Assessing the Impact of Climate Change in the Shire Valley of Malawi
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Transcript of Assessing the Impact of Climate Change in the Shire Valley of Malawi
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Outline of PresentationIntroduction
Statement of Problem
ObjectivesLiterature Review
Methods and material
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Chapter One1.0 INTRODUCTION
Cereal production is a major component of small-scale farming in Southern Africa.
Sorghum is one of the major staple food inMalawi, contributing 60 % of calories to the diet inShire Valley(http://www.fao.org/wairdocs/x5001e/X5001e02.htm)
Decreasing trend in sorghum and others cerealyields due to droughts, floods and prolonged dryspell.
http://www.fao.org/wairdocs/x5001e/X5001e02.htmhttp://www.fao.org/wairdocs/x5001e/X5001e02.htmhttp://www.fao.org/wairdocs/x5001e/X5001e02.htmhttp://www.fao.org/wairdocs/x5001e/X5001e02.htm -
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Comparison of rainfall onset and
crop performance in 2011/2012
seasonPictures taken by Vanya, 28.12.2011
Wilting Maize, in the
peripheral of Shire Valley andShire Hi hlands
Maize flourishing in good
rains, Shire highlands,outskate of Blantyre .
Delayed onset
Dry spells Normal rains
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1.0 INTRO CONTD
Agricultural activities have become a focus ofmodeling the impact of climate change on povertyand people livelihoods
As farmers battle climate change and variability,
poverty is another major threat to food security.Frequent and intense extreme weather events has
disrupted the country both socially and economically,
since 1970, six major droughts occurred (i.e., 1978/79,1981/82, 1991/1992, 1994/95 2001/2002 and 2004/2005)
Extreme exposure and limited adaptation capacity ofthe rural farmers is a major threat to food security.
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1.2 Statement of the problem and
Research question
Statement of the problem
Little has been done on the use of crop models (eg. APSIM)to assess influence of climate change on sorghum yield.
Little is known on the impact of climate change onsorghum yield in Shire Valley using Climate A1B and B2scenarios.
Research questionWhat impact will climate change have on future sorghum
yield in the lower Shire Valley of Malawi?
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1.3 OBJECTIVESMain Objective:
The main objective of this research is to assess theimpact of climate change on sorghum yield underrainfed condition.
SPECIFIC OBJECTIVESTo assess the effects of long term climate variability
and climate change on sorghum yield under presentand future scenarios in the Lower Shire Valley.
Evaluate the capability of APSIM-sorghum model tosimulate growth, development and yield of sorghum.
Quantify the impact of climate change on sorghum
yield
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1.4 Justification Agriculture remains the only major source of
income in terms of employment and foreignexchange in Malawi (FAO, 2007; Deloitte, 2011).
Climate variability has been significantly
destructive and disruptive to crops growingcommunities(ActionAid, 2008) threatening foodsecurity in the areas (World Bank, 2010; NSO2008).
Most studies were on other crops such as maize,rice and cotton, on cultivars, pests and diseasesand very little on sorghum in relation to climate .
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1.4 Justification APSIM has been tested extensively used sorghum,
maize and wheat growth and yield, soil water balanceand summer soil water dynamics in the WesternAfrica, China, India and Australia wheat belt (Assenget al. 1998; Dolling et al. 2006) and found robust
Proposed research addresses one of the corechallenges as identified by the Governments MalawiGrowth and Development Strategy (MGDS) 20062011aimed at making Malawi a hunger free nation
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Chapter two2.0 LITERATURE REVIEW
UNDP, 2010, MDGS 2006-11, NAPA, 2006 noted thatclimate change is a socio-economic and environmentalissue that threatens the achievement of MillenniumDevelopment Goals aimed at poverty and hungerreduction, health improvement and environmental
sustainability.Semenov, 2009, Solomon et al. 2007 observed that
various studies have predicted an increase in frequencyand magnitude of extreme weather under climate
change.Barnett et al. 2006 also observed that most global
climate models (GCM) simulate increased summerdryness and winter wetness over most parts of the global
and sub Sahara Africa.
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2.0 LITERATURE REVIEW CONTD
Over southern Africa an increased chance ofintense rains due to the greater water-holdingcapacity of a warmer atmosphere, and would resultinto flooding was noted.
Prediction by IPCC shows that by 2100 a globalaverage surface temperature increase may bebetween 1.8 and 4.0 C while with a global averagetemperature increases of only 1.5 2.5C degrees,there is high extinction risk of animal and plantspecies by approximately 20-30% (FAO, 2007).
