Assessment of Return Periods for Flood Frequency and Risk Mapping of Floods and Cyclones in India using Arcgis

Abstract

Due to its diverse geography and climate, India is highly susceptible to natural disasters like floods and cyclones, with an 8,000-kilometer coastline exposed to 10% of the world's tropical storms, five to six form annually, with the Bay of Bengal being particularly affected due to its higher frequency. This study aims to conduct a detailed flood frequency analysis and risk mapping for the 2014 Srinagar flood, utilizing statistical techniques and GIS-based tools to evaluate the return periods and recurrence frequencies. The study incorporates data from three gauging stations, Asham, Sangam, and Ram Munsi Bagh, regarding discharge rates in cubic meters per second (cms). Statistical models were applied, including Normal, Log-Normal, Log-Pearson Type III, and Gumbel distributions. GIS data was sourced from USGS, DIVA-GIS, and WorldClim to assess flood risk and affected areas. The study’s result revealed that while Log-Normal and Log-Pearson models did not exceed threshold values, the Gumbel distribution indicated potential exceedance at a 95% confidence level, suggesting enhanced safety measures were needed. The analysis shows varying risk levels across gauging stations, with recommendations for improved flood management strategies, especially for areas prone to high flood risk. Further research should focus on refining flood prediction models, enhancing GIS capabilities for risk assessment, and implementing comprehensive flood mitigation strategies.