Floodplain inundation modeling and mapping using integrated HEC-HMS and HEC-RAS model on Dirma River Watershed, Lake Tana Basin, Ethiopia

Dirma River Watershed, Lake Tana Basin, Ethiopia. Floods are devastating, damaging natural disasters with major environmental, social, and economic consequences. This study focuses on modeling and mapping floodplain inundation in the Dirma River watershed to analyze flood frequency, identify sensitive hydrological parameters, and generate inundation maps for risk management. Hydro-meteorological, geometric, and spatial datasets were collected from on-site measurements and governmental sources, then pre-processed and quality tests were controlled. Flood frequency was analyzed using EasyFit software, rainfall-runoff model was simulated using HEC-HMS, and flood extent was determined using HEC-RAS model. The model was calibrated (2000–2013) and validated (2014–2020). Model sensitivity analysis indicated that the Soil Conservation Services Curve Number (SCS-CN-CN), Soil Conservation Services Curve Number Initial Abstraction (SCS-CN-Ia), and SCS Unit Hydrograph-Lag Time are the most influential parameters. The model demonstrated good performance, with coefficient of determination (R 2 ) values of 0.82 (calibration) and 0.87 (validation), and Nash-Sutcliffe efficiency (NSE) values of 0.73 and 0.78, respectively. Using simulate peak discharges from HEC-HMS, the HEC-RAS model generated floodplain inundation maps, showing inundation extents from 9.58 km² (2-year return period) to 11.68 km² (100-year return period). These results highlight increasing flood risks and emphasize the need for integrated flood management strategies, including structural and non-structural measures such as levees, afforestation, and land-use planning. • Floodplain inundation modeling was conducted in the Dirma River watershed. • SCS Curve Number, Initial Abstraction, and Lag Time were key sensitive parameters. • The model showed good-to-very good performance (NSE = 0.73–0.78; R² = 0.82–0.87). • Flood extent expanded from 9.58 km 2 (2-year) to 11.68 km 2 (100-year) return period. • Findings support integrated flood management and sustainable land-use practices.