CHAPTER 3 Spatial analysis of physical and chemical...

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CHAPTER 3

Spatial analysis of physical and chemical properties of soil

3.1. Introduction

Soil is non-consolidated upper part of the earth’s crust that serves as a natural

medium for growth of plants (Gardiner and Miller, 2008). It is the dynamic and unique gift of

nature that acquires the properties in accordance with forces acting upon it and within itself.

It is a complete physical and biological system providing support, nutrients, water and

oxygen to plants. It sustains the growth of many plants and animals. Rapid industrialization

during recent years has threatened the soil environment through consequences of pollution

(Jeeva and Kiruba, 2010). Soils are considered highly heterogeneous in both space and time,

and this heterogeneity has strong consequences on plant performance and on ecosystem

function (Huber-Sannwald and Jackson, 2001). Spatial studies of soil help to describe soil

properties of a landscape, which is a function of vegetation and other ambient factors

(Maestre and Reynolds, 2006).

Human have been using the soil for food production since 11,000 years ago

(Lenne and Wood, 2011). Soil provides a reservoir of nutrients required by crops and also

therefore for animals but not necessarily at optimum levels of immediate availability to plants

(Petrone et al., 2004). Land use change is a significant problem in wetland ecosystems of

India. There are 200 hectare, dried wetlands in India, but most of the dried wetlands didn’t

become fertile as expected and the territory became infertile because of salinity and wind

erosion (Timur, 2008). Bationo et al., (2006) highlighted inherently low fertility status,

inappropriate land use, poor management, erosion and salinization of riverine wetland, water

irrigation strategy, soil type, ground water quality and depth on salinization of soils.

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Ali et al., (2001) investigated the effects of quality of irrigation water,

irrigation strategy, soil type, ground water quality and depth on salinization of soils. High soil

salinity and alkalinity restricts plants growth by reducing the somatic potential, decreasing

nutrient availability and soil physical quality parameters. Richards et al., (1986) reported

soluble salts affect productivity of soils in two principal ways: changing the osmotic potential

of soil solution and increasing the content of exchangeable sodium.

Alkaline soils are characterized by exchangeable sodium contents and sodium

attached to clay surfaces can increase clay dispersion. Dispersion of clay particles can restrict

air and water transport in soil profile and could promote soil erosion and total loss of soil

(Dougherty and Anderson, 2001). In addition to the natural weathering-pedological

(geogenic) inputs under terrestrial settings, anthropogenic activities, such as the mining and

smelting industries, sewage sludge application and the use of mineral fertilizers are said to be

significantly responsible for elevated micro and macro nutrient concentrations in soils

(Mapanda et al., 2005).

Soil degradation and nutrient depletion have gradually increased and have

become serious threats to wetland productivity (Vanlauwe et al., 2002). Smaling (1995)

described tropical soils are often having negative soil nutrient balances. A major factor in soil

degradation is the soil chemical fertility and then in particular its decline as a result of the

lack of nutrient inputs (Hartemink, 2010). However, not much work has been done on micro

and macro nutrient contamination, source identification and their spatial distribution in

wetland soils of India.

Pollutant activities can have implications for the quality of wetland soils,

including phytotoxicity at high concentrations and the transfer of heavy metals to the human

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diet from plant uptake or soil ingestion by grazing livestock (Li et al., 2009). The continuous

and over application of these agrochemicals may enrich the riverine soil with micro and

macro nutrients.

The purpose of soil analysis is to assess the adequacy, surplus or deficiency of

available nutrients for crop growth and to monitor change brought about by farming

practices. This information is needed for optimum production, to avoid transferring

undesirable levels of some nutrients into the environment and to ensure a suitable nutrient

content in crop products (Tariq et al., 2007). Farm assurance schemes, buyer's protocols and

codes of practice are increasingly demanding more accurate fertilizer recommendations

which must depend on the nutrient-supplying capacity of the soil. Regular soil analysis, every

3-5 years, should be undertaken as a vital part of good management practice. In the present

study, a detailed investigation has been made to identify the hydro geochemical processes and

their relation with soil quality, hydro chemical evolution of soil system through principal

component analysis and seasonal variation in the soil quality.

Soil salinizations are a widespread limitation to agricultural production in dry

land and irrigated soils throughout the world. Soil salinity reduces crop growth because

depression of the osmotic potential of the soil solution limits water uptake by the plant

(Corwin and Lesch, 2003). Salinity may also cause specific ion toxicity or nutrient

imbalances, and soil permeability may deteriorate if excessive amounts of sodium accumulate

on the soil’s cat ion-exchange complex.

The sanitization of soils is harmful to the production potential of soils, causing

sharp reduction in crop yields and changing the adaptability of land cropping; furthermore,

the accumulation of salt will also change the environment of plant growth and cause the

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vegetative degradation (Chen et al., 2011). Understanding the soil salinization degree and

characteristics will help to improve and recover the ecological environment. Especially in the

arid desert areas, the soil micro and macro nutrient content determines the direction of

ecological evolution. Understanding the soil micro and macro nutrients variation has a very

important role in improving the stalinized soils (Dalal et al., 2011).

