Improving flood simulation capability of the WRF-Hydro-RAPID model using a multi-source precipitation merging method

摘要

Flash floods-caused losses are rapidly increasing due to climate change induced extreme weather events and economic development in the world. The WRF-Hydro-RAPID model coupled with land surface model and a vector-based flow routing module is able to simulate discharge at any reach of a watershed, making it a good tool for flood simulation and forecasting. We investigated the flood simulation capability of the WRF-Hydro-RAPID model and evaluated the utility of a multi-source precipitation merging method based on the mixed geographically weighted regression model and Bi-square function (MGWR-BI algorithm), which produces precipitation as forcing with improved quality and resolution, to enhance the simulation accuracy of the WRF-Hydro-RAPID model for the Daheba Watershed, a first-order sub-basin of the Yangtze River Basin. The merged precipitation data have substantial higher quality than the downscaled original CPC MORPHing technique satellite precipitation data (CMORPHd) (r = 0.64-0.74 and RMSE = 1.59-6.64 mm/h for the merged data vs. r = 0.11-0.06 and RMSE = 3.31-8.25 mm/h for the CMORPHd data) by comparing to the ground observations. Floods are better forecasted and simulated by the WRF-Hydro-RAPID model driven by the merged precipitation data than the CMORPHd precipitation data for the four nested medium and small watersheds. Performance of the WRF-Hydro-RAPID model at the watershed outlet station does not differ those at the three inner stations, proving that the WRF-Hydro-RAPID model has a consistent performance in space. The combination of the WRF-Hydro-RAPID with the precipitation merging method makes it a valuable tool for flood simulation of medium and small watersheds.