assessing the impact of climate change in the shire valley of malawi

8/3/2019 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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assessing the impact of climate change in the shire valley of malawi

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