Reclamation of saline, alkaline, and saline-alkaline soils require two

measurements, leaching a soluble salt with the quality water and removing exchangeable

sodium via gypsum application. But salinity and alkalinity can show very complex spatial

variability in a site where different application of water and gypsum are required. Therefore,

seasonal variation of salinity and alkalinity can be determined using geostatistical methods

and also results of management practices can be monitored. The effective management of

saline-alkaline soils requires understanding of not only the salinity sodicity continuum, but

also of its spatial variation (Inakwu et al., 2008). Soil properties show spatial variation with

intrinsic and extrinsic soil forming factors (Heuvelink and Webster, 2001).

Soil scientists focused on predicting spatial variability of soil properties using

geostatistics and different kriging methods over small to large spatial scale (Bo et al., 2003).

Samra et al., (1988) investigated seasonal variability in sodic soils. Cemek et al., (2007)

investigated seasonal variability of some soil properties as related to salinity and alkalinity.

They inferred that the strong spatial dependency of soil properties may have resulted from

extrinsic factors such as ground water level, drainage and irrigation systems. Dhillion et al.,

(1994) used pH as an indicator of soil fertility in strategies based on spatial analysis of plant

nutrients.

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Studies on soil variability has relevance in sampling (Tabi and Ogunkunle,

2007), site specific soil fertility management and definition of land management units and in

explaining variation in crop growth and yield (Kosaki and Juo, 1989). Technologies need to

be adapted to the specific biophysical and a socio-economic circumstance of small-scale

farmers. This is made possible with combined use of classical statistics and multivariate

statistics (principal component).

Principal component analysis (PCA) is a multivariate technique for analyzing

relationship among several quantitative variables measured on a number of objects (Manly,

1997). It provides information about the relative importance of each variable in

characterizing the objects. New variables are calculated, which consist of (usually linear)

combinations of the old ones. A small number of these new variables will usually be

sufficient to describe the observational objects.

The study of the spatial variation of soil texture has an important role in

analyzing and simulating the fluid movement and the material migration process of soil

dissolved matters (Williams et al., 2009), simulating hydrological processes and optimizing

agricultural production activities. The influential factors of spatial variations were also

discussed, which will provide a theoretical base for the protection of water and soil resources

and the management of oases. Saline soil is defined as one containing sufficient soluble salts

to adversely affect the growth of most crop plants (Soil Science Society of America, 2001).

Ali and Malik (2011) reported that the soil quality of rapidly growing

countries of India, during the study of seven physico-chemical parameters and seven micro

and macro nutrients were determined in surface soils. The study was aimed with the

following objectives.

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3.2. Objectives of the present study:

To analyses the physical characteristics of the soil (pH, electrical conductivity and

soil texture),

To analyses the micro and macro nutrients of the soil,

To investigate and interpret spatial relationship and seasonal variation of physico-

chemical parameters,

To analyses the seasonal variation of the soil using statistical methods (descriptive

statistics, principal component analysis).

3.3. Materials and methods

3.3.1. Study area

The study area (25 wetlands) is located in the command area of Tamiraparani

Riverine wetlands in Srivaikundam, Tuticorin and Tiruchendur Taluks of Tuticorin District.

It is located between 8°20¹ - 9°0¹ North Latitude.

A preliminary survey was conducted the 25 wetlands during June 2011 to May

2012. The physico-chemical features of the study area were assessed by using ground survey.

Samples were taken from each study site and their boundaries were delineated. Soil samples

were taken from three sites in each wetland. A total of 225 samples were analyses for three

seasons (75 samples for each seasons). Based upon the analytical values, the potentials and

constraints of the soils were assessed. The relative nutrient supplying power of the soils were

found out.

3.3.2. Climate

The study area has semi arid tropical monsoonal climate. The mean annual

temperature is 33.5°C and the mean annual precipitation is around 750 mm. The seasonal

distribution of the precipitation shows a concentration of rain in the period from October –

December – i.e., north-east monsoon and post-monsoon showers also pronounced in the area.

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3.4. Methodology of soil collection

About one kilogram topsoil sample was collected up to a depth of about 0-20

cm, by auger from each representative sample site. The colour and texture of these samples

were noted at the site. These soils samples were properly labeled, stored in kraft papers and

transferred to the Geochemistry Laboratory for further processing and analysis.

3.4.1. Preparation of soil samples

Soil samples were air-dried and organic matters were removed. These were

then sieved through a 2-mm sieve. Each sample was homogenized and then representative

portion was selected by quartering and coning. This portion was then pulverized in a tungsten

carbide ball mill to 200 mesh size. The powered samples were stored in air tight bottles and

were kept in oven at 1100

C for two hours to remove moisture. The samples were cooled by

placing in desiccators.

3.4.2. Determination of physical parameters in soil

pH

pH in the soil samples was determined by using the method of Page et al.,

(1982). About 50 gram of air dry soil was taken in a glass beaker and 100 ml of distilled

water was added. The content was mixed thoroughly by shaken and allowed to stand for one

hour. The pH of saturated soil paste was recorded by using Consort Electrochemical Analyzer

which was calibrated with buffers solution pH 4, 7 and 9.

