorphology and classification of some plaines and wadies adjacent to Gabel Elba, South East of Egypt – El-Badawi, M., Abdel-Fattah, A. Paper/poster : High resolution terrain mapping and visualization of channel morphology using Lidar and Ifsar data – Sudhir Raj Shrestha, Dr. Scott N. Miller

Sub-theme : Developments in soil sampling and proximal sensing with applications in precision agriculture M. Van Meirvenne, U.W.A. Vitharana, L. Cockx

Paper/poster : Estimating spatial variability of soil salinity using cokriging in Bahariya Oasis, Egypt – Kh. M. Darwish, M.M. Kotb, R. Ali Paper/poster : Spatial variability of drainage and phosphate retention and their inter relationship in soils of the South-Western region of the North Island, New Zealand – A. Senarath, A.S. Palmer, R.W. Tillman

Conclusions


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Soil survey and inventory techniques : Abstract Modern soil survey and inventory techniques have been developed to meet requests for the updating and upgrading of soil information systems and to make primary soil inventories in less accessible areas easier. The methods have in common that that a soil expectation map is produced by statistical inference methods that replace part (not all!) of the field work. Another property is that an assessment of the quality of the soil expectation map is produced as well. The latter property is very useful for cost-quality optimization. Applications of these new methods are given in the fields of soil map updating and soil inventories for precision agriculture. Since digital elevation models play an important role in these new mapping methods, new developments concerning the acquisition, availability and presentation of elevation data are summarized. Sub-theme : DEVELOPMENTS IN SOIL (ATTRIBUTE) MAPPING WITH AN APPLICATION IN MAPING GROUNDWATER DEPTH

P.A. Finke

Lab. of Soil Science, Dept. of Geology & Soil Science, Krijgslaan 281, Ghent University, Gent, Belgium,

Many years of soil mapping has resulted in a wide variety of soil information systems. Differences between and also inside countries are found, when the scale, the mapped objects and the soil parameters contained in different soil information systems (SIS) are evaluated with quality parameters such as completeness, currency and semantic quality.

The completeness of a soil database is the degree to which the necessary data are present. Insufficient completeness can be of geographical nature (incomplete coverage with data, insufficient data density) and of thematic nature (insufficiently sampled soil parameters). This insufficiency combined with an increasing variety of applications of soil information has invoked new soil samplings to upgrade SIS even in areas where the soil mapping had long been done [1,7].

The currency of a soil database is the degree to which the soil map or the data in the SIS are still up-to-date. Thematic soil information that has been reported to loose currency within decades after the primary soil mapping are water table depths [3] and carbon contents [5], and as a consequence updating programs have been implemented [4].

The need to improve the quality of SIS has stimulated the development of new soil sampling and soil mapping methods. In general, methods were needed that (1) reduce field work, (2) employ existing observational data as well as knowledge about soil formation and soil landscape relations. When used for primary soil (attribute) mapping, additionally these methods should (3) employ existing soil maps with partial coverage and (4) work in areas with scarce soil data. In [6] an overview is given of modern so-called "digital soil mapping" methods that meet these requirements. These methods have in common, that they produce a soil expectation map (like in the old reconnaissance survey, but now directly at the target map scale and map extent), that they use statistical inference methods to replace part of field work, and that they in many cases can implicitly assess the quality of the soil expectation map. The latter property is very useful for cost-quality optimization.

One recent example of digital soil mapping was the re-mapping of the water tables in the Netherlands [4]. A high reduction of the field work relative to the traditional mapping approach was achieved by using a highly detailed DEM and existing thematic maps to formalize soil (water)-landscape relations using a combination of stratified multiple regression and kriging to obtain maps of various aspects of water table dynamics. All


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resulting maps are associated with maps of the quality (prediction error), which allows for targeted future improvement.

REFERENCES

[53] C.L. Arnold, Jr., D.L. Civco, M.P. Prisloe, J.D. Hurd, J.W. Stocker. "Remote-sensing-enhanced outreach education as a decision support system for local land-use officials", Photogrammetric Engineering and Remote Sensing, 66 (10), 1251-1260, (2000). [54] J. Bak, J. Jensen, M.M. Larsen, G. Pritzl, J. Scott-Fordsmand. A heavy metal monitoring-program in Denmark. The Science of the Total Environment 207: 179-186., (1997). [55] J.S. Bethel, J.S., J.Ch. McGlone, E.M. Mikhail. "Introduction to Modern Photogrammetry", John Wiley & Sons, Inc., New York, 477p, (2001). [56] D.L. Corwin., S.M. Lesch. “Characterizing soil spatial variability with apparent soil electrical conductivity I. Survey protocols”. Computers and Electronics in Agriculture, 46, pp. 103-133, (2005). [57] D. Devriendt, M. Binard, Y. Cornet, R. Goossens. "Accuracy assessment of an IKONOS derived DSM over urban and suburban area", In : Proceedings of the 2005 workshop EARSeL Special Interest Group “3D Remote Sensing” - use of the third dimension for remote sensing purposes. [58] D. Devriendt, R. Goossens, A. Dewulf, M. Binard. "Improving spatial information extraction for local and regional authorities using Very-High-Resolution data – geometric aspects", High Resolution Mapping from Space (2003). [59] D. Devriendt, R. Goossens, A. De Wulf, M. Binard. "Improving spatial information extraction for local and regional authorities using Very-High-Resolution data - geometrical aspects", In : Proceedings of the 24th EARSeL symposium : New Strategies for European Remote Sensing, /May 2004, Dubrovnik, Croatia, pp 421-428, (2005). [60] P.A. Finke. Updating groundwater table class maps 1:50,000 by statistical methods: an analysis of quality versus cost. Geoderma 97: 329-350, (2000). [61] P.A. Finke, D.J. Brus, M.F.P. Bierkens, T. Hoogland, M. Knotters, F. de Vries. Mapping ground water dynamics using multiple sources of exhaustive high resolution data. Geoderma 123: 23-39, (2004). [62] K. Jacobsen. "Analysis of Digital Elevation Models based on space information", New Strategies for European Remote Sensing, Rotterdam : Millpress, pp 439-451, (2005). [63] K. Jacobsen. "Orthoimages and DEMs by QuickBird and IKONOS", Remote Sensing in Transition, Rotterdam, Millpress, 273-279, (2003). [64] P.J. Kuikman, W.J.M. de Groot, R.F.A. Hendriks, J. Verhagen, F. de Vries. Stocks of C in soils and emissions of CO2 from agricultural soils in The Netherlands. Wageningen, Alterra-report 561. 41 pp. (http://www2.alterra.wur.nl/Webdocs/PDFFiles/Alterrarapporten/AlterraRapport561.pdf ), (2003). [65] A.B. McBratney, M.L. Mendonca Santos, B. Minasny. “On digital soil mapping” Geoderma, 117, pp. 3– 52, (2003). [66] S.P. McGrath, P. Loveland. The Soil Geochemical Atlas of England and Wales. Blackie Academic and Professional, Glasgow, (1992). [67] K. Taillieu, R. Goossens, D. Devriendt, A. Dewulf, S. Van Coillie, T. Willems. "Generation of DEMs and orthoimages based on non-stereoscopical IKONOS images", New Strategies for European Remote Sensing, Rotterdam : Millpress, pp 453-460, (2005). [68] T. Vandevoorde, M. Binard, F. Canters, W. De Genst, N. Stephenne, E. Wolff. "Extraction of land use / land cover - related information from very high resolution data in urban and suburban areas", Remote Sensing in Transition, Rotterdam : Millpress, pp 237-245, (2003). [69] G. Zhou, R. Li. "Accuracy evaluation of ground points from IKONOS high-resolution satellite imagery", Photogrammetric Engineering and Remote Sensing, 66 (9), 1103-1112, (2000).


199

USING GEOGRAPHIC INFORMATION SYSTEMS AND GLOBAL POSITIONING SYSTEM TO MAP SOIL CHARACTERISTICS

FOR LAND EVALUATION

P. Wandahwa1* J. A. Rota1, and D. O. Sigunga2

1Egerton University, Department of Crop and Soil Sciences, P. O. Box 536 Njoro, Kenya. 2Maseno University, Department of Horticulture, P. O. Private Bag, Maseno, Kenya *Presenting author: Tel: +254-733 26 94 60; Fax +254-51 62527; E-mail: [email protected] Abstract Land evaluation is traditionally based on conventional soil survey information i.e. the plan-view maps and written descriptions in soil reports. The maps consist of soil units that are characterized by a single representative soil profile pit on which suitability evaluations are based. The soil unit has single values for all soil characteristics analyzed for the profile and the same spatial boundary for these characteristics. These implies that soil variability encountered in the process of soil survey is not captured on the resulting soil maps and reports, yet analysis of these maps shows that there can be considerable variability in soil properties within soil units with consequent variability in land assessment results. In this study, continuous surface maps of organic carbon, soil pH, base saturation and soil depth having a value at every location are generated from randomly sampled points using geographic information systems and global positioning system. The maps are classified on the basis of suitability levels of a test crop, overlaid and the final evaluation results compared with those obtained using soil units. The results show that a better distribution of suitability in accordance with the random sample points is obtained using these maps than soil units derived from conventional soil survey.

INTRODUCTION The data used for land evaluation have traditionally been derived from conventional soil survey maps and reports that range in degree of details from small to large scales. The basic premise in soil survey is that soils are predictable along landscape positions. Reliability of the predictions is a function of the soil scientists’ abilities to consistently interpret and predict the relationship between soils and landscape. The soil scientist does not physically probe every acre in the survey area, or use random sampling techniques that allow each member of the soil population equal probability of being sampled [12].

The maps produced during soil survey are therefore characterized by a modal soil profile pit representing a soil unit on which suitability evaluations are based [13]. The soil units can be simple map units defined as delineations containing a very low percentage of dissimilar soils and conforming to the definition of a single soil type or compound map units referring to delineations with a higher percentage of dissimilar soils [19, 25]. Purity standards placed on soil map units are therefore a reflection of the expected (interpretative) use of the maps and to a degree have misrepresented the true map unit composition. Focus on the soil map unit that has undoubtedly served well for the purposes of soil classification, does not however produce the best soil database for other applications, thereby weakening the link between soil data and process models [14] and hence land evaluation for land use planning.

An alternative procedure in soil mapping is to focus on point observations that allow each member of the soil population equal probability of being sampled and derive continuous surface individual characteristic or single factor maps through interpolation techniques. The procedure can be used to inventory only soil characteristics required in land evaluation thereby reducing the time and costs normally incurred in conventional soil surveys. The


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boundaries of individual factor maps are independent of one another and a function of interpolation techniques found in Geographic Information Systems (GIS) [27]; therefore free from the subjective interpretative abilities of soil scientists.

Points for interpolation must be geographically referenced using a Global Positioning System (GPS) as a prerequisite for management of the spatial information in Geographic Information System. The purpose of this study was to generate individual soil characteristic maps from randomly sampled points using GIS and GPS and explore their potential for land evaluation. Further information on the application of GIS to soil mapping and research can be found in publications by Burgess and Webster [4, 5]; Webster and Burgess [28]; Wilding and Drees [31]; Trangmar et al. [26]; Webster [30] and Webster and Oliver [29] that represent some of the most acknowledged contributions on the subject.

MATERIALS AND METHODS The Study Area The study was conducted in Kakamega District, western Kenya during the month of April 2001. The District lies between latitudes 0°15' and 1° N and longitudes 34°20' and 35° E in the western part of Kenya. It covers approximately 1,486 km2. The altitude ranges from 1,250 m above sea level (asl) in the southwest to 2,000 m asl in the east. Two distinct physiographic units evident are the southern hilly belt, and the slightly undulating peneplain, stretching from the north to the central and eastern parts. A prominent feature on the eastern border is the Nandi escarpment whose main scarp rises from a general elevation of 1,700 to 2,000 m asl within one kilometer.

Annual rainfall in the District varies between 1,000 and 2,400 mm per annum and is received as heavy afternoon showers with occasional thunderstorms. About 500 to 1,100 mm is received during the first rains (March through June) and 450 to 850 mm during the second rains (August through November). Minimum, maximum and mean temperatures range from 11to16, 24 to 31 and 17 to 23 °C, respectively [11].

In this study, soybean was used as a test crop to explore the potential of the methodology for land evaluation. During the first rains, 78% of the land is very suitable for soybean cultivation because of adequate temperatures and rainfall. Moderate and marginal land is 20.6% and 1.4% due to mean temperature of the growing cycle below 20 and 18°C respectively. The low temperatures are associated with the high altitude of the Nandi escarpment. During the second rains, 9.4% of the land is very suitable while moderate and marginal land is 90.5% and 0.1%, respectively. Farmers should therefore be encouraged to utilize the long rains season to incorporate soybean in their cropping systems [18]. Soils and Landscape Data Figure 1 shows the soil map of the study area. The map was prepared by the Fertilizer Use Recommendation Project [11] using background information from the Reconnaissance Soil Map of the Lake Basin Development Authority at scale 1: 250,000 [2] and the Exploratory Soil Map of Kenya at scale 1: 1,000,000 [20]. The soil units are physiographic and descriptive in nature without any soil characteristic data.


201

Fig. 1: Map showing soil units and sample points in the study area

Suitability class and values Soil characteristic

High Moderate Marginal Unsuitable

Slope (%) 0-8 8-16 16-30 > 30 Soil depth (cm) > 75 75-50 50-20 < 20 Base saturation (%) > 35 35-20 < 20 pH water 5.6-7.5 5.5-5.4

7.5-7.8 5.4-5.2 7.8-8.2

< 5.2 > 8.2

Organic carbon (%) > 1.2 1.2-0.8 < 0.8

Table 1: Soil and landscape requirements for soybean cultivation in Kakamega District (adapted from Sys et al., [23]

Soil characteristic data were obtained from samples collected at 0 to 30 cm and 30 to 60 cm depths for 76 randomly selected sites shown in Fig. 1. The sites were geographically referenced using a portable Global Positioning System (GPS). Soil depth was determined by auguring to 100 cm or impervious layer. Soil drainage and flooding conditions were recorded


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at the sites. The collected soil samples were air-dried and the content of organic carbon determined according to Okalebo et al. [15], cation exchange capacity (CEC) and basic cations (Ca, Mg, K, Na) as described in Sparks [21], and soil reaction (pH) according to Anderson and Ingram [1]. Base saturation was determined from the sum of basic cations and cation exchange capacity. The values from the two depths sampled were averaged to provide the final value for evaluation [24]. Soil unit code1

Unit names [10] No. of Sample points

OC2 %

Soil Depth (cm)

Soil pH

BS3 %

Area (ha)

Slope (%)

UhB3 Cambisol and Ferralsols 2 1.35 100 5.5 18 1434 5-16 UhB5 Rhodic Ferralsols 1 2.95 100 5.7 41 2435 5-16 UhD1 Orthic Acrisols 15 1.91 93 5.5 27 19991 5-16 UhD2 Nito-rhodic Ferralsols 1 1.15 100 5.8 34 135 5-16 UhDC Acrisols and Ferralsols 2 1.53 90 5.4 20 15225 5-16 UhG2 Ferralo-humic Acrisols 4 1.24 51 5.9 27 5797 5-16 UhG5 Humic Acrisols 6 1.74 74 5.6 38 5787 5-16 UhI2 Luvic Phaeozems 5 2.36 100 5.7 35 6829 5-16 UhV1 Dystro-mollic Nitisols 2 1.91 100 5.8 24 1845 5-16 UmD2 Orthic Ferralsols 1 2.42 100 5.6 46 728 2-8 UmD3 Rhodic Ferralsols 4 2.07 100 5.7 42 3011 2-8 UmF1 Cambisols and Phaeozems 1 2.14 100 6.6 71 1042 2-8 UmG2 Ferralo-orthic Acrisols 1 2.14 100 6.6 71 2246 2-8 UmG3 Chromic Acrisols 13 1.63 97 6.3 54 17532 2-8 UmG5 Humic Acrisols 16 1.14 82 5.8 30 28017 2-8 UmG7 Rankers and Cambisols 8 1.18 66 5.6 67 9870 2-8 UmU2 Ferralsols and Cambisols 1 2.14 100 6.6 71 920 2-8 UlG3 Acrisols and Lithosols 1 1.92 55 6.1 21 1779 2-8 UlGC1 Acrisols and Cambisols 4 1.11 63 6.1 26 7548 2-8 UlX1 Rhodic Ferralsols 1 1.18 100 6.4 20 2878 2-8 BXC2 Gleysols, planosols etc 1 - - - - 201 0-5 FUC Ferralsols, Acrisols etc 1 - - - - 1334 2-16 HGC Regosols, Rankers, etc 1 - - - - 456 16-30 HU1 Humic Cambisols 1 - - - - 648 16-30 MU2 Lithosols and Regosols - - - - - 2660 >30 VXC Gleysols, Vertisols etc - - - - - 8232 - 1The first soil unit letter represents physiographic position as follows: M: mountains and major scarps; H: hills and minor scarps; F: footslopes; Uh: upland (upper middle level); Um: uplands (lower middle level); Ul: uplands (lower level); B: bottomlands; V: valleys. 2 Organic carbon. 3 Base saturation.

Table 2: Soil units shown in Fig.1, number of sample points per unit and their characteristics Data Analysis Data analysis comprised use of PC Arc / Info [16] followed by IDRISI32 [9] Geographic Information Systems. The soil map and sample points were digitized along side other physical features in the study area using PC Arc / Info. Vector files for these features were created and exported as UNGEN files to IDRISI32. The files were imported and stored in IDRISI32 as digital maps for further analysis. Sample points were given numbers to identify them and the vector digital map converted to a raster digital map. For each soil characteristic (organic carbon, soil pH, base saturation and soil depth), a data file was prepared using the 76


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point identifiers and the corresponding characteristic value. The values files were then assigned to the digital map having the 76 point identifiers and surface analysis done to produce individual characteristic maps in a three step procedure.

First, the maps were analyzed for spatial dependence in the spatial dependence modeler and semivariograms created. Models were then fitted to the semivariograms in the model- fitting module. Finally, these models were used to produce continuous surfaces of the characteristics using the ordinary kriging method. Ordinary kriging is one of several optimal interpolation techniques useful in mapping soil resources [3]. The technique utilizes information about the spatial autocorrelation in the vicinity of each sample point to provide optimal interpolation between the individual points into continuous surfaces [22].

The continuous surfaces of the kriged maps were smoothed and reclassified based on suitability class values shown in Table 1 for soybean, a test crop. To evaluate the landscape, soil units in Figure 1 were assigned their respective slope values shown in Table 2 and reclassified according to suitability slope classes of soybean shown in Table 1. The classified soil characteristic maps and the landscape map were overlaid to obtain the final soils and landscape suitability map for soybean cultivation based on the most limiting factor. This map was then overlaid with maps representing other physical features such as escarpments, forests, valleys, roads and towns and the land areas representing these features and different suitability levels for soybean cultivation determined.

Evaluation based on soil units was done by averaging values of soil characteristics from a number of sample points within the soil units to obtain a single value for the soil unit as shown in Table 2. The total number of sample points for all the soil units was more than 76 because some fell on boundaries of two soil units and were therefore used for evaluating both units. The soil unit value was compared with the requirements for soybean cultivation shown in Table 1 and a suitability level assigned to the soil unit. The resultant map was also overlaid with maps representing other physical features and land areas representing these features and different suitability levels for soybean cultivation determined.

RESULTS AND DISCUSSION Random sampling of soil at points geographically referenced using a GPS followed by kriging of soil characteristic values in GIS resulted in spatial maps that can be classified for land evaluation. Classification of these maps into suitability levels for soybean cultivation revealed a better distribution of soil characteristics for organic carbon, soil depth and soil pH but not base saturation as shown in Figure 2. The distribution shown by base saturation could be an indication that kriging may not be the best statistical tool to use in producing spatial maps of this characteristic. On the other hand, it could be an indication of a strong influence of soil management practices on base saturation as opposed to the other characteristics. Despite the poor distribution exhibited for base saturation, a general indication of soil characteristics across the district is directly observed and users of this information do not have to glean written descriptions in a separate location as in the case of conventional soil survey maps [8].

A close look at the characteristic maps reveals that soils in the district are generally shallow and poor in fertility. Forty two percent of the district has soil pH equal to or less than 5.5, while 54% has organic carbon equal to or less than 1.2%. Sixty two percent of the district has base saturation equal to or less than 35%, while 59% has soil depth equal to or less than 0.75 m. The maps can be used to identify areas with soil problems that require to be addressed.


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Fig. 2: Maps showing soil characteristics and their level of suitability to soybean cultivation

Organic carbon Soil depth

pH Base saturation Suitability level


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Table 3 shows results of the final evaluation based on soil characteristic maps and the soil unit map. In the study area, 17.6% of the district is accounted for by valleys, escarpments and forests. Evaluation based on soil characteristic maps reveal that very suitable soil is found in 3.5% of the district, while moderate and marginal soil is found in 38.5% and 38.6% of the district, respectively. Unsuitable soil owing to low soil pH is found in 1.8% of the district. On the basis of soil units, highly suitable, moderate and marginal soil is found in 5.8%, 72.7% and 3.9% of the district, respectively. There is no unsuitable land when soil units are used for evaluation yet sample point data shows sites that are classified as unsuitable due to low soil pH values.

Soil characteristic maps Soil units

Suitability level Area (ha) (%) Area (ha) (%) High 5131 3.5 8,609 5.8 Moderate 57,266 38.5 108,024 72.7 Marginal 57,341 38.6 5,830 3.9 Unsuitable 2,725 1.8 0 0 Valleys 8,232 5.5 8,232 5.5 Escarpment 2,660 1.8 2,660 1.8 Forests 15,225 10.3 15,225 10.3 Total 148580 100 148,580 100 Table 3: Land evaluation for soybean cultivation based upon soil characteristic and soil unit maps of

Kakamega District When soil characteristic maps are used for evaluation of soil suitability, the amount of

land delineated as having moderate soil (38.5%) is similar to that indicated as having marginal soil (38.6%) to soybean cultivation. However, on the basis of soil units, the amount of land delineated as having moderate soil (72.7%) is by far more than that delineated as having marginal soil (3.9%) to soybean cultivation. The reason is that large tracts of land are delineated under single soil units and evaluated using one value obtained by averaging a number of sample point values as shown in Table 2. This is the same way representative soil profiles from conventional soil survey maps are used to evaluate soil units.

By randomly sampling points geo-referenced using a GPS and utilizing interpolation techniques in GIS, it was possible to create continuous surface maps for individual soil characteristics and use them to produce soil evaluation maps for soybean production in the study area. Interpolation techniques have been used to create factor maps for evaluation of suitable areas for crops even when detailed soil survey information was available [6, 7]. This is an indication that the procedures provide more information than is otherwise captured in conventional soil survey maps and reports.

CONCLUSIONS The present study successfully demonstrates the potential of using a GPS and GIS for land evaluation. Random soil characteristic data however respond differently when subjected to interpolation techniques during the development of soil characteristic maps. There is need for further research on the type of interpolation techniques suitable for mapping soil characteristics. Soil characteristic maps show spatial variations of these characteristics and are therefore useful in locating soil related problems. Soil variability not captured in


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conventional soil survey maps is captured in soil characteristic maps developed using interpolation techniques. The maps can be used for spatial modeling of soil processes.

ACKNOWLEDGEMENTS

The authors acknowledge the financial support for this study provided by the African Career Award (ACA) program of the Rockefeller Foundation.

REFERENCES [1] J.M. Anderson, J.S.I. Ingram. “Tropical Soil Biology and Fertility: A Handbook of Methods”. C. A. B. International, Wallingford, U.K., pp. 221, (1993). [2] W. Andriesse, B.J.A. van der Pouw. “Reconnaissance soil map of the Lake Basin Development authority area, West Kenya, scale 1:250,000”. Netherlands Soil Survey Institute (STIBOKA) in cooperation with Kenya Soil Survey, Nairobi, (1985). [3] A. Bekele, R.G. Downer, M.C. Wolcott, W.H. Hudnall, S.H. Moore. “Comparative evaluation of spatial prediction methods in a field experiment for mapping soil potassium”. Soil Science 168 (1), pp. 15-28, (2003). [4] T.M. Burgess, R. Webster. “Optimal interpolation and isarithmic mapping of soil properties I. The semivariogram and punctual kriging”. J. Soil Sci. 31, pp. 315-332, (1980). [5] T.M. Burgess, R. Webster. “Optimal interpolation and isarithmic mapping of soil properties II. Block kriging”. J. Soil Sci. 31, pp. 333-341, (1980). [6] A. Ceballos-Silva, J. Lopez-Blanco. “Delineation of suitable areas for crops using a Multi-Criteria Evaluation approach and land use/cover mapping: a case study in Central Mexico”. Agricultural Systems 77, pp. 117-136, (2003). [7] A. Ceballos-Silva, J. Lopez-Blanco. “Evaluating biophysical variables to identify suitable areas for oat in Central Mexico: a multi-criteria and GIS approach. Agriculture”, Ecosystems and Environment 95, pp. 371-377, (2003). [8] A.W. Douglas, P.J. Schoeneberger, H.E. LaGarry. “Soil surveys: A window to the subsurface”. Geoderma 126, pp. 167-180, (2005). [9] J.R. Eastman. “IDRISI Release 32”. Graduate School of Geography, Clark University, Worcester, MA, (2000). [10] FAO. “Soil map of the world. 1: 5,000,000, volume 1 legend”. FAO/UNESCO, pp. 59, (1974). [11] FURP. “Fertilizer use recommendation project: Kakamega District”. Vol. 7, KARI, Nairobi, Kenya, (1987). [12] S.L. Hartung, S.A. Scheinost, R.J. Ahrens. “Scientific methodology of the National Cooperative Soil Survey”. In: Spatial variability of soils and landforms, M.J. Mausbach, L.P. Wilding (eds). SSSA Special Publication Number 28. Soil Science Society of America, Inc. Madison, Wisconsin, USA, pp. 39-48, (1991). [13] D.N. Kimaro, B.M. Msanya, G.G. Kimbi, M. Kilasara, J.A. Deckers, E.P. Kileo, S.B. Mwango. “Computer-captured expert knowledge for land evaluation of mountainous areas: A case study of Uluguru Mountains, Morogoro, Tanzania”. UNISWA Research Journal of Agriculture Science and Technology 6 (2), pp. 120-127, (2003). [14] D. Lammers, M.G. Johnson. “Soil mapping concepts for environmental assessment”. In: Spatial variability of soils and landforms, M. J. Mausbach, P.L. Wilding (eds). SSSA Special Publication Number 28. Soil Science Society of America, Inc. Madison, Wisconsin, USA, pp. 149-160, (1991). [15] J.R. Okalebo, K.W. Gathua , P.L. Woomer. “Laboratory methods of soil and plant analysis: A working manual”. Soil Science Society of East Africa, Nairobi, pp. 128, (2002). [16] PC Arc / Info. “Users guide version 6.1”. Environmental Systems Research Institute (ESRI), Inc., Redlands, CA, USA, (1992). [18] J.A. Rota, P. Wandahwa, D.O. Sigunga. “Land evaluation for soybean (Glycine max L. Merrill) production based on kriging soil and climate parameters for the Kakamega District, Kenya”. Journal of Agronomy, 5(1), pp. 142-150, (2006). [19] W. Siderius. “Standards for soil surveys in Kenya”. National Agricultural Laboratories, Nairobi pp. 13, (1980).


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[20] W.G. Sombroek, H.M.H. Braun, B.J.A. van der Pauw. “Exploratory Soil Map and Agro-climatic Zone Map of Kenya, scale 1: 1,000,000”. Exploratory Soil Survey Report No. E1, Kenya Soil Survey, Nairobi, pp. 56, (1982). [21] D.L. Sparks. “Methods of Soil Analysis. Part 3: Chemical Methods”. SSSA Book Series, 5. SSSA and ASA, Wisconsin, U.S.A, pp. 1390, (1996). [22] A. Stein, C. Ettema. “An overview of spatial sampling procedures and experimental design of spatial studies for ecosystem comparisons”. Agriculture Ecosystem and Environment 94, pp. 31- 47, (2003). [23] C. Sys, E van Ranst, J. Debaveye, F. Beernaert. “Land Evaluation part III: Crop requirements”. Agricultural publication No. 7. GADC, Brussels, Belgium, pp. 197, (1993). [24] C. Sys, E. van Ranst, J. Debaveye. “Land Evaluation part II: Methods in Land Evaluation. Agricultural publication No. 7. GADC, Brussels, Belgium pp: 274, (1991). [25] N.H. Taylor, I.J. Pohlen. “Soil survey method: a New Zealand handbook for the field study of soils”. New Zealand Soil Bureau Bulletin 25, DSIR, Wellington, (1970). [26] B.B. Trangmar, R.S. Yost, G. Uehara. “Application of geostatistics to spatial studies of soil properties”. Adv. Agron. 38, pp. 45-94, (1985). [27] D.R. Upchurch, W.J. Edmonds. “Statistical procedures for specific objectives”. In: Spatial variability of soils and landforms, M.J. Mausbach, L.P. Wilding (eds). SSSA Special Publication Number 28. Soil Science Society of America, Inc. Madison, Wisconsin, USA, pp. 49-71, (1991). [28] R. Webster, T.M. Burgess. “Optimal interpolation and isarithmic mapping of soil properties III. Changing drift and universal kriging”. J. Soil Sci. 31, pp. 505-525, (1980). [29] R. Webster, M. Oliver. “Statistical methods in soil and land resource survey”. Oxford Univ. Press, Oxford, United Kingdom, (1990). [30] R. Webster, “Quantitative spatial analysis of soil in the field”. In B. A. Steward (ed.), Advances in soil science 3. Springer – Verlag, New York, pp. 1-70, (1985). [31] L.P. Wilding, L.R. Drees. “Spatial variability and pedology”. In: L.P. Wilding et al. (ed.). Pedogenesis and soil taxonomy I. Concepts and interactions. Elsevier, New York, pp. 83-116, (1983).


208

Sub-theme : DEVELOPMENTS IN GIS AND REMOTE SENSING WITH EMPHASIS ON HIGH RESOLUTION IMAGERY

AND 3-D PRESENTATION TECHNIQUES

R. Goossens

Dept. of Geography, Krijgslaan 281, Ghent University, Gent, Belgium. Since the year 2000 Remote Sensing is undergoing a drastic change, offering much more possibilities than the decades before. These changes can be summarised as follow: - Very High Resolution imagery (VHR), - Stereo vision at different resolutions, - Digital photogrammetry, - Super to hyper spectral imagery.

The VHR images are recorded mainly with the satellites IKONOS and Quick Bird. Both satellites are comparable concerning the spectral characteristics, they are recording the blue, green red and near infra red light, allowing image analysis in the visual as well as the infra red light. True as well as false colour composites can be created, and image classification can be performed based upon 4 spectral bands. The main characteristics of these sensors are their ground resolution; IKONOS has a ground resolution of 4 meters in the multi spectral mode (XS) and 1 meter in the panchromatic (P) mode while Quick Bird has 2.44 meter in the XS mode and 0.61 meter in the P-mode.

Also other sensors provide stereo imagery at medium resolution. The ASTER sensor is an excellent tool for the creation of DEM, ortho-photo maps and contour maps. Where in the past topographical information at an appropriate scale was a problem, this problem can easily overcome with the ASTER sensor in combination with GPS technology.

Both new types of sensors came available on the moment that also photogrammetry became digital. The combination of both events makes it now possible that topographical information is easy to be created. With a minimum of 6 ground control points, areas of 60 by 60 km can easily be mapped in an automated way. In the frame of soil survey, information on slope and aspect is crucial. It will be discussed how DEM are generated in an automated way.

An other trend in remote sensing is the shift from multi-spectral imagery towards super- and hyper-spectral imagery. The Aster sensor has 16 bands available in the visual, near infrared, short wave infrared and the thermal range. This allows a more detailed mapping of the soil material. A Belgian satellite, called Chris-Proba, is taken super spectral images with 32 bands, with the possibility of stereo viewing. This satellite and sensor summarize the possibilities of future remote sensing.

Also more and more imagery is coming available free of charge or at minimum cost. During the seminar all possibilities of obtaining imagery will be discussed and listed.

REFERENCES

[70] C.L. Arnold, Jr., D.L. Civco, M.P. Prisloe, J.D. Hurd, J.W. Stocker. "Remote-sensing-enhanced outreach education as a decision support system for local land-use officials", Photogrammetric Engineering and Remote Sensing, 66 (10), 1251-1260, (2000). [71] J. Bak, J. Jensen, M.M. Larsen, G. Pritzl, J. Scott-Fordsmand. A heavy metal monitoring-program in Denmark. The Science of the Total Environment 207: 179-186., (1997).


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[72] J.S. Bethel, J.S., J.Ch. McGlone, E.M. Mikhail. "Introduction to Modern Photogrammetry", John Wiley & Sons, Inc., New York, 477p, (2001). [73] D.L. Corwin., S.M. Lesch. “Characterizing soil spatial variability with apparent soil electrical conductivity I. Survey protocols”. Computers and Electronics in Agriculture, 46, pp. 103-133, (2005). [74] D. Devriendt, M. Binard, Y. Cornet, R. Goossens. "Accuracy assessment of an IKONOS derived DSM over urban and suburban area", In : Proceedings of the 2005 workshop EARSeL Special Interest Group “3D Remote Sensing” - use of the third dimension for remote sensing purposes. [75] D. Devriendt, R. Goossens, A. Dewulf, M. Binard. "Improving spatial information extraction for local and regional authorities using Very-High-Resolution data – geometric aspects", High Resolution Mapping from Space (2003). [76] D. Devriendt, R. Goossens, A. De Wulf, M. Binard. "Improving spatial information extraction for local and regional authorities using Very-High-Resolution data - geometrical aspects", In : Proceedings of the 24th EARSeL symposium : New Strategies for European Remote Sensing, /May 2004, Dubrovnik, Croatia, pp 421-428, (2005). [77] P.A. Finke. Updating groundwater table class maps 1:50,000 by statistical methods: an analysis of quality versus cost. Geoderma 97: 329-350, (2000). [78] P.A. Finke, D.J. Brus, M.F.P. Bierkens, T. Hoogland, M. Knotters, F. de Vries. Mapping ground water dynamics using multiple sources of exhaustive high resolution data. Geoderma 123: 23-39, (2004). [79] K. Jacobsen. "Analysis of Digital Elevation Models based on space information", New Strategies for European Remote Sensing, Rotterdam : Millpress, pp 439-451, (2005). [80] K. Jacobsen. "Orthoimages and DEMs by QuickBird and IKONOS", Remote Sensing in Transition, Rotterdam, Millpress, 273-279, (2003). [81] P.J. Kuikman, W.J.M. de Groot, R.F.A. Hendriks, J. Verhagen, F. de Vries. Stocks of C in soils and emissions of CO2 from agricultural soils in The Netherlands. Wageningen, Alterra-report 561. 41 pp. (http://www2.alterra.wur.nl/Webdocs/PDFFiles/Alterrarapporten/AlterraRapport561.pdf ), (2003). [82] A.B. McBratney, M.L. Mendonca Santos, B. Minasny. “On digital soil mapping” Geoderma, 117, pp. 3– 52, (2003). [83] S.P. McGrath, P. Loveland. The Soil Geochemical Atlas of England and Wales. Blackie Academic and Professional, Glasgow, (1992). [84] K. Taillieu, R. Goossens, D. Devriendt, A. Dewulf, S. Van Coillie, T. Willems. "Generation of DEMs and orthoimages based on non-stereoscopical IKONOS images", New Strategies for European Remote Sensing, Rotterdam : Millpress, pp 453-460, (2005). [85] T. Vandevoorde, M. Binard, F. Canters, W. De Genst, N. Stephenne, E. Wolff. "Extraction of land use / land cover - related information from very high resolution data in urban and suburban areas", Remote Sensing in Transition, Rotterdam : Millpress, pp 237-245, (2003). [86] G. Zhou, R. Li. "Accuracy evaluation of ground points from IKONOS high-resolution satellite imagery", Photogrammetric Engineering and Remote Sensing, 66 (9), 1103-1112, (2000).


