Agricultural Drought Monitoring in Kenya Using Evapotranspiration Derived from Remote Sensing and Reanalysis Data

More than half of the people in sub-Saharan Africa live on less than US$ 1.25 per day, and nearly 30% do not receive suf–cient nourishment to maintain daily health (UN, 2009a). These –gures are expected to rise as a result of the recent global –nancial crisis that has led to an increase in food prices. Food for Peace (FFP), the program that administers more than 85% of U.S. international food aid, recently reported that the seven largest recipient countries of food aid worldwide are in sub-Saharan Africa (FFP, 2010). In Kenya, the –fth largest recipient of food aid from FFP and a country highly dependent on rainfed agriculture, below-average precipitation in 2009 led to a 20% reduction in maize production and a 100% increase in domestic maize prices (FEWS NET, 2009). Given these sorts of climatic shocks, it is imperative that mitigation strategies be developed for sub-Saharan Africa and other regions of the developing world to improve the international and national response to impending food crises. Crop monitoring is an important tool used by national agricultural of–ces and other stakeholders to inform food security analyses and agricultural drought mitigation. Remote sensing and surface reanalysis data facilitate ef–cient and cost-effective approaches to measuring determinants of agricultural drought. In this chapter, we explore how remotely sensed estimates of actual evapotranspiration (ETa) can be integrated with surface reanalysis data to augment agricultural drought monitoring systems.