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LITERATURE REVIEW CONTD
The 2002 Vulnerability and Adaptation AssessmentReport indicated that Malawi is experiencing a rangeof climatic hazards, which include extreme rainfall,floods, seasonal and multi-year droughts, dry and coldspells, strong winds, thunderstorms, landslides,hailstorms, earthquake and mudslides, heat waves,and many others.
J.C.R Hunt, et al., 2010 found out that resolutions of
regional climate models (RCM) are finer compared tocoarse GCMs such that they can resolve climaticchanges over spatial order of 10 km so that impacts ofclimate change on agricultural fields can be studiedonly qualitatively at this time,
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Study site and ClimateShire Valley composed of Chikwawa and
Nsanje Districts, located in southern Malawi(32 180 m). A major cereal producing area, semi-arid
climate .It lies between 34.27 to 35.32E and 15.84S to
17.14S and span across two districts fromKapachira falls (Chikwawa) to Nsanje at thebottom of the country where the valley is itsunique feature
Chapter Three
3.0 STUDY SITE, DATA AND METHODOLOGY
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1.4 STUDY AREA
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3.0 Study site and Climate /..
The area has two seasons: Wet and dry ,where wet
season start from November to April
Dry period is divided into two.
Hot period between September till rain starts
Cool period from May to August
Temperatures in the Valley, are hot, with maxima of
around 36 C and minima of 20 C.
Main rain bearing systems apart from, Inter-TropicalConvergence Zone (ITCZ), Congo(Zaire) Air mass,
Tropical Cyclones and Easterly waves also contribute to
rainfall in the area.
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3.2 Data Source and Crop Model
APSIM Parameterisation and Evaluation Two sites will be used with a single summer season Two levels of fertilizers(0, 50 kg ha-1) and three levels of P (0, 25 kg ha-
1)
Climate scenarios: Rainfall, 16% increase, 16%+CO2, Temperatures: andCarbon dioxide: 250 ppm, 625 and 750ppm
Two sorghum Varieties to be used Thengalamanga (Local variety, alate maturing), Pirira (early maturing) from (SVADD)
Management system employed:
Sowing dates range: 15 November- 10 January
Planting density: 30plants/ Space between rows: 1m
Planting depth: 30mm
Soil type: Makande ( black vertosols- clay loam soils)
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3.3 Methodology3.4.1 Estimation of Missing Dataand Data Homogeneity. Arithmetic mean method, the simplest and most objective
method of estimating missing data will be use. It involvesreplacing the missing data with the average or the mean fora given station.
Cumulative annual totals of rainfall, temperatures andsorghum yield data will be plotted against theircorresponding years for all the stations considered in thestudy.
3.4.3 Time Series Analysis and Correlation Analysis. Time series analysis will be used to study the variability of
rainfall, temperatures and sorghum yield characteristics inthe study area during the period under consideration bydetecting trends within seasons.
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3.4Output verification methods The performance of APSIM will be statistically evaluated based
on the observed yield records for 1994-2010 and simulated yield
using root mean square error (RMSE) and Bias, the index ofagreement, din equations 1 and 2 (Willmott et al 1985; Loagueand Green, 1991).
They will be used as indicators for establishing the accuracy ofclimate model outputs.
(1)
The index of argument of the observed and simulated models (0),
(2)
where Si and Oi are the simulated and the observed yields, n thenumber of observations, and the mean of the simulated andobserved yields respectively. For a good simulation, it is expectedto have values of RMSE and das close as possible to 0 and 1respectively. High values ofdclose to 1 indicate good modelperformance and better relation of observed verses simulated.
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4.0 EXPECTED RESULTS
It is expected that this research will result in thefollowing outcomes;
projected changes in sorghum yield under different
climate scenarios. Identification of areas where sorghum production
may be particularly vulnerable to climate change
Identification of climate scenario or, and
management technique that will likely optimize orreduce crop yield in in future.
Dissemination of the above information by published
papers in both local and academic journals.
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TIME PLAN
ACTIVITY TIME FRAME
PROPOSAL WRITTING October-November 2011
PROPOSAL PRESENTATION November 2011 January2012
DATA COLLECTION Nov- January 2011
DATA ANALYSIS Jan-Feb 2012
REPORT WRITTING March-APRIL 2012
PROJECT PRESENTATION AndINCORPORATION OF CORRECTIONS
May 2012
PRINTING AND SUBMISSION
JUNE 2012
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