Leveraging a spatio–temporal drought severity and coverage index with crop yield modelled as a stochastic process

An analysis of spatial and temporal variation of drought impact may offer an unbiased glimpse into factors that may dictate drought severity at an apt local scale. In this study drought indices, for example, drought severity and coverage index, I_SC, and, a derived crop–based drought severity and coverage index, I_SC,AG, were scaled down to county levels. Drought frequency analyses showed clear demarcation of counties in an observable dichotomy. This demarcation has significant implications on crop yield. This impact was analysed using USDA National Agricultural Statistics Service (NASS): a) county level yield; b) developed ISC values; c) Markovian process on transition of crop yield categories. From this study the immediate observation was: a) southwest counties, for example, are also susceptible to secondary effects due to drought; b) crops like corn are more susceptible to periodic wetness disturbance.

Keywords: drought severity, drought coverage index, transition probability, crop yield, modelling, drought impact, USA, United States