A Quantitative Comparison of the Distributed Liuxihe Model’s Performance in Simulating Different Flood Types

To address the challenges in small- and medium-sized basins in China, including the strong suddenness of flood processes, limited hydrological data, and the inadequate accuracy of conventional forecasting approaches, this study used the Chixi Basin in Guangdong Province as a case study to develop the Liuxihe model and calibrate its parameters using particle swarm optimization (PSO). Based on the optimized parameter set, multiple historical floods were systematically simulated, and the model applicability was comparatively evaluated by flood type. The results show that the Liuxihe model performs well overall in the Chixi Basin: the best comprehensive performance was obtained for the medium flood (Nash–Sutcliffe efficiency (NSE) = 0.882; correlation coefficient (R) = 0.962), the optimal hydrograph-shape fitting was achieved for the concentrated flood (NSE = 0.956; R = 0.983), and the simulation accuracy for the single-peak flood was markedly higher than that for the double-peak flood (NSE = 0.905; peak error (PE) = 0.11%). Overall, the model demonstrates strong applicability in the Chixi Basin; however, further optimization is required for complex flood processes, such as the double-peak flood and the flat-peak flood.