A coupled atmospheric–hydrologic modeling system with variable grid sizes for rainfall–runoff simulation in semi-humid and semi-arid watersheds: how does the coupling scale affects the results?

Abstract

Abstract. The coupled atmospheric–hydrologic modeling system is an effective way to improve the accuracy of rainfall–runoff modeling and extend the lead time in real-time flood forecasting. The aim of this study is to explore the appropriate coupling scale of the coupled atmospheric–hydrologic modeling system, which is established by the Weather Research and Forecasting (WRF) model and the gridded Hebei model with three different sizes (1 km×1 km, 3 km×3 km and 9 km×9 km). The Hebei model is a conceptual rainfall–runoff model designed to describe a mixed runoff generation mechanism, including both storage excess and infiltration excess, in the semi-humid and semi-dry area of northern China. The soil moisture storage capacity and infiltration capacity of different grids in the gridded Hebei model are obtained and dispersed using the topographic index. The lumped Hebei model is also used to establish the lumped atmospheric–hydrologic coupled system as a reference system. Four 24 h storm events occurring at two small- and medium-scale sub-watersheds in northern China are selected as case studies. Contrastive analyses of the flood process simulations from the gridded and lumped systems are carried out. The results show that the flood simulation results may not always be improved with higher-dimension precision and more complicated system, and the grid size selection has a strong relationship with the rainfall evenness. For the storm events with uniform spatial distribution, the coupling scale has less impact on flood simulation results, and the lumped system also performs well. For the storm events with uneven spatiotemporal distribution, the corrected rainfall can improve the simulation results significantly, and higher resolution leads to better flood process simulation. The results can help to establish the appropriate coupled atmospheric–hydrologic modeling system to improve the flood forecasting accuracy.