Ke Entong, Zhao Juchao, Zhao Yaolong, Wu Jiazhe, Xu Tao
Beidou Research Institute, South China Normal University, Foshan 528225, China; Guangdong Research Center of Smart Land Engineering, Foshan 528225, China; Key Laboratory of Natural Resources Monitoring in Tropical and Subtropical Area of South China, Ministry of natural resources, Guangzhou 510663, China.
Guangdong Research Center of Smart Land Engineering, Foshan 528225, China; Key Laboratory of Natural Resources Monitoring in Tropical and Subtropical Area of South China, Ministry of natural resources, Guangzhou 510663, China; School of Geography, South China Normal University, Guangzhou 510631, China.
Sci Total Environ. 2024 Mar 20;917:170202. doi: 10.1016/j.scitotenv.2024.170202. Epub 2024 Jan 26.
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.
城市雨洪内涝治理是城市发展中的一项重大挑战。人们已经采用了许多成熟的方法来降低洪水风险。从城市更新规划的角度来看，不透水表面的优化设计（ODIS）是应对城市内涝的一种适应性解决方案。然而，现有的ODIS模型存在局限性，因为它们没有考虑排水系统。为了解决这个问题，本研究基于对暴雨和排水能力的假设，在中国广州市老城区的案例研究中，提出了一种基于非支配排序遗传算法-II（NSGA-II）、多元线性规划（MLP）和土壤保持服务曲线数模型（SCS-CN）的弹性可控优化模型。该模型不仅耦合了排水系统，还对不透水表面和排水系统进行了协同优化。结果表明，所提出的模型实现了5.70%的优化效率，与现有的ODIS模型相比提高了十倍以上。该研究强调，排水系统的优化应作为重点，不透水表面的优化应作为补充，不同的洪水风险区域需要不同的优化策略。此外，将不透水表面转变为不透水表面密度的“高-低-高”空间分布是不透水表面的最优设计方案。总体而言，本研究为城市内涝治理提供了一种新颖的视角和方法，能够从全局角度对洪水进行综合控制。
