A distributed karst hydrological model incorporating flooding detention in peak-cluster depressions

Flooding detention in peak-cluster depressions is a key component of the hydrological cycle in karst basins. To address the limitations of existing hydrological models in accurately representing this process, this study proposes a simulation method based on the water balance principle. A distributed karst Xin'anjiang hydrological model incorporating flooding detention in peak-cluster depressions (DK-XAJ-DF) is developed. Using the Diaojiang River basin as a representative study area, the model simulates the flooding detention volume in the Longtou peak-cluster depression and the streamflow processes at the Hekou and Malong hydrological stations. Results indicate that the hourly simulation of flooding detention volume in the Longtou depression achieves a determination coefficient and relative total error of 0.90 and 0.77%, respectively. During the validation period, the hourly simulation of streamflow yields determination coefficients of 0.85 and 0.89 for the Hekou and Malong stations, respectively, with corresponding total errors of 3.0% and −4.4%. Compared with the original model, the modified DK-XAJ-DF model improves the qualification rates of flood peak discharge and peak timing at the Malong station from 65% to 70% and from 70% to 80%, respectively. By explicitly quantifying the flooding detention effect, the DK-XAJ-DF model enhances simulation accuracy of flood simulation in karst areas.