With global climate change intensifying extreme rainfall and revealing the limited coordination of flood drainage systems in plain river network regions, this study aims to enhance flood control and drainage efficiency in complex networks. A typical plain river network city in eastern China was selected as a case study, and a high-resolution hydrologic–hydrodynamic model was developed to simulate the coupled rainfall–drainage–river process. Based on this model, a zonal progressive scheduling strategy for sluice–dam systems was proposed by integrating physical hydrodynamic mechanisms with a particle swarm optimization algorithm. River storage experiments and storm event simulations demonstrated satisfactory model performance, with Nash–Sutcliffe efficiency values generally exceeding 0.75 and water balance errors in all subregions remaining within acceptable limits, confirming the reliability for evaluating flood drainage scheduling. Comparative simulations under multiple rainfall return periods were conducted for three scenarios: free drainage (Scenario 1), global optimal scheduling (Scenario 2), and zonal progressive optimization (Scenario 3). Results indicate that the proposed strategy significantly outperformed conventional approaches. Results indicate that the zonal progressive strategy significantly outperformed the baseline and global optimization schemes by reducing river overflow and effectively mitigating flood peaks at key control structures, particularly under the 20-year rainfall scenario. Additionally, the strategy achieved coordinated drainage between high- and low-lying zones: compared with the global optimization scenario, the zonal progressive strategy enhanced interzonal flood redistribution by diverting excess floodwater from overloaded river reaches to subsystems with remaining conveyance capacity, effectively alleviating local drainage bottlenecks and enhancing overall system resilience. By integrating intelligent optimization with the physical mechanisms of hydrologic–hydrodynamic processes and spatial heterogeneity constraints, this study enhances both practicality and interpretability, offering a theoretical and technical basis for precise and efficient flood regulation in river network cities.
Liang et al. (Fri,) studied this question.