210

GEOMORPHOLOGY AND CLASSIFICATION OF SOME PLAINES AND WADIES ADJACENT TO GABEL ELBA, SOUTH

EAST OF EGYPT.

El-Badawi, M. and Abdel-Fattah, A.

National Research Center, Soil dept., Cairo, Egypt.

Abstract The area under investigation is located in the southern eastern part of Egypt (Gabel Elba). It is considered as a promising part for the urban extension by establishing new communities due to the abundance of the natural resources. The current work used the remote sensing tools for preparing a geomorphological and soil maps based on the delineating of the photomorphic units (PMU`s) according to the visual perception (visual interpretation). The image classification is based upon the photomorphic elements, which can be easily distinguished. Their values are combined to define the PMU`s. Ten photomorphic units were recognized namely, Delta plain, Alluvial plain, Wadi, Sand dunes, Beach, Sabkhas, Costal plain, Plain with rock out crop, Denuded hill and Mountain. According to the USDA soil taxonomy (1998), the data showed that the soils belong to Entisolos and Aridisolos orders. These orders could be classified into six sub great groups: namely, Typic Torrifluvents, Typic Quartzpssaments, Typic Torripssaments, Typic Haplosalids, Typic Petrocalcids and Typic salorthids. The study has produced geomorphological and soil maps of scale 1:100000 based on remote sensing (Landsat TM) accomplished with the field observation and laboratory analysis. Key words: soils, south east Egypt, remote sensing, visual interpretation, soil taxonomy.

INTRODUCTION The total area of Egypt is about one million square kilometers. It consists of about 94% desert and 6% as a traditional agricultural land of the Nile delta and valley. Therefor, there is a severe pressure and demand dictated by the growing population on this limited area of agricultural land.

Rehabilitating and developing the south eastern part of Egypt are among the major aims of the government. Hence, this study may be regarded as a base for a better understanding of the soil characteristics and soil classification of these areas.

The current work has been performed by applying a false color composite landast TM image as suitable tools to define the main soil mapping units by the recognition of the geomorphological units and the field observation. Eventually, the geomorphological characteristics and the soil classification of the different features adjacent to Gabel Elba would be performed.

PHYSIOGRAPHIC FEATURES

The area under investigation occupies the extreme south eastern part of Egypt. It is bounded by 36°00` and 36°30` east and 22°30` and 22°00` north fig(1).

It has torric and hyperthermic moisture and temperature regimes. The mean annual rainfall is 6.5 mm, mainly falling in winter and the mean maximum temperature is 29.71 °C


211

mainly in summer. The area is exposed to north – eastern and south - western winds with a mean velocity of about >21 Knots.

Egyptian Geological Survey and Mining Authority Staff (1981)[6], Egyptian General Petroleum Cooperation Staff (1987) [5], Said (1990) [15] and El-Rakaiby et al. (1996) [13] indicated that the surface of (Halaib-Shalatin) region is occupied by about fourteen rock formations belong to Precambrian, Cretaceous, Miocene and Quaternary ages Abu Al-Ezz, (1987) [13], Hammad (1994) [7], Desert research center (1994) [4] stated that two main geomorphic units are recognized; a) Basement ridges which occupy most of the surface area around 13000Km2; (78% of the total area). It is formed by fractured hard igneous and metamorphic rocks, having an elevation ranging between 1000-1900 m a.s.l. the ridges are considered as the main watershed area. The surface is severely dissected by many wadis tributaries. b) The coastal plains represent a continuous strip of low lands bordered from north to south by the Red Sea, at altitude rarely exceeding 100 m a.s.l. The width varies greatly (5-30 Km) and the largest width is found at Di`ib`s delta Fig (1). It occupies an area of about 3700 Km2, represents about 22% of the total area. It includes different landforms, namely; sabkha, alluvial fans, and shallow wadis mostly perpendicular to the coast.

Fig 1: location of the study area

MATERIALS AND METHODS The following methods have been used: 1- Visual interpretation Landsat TM image acquired on path 72 and row 44/45 in 19-7-1995 was used. The interpretation was done on a false color composite of bands 2, 4 and 7 at scale 1:100000 fig (2). The major landforms were identified by the physiognomic analysis, Bennema and Gelens, (1969) [10].

The landast image was carefully analyzed to demonstrate easily the distinguishable physiographic features and land cover. Among the image characteristics, the following elements have been used; shape, size, color tone, texture and pattern recognition. The image interpretation was based on the following criteria; soil surface, slope relief, drainage patterns, vegetation etc. Vink, (1963)[1].


212

Geological map at scale 1:500000 and topographic map at scale 1:100000 were used to guide the image interpretation. 2- Field work and laboratory studies The field work was undertaken to verify the established soil mapping units, which were represented by ten soil profiles fig (3). A detailed morphological description was performed according to the guide lines FAO (1970) [8],Table (3). Thirty soil samples were collected and subjected to the following analysis: 1- Particle size distribution was carried out by dry sieving as described by Black (1985) [2]. 2- Calcium Carbonate by the Collin`s Calcimeter methods (Piper, 1950) [3]. 3- Soluble salts in the saturated soil extract, soil reaction in the soil paste, cation exchange capacity and gypsum percentage were determined according to the standard methods by Richards (1964) [11]. 4- Organic matter was determined by the method of Walkely and Black (Jackson, 1973) [12]. 5- Soil classification was carried out according to the USDA soil taxonomy (1998) [16].

RESULTS AND DISCUSSION 1. Visual interpretation The best color combination for the recognition of soil and water bodies has been the enhanced FCC of bands, 2 (visible green) as blue, 4 (NIR) as green and 7 (MIR) as red. The FCC was projected on a transparent screen at scale of 1:100 000 for image interpretation.

Based on the interpretation elements and the knowledge drawn from other sources (i.e. geological map, topographical map and the field work); eleven photomorphic units could be delineated and discussed. fig (2) and table (1)

Image characteristics Group Geomorphic unit

color texture pattern Nature of the pattern

1 Water Very dark blue F No X 2 Delta plain Mixed colors F to M P Y 3 Alluvial plain Light to dark G F P X 4 Wadi W - Grey F to M L X 5 Sand dunes W / Y M to F L X 6 Beach Y (W) F No X

7 Sabkhas Light to dark B(W) F to M P Y

8 Costal plain Very pale G F to M No Y

9 Plain with rock out crop Mixed colors F to M No Y

10 Denuded hill Dark G M to C Pol to P Y 11 Mountain Light to dark G C pol X

Table 1: Image characteristics of the mapped pmu`s


213

Group 1 This PMU was the easiest unit to be interpreted, since it shows nearly the same color of water bodies. The dominant and the only color of the PMU is very dark blue. The unit has a fine homogenous texture and no pattern has been detected.

The color characteristics of the PMU is coinciding with the water bodies i.e. the red sea and the water logged area. Group (2): This PMU appears in various color (light green, pinky and dark green color) and refers to the out-wash of the mountain, fine to coarse in texture. Since the coarse materials precipitate first and the fine materials come at the end of the precipitation, the unit takes a delta shape. Group (3): This PMU refers to the alluvial plains, founded in the out-wash area and having a very fine materials. Group (4): This PMU refers to the wadies having many drainage patterns. Group (5): This PMU exists in the north west of the study area, it displays as an accumulation area of wind blown sand in longitudinal shape. The desert pavement and the gravelly corridors between the dunes appear in a pale pink and greenish color. Group (6): The yellowish and the whitish colors indicate a high reflection through out the wavelength range of the spectral bands; referring to the landscape features of fine homogenous texture and the smoothness of the surface. According to the color characteristics and the patterns; this PMU has been interpreted as beach. Group (7): This PMU has been interpreted as sabkhas and could be divided into wet and dry. The blue color refers to the presence of water, Group (8): According to image interpretation and the field observation, the PMU has been referred to the costal plain. Group (9): This PMU has mixed colors of light green, pale yellow and pale green with inclusion of white. It is covered by gravelly and stony materials transported by water stream. The PMU has been interpreted as plain with rock out crop.


214

Group (10): The distribution of this unit inside the macro PMU, is homogenous. In few cases a relation was found with the hydrographic network. It refers to the strongly exposed rock out crop and interpreted as denuded hill. Group (11): This PMU refers to Mountain 2. Field trip According to the differences in the photomorphic unit (preliminary classification) the sample areas were chosen and ten soil profiles have been described and sampled, Fig (3). 3. Final classification map The final delineation of the geomorphic units was based on the image characteristics and the field observation. Fig (2), table (2) Each geomorphic unit was described as following:- 1. Sabkhas The total area of this unit is about 8.6 Km2 (2064 feddan) and represented by profile 4. The soil surface slopes towards the sea. The soils are originated from alluvial deposits mixed with marine deposits. The surface is covered with shells, some low hummocks and few scattered vegetation mainly from halophytes. The profile depth is varied from shallow to deep as far from the sea. The fine texture is dominated while the gravel content is varied from layer to another; it is 17.2% at the surface layer and 9.1 % in the lower one, as indicated in table (4). - The salinity is very high and increased by depth. Table (5) - The soil pH was 7.5 which are due to the increase of salinity. - The soil has low percentage of CaCO3 content. - The color is varied from yellow (10yr 7/6 dry) to (very pale brown 7/4dry) and from

yellowish brown (10yr 5/6 moist) to yellowish brown (10 yr 5/4 moist). Table (3) - According to the USDA soil taxonomy 1998 the soils Typic Salorthids. 2. Alluvial plain The total area of this unit is 662.3 Km2 (158952 fedden) and geographically could be divided into two parts from north to south as follows: a) From 22°30`N to Abu Ramad (22°20`N) b) From 22°20`N to Halaib (22°15`N)

a) From 22°30`N to Abu Ramad (22°20`N) The total area of this unit is 245.7 Km2 (58968 fedden). It is represented by two profiles (profile 1 and profile 2) and characterized as following: - the surface is almost flat, covered by desert pavement in some places.


215

- In the upper layer the soil texture is commonly fine sand, while in the subsurface it is commonly very gravelly coarse sand.

- The soil surface is covered by some scattered young trees and some natural vegetation. - Generally the EC value of profile 1 is lower than 4 dS/m, while in profile 2 it is higher

than 8 dS/m. - The mean CaCO3 content in profile 1 is lower than 2 %, and 4.5 %.in profile 2. - The soil taxonomy according to the USDA soil taxonomy 1998 is Typic Torrifluvents.


216

Feddan (4200m2)

Map. units Phase Landform Lithology Relief Landscape

320 P111 This soil covers most of the costal region and could be identified easily in the satellite image and

classified as Typic Torrifluvents Delta plain

158952 P112

Flat, surface covered by desert pavement, varying texture from fine sand to gravelly coarse sand, common to many calcium carbonate and salt contents, classified as Typic Torrifluvents, Typic Haplosalids, and

Typic Petrocalcids Alluvial plain

5832 P113 Alluvial, sandy texture, covered by silty crust (in some areas). This soil could be classified as Typic

Torrifluvents Wadi

Alluvial Deposit

P11

Flat to gently undulating

P1

400 P211 Undeveloped soils consist of sand accumulation of different altitudes, barchanoid and longitudinal form

the main dune types and could be classified as Typic Quartzpssaments Sand dunes

Aeolian deposit

P21

Almost flat to Hilly

P2

1360 P221 Flat to undulating surface, some vegetation cover, loose, few to many calcium carbonate and salt

contents. It could be classified as Typic Torripssaments Beach

2064 P222 Flat to undulating surface, sandy and strongly saline soils, shallow depth, highly saline gypsiferous origin,

motels of iron and manganese oxide also exist. The soil could be classified as Typic salorthids Sabkhas

3120 P224 Coarse sandy soils include gravels, less vegetation covers, medium calcium carbonate and salt content.

Could be classified as Typic Torrifluvents Costal plain

Marine deposit P22

Almost flat to

Hilly P2

49248 P311 The soil surface is covered by stones in different size mixed with sand and gravels, shallow depth, could

be classified as Typic quartzpssament

Plain with Rock outcrop

P311

Colluvial deposit

P31

Undulating to hilly

P3

Plain, P

49248 M111 Area covered with big rocks and stones of different size Denuded hill M111

189660 M112 rocks Mountain M112

Rock M11

Hill or Mountain M1

Mountain, M

Table 2: The final legend of the classified image, zink, (1988) [9]


217

Fig 2: Map of photomorphic units

Fig 3: Location of the soil profile


218

b) The alluvial plain from 22°20` N to 22°15`N This area is very narrow plain and has very small wadies namely; wadi Ashmahi, wadi Udar, wadi Ediab and wadi Cermatai. The total area is about 225 Km2 (54000 fedden) and is represented by profile 6, 9 and 10. The soil profiles are characterized as following: - The topography is almost flat; some small sandy hills could be noticed in some places due

to the wind activity. - The texture is varied from fine to very gravely coarse sand. - Most of the soil profiles have a mean EC value over 8 dS/m, while in profile 6 it is very

obvious in the sublayer. The variations of the EC values are in relation to the distance from the sea.

- The CaCO3 content of most profiles is lower 4 %. It is over 8% in profile 10 and reaching 45% in profile9.

- Generally, the pH values are varied between 7 and 8.2. A reversible relationship between pH and EC values are obvious as indicated in profile 6 where the pH value is 8.1 and the EC value was 0.2 dS/m in the upper layer. While, in the lower layer the pH value was 7.4 and the EC value was 11.2. This contradiction refers to the lowness of the buffering capacity of the sandy soils and the dominant of NaCl salt.

- The soil taxonomy of this unit according to the USDA soil taxonomy 1998 is Typic Torrifluvents except for profile 9 is Typic Haplosalids and profile 10 is Typic Petrocalcides.

3. Wadies This unit occupies a total area of about 24.3 Km (5832 feddens) could be divided into two sub unit namely; main wadi and tributaries. It is represented by profiles no. (Profile 3, 5, 7 and profile 8) - The soil surface is flat to undulating covered by gravels varied in size from small to

coarse gravel and few scattered natural vegetation. - Geomorphologicaly the wadi could be divided into three sub units namely; wadi bottom

which is normally affected by water erosion, flood plain and wadi terraces. - The EC mean value is lower 2 dS/m in profile 3, and 8.6 dS/m in profile 5 (wadi Oshipa),

while in profile 7 (wadi Udar) and profile 8 (wadi Ediab) it reaches 18.6. - 50% of the pH values of the studied soil profiles are varying between 7 and 7.5, the rest

are 7.6 to 8.2. - Most of the CaCO3 values of the profile are very low except for profile 7 and profile 12,

it reaches to more than 8% - The soil texture is varied from fine sand to very gravelly fine sand and from coarse sand

to gravelly coarse sand. - The soil classification according to USDA soil taxonomy 1998 is Typic Torrifluvents.

Table (3) 4. Delta plain The total area of this unit is 320 fedden. This soils covers most of the costal region and can be identified in the satellite images. The soil can be classified as Typic Torrifluvents.


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color Pro

f. no.

Locations Map. units

vegetation

drainage

Parent material classification Depth

Cm. dry moist

texture

Structure

consistence

effervescence

boundary

1

Lg.: 22 29` 26.8" N

Lt: 36 5` 12.6" E

P112 few well Alluvial deposit

Typic Torrifluvents

0-15

15-50

50-100

10 YR 7/3

10 YR 6/6

10 YR 7/3

5/4

5/6

5/4

FS

FS

GCS

Sg

Sg

Sg

dL

dL

dL

s

s

st

d

d

-

2

Lg. 22 28` 36.3" N

Lt:36 8` 00" E

P112 common well Alluvial deposit

Typic Haplosalids

0-15

15-35

35-70

10YR 7/4

10 YR 7/8

10 YR 7/8

6/3

5/4

6/4

GFS

VGCS

GCS

Sg

Sg

Sg

dL

dL

dL

s

v

s

c

cw

cw

3

Lg. 22 28` 36.3"N

Lt:36 4` 44.2" E

P113 few well Alluvial deposit

Typic Torrifluvents

0-25

25-40

40-60

60-100

10 YR 7/2

10 YR 7/4

10 YR 7/6

10 YR 7/6

5/3

5/3

6/6

6/8

GFS

GFS

CS

GCS

Sg

Sg

Sg

Sg

dL

dL

dL

dL

vs

st

s

s

d

d

d

-

4

Long. 22 25` 00' N

Lat:36 5` 12.6" E

P216 few well Marine deposits

Typic Aquisalids

0-15

15-45

45-100

10 YR 7/6

10 YR 7/4

10 YR 7/4

5/6

5/6

5/4

FS

FS

FS

Sg

Sg

Sg

dL

dL

dL

vs

st

st

cs

cs

-


220

5

Lg. 22 23` 36.32" N

Lt:36 19` 31.6" E

P112 few well Alluvial deposits

Typic Torrifluvents

0-15

15-30

30-100

10 YR 7/8

10 YR 7/4

10 YR 7/6

6/6

6/4

5/6

GFS

GFS

GCS

Sg

Sg

Sg

dL

dL

dL

st

s

s

cs

cs

-

6 Lg. 2222`00' N

Lt:36 25`00"E P112 few well Alluvial

deposits Typic

Torrifluvents

0-30

30-60

60-150

10 YR 7/3

10 YR 7/4

10 YR 7/4

5/4

5/6

5/4

GFS

GCS

GCS

Sg

Sg

Sg

dL

dL

dL

s

vs

st

d

cs

-

7

Long. 22 20` 00" N

Lat:36 25` 42.6" E


Typic Torrifluvents

0-25

25-55

55-100

7.5 R 6/6

7.5 YR 6/6

7.5 YR 7/6

5 YR 4/6

7.5 YR 4/4

7.5 YR 5/8

VGFS

GCS

VGCS

Sg

Sg

Sg

dL

dL

dL

st

s

vs

d

cs

-

8

Long. 22 18`31.6" N

Lat: 36 25` 25.3" E


Typic Torrifluvents

0-25

25-80

80-100

10 YR 6/4

10 YR 6/6

10 YR 6/4

5/4

6/8

5/4

FS

GFS

FS

Sg

Sg

Sg

dL

dL

dL

st

st

st

d

cs

-

9

Lg. 22 18` 00" N

Lt:36 26` 23.7" E

P311 common well Colluvial deposits

Typic Haplocalcids

0-25

25-70

10 YR 7/6

10 YR 7/4

5/4

6/3

FS

GFS

Sg

Sg

dL

dL

v

v

d

cs

10 Lg. 22 18` 00"

P112 Few well Alluvial Typic

0-15 10 YR

5/6 GFS Sg dL v c


221

N

Lt:36 24` 39.5" E

deposits petrocalcids 15-30

30-100

7/4

10 YR 5/3

10 YR 7/2

4/4

7.5 YR 4/4

GFS

VGFS

Sg

Sg

dL

dL

v

v

d

-

Where: -Texture: FS= fine sand, GFS= gravelly fine sand, VGFS= very gravelly fine Sand, GCS= gravelly coarse sand, VGCS= very gravelly coarse sand

-Structure: Sg= single grain -Consistence: d=dry, L=loose - Boundary: c=clear, d= diffuse, s=smooth - effervescence with HCl: vs= very slight, s= slight, st= strong, v= violent

Table 3: Morphological description and classification of the studied soil profiles


222

5. Beach The area of this unit is 1360 fedden. Almost flat to undulating, some vegetation cover, loose, few to many calcium carbonate and salt content could be classified as Typic Torripssament 6. Sand dunes The total area of this unit is 400 fedden. Undeveloped soils consist of sand accumulation of different altitudes, barchanoid and longitudinal forms area the main dune type. Could be classified as Typic Quartzpssaments. 7. Coastal plain The total area of this unit is 3120 fedden. the soil surface is sloping towards the sea and the soil originated from alluvial deposit mixed with marine deposit. Coarse sandy soils, include gravels, less vegetation covers, medium calcium carbonate and salt content, the surface covered with shells. It could be classified as Typic Torrifluvents.

Percentage of separate particles (mm)

exture <0.05 Si&C

l

0.1-0.05 VFS

0.25-0.1 FS

0.5-0.25 MS

1-0.5 CS

2-1 VCS

Gravel >2mm

%

Soil depth (cm)

Profile nr.

Fine Sand Fine Sand

Gravelly Coarse Sand Gravelly Fine Sand Gravelly Fine Sand

Very Gravelly Fine Sand Gravelly Fine Sand Gravelly Fine Sand

Coarse Sand Gravelly Coarse Sand

Fine Sand Fine Sand Fine Sand

Gravelly Fine Sand Gravelly Fine Sand

Gravelly Coarse Sand Gravelly Fine Sand

Gravelly Coarse Sand Very Gravelly Coarse Sand Very Gravelly Fine Sand

Gravelly Coarse Sand Gravelly Coarse Sand

Fine Sand Gravelly Fine Sand

Fine Sand Fine Sand

Gravelly Fine Sand Gravelly Fine Sand Gravelly Fine Sand

6.4 3.0 4.1 8.0 3.1 1.7 6.0 6.2 4.0 8.6 2.4 4.1 4.1 3.8 2.9 1.5 5.3 3.7 2.9 3.9 3.0 3.1 6.0 4.6 4.5 8.4 4.5 6.1 7.7

12.5 8.4 7.0

10.9 2.8 5.4 9.9 9.0 2.9 4.0 9.9

11.1 10.1 8.8

11.9 5.0

13.4 4.8 4.9 4.9 2.8 3.2

16.2 13.3 13.4 13.2 13.6 13.7 14.4

43.8 50.2 18.5 46.0 14.4 16.2 44.4 46.0 12.4 11.4 50.0 52.2 46.5 49.0 44.5 20.3 43.3 17.9 27.9 56.9 23.8 23.3 41.5 44.7 43.6 41.6 41.4 40.9 40.3

17.3 19.2 29.7 18.1 31.9 27.4 18.1 17.7 32.7 28.5 19.4 12.2 20.1 21.7 22.8 30.0 20.3 23.8 23.0 19.6 30.1 30.2 16.9 16.3 17.4 16.0 17.9 16.5 17.6

10.5 10.1 10.9 12.0 18.8 17.3 12.5 12.3 17.9 16.3 10.4 9.8 9.1 7.7 9.8

20.9 11.3 18.7 21.2 8.1

13.3 12.1 11.5 13.4 12.5 10.4 9.7

11.9 9.3

9.5 9.1

29.8 5.0

29.0 32.0 9.1 8.8

30.1 31.2 7.9

10.6 10.1 10.0 8.1

22.3 6.4

31.1 20.1 6.6

27.0 28.1 7.9 7.7 8.6

10.4 12.9 10.9 10.7

2.5 3.4

23.7 35.7 54.0 47.1 38.5 40.4 17.4 50.0 17.2 3.1 9.1

38.8 46.5 42.9 37.4 31.4 68.2 54.9 27.9 34.1 17.7 42.3

-- 14.7 12.9 42.4 36.0

0-15 15-50

50-100 0-15

15-35 35-70 0-25

25-40 40-60

60-100 0-10

10-45 45-100

0-15 15-30

30-100 0-30

30-60 60-150

0-25 25-55

55-100 0-25

25-80 80-100

0-20 20-70 0-15

15-30

1

2

3

4

5

6

7

8

9

10

Table 4: Grain size distribution


223

Soluble cations me/L Soluble anion me/L Profile nr.

Depth in, Cm S.P. EC

ds/m pH CaCO3 % OM % Na+ K+ Ca++ Mg++ HCO3

- Cl- CO3-- SO4

++

1

2

3

4

5

6

7

8

9

10

0-15 15-50

50-100 0-15

15-35 35-70 0-25

25-40 40-60

60-100 0-10

10-45 45-100

0-15 15-30

30-100 0-30

30-60 60-150

0-25 25-55

55-100 0-25

25-80 80-100

0-20 20-70 0-15

15-30 30-70

21.8 19.1 20

23.1 22 19 18 18 20 20 21 22 21 21 22 22 21 18 21 19 21 22 19 22 21 22 20 20 21 22

0.8 0.36 0.41 11.45 25.4 16.4 1.43 0.5

0.69 3.58 20.6 26.9 23.6 1.92

1 5.4

0.92 2.9

11.2 14.53 11.6 4.99 5.4 8.9

14.9 23.9 6.8

12.1 2.9 5.9

7.8 7.9 7.9 8.2 7.2 7.2 7.9 8.2 8

7.9 7.5 7.6 7.9 8

7.9 8.2 8.1 8

7.4 7.6 7.8 7.8 7.9 8

7.8 8 8 8

7.7 8.2

0.1 1.3 2

1.6 1.3 3.6

0.76 4.9

2.09 0.83 6.4 5.4

14.2 8.1 4.5 9.8 2.1 1.8 7.1

1.05 0.09 1.6 9

10.1 3.93 45

12.8 40.9 28.5 19.8

0.36 0.23 0.29 0.5

0.23 0.21 0.01 0.07 0.07 0.06 0.04 0.02 0.01 0.5

0.02 0.02 0.2

0.02 0.01 0.53 0.02 0.02 0.2

0.28 0.14 0.04 0.01 0.06 0.01 0.01

0.8 0.78 0.7

69.8 163.9 15.6 0.14 2.7

0.19 0.47 34.4 5.56 15.5 3.56

6 42.9 0.12 0.27 .96

54.35 54.4 0.53 43 60

18.9 210 46

0.24 18 46

0.12 0.1

0.05 3

0.55 0.4

0.01 0.4

0.01 0.02 0.09 0.17 0.09 0.06 0.4 0.4

0.01 0.02 0.05 0.82 1.7

0.05 1

0.6 0.16 0.5 2.2

0.01 0.6 0.3

1.05 0.65 0.54 29.9 41.51 19.71 0.14

1 0.08 0.23 6.93 7.53 9.61 0.74 2.7

12.6 0.02 0.03 0.2

50.52 46

0.27 11.4 21.8 4.29 52.1 24.2 0.03 7.4

12.5

0.22 0.21 0.1

15.6 36.9 11.3 0.05 0.6

0.12 0.14 6.38 2.97 5.8

0.46 1.1 6.1

0.0`4 0.1

0.78 21.5 5.6

0.69 7.8

12.8 3.57 23.9 7.6

0.05 5.4 7.5

0.52 0.6

0.61 5.4 4.1 3.6

0.17 0.9

0.15 0.15 0.72 0.76 0.45 0.08 0.9 4.6

0.04 0.03 0.42 4.08 4.29 0.17 5.3

11.6 0.39 17.6 9.3

0.12 3.8 6.3

1.01 0.5 0.5

81.3 200.1 29.9 0.12 2.6

0.16 0.24 10.2 2.22 2.05 2.29 5.3

41.3 0.14 0.37 0.96

82.93 72

0.72 47.5 67.5

15.03 245 50

0.16 23.5 45.7

- - - - - - -

0.5 - - - - - -

0.4 - - - - - - - - - - - - - - -

0.064 0.62 0.31 31.4 40.3 13.5 0.05 0.7 0.1

0.77 36.92 13.25 9.86 2.25 3.5

16.1 0.01 0.02 0.6

40.19 41.41 0.65 10.4 15.7 11.5 23.9 20.7 0.05 4.1

14.3

Table 5: Analysis of soil paste extract


224

8. Plain with rock outcrop The soil surface is covered by stones in different size mixed with sand and gravels, shallow depth and it could be classified as Typic quartzpssament 9. Denuded hills The total area of this unit is 49248 fedden. Area covered with big rocks and stones of different size 10. Mountain The total area of this unit is 189660 fedden. Rocks.

REFERENCES

[1] A.P.A., Vink "Aerial photographs and soil sciences". UNESCO report, Paris, (1963). [2] C. A., Black; D.D., Evans; L.E., Ensminger; J.L, White and F.E., Clark."Methods of soil analysis". Medison: American Society of Agronomy. IAC., Medison, Wisconsin, USA., (1985) [3] C. S., Piper "soil and plant analysis". Inter science Publishers, Inc., New York, PP.59-75, (1950). [4] Desert Research Center (1994). Reconnaissance studies for natural and human resources in El-Shalatein-Halaib. Supervising committee on Technical studies and natural resources of El-Shalatein-Halaib region, D.R.C. Mataria, Cairo, Egypt (in Arabic). [5] Egyptian General Petroleum Cooperation Staff "Geological map of Egypt scale 1:500000". The Egyptian General Petroleum Cooperation, Cairo, Egypt, (1987). [6] Egyptian Geological Survey and Mining Authority Staff "Geological map of Egypt, Scale 1:2000000". Ministry of industry and mineral resources, Cairo, Egypt, (1981). [7] F. A., Hammad "Water situation in El-Shalatien- Halaib region sustainable agriculture potentiality". International Egyptian center of Agriculture, Cairo, Egypt. Report (in Arabic). (1994). [8] F.A.O. staff "Guidelines for soil profile description". F.A.O. soil Bulletin 6, F.A.O, (1966). [9] J. A., Zink "Geomorphology and soils", internal publ., I.T.C. Enschede, (1988). [10] J., Bennema and M. F., Gelons "Aerial photo interpretation for soil survey". Lecture note, I.T.C. courses photo-interpretation in soil survey I.T.C., Enschede, The Netherlands, (1969). [11] L. A., Richards "Diagnosis and improvement of saline and alkali soils". U. S. Dep. Of Agric. Hand Book, No. 60, pp. 102, (1954). [12] M. L., Jackson (1973). Soil chemical Analysis. Inter. Sci. pub. Inc., N.Y. [13] M. S., Abu Al-Ezz "Land form of Egypt'. Jojn Wiley and sons., Inc., New York. (1987). [14] M., El-Rakaiby; T., Ramadan; A., Morsy and M., Ashmawe "Geological and geomorphological studies of Halaib and Shalatien region and its relation to surface and subsurface water". NARSS, Cairo, Egypt, (1996). [15] R., Said (1990). "The geology of Egypt". A. A. Balkema, Rotterdam, Brookfield (1990). [16] USDA (1998) "key to soil taxonomy". SCC, SMSS Technical Monograph 19, USDA, USA., (1987).


225

HIGH RESOLUTION TERRAIN MAPPING AND VISUALIZATION OF CHANNEL MORPHOLOGY USING LIDAR

AND IFSAR DATA

Sudhir Raj Shrestha1*, Dr. Scott N. Miller2

1Graduate Research Assistant, University of Wyoming, Department of Renewable Resources, Laramie, WY

82071, USA, Email: [email protected], Phone: 1-307-766-5305, Fax: 1-307-766-6403, 2Professor Poster Extended Abstract Channel morphology characteristics play crucial roles in the understanding and interpretation of the geomorphic and hydrologic characteristics of an area. Conventional techniques for determining channel width, depth and cross-section area is time consuming and most of the time may not represent the spatial variability within the watershed. This poster presents an overview of the methods for extracting average channel morphology characteristics on a channel reach basis from a high resolution Digital Elevation Model (DEM) of 1m and 2.5m respectively build from Light Detection and Ranging (LiDAR) and Interferometric Aperture Radar (IFSAR) for 150 km2 USDA-ARS Walnut Gulch Experimental Watershed in Arizona.

LiDAR is an active remote sensing technology used on a satellite or airborne platform. By the use of laser light for reflection, high precision kinematic DGPS (differential global positioning systems) for position information, and an IMU (intertial measuring unit, also know as inertial navigation system, INS) for altitude calculations, this system can collect high density, highly accurate topographic and bathymetric data. Digital products delivered to the end user include a grid or irregular network of XYZ data points with maximum vertical accuracy on the order of 15 cm and horizontal spacing on the order of 1m, but under some circumstances as fine as 30-60 cm. This technology holds the promise of producing fine resolution digital elevation model (DEM) for use in soil survey, subaqueous soil survey, and other related pedologic and geomorphological work.

IFSAR is an active remote sensing technology used on satellite or aircrafts. It combines complex images recorded by antennas at different locations or at different times. It is an alternative to conventional stereo photographic techniques for generating high resolution topographic maps. The primary objective of this project was to evaluate the accuracy of the LiDAR and IFSAR data in estimating channel morphology and build an input for Predictive Soil Mapping (PSM) project. An approach was developed in a geographic information system (GIS) to extract cross-section profiles on a stream system derived from the topographic models. Simultaneous to the acquisition of LIDAR data a field campaign was undertaken by to evaluate the accuracy of the LiDAR DEM; a total station was used to evaluate cross sections at 22 sites within the study area. Manual interpretation was required to identify the bank location from the profiles extracted from the GIS, after which average channel morphologic properties of width, depth and cross-section area were determined. Results from both the LiDAR and IFSAR data were highly correlated with field observations, although the LiDAR data performed significantly better in terms of the ability to determine channel depth. These results illustrate the benefits of using high resolution data in hydrologic and geomorphic study, and show promise towards the development of a fully automated system for extracting channel morphology from surface terrain models which can be used as one of the proxies of soil forming factors in PSM.


226

Sub-theme : DEVELOPMENTS IN SOIL SAMPLING AND PROXIMAL SENSING WITH APPLICATIONS IN PRECISION

AGRICULTURE

M. van Meirvenne, U.W.A. Vitharana L. Cockx

2 Research unit Soil Spatial Inventory Techniques, Dept. of Soil Management & Soil Care, Coupure 653, Ghent

University, Gent, Belgium Detailed soil spatial information has become indispensable for a variety of agronomic and environmental applications. Precision agriculture is one of the applications which refers to a crop management concept that allows for variable management practices within a field according to soil or site conditions. The economic and environmental benefits of precision agriculture have stimulated the research interest and farmer adoption level in developed countries. Moreover, there are evidences for the potential applications of precision agriculture technology in developing countries with proper adjustments. Intensive soil sampling and analysis is not a realistic alternative to explore the detailed soil spatial variation due to cost constraints. The advances in soil sensing technology, global positioning systems (GPS) and spatial prediction techniques make it possible to acquire accurate high resolution soil information in a cost effective manner. The user friendly geographical information systems have provided tremendous opportunities to analyze, display and inventory soil information. Consequently, new digital soil mapping techniques are aimed to produce soil inventories with 5 m resolution [6].

