Prediction Of Wheat Yield By General Large Area Model For Annual Crops As Driven By Regional Climate Model And Observational Data

A new process based crop model, the general large area model (GLAM) for annual cropsrnand a Regional Climate Model (RegCM3) have been used for this study to predict thernwheat yield in Southern nations, nationalities and people's region (SNNPR) of Ethiopia.rnThis study aims to demonstrate how RegCM3 and GLAM could be used to forecastrnwheat yield. RegCM3 is used to predict precipitation, maximum temperature, minimumrntemperature and solar radiation over SNNPR. These variables are used in GLAM asrninputs for yield forcast. All the internal consistency checks that are used to ensure thernperformance of the crop model prove that GLAM performs magni cently. The observedrnand the simulated yield exhibit a high correlation on the central part of the study area.rnHowever, GLAM yield has a negative bias which is found to be related with water stress.rnThe water stress is con rmed from RegCM3 precipitation forcast which has a negativernbias with respect to observed precipitation from Central Research Unit (CRU). As a resultrnof this low correlation of observed and simulated yield has been detected in the North-rneast and South-west part. The model can be easily extended to any annual crop for therninvestigation of the impacts of climate variability (or change) on crop yield over largernareas

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