Natural Hazards and Earth System Sciences (Feb 2023)
Evolution of multivariate drought hazard, vulnerability and risk in India under climate change
Abstract
Changes in climate and socio-economic conditions pose a major threat to water security, particularly in the densely populated, agriculture-dependent and rapidly developing country of India. Therefore, for cogent mitigation and adaptation planning, it is important to assess the future evolution of drought hazard, vulnerability and risk. Earlier studies have demonstrated projected drought risk over India on the basis of frequency analysis and/or hazard assessment alone. This study investigates and evaluates the change in projected drought risk under future climatic and socio-economic conditions by combining drought hazard and vulnerability projections at a country-wide scale. A multivariate standardized drought index (MSDI) accounting for concurrent deficits in precipitation and soil moisture is chosen to quantify droughts. Drought vulnerability assessment is carried out combining exposure, adaptive capacity and sensitivity indicators, using a robust multi-criteria decision-making method called the Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS). In the worst-case scenario for drought hazard (RCP2.6-Far future), there is a projected decrease in the area under high or very high drought hazard classes in the country by approximately 7 %. Further, the worst-case scenario for drought vulnerability (RCP6.0-SSP2-Near future) shows a 33 % rise in the areal extent of high or very high drought vulnerability classes. The western Uttar Pradesh, Haryana and western Rajasthan regions are found to be high risk under all scenarios. Bivariate choropleth analysis shows that the projected drought risk is majorly driven by changes in drought vulnerability attributable to societal developments rather than changes in drought hazard resulting from climatic conditions. The present study can aid policy makers, administrators and drought managers in developing decision support systems for efficient drought management.