Modeling non-stationary 1-hour extreme rainfall for Indian river basins under changing climate

Abstract

India’s complex topography and the increasing influence of climate change have exacerbated the challenges of modeling 1-hour non-stationary extreme rainfall events. Prior studies have indicated rising intensities of such events, particularly in coastal and urban areas. This study addresses these issues by developing 155 basin-specific non-stationary surface response models, incorporating geographical, climatic, and temporal covariates. Using 13 Max-Stable Process (MSP) characterizations, extreme rainfall variability across 11 major river basins and three-time scales were effectively modeled. The Brown-Resnick, Geometric-Gaussian, and Extremal-t models demonstrated varying effectiveness across regions. The findings emphasize the critical role of region-specific analysis in water resource management and disaster preparedness, where the high temporal resolution datasets are limited for the point process-based models. The global processes and regional climate change are found to predominantly influence 1-hour extreme rainfall across the majority of river basins in India.