Analysis of flood streamflow sensitivity to precipitation using the WRF-Hydro model in a humid environment

Basin-scale runoff forecasting requires controlling absolute relative errors within 0.2 for accurate predictions. This study examines the sensitivity of simulated flood deviations in frequently flooded humid regions to discrepancies in precipitation driving the Weather Research and Forecasting (WRF)-Hydro model. Key parameters of various WRF-Hydro modules are calibrated from 23 flood events between 2003 and 2017. Two experiments were designed with minimized uncertainty in both model and parameterization to explore the sensitivity of streamflow changes to precipitation misestimations, both in total and graded precipitation. The sensitivity of runoff relative errors is more pronounced than that of precipitation relative errors, influenced by the magnitude, variability, and duration of rainfall. During processes involving heavy rainstorm, precipitation absolute relative errors increased by 50%, while runoff absolute relative errors increased by more than 60%. This sensitivity trend is linked to variations in components generated by misestimated precipitation. Runoff relative errors are higher when precipitation is misestimated at high rainfall levels compared to the same misestimation at low rainfall levels. For effective flood simulation and prediction, it is crucial to emphasize the accuracy of precipitation, especially during high rainfall events. Future research will incorporate more realistic precipitation forcing mechanisms and additional metrics for evaluating precipitation forecast.