Proximal soil sensing is widely accepted as a suitable ancillary information source for detailed soil mapping. Currently, different types of proximal soil sensor techniques are available. These include electromagnetic induction (EMI), magnetics, soil resistivity, spectrometry, ion selective field effect transistors, aerial digital photography and ground penetrating radar. In addition, combines mounted with crop yield sensors became commercially available in the last decade. These sensors are capable to reflect the spatial variability of different crop and soil properties, e.g. the EMI based EM38 sensor measurements reflect soil textural variation. Proximal sensors are coupled to a GPS receiver and a data logger to obtain large numbers of on-the-go georeferenced measurements. The spatial variation observed with sensor information can be used to design a targeted field soil sampling scheme consisting of a limited number of samples [2]. The relationships identified between the proximal sensor information and soil properties are used to predict soil variation using appropriate prediction technique. The prediction approaches include techniques such as geostatistical methods, different forms of regression, neural networks and Bayesian maximum entropy. The clustering procedures like fuzzy k-means algorithm facilitate to identify within-field zones characterized with a unique combination of soil properties to manage crops at a within-field scale.

REFERENCES

[87] C.L. Arnold, Jr., D.L. Civco, M.P. Prisloe, J.D. Hurd, J.W. Stocker. "Remote-sensing-enhanced outreach education as a decision support system for local land-use officials", Photogrammetric Engineering and Remote Sensing, 66 (10), 1251-1260, (2000). [88] J. Bak, J. Jensen, M.M. Larsen, G. Pritzl, J. Scott-Fordsmand. A heavy metal monitoring-program in Denmark. The Science of the Total Environment 207: 179-186., (1997). [89] J.S. Bethel, J.S., J.Ch. McGlone, E.M. Mikhail. "Introduction to Modern Photogrammetry", John Wiley & Sons, Inc., New York, 477p, (2001).


227

[90] D.L. Corwin., S.M. Lesch. “Characterizing soil spatial variability with apparent soil electrical conductivity I. Survey protocols”. Computers and Electronics in Agriculture, 46, pp. 103-133, (2005). [91] D. Devriendt, M. Binard, Y. Cornet, R. Goossens. "Accuracy assessment of an IKONOS derived DSM over urban and suburban area", In : Proceedings of the 2005 workshop EARSeL Special Interest Group “3D Remote Sensing” - use of the third dimension for remote sensing purposes. [92] D. Devriendt, R. Goossens, A. Dewulf, M. Binard. "Improving spatial information extraction for local and regional authorities using Very-High-Resolution data – geometric aspects", High Resolution Mapping from Space (2003). [93] D. Devriendt, R. Goossens, A. De Wulf, M. Binard. "Improving spatial information extraction for local and regional authorities using Very-High-Resolution data - geometrical aspects", In : Proceedings of the 24th EARSeL symposium : New Strategies for European Remote Sensing, /May 2004, Dubrovnik, Croatia, pp 421-428, (2005). [94] P.A. Finke. Updating groundwater table class maps 1:50,000 by statistical methods: an analysis of quality versus cost. Geoderma 97: 329-350, (2000). [95] P.A. Finke, D.J. Brus, M.F.P. Bierkens, T. Hoogland, M. Knotters, F. de Vries. Mapping ground water dynamics using multiple sources of exhaustive high resolution data. Geoderma 123: 23-39, (2004). [96] K. Jacobsen. "Analysis of Digital Elevation Models based on space information", New Strategies for European Remote Sensing, Rotterdam : Millpress, pp 439-451, (2005). [97] K. Jacobsen. "Orthoimages and DEMs by QuickBird and IKONOS", Remote Sensing in Transition, Rotterdam, Millpress, 273-279, (2003). [98] P.J. Kuikman, W.J.M. de Groot, R.F.A. Hendriks, J. Verhagen, F. de Vries. Stocks of C in soils and emissions of CO2 from agricultural soils in The Netherlands. Wageningen, Alterra-report 561. 41 pp. (http://www2.alterra.wur.nl/Webdocs/PDFFiles/Alterrarapporten/AlterraRapport561.pdf ), (2003). [99] A.B. McBratney, M.L. Mendonca Santos, B. Minasny. “On digital soil mapping” Geoderma, 117, pp. 3– 52, (2003). [100] S.P. McGrath, P. Loveland. The Soil Geochemical Atlas of England and Wales. Blackie Academic and Professional, Glasgow, (1992). [101] K. Taillieu, R. Goossens, D. Devriendt, A. Dewulf, S. Van Coillie, T. Willems. "Generation of DEMs and orthoimages based on non-stereoscopical IKONOS images", New Strategies for European Remote Sensing, Rotterdam : Millpress, pp 453-460, (2005). [102] T. Vandevoorde, M. Binard, F. Canters, W. De Genst, N. Stephenne, E. Wolff. "Extraction of land use / land cover - related information from very high resolution data in urban and suburban areas", Remote Sensing in Transition, Rotterdam : Millpress, pp 237-245, (2003). [103] G. Zhou, R. Li. "Accuracy evaluation of ground points from IKONOS high-resolution satellite imagery", Photogrammetric Engineering and Remote Sensing, 66 (9), 1103-1112, (2000).


228

ESTIMATING SPATIAL VARIABILITY OF SOIL SALINITY

USING COKRIGING IN BAHARIYA OASIS, EGYPT

Kh. M. Darwish*, M.M. Kotb and R. Ali

Soils & Water Use Dept., National Research Centre (NRC), Cairo, Egypt. * [email protected]

Abstract The mapping of saline soils is the first task before any reclamation effort can be conducted. Soil salinity is determined, traditionally, by soil sampling and laboratory analysis. Recently, it became possible to complement these hard data with soft secondary data made available using field sensors like electrode probes or satellite images. Estimating spatial variability of soil salinity is an important issue in precision agriculture. In this study, geostatistical method of cokriging, were applied to estimate and identify the spatial variability of soil salinity with ECe measurements in 200 km2 agricultural fields in the north and south Bahariya oasis. In cokriging, more densely sampled secondary data from the ETM satellite image source were incorporated to improve the estimation of the electrical conductivity (ECe). The estimated spatial distributions of ECe using the geostatistical methods with various reduced data sets were compared with the extensive salinity measurements in the large field. The results suggest that sampling cost can be dramatically reduced and estimation can be significantly improved using cokriging. Compared with the kriging results using only primary data set of ECe, cokriging with reduced data sets of ECe improves the estimations greatly by reducing mean squared error and kriging variance up to 70% and increasing correlation of estimates and measurements about 25%. Relative improvements in map accuracy were highest (25% to 38%) in regression colocated cokriging approach, which also performed better than ordinary kriging method that utilized only one ancillary variable. The relative gain from incorporating remote sensing secondary information increased with decreasing sampling density. The results of these models allow to interpolate and classify salinity on a more realistic and continuous scale. Keywords: soil salinity - spatial variability - cokriging algorithm – colocated cokriging. Introduction

Soil salinity limits food production in many countries of the world. There are mainly two

kinds of soil salinity: naturally occurring dryland salinity and human-induced salinity caused by the low quality of water. In both cases the development of plants and soil organisms are limited leading to low yields. In Bahariya oasis, where more than 10% of the land is affected by salt, groundwater and inadequate drainage conditions are the major causes of salinization. Generally, the classical soil survey methods of field sampling, laboratory analysis and interpolation of these field data for mapping, especially in large areas is relatively expensive and time consuming. Remote sensed data might be a useful tool to overcome these problems. Dwivedi (1992) used Landsat MSS and TM data for more detailed mapping and monitoring of the salt affected soils in the frame of the reconnaissance soil map of India. Also, De Dapper and Goossens (1996) indicated the development of GIS and remote sensing for monitoring and predication of soil salinity in the Desert-Delta fringes of Egypt.

Conventionally (Soil and Plant Analysis Council, 1992) soil salinity is determined by laboratory analysis (electrical conductivity of the saturated soil paste extract ECe). This


229

procedure is expensive and time-consuming, and provides an incomplete view of the extent of soil salinity. An alternative to laboratory analysis is to assess soil salinity in the field by determining the apparent electrical conductivity (ECa). This can be done using sensors such as the four-electrode probes (Rhoades and van Schilfgaarde, 1976) or by electromagnetic induction instruments (McNeil, 1980). This procedure is cheaper and less time-consuming and enabling a more intensive survey of the study area. Creating maps typically involves sampling, measuring the variable of interest, and estimating values at unsampled locations through some form of interpolation, plain regression, data aggregation, or other prediction techniques (McBratney et al., 2003).

Geostatistics offers a collection of deterministic and statistical tools aimed at understanding and modeling spatial variability. Hybrid geostatistical procedures that account for environmental correlation have become increasingly popular in recent years because they allow utilizing secondary information that is often available at finer spatial resolution than the sampled values of a primary target variable. If the correlation between primary and secondary variables is significant, hybrid techniques generally result in more accurate local predictions than ordinary kriging or other univariate predictors (Goovaerts, 1999; McBratney et al., 2000; Odeh et al., 1994; Triantafilis et al., 2001).

Cokriging is the extension of kriging to more than one variable. It is most likely to be beneficial where the primary variable (the one be estimated) is under sampled with respect to the secondary variable(s) that are assumed to be correlated with the primary variable. In some applications there are only a few measurements of the attribute of interest; the resultant predicated maps have poor resolution and the corresponding uncertainty may be very large. In such situation it is critical to account for secondary, indirect information that may be more densely sampled (Goovaerts, 1997).

In this way, colocated cokriging is as reduced form of full cokriging. It requires only knowledge of the semivariogram of the primary variable and the cross-variogram between the primary and secondary variable (Curran & Atkinson, 1997). Furthermore, the combination of geostatistics and remote sensing techniques has been used before to study and assess the magnitude and extent of spatial variability in soil salinity (Lesch et al., 1995; Christakos & Li, 1998.; Darwish, 1998).

This study aims to map soil salinity in the northern and southern part of Bahariya oasis using geostatistical techniques, integrating a limited data set of soil salinity measurements (ECe) as a primary variable with ETM satellite image as a secondary data source. The result of this methodology will be qualified using the cross validation method. Material and methods Study site description

Bahariya depression is located nearly in the middle of the Western desert of Egypt and comprising a total area of approximately 2250 km2 (Fig.1). The area falls under the arid condition as the total rainfall is (3-6) mm/year. Springs and wells are the main two groundwater resources for irrigation and civic purposes (Salem, 1987). In Bahariya, it is found that the main unsuitability criteria eliminating more extend of cultivation areas is the excess of salts. In this research, two study areas were selected. One is in the north of Bahariya covering an area of about 118.3km2 and the second is covering partly the southern part of it with an area of 77.5km2 (Fig.2).


230

Data description Based on the pre-field and information obtained, 45 soil profiles and 71 soil augers were examined in different locations. Fig. 3a and 3b show the location of the observation sites where soil samples were taken. Four transects in area1 and two in the southern one. Electrical conductivity soil salinity measurements (ECe) dS/cm were determined in the soil water extract out of the saturated soil paste. Total of six sample areas were selected and distributed over the study areas with a fixed wide of 1km for each. The exact locations of the soil profiles and auger points were precisely defined in the field by using the DGPS, and plotted on the maps.

Figure 1 & 2. Location and the study areas in N and S Baharyia.

Figure 3a. Location of sample points in study area-1 (North).


231

Figure 3b. Location of sample points in study area-2 (South).Fig. 4a and 4b show the frequency distribution of ECe (dS/cm) values in study areas-1 and 2 respectively. The first one exhibit abnormal

distribution, while the second is normally distributed, which does not deemed Ln transformation. Although the Ln transformation ECe semivariogram can give a better fitting, but the problem of back

transformation through the estimation procedure is limiting its usability.

0,0 2,3 4,5 6,8 9,0

0,96 59,97 118,99 178,00

Freq

uenc

y

"ECe"

Figure 4a. Frequent distribution of ECe values in study area-1.

0 1 2 2 3

0,86 44,57 88,29 132,00

Freq

uenc

y

"ECe"

Figure 4b. Frequent distribution of ECe values in study area-2

Method of geostatistical analysis The variability of soil salinity representing horizontal distribution of salts in continuous model was mapped. The study shows that it is possible to map soil salinity variability using


232

an appropriate interpolation technique. The part of the study, as reported here, includes reconstructing the spatial variability of salinity; and evaluating the accuracy to predict electrical conductivity measurements.

Geostatistical methods can be used to measure and model the spatial correlation of soil salinity measurements as a primary variable and the satellite image as a secondary data variable. The models of spatial correlation are then used along with Kriging and the new geostatistical technique of Collocated Cokriging to develop large scale maps showing the spatial pattern of soil salinity status in the selected study area.

Colocated Cokriging As mentioned before, Cokriging is the extension of Kriging to more than one variable. Colocated cokriging is as reduced form of full cokriging.

Considering Z (the primary variable) = 1 and Y (The secondary variable) = 2 Then, colocated cokriging with Markov-type approximation of attribute Z at location X

is given by:

Z*cok (u) = n i=1∑ λ1i (u) Z (ui) + λ2 (u) [Y (u) + mz - my] (1)

Where: Z*cok (u): cokriging estimator of Z(u) λ1i (u): cokriging weight associated to neighboring datum Z(u) for estimation at location u. λ2 (u): cokriging weight associated to collocated secondary datum Y(u). mz: mean of the primary variable (ECe measurements). my: Mean of the secondary variable (Satellite data).

In this study, colocated cokriging was applied to map soil ECe values, from available ECe data as primary data and ETM Satellite image as densely sampled secondary data source. When the collocated secondary variable Y (u) is known everywhere and varies smoothly across the study area (e.g., satellite data & surface reflectance) there is little loss in retaining in the cokriging system, provided that it is available at each location u being estimated (Xu et al., 1992; Goovaerts, 1998b). This is clear the case in remote sensing where the secondary variable is provided by remotely sensed imagery data, which often completely covers the area of interest. Selection of the imagery Two smaller windows of a complete Landsat 7 Enhanced Thematic Mapper (ETM) satellite image of Bahariya Oasis dated in 21-04-2002 were chosen to be used in this study (Fig.2). The False Color Composite (FCC) of these image windows is covering area-1 as shown in Fig. 3a and area-2 in Fig. 3b. The first image window is within the Northern part of Bahariya depression, which is covering most of the villages located there. The second one is covering partly the southern part of Bahariya.

The following geo-morphological features are covered by image one from north to south: 1- Maysera Plateau, escarpment and plateau footslope. 2- Mandisha Hill, hilland and footslope. 3- Peneplain sand sheet and rock out crop. 4- Plain sand sheet, sand flat and playa. On the other hand, the following geo-morphological features can be recognized in image two: 1 Plain sand sheet, sand flat, playa and isolated conical hills.


233

2 Plateau footslope and escarpment.

RESULTS AND DISCUSSION Exploratory data analysis Some statistics about the hard data (ECe) for areas-1 &-2 are reported in Table 1. It was noted the presence of a strong spatial variability. For example in areas 1 & 2, there is a big difference between the extreme values (minimum and maximum). In addition, to improve estimation accuracy, the correlation between the primary and secondary variables should be as high as possible. Therefore, the Pearson correlation coefficient was applied on the ECe values that were available and the colocated reflectance measurements provided by the eight spectral bands of the ETM image. It is found, that the highest correlation (r≅0.3) of the ETM bands with the EC observations is signed for the ETM low gain band 6 (Fig. 5). At study areas 1 and 2, the relationship between EC and surface reflectance REF was probably masked by the sand sheet and flat layer on the soil surface, which had accumulated as a result of geological history and greatly affected surface reflectance shown in the satellite image, but not mainly EC. The oldest rocks exposed within Bahariya depression are sandstone, siltstone and clay of Cenomanian age that cover the floor of the depression and crop out along the base of the escarpment (Parsons, 1962). In this way, the secondary variable could be determined for every pixel covered by the image.

Items Mean Standard Deviation Sample variance Min. Max.

Area 1 (N) 37.27 46.51 2163.06 0.96 178.0

Area 2 (S) 51.26 39.41 1552.79 0.86 132.0

Table 1. Statistical summary of ECe (dS/cm) data.

-0.05

0

0.05

0.1

0.15

0.2

0.25

0.3

Corr

elat

ion

Coef

ficie

nt

1 2 3 4 5 6 7 8

ETM spectral bands

Figure 5. The Correlation Coefficient statistical analysis among primary and secondary variables. (All correlations were significant at P < 0.001 level).

On the other hand, the frequent distribution of the colocated reflectance measurements

of ETM low gain band 6 for area 1 and 2 is illustrated in Fig. 6a & 6b.


234

0 2 4 6 8

148.0 169.0 190.0 211.0

Freq

uenc

y

ETM LG band 6

NonTransformed

0 1 1 2 2

161.0 177.0 193.0 209.0

Freq

uenc

y

ETM LG band 6

NonTransformed

Figure 6a. Frequent distribution of ETM low gain band 6 for area-1.

Figure 6b. Frequent distribution of ETM low gain band 6 for area-2.

The reflectance values of ETM LG band 6 were standardized to zero mean and unit variance for each study area and re-combined into one dataset of standardized the field surface reflectance (REF) for whole study area. The confirmed Regression Coefficient of (ETM LG band 6) with the EC observations for study areas 1 and 2 is indicating relatively higher correlation for area-1 than area-2 (Fig. 7a & 7b).

0.96

45.22

89.48

133.74

178.00

148.00 169.00 190.00 211.00

Prim

ary

("EC

")

Covariate ("ETM LG 6")

Regression coeff icient = 0.9 (SE = 0.6, r2 =0.065, y intercept = -126.705, n = 31)

0.86

33.65

66.43

99.22

132.00

161.0 177.0 193.0 209.0

Prim

ary

(EC

)

Covariate (ETM LG band 6)

Regression coefficient = 0,6 (SE = 0,8, r2 =0,047, y intercept = -72,154, n = 14 Figure 7a. The Regression Coefficient among variables (Z & Y) in area-1

Figure 7b. The Regression Coefficient among variables (Z & Y) in area-2.

Structure analysis It is necessary to analyze the spatial variability of the data above by semivariance function. Fig. 8a and 8b illustrate the semivariance value of primary variable (ECe) of study areas 1 & 2. The sill of EC in areas 1 & 2 are 2620.0m and 1845.0m and their correlation lag range 3710.0m and 1120.0m respectively


235

0

1451

2902

4353

5805

0.0 2596.0 5192.0 7788.0

Sem

ivar

ianc

e

Separation Distance (h) m

0

870

1741

2611

3482

0.0 2257.7 4515.3 6773.0

Sem

ivar

ianc

e


Figure 8a. Isotropic variogram (spherical model) of ECe (dS/cm) in area-1.

Figure 8b. Isotropic variogram (spherical model) of ECe (dS/cm) in area-2.

The variogram shows a relative nugget effect of 11.7% for study area-1 and 10.0% for area-2, which cloud be calculated through this ratio [(C

0/(C

0 + C)) x 100] between nugget variance

and sill. The nugget effect looks more significant in study area-2 than area-1, which causes by random factors.

On the other hand, as Cokriging is a multivariate extension of kriging, when the secondary variable is known everywhere and varies smoothly across the study area (e.g., colocated reflectance measurements provided by ETM low gain band 6) there is little loss in retaining in the cokriging system. The secondary variable provides information only about the primary trend at location u.

In order to apply a colocated cokriging method a cross-semivariance analysis must be performed prior to cokriging, where CZY(ui - u) is the cross covariance between primary and secondary variables at locations ui and u, respectively. Again, the common practice consists of estimating and modeling the (cross) semivariogram, then retrieving the (cross) covariance. Fig. 9a and 9b show the experimental semivariogram of the secondary variable ETM LG band6 and cross semivariogram with the primary one (ECe point observations) for study area-1, computed as:

(2)


236

0.0

131.6

263.1

394.7

0.0 2596.0 5192.0 7788.0

Sem

ivar

ianc

e


"ETM LG 6": Isotropic Variogram

-34.

698.

1431.

2163.

0.0 2596.0 5192.0 7788.0

Sem

ivar

ianc

e


"EC" x "ETM LG 6": Isotropic Cross Variogram

Figure 9a. The semivariogram of secondary

variable for study area-1 Figure 9b. The cross-variogram of primary and

secondary variables for area-1. The sampling interval can be determined based on the semivariograms. In Fig. 9a & 9b, an exponential model of isotropic variogram was fitted for the secondary variable (ETM LG 6) using an iterative procedure developed by Goulard (1989). The cross-variogram between the primary and secondary data sets is modeled (here a small nugget effect 11.6m and a spherical model with sill 232.2m and range 3400.0m), indicating that the intensive sampling scheme used resolved most of the spatial variation

Nevertheless, Fig. 10a & 10b illustrate the experimental semivariograms of the secondary variable (ETM LG 6) and the cross-variogram in study area-2. At area-2, the isotropic varigram of (ETM LG 6) shows a spherical model with a sill of 164.7m and a fitted range of 1150.0m, which probably reflected gradual differences in EC due to elevation. The cross-variogram between the primary and secondary data sets in area-2 modeled linearly with sill of 0.1m and range of 0.75m. Although in study area-2, EC was less significantly correlated with the secondary variable compare with area-1, only a small portion of the variation in EC can be explained by variation in elevation. Generally, cross-variograms largely confirmed the findings of the simple correlation analysis, showing (i) more spatial correlation between EC and ETM LG 6 at area-1, and (ii) declining spatial correlation between EC and ETM LG 6 at area-2 (Fig. 10b). This proves the existence of correlation between spatial variability of the soil salinity data, which belongs to nugget effect.

0.0

150.0

300.0

450.0

0.0 2257.7 4515.3 6773.0

Sem

ivar

ianc

e


"ETM LG 6" Isotropic Variogram

-1251.75

-550.61

150.52

851.66

1552.79

0.00 2257.67 4515.33 6773.00

Sem

ivar

ianc

e


"EC" x "ETM LG 6" : Isotropic Cross Variogram

Figure 10a. The semivariogram of secondary

variable for study area-2. Figure 10b. The cross-variogram of primary and

secondary variables for area-2.


237

Colocated Cokriging of EC point observations with ETM as secondary data source The colocated cokriging interpolated maps cover study areas 1 and 2 is shown in Fig. 11a & 12a. The ordinary cokriging algorithm was applied to interpolate the EC data using GS+ program.

As a result of using search neighborhood area as indicated in the cross-variograms of area-1 and area-2, quite lots of areas were closed to the primary observation points and this give high effect of the secondary data. Closer to primary observation points this effect is more screened by the available primary data and this significantly improved the accuracy of colocated EC maps.

However, the visual interpretation of the EC colocated map of area-1 in relation to the DEM (digital Elevation Model) grid image of each area give a good impression that the estimation of salinity values is logical, taken into consideration the location from the salt effected soils (playa), the relatively lower elevation units (depressions) and the position in landscape in the oasis (Fig. 11b).

35679444 35687159 35694874"m east"

3134583

3138434

3142286

"m n

orth

"

"EC"

> 164> 151> 139> 126> 114> 102> 89> 77> 64> 52> 39> 27> 15> 2> -10

Figure 11a. Interpolate-colocated cokriging map of EC (dS/cm) of the study area-1 (North of Bahariya).

On the other hand, the relatively high ECe (dS/cm) values that are pronounced and

presented as connected counter lines are expressing the areas where low elevation and much salinity features are available. This is clear presented for area-2 in Fig. 12b. This quite validating the estimated interpolated cokriged maps obtained. Obviously, there is a visually better resolution of spatial detail in the EC colocated cokriging interpolated maps.


238

35680000 35684000 35688000 35692000

3136000

3138000

3140000

3142000

92

96

100

104

108

112

116

120

124

128

132

136

140

144

Playa

Playa

Depression

Figure 11b. The Digital Elevation Model (DEM) map of area-1.

35657997 35663986 35669976"m east"

3097399

3100634

3103869

"m n

orth

"

"EC south area"

> 119> 110> 102> 93> 85> 77> 68> 60> 51> 43> 34> 26> 18> 9> 1

Figure 12a. Interpolate-colocated cokriging map of EC (dS/cm) of the study area-2 (South of Bahariya).

35658000 35661000 35664000 35667000

3098000

3100000

3102000

94

98

102

106

110

114

118

122

126

130

134

138

142

Playa

Figure 12b. The Digital Elevation Model (DEM) map of area-2


239

Perform cross validation analysis To assess the accuracy of the colocated cokriging estimated maps, there is a cross validation analysis for evaluating effective parameters for cokriging. In cross-validation analysis a graph can be constructed of the estimated vs. actual values for each sample location in the domain. The cross validation analysis of study areas 1 and 2 are presented in Fig. 13a & 13b. Each point on the graph represents a location in the input data set for which an actual and estimated value are available.

0.96

45.22 89.48

133.74 178.00

0.96 59.97 118.99 178.00

Actu

al "E

C"

Estimated "EC"

Regression coeff icient = 0.321 (SE = 0.363 , r2 =0.026,y intercept = 26.72, SE Prediction = 45.893)

0.86

33.65

66.43

99.22 132.00

0.86 44.57 88.29 132.00

Actu

alEstimated

Regression coeff icient = -0.455 (SE = 0.390 , r2 =0.102,y intercept = 75.99, SE Prediction = 37.344)

Figure 13a. Cross Validation (CoKriging) of study area-1.

Figure 13b. Cross Validation (CoKriging) of study area-2.

The regression coefficient, which is describing the linear regression equation is for

(area-1) = 0.3 and for (area-2) = -0.4. The standard error of the regression coefficient (SE = 0.36, 0.39 for area-1 & 2 respectively). The r2 value is the proportion of variation explained by the best-fit line (in case of (area-1) = 2.6% and 10.2% for (area-2)); and the y-intercept of the best-fit line is also provided. The SE Prediction term is defined as SD x (1 - r2)0.5, where SD = standard deviation of the actual data (45.9 and 37.3 for areas-1 & 2 respectively).

Generally, the method of colokated cokriging significantly improved the accuracy of interpolated cokriged EC maps, as shown by a reasonable acceptable regression coefficient values in both study areas. For cokriged EC, patterns in the interpolated EC maps closely resembled those of the DEM maps, indicating that this method is also more vulnerable to potential artifacts in ancillary variables. In study areas 1 & 2, both the primary variate (ECe measurements) and secondary one (surface reflectance derived from ETM satellite image) contributed significantly to predicting the local means of ECe.

However, it is clear that the spatial variability of area-2 is comparatively less than that in area-1. The main reason for this weakness of spatial variability in area-2 could be referred to the lack of EC sampling points available and still to the high influence of the ECe (dS/cm) extreme values on neighboring locations.

Although two sites were used in our study, the range in soil types and terrain conditions was limited. Clearly, more work needs to be done, to develop a flexible, more generic framework for soil salinity mapping at different scales and in different environments. Of particular interest is what secondary data source (e.g. surface reflectance derived from satellite images) are most suitable for EC mapping across larger regions, for which detailed on-the-go mapping of EC or similar properties is not feasible. Our study indicates great potential for reducing sampling demand in digital soil salinity mapping when a cokriging approach is used. However, the reduction of sample size tested here (Fig. 13a & 13b) was somewhat arbitrary. Better procedures are needed for optimizing sampling with regard to


240

covering the variation in primary and secondary variables in both feature and geographic spaces, including situations where little prior information about the target variable is available.

CONCLUSION The spatial distribution maps drawn based on cokriging interpolation method explain clearly the spatial variability of soil salinity in north and south study areas of Bahariya oasis. Geostatistical method of colocated cokriging that utilized spatially correlated secondary information increased the quality of maps of soil salinity (ECe measurements) as compared to ordinary kriging method. Apparent EC cokriged with surface reflectance derived from satellite images performed best in terms of increasing map accuracy. In this method, relative improvements in map accuracy over ordinary kriging method ranged from 19% to 38% at the two study areas and there was little loss of accuracy when sampling intensity was reduced by half as shown in area-2. The ETM LG band 6 secondary data source is considered valuable one for detailed mapping of EC at the field scale, whereas the relative value of terrain attributes varied geographically.

Indeed, there are different original factors have influenced the final output of the cokriging logarithm technique. Those factors can be related to the issues of sampling, the spatial distribution of the soil salinity measurements in the space, the total number of the observation points and the variability of the ECe data set obtained. In addition, most secondary information (i.e. satellite image data) contains uncertainties that may mask relationships with EC values, or other soil properties of interest. Furthermore, relying on a single secondary attribute is risky because (i) the variable chosen may not be related to the primary variable of interest and (ii) field artifacts or errors in the secondary information could cause significant errors in the EC prediction.

Improving those factors especially in the south study area-2, would play an important role for receiving more accurate results out of this interpolation method.

At the end of the whole procedure, it is still manage successfully to use the obtained interpolated EC salinity maps. To reduce uncertainties, we recommend using independently measured, multivariate secondary information in estimating spatial variability of soil salinity approach.

REFERENCES

[104] A.B. McBratney, I.O.A. Odeh, T.F.A. Bishop, M.S. Dunbar and T.M. Shatar. "An overview of pedometric techniques for use in soil survey". Geoderma 97, 293– 327, (2000). [105] A.B. McBratney, M. L. Mendonca Santos and B. Minasny. "On digital soil mapping". Geoderma 117, 3– 52, (2003). [106] G. Christakos, X. Li. "Bayesian maximum entropy analysis and mapping: a farewell to kriging estimators". Mathematical Geology 30, 435–462, (1998). [107] I.O.A Odeh, A.B McBratney and D.J. Chittleborough. "Spatial prediction of soil properties from landform attributes derived from a digital elevation model". Geoderma 63, 197–214, (1994). [108] J. D. McNeil. "Electromagnetic Terrain Conductivity Measurement at Low Induction Numbers: Technical Note TN-6". GEONICS Limited, Ontario, Canada (15 pp.), (1980). [109] J.D. Rhoades and J. Van Schilfgaarde. "An electrical conductivity probe for determining soil salinity". Soil Science Society of America Journal 40, 647– 651, (1976). [110] J. Triantafilis, A.I. Huckel and I.O.A Odeh. "Comparison of statistical prediction methods for estimating field-scale clay content using different combinations of ancillary variables". Soil Sci. 166, 415–427, (2001).


241

[111] Kh. M. Darwish. "Integrating soil salinity data with satellite image using geostatistics". M.Sc. Thesis, Faculty of Agricultural and Applied Biological Sciences, Gent University, Gent, Belgium, (1998). [112] M. De Dapper, R. Goossens. "Modeling and monitoring of soil salinity and water logging hazards in the Desert-Delta fringes of Egypt based on Geomorphology", Remote Sensing and GIS, (1996). [113] M. Goulard. "Inference in a coregionalization model". In: M. Armstrong, Ed. Geostatistics, Kluwer, Dordrecht, pp. 397-408, (1989). [114] M. Z. Salem. "Pedological characteristics of Bahariya Oasis soils". Ph.D. Thesis, Fac. of Agric. Ain Shams, Univ., Egypt, (1987). [115] P. Goovaerts. "Geostatistics for Natural Resources Evaluation", Oxford University Press, London, (1997). [116] P. Goovaerts. "Ordinary cokriging revisited", Math. Geol., 30(1), pp. 21-42, (1998b). [117] P. Goovaerts. "Geostatistics in soil science: state-of-the-art and perspectives". Geoderma 89, 1 –45, (1999). [118] P.M. Atkinson and P.J. Curran. “Choosing an appropriate spatial resolution for remote sensing investigations”. Photogrammetric Engineering and Remote Sensing, 63, 1345-1351, (1997). [119] R. M. Parsons. "Bahariya and Farafra areas (New Valley Project, Western Desert of Egypt)", Final Report. Egyptian General Desert Development Organization, U.A.R, (1962). [120] R. S. Dwivedi. "Monitoring and the study of the effect of image scale on delineation of salt affected soils in the Indo-Gangentic plains". Intern. Journal of Remote Sensing, 13: 1527-1536, (1992). [121] S. M. Lesch, D. J. Strauss and J. D. Rhoades. "Spatial predication of soil salinity using electromagnetic induction techniques. 1. Statistical predication models: A comparison of multiple linear regression and cokriging". Water Resour. Res. 31, 373-386, (1995). Soil and Plant Analysis Council. "Handbook on Reference Methods for Soil Analysis". Georgia University Station, Athens, Georgia, (1992). [122] W. Xu, T.T. Tran, R.M. Srivastava and A.G. Journel. "Integrating seismic data in reservoir modeling: the collocated cokriging alternative", Society of Petroleum Engineers, paper no. 24,742, (1992).


242

SPATIAL VARIABILITY OF DRAINAGE AND PHOSPHATE RETENTION AND THEIR INTER RELATIONSHIP IN SOILS OF

THE SOUTH-WESTERN REGION OF THE NORTH ISLAND, NEW ZEALAND

A.Senarath*, A.S.Palmer and R.W.Tillman

Soil & Earth Sciences, Institute of Natural Resources, Massey University, Palmerston North, New Zealand

Abstract Spatial variability of drainage, phosphate retention and their inter-relationship was investigated in soils developed from mixed quartzo-feldspathic and tephric parent material on river terraces in the south western region of the North Island . A series of drainage class maps at 1:25,000, 1:10,000 and 1:5000 scales were produced for selected window areas. The optimal soil mapping scale for capturing soil drainage variability and the usefulness of the soil maps for identifying spatial variability of phosphate-retention was investigated. Soil drainage varies from well drained through moderately well drained to imperfectly drained and poorly drained within a paddock scale (2-3 ha). In this study, soil drainage had no topographic control which makes soil mapping extremely difficult. The reason for the short distance variability in drainage is attributed to slight textural variations of the original alluvial parent material. This gives rise to the formation of different soil structures, which in turn influences the hydraulic conductivity of the soil and results in variable drainage properties which influence the clay mineralogy. There is a close relationship between soil drainage, P-retention and clay mineralogy. Well drained soils have high P-retention and the clay fraction contains 12-13% allophane. Poorly drained soils have low P-retention and the clay fraction has no allophane and contains mainly kandite. The relationship between soil drainage and P-retention can be used to identify different P-retention areas on soil maps. In addition, 1:10,000 is the most suitable soil mapping scale for practical farm planning in the Region.

INTRODUCTION A detailed soil survey carried out at 1:25,000 scale in an area covering 2000 ha of terraced land near Kiwitea village in south western region of the North Island reveals that the soil drainage varies over the landscape at paddock scale (2-3 ha.) having no topographic control [15]. Soil drainage dictates suitability for cropping and intensive grazing and sensitivity of land to a number of management practices so, soil drainage class maps will be helpful in land use planning and management practices. Furthermore previous studies have shown that phosphate retention (P-retention) is related to soil drainage; and in particular Parfitt et all[10] have shown that soil drainage influences clay mineralogy and hence P-retention. Phosphate retention is an important soil attribute determining the amount of P needed to be applied for plant production. Soil maps are therefore valuable tools. Small scale existing soil maps published for the area at 1:250,000 [9] and at 1:63,360 [8] are clearly incapable of showing drainage variability on soil maps [15].