Electrical conductivity (EC)

Electrical conductivity of soil paste was recorded by using Consort

Electrochemical Analyzer Conductivity meter after standardization with 0.01 N KCl

solutions.

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Soil texture

The colour and texture of these soil samples were noted at the site.

3.4.3. Determination of major elements in soil samples

Perkin Elmer atomic absorption spectrometer was used for determination of

macro elements (i.e., Na, P and K) in all soil samples. Micro nutrients-zinc, copper, iron and

magnesium were analysis by atomic absorption spectrometer in air acetylene flame mode.

3.4.4. Statistical methods

Analytical results were compiled to form a multi elemental database using

EXCEL and SPSS prior to multivariate analysis.

Descriptive statistics such as minimum, maximum values, mean, Standard

deviation, skewness, kurtosis and coefficient of variation were carried out.

Principal component analysis (PCA),

Seasonal variations of the soil samples.

3.5. Results

Physico chemical properties

Physico-chemical parameters were mainly deal with the colloidal properties of

the soil. PH, electrical conductivity and soil texture for three seasons were shown in tables

3.1.1, 3.1.2, 3.1.3 and micro, macro nutrients of the soil for three seasons were shown in

tables 3.2.1, 3.2.2, 3.2.3. Seasonal variation of the physico-chemical parameters was shown

in the table 3.3.

3.5.1. pH

pH level showed a moderate variation between each seasons with an average

levels of 8.2, 8.3 and 8.1 during south-west monsoon, north-east monsoon season 2011 and

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post-monsoon season 2012. The maximum pH value 8.2 was observed in site 25 and

minimum pH value of 7.1 was observed in site 6 during south-west monsoon. In north-east

monsoon period, minimum pH value of 6.1 was observed in site 15 and maximum pH value

of 8.3 was observed in site 24. In post-monsoon season the minimum pH value 6.4 was

notified in site 5 and maximum pH value of 8.4 was observed in site 18.

3.5.2. Electrical Conductivity

Electrical conductivity showed high value of variations between each seasons

with an average levels of 0.95 mho/cm, 0.78 mho/cm and 0.98 mho/cm respectively, south-

west monsoon season, north-east monsoon season of 2011 and post-monsoon season of 2012.

The maximum and minimum electrical conductivity was observed during south-west

monsoon season and the values were noted as 0.98 mho/cm in site 25 and 0.18 mho/cm in

site 7. During north-east monsoon period maximum and minimum electrical conductivity was

observed as 0.78 mho/cm (site 25) and 0.10 mho/cm was noted (site 2). In post-monsoon

period minimum electrical conductivity value of 0.08 mho/cm was observed in site 2 and

maximum electrical conductivity value of 0.98 mho/cm was noted in site 25.

3.5.3. Soil texture

Sandy loam soil texture was observed in 19 sites. Clay loam soil texture was

found in 3 sites (site 22, site 23 and site 24). Sandy soil texture was observed in three sites

(site 9, site 10, and site 25). But there was no seasonal variation in soil texture. These

differentiations were due to sedimentation of soil.

3.5.4. Macronutrients

The surface soils were collected from three random places with a quadrat size of

100 m2

at a depth of 22cm. A total of 225 surface soil samples were collected from 25

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selected Tamiraparani Riverine wetlands for three seasons (south-west monsoon, north-east

monsoon and post-monsoon). The micro and macro nutrients contents of the samples analysis

during south-west monsoon season were shown in table 3.3.1, north-east monsoon was

shown in table 3.3.2 and post-monsoon season were shown in table 3.3.3. Seasonal variations

of micro and macronutrient content in three seasons were shown in table 3.4.

Nitrogen

Nitrogen value showed high level of variations between each season with

average levels of 186 mg/kg, 90 mg/kg and 223 mg/kg respectively, during south-west

monsoon, north-east monsoon during in 2011 and post-monsoon during in 2012. During

south-west monsoon minimum nitrogen value of 24 mg/kg was noted in site 1 and maximum

nitrogen value of 186 mg/kg was noted in site 24. The minimum and maximum nitrogen

content was observed in north-east monsoon in site 3 (10 mg/kg) and in site 20 (90 mg/kg).

During post-monsoon period minimum and maximum nitrogen content was noted in site 1

(27 mg/kg) and in site12 (223 mg/kg).

Phosphorus

Phosphorus level showed slight variations between each season with an

average levels of 68.0.mg/kg, 50.4 mg/kg and 69 mg/kg during south-west monsoon, north-

east monsoon season in 2011 and post-monsoon season in 2012. The maximum and

minimum phosphorus values were observed as 68.0 mg/kg (site 24) and 3.5 mg/kg (site 1)

during south-west monsoon period. The maximum and minimum phosphorus content of 50.3

mg/kg (site 3) and 7.2 (site 21) were observed in north-east monsoon period. The maximum

and minimum phosphorus were noted as 69.0 mg/kg in site 24 and 3 mg/kg in site 3 during

post-monsoon period.

