Regional Climatological Drought: An Assessment Using High-Resolution Data

Abstract

Regional assessments of droughts are limited, and meticulous assessments over larger spatial scales are generally not substantial. Understanding drought variability on a regional scale is crucial for enhancing the resiliency and adaptive ability of water supply and distribution systems. Moreover, it can be essential for appraising the dynamics and projection of droughts based on regional climate across various spatial and temporal scales. This work focuses on drought analysis using a high-resolution dataset for three drought-prone regions of India between 1950 and 2016. This study also uses monthly values of the self-calibrating Palmer Drought Severity Index (scPDSI), incorporating Penman–Monteith approximation, which is physically based on potential evapotranspiration. Climate data are statistically downscaled and formulated to form a timeline for characterizing major drought events. The downscaled climate data hold a good statistical agreement with station data with correlation coefficients (R) ranging from 0.91 to 0.96. Drought analysis indicates and identifies several major incidences over the analysis time period considered in this work, which truly adheres to the droughts recorded in reports of various literatures for those regions.

Keywords

• drought index
• climate variability
• downscaling
• scPDSI
• precipitation
• temperature