Estimation of peak discharge and flood volume in ungauged basins using HydroCAD software

Accurately estimating peak discharge and flood volume in small and data-deficient basins within larger watersheds is crucial for effective flood planning and management. This study focuses on the Kamalvand Central Site and the Faculty of Agriculture and Natural Resources (FANR) at Lorestan University to determine maximum flow and flood volume. This estimation is achieved by applying the SCS-CN method , utilizing rainfall patterns generated by the fractal method within the HydroCAD software environment. Flow measurements were taken during precipitation events on December 18, 2021 (39 mm of precipitation) and January 03, 2022 (29 mm of precipitation) for the FANR basin and Sub-basin 2 of the Kamalvand site to validate the rainfall-runoff model. The results from the SCS-CN model were compared with empirical methods, such as Fuller and Creager , to assess its performance. The results showed that the fractal method could accurately estimate precipitation duration and return periods. In addition, the IDF of this method, compared with Ghahraman, showed low RMSE in the period of low returns (from 2 to 100 years). The relationship between the scale exponent and weighted moment order for all stations was linear and statistically significant at the 1% level. The highest peak flow and runoff volume in the FANR Basin belong to Sub-basin 1 , measuring 22.35 m 3 /s and 1,32,000 m 3 for a 25-year return period, respectively. Furthermore, the highest values for these variables in the Kamalvand basin are associated with Sub-basin 2 , which covers an area of 237 hectares and has a curve number of 80, with a concentration–time of 18.4 min. In this context, peak flow and flood volume for the 25-year return period were estimated at 23.49 m 3 /s and 54,540 m 3 , respectively. Flow measurement results from both basins indicated the accuracy of the SCS-CN model in simulating and estimating flow, with correlation coefficients of 0.88 and 0.94 and Nash–Sutcliffe coefficients of 0.74 and 0.52 for the Kamalvand and FANR basins, respectively. Moreover, the results demonstrated the high performance of the SCS-CN model in estimating peak flow based on designed rainfall patterns using the fractal method and utilizing the curve number obtained from Sentinel 2 imagery within the HydroCAD software environment, compared to empirical methods like Fuller and Creager , for return periods of 25, 50, and 100 years. Therefore, this rapid and practical approach is recommended for other ungauged basi