The aim of this study is to investigate variability of soil drainage status over the landscape, the best scale to map soil drainage classes to aid land management decisions,


243

ability of soil drainage class maps to predict P-retention values and the reasons for short distance soil drainage variability in the region..

OVER VIEW OF THE STUDY AREA The study area, 2000 ha in extent, is located near Kiwitea village in the northern Manawatu district which is situated towards the south-western part of the North Island. The landform of the area is characterized by suites of river terraces at different elevations. Three major terraces can be identified within the area; the river flats (180 m above msl) covered with recent alluvium (1000-2000 years BP) having flat to gently sloping topography, the intermediate terrace (200-240 m above msl) covered with a mixture of old alluvium, colluvium, loess and tephra (<15,000 years BP) having flat to gently sloping topography and the upper terrace (240-300 m above msl ) covered with a mixture of loess and tephra (15,000-25,000 years BP) having flat to rolling topography. The annual rainfall ranges from 900-1200 mm having dry summers and wet winters. The mean annual temperature in the area ranges from 12-13.5 º C [7].

MATERIALS AND METHODS Soil Sampling A window area (2000 m by 300 m) (Figure 1a and 1b) was selected from the intermediate terrace of the study area and mapped at a scale of 1:25,000 [15]. The window area was chosen on the basis that it had both reasonably large areas with similar drainage, but also rapid change from one drainage class to another. The window area, on the 1:25,000 scale map, has three different soil drainage classes; well drained, moderately well drained and imperfectly drained. The drainage classes were used to define new soil series. No artificial drainage has been installed by the farmers. On each map unit a 300 m by 250 m small window area (Blocks A, B and C) was established and sampling points were selected on a 50 m grid (Figure.1b). Soil sampling methods for drainage class mapping and P-retention are discussed below. Drainage class mapping Soil drainage properties were examined by making auger observations to a depth of 110 cm where possible on the established grid, giving 42 observation points in each window. The drainage classes were determined on the basis of depth to a redox mottled horizon and /or reductimorphic horizon [4,17]. In the soil survey, soils with gley profile form are considered poorly drained; soils with mottled profile form are considered imperfectly drained; soils containing a redox-mottled horizon below 60 cm are considered moderately well drained; while soils containing no reductimorphic horizon or redox-mottled horizon within 90 cm are considered well drained. These criteria follow the drainage class separation criteria used in New Zealand soil surveys [6]. Phosphate retention Soil samples were collected from 0-7.5 cm surface soils, on the grid patterns shown in Figure 1b. Three soil samples were taken within 30 cm diameter of each observation point using a


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core sampler and were combined to form a composite sample to determine P-retention. This is the methodology used in New Zealand as part of a fertiliser recommendation for pastures.

P-retention of soils was determined according to the method given by Saunders [13] and the results are expressed as percentage values. Eight quality control samples with known P-retention values were incorporated within each 100-sample batch to monitor the possible variations that might arise among different batches. The same P-retention solution and vanado-molybdate solutions were used throughout the analysis of the samples for a fair comparison of results. Preparation of maps Drainage class maps were generated by the “Surfer” programme (version 5.0) based on the point drainage class data. The drainage class maps (Figure 3A, 3B and 3C) are contour maps generated by the “Surfer” programme based on the point drainage data. The programme generates values between the points automatically by kriging [14]. To generate maps, drainage classes were given numerical values of 100, 90, 60 and 30 for well drained, moderately well drained, imperfectly drained and poorly drained drainage classes respectively [6]. When generating the contour pattern, the programme always generates a sequential drainage pattern according to this order. That is if a well drained soil was found by augering to occur adjacent to a poorly drained soil, the programme automatically interpolates moderately well drained and imperfectly drained soil units between the two.A series of soil drainage class maps were produced at 1:25,000 (observations on a 250 m grid), 1:10,000 (observations on a 100 m grid) and 1:5000 (observations on a 50 m grid) scales Bulk density Bulk density measurements were made on core samples (with known volume) taken from each soil horizon. Soil samples were oven dried at 105° C until the weight became constant. Saturated hydraulic conductivity (Ksat) Saturated hydraulic conductivity measurements were made for undisturbed soil samples taken from each soil horizon, using intact cores (150 mm height and 74 mm diameter) according to the method of Klute [5]. Mineralogical analysis Mineralogical properties of soil samples were determined according to methods described by Whitton and Churchman [18]. Allophane present in soils was determined according to the method of Parfitt [11] and Parfitt and Wilson [12]. Acid-oxalate extractable Si was determined according to the method of Blakemore et.al..[1].


Soil drainage variability The 1:250,000 scale soil map [9], of the study area portrays the 2000 m by 300 m window area as well drained, Kawhatau silt loam (Table 1). A subsequent land resource map at 1:63,360 scale [8] shows the area to be well drained, Kiwitea loam. Senarath [15] has


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explained why neither series name is appropriate for the soils on the Intermediate terrace, and introduced new series. When the authors mapped the area at 1:25,000 scale it appears to encompass three different soil drainage classes (Figure 1a); well drained, Coulter silt loam, moderately well drained, Horoeka silt loam and imperfectly drained, Barrow silt loam (Figure

Figure: 1a Soil drainage class map for the 2000 m by 300 m window area (60 ha) when mapped at

1:25,000 scale.

Figure: 1b Grid sampling design (50 m by 50 m) within blocks A, B and C established within the 2000 m by 300 m large window area on imperfect, moderately well and well drained soil units respectively

mapped at 1:25,000 scale.

Figure: 1c .Soil drainage class maps for the 300m by 250m window (7.5 ha) areas when mapped at 1:10,000 scale.

Figure: 1d Soil drainage class maps for the 300 m by 250m blocks (7.5 ha) when mapped at 1:5,000

scale.


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Table 1:Classification of soil types according to the New Zealand soil classification system and the

USDA Soil Taxonomy.

1a). When selected window areas (blocks A, B and C) are mapped at 1:10,000 scale it becomes apparent that the relatively simple soil drainage pattern represented in the 1:25,000 scale map (Figure 1a) is much more complex (Figure 1cA, 1cB, and 1cC). Instead of a gradation of drainage status from well drained to imperfectly drained soils (Figure 1a), there is a mixture of well, moderately well and imperfectly or poorly drained soils present in each block within close proximity. At least three different soil drainage classes are identified in each of the 300 m by 250 m blocks when mapped at 1:10,000 scale. Each of these blocks comprises only one soil drainage class when mapped at 1:25,000 scale.

When blocks A, B and C are mapped at 1:5000 scale, no new drainage classes are found in any areas except for block B (Figure 1d B), but the drainage class boundaries could be shown more accurately and it is apparent that the distribution of drainage classes is more complex even than that revealed at 1:10,000 scale (Figure, 1d A, 1d B and 1d C). It is evident that when ground observation intensity is increased a more and more variable soil drainage pattern can be observed. Soil-landscape relationship The problem associated with mapping of drainage classes (soil mapping) in this area is that it is difficult to establish an obvious relationship between soil drainage and the topography of the land [15]. The land is essentially flat to gently undulating, with a gentle tilt to the west. There are some instances where soils in local depressions, areas close to water bodies or streams are imperfectly or poorly drained, but that cannot be accepted as a general rule for the entire area. Phosphate retention (P-retention) The relationship between soil drainage and P-retention was investigated in detail using soil drainage information collected from blocks A, B and C on a 50 m interval grid (Figure 1b). The comparison between soil drainage and the P-retention at each observation point indicates that 100% of the poorly drained soils in the study area have low P-retention, whereas 100% of the well drained soils have high P-retention. P-retention in imperfectly drained soils ranges from low through medium to high, but 69% of the observations have medium P-retention. Twenty two percent show high values and only 8% show low values. A majority of the moderately well drained soils have high P-retention (85%), whereas only 15% of the observations have medium P-retention values (Table 2).

Soil type New Zealand Classification [4]

USDA Soil Taxonomy [16]

Kawhatau silt loam Acidic Allophanic Brown Soil Andic Eutrudepts Kiwitea loam Typic Orthic Melanic Soil Eutrudepts Coulter silt loam Typic Orthic Allophanic Soil Dystrudepts Horoeka silt loam Typic Orthic Melanic Soil Andic Eutrudepts Barrow silt loam Mottled Immature Pallic Soil Aqualfs


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Blocks A+B+C

Blocks A+B+C

Total number of observations

Percentage number of observations

Drainage class

LP-ret 0 - 30%

MP-ret 31 – 60%

HP-ret 61 – 100%

LP-ret 0 -30%

MP-ret 31 – 60%

HP-ret 61 – 100%

Poorly drained 9 0 0 100 0 0 Imperfectly drained 4 34 11 82 69.4 22.4 Moderately well drained 0 5 29 0 14.7 85.3 Well drained 0 0 34 0 0 100

Table 2:The relationship between soil drainage classes and P-retention classes. LP-ret = low P-retention; MP-ret = medium P-retention; HP-ret = high P-retention.

From these observations it is evident that poorly drained soils have low P-retention,

imperfectly drained soils have medium P-retention and moderately well drained and well drained soils have high P-retention. Therefore, the variability in P-retention within paddocks can be attributed to the variability of soil drainage. The relationship has been suspected but never before demonstrated for New Zealand soils. Soil drainage, phosphate retention and clay mineralogy The sand fractions of both the well drained and imperfectly drained soils on the intermediate terrace contain volcanic glass (Table 3). But the clay fraction of the well-drained soils contains allophane whereas the clay fraction of the imperfectly drained soils contains no allophane. The P-retention also varies accordingly (Table 3).

Sand fraction Clay fraction Soil Type

Quartz%

Feldspar%

Volcanic.glass%

Kandite %

Allophane %

P-Ret.%

Coulter silt loam

Well drained 41 32 13 16 10 86

Barrow silt loam

Imperfectly drained

54 29 8 31 0 50

Table 3.The relationship between soil drainage, P-retention and clay mineralogy of the topsoil of two

of the soils (Senarath, 2003).

As mentioned in the introduction, Parfitt et al. [10] showed that clay mineralogy is related to soil drainage. It is well known in New Zealand that topsoils dominated by allophane have high P-retention while those dominated by kandite have low P-retention. These results show that the average P-retention of the topsoil is also influenced by the drainage of the whole profile. Soil mapping scale and variability of P-retention The P-retention values of the topsoil samples collected from the study area range from 15% to 86% [15]. These values indicate that there is considerable variability in P-retention within the soils, ranging from low to high [13]. When the area is mapped at 1:25,000 scale, the ranges of P-retention within the imperfectly, moderately well and well drained map units, are 15-72%, 23-86% and 34-86% respectively (Table 4). These figures show that the variability


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within each map unit at this scale has not reduced significantly compared to the total range of P-retention (15 – 86%).

Phosphate Retention Map unit Range Mean STD CV% Mapping scale 1:25,000 Ohakea silt loam (PD) No mapping unit at 1:25,000 scale Barrow silt loam (ImD) 15 - 72 44.1 14.4 32.6 Horoeka silt loam (MWD) 23 - 86 65.1 14.2 21.8 Coulter silt loam (WD) 34 - 86 71 12.4 17.4 Mapping scale 1:10,000 Ohakea silt loam 22 - 44 28 6.7 23.9 Barrow silt loam 15 - 73 46.2 13.5 29.2 Horoeka silt loam 23 - 86 64.8 13.8 21.2 Coulter silt loam 54 - 86 75.9 6.1 8 Mapping scale 1:5,000 Ohakea silt loam 16 - 52 27.5 8.3 22.3 Barrow silt loam 15 - 78 48.5 14 28.8 Horoeka silt loam 32 - 85 67.9 10.4 15.3 Coulter silt loam 54 - 86 76.7 5.9 7.6 Table 4:The variability of P-retention within the soil map units when mapped at three different scales.

(Senarath, 2003). STD = standard deviation; CV% = coefficient of variation; PD = poorly drained; ImD = imperfectly

drained; MWD = moderately well drained; WD = well drained

When the mapping scale is increased from 1:25,000 to 1:10,000 a new poorly drained map unit (Ohakea silt loam) with less variable P-retention values (22 – 44%) is added to the soil map (Table 4). The range of P-retention values in the Barrow (15 – 73%) and Horoeka (23 – 86%) map units changed only slightly. However, there is a considerable change of range in P-retention within the Coulter map unit (from 34 – 86% to 54 – 86%). The co-efficient of variation (CV) indicates that Barrow and Horoeka map units mapped at 1:10,000 scale are slightly less variable compared to that of 1:25,000 scale. CV of P-retention slightly reduced in Barrow (from 32.6 to 29.2%) and Horoeka (from 21.8 to 21.2%) silt loams whereas CV considerably reduced in Coulter silt loams (from 17.4% to 8%) (Table 4).

When the mapping scale increased from 1:10,000 to 1:5,000, the variability of P-retention very slightly decreased in Ohakea , Barrow, Horoeka and Coulter silt loam map units (Table 4).

Therefore map units at all scales have a considerable range in P-retention, but their mean P-retention values increase in an orderly manner with improving drainage.

Soil maps at 1:25,000 scale are of little use in identifying different areas of P-retention in the field. Drainage class maps at 1:10,000 scale can be used to identify low and high P-retention areas successfully, but always some uncertainty exists within moderately well and imperfectly drained areas. Although 1:5000 scale maps are more precise and less variable, there is no advantage in using them instead of 1:10,000 maps when the added cost of producing the maps at the larger scale is taken into account.


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Genesis of soil drainage conditions Soil texture is a property that is initially inherited from its parent material, so variations in soil texture are presumed to reflect variations in initial deposition overprinted by changes due to weathering.

The slight textural variations in the parent material probably effected slight variations in soil structural development. In the soils of the study area, silt loam soil textures are associated with nutty structure while silty clay loam; clay loam or clay soil textures are associated with blocky structures (Table 5 and 6). Horizon Depth (cm) Field -texture Structure Macro-

Porosity (%) Ksat

(mm hr –1)

Ap 0-20 silt loam moderate fine to medium nutty 6 to 7 8

Bw1 20-65 silt loam moderate fine to medium nutty 11 8

Bw2 65-95 silt loam moderate fine to medium nutty and moderate medium blocky

8 4.3

2Ab 95-125 clay loam moderate medium to coarse blocky

5 4.6

Table 5:The physical properties of a representative profile of well drained Coulter silt loam related to

water movement in soil (Senarath, 2003).

Horizon depth (cm)

Field-texture Structure Macro- porosity (%)

Ksat (mm hr –1)

Ap 0-21 silt loam Strong fine to medium nutty 4 to 8 6.4 to 14

Bg1 21-34 silty clay loam strong very fine, fine and medium nutty and moderate medium blocky

12 0.9

Bg2 34-65 fine sandy clay loam strong medium to coarse nutty

9 7.6

Bg3 65-82 clay loam moderate medium to coarse blocky

3 0.8

Table 6:The physical properties of a representative profile of imperfectly drained Barrow silt loam

related to water movement in soil (Senarath, 2003). It is hypothesised that the differences in soil structure largely caused the differences in drainage status. The hydraulic conductivity of a soil is directly related to its porosity, more importantly the macro porosity. The shape and the size of the soil structural units has a noticeable affect on the space between them [2,3] Blocky structure is more closely fitting than nutty structure hence water can move more readily along structural faces of soils having nutty structure.

Saturated hydraulic conductivity (Ksat) values in the Bg1 and Bg3 horizons (0.9 and 0.8 mm/hr) are very slow in the imperfectly drained Barrow soils (Table 6). This impedes drainage in the whole profile. K sat values for the other two horizons are approximately same as that of the Coulter soil (Table 5). Ksat values range from moderately slow to very slow in soils having blocky structures [3] Although macro porosity is more or less similar to that of Coulter soils (Table 5), they may not be interconnected within soil aggregates, because


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blocky structure is rather compact compared to nutty structure [3]. Therefore, water moves very slowly within Barrow soils, creating imperfect drainage conditions.

The soil textures of Coulter soils are silt loam and the structures are nutty. The structural units are not closely packed as explained above. Therefore, water can move through soils more rapidly and hence soils are well drained.

From these observations it is possible that the drainage variability of soils within short distances on the intermediate terrace may be associated with the slight textural variations of the original alluvial parent materials from which the soils are formed, and the resulting development of contrasting soil structure. These subtle changes in texture have been subsequently masked by weathering including clay formation and changes in clay mineralogy.

Soil drainage conditions influence clay mineralogy. According to Parfitt et al. [10] weathering of rhyolitic tephra is controlled by Si in soil solution. When Si concentration in the soil solution is low (possibly < 10 µg cm-3), due to leaching, allophane is formed from volcanic glass whereas if Si concentration is high (possibly >10 µg cm-3), in the soil solution due to impeded drainage conditions, halloysite is formed. The presence of allophane in the clay fraction of Coulter silt loam can be attributed to weathering of volcanic glass under well-drained conditions. Under well-drained conditions Si is leached from the profile and allophane forms. Imperfectly drained Barrow silt loam contains no allophane in the clay fraction due to Si not being leached from the profile, and kandite minerals (kaolinite + halloysite) form instead.

The variability in P-retention within a paddock should have a significant influence on the amount of phosphate fertilizer applied by farmers. If fertilised at a rate suited to the low P-retention soil, then the high P-retention soils in the paddock will be deficient in P and will have suboptimal productivity. If land is fertilised according to the high P-retention soil, then surplus P will be applied to the low P-retention soil which is uneconomic and may increase the rate of loss of P to waterways. Thus it is clear from both an economic and an environmental point of view that soils within different P-retention classes should be treated differently. Therefore, identification of low, medium and high P-retention areas in the landscape and managing them accordingly is important. Variable rate of application of phosphate fertiliser through precision agriculture is an obvious solution, if the areas of low, intermediate and high P-retention in a paddock can be identified. This is most cheaply and efficiently achieved by soil survey recognising drainage classes.

CONCLUSIONS

• Soil drainage properties in the study area vary from well drained through moderately well drained to imperfectly drained and poorly drained with in the paddock scale.

• The poor relationship between soil drainage and the topography of the landscape poses difficulties for conventional soil survey.

• There is a strong relationship between soil drainage, phosphate retention and clay mineralogy in soils developed from tephra mixed parent materials. Well drained soils have high P-retention and the clay fraction contains allophane whereas poorly drained soils have low P-retention and the clay fraction contains no allophane but mainly kandite.

• The positive relationship between soil drainage and P-retention can be used to identify different P-retention areas on soil maps.

• 1:10,000 is the optimal soil mapping scale for practical farm planning in this area.


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• Short distance drainage variability has a relationship to the textural variations of the original alluvial parent material which gives rise to the formation of different soil structures and different pathways of weathering. This in turn influences the hydraulic conductivity of the soil and results in variable drainage conditions and different P-retention values.

REFERENCES [1] L.C.Blakemore, P.L.Searle, B.K.Daly. Methods for chemical analysis of soils, New Zealand Soil Bureau Scientific Report no.80, .New Zealand Society of Soil Science, Lower Hutt, New Zealand, (1987). [2] E.Griffiths, T.H.Webb, J.P.C.Watt, P.L.Singleton. “Development of soil morphological descriptors to improve field estimation of hydraulic conductivity”, Australian Journal of Soil Research, 37, PP. 971-982, (1999). [3] E.Griffiths. Interpretation of soil morphology for assessing moisture movement and storage, New Zealand Soil Bureau Scientific Report, 74, (1985). [4] A.E.Hewitt. New Zealand Soil Classification, DSIR, Land Resources Scientific Report No.19,(1992). [5] A.Klute. Methods of soil analysis part 1, American Society of Agronomy Inc., Soil Science Society of America, Inc., PP. 694-696, (1986). [6] J.D.G Milne, B.Clayden, P.L.Singleton, A.D.Wilson. Soil Description Handbook, Lincoln, Canterbury, New Zealand, (1995). [7] New Zealand Meteorological Service. Summaries of climatological observations to 1980, New Zealand Meteorological Service Miscellaneous Publication 177, Ministry of Transport, (1983). [8] New Zealand Land Resource Inventory Work sheet, Feilding N.144. The National Water and Soil Conservation Organization, Water and Soil Division, Ministry of Works and Development, (1979). [9] New Zealand Soil Bureau General survey of the soils of North Island, New Zealand, New Zealand Soil Bureau Bulletin 5, (1954). [10] R.L.Parfitt, M.Saigusa, D.N.Eden. “Soil development processes in an Aqualf-Ochrept sequence from loess with admixtures of tephra”, New Zealand .Journal of Soil Science, 35, PP. 625-640,.(1984). [11] R.L.Parfitt. Towards understanding soil mineralogy III, Notes on allophane. New Zealand Soil Bureau Laboratory Report CM 10, (1986). [12] R.L.Parfitt, A.D.Wilson. Estimation of allophane and halloysite in three sequences of volcanic soils, New Zealand, Catena Supplement 7, PP. 1-8, (1985). [13] W.M.H.Saunders. “Phosphate retention by New Zealand soils and its relationship to free sesquioxides, organic matter and other soil properties”, New Zealand Journal of Agricultural Research, 8, PP. 30-57, (1965). [14] A.Senarath, G.Arnold, A.S.Palmer, R.W.Tillman, M.P.Tuohy. Use of geostatistics in soil mapping for precision agricultural management, In precision tools for improving land management (Eds LD Currie and P Loganathan).Occasional report No.14.Fertiliser and Lime Research Centre, Massey University, Palmerston North, PP. 161-171, (2001). [15] A.Senarath. Soil spatial variability in northern Manawatu, New Zealand, Unpublished PhD thesis, Massey University, Palmerston North, New Zealand, (2003). [16] Soil Survey Staff Soil Taxonomy. A Basic System of Soil Classification for Making and Interpreting Soil Surveys., United State Department of Agriculture, Agriculture Handbook Number 436, Washington D.C., (1999). [17] N.H.Taylor, I.Pohlen. Classification of New Zealand Soils, In Soils of New Zealand, Part 1 (Ed Jean Luke) PP. 15-46, New Zealand Soil Bureau Bulletin. 26(1), (1968). [18] J.S.Whitton, G.J.Churchman. Standard methods for mineral analysis of soil survey samples for characterization and classification in New Zealand, New Zealand Soil Bureau Scientific Report 79, (1987).

ACKNOWLEDGEMENTS

The authors are grateful to the technical staff of the Fertilizer and Lime Research Centre, Massey University, Palmerston North particularly Ian Furkert, Bob Toes, James Hanly and Lance Currie for help in the field and laboratory experiments and farmers of the Kiwitea study area for their co-operation during the soil survey and field experiments.


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WORKSHOP Theme: Soil survey and inventory techniques

Convenors: P. Finke, M. Van Meirvenne, R. Goossens

CONCLUSIONS This workshop focused on current and developing techniques for soil and terrain inventory to meet requests for the construction, updating and upgrading of soil information systems. The papers were grouped into three perspectives:

1. Soil (attribute) mapping at regional and national scales

The keynote by Finke addressed the quantitative soil mapping methods coined as digital soil mapping methods. Based on the overview it was concluded that these methods have a great potential for mapping soil types and soil attributes in scarcely visited areas if ancillary data like DTM and remote sensing images are available. As these methods give an indication of the precision of their output, they allow for a motivated choice on the positioning of future field work. Because of their complexity, applucation of these methods require an expert. It was stressed that the resulting maps and data bases are as reliable as the (amount and quality) of the data used as input.

The paper by Wandahwa et al. treated the issue of how to obtain soil characteristics for land evaluation in a case study from Kenyia. A comparison was made between the approaches “calculate first, interpolate later” and its opposite. It was found that soil characteristics respond differently when subjected to interpolation. Conclusion was, that a combination of landscape and soil characteristic maps derived from interpolation gave better distribution of suitability classes than the approach based directly on soil units. The study successfully demonstrates the potential of using GPS and GIS for land evaluation.

2. Gis and remote sensing

The keynote by Goossens highlighted a number of important developments in remote sensing for data users worldwide. It was concluded that in the near future, 3-D visualisation of remote sensing images will become accessible since data and techniques are available and costs are low (e.g. the Corona images at $18 / 14*188 km). Another trend is that ground resolutions are becoming increasingly finer (± 1.2-1.8 m to near the physical threshold of 30 cm). Thirdly, the emergence of hyperspectral imagery (from the Chris-Proba satellite) was mentioned.

The paper by El-Badawi on mapping soils in southeastern Egypt in difficult field circumstances demonstrated that aerial photo interpretation in combination with remote sensing is a powerful method to make a physiographic soil map.


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3. Soil sampling at field scale

The keynote by Van Meivenne addressed some developments in soil sampling and proximal sensing with applications in precision agriculture. The measurement precision of position (by GPS) and crop yield has greatly improved over recent years, is operational and commercially available. One bottleneck is the characterization of the within field variability of crop controlling variables, especially soil. Usage of soil sensors based on the principle of electromagnetic induction (EMI) offers a promising alternative to detailed soil maping and intensive sampling schemes. In the context of precision agriculture, it was concluded, that the within-field soil variability is often underestimated, especially of deeper soil horizons. There is a potential for improved crop management with a reduced environmental pressure.

Workshop IC-PLR 2006 – Theme E – Soil processes and analytical techniques

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WORKSHOP THEME E – SOIL PROCESSES AND ANALYTICAL TECHNIQUES

Sub-theme : Development in soil genesis and mineralogy Van Ranst E., Mees F.

Paper/poster : Impact of acid deposition on cation leaching from Mt. Talang airfall ash – D. Fiantis, Nelson, E. Van Ranst, J. Shamshuddin Paper/poster : Stone lines and weathering profiles of ferrallitic soils in Northeastern Argentina – Morrás H., Moretti L., Piccolo G., Zech, W. Paper/poster : Pedogenesis along a hillslope traverse in the upper Afram basin, Ghana – T. Adjei-Gyapong, E. Boateng, C. Dela Dedzoe, W.R. Effland, M.D. Mays, J.K. Seneya Paper/poster : Influence of titanomagnetite on dithionite-citrate-bicarbonate (DCB) and oxalate extractions in weathered dolerite – C.G. Algoe, E. Van Ranst, G. Stoops

Sub-theme : Developments in soil micromorphology G. Stoops, V. Marcelino, F. Mees

Paper/poster : Spheroidal weathering of dolerite in Suriname : evidence from physical, chemical and mineralogical data – C.G. Algoe, E. Van Ranst, G. Stoops Paper/poster : Micromorphological characteristics of andisols in West Java, Indonesia – Mahfud Arifin, Rina Devnita Paper/poster : Micromorphological features of some soils in the Afram plains (Ghana, West Africa) – M.D. Mays, W.R. Effland, T. Adjei-Gyapong, C.D. Dedzoe, E. Boateng

Conclusions


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Sub-theme : DEVELOPMENTS IN SOIL GENESIS AND MINERALOGY

Overview of latest research in soil genesis and soil mineralogy conducted at the Department of Geology and Soil Science

Van Ranst E. & Mees F.

Department of Geology and Soil Science, Ghent University, Gent, Belgium

The research related to mineral weathering/formation and soil processes is concentrated within three big research programs that are still going on: (1) Interaction between atmospheric deposition, soil acidification, and mineral weathering, using soil solution analyses, laboratory and field experiments; (2) Mineralogy and chemistry of variable charge soils to determine their constraints and management options; and (3) Formation of authigenic minerals in atmospheric conditions, studied by means of an analysis of regional variations. In the first research programme a fortnightly monitoring of the chemical composition of the bulk precipitation, throughfall, humus water and soil water at three depths in 6 forest ecosystems in Flanders (N-Belgium) is carried out from 1993 onwards. The selected forest plots, with soils ranging from sand to silt of Pleistocene origin, belong to the forest condition monitoring programme that started in Flanders in 1987, as part of the ‘International Co-operative Programme (ICP) on the Assessment and Monitoring of Air Pollution Effects on Forests’ under the Convention of Long-range transboundary Air pollution (UN/ECE) and the European Scheme on the Protection of Forests against Atmospheric Pollution. Based on chemical and mineralogical analyses a methodology to assess the total acid-neutralizing capacity (ANC) of forest soils has been developed and applied on the forest floor and the mineral topsoil in the 6 forest ecosystems. As the total ANC is clearly related to the soil texture class, the existing soil maps are ideal documents to assess the sensitivity of the soils for acidic pollution. Considering the average acid loads on the plots a danger for further aluminization of the organic complexes would be real. Although since these analyses did not consider the neutralizing effect occurring during turn-over of organic matter, the actual outlook is probably less dramatic. The chemical analyses of the monitoring programme proved that previous and present weathering is predominantly due to synthesis of HNO3 out of organic remains and subsequent reaction with silicates with release of Al3+ and acidity. The influence of the synthesis of HNO3 on the nutrient replenishment in these forest soils has been studied as well. The weathering of soil minerals was studied further in detail using different approaches(batch-, column and field experiments). The laboratory experiments, performed under different conditions (acid type and strength, temperature, solid:liquid ratio, etc.) served to better understand the ability and mechanisms of different minerals (hectorite, biotite, vermiculite, etc.) to neutralize acidity. The field experiments, based on the test mineral technique, were set up under the hypothesis that a residence of the minerals (trioctahedral vermiculite and glauconite) in the soil during 4 years, would result in the extraction of quantiable amounts of structural elements, rendering it possible to deduct the in situ weathering rates. The


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test-mineral(vermiculite) technique was used to distinguish simple acidolysis from acido-complexolysis in a Podzol profile.

In the second research programme a great deal of time and effort is spent to study the chemical behaviour of variable charge minerals and soils, mainly highly weathered soils (Oxisols and Ultisols) of the tropics and volcanic ash soils (Andisols), to elucidate different aspects of their behaviour. Variable charge soils (VCS) are heterogenous charge systems. The coexistence and interactions of soil particles and colloids with net opposite surface charges confer a quite interesting, and much more complex pattern with respect to soil physical and chemical behaviour compared to homogeneously charged soil systems of temperate regions. Different methods (NH4OAc, Charge Fingerprint, Compulsive Exchange) to determine the electrochemical properties, in particular ion exchange capacities, have been tested to assess variation in exchange capacity with respect to the composition of the colloid fraction. The application of Ca-silicate slags and calc-alkaline pyroclastic materials has been used to increase the cation exchange capacity (CEC) of highly weathered VCS. Research using other natural amendments on sandy soils is going on at moment. Special emphasis is given to the study of Andisols on volcanic ash, mainly from the Indonesian islands, Java and Sumatra. The physico-chemical and mineralogical properties of ash soils along the Sunda arc were characterized in order to assess the influence of the change of parent material on differing soil characteristics and on surface reactivity with emphasis on short-range-order mineral constituents and active Al and Fe compounds on fluoride and phosphate sorption. This study provided a scientific basis for (1) localizing the soils which are less likely to be deficient in Ca and Mg under yearly application of acidifying nitrogenous fertilizers and (2) proposing separate regions in terms of P-fertilizer strategy for sustainable crop production.

The aim of the third research programme is to contribute to a fundamental understanding of the factors and mechanisms that control the formation of authigenic minerals at earth-surface conditions. Specific objectives are (i) an evaluation of the conditions of formation of authigenic minerals for individual lake basins in selected study areas, and (ii) the creation of a regional synthesis for each study area, relating variations in the nature and mode of occurrence of authigenic minerals to regional patterns and factors. One of both regions selected for this research project is a zone with temporary and dry salt lakes in a karst area of the Ebro Basin in northern Spain (Los Monegros), with e.g. abundant gypsum, magnesite, halite and Mg-bearing sulfates. The second study area is a region with dry lake basins in the southwestern Kalahari, Namibia, which contain smectite, sepiolite, dolomite, thenardite and various other authigenic minerals in two previously studied basins. The lakes in both regions represent a series of mainly groundwater-fed flow-through basins. Both study areas contain a group of about 20 isolated lake basins, characterised by (i) the presence of authigenic minerals belonging to different mineral groups, (ii) differences in mineral associations between the basins, and (iii) important variations within the individual basins, which represent a set of characterstics that renders the study areas ideally suited for investigating the conditions of authigenic mineral formation. These conditions will initially be determined for each individual lake basins, considering various modes of mineral formation (synsedimentary vs pedogenic, direct precipitation vs transformation) and the processes and factors that control mineral distribution patterns (e.g. lateral and vertical groundwater movement, flooding, groundwater composition, groundmass characteristics, porosity, lithological discontinuities). Subsequently, a regional synthesis for each study area will be made, allowing the development of a model for authigenic mineral formation, in relation to the evolution of groundwater composition within the region, modified by local factors. Samples were collected in both study areas in the


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course of 2005. Analysis of the available samples is in progress, using X-ray diffraction methods, thin section observations and chemical analyses.

REFERENCES

[123] D. Fiantis, E. Van Ranst, J. Shamshuddin, I. Fauziah, S. Zauyah. "Effect of calcium silicate and superphosphate application on surface charge properties of volcanic soils from west Sumatra, Indonesia". Comm. Soil Sci. Plant Anal., 33: 1887-1900, (2002). [124] P. Kanyankogote, E. Van Ranst, A. Verdoodt, G. Baert. "Effet de la lave trachybasaltique broyée sur les propriétés chimiques de sols de climat tropical humide", Etude et Gestion des Sols, 12(4):301-311, (2005). [125] O.T. Mandiringana, P.N.S. Mnkeni, Z. Mkile, W. Van Averbeke, E. Van Ranst, H. Verplancke. "Mineralogy and fertility status of selected soils of the Eastern Cape Province, South Africa". Comm. In : Soil Science and Plant Analysis, 36:2431-2446, (2005). [126] F. Mees. “Salt mineral distribution patterns in soils of the Otjomongwa pan, Namibia”. Catena, 54:425-437, (2003). [127] F. Mees, M. De Dapper. “Vertical variations in bassanite distribution patterns in near-surface sediments, southern Egypt”. Sedimentary Geology, 181:225-229, (2005). [128] F. Mees, A. Singer. “Surface crusts on soils/sediments of the southern Aral Sea basin, Uzbekistan”. Geoderma, in press. [129] F. Mees, G. Stoops, E. Van Ranst, R. Paepe, E. Van Overloop. "The nature of zeolite occurrences in deposits of the Olduvai Basin, northern Tanzania", Clays and Clay Minerals, 53(6) : 659-673, (2005). [130] J. Neirynck, E. Van Ranst, P. Roskams, N. Lust. "Impact of decreasing throughfall depositions on soil solution chemistry at coniferous monitoring sites in northern Belgium", Forest Ecology & Management, 160:127-142, (2002). [131] N.P. Qafoku, E. Van Ranst, A.Noble, G. Baert. "Mineralogy and chemistry of variable charge soils. In : The Encyclopedia of Soil Science (Ed. : R. Lal), M. Dekker, Inc. (ISBN:0-8247-0846-6)", Online Published:1-8, (2003). [132] N.P. Qafoku, E. Van Ranst, A.Noble, G. Baert. "Variable charge soils : their mineralogy, chemistry and management", Advances in Agronomy, 84:159-215, (2004). [133] G. Stoops, E.Van Ranst, K. Verbeek. "Pedology of soils within the spray zone of the Victoria Falls (Zimbabwe)", Catena, 46:63-83, (2001). [134] E. Van Ranst, F. De Coninck. "Evaluation of ferrolysis in soil formation", European Journal of Soil Science, 53:513-519, (2002). [135] E. Van Ranst, F. De Coninck. "Synthesis of HNO3 out of organic matter and its influence on weathering. In : Soil Science : Confronting New Realities in the 21st Century", Transactions 17e World Congress of Soil Science (CD-Rom), Bangkok, Thailand : 285, 1-10, (2002). [136] E. Van Ranst, F. De Coninck, K. Van Rompaey. "Synthesis of HNO3 from organic matter and its influence on nutrient replenishment in forest soils", Environmental Monitoring and Assessment, 98:409-420, (2004). [137] Van Ranst, E., De Coninck, F., Roskams, P., Vindevogel, N. "Acid-neutralizing capacity of forest floor and mineral topsoil in Flemish forests (North Belgium)", Forest Ecology and Management, 166:45-53, (2002). [138] E. Van Ranst, S.R. Utami, J. Shamshuddin. "Andisols on volcanic ash from Java Island, Indonesia : Physico-chemical properties and classification", Soil Science, 167:68-79, (2002). [139] E. Van Ranst, S.R. Utami, J. Vanderdeelen, J. Shamshuddin. "Surface reactivity of Andisols on volcanic ash along the Sunda arc crossing Java Island, Indonesia", Geoderma, 123:193-203, (2004). [140] K. Van Rompaey, E. Van Ranst, F. De Coninck, N. Vindevogel. "Dissolution characteristics of hectorite in inorganic acids". Applied Clay Science, 21 : 241-256, (2002). [141] K. Van Rompaey, E. Van Ranst, A. Verdoodt, F. De Coninck, 2006. Use of the test-mineral technique to distinguish simple acidolysis from acido-complexolysis in a Podzol profile. Geoderma (in press).


