Future drought changes and associated uncertainty over the homogenous regions of India: A multimodel approach

Abstract

AbstractDrought frequency and intensity have increased in recent decades and are expected to escalate in future under the changing climate scenario. However, a wide range of uncertainty exists regarding the risk, variability and severity of the drought. This study evaluates the future drought and associated uncertainty over homogeneous regions of India using the suites of CMIP5 global climate models (GCMs) and CORDEX‐SA regional climate models (RCMs). The drought characteristics and its projected future changes are analysed using probability density functions derived from hydroclimatic parameters, including the standardized precipitation index (SPI) and the standardized precipitation‐evapotranspiration index (SPEI). Besides, uncertainties from various sources such as inter‐model variability, indices type, timescale, adapted methods, and time‐slices are explored under the RCP8.5 emission scenario to the end of the 21st century. Our study reveals large biases in the individual model; however, both the multi model ensembles (GCM and RCM) generally demonstrate better performance with respect to observation. In particular, the RCM ensemble showed limitations in capturing the regional precipitation pattern while temperature and potential evapotranspiration (PET) showed considerable enhancement concerning GCMs. SPI (SPEI) generally exhibited enhanced wetness (dryness) derived from increased precipitation (PET), although a few discrepancies were noticed. The regional heterogeneity was also found to exist, although some robust changes were noticed in drought frequency and severity with different return periods. Our finding underscores a wide range of uncertainties in drought projection, with maximum contribution from indices selection followed by model variability whereas other sources have the least contribution. The primary drivers for all these uncertainty sources arise due to variations among models simulated hydroclimatic variables that need to be parameterized more precisely for sustainable drought management.