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Potassium

Potassium level showed variations between each season with an average level

of 510 mg/kg, 240 mg/kg, 256 mg/kg, during south-west monsoon, north-east monsoon

season (2011) and post-monsoon season (2012). The minimum and maximum potassium

value was observed during south-west monsoon period (18 mg/kg) in site 18 and in site 25

(240 mg/kg). The minimum and maximum potassium value was observed during north-east

monsoon period as 29 mg/ kg in site 21 and 150 mg/kg in site 5. The minimum and

maximum potassium value was observed during post-monsoon period as 51 mg/kg in site 3

and 256 mg/kg in site 25.

3.5.5. Micro nutrients

The micronutrients analyses for the present study were zinc, copper, iron and

magnesium

Zinc

Zinc value showed high variations between each seasons with an average

levels of 18.0 mg/kg, 0.92 mg/kg and 8.82 mg/kg during south-west monsoon, north-east

monsoon season (2011) and post-monsoon season (2012). The minimum and maximum zinc

value was observed during south-west monsoon (0.35 mg/kg) in site 7 and in site 18 (18.6

mg/kg). The minimum and maximum zinc level was observed as 0.30 mg/kg (site 13) and

0.92 mg/kg (site 3) during north-east monsoon period. The minimum and maximum zinc

value was observed during post-monsoon period as 0.24 mg/kg in site 22 and 8.82 mg/kg in

site 11.

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Copper

Copper level showed variations between each seasons with an average level of

12.00 mg/kg, 3.00 mg/kg and 11.88 mg/kg during south-west monsoon, north-east monsoon

season (2011) and post-monsoon season (2012). The minimum and maximum copper value

was observed during south-west monsoon as 0.82 mg/kg in site 6 and 12.00 mg/kg in site

23.The minimum and maximum copper value was observed during north-east monsoon as

0.05 mg/kg in site 16 and 3.00 mg/kg in site 25. The minimum and maximum copper value

was observed during post-monsoon period as 0.79 mg/kg in site 7 and 11.88 mg/kg in site 21.

Iron

Iron level showed level variations between each seasons with an average level

of 14.01 mg/kg, 12.36 mg/kg and 14.20 mg/kg during south-west monsoon, north-east

monsoon season (2011) and post-monsoon season (2012). The minimum and maximum iron

value was observed during south-west monsoon as 0.62 mg/kg in site 23 and 14.01 mg/kg in

site 25. The minimum and maximum iron value was observed during north-east monsoon as

0.70 mg/kg in site 22 and 12.36 mg/kg in site 17. The minimum and maximum iron value

was observed during post-monsoon as 0.62 mg/kg in site 23 and 14.20 mg/kg in site 25.

Magnesium

Magnesium level showed high level variations between each seasons with an

average level of 12.90 mg/kg, 17.21 mg/kg and 14.62 mg/kg during south-west monsoon,

north-east monsoon season (2011) and post-monsoon season (2012).The minimum and

maximum magnesium value was observed during south-west monsoon as 0.99 mg/kg in site

21 and 12.90 mg/kg in site 17. The minimum and maximum magnesium value was observed

during north-east monsoon period as 10.30 mg/kg in site 8 and 17.00 mg/kg in site 25. The

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minimum and maximum magnesium values were observed during post-monsoon period as

0.99 mg/kg in site 23 and 16.17 mg/kg in site 12.

3.5.6. Descriptive statistics of soil properties

Descriptive statistics of some chemical properties of the soil such as

minimum, maximum, mean, standard deviation, coefficient variation, skewness and kurtosis

are given in tables 3.4.1, 3.4.2, 3.4.3. Large differences were found between minimum and

maximum values of the investigated soil samples.

Nitrogen

The minimum and maximum nitrogen level observed during south-west

monsoon period as 25.25 and 225.75.The minimum and maximum nitrogen was observed

during north -east monsoon period as 1.65 and 115. The minimum and maximum nitrogen

was observed during post-monsoon period as 16.25 and 209.5.

Phosphorus

The minimum and maximum phosphorus level was observed during south-

west monsoon period and the values are 3.825 and 116.5. The minimum and maximum

phosphorus level was observed during north-east monsoon period and the values are 6.72 and

53.25. The minimum and maximum phosphorus level was observed during post-monsoon

period and the values are 7 and 82.

Potassium

The minimum and maximum potassium level was observed during south-west

monsoon period and the values are 15.62 and 239.5. The minimum and maximum potassium

level was observed during north-east monsoon period and the values are 5.85 and 512. The

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minimum and maximum potassium level was observed during for post-monsoon period and

the values are 22.62 and 501.0

Zinc

The minimum and maximum zinc level was observed during south-west

monsoon period and the values are 0.22 and 15.62. The minimum and maximum zinc level

was observed during north-east monsoon period and the values are 0.31 and 6.35. The

minimum and maximum zinc level was observed during post-monsoon period and the values

are 0.16 and 0.89.

Copper

The minimum and maximum copper level was observed during south-west

monsoon period and the values are 0.80 and 13.16. The minimum and maximum copper level


minimum and maximum copper level was observed during post-monsoon period and the

values are 0.54 and 2.32.