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IMPACT OF ACID DEPOSITION ON CATION LEACHING FROM MT. TALANG AIRFALL ASH

Fiantis, D., Nelson1, E. Van Ranst2 and J. Shamshuddin3

Department of Soil Science, Faculty of Agriculture University of Andala, Kampus Unand Limau Manis, Padang

25163, Indonesia; 1Department of Crop Estate, Polytechnic of Agriculture University of Andalas, Kampus Politani Tanjung Pati, 50 Kota, Sumbar, Indonesia; 2 Department of Geology and Soil Science, Laboratory of Soil Science,

Ghent University, Krijgslaan 281/S1, B- 9000 Gent, Belgium; 3Department of Land Management, Faculty of Agriculture, Universiti Putra Malaysia, Serdang 43400 Selangor, Malaysia

Abstract An evaluation of the response of airfall ash from Mt. Talang on acid deposition and weathering rates was studied by using a controlled laboratory leaching experiment. Airfall ash from Mt. Talang was collected a few days after it was blown up by a phreatic eruption at the upper NE side of the volcano. The ash samples were leached with de-ionized water and nitric acid 0.05 M (pH 2) for seven weeks. Solutions leachates were collected after 2 and 48 hours, and after 7, 14, 21, 28, 35 and 42 days for chemical analyses. Measured cations were Ca and Fe. Two sets of sample containers were constructed, namely (1) successive incubation and (2) separated incubation. The successive incubation set up consisted of the addition of new solutions to the containers after each collection of leachate to simulate the leaching conditions in the field. The containers for separate incubation were set up according to the respective time and discharge afterward. Acidic input increased iron leaching; Fe was increased by 1.75-folds in successive incubation and 47 times in separated incubation, while Ca was elevated 1.5 times in successive mode and 4-folds in separate set. The Fe release was increased sharply after 3 weeks and started to level off after 6 weeks. Meanwhile, Ca was released sharply after 1 week and started to level off after 2 weeks. In total, 0.08 to 0.13 % of iron was released after addition of de-ionized water in successive mode and 0.05 – 0.08% in separate mode. Treating the airfall ash with nitric acid yielded more Fe, in the range of 0.34 – 0.37% and 1.41 to 2.42 %, in successive and separate modes respectively. Addition of de-ionized water resulted in higher concentration of Ca in contrast to addition of nitric acid. The value of Ca between 2.54 to 6.64 % was obtained in the reconstructed field condition and between 6.04 – 6.84 % in separated sets. The total concentration of calcium after applying nitric acid was between 2.06 – 3.03 %, and 5.10 – 5.91 %.

1. INTRODUCTION

Owing to its position in the mid-western part of the Barisan Mountain Range of Sumatra, to its shape and size and to its activity, Mt. Talang is one of the most important and active volcano in Sumatra. Mt. Talang is a strato volcano, formed of lava flows alternating with pyroclastic materials, emitted from various eruptive cases over the centuries. Summit elevation of Mt. Talang reaches 2896 m above sea level and located at 100° 40' 41.9304" E and 0° 58' 40.8072" S


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and the distance from the city of Padang to Talang is about 35 km. (Figure 1). Historical eruptions from Talang volcano have occurred many times from flank vents and most of the eruptions are moderate in size. On April 12th, 2005 an explosion was heard 25 km from Talang and grayish ash was emitted to the sky. Ash fell to the south and eastern-northern slope of Mt. Talang.

Volcanic ash, the smallest tephra fragments, is highly disruptive to economic activity because it covers just about everything, infiltrates most openings, and is highly abrasive. On the other hand, from these ashes of devastation arise some of the most productive soils in the world with the capacity to sustain high human population densities.

Figure 1. Satellite image of Mt. Talang and surrounding area Airfall volcanic ash has fine particle size, vesicular nature with high surface area, high porosity and permeability enhance weathering rates [4]. Rapid weathering of the ash liberated cations through surface exchange with aqueous hydrogen ions [13]. Volcanic ash is believed to release elements faster than other primary or secondary crystalline minerals [11]. The primary proton donors in the weathering of airfall ash are both acidic aerosols, carbonic and organic acids [3]. Proton donors or acids affect weathering by providing H+ which may attack rocks or minerals [12] The acidic aerosols, such as sulfuric acid (H2SO4), hydrochloric acid (HCl), fluoric acid (HF) and nitric acid (HNO3), which come from eruption plume during the eruption while the carbonic and organic acids derived from biota [3].

Both mineral and organic acids play an important role in soil environments and provided evidence that weathering of rocks and minerals are facilitated by these acids through


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organometallic complex formation or through metal chelation process [9]. Furthermore, [7] found out that the ratio between anion or cation released over protons-added from organic acids are greater than those from mineral acids. The ability of organic acids to complex metals is more important than the strength of mineral acids that have lower dissociation constant (pK1). Mineral acids are considered as strong noncomplex forming acids [12].

Solutions leached from the tephra layer indicate incongruent dissolution resulting in formation of a cation-depleted, silica-rich leached layer on glass and mineral surfaces [4] As reported by [1] the initial lechates from the 1980 eruption of Mt. St. Helens composed primarily of base cations (Ca2+ > Na+ >> Mg2+ > K+) and strong acid anions (SO4

2- >> Cl- > F- >> NO3-). The rate of aluminum release from colored volcanic glass in order of 10-12 mol g-1 s-1 at pH 4.00. Colored volcanic glass release cations 1.5 times greater than non-colored glass, reflecting its lower stability [11]. As weathering progresses, dissolution rates are controlled by surface dissolution with concurrent diffusion of cations through the leached layer near the glass surface. A shift from incongruent to congruent dissolution presumably occurs when the increase in the diffusion length equals the rate of retreat of the solution-solid interface [14].

The primary objective of this study was to provide a direct measurement of acid dissolution from unweathered airfall ash deposits in a warm, humid climate regime. The questions addressed in this research concerning the initial stages of volcanic ash weathering including: (1) what are the initial cations releases from fresh volcanic ash; (2) does the volcanic ash dissolve stoichiometrically or incongruently? To answer these questions fresh airfall ash of Mt. Talang were subjected into laboratory dissolution experiment for 7 weeks with nitric acid, which is considered as strong mineral acid, de-ionized water as weak noncomplex acid and acetic acid of the organic acid. Lechates from ash deposits were collected weekly for chemical analysis and are used to calculate elemental fluxes and weathering rates of airfall ash.

2. MATERALS AND METHODS 2.1. Study area Mt. Talang is considered as type-A volcano and has been in continuous eruption for decades either from flank vent, radial fissures or summit of volcano. The area affected by volcanic activity covers at about 42103.6 ha and mostly from Quaternary age. The recent eruption of April 12, 2005, blew away airfall ash tephra over portions of Solok District of West Sumatra, Indonesia. The maximum thickness of ash was 5 cm in the upper NE slope of Mt. Talang and the minimum thickness of 1 mm blanketed the area in the foot slope. 2.2. Collection and Analysis of Ash Lechates Airfall ash was collected from the affected areas of tea-plantation shortly after the April 12th

2005 eruption. The ash was collected prior to any rainfall and sealed in watertight containers until it was used for mineralogical and chemical analysis as well as applied it for the dissolution experiments. The airfall ash fractions were analyzed in grain mounts with a polarizing microscope. Elemental analyses of airfall ash were done by X-ray fluorescence spectrometry after ignition at 11000C.


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The dissolution experiment was carried out as follows. One gram of airfall ash was placed in each 250 ml plastic container with a stopper, and 200 ml of de-ionized water and nitric acid 0.05 M (pH 2) for seven weeks at room temperature. Mixing of the solution was made by shaking the containers once a day for 60 minutes during the dissolution. The solution was separated after 1 hour, 24 hours, and after 2, 7, 14, 21, 28, 35 and 42 days. Chemical analysis of lechates were conducted to determine the pH, cations (Ca and Fe) were measured by AAS.

Two sets of sample containers were constructed, namely (1) successive incubation and (2) separated incubation. The successive incubation set up consisted of the addition of new solutions to the containers after each collection of lechates to simulate the leaching conditions in the field. The containers for separate incubation was set up according to the respective time and discharge afterward. All values represent the mean of duplicate analyses.

3. RESULTS AND DISCUSSION 3.1. Mineralogical Characteristics of Mt. Talang Airfall Ash The mineralogical composition of the ash consisted of noncrystalline and crystalline components. The noncrystalline mineral is volcanic glass (30%) and the rest are crystalline minerals. The glassy materials of volcanic glass appear optically isotropic under crossed polarizer microscope and usually present as clusters of small particles with vesicular morphology. Volcanic glass, as it was believed [2], is the most weatherable components as a result of its amorphous nature in volcanic deposits. Weathering of volcanic glass can be described in term of a combination of parabolic and linear kinetics, reflecting the hydration of glass and the formation of secondary clay minerals. Furthermore they stated that the mineralogical composition of volcanic ash varies widely as a function of particle-size and that volcanic glass increases in relative proportion to plagioclase as the particle size decreases.

The crystalline minerals include andesine (1%), quartz (<1%), labradorite (42 – 46%) and rock fragments (11 - 16%), can be grouped as light minerals, while heavy minerals of airfall ash of Mt. Talang consist of hypersthene (6 – 11%), augite (2 – 3%), hornblende (1 – 2%) and opaque mineral (1-2%). The presence of these minerals confirms that the volcanic materials are of basaltic andesitic composition. Similar findings were also reported by [5] that the primary minerals composition of volcanic ash of Mt. Marapi which were ejected in 1996. The above findings are in accordance with the report of Dahlgren et al. (1993) that 70 to 95% of the primary minerals in volcanic soils are light minerals and heavy minerals comprise only small amount and heavy minerals preferentially are deposited nearest the volcanic vent.

Volcano-derived ejecta, including both pyroclastic fall and flow materials such as volcanic ash, pumice, and scoria are referred to collectively as pyroclastic materials. According to the size of the pyroclastic, they can be divided further into the size of silt (< 0.26 mm), sand (0.25 – 4 mm), lapilli or ‘little stone’ (4 – 32 cm) and bomb (> 32 mm). As it is, the mineralogical composition of volcanic ash varies according to rock types. Ash of rhyolite, dacite or andesite composition is dominated by noncolored volcanic glass with lesser amounts of plagioclase, pyroxenes, and ferromagnesian minerals. On the other hand, volcanic ash having the composition of basalt and basaltic andesite composition is dominated by colored volcanic glass accompanied by plagioclase, olivine, pyroxenes and ferromagnesian minerals [2].


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3.2. Elemental Composition of Mt. Talang Airfall Ash Air fall ash, as a parent material of soils, controls soil formation more than any other parent materials. The behavior of chemical elements in airfall ash can be inferred by comparing the total elemental analysis. The elemental composition of the airfall ash is depicted in Tables 1. Each element is expressed in oxide percentage on the basis of an oven-dried weight (1050C). Based on the silica content of 54%, the airfall ash of Mt. Talang can be considered as basaltic-andesitic type. A classification of volcanic ash was proposed by [10] into five groups based on the silica (SiO2) content: rhyolite (100-70%); dacite (70-62%); andesite (62-58%); basaltic andesitic (58-53.5%) and basalt (53.5-45%). The result of this study is different with the report of [5] that volcanic ash of Mt. Marapi, located 140 km north of Mt. Talang, are considered as andesitic type since the silica contents was higher 15%. Japanese soil scientists stated that silica content of volcanic ash from Japan in the range of 48 – 73% and exists strong correlation between silica content and most of chemical elements except for K [15]. Similar findings were also reported for volcanic ash originating from New Zealand [8]. SiO2 is regarded as one of the immobile element found in tephra as well as Al2O3 and Fe2O3 [2].

Composition (%) Element Fresh Oxalate-treated SiO2 54.37 64.36 Al2O3 18.33 15.00 Fe2O3 4.82 5.95 CaO 4.19 4.25 MgO 1.33 1.42 K2O 1.15 1.49 Na2O 0.61 0.67 LOI 4.2 4.88

Table 1: Contents of major elements in fresh and oxalate-treated

airfall ash of Mt. Talang The molar ratio between SiO2/Al2O3 is 6.14 in fresh volcanic ash and decrease into 4.29

in oxalate-treated ash of Mt. Talang. The down shift value of the molar ratio is assumed to be largely due to presence of the amorphous and noncrystalline components of volcanic materials. This is in accordance with the report else where in Japan [15]. Meanwhile the SiO2, Al2O3 and Fe2O3 are originated from both volcanic glass and plagioclase while Fe2O3 can be found also in mafic minerals [10].

The alkaline earth elements (CaO and MgO) found in the studied ash are higher then the alkaline elements (K2O and Na2O). The higher contents of CaO and MgO because the samples are very new and is not subjected to any weathering process yet. These data are in line with those obtained by [10] that CaO and Na2O are originated from volcanic glass and plagioclase, MgO is from mafic mineral and K2O mainly occurs in volcanic glass. They added that proportion of CaO, Na2O and MgO were decreased as weatherings proceed contrary to K2O content. Both CaO and Na2O have high solubility and easily lost by leaching. The mobility sequence found in volcanic ash parent materials are in order: CaO, Na2O >SiO2 >MgO > Al2O3, Fe2O3, K2O [7, 10, 2].


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Removal of the amorphous constituents by using oxalate increased the concentration of all elements except for the aluminum oxide concentration, which is down from 18% to 15%. Although SiO2 concentration is exceeding the requirement for basaltic andesitic, it is our belief that treated the samples with chemical solutions does not necessary change the rock type of the airfall ash from basaltic andesitic into dacitic. The ammonium oxalate acid dissolution is intended to remove the amorphous fraction that is coating some of the crystalline particles. Unfortunately, we do not have any value of dissolved cations from the lechates to be reported and compared with the concentration of cations from ash-residue or solid components after ignition to 11000 C. 3.3. Dissolution Rate of Calcium The solubility of solid-phase of calcium upon leaching with different acids in successive and separate mode incubation is shown in Table 2 and 3. Different results obtained from the two mode of incubation. Ca obtained from the successive mode, reflecting the leaching conditions in the field, are lower than the separated incubation mode. Comparable results were also reported by [3] maximum solute concentrations in solutions draining from tephra layer during rainy season during initial weathering study (12 months) and there was a distinct decrease in the annual concentrations of several solutes such as calcium, sodium, silicon and bicarbonate after 4 years of study.

After 2 h After 24 hAfter 1 w After 2 w After 3 w After 4 w After 5 w After 6 wH2O 13.83 18.82 102.47 57.40 13.18 31.89 15.56 0.39

Acetic acid 19.72 20.48 229.17 85.46 28.49 25.09 39.86 0.52HNO2 17.38 13.35 161.99 30.19 4.68 15.73 16.25 0.27

NH4 OACe 14.02 14.78 339.71 161.14 60.80 23.38 65.56 0.61

H2O 18.05 20.08 451.96 92.26 31.04 31.04 19.72 0.34Acetic acid 20.41 19.02 503.83 296.34 45.49 18.28 32.22 1.06

HNO2 20.27 19.02 192.60 46.34 6.38 2.98 14.86 0.31NH4 OACe 19.04 21.01 416.24 304.00 86.31 26.79 32.92 0.76

Ca concentration in the lechates (g/kg)TreatmentsLocation

Bukit Sileh

1.300 m a.s.l

Aie Batumbuk

1.100 m a.s.l

Table 2: Ca concentration in the lechates as a function of residence time and type of acids in successive

mode of incubation


264

After 2 h After 24 hAfter 1 w After 2 w After 3 w After 4 w After 5 w After 6 wH2O 13.83 18.82 158.59 117.77 105.02 96.51 90.56 3.24

Acetic acid 19.72 20.48 130.53 122.02 99.06 109.27 88.47 2.36HNO2 17.38 13.35 117.77 94.81 105.87 81.21 78.06 2.02

NH4 OACe 14.02 14.78 140.73 123.72 67.60 102.47 105.83 3.60

H2O 18.05 20.08 144.13 141.58 109.27 138.18 109.31 2.92

Acetic acid 20.41 19.02 157.74 134.78 126.28 123.72 107.22 2.77HNO2 20.27 19.02 120.32 108.42 107.57 111.82 100.97 2.53

NH4 OACe 19.04 21.01 149.23 139.88 80.36 168.79 138.47 4.48

Location Treatments Ca concentration in the lechates (g/kg)

Bukit Sileh

1.300 m a.s.l

Aie Batumbuk

1.100 m a.s.l

Table 3: Ca concentration in the lechates as a function of residence time and type of acids in separate

mode of incubation Comparing the source of proton donors used to age the airfall ash of Mt. Talang, acetic

acid released cations more than deionized water, nitric acid and sulfuric acid as well as ammonium acetate. Acetic acid is one of the organic acids, nitric acid is considered as strong mineral acid, deionized water is a weak acid while ammonium acetate is an alkaline solution with pH value of 7. Organic acids, as explained by [12], are capable of dissolving and complexing the cations from the surface layer of colloid or clay particles. Deionized water as a weak acid, is a source of protons in soil. It can be involved in hydrolytic reactions leading to partial dissolution (incongruent) and total dissolution (congruent) of minerals as time progresses. Furthermore, they discussed that strong acid, like nitric acid with a pKa of -1, capable of lowering the pH and to dissolve cations congruently, leaving no residue in the mineral surfaces.

Changes in leachates chemistry of progressive weathered of ash during incubation are illustrated in Figure 2 and Figure 3. As indicated, the amount of Ca in leachates increases with time, especially after 24 hours of contact time between the ash and the proton donor of each respective solution and started to level off after 5 weeks. Similar trend was also observed by [14] both in field and laboratory experiments of the Mt. St. Helens ash fall. They explained that increasing of the cations (ca and Mg) from field study reflecting retention of the cations in the soils after 2 years. Meanwhile higher amount of cations in lechates obtained from the leaching experiments as surface layer of the ash become cations-depleted. The same author presumed that rapid weathering of the ash liberated cations through surface exchange with aqueous hydrogen ions.


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Bukit Sileh (Successive incubation mode)

0.0001.0002.0003.0004.0005.0006.0007.0008.000

After 2 h After 24 h After 1 w After 2 w After 3 w After 4 w After 5 w

Times

Ca

diss

olut

ion

(%)

H2O H Acetat HNO2 NH4 OACe

Figure 2: Concentration of Ca after leached with different acids for 5 weeks

Bukit Sileh (separate incubation mode)

0.0001.0002.0003.0004.0005.0006.0007.000


Times

Ca

Dis

solu

tion

(%)


Figure 3: Concentration of Ca after leached with different acids for 5 weeks

3.4. Dissolution Rate of Iron

The solubility of solid-phase of iron upon leaching with different acids in successive

mode incubation is shown in Table 4 and Figure 4, whereas the result of the separated mode incubation is displayed in Table 5 and Figure 5. Fe concentrations are much lower compared to concentration of Ca. Aqueous concentration of iron is low because of the low solubility of the iron during initial period of weathering. As explained by [3] that Fe display low solubility during the first two years of experiments and increase slightly during the last two stages of their study. The dissolution of iron by soluble organic acids involving complexation process for quite long period of time [12].


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After 2 h After 24 h After 1 w After 2 w After 3 w After 4 w After 5 w After 6 wH2O 0.45 0.97 0.01 2.00 8.27 0.43 0.24 0.15

Acetic acid 1.91 2.08 1.66 3.57 2.29 1.74 2.18 1.30HNO2 5.35 6.25 2.46 6.27 3.56 4.15 4.48 1.89

NH4 OACe 0.05 0.06 0.26 0.42 0.50 0.43 0.52 0.39

H2O 0.09 0.13 0.01 2.22 4.44 0.14 0.94 0.37Acetic acid 1.93 1.49 1.41 4.54 2.36 2.20 2.33 1.38

HNO2 5.10 6.13 1.66 6.76 4.24 5.72 5.12 2.75NH4 OACe 0.00 0.05 0.30 0.45 0.16 0.40 1.15 0.37

Location Treatments Fe concentration in the lechates (g/kg)

Bukit Sileh

1.300 m a.s.l

Aie Batumbuk

1.100 m a.s.l

Table 4: Fe concentration in the lechates as a function of residence time and type of acids in successive

mode of incubation

After 2 h After 24 h After 1 w After 2 w After 3 w After 4 w After 5 w After 6 wH2O 0.45 0.97 0.72 0.72 0.72 0.72 0.72 0.00

Acetic acid 1.91 2.08 0.72 0.72 7.93 10.09 10.81 0.29HNO2 5.35 6.25 58.36 7.20 48.27 54.76 61.96 0.29

NH4 OACe 0.05 0.06 2.88 4.32 4.32 3.60 8.65 0.24

H2O 0.09 0.13 0.72 2.88 2.16 0.72 0.72 0.11

Acetic acid 1.93 1.49 2.88 6.48 6.48 4.32 7.93 0.26HNO2 5.10 6.13 3.60 17.29 36.02 36.02 36.74 0.17

NH4 OACe 0.00 0.05 0.72 4.32 0.72 0.72 5.76 0.09

Treatments Fe concentration in the lechates (g/kg)

Bukit Sileh

1.300 m a.s.l

Aie Batumbuk

1.100 m a.s.l

Location

Table 5: Ca concentration in the lechates as a function of residence time and type of acids in separate mode of incubation

Aie Batumbuk (successive incubation mode)

0.0000.0500.1000.1500.2000.2500.3000.3500.400


Times

Fe d

isso

lutio

n (%

)


Figure 4: Concentration of Fe after leached with different acids for 5 weeks


267

Aie Batumbuk (Separate incubation mode)

0.000

0.200

0.400

0.600

0.800

After 2 h After 24h

After 1 w After 2 w After 3 w After 4 w After 5 w

Times

Fe d

isso

lutio

n (%

)


Figure 4: Concentration of Fe after leached with different acids for 5 weeks

4. CONCLUSIONS The preceding data and discussion indicate that the recent airfall ash of Mt. Talang considered as basaltic andesitic rock type with higher amount of volcanic glass and plagioclase. Other primary minerals exists are hypersthene, augite, hornblende, opaque or ferromagnesian minerals. The elemental composition of the ash reaches the value of 55% for silica, with lesser amount of calcium, magnesium, potassium and sodium oxides. The calcium concentration detected in the leachates increased sharply up to 4 weeks and started to level off after 5 weeks. Among the proton donors, acetic acid is capable to dissolve more cations from air fall ash compared to other source proton donors such as deionized water, nitric acid and ammonium acetate. Concentration of Ca is higher thru the experimental study compared to Fe concentration.

ACKNOWLEDGEMENTS This work is supported by Directorate of Higher Education Department of National Education of Republic of Indonesia under Fundamental Research Grant no: 005/SP3/PP/DP2M/II/2006, granted to the first author. Total elemental analyses with XRF Spectrophotometer were performed at the Laboratory of Research and Development of PT. Semen Padang, Indonesia.

REFERENCES

[142] Dahlgren, R. A. and F. C. Ugolini. Effects of Tephra Addition on Soil Processes in Spodosols in the Cascade Range, Washington, U.S.A. Geoderma, 45:331-355. (1989). [143] Dahlgren, R., S. Shoji and M. Nanzyo. Mineralogical characteristics of volcanic ash soils. In: S. Shoji, M. Nanzyo and R. Dahlgren (eds.). Volcanic Ash Soil-genesis, properties, and utilization. Developments in Soil Science 21, Elsevier, Amsterdam. 101-144. (1993).


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[144] Dahlgren, R. A., F. C. Ugolini and W. H. Casey. Field weathering rates of Mt. St. Helens tephra. Geochim. Cosmochim. Acta. 63, 587-598. (1999). [145] Dahlgren, R. A., M. Saigusa and F. C. Ugolini. The Nature, Properties and Management of Volcanic Soils. Advances in Agronomy, Academic Press. Vol. 82:113-182. (2004). [146] Fiantis, D. Colloid-Surface Characteristics and Amelioration Problems of some volcanic soils in West Sumatra, Indonesia. Ph. D. Thesis. Universiti Putra Malaysia, Serdang, Selangor, Malaysia. 315 p. (2000). [147] Kpomblekou-A, K. and M. A. Tabatabai. Effect of Organic Acids on Release of Phosphorus from Phosphate Rocks. Soil Sci. Vol 156, No.6:442-453. (1994). [148] Kurashima, K., S. Shoji and I. Yamada. Mobilities and related factors of chemical elements in the toposoils of Andosols in Tohoku, Japan: 1. Mobility sequence of major chemical elements. Soil Sci. 132:300-307. (1981). [149] Lowe, D. J. Controls on the rates of weathering and clay mineral genesis in airfall tephras: a review and New Zealand case study. In: S. M. Colman and D. P. Dethier (eds.), Rates of Chemical Weathering of Rocks and Minerals. Academic Press, Inc. Orlando. 265-330 pp. (1986). [150] Robert, M. and J. Berthelin. Role of Biological and Biochemical factors in Soil Mineral Weathering. In Interactions of Soil Minerals with Natural Organics and Microbes. P. M. Huang and M. Schnitzer (eds). Soil Sci. Soc. Am. Spec. Publ. 17. Madison, WI, pp.453-495. (1986). [151] Shoji, S., I. Yamada and K. Kurashima. Mobilities and related factors of chemical elements in the toposoils of Andosols in Tohoku, Japan: 2. Chemical. and mineralogical compositions of size fractions and factors influencing the mobilities of major chemical elements. Soil Sci. 132:331-346. (1981). [152] Shoji, S., M. Nanzyo and R. A. Dahlgren. Volcanic Ash Soils – Genesis, Properties and Utilization. Elsevier, Amsterdam, the Netherlands. 288 p. (1993). [153] Ugolini, F. C. and R. S. Sletten. The Role of Proton Donors in Pedogenesis as Revealed by Soil Solution Studies. Soil Sci. Vol. 151, No. 1:61-75. (1991). [154] White, A. F. Surface chemistry and dissolution kinetics of glassy rocks at 25°C. Geochim. Cosmochim. Acta. 47, 805-815. (1983). [155] White, A. F., L. V. Benson and A. Yee. Chemical Weathering of the May 18, 1980, Mount St. Helen Ash Fall and the Effect on the Iron Creek Watershed, Washington. In “Rates of Chemical Weathering of Rocks and Minerals”. Colman, S. M. and D. P. Deither (Eds.). pp.351-375. Academic Press, Orlando. (1986). [156] Yamada, I., S. Shoji, S. Kobayashi and J. Masui. Chemical and mineralogical studies of volcanic ashes. II. Relationship between rock types and mineralogical properties of volcanic ashes. Soil Sci. Plant Nutr., 24:75-89. (1975).


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STONE LINES AND WEATHERING PROFILES OF FERRALLITIC SOILS IN NORTHEASTERN ARGENTINA

Morrás, H.1*, Moretti, L.1, Píccolo, G.2, Zech,W.3

1INTA-CIRN, Instituto de Suelos, 1712 Castelar, Buenos Aires, Argentina, 2INTA-EEA Cerro Azul, 3313 Cerro

Azul, Misiones, Argentina, 3Institute of Soil Science, University of Bayreuth, Bayreuth, Germany

Abstract A ferrallitic pedological mantle with Ultisols and a lower proportion of Oxisols, is found in the Province of Misiones, in northeastern Argentina. This ferrallitic material usually has a depth of 3 to 7 m above the weathered basalt, and frequently a “stone line”, many times lying on a thin structured layer, appears in its lower part, close to the limit with the saprolite. The autochthonous or allochthonous origin of materials composing this type of profile, frequent in tropical and subtropical environments, is controversially discussed in the literature. Referring specifically to the area of Misiones and to neighbouring regions in Brazil and Paraguay, Iriondo and Kröhling [5] postulated that the material that covers the basaltic rock and in which the red soils have developed is an eolian sediment (a “tropical loess”) of upper Pleistocene age, deflated from the alluvial plains of the Paraná and Uruguay rivers. The work we have carried out in this region, allows us to distinguish two basic types of “stone lines”: the first one is a “nodular line”, more typical for the southern part of Misiones, composed by goethitic nodules of gravel size, and appearing to derive from differential weathering of more resistant basaltic layers. The second one is a “siliceous” layer of quarzitic nature, characterizing profiles in central Misiones: these silica concentrations in some instances are in situ relicts of former quartz veins in the basalt, and in other cases the “line” may be defined as a “silcrete”; a secondary accumulation of quartz on relictic quartz veins seems to happen in other cases. Concerning the blocky structured subsurface levels below the “stone lines”, the results lead to conclude that they are not paleosols, and that they can not be considered as an evidence of paleosurfaces. Consequently, according to our field observations and to our laboratory results (clay and sand mineralogy, magnetic susceptibility, geochemical data, granulometry, micromorphology and stable carbon isotope analysis), we consider that the “stone lines” as well as the surface ferrallitic soil materials in Misiones have an autochthonous origin, deriving from in situ weathering of basaltic rock.

INTRODUCTION A ferrallitic pedological mantle with Ultisols and a lower proportion of Oxisols, covers most part of the landscape in the Province of Misiones, in northeastern Argentina. This ferrallitic material usually has a depth of 3 to 7 m above the weathered basalt, and frequently a “stone line’, many times lying on a thin structured layer, appears in its lower part, close to the limit with the saprolite.

The nomenclature of different layers and the autochthonous or allochthonous origin of materials composing this type of complex profile, frequent in tropical and subtropical environments, is a controversial matter that has deserved numerous interpretations and proposals [19, 20]. The presence of the “stone lines” suggests the existence of an unconformity and this feature has been generally considered to be of sedimentological rather than of pedological origin. Thus, most part of diverse hypotheses proposed considers processes of generation, movement and accumulation of pebbles, though differing in the interpretation of their genesis and that of the overlying material.


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According to Segalen [19] the different interpretations currently admitted concerning the origin of the “stone lines” can be grouped in the following way: 1) processes of pediplanation related to climatic changes, producing the erosion of laterites and quartz veins followed by the transport of their fragments; 2) colluvial processes in steep slopes, producing the erosion and transport of hardened horizons and veins; 3) autochthony or in situ sinking of hardened laterites previously fragmented by chemical weathering. The activity of the soil fauna has also been proposed to be responsible for the downward movement of the pebbles within the profiles, and for covering them with fine textured materials.

For the origin of surface material above the stone lines different interpretations have also been suggested. A two stages process made up by a first one of deflation and exposure of pebbles and a second one of covering due to a later sedimentation is among the older explanations; this would be eventually possible at certain localities but it is considered unacceptable as a general interpretation [3, 19, 20]. At present, two explanations of general application about the origin of the fine textured surface materials are a colluvial deposition and an upward vertical transport of fine material by termites from the saprolite [19, 20]. Segalen [19] also mentions that several authors have presented interpretations involving the simultaneous effect of different processes in the development of these soil profiles. Recently, Johnson [7, 8] proposed a general explanation combining different theories and principles of geomorphology, pedology and hydrology that he named “the dynamic denudation theory”, and in which the dynamic processes and conditions are driven by gravity, water and biotic agents.

With regard to Misiones in Argentina, the red soils were traditionally considered to be the result of in situ weathering of the tholeiitic basalt of the Serra Geral Formation [18]. On the contrary, Iriondo and Kröhling [5] referring to Misiones as well as to neighbouring regions in Brazil and Paraguay, postulated that the material covering the basaltic rock and in which the red soils have developed is an eolian sediment of upper Pleistocene age, deflated from the alluvial plains of the Paraná and the Uruguay rivers. The authors consider this surface material to be a “tropical loess” and have formally named it “Oberá Formation”, identifying an “Upper member” and a “Lower member” separated by the “stone line”. Besides some analytical data, the main arguments are the presence of a “stone line” described as platy-gravel sized silica and, less frequently, the presence of a buried soil (classified as Ultisol) represented by a moderately structured B horizon below the ¨stone line¨ and therefore regarded as an evidence of a paleosurface.

Similarly, Lichte y Behling [10] referring to the Quaternary landscape evolution in southeastern Brazil, also consider that the “stone lines” have developed on a now fossil surface that was subsequently covered by an eolian sediment. For these authors the quartz pebbles derive from quartz veins included in the Precambrian crystalline rocks, which were distributed by heavy rains along the slopes, and later on covered by fine eolian sediments deriving at least partly from the lateritic cover of the Sudamericana plain. Consequently, taking into account the diversity of hypotheses concerning the origin of this type of ferrallitic soils with “stone lines”, and due to the role they play with respect to the interpretation of landscape evolution, we focus since some years on this phenomena in Misiones [13, 14, 15, 16]. In the following our results will be summarized.


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MATERIAL AND METHODS The Province of Misiones is located in northeastern Argentina, around 28º S and 54º W (Fig. 1). The climate is subtropical humid without dry season; the mean annual temperature is around 20°C and the mean annual rainfall increases from 1750 mm in the south to 1950 mm in the north. The present vegetation is a subtropical forest, except a narrow strip along the southern border with a savanna type vegetation. The field work for the study of ferrallitic soils was for the most part done on exposed profiles along the main roads in the Province. The sites observed and described up to the present are more than sixty, and several of the profiles in different sectors of the Province have been selected and sampled for detailed studies. Some soil profiles in concave topographic positions have also been sampled and analyzed. The samples were characterized by conventional analysis; in addition clay mineralogy (DRX and TEM), sand mineralogy (optical microscopy and SEM), magnetic mineralogy (magnetic susceptibility), micromorphology, geochemistry (macro- and micro-elements), and stable carbon isotopes analysis were taken into consideration.

