Integration of frequency analysis and HEC-RAS for probabilistic flood hazard mapping

Climate change is altering flood patterns in India, emphasising accurate flood assessment for effective resource management through flood frequency analysis. This study evaluates three probability distribution methods: log-normal, Gumbel’s extreme value (GEV), and log-Pearson type 3 (LP3) using annual maximum discharge data (1973–2018) from the Dhanera gauging station in the Rel River basin. The most suitable model is determined by way of Kolmogorov–Smirnov, Anderson–Darling and chi-squared tests at a 5% significance level, with GEV identified as the best fit. Predicted peak discharge values for return periods of 2, 5, 10, 25, 50, 100 and 200 years were integrated into a two-dimensional hydraulic model, validated against observed flood depths from July 2017. Maximum discharge and averaged digital elevation model data were utilised in the Hydrologic Engineering Center river analysis system (HEC-RAS) model to predict inundation, processed with ArcGIS to create flood inundation maps. The 200 year return period simulation revealed areas also affected by the historic 2017 floods. This research offers crucial insights into flood depths and characteristics, aiding government authorities and stakeholders in making informed decisions for risk-based mitigation post the floods of 2015 and 2017.