Iron

The minimum and maximum iron value was observed during south-west

monsoon period and the values are 0.71 and 13.16.The minimum and maximum iron level


minimum and maximum iron level was observed during post-monsoon period and the values

are 4.45 and 15.21.

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Magnesium

The minimum and maximum magnesium level was observed during south-

west monsoon period and the values are 0.86 and 28.55. The minimum and maximum

magnesium level was observed during north-east monsoon period and the values are 9.21 and

16.00. The minimum and maximum magnesium level was observed during post-monsoon

period and the values are 9.17 and 15.62.

3.5.7. Principal component analysis

The results of PCA in the soil samples of 25 sites in Tamiraparani Riverine

wetlands (Tables 3.5.1, 3.5.2 and 3.5.3 and in Figures 3.1.1, 3.1.2 and 3.1.3) were grouped

into five-components that accounts for 75.79 % of all the data variation. PC1 represented

26.41% of the total variance and is the most important component. This distribution was

control by K, Na, Mg, Fe, and Mn and, partially by Zn and Co in the first principal

component which could be due to non-point source such as agricultural activities. Principal

component analysis yielded 5 components and these were retained for interpretation. The

communalities for soil attributes indicate that the five components explained more than 90%

of the variance in north east monsoon for nitrogen when compare with other two seasons,

phosphorus and potassium ratio were 80 to 70% for south-west monsoon season period and

post-monsoon season period 60-70% of the variance in Zn, Cu, Fe and Mn less than 60%.

The principal component 1 (PC1) was named the base status factor because it had a high

positive loading on cation exchange capacity and a high positive loading on exchangeable Zn

(0.73) and CU (0.90) and a moderate positive loading for MN (0.73).

3.6. Discussion

A soil pollutant is a factor which deteriorates the quality, texture and mineral

content of the soil or which disturbs the biological balance of the organisms in the soil

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(Zhang et al., 2007). Soil nutrients are important for plant growth and development. Plants

obtain carbon, hydrogen and oxygen from air and water. But other necessary nutrients like

nitrogen, phosphorus, potassium, calcium, magnesium, sulfur and more must be obtained

from the soil (Lark, 2002). Pollution in soil has adverse effect on plant growth (Singh et al.,

2004).

In the present study, pH was slightly higher in Tamiraparani River soil, which

may be due to greater input of effluents from different types of industries. But lower than the

finding of a similar study carried out by Adjia et al., (2008). In addition to lack of inputs as a

factor causing soil degradation, High soil salinity and alkalinity restricts plants growth by

reducing the osmotic potential, decreasing nutrient availability and soil physical quality

parameters. The study of soil pH is important since it controls the base status and microbial

activities (Venkatachalam, 2007). The acidic nature of soils as observed presently could also

be a property inherited directly from the parent material. At low pH, acidity can directly

inhibit plant growth and make most of the elements including toxic metals in soil bioavailable

and induce production of toxic soluble-aluminum in the soil-water solution. This might be as

a resultant of the absorption of metals in the soil (Lee, 2003). The moderately alkaline pH

of the soil indicates the deteriorate quality of the soil. High soil pH greatly reduces the

solubility of soil manganese and therefore its availability to roots (Pan et al., 2007).

Electrical conductivity value was significantly higher during post-monsoon

period as compared to the other two seasons (north-east monsoon and south-west monsoon).

The high values of electrical conductivity in the area indicated that anthropogenic activities

are too high in the river contributing significant rise in the electrical conductivity level

(Paine, 2003). The increased conductivity might be attributed to high deposition of salts of

sulphates and phosphates (Kaffka et al., 2005).

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There is no change in soil texture for three seasons. Nitrogen values are noted

as higher during post-monsoon period. The nitrogen is one of the most important factors

controlling potentially mineralizable nitrogen in riverine wetland soils (Leinweber et al.,

2000). Nitrogen is generally limiting due to its low content in study area and its high

propensity to absorption on mineral surfaces (Coulombe et al., 1996). Na is one of the most

critical elements in soil permeability (Azeez et al., 2000). That deflocculates the soil

(Senthilnathan and Azeez 1999) and makes the crust impermeable. An excess of neutral salts

of Na leads to an alkaline condition is usually termed soil salinity (Rosicky et al., 2006).

Another feature of the saline–alkaline soil studied by Seifi et al., 2010 and in the case high

pH values coinciding with high Na content. High Na is indicators of an alkaline soil (Singh et

al., 2005).

In the present study, phosphorus was slightly higher during south-west

monsoon period. The phosphorus concentrations in the studied soil samples were found

greater than those reported by Iqbal and Shah (2011). But its concentration was found lower

then that reported by Muhammad et al., (2011). Micronutrient plays a vital role in

maintaining soil health and also productivity of aquatic plants. Zinc concentrations in soil

samples was found to be lower than the Indian standards (250 mg/kg) but higher than those

reported by other researchers for Indian soils (Shah et al., 2011). The low concentration of

zinc in river soil could be due to the fact that pH of water samples was slightly alkaline and

its solubility is a function of decreasing pH (Aamir and Tahir, 2003). Low intake of zinc

ultimately resulted in growth retardation, immaturity and anemia in human (Vijaya Bhaskar

et al., 2010)

Cu concentrations in 90% of the soil samples of two sites were found below

1.0 mg/kg north-east monsoon season. This is in agreement with the observations of Wong et

al., (2004) who reported that concentrations for most of the surface soils not exceeded 1.0 to

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1.1 mg/kg worldwide. While it was found lower than that reported by Malik et al., (2010)

reported in low Cu soils collected from different areas of India. Generally, in most of the soils

was maximum and minimum Cu was observed during south-west monsoon period.