Figure 1: Map of the Misiones Province, and location of some of the surveyed sites.

RESULTS Considering that the genesis of ¨stone lines¨ and associated ¨structured horizons¨ is unclear, we have focused our study on these features. The work we have carried out in this region, allowed us to distinguish several morphological types of ¨stone lines¨, from which two basic compositional types were identified.


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a) The ¨nodular lines¨ The first type of “stone line” we named “nodular line” (Fig. 5-A), typical for the southern part but also observed in other sectors of Misiones, is composed by ferruginous nodules of gravel size, usually with a mean size of around 15 mm. According to their mineralogy and morphology three groups were distinguished: the first one consists of hematitic nodules, dark red in colour and bright, and being the smallest in size; the second group is composed by goethitic nodules, reddish yellow in colour, opaque, and the bigger in size; the third group is composed by nodules of intermediate aspect and composition. The hematitic nodules occur in low proportion along the profile, as well above as below of the ¨stone line¨ with a slight maximum at that level; the goethitic nodules are in a high proportion within the ¨stone line¨ and appear only in this layer, while the intermediate nodules are in low proportion above and below the ¨stone line¨ showing there a sharp quantitative increment though the increases in size is progressive (Fig. 2). Though the nodules are more abundant at a particular level thus defining a ¨stone line¨, the fact that those ¨iron gravels¨ are not restricted to that level, together with their verticals variation in quantity, size and composition, suggest that they are not the result of a sedimentary process of accumulation. Secondly, the goethitic nature of gravels appearing exclusively at the “stone line” level, would not be compatible with their residence at a surface under an arid climate.

Moreover, transitional vertical or horizontal steps of rock weathering observed in several profiles have furnished the evidence of the in situ formation of this type of “stone line”: thus for example, it was observed the transition from homogeneous saprolite bodies to levels with an incipient individualisation of soft rounded and more yellowish nodules, in turn passing to rounded hardened fragments increasingly individualised and sparsed, giving finally rise to a kind of relictic ¨stone line¨ (Figs. 5-C, 5-E, 5-F). Microscopic analysis of the nodules forming the “stone line” shows an internal porphyric texture with weathered phenocrysts, partially filled with goethitic iron, thus revealing its relationship with the basaltic rock. b) The ¨siliceous lines¨ The second type of ¨stone line¨, mainly observed in the central part of the Province, is a “siliceous” level of quartzitic nature (Fig. 5-B). In this type of ¨line¨ the silica appears as horizontal levels of variable thickness, from a few millimeters (in this case usually fractured and with the appearance of laminar fragments) up to 30 cm or more.

In some instances these silica concentrations are clearly in situ relicts of former quartz veins in the basalt. Lateral as well as vertical transitions from weathered basalt levels including quartz veins to pedogenized red materials including quartz ¨lines¨ have been observed (Figs. 5-E, 5-F). In some cases these siliceous levels into the pedogenized material seem to result from a secondary crystallisation of quartz, thus developing as ¨silcretes¨. Besides, in several instances, a secondary crystallisation of quartz seems to happen on relictic quartz veins; the upper face of these levels shows an irregular morphology that could be the result of dissolution as well as crystallization of silica.

In every case it is clear that the siliceous levels are basically massive and continuous, i.e. they are not constituted by pebbles or fragments that were submitted to transport. Some fragmentation of thick siliceous ¨lines¨ observed in some cases on vertical walls is the artificial result of the excavation, which is not observed when the ¨levels¨ are carefully exposed removing


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the covering material. Thin veins may be naturally fragmented, but the fragments appear perfectly accommodated as the pieces of a floor (Fig. 5-D), this being the result of internal movements and eventually from processes of dissolution, during the processes of rock weathering and soil formation.


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In these profiles, the ferruginous nodules are scarce and its vertical distribution is different to the profiles with ¨nodular lines¨. In some cases levels showing a relatively higher concentration of iron nodules, dark red and hematitic, and appearing regularly with depth, coincides with a higher concentration of quartz gravels (Fig. 3). The last may be interpreted as fragments of presently dissolved thin relictic quartz veins; it may be hypothesized that those former veins have slowing down the process of lixiviation thus contributing to an accumulation of iron and promoting the development of iron nodules. c) The ¨structured horizons¨ Concerning the blocky structured subsurface levels below the “stone lines” (Figs. 5-A, 5-F), field and analytical results lead to the conclusion that they are not buried paleosols and that they can not be considered as an evidence of paleosurfaces. Two processes may be responsible for the formation of these structured layers: 1) The first one is similar to the “stone line” development described above, to which sometimes they are associated: in this case a lateral sequence of weathering, from the weathered rock to a structured and fine textured material, can be observed (Figs. 5-E, 5-F). 2) In a second one, nodular or siliceous layers derived from the above mentioned processes, may exert a “protection” effect on the underlying fine textured materials against the weathering front, thus allowing the development or conservation of structural blocky units. As a consequence, places are found in which a well defined “stone line” covers a continuous structured horizon, as well as places where short discontinuous ¨lines¨ or even isolated gravels preserve structured micro-horizons, surrounded by a differently organized material.

Besides the profiles showing one of the above mentioned two types of ¨stone lines¨, other situations have been also observed: profiles with several superimposed ¨lines¨ of the same type; profiles with different types of ¨lines¨ superimposed at different depths; ¨lines¨ with dark and bright gravels of laminar morphology; profiles without ¨lines¨; ¨stone lines¨ appearing above, below as well as inside of structured layers, thus do not having a fixed positional relation with structured horizons, and “lines” lying directly on or within the saprolite. It is also to be mentioned that besides the horizontal facies, many times “stone lines” and structured layers show sub-horizontal directions and bifurcations or branchings (Fig. 5-A). ¨Lines¨ with an undulated morphology, sometimes described as ¨funnel-like¨ [20], are also common. d) Clay mineralogy. The XR-diffractometry of the clay fraction from different profiles, those having a nodular “stone line” as well as those with a siliceous line, shows a similar composition and gradual mineralogical variation from the saprolite up to the soil surface (Fig. 4). The more abundant components of the fraction are kaolinitic minerals, i.e mainly kaolinite and some halloysite, the last evidenced clearly by TEM; the content of these phyllosilicates decrease progressively from the saprolite up to the surface. At the same time, a continuous increase of chloritic minerals is observed from the “stone lines” up to the surface, where they comprise around the 15% of the clay fraction. These last minerals known under different names, v.g. pseudo-chlorites, aluminous chlorite, aluminous vermiculites, develop in pedogenic environments.

This mineralogical vertical variation suggests that these profiles are the result of in situ weathering of the basalt rock. Besides, it can be observed that the mineralogical composition of structured levels below the “stone lines”, which have been interpreted as paleosols, have a mineralogical composition similar to that of the saprolite and thus differing from that of the upper B soil horizons.


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e) Sand mineralogy and quartz exoscopy The sand fraction of the ferrallitic soils in Misiones is almost exclusively composed by quartz and magnetite, the first being more abundant in the finer fractions while the second is more abundant in the coarser ones. Variable proportions of pseudosand grains and small iron nodules are also observed by microscopy. Other stable minerals as ilmenite, anatase and rutile have been detected by XRD [2, 12]. The mineralogical composition of sands is thus typical for highly weathered materials.

On the other hand, the morphological study of quartz grains by optical microscopy and by SEM, recording their general morphology and the features on their surfaces, provides information about their history, i.e. processes of transport and chemical environment that have affected the materials where the grains are included [4, 9].

Microscopic analysis of the sand fraction from soils of Misiones reveals that a considerable part of quartz grains have experienced a high degree of weathering, characterised by deep and interconnected pits of dissolution (Fig. 5-G). On the other hand, many of the grains are clearly the result of secondary crystallisation of quartz. This secondary quartz can be observed as individualized single grains, or as a secondary crystallisation on the surface of other quartz grains acting as a nucleus or template for silica deposition (Fig. 5-G). Some of the grains appear rounded under optical microscopy, but under the SEM these grains show sharp and well developed crystal faces (Fig. 5-H). Besides, these grains show on their surface typical marks of dissolution with an inverted trigonal symmetry [12]

The exoscopy performed on sand grains from different horizons of ferrallitic soils from Misiones, do not show evidences of eolian transport. On the contrary clear traces of quartz crystallisation and of chemical dissolution appear. Very interesting are those grains showing both processes, a first one of quartz crystallisation, with silica supposedly mainly coming from more weatherable minerals, followed by the dissolution of that secondary quartz (Fig. 5-


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H). Thus, morphology and surface textures of quartz grains are consistent with a in situ development of these ferrallitic soils.

f) Magnetic susceptibility Magnetic susceptibility was measured in the field and in the laboratory, in this case at high and low frequency. Results obtained show high values, fitting the concept of “magnetic” soils, increasing progressively from the saprolite up to the soil surface. The difference between high and low MS –the frequency dependent MS– is low in the saprolite, shows a rapid increase from the “stone line” to lower B horizons, and then keeps similar differences up to the surface (Figs. 2, 3).

The gradual increase of MS from the saprolite towards the surface can be related to a gradual increment in the magnetite content, a highly resistant mineral found in the basalt rock [2]. In turn, the high value of the frequency dependent MS above the “stone line”, is an indication of the existence of superparamagnetic magnetite, which is of pedogenic origin. Thus, both results suggest that these soil profiles are developed through in situ ferrallitic processes of weathering from the basalt. Besides, data from the structured horizons below the stone line differ from the soil horizons above it, thus being an additional indication that they are not paleosols. g) Granulometry The granulometric data show a gradual increase of clay and silt fractions from the surface to the middle part of the B horizons, and then a progressive decrease towards the base of the saprolite (Figs. 2, 3). The maximum of fine materials observed in the B horizon would be the result of a twofold process, in a one hand the result of the process of illuviation typical for Ultisols, and in the other hand a process of argilogenesis due to rock weathering and soil development. Particularly, the progressive increase of fine fractions from the saprolite towards the middle part of B horizons suggests that the materials are in situ. Besides, the content of fine fractions in the structured horizons below the “stone lines” are quite different from the B horizons, and do not seem to correspond to a paleo Ultisol as has been proposed. h) Geochemistry Total amounts of selected chemical elements and their ratios generally show continuous transitions from the saprolite up to the soil surface, evidencing the weathering process and the neoformation of minerals that have occurred in these soils. Total content of silica increases rapidly above the saprolite, due to the neoformation of clay minerals as well as quartz crystallisation. The Si/Al ratio increases progressively towards the surface, running parallel with the increase of chloritic minerals in the same direction (Fig. 3). A stable element as Zr increases progressively towards the surface, which would reflect the increasing intensity of weathering in the same direction. Weathering indices such as the one of Parker and homogeneity indices such as Ti/Zr do not show discordances (Fig. 3). But the same elements and certain ratios shift significantly below the “stone lines”. These results indicate that the reddish materials and the “structured horizons” below the “stone lines” do not correspond to a paleosol and to a lower member of a sedimentary formation as has been interpreted [5], but to slightly pedogenized transitional levels between the saprolite and the B horizons of the soils.


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i) Stable Carbon Isotopes The stable carbon isotope composition of plants differs according to their photosynthetic pathway (C3, C4, and CAM). δ13C values of C3 plants like trees and almost all the plants in temperate and cold regions, range from approximately –32‰ to –20‰ PDB, with a mean of –27‰. In contrast δ13C values of C4 plants, adapted to conditions of higher hydric stress, range from –17‰ to –9‰, with a mean of –13‰ [11, 17]. Isotopic fractionation depends not only on the type of vegetation but also on the plant environment, the CO2 atmospheric concentration, the temperature and on the humidity level. During litter decomposition and humification the isotopic signal of plants is transferred into the soil organic matter (SOM). Thus, the analysis of carbon isotopic composition of SOM may allow to deduce information about the environments and climatic conditions under which plants have grown in former times.

Results obtained in Misiones [16] show that surface soil horizons (0-50 cm) have δ13C values around –25‰ in accordance with the present humid climate and a C3 vegetation cover. At around one meter depth the isotopic signature shows a significant enrichment in δ13C of up to –15‰ (Figs. 2, 3).This result indicates that the SOM has derived from a vegetation dominated by C4 plants developed under conditions of hydric stress in a savanna environment. Such conditions have probably existed in Misiones during the Last Glacial Maximum and the first half of the Holocene, as it is reported by several authors in southern Brazil [6, 17].

In the lower part of the profiles, the measurement of δ13C gives intermediate values (around -21‰) that are more difficult to be explained. Anyway, and in accordance with the interpretations made for similar situations, it is considered that these δ13C values result from a vegetation dominated by C3 plants in an open forest and under intermediate climatic conditions. Consequently, in the vicinity of the “stone lines” there are no evidences of arid to semiarid environmental conditions suitable for a denudation, accumulation of gravels on a paleosurface, and a later eolian sedimentation several meters thick during the LGM as has been proposed by Iriondo and Kröhling [5].

DISCUSSION AND CONCLUSIONS According to our field and laboratory results, it is possible to attribute an autochthonous origin to the “stone lines” appearing in the red soils of Misiones.

In the case of the “nodular lines”, the rounded goethitic gravels seem to derive from a differential weathering of relatively more resistant basaltic layers. Transitional situations between the weathered basalt and the well defined “stone lines” clearly show the origin and the process of individualisation and accumulation of single nodules. Besides, the ferruginous nodules are not restricted to the “stone lines”. The hematitic ones as well as those with a partial covering of hematite at their surfaces, both appearing in an increasing proportion with depth down to the “stone line”, may also be interpreted as relictic fragments of the basaltic saprolite, i.e. formed similarly to the ones in the “stone line” but that has been progressively weathered, sparsed and covered by hematite as the result of soil development.

In the case of the “siliceous lines” several evidences indicate that they are also autochthonous, and derived from pre-existing quartz veins within the basalt. Here also transitional situations between the weathered basalt intruded by quartz veins, and silica accumulations into pedogenized materials have been observed. Besides it has clearly appeared that platy siliceous gravels are not transported and that they result from in situ fragmentation of quartz veins. Some additional complexity in the evolution and morphology of these


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“siliceous lines” is given by the frequently evident secondary accumulation of quartz on the relictic veins, which in cases make difficult to distinguish relictic features from newly formed levels that would better fit with the concept of “silcretes”.

Concerning the “structured horizons” below the “stonelines”, field and analytical data indicate that they are not paleosols. Though the process of structuration is not so clear, it also seems to be associated to the existence of the relatively more resistant layers within the basalt. In the case of profiles with “nodular lines”, it seems that during the process of nodules development, the material in between and immediately below gets a polyhedric structure. In this process of aggregates development, the “lines” seem to play as a sort of “protection” against the weathering front. This “protective” effect would be the origin of structuration in the case of “siliceous lines”. Several field evidences seem to support these interpretations: in many cases the “structured horizons” conserve many morphological features from the saprolite. In the cases where the “nodular” or “siliceous” lines have subhorizontal directions or when they bifurcate, “structured horizons” follow the orientation of those gravelly “lines”. Moreover, in the cases where the horizontal gravelly “lines” are interrupted, a feature that may be interpreted as the result of weathering proceeding through pockets into the parent rock, the “structured horizons” also disappear.

Thus, both types of gravelly ”lines” identified in the ferrallitic soils of Misiones as well as the “structured horizons” are considering to be in situ relictic features deriving from the ferrallitic weathering of two types of basaltic flows appearing in the area. The soils showing both types of “stone lines” superposed within the same profile, the “nodular” one above the “siliceous” one -as was consistently observed up to the moment- in agreement with the usual lying of both types of basalt layers at the surface, are additional evidences of its autochthonous origin.

ACKNOWLEDGMENTS

The authors thank the Ägencia Nacional de Promoción de la Investigación Científica y Técnica¨ –ANPCyT- of Argentina, for supporting a great part of this research through the Project PICT 07-08879.

REFERENCES [1] H. Behling, M, Lichte, A., Miklós. Evidence of a forest free landscape under dry and cold climate conditions during the Last Glacial Maximun in the Botocatu region (Sao Paulo State), Southeastern Brazil. Quaternary of South America and Antartic Peninsula, 11, 99-110, (1998). [2] H. Causevic, H. Morrás, A. Mijovilovich, C. Saragovi. Evidences of the stability of magnetite on a soil from Northeastern Argentina by Mössbauer spectroscopy and magnetization measurementes. Physica B: Physics of Condensed Matter, 354 (1-4): 373-376, (2004) [3] Y. Chatelin, Influence des conceptions géomorphologiques et paléoclimatiques sur línterpretation de la genèse et la classification des sols ferrallitiques dÁfrique Centrale et Australe. Cah. ORSTOM, sér. Pédol., V(3): 243-255, (1967) [4] H. Eswaran, G. Stoops. Surface textures of quartz in tropical soils. Soil Science Society of America Journal. 43(2):420-424, (1979). [5] M. Iriondo, D. Kröhling. The tropical loess. Proc. 30th International Geological Congress, (An Zhisheng et al., Eds.), Vol. 21, p. 61-77, (1997). [6] T. Desjardins, F. Andreux, B. Volkoff., C. Cerri, Distribution de l’ isotope 13C dans des sols ferrallitiques du Brésil. Cah. ORSTOM, sér. Pédol., XXVI (4): 343-348, (1991). [7] D. Johnson. Dynamic denudation evolution of tropical, subtropical and temperate landscapes with three tiered soils: toward a general theory of landscape evolution. Quaternary International, 17: 67-78, (1993).


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[8] D. Johnson, J. Domier, D.N. Johnson. Animating the biodynamics of soil thickness using process vector analysis: a dynamic denudation approach to soil formation. Geomorphology, 67, 23-46, (2005). [9] L. Le Ribault. L´exoscopie des quartz. Masson, Paris, 150 p, (1977) [10] M. Lichte, H. Behling, Dry and cold climatic conditions in the formation of the present landscape in Southeastern Brazil. Z. Geomorph. N.F., 43(3):341-358, (1999). [11] A. Mariotti. Le carbone 13 en abondance naturelle, traceur de la dynamique de la matière organique des sols et de l’évolution des paléoenvironments continentaux. Cah. ORSTOM, sér. Pédol., XXVI (4): 299-313, (1991). [12] A. Mijovilovich, H. Morrás, C. Saragovi, G. Santana, J. Fabris. Magnetic fraction of an Ultisol from Misiones, Argentina. Hyperfine Interactions, C, 3: 332-335, (1998) [13] H. Morrás, L. Moretti, G. Píccolo, W. Zech. Algunas observaciones sobre la composición y el origen del material edafizado y las líneas de piedra sobreyacentes a los basaltos de Misiones. Actas X Reunión Argentina de Sedimentología, San Luis, pp. 106-108, (2004) [14] H. Morrás, L. Moretti, G. Píccolo, W. Zech. New hypotheses and results about the origin of stonelines and subsurface structured horizons in ferrallitic soils of Misiones, Argentina. 2nd Assembly of the European Geosciences Union, Vienna, Geophysical Research Abstracts, Vol. 7, 05522, (2005). [15] H. Morrás, L. Moretti, B. Glaser, G. Píccolo, W. Zech. Eolian transport vs. in situ weathering: evidences for supporting an autochthonous origin of ferrallitic soil parent materials in subtropical norhteastern Argentina. Abstracts, INQUA International Workshop, Lower Latitudes Loess - Dust transport. Past and Present, Lanzarote, Canary Islands, (2006) [16] H. Morrás, L. Moretti, B. Glaser, G. Píccolo, C. Hatté, W. Zech. Paleoenvironments in the subtropical northeastern Argentina as deduced from stable Carbon isotopes composition of ferrallitic soils. V South American Symposium on Isotope Geology. Punta del Este, Uruguay, pp. 267-271, (2006) [17] L. Pessenda, S. Gouveia, R. Aravena, R. Boulet, E. Valencia. Holocene fire and vegetation changes in southeastern Brazil as deduced from fossil charcoal and soil carbon isotopes. Quaternary International, 114, 35–43, (2004). [18] G. Sanesi. I souli di Misiones. Academia Italiana di Scienze Forestali, 343 p., (1965). [19] P. Ségalen. Les sols ferrallitiques et leur répartition géographique. Orstom Éditions, Paris, Tome 1, 198 p., (1994). [20] G. Stoops. Le profil d´alteration au Bas-Congo (Kinshasa). Sa description et sa genèse. Pédologie, XVII (1): 60-105, (1967).


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Figure 5. A: soil profile with a ¨nodular line¨ (profile M0 in the locality of Leandro N. Alem); see the

complex morphology of the ¨line¨. B: a profile with a ¨siliceous line¨ (M10, in the locality of Aristóbulo del Valle). C: goethitic nodules developing in the saprolite, and giving rise to a ¨nodular line¨. D: vertical view of a ¨siliceous line¨ deriving from a quartz vein into the basalt; E: at left, two

superposed weathered basalt layers; the lower layer includes quartz veins; at right, the same profile in a more advanced step of weathering. F: the same sequence of basalt layers showed in figure E,

already pedogenized; remark the superposition of a ¨nodular line¨ above a ¨siliceous line¨, each one with its own ¨structured horizon¨ G: sand fraction from a Bt horizon, composed by magnetite, quartz and pseudosands (optical microscopy); remark the presence of very weathered quartz grains together with secondary quartz. H: a grain of secondary quartz from the sand fraction; remark the dissolution

pits.


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PEDOGENESIS ALONG A HILLSLOPE TRAVERSE IN THE UPPER AFRAM BASIN, GHANA

T. Adjei-Gyapong,1 E. Boateng,1* C. Dela Dedzoe,1 W.R. Effland,2 M.D. Mays2 and J.K.

Seneya1

1Ghana Soil Research Institute and 2USDA/NRCS Soil Survey Division

E-mail: [email protected], Tel: 23321778226, Fax: 23321778219 Poster Extended Abstract

In March 2004, six pedons were sampled during a collaborative Ghana-U.S. inter-laboratory soil characterization project. This poster presents results from three pedons located along a hillslope traverse. The objectives of this research are: (1) to compare the morphology of the soils; (2) to examine the chemical, physical and mineralogical composition of each soil; and (3) to understand the genesis and variation of soil properties along the hillslope. Three locations were selected to represent soil variation along a hillslope traverse with consistent parent materials, climate, and native vegetation. Standard soil characterization analyses were conducted at the USDA/NRCS National Soil Survey Laboratory in Lincoln, NE (Soil Survey Staff, 1996),and the Soil Research Institute , Ghana. Analytical results for particle size distribution, pH, clay and sand mineralogy, and citrate-dithionite extractable “free” Fe are discussed. Thin sections were prepared from oriented clods The soils are developed over relatively similar parent materials (fine-grained Voltaian sandstones) and in similar macro-climates. Occurring at the forest-savannah transition, they display contrasting morphological properties, which affect their soil classification, land use and management. The Techiman series (Typic Rhodustalfs) on the summit to shoulder is well to excessively drained, moderately deep (80-100 cm), grayish brown, loamy fine sand with many (35%) ironstone concretions and nodules over a reddish brown, dominantly ironstone-concretionary (65%) sandy clay loam subsoil. On the linear (middle) back slopes, the Amantin series (Typic Kandiustalfs) is moderately well drained, very deep (> 190 cm), grayish brown, loamy fine sand over yellowish brown sandy clay loam free of coarse fragments. The Denteso series (Oxyaquic Dystrudept) on the foot (lower) slope is poorly drained, grayish brown, loamy fine sand over structureless, single-grained pinkish gray sand. Iron concretions and ironpans occur within, and in some cases beneath, the soils studied along the hillslope in the Upper Afram Basin. The genesis of ironpans involves cycles of Fe mobilization, redistribution and concentration within the landscape. The higher Fe content results from element release through mineral weathering from overlying horizons and neighboring upslope soils. Further research is planned with an evaluation of terrain data on elevation, slope classes, slope aspect and other derivatives for the Afram Basin study area. Current environmental conditions (elevation, slope classes, aspect) within the Afram Basin study area are displayed with derivatives from a 200 ft resolution digital elevation model (DEM).

REFERENCES

[157] S.V. Adu, J. A. Mensah-Ansah. "Soils of the Afram Basin, Ashantiand Eastern Regions, Ghana", CSIR-Soil Research Institute, Memoir No. 12. Kwadaso-Kumasi, Ghana. 90pp., (1995).


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[158] T.W. Awadzi, R.D. Asiamah. "Soil Survey of Ghana", Soil Survey Horizon. 43 (2): 44-52, (2002). [159] E. Boateng, TR. E. Chidley, D. J. Savory, J. Elgy. "Soil Information System Development and Land Suitability Mapping at the Ghana Soil Research Institute", Poster Presentation at 16th World Congress of Soil Science, Montpellier, France. August 20-26, (1998). [160] Soil Survey Staff. "Soil Survey Laboratory Methods Manual". USDA/NRCS Soil Survey Investigations Report No. 42, January, (1996).


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INFLUENCE OF TITANOMAGNETITE ON DITHIONITE-CITRATE-BICARBONATE (DCB) AND OXALATE

EXTRACTIONS IN WEATHERED DOLERITE

C. G. Algoe 1*, E. Van Ranst 2, G. Stoops 3

1* Anton de Kom Universiteit van Suriname, Faculteit der Technologische Wetenschappen, POB 9212,

Paramaribo, Suriname, Tel: +597 465558 ext. 413, Fax: +597 495005, Email: [email protected] 2 Laboratorium voor Bodemkunde, Universiteit Gent, Krijgslaan 281, S8, B-9000 Gent, Belgium

3 Laboratorium voor Mineralogie, Petrologie en Micropedologie, Universiteit Gent, Krijgslaan 281, S8 B-9000 Gent, Belgium

Abstract Four dolerite boulders were collected in weathered profiles in the Precambrian Guiana Shield occurring in Suriname. These spheroidally weathered boulders were sub-sampled in the laboratory to obtain shells of different weathering grades, which were analysed using chemical and mineralogical techniques. The high amount of ammonium-oxalate extractable iron as compared to the dithionite-citrate-bicarbonate (DCB) extractable iron and the presence of titanomagnetite in the fresh rock questions the influence of (titano)magnetite on either type of extraction technique. Highly magnetic fractions were separated from the fresh rock and studied using microprobe analyses, oxalate and DCB extractions. Oxalate and DCB extractions were also carried out on thin sections. The results confirm the influence of titanomagnetite on the extractable iron content.

INTRODUCTION Two techniques are most commonly used to extract pedogenic iron from soil and regolith samples: the ammonium-oxalate method (Ox) and the dithionite-citrate-bicarbonate (DCB) method. The oxalate extraction is presumed to remove X-ray amorphous and organic bound iron oxides, whereas the dithionite extraction is supposed to remove in addition the finely crystalline iron oxides [9, 10, 21]. The amount of iron released by the dithionite extraction should therefore be equal to or greater than the amount of iron released by the oxalate extraction method [21].

In order to study the spheroidal weathering of dolerite, four boulders were collected in a weathered profile within the Precambrian Guiana Shield occurring in Suriname. These boulders were sub-sampled in the laboratory, to obtain shells of varying weathering grade, which were analyzed with various chemical and mineralogical techniques, among which the oxalate and DCB extractions. The amount of iron extracted by the ammonium-oxalate method was unexpectedly higher than the amount of Fe extracted by the DCB method carried out on fresh rock (Table 1). One of the possible explanations for this result could be the presence of magnetic minerals in the samples, influencing the extraction methods. This study aims at determining the influence of magnetic minerals on the ammonium oxalate extractable and DCB extractable iron. Analyses are made on bulk samples as well as thin sections of the fresh rock.

A number of studies have been dedicated to investigate the influence of magnetite on both the dithionite and oxalate extraction methods. The results are sometimes however a bit contradictory. It has been demonstrated that oxalate extraction dissolves magnetite and that


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dithionite extraction does not attack primary magnetite [10] but does attack hematite in or on the magnetic grains [19, 20, 21]. Other studies however reveal that the presence of magnetite or maghemite does influence the DCB extraction method [4, 5, 6, 7, 8].

DCB extraction depends on the extraction temperature, as well as on the concentration of the magnetic minerals [18]. Athough some distinction between fine grained maghemite and magnetite could be made the DCB extraction treatment alone was proven not to be suitable for distinction between fine-grained magnetic iron oxides [18].

It was stated [18] that the results of reported DCB extraction studies varied considerably. In some cases the DCB method was reported to dissolve only the pedogenic maghemite [5, 16, 17] while in other cases the fine-grained magnetite was dissolved as well [8]. The results of different studies were found difficult to compare, because the extraction procedure of each study was not always clearly specified. Factors such as amount of sample, type of sample, amount of dithionite and extraction temperature varied with each study.

The reductive dissolution of iron oxides is a kinetic process and factors such as pH, crystallinity and temperature have a major effect on the dissolution rate [11, 13, 22]. Therefore, results of extraction studies with differences in extraction procedures do not necessarily reflect the same dissolution behaviour. The sample type (natural or synthetic) also determines the results obtained by DCB extraction.

Chemical extractants, including acid ammonium oxalate and DCB, have also been used for studying the spatial distribution of iron and other oxides in thin sections of undisturbed soil [1, 2, 3], proving the usefulness for these techniques for extractions carried out on thin sections.


The material selected for this study consisted of dolerite samples obtained in the Central-North area of Suriname in a village called Berg en Dal (Figure 1). The dolerite boulders showing spheroidal weathering patterns were collected in the field and shells were sub-sampled in the laboratory. For this study samples of the unweathered dolerite were selected for analyses. Ammonium-oxalate extractions and DCB extractions were carried out on bulk samples, their highly magnetic fraction, and on thin sections. The highly magnetic fraction was separated from the bulk sample by passing a hand magnet over the sample at a distance of 1 cm. The highly magnetic fraction was studied using microprobe analyses, ammonium-oxalate extractions, DCB extractions, and X-Ray analyses. The extracts were measured using atomic absorption spectrophotometry (AAS).

The ammonium oxalate extraction is based on solubilisation of the amorphous sesquioxides after reduction reactions with ammonium oxalate in the dark. The method followed was retested by Schwertmann [14, 15] who found out that in the darkness the ammonium-oxalate extraction only dissolved X-ray amorphous oxides [9]. Fe, Al, Si and Mn are measured by atomic absorption spectrophotometry (AAS). A 0.2M ammonium oxalate solution and a 0.2M oxalic acid solution were prepared and mixed to obtain an ammonium oxalate-and oxalic acid mixture with pH = 3. The sample (250 mg) was weighed in a plastic centrifuge tube to which 50 ml ammonium oxalate mixture was added. This mixture was stirred in the dark for 4 hours and centrifuged during 10 minutes at 2000 rpm. The supernatant clear solution was decanted to a volumetric flask of 50 ml and the volume was made up with the oxalate mixture. This solution was used for the measurement of Fe, Al, Si and Mn. The same procedure was followed for extraction of thin sections, varying the extraction time from 4 to 6, and finally 12 hours [1, 2, 3].


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Figure 1: Location of the study area Berg en Dal in Suriname (Modified after [12])


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Using the DCB extractions, amorphous coatings and crystals of free iron oxides and other sesquioxides are removed using sodiumdithionite as reducing agent. The removal of free iron oxides aids in dispersion of the silicate proportion [11]. The DCB extractions were carried out following the procedure outlined by Mehra and Jackson [11]. The concentration of Fe, Al, Si and Mn are determined from a solution in which the solubilized cations are kept in solution by complexation with Na citrate. A Na citrate bicarbonate buffer is added to the sample, which is placed in a waterbath, for 20 minutes after which sodium dithionite powder (0.75 gram) is added, while stirring and the solution is again left for 20 minutes. After cooling, the mixture is centrifuged at 3000 rpm, decanted, washed, again centrifuged and decanted. The collected extraction solution is used for determination of Fe, Al, Si and Mn using AAS. The same procedure was followed for DCB extraction on thin sections. In some cases multiple DCB extractions were carried out on the same thin section. The total values for Fe, Al, Si and Mn were measured for the fresh rock using AAS.

The mineralogical composition of the opaque minerals was determined by wavelength dispersive spectrometry (WDS) microprobe analyses on uncovered thin sections and Energy dispersive spectrometry (EDS) microprobe analyses on magnetic grains, as well as X-Ray Diffraction analyses on the highly magnetic fraction. The XRD patterns were collected with a Phillips X’PERT system with a PW 3710 based diffractometer (Laboratory of Soil Science, Ghent University), equipped with a Cu tube anode, a secondary graphite beam monochromator, a proportional xenon-filled detector, and a 35-position multiple sample changer. The incident beam was automatically collimated. The irradiated length was 12 mm. The secondary beam side comprised a 0.1 mm receiving slit, a soller slit, and a 1° anti-scatter slit. The tube was operated at 40 kV and 30 mA, and the XRD data were collected in a θ/2θ geometry from 3° 2θ onwards, with a step of 0.02° 2-theta and a count time of 1 second per step. The highly magnetic samples were analysed using unoriented powder samples (3° to 60° 2θ) that were placed on a glass plate using collodium solution.

RESULTS AND DISCUSSION Mineralogical composition - Microprobe analyses In order to determine the composition of the opaque minerals, 12 WDS microprobe analyses were carried out in thin sections. All analysed grains are Fe-Ti oxides. Three analyses gave Fe/Ti ratios equal to 1, pointing to an ilmenite composition (FeTiO3). For the remaining analyses, the Fe/Ti ratio was close to 2, which is compatible with an ulvospinel composition (Fe2TiO4). Investigation of the opaque grains at a magnification of 400 times shows the intergrowth of ulvospinel in a mass of ilmenite. EDS microprobe analyses of the highly magnetic fraction give similar results, and point to an ulvospinel composition. Mineralogical composition – X-Ray Diffraction The mineralogical composition of the highly magnetic fraction was determined using X-ray diffraction. The X-Ray diffraction pattern obtained is presented in Figure 2. The peaks indicate the presence of spinel, magnetite and/or (titanian) maghemite. The peaks do not indicate the presence of ilmenite.


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Oxalate and DCB extraction on samples Table 1 shows the results of the extractions carried out on the samples. The higher amounts of oxalate extractable iron in the bulk samples as apposed to the amounts of DCB extractable iron are clear. The same can be stated for Al2O3. In order to infer whether the difference can be attributed to the presence of magnetic minerals in the fresh rock, the analyses were repeated on magnetic fractions.

0

50

100

150

200

250

300

350

400

15 18 21 24 27 30 33 36 39 42 45 48 51 54 57 60

2θ

Inte

nsity

0.48

3 S

p/M

t/Mgt

0.37

4 M

gt

0.33

6 M

gt0.

