The complex subsurface conditions and spatial anisotropy of water-bearing media in karst basins result in much more variable runoff generation and confluence processes and water circulation than those in nonkarst basins. Therefore, accurate flood forecasting is more difficult in karst areas, and it is challenging to accurately quantify the water exchange relationship between surface rivers and karst aquifers. To provide key technical support for accurate flood forecasts in karst basins, this study improved a distributed physical hydrologic model, the Karst-Liuxihe model, by improving the runoff generation and confluence algorithms and the parameter optimization algorithm to simulate surface floods in three different karst watersheds in southern China. Additionally, in the model calculations, this study focused on the influence of water exchange on surface flood simulations in changing watersheds. The results showed that for the largest basin, Xijiang Basin (353,100 km2), considering or not considering the water exchange between the surface river and karst aquifer had little effect on the surface flood simulation results. However, this water exchange had a great effect on the surface simulations for the smallest basin, the Beijiang Basin (1,700 km2). For instance, the simulated average peak flow showed a 29 % difference, and the total amount of flooding showed a 25 % difference between dry years and normal years. Therefore, when forecasting surface floods in small karst areas, the water exchange relationship between surface rivers and karst aquifers must be considered. The results showed that the impact of groundwater on surface rivers can be disregarded when forecasting surface floods in the large Xijiang karst basin and can be treated directly as surface flood forecasting in nonkarst areas. The application of this strategy will greatly simplify the cost of hydrologic modelling in the Xijiang basin. By improving the Karst-Liuxihe model, the accuracy of its flood simulation and general applicability in karst basins were greatly enhanced. The improvement in the karst hydrological model in this study provides a good tool for flood simulation and forecasting in the karst regions of Southwest China.
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