The concentrations of Fe in all sites were found higher (14.20 mg/kg) than the

reported by other researchers (Tume et al., 2011). The concentration of Mn was found higher

than the reported by Sharma et al., (2007) in the soils of Sudurban areas of Varanasi, India.

While manganese (Mn) is present in the soil as free Mn2+

, which is readily available to plants

and as oxides of low solubility. High soil pH greatly reduces the solubility of soil manganese

and therefore its availability to roots. Magnesium value was observed high during north-east

monsoon period, when compare with other two seasons. Thus the present status of

manganese in the soil revealed its poor quality in terms of manganese (Johnston, 1996). This

study show that Mn content in soil was higher during post-monsoon season as compared to

rest of the seasons. Similarly, observed the levels of manganese were lower during north-east

monsoon period than during post-monsoon season period (Ramesh and Vennila, 2012). In the

soil excess potassium causes a loss of plant structure (Joshi and Kumar, 2011).

The chemical properties of the soils varied considerably among samples

particularly in nutrient and iron level. The total amount of N, P, K, ZN, CU, FE and Mg were

maximum in the south-west monsoon, north-east monsoon and high in post-monsoon season.

The micronutrients such as zinc, copper, iron and manganese also present in moderate level

in all the season. Among the soil samples, all the micronutrients were maximum in south-

west monsoon, north-east monsoon and minimum in post-monsoon season.

The fifth principal component analysis confirms the findings of (Mengel and

Kirkby, 1985). Phosphorus is generally limiting due to its low content in parent material and

its high propensity to sorption on mineral surfaces. Low level of phosphorus was noted

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during north -east monsoon period. Phosphorus ranged from 10 to 60 mg/kg depending on

the parental material (Adriano, 2001). Cu, Zn, Fe and Mn can be considered as a geogenic

and anthropogenic component due to the presence of high levels in soils (Mico et al., 2006).

The high Cu values can be contributed from Cu-based agrochemicals related to specific

agronomic practices, whereas water and irrigation time can also be the source for the high Pb

values found in some soils (Rajaganapathy et al., 2011). These stations receive pollution

mostly from agricultural, river sand mining and fish farming activities.

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Table.3.1.1 Soil parameters during south-west monsoon period

Site No. PH EC Soil Texture

1 7.6 0.38 Sandy loam








9 7.4 0.28 sandy

10 7.3 0.31 sandy












22 7.9 0.19 Clay sandy loam



25 8.2 0.95 sandy

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Table.3.1.2.Soil parameters during north-east monsoon period











10 7.4 0.30 Sandy

11 7.9 0.12 Sandy















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Table.3.1.3. Soil parameters during post-monsoon period










9 8.1 0.15 Sandy

10 7.4 0.22 Sandy















25 8.1 0.98 Sandy

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Table.3.2.1. Soil parameters during south-west monsoon period.

Site No.

Macro Nutrients Micro Nutrients

Nitrogen Phosphorous Potassium Zn Cu Fe mn

1 24 3.5 65 0.66 1.10 11.76 14.2

2 28 5.5 71 0.59 1.20 9.63 12.13

3 49 3.8 51 0.47 1.30 7.42 11.11

4 46 4.3 50 0.61 1.69 7.20 10.16

5 48 4.5 63 0.63 2.01 6.00 9.14

6 49 17.0 132 0.49 0.82 8.21 12.80

7 43 19.1 169 0.35 0.98 9.36 10.40

8 74 16.8 102 0.72 0.96 9.02 11.11

9 75 20.0 103 0.76 0.92 9.16 10.20

10 92 19.3 57 0.61 0.92 10.78 10.01

11 28 17.8 142 8.98 1.04 8.98 10.14

12 63 18.6 115 8.70 1.16 10.18 10.30

13 128 25.2 174 0.67 1.19 7.98 15.01

14 45 18.0 153 0.36 1.09 8.89 9.18

15 26 9.7 147 0.88 1.12 9.99 10.18

16 65 8.5 55 0.58 1.19 9.64 12.12

17 38 10.2 170 0.60 0.90 5.40 12.90

18 52 11.4 18 18.60 2.82 8.99 10.19

19 37 9.5 158 0.85 0.96 10.90 9.90

20 44 13.9 158 0.72 0.97 13.66 10.02

21 128 9.8 230 12.66 11.40 0.68 0.90

22 36 9.1 155 0.25 0.92 6.50 14.70

23 132 10.2 180 12.33 12.00 0.62 0.99

24 186 68.0 218 15.60 10.80 0.89 1.30

25 118 56.6 240 0.82 0.99 14.01 11.38

85

Table.3.2.2.Soil parameters during north-east monsoon period.

