Copula-based drought risk analysis on rainfed agriculture under stationary and non-stationary settings.

Assessing the risk to the agricultural system is important for agricultural sustainability. The present study analyses agricultural drought risk with respect to different drought severities. Different drought indices – namely, Standardized Precipitation Evapotranspiration Index (SPEI), Standardized Soil moisture Index (SSI), Vegetation Condition Index (VCI), and Temperature Condition Index (TCI) – are used to evaluate the conditional probability. Non-stationary analysis is carried out for SPEI and SSI to incorporate the impact of large-scale oscillations and regional hydrological variability. Copula analysis is performed between drought conditions and various crop yield anomalies over Maharashtra, India, during 1998–2015. The outcomes suggest that SPEI is a significant drought indicator over the maximum number of districts in all the crops. Sea Surface Temperature (SST) and Indian Summer Monsoon Index (ISMI) are selected as suitable covariates to model the non-stationarity in the SPEI time series. The drought risk is estimated to increase with drought severity for all of the selected crops. It is observed that the exclusion of non-stationarity will underestimate the agricultural risk. [ABSTRACT FROM AUTHOR]