Agricultural Risk Decision Support System for Resource-Poor Farmers in Burkina Faso, West Africa

Abstract

A stochastic mixed integer programming decision support system (DSS) to aid farmers in the Sahel-Sudan region of West Africa is formulated. It provides optimal crop planting practices that minimize the caloric deficit of a household and maximize limited household income given a seasonal probabilistic rainfall forecast and the farmer’s risk level. The recommendations of the DSS are subjected to sensitivity analyses related to labor availability, prices, and risk level. Furthermore, survey data gathered from a case study of Bonam Village are presented for comparison with the output of the DSS. It is found that the DSS captures many of the complexities of agricultural management practices such as the strategy of diversification. An optimization model like this may have future applications in West Africa to improve agricultural decision making and also test hypotheses related to climate forecasts and improvements in household food security.