Site No.


Nitrogen Phosphorous Potassium Zn Cu Fe mn

1 11 12.5 285 0.86 1.18 6.12 12.66

2 13 15.3 290 0.90 1.19 6.18 12.75

3 10 15.1 301 0.92 1.20 6.90 12.60

4 48 49.2 509 0.62 1.72 8.68 12.16

5 51 50.3 510 0.68 1.90 9.01 12.28

6 38 43.7 499 0.78 1.70 8.22 12.80

7 30 44.5 501 0.60 1.72 8.40 13.10

8 60 15.6 104 0.58 1.13 8.70 10.30

9 82 16.1 106 0.67 1.72 8.12 11.48

10 85 17.2 109 0.60 1.72 9.50 12.30

11 44 14.6 142 0.38 1.08 9.16 9.16

12 50 18.0 170 0.78 1.90 10.60 10.33

13 42 50.4 60 0.30 0.92 10.12 12.10

14 38 35.0 58 0.58 0.96 10.75 12.11

15 40 36.8 60 0.60 0.99 10.80 12.32

16 22 24.6 160 0.45 0.50 12.32 12.52

17 24 16.1 160 0.32 0.57 12.36 14.01

18 67 16.8 108 0.55 1.30 8.40 15.10

19 68 18.6 120 0.50 1.40 15.00 13.10

20 90 16.3 100 0.40 1.80 9.60 13.00

21 82 7.2 29 0.70 1.50 1.65 10.40

22 85 7.9 36 0.70 1.55 0.70 10.48

23 16 20.1 380 0.80 3.40 8.11 16.10

24 14 19.2 270 0.70 2.60 8.10 11.30

25 67 16..8 130 0.75 3.00 11.80 17.00

86

Table.3.2.3.Soil parameters during post-monsoon period.

Site No.


Nitrogen Phosphorous Potassium Zn Cu Fe Mn

1 27 4 67 0.69 1.13 11.89 15.8

2 30 5 73 0.61 1.32 9.70 14.1

3 49 3 51 0.47 1.30 7.42 11.11

4 47 4 52 0.52 1.30 7.10 10.12

5 50 4 64 0.59 2.09 6.20 9.60

6 49 18 130 0.32 0.83 8.10 13.21

7 72 18 106 0.76 0.79 8.16 11.12

8 106 27 58 0.27 0.93 10.12 12.06

9 92 19 57 0.61 0.92 10.78 10.01

10 29 17 150 8.42 1.09 8.99 10.20

11 64 18 116 8.82 1.16 10.01 10.34

12 223 26 162 0.48 1.18 7.68 16.17

13 43 18 160 0.38 1.01 8.80 9.18

14 26 9 147 0.88 1.12 9.99 10.18

15 65 9 58 0.64 1.30 9.88 12.68

16 36 12 175 0.65 0.92 6.50 14.70

17 36 9 155 0.72 0.94 10.85 9.88

18 37 9 158 0.85 0.96 10.90 9.90

19 44 13 158 0.72 0.97 13.66 10.02

20 130 9 210 2.68 11.80 0.72 0.92

21 135 9 218 2.98 11.88 0.79 0.98

22 36 10 168 0.24 0.95 7.70 14.62

23 132 10 180 2.33 12.00 0.62 0.99

24 186 69 218 5.60 11.10 0.90 1.30

25 118 58 256 0.90 0.98 14.20 11.40

87

Table.3.3.Seasonal variations of physico-chemical parameters of soil

Parameters UnitsSouth-west

monsoon

North-east

monsoonPost-monsoon

pH - 8.2 8.3 8.1

Ec mho/cm 0.95 0.78 0.98

Nitrogen mg/l 186 90 223

Phosphorous mg/l 68.0 50.4 69.2

Potassium mg/l 510 240 256

Zinc mg/l 18.0 0.92 8.82

Copper mg/l 12.00 3.00 11.88

Iron mg/l 14.01 12.36 140.20

Magnesium mg/l 12.90 17.21 14.62

Table.3.4.1.Soil variables of chemical parameters during south-west monsoon period

Min Max MeanStandard

deviationSkewness Kurtosis

Coefficient

variation

N 25.25 225.75 70.46 50.94951 1.758792 2.883347 72.30983

P 3.825 116.5 20.626 24.61662 2.939936 9.654315 119.3475

Po 15.625 239.5 125.1234 62.54762 0.032573 -1.01839 49.98875

Zn 0.22 15.625 3.3497 5.237071 1.519028 0.646422 156.3445

Cu 0.805 13.16 2.488 3.577991 2.430256 4.535933 143.8099

Fe 0.7125 13.705 8.1971 3.425323 -0.94216 0.896743 41.78701

Mn 0.8625 28.55 10.7083 5.285351 0.952174 5.458269 49.35752

88

Table.3.4.2.Soil variables of chemical parameters during north-east monsoon period