322

u 0.31

8 u

0.29

6 S

p/M

t/Mgt

0.27

5 Ilm

/Mgt

0.25

2 S

p/M

t/Mgt

0.24

2 S

p/M

t/Mgt

0.22

3 M

gt

0.20

9 S

p/M

t/Mgt

0.17

2 S

p/M

t

0.16

1 S

p/M

gt

0.18

7 u

0.21

4 u

Figure 2: XRD Diffraction pattern for highly magnetic samples , Sp: Spinel, Mt: Magnetite, Mgt:

maghemite, U: Unidentified

DB1-C: Bulk Sample DB1-C: highly magnetic sample Wt % Fe2O3DCB 1.73 4.64 Fe2O3OX 3.91 12.42 Fe2O3-total 15.60 - Al2O3DCB 0.18 0.14 Al2O3OX 0.52 0.31 Al2O3-total 12.80 - MnO2DCB 0.01 0.01 MnO2OX 0.01 0.02 MnO2-total 0.23 - SiO2DCB 0.90 0.32 SiO2Ox 0.49 0.27 SiO2-total 48.90 -

Table 1: Total oxide values, ammonium-oxalate and DCB extractable oxides in bulk and magnetic samples


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Figure 3: Image of untreated section (A), ammonium-oxalate treated section (B) and DCB treated section (C)

The results indicate that the oxalate extractable Fe and to some extend Al are much higher than the DCB extractable ones. Oxalate and DCB extractions on thin sections After treatment of the thin sections digital photographs were taken in order to visually detect changes in the minerals present. Figure 3 gives three photomicrographs of the fresh rock, one before treatment (A), one after 4 hours of oxalate treatment (B) and one after DCB treatment (C), each taken in plain polarised light.

The fresh rock is composed of predominantly lathshaped plagioclases which are colourless and bright in the pictures. The second most abundant are the pyroxenes, which are also colourless but have higher relief as compared to the plagioclases. The treatments were focused on the black opaque grains of either ulvospinel or ilmenite composition.

After the ammonium-oxalate treatment the thin section appears brighter. The opaque grains show no visible changes. There is however the appearance of a black spot (outlined with an ellipse) that was not present in the untreated sample. After DCB treatment the section is far less bright, the black spot is no longer present and no changes have been noticed in the opaque grains. The DCB and oxalate extractions on thin sections of fresh rock material did not show any sign of mineral dissolution. For this reason the oxalate extraction period was extended to 6, 8 and 12 hours, however still without signs of apparent dissolution.

CONCLUSIONS AND DISCUSSION This study demonstrates that the amount of oxalate extractable Fe was much greater than the DCB extractable Fe. These differences are even more pronounced in the magnetic fraction


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suggesting influence from the magnetic fraction. The XRD pattern of the magnetic fraction point to the presence of magnetite, spinel or maghemite. The percentage of the magnetic fraction was however not determined. The data presented does suggest attack of the magnetic mineral (ulvospinel) by the oxalate solution. The higher values for DCB extractable iron measured in the magnetic fraction, also point to attack of the magnetic grains by the DCB extraction technique. This means that Fe values obtained from samples containing a magnetic mineral (magnetite or ulvospinel) can be overestimated. The XRD pattern of the magnetic fraction did not point to the presence of ilmenite, and consequently the influence of ilmenite was not investigated. Although this is apparent in the chemical data the extractions on the thin sections do not reveal attack or dissolution of the opaque (and possibly magnetic) mineral. A possible dissolution of the opaque grains should be confirmed by studying the thin sections using scanning electron microscopy and microprobe analyses before and after treatment. This would also investigate the influence of ilmenite on the extraction techniques.

REFERENCES

[1] J.M. Arocena, G. De Geyter, C. Landuyt and U. Schwertmann. “Dissolution of soil iron oxides with ammoniumoxalate: comparison between bulk samples and thin sections”. Pedologie, 29, pp. 275-297, (1989) [2] J.M. Arocena, G. De Geyter, C. Landuyt and G. Stoops. “A Study on the Distribution and Extraction of Iron and Manganese in soil thin sections”. In: Douglas L.A (ed.). Soil Micromorphology: A Basic and Applied Science. Elsevier, Amsterdam, pp. 621-626, (1990) [3] P. Bullock, P.J. Loveland and C.P. Murphy. “A technique for selective solution of iron oxides in thin sections of soil”. Journal of Soil Science, 26: 247-248, (1975). [4] P. Fine, and M.J. Singer. “Pedogenic factors affecting magnetic susceptibility of northern California soils”, Soil Science Society of America Journal, 53, pp. 1119-1127, (1989). [5] P. Fine, M.J. Singer, R. La Ven, K.L. Verosub and R.J. Southard. “Role of pedogenesis in distribution of magnetic susceptibility in two California chronosequences”, Geoderma, 44, pp. 287-306, (1989). [6] P. Fine,. M.J. Singer and K.L. Verosub. “Use of magnetic susceptibility measurement in assessing soil uniformity in chronosequence studies”, Soil Science Society of America Journal, 56, pp. 1195-1199, (1992). [7] P. Fine, M.J. Singer, K.L. Verosub and J. TenPas. “New evidence for the origin of ferrimagnetic minerals in loess from China”, Soil Science Society of America Journa, 57, pp. 1537-1542, (1993). [8] C.P. Hunt, M.J. Singer, G. Kletetschka, J. TenPas and K.L. Verosub. “Effect of citrate–bicarbonate–dithionite treatment on fine-grained magnetite and maghemite”, Earth and Planetary Science Letters, 130, pp. 87–94, (1995). [9] J.A. McKeague, and J. H. Day. “Dithionite and oxalate extractable Fe and Al as aids in differentiating various classes of soils”, Canadian Journal of Soil Science, 46, pp. 13-22, (1966). [10] J.A. McKeague, J.E. Brydon and N.M. Miles. “Differentiation of forms of extractable iron and aluminium in soils”, Soil Science Society of America Proceedings, 35, pp. 33-38, (1971). [11] O.P. Mehra, and M.L. Jackson. “Iron oxide removal from soils and clays by a dithionite–citrate system buffered with sodium bicarbonate”, Clays and Clay Minerals., 7, pp. 317–327, (1960). [12] Narena-Celos. Suriname kaarten collectie, 1p., (2004). [13] D. Postma. “The reactivity of iron oxides in sediments: a kinetic approach” Geochimica Cosmochimica Acta, 57, pp. 5027–5034, (1993). [14] U. Schwertmann. “Differenzierung der Eisenoxide des Bodens durch photochemische Extraktion mit saurer Ammoniumoxalat-Lösung”. Z. Pflanzenernähr. Düng., Bodenkunde, 105, pp. 194-202, (1964). [15] U. Schwertmann. “Use of oxalate for Fe extraction from soils”. Canadian Journal of Soil Science., 53: pp. 244-246, (1973) [16] M.J. Singer and P. Fine. “Pedogenic factors affecting magnetic susceptibility of Northern California soils”, Soil Science Society of America Journal, 53, pp. 1119–1127, (1989). [17] M.J. Singer, L.H. Bowen, K.L. Verosub, P. Fine and J. TenPas. “Mössbauer spectroscopic evidence for citrate–bicarbonate–dithionite extraction of maghemite from soils”, Clays and Clay Minerals, 43, pp. 1-7, (1995). [18] I.H.M. van Oorschot, and M.J.Dekkers. “Dissolution behaviour of fine-grained magnetite and maghemite in the citrate–bicarbonate–dithionite extraction method”, Earth and Planetary Science Letters, 167, pp. 283–295, (1999).


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[19] I.H.M. van Oorschot and Mark J. Dekkers. “Selective dissolution of magnetic iron oxides in the acid–ammonium oxalate/ferrous iron extraction method—I. Synthetic samples, Geophysical Journal International, 145, pp. 740–748, (2001). [20] I.H.M. van Oorschot, M. J. Dekkers and P. Havlicek,. Selective dissolution of magnetic iron oxides with the acid-ammonium-oxalate/ferrous-iron extraction technique—II. Natural loess and palaeosol samples . Geophyisical Journal International, 149, pp. 106–117, (2002). [21] A.L. Walker. “The effects of magnetite on oxalate and dithionite extractable iron”, Soil Science Society of America Journal, 47, pp. 1022-1026, (1983). [22] B. Zinder, G. Furrer and W. Stumm. “The coordination chemistry of weathering, II. Dissolution of Fe(III) oxides”, Geochimica Cosmochimica Acta, 50, pp. 1861–1869, (1986).


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Sub-theme : DEVELOPMENTS IN SOIL MICROMORPHOLOGY

Stoops, G., Marcelino, V., Mees, F.

Department of Geology and Soil Science, Ghent University, Gent, Belgium

Abstract This contribution brings an overview of latest research in soil micromorphology conducted at the Department of Geology and Soil Science of the Ghent University, and a short introduction to two important current themes in this field.

INTRODUCTION

Although soil microscopy has been totally excluded from the new curriculum of “Physical Land Resources” studies in Ghent, research in this field is still being continued.

Apart from applications of micromorphological techniques to soil genesis and development [1-23] and to archaeology (the latter especially by Prof. R. Langohr and co-workers), attention has also been paid to the development and/or critical evaluation of special methodologies such as image analysis and X-ray-tomography, and observation and description techniques. A book on genetic interpretation of micromorphological data is in progress (Stoops et al.).

APPLICATIONS IN SOIL GENESIS AND DEVELOPMENT Amongst the applications in soil genesis and development the following will be summarised: 1° circumgranalar bassanite formation around quartz grains in a natural gypsum crust. Heating experiments suggest that differences in heat capacity between the components can explain the observed patterns, but in the natural crust they were found to be related to the availability of space around the enclosed detrital mineral grains. Coatings of the studied type, or derived relict features, are potential palaeosurface indicators [9]. 2° zeolite neoformation in the Olduvai (Tanzania) stratigraphic sequence of lacustrine and fluvial sediments, related to the interaction of volcanic material with saline alkaline lake water or groundwater [10]. The conditions formation of the various zeolite minerals were investigated (analcime, chabazite, phillipsite, erionite, clinoptilolite), based on their mode of occurrence, including their relationship with other pedogenic materials. 3° differentiation of pedogenic and geogenic calcite in soils from Iran, using UV and blue light fluorescence techniques combined with cathodoluminescence [7]. 4° impact of land use (forest, afforested pasture and crop land) and seasonal freezing on the (micro)morphological properties of silty Norwegian soils [20]: platy and lenticular microstructures due to frost are present in the upper part of all soils studied but occur at shallowest depth (35 cm) under forest than in the other soils (50 cm); planar voids associated with these structures are not or partially accommodating, meaning that when the soil is wet they do not completely close and water can still move parallel to the soil surface. Dusty clay coatings (agricutans) and infillings and compound layered infillings are observed immediately below the plough layer in the cropland but not at the same depth in the other soils. They thus reflect the increased internal soil erosion associated with cultivation.


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5° soil evolution on volcanic ash in Europe [19, 22]: as a first step coatings of fine material develop around the coarse particles (chitonic c/f related distribution pattern), or form hypo-coatings in the case of pumice; with increasing amount of fine material an enaulic c/f r.d.p. is formed, that gradually grades into a fine granular microstructure. The latter is preserved as an intrapedal microstructure in the more clayey Bw horizons where a (sub)angular blocky microstructure prevails. In the case of Icelandic soils a lenticular microstructure developed, related to freeze-thaw cycles [21] and a microstratification, often with organic layers, is throughout preserved, pointing to the quasi absence of biological activity, in contrast to what happens in temperate and tropical areas [1]. The transformation of volcanic glass to alteromorphs of allophane, with a palagonite like appearance, is discussed [2]. Throughout the profiles an undifferentiated b-fabric is noticed in the fine mass of the European soils on volcanic ash. Alteration products of volcanic ash in Mexico give rise to specific opaline features [3, 4]. 6° research on micromorphological concepts and terminology lead to the publication of a new manual [19], in order to replace the standard work of Bullock et al. (1985) out of print since many years.

IMAGE ANALYSIS Presently, low-cost software-based image analysis systems make automated analysis of soil pore space and other features very attractive. Large amounts of data on feature characteristics can be easily generated. Although it is currently possible to use 3D image analysis associated with non-destructive tools such as X-ray CT to observe and quantify soil porosity, 2D image analysis procedures are still commonly applied because of their lower cost and easier accessibility. With the aim of investigating whether different sorts of images analysed with different methods produce comparable results, three widely used sample preparation and image acquisition procedures and three 2D-image analysis methods with different levels of manual intervention were compared. The quality of the image, determined by the image acquisition and sample preparation method used, affects average porosity measurements significantly: fluorescent images compared with BSE-images clearly underestimate porosity. On the other hand, different interventions and methods used to increase image quality and to segment images also affect porosity measurements significantly. Moreover, in the particular case of manual thresholding, porosity values obtained by the same observer are more reproducible than those from different observers. These results stress the need for standardization of image analysis protocols and warn of the dangers of comparing soil porosity measurements performed on different types of images.

X-RAY TOMOGRAPHY X-ray computed tomography (X-ray CT) is a non-destructive imaging technique that provides information about the internal structure of objects. X-ray CT images are obtained by recording radiographs for successive positions during step-wise rotation of a sample relative to an X-ray source and a detector. These radiographs are then used to create images showing variations in X-ray attenuation values, determined by density and element composition, for cross-sections perpendicular to the axis of rotation. One of the advantages of X-ray CT is the


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possibility of obtaining a large number of parallel cross-sections, which can be used for 3D imaging and analysis.

Since its development as a medical technique, X-ray CT has been applied in various other fields of research, including earth sciences and engineering (e.g. [28]). In soil science, it has mainly been used for the study of pore characteristics. Aspects of soil porosity that have been investigated with X-ray CT include the effects of faunal activity (e.g. [24]), soil compaction (e.g. [27]), erosion control measures (e.g. [31]), and tillage practices (e.g. [30]). Examples of other applications are the study of root development (e.g. [26]), water movement (e.g. [25]), and soil surface morphology (e.g. [25]).

Ghent University has X-ray CT facilities for material research, operated by the Department of Geology and Soil Science and the Department of Subatomic and Radiation Physics. The available scanners can handle a wide range of sample types, for studies requiring CT images with specific requirements regarding spatial resolution and material contrasts.

REFERENCES Most important micromorphological contributions from the Department of Geology and Soil Science over the last five years [1] Fauzi, A.I., Stoops, G. Influence of Krakatau ash fall on pedogenesis in West Java. Example of a toposequence in the Honje Mountains, Ujung Kulon Peninsula, Catena, 56, 45-66, (2004). [2] Gérard, M., Caquineau, S., Pinheiro, J., G. Stoops. Weathering and allophane neoformation in soils on volcanic ash from the Azores, Europ. J. Soil Sci.(in press). [3] Gutierrez Castorena, M.d.C., Stoops, G., Ortiz Solorio, C.A., Lopez Avila, G. Amorphous silica materials in soils and sediments of the Ex-Lago de Texcoco, Mexico. An explanation of its subsidence, Catena, 60, 205-226, (2005). [4] Gutierrez Castorena, M.d.C., Stoops, G., Ortiz Solorio, C.A., Sanchez-Guzman, P. Micromorphology of opaline features in soils on the sediments of the Ex-Lago de Texcoco, Mexico, Geoderma, 132, 89-104, (2005). [5] Heidari, A., Mahmoodi, Sh., Stoops, G., Mees, F. Micromorphological characteristics of Vertisols in Iran, including non-smectitic soils, Arid Land Research and Management, 19, 29-46, (2005). [6] Khormali, F., Abtahi, A., Mahmoodi, S., Stoops, G. Argillic horizon development in calcareous soils of arid and semi-arid regions of southern Iran, Catena, 53, 273-301, (2003). [7] Khormali, F., Abtahi, A., Stoops, G.. Micromorphology of calcitic features in highly calcareous soils of Fars Province, Southern Iran, Geoderma, 132, 31-46, (2006). [8] Marcelino V., Cnudde V., Vansteelandt S., Carò F.. An evaluation of 2D-image analysis techniques for measuring soil microporosity, European Journal of Soil Science (in press). (2006). [9] Mees, F., Stoops, G. Circumgranular bassanite in a gypsum crust from eastern Algeria - a potential palaeosurface indicator, Sedimentology, 50, 1139-1145, (2003). [10] Mees, F., Stoops, G., Van Ranst, E., Paepe, R., Van Overloop, E. The nature of zeolite occurrences in deposits of the Olduvai Basin, northern Tanzania, Clays and Clay Minerals, 53,659-673,. (2005). [11] Mees, F., De Dapper, M. Vertical variations in bassanite distribution patterns in near-surface sediments, southern Egypt, Sedimentary Geology, 181, 225-229, (2005). [12] Mees, F. Salt mineral distribution patterns in soils of the Otjomongwa pan, Namibia, Catena, 54, 425-437, (2003). [13] Mees, F., Singer, A. Surface crusts on soils/sediments of the southern Aral Sea basin, Uzbekistan, Geoderma, (in press). [14] Mulyanto, B., Stoops, G.. Mineral neoformation in pore spaces during alteration and weathering of andesitic rocks in humid tropical Indonesia, Catena, 54, 385-392, (2003). [15] Oleschko, K., Parrot, J-F., Ronquillo, G., Shoba, S., Stoops,, G. Marcelino, V. Weathering: towards a fractal quantifying,. Mathematical Geology,. 51: 607-627, (2004). [16] Stoops, G., Van Ranst, E., Verbeek, K. Pedology of soils within the spray zone of the Victoria Falls (Zimbabwe), Catena, 46, 63-83, (2001). [17] Stoops, G.,. Achievements in micromorphology,. Catena, 54, 317-319, (2003).


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[18] Stoops, G. Guidelines for the Analysis and Description of Soil and Regolith Thin Sections. SSSA. Madison, WI., 184pp + CD. ISBN 0-89118-842-8, (2003). [19] Stoops, G., Gérard, M., Micromorphology. In: Arnalds, O., Bartoli, F., Buurman, P., Garcia-Rodeja, E., Oskarsson, H., Stoops, G. (eds), Soils of Volcanic Regions of Europe, (in press). [20] Stoops, G., D. Dedecker. Microscopy on undisturbed sediments as a help in planning dredging operations. A case study from Thailand. Proceedings International Conference Pnom Penh, KAOW. (in press). [21] Stoops, G., Gérard, M., Arnalds, O. A micromorphological study of andosol genesis in Iceland, Geoderma, (accepted). [22] Stoops.G. Micromorphology of soils on volcanic ash in Europe. A review and synthesis. Europ. J.Soil Science, (accepted). [23] Sveistrup T. E., Haraldsen T.K., Langohr R., Marcelino V., Kværner J.. Land use impact on seasonally frozen silty soils in South Eastern Norway, Soil and Tillage Research, 81: 39-56, (2005). Cited papers – X-ray tomography [161] Bastardie, F., Capowiez, Y., Cluzeau, D. 3D characterisation of earthworm burrow systems in natural

soil cores collected from a 12-year-old pasture. Applied Soil Ecology 30, 34-46, (2005). [162] Fohrer, N., Berkenhagen, J., Hecker, J.M., Rudolph, A. Changing soil and surface conditions during

rainfall - Single rainstorm/subsequent rainstorms, Catena, 37, 355-375, (1999). [163] Gregory, P.J., Hutchison, D.J., Read, D.B., Jenneson, P.M., Gilboy, W.B., Morton, E.J. Non-invasive

imaging of roots with high resolution X-ray micro-tomography, Plant and Soil, 255, 351-359, (2003). [164] Langmaack, M., Schrader, S. & Rapp-Bernhardt, U., Kotzke, K. Soil structure rehabilitation of arable

soil degraded by compaction, Geoderma, 105, 141-152, (2002). [165] Mees, F., Swennen, R., Van Geet, M., Jacobs, P. (eds). Applications of X-ray Computed Tomography

in the Geosciences. Geological Society Special Publication 215, 328 pp. Geological Society Publishing House, Bath, United Kingdom. (2003).

[166] Mooney, S.J. Three-dimensional visualization and quantification of soil macroporosity and water flow patterns using computed tomography, Soil Use and Management, 18, 142-151, (2002).

[167] Pedrotti, A., Pauletto, E.A., Crestana, S., Holanda, F.S.R., Cruvinel, P.E., Vaz, C.M.P. Evaluation of bulk density of Albaqualf soil under different tillage systems using the volumetric ring and computerized tomography methods, Soil & Tillage Research, 80, 115-123, (2005).

[168] Rachman, A., Anderson, S.H., Gantzer, C.J., Computed-tomographic measurement of soil macroporosity parameters as affected by stiff-stemmed grass hedges, Soil Science Society of America Journa, 69, 1609-1616, (2005).

Some new publications on micromorphology [169] Eswaran, H., Drees, R. Soil under the Microscope: Evaluating Soil in Another Dimension. CD. Soil

Micromorphology Committee of the Soil Science Society of America. [170] FitzPatrick, E.A., Soil Microscopy and Micromorphology. CD. Interactive Soil Science, 76 Burns Road,

Aberdeen, AB15 4NS, UK, (2006) [171] Kapur, S., Mermut, A., Stoops, G., (Eds.), Special Issue of Geoderma (papers presented during the

International Working Meeting on Soil Micromorphology, 2004, Adana, Turkey) (in preparation [172] Stoops, G. (Ed.), Achievements in Micromorphology. Special Issue of Catena, Vol. 54, Issue , pp 317-

678 (papers presented during the International Working Meeting on Soil Micromorphology, 2001, Gent, Belgium) (2003)


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SPHEROIDAL WEATHERING OF DOLERITE IN SURINAME: EVIDENCE FROM PHYSICAL, CHEMICAL AND

MINERALOGICAL DATA

C. G. Algoe 1*, E. Van Ranst 2, G. Stoops 3

1* Anton de Kom Universiteit van Suriname, Faculteit der Technologische Wetenschappen, POB 9212, Paramaribo, Suriname, Tel: +597 465558 ext. 413, Fax: +597 495005, Email: [email protected]

2 Laboratorium voor Bodemkunde, Universiteit Gent, Krijgslaan 281, S8, B-9000 Gent, Belgium 3 Laboratorium voor Mineralogie, Petrologie en Micropedologie, Universiteit Gent, Krijgslaan 281, S8 B-9000

Gent, Belgium

Poster Extended Abstract Suriname consists geologically for about 80 % of a Precambrian basement, the Guiana shield. At numerous places this shield is intersected by Permo-Triassic NS striking dolerite dike suites. In the regolith they appear as spheroidally weathered boulders with an “onion-skin” fabric.

Four weathered boulders were collected in profiles near the locality Berg en Dal and shells of different weathering grades sub-sampled in the laboratory. These shell-samples were analysed using physical, chemical and mineralogical methods in order to characterize the spheroidal weathering process and the resulting weathering products. The chemical analyses comprise total elemental contents, oxalate and dithionite-citrate-bicarbonate extractions, cation exchange capacities and pH values. The mineralogical data is obtained from thin section studies, WDS microprobe analyses, X ray diffraction data, and scanning electron microscopy.

The bulk densities show a vast decrease with increasing weathering grade. The total elemental data show a progressive and complete loss of the alkaline and earth alkaline elements in course of the weathering process. These data also allow the calculation of a number of weathering indices, used to define the behaviour of elements during the weathering process. The total elemental data and bulk densities are used to calculate the isovolumetric weathering in the boulders. Special attention is given to the behaviour of both free and amorphous Fe as revealed from the oxalate and dithionite-citrate-bicarbonate extractions.

The unweathered parent material consists predominantly of lath-shaped plagioclases (andesite and labradorite), pyroxenes (augite and pigeonite), chlorites, opaque minerals (ilmenite and titanomagnetite), granophyric intergrowths of quartz, feldspars, apatite and ilmenite. In addition amphiboles and apatite occur in small amounts. All mineral data of the weathered samples point to an end system with residual weathering products consisting mainly of clay minerals (kaolinite and chlorite) and Fe- and Al-hydroxides (goethite and gibbsite). Weathering of minerals takes place abruptly, and although the original minerals are completely altered, their alteromorphs can still be recognised in the thin sections upto the latest weathering stages.

The isovolumetric condition of spheroidal weathering and the mobility of Al and Ti in the weathering system are discussed as well as the in situ character of the boulders based on the sharp contrasts in data between weathered dolerite samples and the residual soil. Another point of discussion is the influence of magnetic minerals on the oxalate and DCB extractable components.


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MICROMORPHOLOGICAL CHARACTERISTICS OF ANDISOLS IN WEST JAVA, INDONESIA

Mahfud Arifin*, Rina Devnita

Dept. of Soil Science, Faculty of Agriculture, Padjadjaran University, Bandung, Indonesia

[email protected] Tel. ++62-22/779.63.16 Fax. ++62-22/779.63.16; ++62-22/779.72.00

Abstract Micromorphological characteristics have been studied for six pedons of Andisols developed in volcanic materials in West java, Indonesia. The pedons represent deposits of different volcanoes (Mt.Tangkuban Perahu A and C, Mt. Patuha, Mt. Kendeng, Mt. Papandayan, Mt. Guntur), with different ages (Pleistocene, Holocene) and different types of volcanism (andesitic, basaltic), in three agroclimatic zones (A, B1, B2). Undisturbed soil samples for thin section preparation were taken from every identifiable horizon (49 samples in total). Observations were made with a magnifying lens, binocular stereomicroscope, polarization microscope, and scanning electron microscope. The results demonstrate that the study of micromorphological characteristics is very useful to identify pedogenetic processes in Andisols.

INTRODUCTION

Soil micromorphology is a method to study undisturbed soil samples using microscopic and submicroscopic techniques to identify soil components and establish their spatial, temporal, genetic and functional relationships [3, 13].

Historically, micromorphological investigations have mainly been used for soil genesis studies, but they also have wider applications, e.g. in soil physics, biology and chemistry [3]. Two basic principles of micropedology are the use of undisturbed (oriented) samples and the concept of functional research whereby all observations are directed towards reaching as an understanding of the function of soil components and the relationship between one another.

Micropedology covers all microscopic analyses of undisturbed soil samples [14], including the study of soil thin sections, microchemical and microphysical methods, and submicroscopic techniques. The most advanced analysis is the study of the entire soil fabric (soil micromorphology) and its quantitative aspects (soil micromorphometry).

Many soil micromorphology studies have been conducted and published, especially on Ultisols, Oxisols, Spodosols and Paleosols [3]. However, research on Andisols is still rare, especially in Indonesia. Therefore, there is only a few information concerning micromorphological features of Andisols in Indonesia, particularly the Andisols developing on different parent materials and in different agroclimatic zones.

For this study, research has been done on the micromorphological characteristics of Andisols in six pedons in the tea plantation area of West Java, Indonesia. The studied soils represent six different volcanic eruptions, ages, and parent materials, in three agroclimatic zones [11].


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Pedon CTR-A2 (Acrudoxic Durudan) represents eruption C (middle Holocene) of Mt. Tangkuban Perahu (Ciater District, andesitic, agroclimatic zone A), and pedon CTR-B4 (Acrudoxic Thaptic Hydrudand) represents eruption A (early Holocene) of Mt. Tangkuban Perahu (Ciater District, andesitic, agroclimatic zone A), both located in Subang Regency. Pedon SNR-A2 (Acrudoxic Hydrudand) at Mt. Kendeng (Sinumbra District, Pleistocene, andesitic, agroclimatic zone B1), pedon SNR-B5 (Lithic Hapludand) at Mt. Patuha (Sinumbra District, Holocene, basaltic, B1), pedon SDP-A3 (Typic Hapludand) at Mt. Guntur Cs (Sedep District, Pleistocene, basaltic, agroclimatic zone B2), and pedon SDP-B5 (Hydric Thaptic Hapludand) at Mt. Papandayan (Sedep District, Holocene, basaltic, agroclimatic zone B2) are all located in Bandung Regency.

Undisturbed soil samples for the preparation of soil thin sections were obtained for every identifiable horizon in all profiles. The total number of samples was 49. Preparation of the soil thin sections involved hardening of the samples by impregnation. Observations of the undisturbed samples were made with the naked eye, a magnifier lens, binocular stereomicroscope, polarization microscope and scanning electron microscope. The terminology and concepts of the Handbook for Soil Thin Section Description [3] were used, with a few modifications.


Micromass Colour The colour of the micromass as observed in thin sections partly depends on thickness, light source properties and magnification.

In this study, only small variations in colour were observed. Horizon A/Bw has a brown to dark brown colour. Horizon BC generally has a lighter colour compared to the other genetic horizons. Surface horizons and buried A horizons have the darkest colour. In general, the horizons of pedons CTR-A2, SNR-A2, SNR-B5 and SDP-A3 have a brown colour, except pedon SDP-A3, which was lighter. Pedon CTR-B4 and SDP-B5 have a dark brown colour. The micromass colour in the thin sections was generally more brownish than the field soil capacity colour. Rainfall, age and parent material appear to have no significant effect on micromass colour. However, in Ciater District pedon CTR-A2 generally has a lighter colour than CTR-B4, in Sinumbra District pedon SNR-A2 has a lighter colour than SNR-B5, and in Sedep District SDP-A3 is lighter than SDP-B5. This indicates that the older parent materials have a lighter colour than the younger parent materials. Microstructure Microstructure refers to the shape, size and arrangement of soil aggregates and pores, generally observed at rather low magnification. Pedality The complete results of observation of the microstructure are presented in Table 1. Some examples of soil microstructure features are presented in Figure 1. The microstructure of the Andisols ranges from granular to massive. The surface horizon generally has crumb and


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granular microstructures (Fig. 1.a and 1.b), whereas the subsurface horizon has a blocky to subangular blocky microstructure.

The surface horizons (Ap) of soils developed in areas with high rainfall (e.g. Ciater) have a more strongly developed pedality (and darker colour) than those developed in relatively drier areas (Sinumbra and Sedep), which generally also have a lighter colour and tend to show rounded and subangular peds. This suggests a relationship between organic matter content and pedality. Besides, the granular peds in the Ap horizon of soils developing on older parent materials are generally larger and have a denser groundmass than the younger soils. Chemical analysis indicates that the Ap horizon has a high organic carbon content and also contain Al- and Fe-bearing organic complexes. Those materials are predicted to play a role in forming a stable granular microstructure. In all horizons, the size of the peds shows a rather wide range (0.02-11.00 mm). The degree of accommodation ranges from well accommodated to unaccommodated, and is generally partly accommodated (Fig. 1.f). Types of voids In surface horizons, compound packing voids are observed (Fig. 1.a and 1.b). The voids are equant to elongate, interconnected, occurring between granular, crumb and angular blocky peds, which are unaccommodated. Other void types that are recognized are planar voids, chambers and vughs (Fig. 1.a, 1.b, 1.f)

Subsurface horizons, which show crumb, granular or angular blocky microstructures, with or without pores, generally have planar voids, or planar voids with compound packing voids (Fig. 1.f). In a subsurface horizon (A’’, Bw) developed on old parent material (e.g. pedon SNR-A2 and SDP-A3), planar voids, vughs, channels, chambers and vesicles are recognized. a

b

c

d


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e

f

g

h

Figure 1. Photomicrograph of thin section with plane polarized light. Hor. Ap, CTR-A2 (a); Hor. Ap, SNR-B5 (b); Hor B’wb, SDP-A3 (c); Hor. 2Ab SNR-A2 (d); Hor. 3Ab, CTR-A2 (e); Hor. Ap, SNR-A2

(f); Hor. A’b2, SDP-A3 (g); Hor. Bw SDP-A3 (h)

Planar voids in the surface horizon (Ap) generally developed along roots residues or microfauna remains. In the subsurface horizon, planar void mainly formed by development of cracks in dense groundmass material. Abundance of voids The abundance of voids in the thin sections was determined, expressed as percentage of the total area of the thin section [5]. The results show that surface horizons have a higher porosity than the subsurface horizons. Hence, the percentage of voids decreases with depth. This can be clearly seen in old pedons such as SNR-A2 and SDP-A3. This was predicted referring to processes of infilling of voids by illuvial material derived from the groundmass by


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percolation of water, gravity, and biological activity, taking place during a long period. Therefore several pores have been closed by material derived from upper horizons. Related Distribution Patterns Horizons in Andisols have porphyric and enaulic c/f related distribution patterns, i.e. they are composed of coarse material embedded in finer material (porphyric) or they have a skeleton of larger fabric units with aggregates of fine material in the interstitial spaces (enaulic) [1,8]. In the latter, the aggregates do not completely fill the interstitial spaces, and the larger units support each other.

Surface horizon generally have enaulic c/f related distribution patterns (Fig. 1.a and 1.b), especially in Andisols developed on young parent materials. Andisols developed from old parent material have porphyric c/f related distribution patterns in their surface horizon. The granular or crumb structure in the surface horizon could be related to high biological activity (e.g. termites, ants), and the intensive growth of roots. The allophane content in the surface horizon is generally lower than in subsurface horizons due to the strong accumulation of organic matter in the surface horizon, preventing the formation of allophanes because of the formation of Al-humus complexes [9].

The subsurface horizons have porphyric c/f related distribution patterns. These horizons have a high total density, with porous and non porous parts. Pores in the porous parts can be filled with material derived from upper horizons. With time, they can develop into non-porous materials in this way.

Pedons SNR-A2 and SDP-A3 have porphyric c/f related distribution patterns (Fig. 1.c and 1.d). Both pedons represents the older parent materials. The partly short range-order minerals have been weathered to crystalline minerals like halloysite, metahalloysite and gibbsite. The change in mineral composition was predicted to be accompanied by a change in c/f related distribution pattern from enaulic to porphyric.

The subsurface horizons of pedon CTR-B4 still have enaulic c/f related distribution patterns, although the age of this pedon is older than that of CTR-A2, which shows porphyric c/f related distribution patterns. This indicates that the accumulation process in the subsurface horizons (pedon CTR-A2) was intensive due to the presence of impervious layers that prevent transportation of material to the lower horizons.

Pedon/ Hor.

