Author(s): Ankita Mukherjee; Vikas Poonia; Somil Swarnkar
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Keywords: Compound flood Copula Flood drivers Extreme events River basin Indi
Abstract: Floods are among the most devastating natural disasters in India, causing significant loss of life and property. While recent studies have focused on simultaneous flood drivers, such as precipitation and storm surge, precipitation and runoff, and more, there has been a lack of focused study on concurrent flood drivers in India. To address this gap, we have conducted a detailed flood analysis from 1980 to 2023 for Peninsular India river basins, based on precipitation, runoff, and soil moisture data. A specific percentile threshold (95th and 99th percentile) was selected for each of the three parameters to identify extreme events. A univariate analysis was first performed on each parameter individually. The copula method was then applied to estimate joint distributions, followed by calculations of exceedance probability, conditional probability, joint return period, and conditional return period for the pairs of precipitation-runoff, precipitation-soil moisture, and runoff-soil moisture. To analyse the impact of all three parameters at once, trivariate copula was used to denote the joint distribution of precipitation, runoff and soil moisture and understand their joint exceedance and return period. Results indicate that bivariate and trivariate analysis provides deeper insights when two or more parameters contribute to flood events, a phenomenon known as compound flooding. Our findings underscore the importance of understanding the interactions between multiple drivers in assessing flood risk, contributing valuable knowledge to flood management strategies in India.
Year: 2025