<![CDATA[The Air Bengkulu River experiences flooding at least twice a year due to increased discharge during the rainy season. This study aims to calibrate hydrological model parameters based on daily rainfall data for the flood event of 30 August 2022 using HEC-HMS modeling to obtain a best design for flood discharge. Calibration was conducted by simulating the rainfall occurred during the flood event to reproduce the observed discharge recorded at the gauging station, using the SCS-Curve Number (SCS-CN) loss method and the Snyder transform method in HEC-HMS 4.10. The parameters included the Peak Rate Factor (PRF) in the SCS loss scheme and the Ct and Cp coefficients in the Snyder method, while the CN and impervious values were determined based on land-use maps. The results indicated that both approaches produced relatively similar calibration outcomes; however, the Snyder method is better than the SCS-CN. The Snyder approach showed moderate performance with PBIAS = 0.34% (Very Good), RMSE = 0.7 (Satisfactory), and NSE = 0.509 (Good). It was, therefore, adopted for design flood discharge estimation with results Q2 = 277.9 m³/s, Q5 = 458.5 m³/s, Q10 = 585.9 m³/s, Q25 = 752.6 m³/s, and Q50 = 879.4 m³/s. The observed discharge during the 30 August 2022 flood event (478.55 m³/s) falls between the Q5 and Q10 return periods. Overall, the study demonstrates that parameter calibration plays a crucial role in improving hydrograph representation, although further evaluation using hourly data and multiple flood events is necessary to enhance model reliability.]]>
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