Flood Simulation Study of China’s Data-Deficient Mountainous Watersheds Based on CMPA-Hourly

Abstract

Heavy rainfall and flood disasters are frequent in mountainous watersheds in southwest China, and forecasting runoff floods in some mountainous watersheds is difficult. In this study, a typical watershed in the southwest mountainous region, the Qingyi River (13,000 km2), was selected for the lack of precipitation observation data in the watershed, and the BTOPMC (block-wise use of the topographic-based hydrologic model (TOPMODEL)) was used, using CMPA-Hourly (China Hourly Merged Precipitation Analysis combining observations from automatic weather stations, meteorological satellite, and weather radar at 0.05° × 0.05° grid) to improve the accuracy of flood forecasting. The results show that the Nash–Sutcliffe efficiency (NSE) of the flood forecast for the verification period in the Jiajiang section of the Qingyi River using CMPA-Hourly improved from 0.66 to 0.78, the flood error reduced from 18% to 9%, and the overall accuracy reached grade B or above. The results indicate that CMPA-Hourly, which integrates ground observation–radar–satellite precipitation, effectively combined the advantages of different sources of data to improve the resolution and accuracy of precipitation data, and then CMPA-Hourly can be used to improve the accuracy of runoff and flood forecasting.