A Satellite-Based Crop Insurance That Compensates for Rainfall Deficit

Abstract

There is urgent need for innovative solutions that can be used to reduce the devastating impacts that extreme weather has on agriculture. Index-based crop insurance (IBCI) promises to be a capable tool that can be used to this end. However, the widespread adoption of IBCI is hindered by basis risk, which plagues many IBCI designs. This study uses satellite-based rainfall estimates (SRFE) and weather station-based evapotranspiration (WSE) data to design an IBCI model for maize. The SRFEs estimate rainfall with high accuracy at 20day and monthly time steps and are then combined with WSE data to design an IBCI model. The model covers the (1) development, (2) mid-season, and (3) late-season stages of maize. We then formulate IBCI thresholds including the weight, trigger, exit and tick, for each of the above-listed growth stages. This approach can be tested in other areas with different growing conditions and alternative sources of rainfall and evapotranspiration data.