Depth (cm)

Shape Size (mm)

Pedality Acc. Proportion(%)

Pedon CTR-A2 Ap 0-17 gr 0.042-0.2 s no 80 ab 0.4-4.0 w pr 20 Bw 17-31 gr 0.04-0.4 m-w no 45 sab 0.4-1.6 w pr 55 BC 31-43 ab-sab 1.6-2,8 w pr 30 gr 0.4-0.8 w no 30 gr 0.04-0.12 w no 40 2Ab 43-60 gr < 0.08 w-m pr 20 gr 0.4-0.8 w-m pr 40 gr 1.6-2.4 w no 40 2Bw 60-70 cr-gr 0.04-0.2 m-s pr 40 ab 0.08-4.4 m-s pr 60 2BC 70-94 mv - - - 90 ab - m no 10


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3Ab 94-110 sab 0.4-0.8 m pr 40 cr 0.04-1.2 w no 60 3Bw 110-128 ab 4.8 s-m pr 80 gr 0.08-0.4 s-m no 20 Pedon CTR-B4 Ap 0-15 gr 0.04-0.2 m no 60 gr 0.2-0.4 m no 20 gr 0.4-3.2 m no 20 Bw 15-30 cr 0.04-11.0 m no 70 ab 2.0-5.0 m no 30 BC 30-38 mv - - - 100 2Ab 38-52 cr 0.02-0.04 m no 80 ab 0.4-1.0 m pr 20 2BCb1 52-65 gr 0.02-0.2 m no 60 ab 0.7-2.0 m pr 40 2BCb2 65-90 ab 5.0 m pr 100 2A’b1 90-105 ab 0.04-0.4 m pr 50 ab 1.0-7.0 m pr 50 2A’b2 105-120 ab 1.0-8.0 m pr 85 gr 0.04-0.8 m no 15 Pedon SNR-A2 Ap 0-10 gr 2.0-3.0 m no 100 Bw1 10-23 ab 2.0-5.0 s no 50 sab 5.0-5.9 s no 50 Bw2 23-40 ab 3.0-5.0 s gd 100 Bw3 40-54 sab 1.0-10.0 s pr 70 BC 54-73 sab 5.0-10.0 m pr 70 2Ab 73-84 ab,sab 5.0-7.0 m pr 80 2BCb 84-98 ab 2.0-7.0 m pr 100 2A’b -120/130 ab 2.0-3.0 m pr 80 2BC’b -142/148 sab,ab 1.0-2.5 m pr 100 Pedon SNR-B5 Ap 0-10 ab,sab 0.04-4.0 m pr 70;30 Bw 10-19 ab,gr 0.04-3.6 m pr 70;30 A’b 19-44 ab,gr 0.2-1.2 m pr 70;30 Bcb 44-60 ab,sab 0.5-5.0 m pr Pedon SDP-A3 Ap 0-14 ab 1.0-5.0 m pr 100 A2 14-24 ab,gr 1.0-4.0 m no 50:50 Bw 24-35 ab 0.05-5.0 m pr 60 gr 0.12-0.24 m pr 40 A’b1 35-46 ab 1.0-10.0 m gd 100 A’b2 46-65 ab 0.1-5.0 m pr 100 B’wb 65-81 ab 0.4-10.0 m gd 100 A”b 81-95 ab 1.0-5.0 m pr 100 B”wb 95-105 ab 0.4-2.8 m pr 100 BCb 105-130 ab,mv - w pr Pedon SDP-B5


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Ap 0-11 sab 1.0-8.0 m pr 100 Bw 11-30 gr,sab - m pr 25:75 A’b 30-45 sab,gr - m pr 70:30 B’wb 45-54 sab 0.2-2.4 m pr 70 gr 0.08-2.4 m pr 30 A”b1 54-72 sab - s pr 100 A”b2 72-94 sab 0.2-1.0 m pr 70 gr 0.02-0.04 m pr 30 B”wb 94-115 sab 7.0-8.0 m pr 100 BCb 115-135 sab 0.4-4.00 m pr 100 A”’b 135-152 sab 0.4-2.4 s pr 100

Table 1. Shape and size of aggregates, degree of pedality and accommodation of the studied profiles. ab; angular blocky;sab subangular blocky; gr granular; cr crumb; mv massive; w weak; m medium; s

strong; pr part; gd good; no non Pedofeatures and weathering features The types of pedofeatures that have been recognized are textural, amorphous and cryptocrystalline, fabric and excrement pedofeatures [3,4]. Weathering of primary mineral grains is also considered in this chapter. Table 2 gives a detailed overview of the pedofeatures observed in every studied horizon.

The features most commonly found in Andisols are the weathering of primary minerals and the illuviation and accumulation of material derived from upper horizons, as found by Goenadi and Tan [6, 7]. Illuvial material can be material derived from the groundmass, or fine organic material mixed with silt to very fine sand (Fig. 1.c and 1.d). In addition, humic substances quite often penetrate the groundmass. These pedofeatures are generally found in the site with young parent material and high rainfall (Ciater), or in the horizon directly underlying the buried A horizon (thaptic) (Fig. 1.e).

The other features generally found were the strong alteration of primary mineral, e.g. minerals susceptible to physical and chemical weathering in A, B, and BC horizons. Physical weathering can be in the form of fragmentation. Chemical weathering can be recognized by the change of form or colour of the mineral grains. Mineral grains in pedons originated from old parent material generally have anhedral shapes (and low c/f2µ ratios), whereas grains in younger pedons usually have subhedral to euhedral shape (and higher c/f2µ ratios). Iron nodules are found in old pedon like SDP-A3 in Sedep (Fig. 1.g). The nodules were formed by residual accumulation of iron compounds, related to weathering of primary minerals. Gibbsite coatings (Fig. 2.a) are found in Acrudoxic Hapludand.

Weak indications for clay illuviation are only recognized for the B’wb horizon in pedon SDP-A3, originated from old parent material, and in horizon 2BCb of pedon SNR-A2 (Fig. 2.b). These horizons do not fulfill the prerequisite of an argillic horizon in Soil Taxonomy [12] due to the small total volume of illuvial clay (< 1 %) and the low degree of orientation within the clay coatings. Maeda et al [10] also reported a few coatings in Andisols. Mohr et al [11] proposed that Andisols often include a horizon with clay accumulation.


303

Pedon/horizon Pedofeatures and weathering features (and plant remains) CTR-A2 Ap Partly weathered primary minerals Bw Voids of root residue filled by granular groundmass material [??] Fragment of altered root, coloured brown-black at the edge BC Planar voids filled by isotropic clay mixed with very fine sand 2 Ab Fragment of yellowish weathered rock 2Bw - 2BC Plagioclase covered by opaque material 3Ab Planar void filled by a mixture of clay and very fine sand 3Bw Planar voids filled by clay Root residue, with black soil material at the edge CTR-B4 Ap Voids of root residue, brownish, 20 % Bw Voids of root residue, 15 % BC Planar voids filled by a mixture of clay and very fine sand Brownish red organic fragments, 10 % 2Ab - 2BCb1 Voids of root residue and organic fragments, 10 % 2BCb2 Planar void filled by granular clay aggregates and very fine sand Fragment of reddish weathered rocks with volcanic glass 2A’b1 Tuff with volcanic glass and yellowish brown clay minerals 2A’b2 Voids filled by very fine sand 2B’wb Voids filled by very fine sand and groundmass material SNR-A2 Ap Voids of tea plant’s root residue, reddish brown wall Bw1 Voids filled by gibbsite Bw2 Partly altered root fragments Bw3 - BC Voids of rounded root residue filled by granular groundmass material 2Ab Planar void filled by clay and gibbsite 2BCb Planar void filled by clay Root fragments, 7 % [or phytoliths ??] non crystalline !! 2A”B Void of weathered mineral residue Planar void filled by clay and gibbsite 2BC’b Planar voids and vughs filled by granular groundmass material SNR-B5 Ap Opaque root fragments Bw Opaque root fragments A’b Opaque root fragments BC’b Voids of root residue, partly filled with groundmass material Typic nodules SDP-A3 Ap Opaque and reddish brown root fragments Voids of root residue, partly filled with granular groundmass material A2 Typic and nucleic nodules Root fragments [or phytoliths ??] non crystalline !! Bw Typic and nucleic nodules


304

BC Planar voids filled by groundmass material and very fine sand A’b1 Hypocoating in the planar voids Typic nodules Planar voids filled by groundmass material and very fine sand A’b2 Typic nodules Voids of root residue, reddish brown wall, partly coated by groundmass

material B’wb Typic nodules Voids of root residue (Chamber), filled with groundmass material Typic hypocoating in planar voids Planar voids filled by groundmass material and very fine sand A”b Planar voids coated by groundmass material and very fine sand (Typic)

[type ?] B”wb Typic coating in planar voids Planar voids filled by groundmass material BC”b Coating in planar voids (Typic) Planar voids filled by groundmass material and very fine sand Typic nodules SDP-B5 Ap Planar voids filled by groundmass material and very fine sand Bw - A’b Planar voids filled by groundmass material and very fine sand Voids of weathered root residue, rounded, reddish brown wall B’wb Planar voids and compound packing voids filled by groundmass

material and very fine sand A”b1 Planar voids filled by groundmass material and very fine sand A”b2 - B”wb Chamber filled by micropeds BCb - A”’b Planar voids and vesicles!! filled by groundmass material and very fine

sand [vesicles ?]

Table 2. Pedofeatures of every identifiable horizon in the studied soils.


305

A

b

C

d

e

Fig.2 . Scanning electron microscope images (a and e) and thin section photographs. Gibbsite

coating in hor. 2BCb, SNR-A2 (a); clay coating in hor. B’wb-SDP-A3, XPL (b); coatings of organic material in hor. B’wb, SDP-A3, PPL (c); pores with infilling in hor. 2BCb, SNR-A2, XPL (d); clay

coating on sand grains, hor. Bw, SNR-B5 (e)


306

CONCLUSION

(1) Pedofeatures observed in thin sections are very useful to reveal pedogenetic processes. The pedon developed after the eruption of Mt. Guntur has clay coatings and nodules. The pedon developed at Mt. Kendeng has gibbsite coatings, and pedons developed at Mt. Papandayan and Mt. Tangkuban Perahu (eruption A and C) had coatings of organic material. (2) Micromorphological characteristics of Andisols developed from old parent material were different from those of soils developed from young parent material. The former have porphyric c/f related distribution patterns, low c/f2µ ratios, poor sorting, common infillings and coatings of voids, a few clay and gibbsite coatings, anhedral primary mineral grains, planar voids, a blocky to angular blocky microstructure, well-developed pedality and good accommodation. The soils on young parent materials have enaulic c/f related distribution patterns, high c/f2µ ratios, poor sorting, infillings composed of groundmass material, silt and organic material, subhedral to euhedral primary mineral grains, a granular microstructure, a crumb to blocky microstructure with medium pedality, partly accommodated peds and compound packing voids.

REFERENCES

[1] Brewer, R. “Fabric and Mineral Analysis Soils”, John Wiley & Sons, Inc., New York, (1964). [2] Brewer, R. “Fabric and Mineral Analysis Soils”, Robert E. Krieger Publ. Co., New York, (1976). [3] Bullock, P. L., Federoff, N., Jongerius, A., Stoops, G. and T. Tursina, “Handbook for Soil Thin Section Description”, Waine Research Publ, 152 p (1985). [4] Bullock, P. L. “The Role of Micromorphology in the Study of Quaternary Soil Process. Soil and Quaternary Landscape Evolution”, J. Boardman (ed), John Wiley & Sons Lt, (1985). [5] FitzPatrick, E. A. “Micromorphology of Soils”, Chapman and Hall, London, (1984). [6] Goenadi, D. H. and Tan, K. H. “Mineralogy and micromorphology of soils from volcanic tuffs in the humid tropics”, SSSAJR, 53(6):1907-1911 (1989). [7] Goenadi, D. H. and Tan, K. H. “Relationship of soil fabric and particle-size distribution in Davidson soil”, Soil Sci. 147:264-269 (1989). [8] Goenadi, D.H and Tan, K. H. “Micromorphology and x-ray microanalysis of an Ultisols in the tropic”, Indon. J. Trop. Agric, 1:12-16 (1989). [9] Maeda, T., H. Takenaka and B.P Warkentin. “Physical properties of allophane soils”, Advances Agronomy, 29:229-264 (1977). [10] Mohr, E.J.C., F.A van Baren and I. van Schuylenborg. ”Tropical Soils, A Comprehensive Study of Their Genesis”, The Hague-Paris-Djakarta, (1972). [11] Oldeman, L. R. “An Agroclimatic Map of Java Central Research”, Institute of Agricultur, Bogor, (1975). [12] Soil Survey Staff. “Keys to Soil Taxonomy, SMSS, Technical Monograph No.19, Fifth Edition”, Pocahontas Press. Inc, Blacksburg. Virginia, (1992). [13] Stoops, G and A. Jongerius. “Proposal for micromorphological classification in soil materials, I. A classification of the related distribution of coarse and fine particles”, Geoderma, 13: 189-200 (1975). [14] Stoops, G and H. Eswaran. “Soil Micromorphology”, Van Nostrand Reinhold, New York (1986).


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MICROMORPHOLOGICAL FEATURES OF SOME SOILS IN THE AFRAM PLAINS (GHANA, WEST AFRICA)

M.D. Mays1, W.R. Effland2, T. Adjei-Gyapong3, C.D. Dedzoe3 and E. Boateng4*

1National Soil Survey Centre, USDA-NRCS, Lincoln NE; 2USDA-NRCS, Washington, D.C.; 3CSIR-SRI, Kumasi (Ghana); 4CSIR/SRI, Accra (Ghana)

E-mail: [email protected], Tel: 233-21-778226, Fax: 233-21-778219 Poster Extended Abstract

An eight-member sampling team from Ghana’s Council for Scientific and Industrial Research (CSIR) / Soil Research Institute (SRI) and from the USDA-National Resources Conservation Service (NRCS) sampled soils in the Upper Afram Basin as part of a co-operative project that included providing training in modern soil survey methodologies. The field portion of the project included sampling six soil pedons that represent a variety of soil types for complete analyses. These soils are developed in Paleozoic fine- and coarse-grained Voltaian sandstone and shale. The objective is to relate clay and optical mineralogy findings to micromorphological properties of the studied soils. As in many tropical soils, they did not reflect strong pedofeatures, except for clay illuviation, which may be masked in thin sections by illuvial iron and manganese that coats peds and grains. The illuvial iron/ferri-argillans mask the cation exchange capacity of the soil and other clay expressions such as x-ray diffractions. It also fixes phosphorous and produces the red colour exhibited in these soils. X-ray diffraction analysis showed that quartz is the dominant mineral in the clay fraction. Faunal activity, e.g. by termites and earthworms, and vegetation differences are important soil developmental factors observed in thin sections. Also, iron and clay illuviation was dominant in soils on mature landscapes. Quartz grains in thin sections in these soils are highly weathered with rounded edges and striated marks in grains surfaces. These features are evidence of the long and continuous weathering that has taken place in these soils or parent materials over time. Remnants of termite and worm activity include vermiform features composed of kaolinitic clays that have been ingested and are plastered along the walls of channel. The soils in this study record a large variation in animal activities. There was a larger variety of activities in the surface layer of forested areas than in cultivated fields. However, termites were active in both forested and cultivated areas.

REFERENCES

[173] S.V. Adu, J. A. Mensah-Ansah. "Soils of the Afram Basin, Ashantiand Eastern Regions, Ghana", CSIR-Soil Research Institute, Memoir No. 12. Kwadaso-Kumasi, Ghana. 90pp, (1995). [174] D.A. Bates. Geology. P51-61. In J. Brian Wills (ed). "Agriculture and land use in Ghana", Oxford University Press, London, (1962). [175] R. Brewer. "Fabric and Mineral Analysis of Soils", John Wiley & Sons, Inc. New York. 304pp., (1964). [176] E.A. FitzPatrick. "Soil Microscopy and Micromorphology", John Wiley & Sons, Inc. New York. 304pp., (1993). [177] Soil Survey Staff. "Keys to Soil Taxnomy", Ninth Edition. United States Department of Agriculture and Natural Resources Conservation Service. 332pp., (2003). [178] G. Stoops. "Guidelines for Analysis and Description of Soil and Regolith Thin Sections", Soil Science Society of America, Inc. Madison, WI, 184pp, (2003).


308

WORKSHOP Theme: Soil Processes and analytical techniques

Convenors: E. Van Ranst, G. Stoops, F. Mees, V. Marcelino

CONCLUSIONS

About 15 participants attended the session for this workshop theme. They were mainly alumni of the former “Soil Science” and “Soil Science and Eremology” programmes, in which more attention was given to the understanding of soil genesis and dynamics (e.g. using mineralogical and micromorphological methods) compared to the curriculum of the present “Physical Land Resources” programme. A majority of the participants is involved in teaching at university level, which implies that the total impact of the session will be important, due to the multiplication effect of dealing with teaching staff.

The first part of the session was concentrated mainly on soil mineralogy. E. Van Ranst (UGent), chairing that part, illustrated the importance of physico-chemical and mineralogical studies of the clay fraction for understanding soil dynamics, followed by a presentation of an ongoing research project about authigenic mineral formation (F. Mees, UGent). Lectures by Fiantis et al. and Morras et al. illustrated the use of various techniques for the mineralogical study of soils.

During the coffee break, attention was focussed on the presentation of posters by participants of this workshop theme session.

The second part started with an introduction by G. Stoops (UGent), describing recent advances in soil micromorphology and the present research in this field within the Department, followed by more detailed discussions on the problem of comparing micromorphometric data obtained by different techniques (V. Marcelino, UGent) and on the application of X-ray tomography in soil micromorphology (F. Mees, UGent). Two alumni presented papers on their current research in Suriname and Indonesia, using combined mineralogical and micromorphological techniques to disentangle complex pedogenic processes.

All presentations, during both parts of the session, were followed by a discussion with the audience.


309

Closing Word

310

CLOSING WORD

Closing Address by Prof. E. Van Ranst, Chairman Steering Committee Physical Land Resources and Promotor of the Master Programme (UGent)

Closing Word

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Closing Address by Prof. E. Van Ranst, Chairman Steering Committee Physical Land Resources and Promotor of the Master

Programme (UGent)


9 September 2006

Dear Alumni, Dear Colleagues, Esteemed Guests, On behalf of the Steering Committee and the Staff of our programme in PLR, I first want to congratulate all of you, alumni and staff who attended this 5th refresher course, for your contributions and active participation in the discussions. I am proud to be able to announce that this refresher course was attended by 40 alumni coming from 22 countries spread over different continents. As I said already during my opening speech, our major objective was to come to an overall exchange of knowledge and information from alumni to staff and vice versa, as well as amongst alumni. I hope we have succeeded in this objective? I hope that all of you enjoyed the sessions, that you could establish cooperative linkages, upgrade your knowledge with the latest developments in the field of soil science and engineering geology, and that you were able to collect valuable information about the wide range of existing funding opportunities provided by VLIR or offered by other institutions in Belgium that are involved in development cooperation. I think that the information session we had on Monday afternoon on possibilities for co-operation, financial support, project planning, etc.. with presentations of VLIR, BTC, the Department of Research Affairs from the Ghent University and the Department for Development Cooperation of the Free University of Brussels was very informative to strengthen your academic cooperation in the near future or to help younger colleagues or scientists of your institute in their further training or career development. The flash presentations proved to be an ideal communication tool, inviting us to explore the differences and similarities in the problems you, the alumni, face while developing your scientific career. It stressed the importance of funding – through projects with professors from Ghent University and the Free university of Brussels - but it also highlighted opportunities for co-operation among the alumni themselves. The most important limitation experienced by the majority of the speakers is the lack of funds and consequently, there’s a high necessity for cooperation with other institutes through projects. The funds raised as such are necessary to buy basic equipment for laboratories or field experiments, or to buy data such as climatic records or satellite imagery. The collaboration with European universities also opens opportunities for knowledge exchange, through guest lectures or short trainings. The insight in current leading research topics is broadened as the alumni get access to e-papers.

Closing Word

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However, a project starts with writing a well-prepared project proposal, and this initial proposal writing is not as evident as it seems if there’s no access to basic computer infrastructure, internet services or e-subscriptions to journals that allow the alumni to keep pace with the latest developments in their field of expertise. Once the project finishes, often, there are no funds anymore that can be used to maintain, repair or order spare parts of the laboratory equipment acquired. This opened the discussion with respect to the frequent demand of alumni for more sophisticated instruments. In reality, they more urgently need good basic infrastructure that is maintained correctly. This maintenance not only requires funds, but also a good management with continuous supervision. All speakers are also willing to exchange MSc and PhD students. These foreign students bring along with them their knowledge of tools, theories, and new advances in soil science. On the other hand, several alumni highlighted the lack of interest in soil science shown by the local students. Often, these students don’t choose for soil science because they don’t have any idea of the potential future jobs. They also need to be convinced of the persisting (or even increasing) importance of soil science in our modern communities. Upon the demand for more « upgraded » local staff, the problem of brain-drain is raised, faced by many developing countries. However, there are also positive, encouraging statements. Facing all the problems, making it difficult (at might take several years) to get a project proposal launched, some of the speakers already successfully got involved in national and international projects. Cooperation among the alumni of different universities or research institutes within a country or within neighbouring countries, is often a way of getting access to papers, to data, or to specific laboratory instruments. Also our newsletter “PEDON” can play a major role in all this, as I mentioned already in the editorial of Pedon nr. 16 (2005). I wish to remind everyone of you that Pedon is not meant as a one-way channel of information from our centre towards alumni. Pedon also makes room for your contributions, reactions, call for research partners, important events in your research groups, as well as activities and projects organised in the frame of the soil science – and engineering geology – community in your country and, perhaps, by associations of alumni. In 1992, a local Alumni Association was set up in Malaysia. We have about 70 alumni from Malaysia, and they were one of the most prominent countries represented here during the seventies and eighties. At present, other nationalities surface in our international student community. Ethiopia is certainly taking the lead. In 1996, an association of Ethiopian alumni from Belgian universities was founded. Although this association groups alumni from different programs in Belgium, it does provide a channel through which our alumni can meet and (we hope) keep contact. Associations like these can facilitate networking and set up of research activities within and across borders. Please send us information to be published in PEDON!

Closing Word

313

Before ending this speech, I once again would like to thank the VLIR for co-financing this event; the Ghent University for hosting this workshop, and especially the administrative staff of the secretariat of the PLR for the hard work done over the past weeks making the organization of this refresher course possible. Thanks, let’s keep in touch, and have a safe journey back home.

Prof. E. Van Ranst

Agenda

314

Workshop for Alumni of the M.Sc. programmes in Soil Science, Eremology and Physical Land Resources

NEW WAVES IN PHYSICAL LAND RESOURCES

3-9 September 2006

AGENDA Sunday September 3, 2006 : 04.00–06.00 pm : Registration and reception of participants, Faculty of Bioscience

Engineering, Coupure Links 653, 9000 Gent (FBE, UGent), Bldg. E Monday September 4, 2006 : Place: Faculty of Bioscience Engineering, Coupure Links 653, 9000 Gent (FBE, UGent), Bldg. E, room E009 09.00-09.30 am : Registration 09.30-10.00 am : Welcome of the participants by

. course promoter(s)

. Rector UGent

. Director VLIR-UOS (K. Verbrugghen) 10.00-11.30 am : Opening lectures by alumni

. Prof. Dr. Mitiku Haile, Rector, Mekelle University College, Ethiopia

. Prof. Dr. Tang Hua-Jun, Director General, National Institute of Agricultural Resources and Regional Planning, Chinese Academy of Agricultural Science (CAAS), China

. Prof. Dr. Erpul Gunay, Ankara University, Turkey 11.30-02.00 pm : Reception - Lunch 02.00-05.30 pm : Informative session on possibilities for co-operation, financial support,

project planning etc. . UGent, Dept. Research Affairs (Dr. D. De Craemer) . VUB, Dept. Devt. Cooperation (J. Couder) . BTC (C. Michiels) . VLIR (F. Vermeulen) . DGOS (D. Molderez, A. Van Malderghem)

Agenda

315

Tuesday September 5, 2006 : Place: FBE (UGent), Bldg. E, room E009 09.00–11.00 am

: Flash presentations by alumni on background, current work, needs, demands for co-operation

11.00–11.30 am : Break 11.30-12.30 am : Discussion 02.00–04.00 pm : Flash presentations by alumni on background, current work, needs,

demands for co-operation (cont’d) 04.00-04.30 pm : Break 04.30-05.30 pm : Discussion 6.00 pm : reception at the town hall and guided city walk Wednesday September 6, 2006 : Full day excursion:

meeting time and meeting place: 7.30 am: Monasterium Poortackere, Oude Houtlei 56, 9000 Gent 8.00 am: in front of the entrance hall of the building S8, De Sterre, Krijgslaan 281, 9000 Gent

Expected time of return: It is expected to leave from Brussels around 4.00 pm. Morning : Visit to the labs of ICP staff at the VUB (Brussels) Afternoon : Visit to the Royal Museum of Central Africa, Tervuren, dept.

Teledetection Thursday September 7, 2006 : Visit to the labs of ICP-staff (UGent):

meeting time: 15 minutes before start of each tour (08.45 am and 01.45 pm respectively) meeting place: entrance hall of the building concerned (S8, Sterre and Bldg. B, FBE respectively)

Note: a bus will pick up participants at the Monasterium at 8.30 am, with destination the Sterre. A bus will take the participants at 12.00 am to the FBE for lunch and continuation of the visit there.

Agenda

316

place time nr. lab/dept. De Sterre, S8 09.00 – 12.00

am (3 groups)

1 2 3

Lab. Soil Science Lab. Applied Geology & Hydrogeology Center for Remote Sensing

FBE, bldg B 02.00 – 05.30 pm (4 groups)

4 5 6 7

Lab. Applied Physical Chemistry Lab. Analytical Chemistry & Applied EcochemistryLab. Soil Physics Lab. Soil Fertility & Data Processing

FBE, bldg A By appointment 8 9 10

Lab. Hydrology & Water Management Dept. Applied Ecologie & Environmental Biology Dept. Applied Mathematics, Biometry & Process Regulation

Friday September 8, 2006 : Place: FBE (UGent), Bldg. E 09.00 – 12.30 am break: 10.30-11.00 am

: Parallel theme-workshops based on papers and posters: Theme A : Soil and groundwater pollution and

remediation Theme C : Land evaluation and land degradation

Room E010 E009

02.00 – 05.30pm break: 03.30-04.00 pm

: Parallel theme-workshops based on papers and posters : Theme B : Integrated soil fertility management Theme D : Soil survey and soil inventory techniques Theme E : Soil processes and analytical techniques

Room E009 E010 E015

7.30 pm : Workshop Dinner at Monasterium Poortackere, Oude Houtlei 56 Saturday September 9, 2006 : Place: FBE (UGent), Bldg. E, room E010 09.00 - 10.00 am 10.00 – 10.30 am 10.30 – 11.30 am

: : :

Time for making reports of the workshops Coffee break Reporting on theme workshops, conclusions

11.30 am : Closing of the meeting

Agenda

317

List of Participants

318

LIST OF PARTICIPANTS Dr. Héctor Morrás Instituto Nacional de Tecnolgia Agropecuaria (INTA), Centro de Investigación de Recursos Naturales (CIRn) - Instituto de Suelos Las Cabañas y Los Reseros, 1712 Castelar, Argentina tel.: 54-1146211448 fax: 54-114811688 e-mail: [email protected] Promotion: 1972, Soil Science Ms. Katherine Verbeek Goedingenstraat 20, 9051 Afsnee, Belgium tel.: 0473/522513 fax: e-mail: [email protected] Promotion: 1982, Soil Science Prof. Boon Goh Tee University of Manitoba, Dept. Of Soil Science R3T 2NZ Winnipeg, Canada tel.: 204-4746046 fax: 204-4747642 e-mail: [email protected] Promotion: 1978, Soil Science Dr. Youqi Chen National Institute of Natural Resources and Soil Science, CAAS, 12 Zhong Guan Cun South Avenue, 100081 Beijing, China tel.: 0086-10-68919638 fax: 0086-10-68976016 e-mail: <[email protected]><[email protected]> Promotion: Dr. Jin Ke Soil and Fertilizers Institute, Baishiqiao 30, 100081 Beijing, China tel.: 0086-10-68918672 fax: e-mail: [email protected] Promotion: 2002? Physical Land Resources Prof. Dr. Tang Huajun National Institute of Natural Resources and Soil Science, CAAS, 12 Zhong Guan South Ave., 100081 Beijing, China tel.: 86-10-68919638 fax: 86-10-68976016 e-mail: <[email protected]><[email protected]> Promotion: 1993, Soil Science Prof. Dr., Dean Luhembwe Ngongo University of Lubumbashi, 825 Lubumbashi, D.R. Congo tel.: 243-997027140 fax: e-mail: [email protected] Promotion: 1986, Soil Science


319

Prof. Jorge Valarezo Universidad Nacional de Loja-Ecuador, Ciudad Universitaria, La Argelia, 1101 Loja, Ecuador tel.: 593-72546671 fax: 593-72545054 e-mail: [email protected] Promotion: 1977, Soil Science Ing. M.Sc. Carlos Valarezo Universidad Nacional de Loja-Ecuador, Ciudad Universitaria "Guillermo Falconi" - La Argelia, 1101 Loja, Ecuador tel.: 93-72545054 fax: 593-72584802 e-mail: [email protected] Promotion: 1978, Soil Science Dr. Ahmed Taalab National Research Centre, Tahrrer St., 12622 Dokki, Cairo, Egypt tel.: 123991830 fax: 2023371362 e-mail: [email protected] Promotion: Prof. Dr. Mohamed El-Badawi National Research Centre, Soil Dept. El-Bohouse St., 123 Dokki, Cairo, Egypt tel.: 20123707177 fax: 20123370931 e-mail: [email protected] Promotion: 1986, Ph.D. Soil Science Dr. Ageeb Gamil Waheeb National Research Centre, Al Bohos St., 12622 Dokki, Cairo, Egypt tel.: 202-0106833629 fax: 202-3370931 e-mail: [email protected] Promotion: 1994, Soil Science Prof. Dr., President Mitiku Haile Mekelle University, P.O. Box 231, 231 Mekelle, Ethiopia tel.: 251-344402264 fax: 251-344409304 e-mail: [email protected] Promotion: 1987, Soil Science Drs. Meklit Tariku Ugent, Dept. Soil Mant. & Soil Care Coupure Links 653, B 9000 Gent, Belgium tel.: fax: e-mail: [email protected] Promotion: 2004, Physical Land Resources Mr. Enoch Boateng CSIR-Soil Research Institute, P.O. Box 1132, Accra, Ghana tel.: 233-244732410 fax: 233-21778219 e-mail: [email protected] Promotion: 1990, Soil Science


320

Mr. Ebenezer Abuaku University of Cape Coast, Dept. of Soil Science, School of Agriculture 23342 Cape Coast, Ghana tel.: 233-244736051 fax: 233-21-774313 e-mail: [email protected] Promotion: 2002, Physical Land Resources Prof. Dr. Arifin Mahfud Padjadjaran University, Faculty of Agriculture, Dept. of Soil Science Jl. Raya Sumedang km 21 Jatinangor, 46000 Bandung, Indonesia tel.: 062-22-7797200 fax: 062-22-7796316 e-mail: [email protected] Promotion: ir. M.Sc. Rina Devnita Padjadjaran University, Faculty of Agriculture, Dept. of Soil Science Jl. Raya Sumedang km 21 Jatinangor, 46000 Bandung, Indonesia tel.: 062-22-7797200 fax: e-mail: [email protected] Promotion: 1993, Soil Science Dr. Dian Fiantis University of Andalas, Dept. Of Soil Science, Faculty of Agriculture Kampus Unand Limau Manis, 25163 Padang, Indonesia tel.: 62-75128136 fax: 62-75172702 e-mail: [email protected] Promotion: 1995, Soil Science Dr. A. Arivin Rivaie Indonesian Centre for Estate Crops Research & Development, Jl. Tentara Pelajar n° 1, 16111 Bogor, Indonesia tel.: 62-251313083 fax: 62-251336194 e-mail: [email protected] Promotion: 1998, Soil Science and Eremology Dr. Mugai Njue Jomo Kenyatta University of Agriculture and Technology, Horticulture Department P.O. Box 62000, Nairobi, Kenya tel.: 722-337605 fax: e-mail: [email protected] Promotion: 1982, Soil Science Dr. Philip Wandahwa Egerton University, Dept. Of Soil Science P.O. Box 536, Njoro, Kenya tel.: 254-733269460 fax: 254-5162527 e-mail: [email protected] Promotion: 1992, Soil Science Mr. Peter Njoroge Kamande University of Nairobi, P.O. Box 29053, Nairobi, Kenya tel.: 254-726378491 fax: e-mail: [email protected] Promotion: 2005, Physical Land Resources


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Prof. Bin Jusop Shamshuddin Universiti Putra Malaysia, Department of Land Management, Faculty of Agriculture 43400 Serdang, Selangor, Malaysia tel.: 603-89466985 fax: 603-89434419 e-mail: [email protected] Promotion: 1981, Soil Science Dr. Abdul Razzaq University of Agriculture, Dept. of Soil Science Faisalabad, Pakistan tel.: fax: e-mail: Promotion: 1969, Soil Science Dr. Renato Boniao MSU-NAAWAN, Naawan, Misamis Oriental, 9023 Naawan, Philippines tel.: H/P # 063 63 9164958669 fax: e-mail: [email protected] Promotion: 1996, Soil Science Prof. Rosa Poch Universitat de Lleida, Departament de Medi Ambient i Ciències del Sòl Av. Rovira Roure 191, 25198 Lleida, Spain tel.: 34973702621 fax: 34973702613 e-mail: [email protected] Promotion: 1989, Soil Science Drs. Udayakantha Vitharana Ugent, Dept. Soil Mant. & Soil Care Coupure Links 653, B-9000 Gent, Belgium tel.: fax: e-mail: [email protected] Promotion: 2004, Physical Land Resources M.Sc. Chandra G. Algoe Anton de Kom Universiteit van Suriname, Faculteit der Technologische Wetenschappen Universiteitscomplex, Leysweg, POB 9212, Paramaribo, Suriname tel.: 465558 ext. 413 fax: 495005 e-mail: [email protected] Promotion: 1999, Physical Land Resources Dr. Somjate Pratummintra Department of Agriculture, Chatuchak, 10900 Bangkok, Thailand tel.: 66-2-5790574 fax: 66-2-9405472 e-mail: [email protected] Promotion: 1996, Soil Science Dr. Gunay Erpul Ankara University, Faculty of Agriculture, Soil Science Department 06110 Ankara, Turkey tel.: 90-312/5961796 fax: 90-312/5171917 e-mail: [email protected] Promotion: 1996, Eremology


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Dr. Hasan Öztürk Ankara University, Faculty of Agriculture, Dept. of Soil Science 06110 Diskapi, Ankara, Turkey tel.: 90-312-5961757 fax: 90-312-3178465 e-mail: [email protected] Promotion: 1997, Eremology Dr. Crammer Kayuki Kaizzi Kawanda Agricultural Research Institute (KARI), P.O. Box 7065, Kampala, Uganda tel.: 256-41567649696 fax: 256-41567649 e-mail: [email protected] Promotion: 1994, Soil Science M.Sc. Tran Thi Le Ha Hanoi Agricultural University, Faculty of Land and Environment, Department of Soil Science 22A Duong S., Trau Quy, Gia Lam, 10700 Hanoi, Vietnam tel.: 84-912554602 fax: 84-48276554 e-mail: [email protected] Promotion: 2000, Physical Land Resources Mr. Dai Trung Nguyen Research Institute of Geology and Mineral Resources, Soil and Landuse Dvision Nguyen Trai Road, km 9 + 200 Chien Thang Street, Thanh Xuan, 0084 Hanoi, Vietnam tel.: 84-4/8543107 fax: 84-4/8542125 e-mail: [email protected] Promotion: 2001, Physical Land Resources Sr. Lecturer, Director Khoa Le Van Can Tho University, 3/2 Street, Ninh Kieu District, Cantho City, Vietnam tel.: 84-71-832971 fax: 84-71-838474 e-mail: [email protected] Promotion: 2002, Ph.D.

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