A Coupled Simulation and Flood Mitigation Design Framework for Urban Waterlogging Based on LID Spatial Layout Optimization

Abstract

Urban stormwater poses a threat to urban safety and development. The systematic spatial planning of low-impact development (LID) facilities is increasingly recognized as a sustainable approach to enhancing urban flood resilience. Previous studies have largely focused on empirically-based design approaches or have employed uncoupled computational methods, resulting in a lack of accuracy in flood simulation results. In this study, a novel framework was proposed. The Non-dominated Sorting Genetic Algorithm II was employed to perform multi-objective optimization of the spatial layout of LID facilities, and a coupled model of SWMM and TELEMAC was developed to simulate surface flooding based on the optimized schemes. Under three rainfall scenarios, three schemes on the Pareto Front—representing the lowest cost, the optimal compromise and the least overflow—were selected to investigate how scheme parameters and overflow are influenced by rainfall intensity and design preferences. The results indicate that scheme parameters and node overflow show greater variation under the influence of different design preferences than under different rainfall conditions. Taking the schemes selected in this study as examples, under the lowest-cost scheme, LID coverage was less than 10%, resulting in a limited reduction in node overflow; but when ‘minimum overflow’ was set as the design preference, node overflow was virtually eliminated, with peak water levels at flood-prone locations reduced to 0.05 m, 0.08 m and 0.10 m under 50-year, 100-year and 200-year storm conditions, respectively. The framework for urban flooding simulation and flood control scheme design proposed in this study is potentially applicable to comparable settings, subject to similar data availability and physical conditions, serving as a reference for enhancing urban resilience to flooding.