Coupled and collaborative optimization model of impervious surfaces and drainage systems from the flooding mitigation...

Urban pluvial flooding mitigation is a significant challenge in city development. Many mature methods have been used to reduce the risk of flood. The optimal design of impervious surfaces (ODIS) is an adaptive solution to urban flooding from the perspective of urban renewal planning. However, existing ODIS models are limited because they do not consider the drainage systems. To address this issue, this study proposes an elastic and controllable optimization model based on assumptions about rainstorm and drainage capacity, nondominated sorting genetic algorithm-II (NSGA-II), multivariate linear programming (MLP) and soil conservation service curve number model (SCS-CN) in a case study of the old town of Guangzhou city, China. The model not only coupled the drainage systems, but also collaboratively optimized the impervious surfaces and the drainage systems. The results show that the proposed model achieved an optimized efficiency of 5.70 %, which is more than a tenfold improvement compared to existing ODIS models. The study emphasizes that the optimization of the drainage system should be the focus and the optimization of impervious surfaces should be supplementary, and different flood risk areas require different optimization strategies. Furthermore, transforming impervious surfaces into a "high-low-high" spatial distribution of impervious surface densities is the optimal design solution for impervious surfaces. In general, this study offers a novel perspective and approach to urban flooding mitigation, enabling comprehensive control of flooding from a global perspective.