Coefficient

variation

N 1.65 115 47.3489 32.22021 0.173442 -0.79436 68.04849

P 6.725 53.25 22.282 12.08989 1.234737 0.765411 54.25854

Po 5.85 512 178.437 131.81 1.355457 1.386542 73.86921

Zn 0.3125 6.3575 0.83 1.161436 4.862665 24.05201 139.9321

Cu 0.55 3.23 1.5861 0.765367 1.030677 0.204137 48.25467

Fe 1.4125 12.175 9.167 2.250361 -1.71329 4.797005 24.5485

Mn 9.2175 16 12.5182 1.608643 0.287536 0.577418 12.85044

Table.3.4.3.Soil variables of chemical parameters during post-monsoon period



Coefficient

variation

N 16.25 209.5 100.19 65.61465 0.439613 -1.03241 65.49022

P 7 82 31.7473 17.42968 1.176128 1.640152 54.90129

Po 22.625 501 152.86 115.5988 2.229823 5.619833 75.62399

Zn 0.165 0.89 0.5019 0.213558 -0.064 -0.71494 42.54986

Cu 0.54 2.3225 1.1615 0.328144 1.462037 6.110901 28.2517

Fe 4.4575 15.21 9.8405 2.599404 0.01749 0.049936 26.41537

Mn 9.175 15.625 11.2143 1.481598 0.987426 1.790083 13.21169

89

Figure.3.1.1. PCA of chemical parameters during south-west monsoon period

Table.3.5.1.PCA of chemical parameters during south-west monsoon period

Table.3.5.2. PCA loadings of soil quality parameters during

south-west monsoon period

Axis 1 Axis 2 Axis 3 Axis 4 Axis 5 Axis 6 Axis 7

N 0.6883 0.4561 -0.1969 -0.4149 0.0733 0.3193 0.002116

P 0.3893 0.8244 0.319 -0.00824 -0.1057 -0.2361 -0.00544

Po 0.3054 0.2327 -0.7593 0.5207 -0.05122 -0.0367 0.02923

Zn 0.5557 -0.0248 0.5043 0.6195 -0.05667 0.222 -0.00067

Cu 0.9012 -0.2095 0.1048 -0.03482 0.3228 -0.1321 0.1009

Fe -0.791 0.3554 0.03365 0.2355 0.4342 0.03345 -0.04247

Mn -0.9453 0.2351 0.1109 -0.00328 -0.09565 0.09999 0.1401

PC Eigen values % variance

1 3.35873 47.982

2 1.168 16.686

3 0.995862 14.227

4 0.883786 12.626

90

Figure. 3.1.2. PCA of chemical variables during north-east monsoon period

Table.3.5.3. PCA of chemical variables during north-east monsoon period

Table.3.5.4.PCA loadings of soil quality parameters during

north-east monsoon period

Axis 1 Axis 2 Axis 3 Axis 4 Axis 5

N -0.2507 0.1387 0.9241 0.0958 0.09402

P 0.4989 -0.5428 0.2374 -0.6088 -0.05944

Po 0.807 -0.2786 -0.2283 0.06715 0.3416

Zn 0.5335 0.7031 -0.1473 0.05497 0.2244

Cu 0.5666 0.6246 0.3633 -0.1528 0.108

Fe 0.4404 -0.6821 0.2854 0.4322 0.1296

Mn 0.7343 0.1387 0.0606 0.1913 -0.627

PC Eigen values % variance

1 2.302 32.886

2 1.76055 25.151

3 1.20117 17.16

4 0.634094 9.0585

5 0.601034 8.5862

Component 1

N

P

Po

Zn

Cu

Fe

Mn

1

2 3

4 5

6 7 8

9

10

11

12

13

14

15

16

17

18

19

20

21

22

23

24

25

-2.4 -1.6 -0.8 0.8 1.6 2.4 3.2 4.0

-2.0

-1.5

-1.0

-0.5

0.5

1.0

1.5

2.0

2.5 C

om

pone

nt 2

91

Figure.3.1.3. PCA of chemical variables during post-monsoon period

Table.3.5.5. PCA of chemical variables during post-monsoon period

Table. 3.5.6. PCA loadings of soil quality parameters during post-monsoon period

Axis 1 Axis 2 Axis 3 Axis 4 Axis 5

N 0.3056 0.86 0.2975 -0.0509 0.04152

P 0.7514 0.4924 0.157 0.2369 -0.2544

Po 0.2067 0.1854 -0.7524 0.5706 0.1721

Zn 0.7314 -0.4916 -0.2502 -0.2076 -0.05182

Cu 0.8089 -0.4543 0.08034 0.1575 -0.1695

Fe 0.8645 0.01537 0.1661 -0.2296 0.3841

Mn -0.1091 -0.3907 0.7234 0.5264 0.1298

N

P

Po

ZnCu

Fe

Mn1

2

3

45

6

7

89

10

1112

13

1415

16

1718

19

20

21

22

23

24

25

-4.0 -3.2 -2.4 -1.6 -0.8 0.8 1.6 2.4 3.2

Component 1

-3.0

-2.4

-1.8

-1.2

-0.6

0.6

1.2

1.8

2.4C

om

po

nen

t2

PC

Eigen

value % variance

1 2.64923 37.846

2 1.61744 23.106

3 1.29921 18.56

4 0.78201 11.172

5 0.291851 4.1693

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