Multivariate Analysis and Assessment of Regional Drought Risks under Climate Change using Copulas

This study intended to understand the effect of climate change on spatiotemporal characteristics of multivariate drought risk over the Vidarbha region of India. The Standardized Precipitation Evapotranspiration Index (SPEI) is employed to characterize droughts in the region. Gridded daily precipitation and temperature data produced by the Indian Meteorological Department (IMD) and Coupled Model Inter-comparison Project Phase 6 (CMIP6) were utilized for estimating the SPEI. The drought events were identified and subsequently characterized by duration, severity, and peak. Different goodness of fit tests was applied to select the best fitting marginal distributions of the individual drought characteristics. Several symmetric and asymmetric Archimedean trivariate copulas and seven bivariate copula families were evaluated for joint distribution modeling. Maximum pseudo-likelihood and genetic algorithms have been applied to estimate the copula parameters accurately. The asymmetric Frank copula was selected to construct the trivariate distribution of the drought characteristics. Frank, Student’s t and Clayton copulas were chosen to build the bivariate distribution of duration-severity, duration-peak, and severity-peak, respectively. The joint distributions were applied for computing the joint return periods of drought events. The drought risk over the region was illustrated using zoning maps for historical along with near and far future periods. The inferences derived from the study will help policymakers to prepare better mitigation strategies under the changing environment.