College of Hydrology and Water Resources，Hohai University
The insufficient rain gauges and historical observational data bring difficulties to snowmelt runoff forecast in the Dadu River Basin. Based on the high-resolution ERA5-Land reanalysis dataset, snow cover fraction and average snow depth were introduced into the snowmelt model to improve the snowmelt routine of the HBV hydrological model, so as to enhance the reliability of simulating snowmelt runoff. Taking the upper reaches of the Dadu River as the study area, hydro-meteorological data from 1961 to 2018 were selected for model calibration and validation, and 2019 for trial forecasting. The results demonstrate that by incorporating ERA5-Land reanalysis data and improving the snowmelt module, the advantages of simulating snow accumulation and ablation are fully utilized, which effectively enhances the accuracy of forecasting snowmelt runoff, showing the applicability of this approach in the data-scarce Dadu River Basin. This study could provide references of snowmelt runoff simulation and forecasting to regions with limited hydrological data.