Improving streamflow simulation in Dongting Lake Basin by coupling hydrological and hydrodynamic models and considering water yields in data-scarce areas

Abstract

Study region: The Dongting Lake Basin is a typical regional study in humid southern China with data-scarce areas. Study focus: This study improved the streamflow simulation by coupling hydrological and hydrodynamic models and considering water yields in data-scarce areas. We constructed a soil and water assessment tool (SWAT) hydrological model of the Dongting Lake Basin to simulate the streamflow in the data-scarce areas, which was further coupled into the MIKE21 hydrodynamic model as additional boundary conditions. New hydrological insights: The results showed that the relative error of streamflow simulation was reduced from 24.64 % to 10.50 % in the coupled hydrological-hydraulic model over the singular hydrodynamic model, which also indirectly verified the results of streamflow simulation in the data-scarce area. Based on the coupled model, the annual water yields in the data-scarce areas were estimated to be 38.95 × 109 m3, representing 15.13 % of the yearly water yields in the basin. The water yields in the data-scarce areas showed a seasonal variation, which was concentrated from April to July. The monthly water balance error of the Dongting Lake Basin was significantly reduced (57.42 %) when considering the water yields in data-scarce areas. The model-coupling approach in this study can be applied to other data-scarce areas to improve streamflow simulation.