Chinese Research Academy of Environmental Sciences, Beijing 100012, China.
School of Water Resources and Environment, China University of Geosciences, Beijing 100083, China.
Int J Environ Res Public Health. 2021 Jul 16;18(14):7586. doi: 10.3390/ijerph18147586.
Non-Point Source Pollution (NPS) caused by polluted and untreated stormwater runoff discharging into water bodies has become a serious threat to the ecological environment. Green infrastructure and gray infrastructure are considered to be the main stormwater management measures, and the issue of their cost-effectiveness is a widespread concern for decision makers. Multi-objective optimization is one of the most reliable and commonly used approaches in solving cost-effectiveness issues. However, many studies optimized green and gray infrastructure under an invariant condition, and the additional benefits of green infrastructure were neglected. In this study, a simulation-optimization framework was developed by integrated Stormwater Management Model (SWMM) and Non-dominated Sorting Genetic Algorithm (NSGA-II) to optimize green and gray infrastructure for NPS control under future scenarios, and a realistic area of Sponge City in Nanchang, China, was used as a typical case. Different levels of additional benefits of green infrastructure were estimated in the optimizing process. The results demonstrated that green-gray infrastructure can produce a co-benefit if the green infrastructure have appropriate Value of Additional Benefits (VAB), otherwise, gray infrastructure will be a more cost-effectiveness measure. Moreover, gray infrastructure is more sensitive than green infrastructure and green-gray infrastructure under future scenarios. The findings of the study could help decision makers to develop suitable planning for NPS control based on investment cost and water quality objectives.
非点源污染（NPS）是指受污染和未经处理的雨水径流排入水体对生态环境造成的严重威胁。绿色基础设施和灰色基础设施被认为是主要的雨水管理措施，其成本效益问题是决策者普遍关注的问题。多目标优化是解决成本效益问题的最可靠和常用方法之一。然而，许多研究在不变条件下优化绿色和灰色基础设施，忽略了绿色基础设施的附加效益。本研究通过集成雨水管理模型（SWMM）和非支配排序遗传算法（NSGA-II），开发了一个模拟-优化框架，用于优化未来情景下的 NPS 控制的绿色和灰色基础设施，并以中国南昌的一个真实海绵城市区域为典型案例。在优化过程中估计了绿色基础设施的不同附加效益水平。结果表明，如果绿色基础设施具有适当的附加效益价值（VAB），则绿色-灰色基础设施可以产生共同效益，否则，灰色基础设施将是更具成本效益的措施。此外，灰色基础设施对未来情景的敏感性高于绿色基础设施和绿色-灰色基础设施。本研究的结果可以帮助决策者根据投资成本和水质目标制定适合的 NPS 控制规划。
