Abstract
Assessing the risk on agricultural system is important for agricultural sustainability. The present study analyses the agricultural drought risk with respect to different drought severities. Different drought indices namely SPEI, SSI, VCI and TCI are used to evaluate the conditional probability. The non-stationary analysis is carried out for SPEI and SSI drought indices to incorporate the impact of large-scale oscillations and regional hydrological variability. The copula analysis is performed between drought conditions and different crop yield anomalies over the Maharashtra, India during 1998-2015. The outcomes suggest that SPEI is found as significant drought indicator over the maximum number of districts in all the crops. The SST and ISMI are selected as suitable covariates to model the non-stationarity in SPEI time series. The drought risk is estimated to increase with the drought severity for all the selected crops. It is observed that the exclusion of non-stationarity will underestimate the agricultural risk.
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