Abstract
<title>Abstract</title> <p>Flooding is a recurring problem in the Wainganga River basin of central India, causing considerable damage to agriculture, infrastructure, and human settlements during intense monsoon events. This study presents an integrated approach for rainfall-runoff modelling and flood forecasting using geospatial techniques and the Hydrologic Engineering Center–Hydrologic Modeling System (HEC-HMS). Rainfall and discharge data from 2001–2017 were collected for the Wainganga basin to identify representative rain gauge stations and evaluate runoff behaviour. Hierarchical clustering was applied to classify rain gauge stations according to rainfall similarity, while the Thiessen polygon method was used to determine areal rainfall distribution. Basin delineation, land use/land cover analysis, and hydrological parameter extraction were performed using ArcGIS and HEC-GeoHMS.The HEC-HMS model was calibrated for 2001–2010 and validated for 2011–2017 using observed discharge data at Asthi outlet station. Model performance was evaluated using Nash–Sutcliffe Efficiency (NSE), coefficient of determination (R²), and Root Mean Square Error (RMSE). The model produced satisfactory results, with NSE values ranging from 0.897 to 0.98, R² values above 0.895, and RMSE values between 0.2 and 1.36 during calibration and validation. Simulated peak discharge values closely matched observed discharge trends for major monsoon events. The results demonstrate that the combined application of hierarchical clustering, Thiessen polygon analysis, and HEC-HMS modelling significantly improves runoff estimation and flood forecasting accuracy in the Wainganga basin. The developed framework can support flood management, water resource planning, and early warning systems in monsoon-dominated river basins.</p>