A distributed hydrological model for semi-humid watersheds with a thick unsaturated zone under strong anthropogenic impacts: A case study in Haihe River Basin

In the past decades, human activities, including hydraulic structure construction and operation, and groundwater overexploitation have largely changed the land surface conditions and correspondingly altered the natural rainfall-runoff processes. These changes make the traditional operational flood forecasting models without considering these anthropogenic impacts fail to capture these changes, leading to a downgraded forecasting capability. To improve the accuracy of flood forecasting in semi-humid watersheds under strong aboveground and underground anthropogenic impacts, the widely used operational flood forecasting model, the Xin'anjiang model, was chosen as a basis to build a new distributed hydrological model accounting for these anthropogenic impacts. To characterize the runoff generation process under the condition of a thick unsaturated zone caused by groundwater overexploitation, this study developed a runoff generation algorithm based on an idea that conceptualizes the soil free-water storage into two virtual reservoirs. To characterize the impacts of manmade reservoirs on the runoff concentration process, we modified the Muskingum method. In addition, we further developed a priori estimation method for deriving the spatial distribution of the tension water storage capacity by considering the anthropogenic impacts and geographical conditions. Based on the above work, a Grid Xin'anjiang-Haihe model (GXH) was developed. In this study, the Qingshui River, which is a tributary of the Haihe River Basin and a typical semi-humid medium-sized watershed in China with poor flood forecasting accuracy, was selected as the study area to test the effectiveness of the model. The results show that the GXH model can simulate the flood peak flow and peak time with higher accuracy than the current operational flood forecasting models and several other models. In addition, the parameter estimation method developed in this study has also proven to be superior in theory and practice.