Rainfall risk and “response farming”: Using rainfall analysis, simulation modeling and GIS to improve agricultural decisions in Mali
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SANREM CRSP, University of Georgia
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In this study, analyses of historical rainfall records are combined with GIS and biophysical modeling of soil water balance and crop production to predict performance of millet cultivars in Mali. The research improves previous efforts to apply rainy season predictions to agricultural decisions in the Sahel region, by integrating soils and crops information and by using crop simulation modeling. For two data sets defined by (early or late) rainfall onset date, the simulated crop yields, average water stress, and overall stress indices relative to yield potential have been computed and mapped. Research findings indicate that probability analysis and simulation modeling can be used to minimize agro-climatic risk.
(Excerpt from paper)
This brief draws from a paper by Oumarou Badini and Lassana Dioni entitled “Application of Rainfall Analysis, Biophysical Modeling and GIS to Agroclimatic Decision Support in Madiama Commune, Mali (West Africa).” and presented to the SANREM CRSP Research Scientific Synthesis Conference, November 28-30, 2001, Athens, Georgia.