State Key Laboratory of Water Environment Simulation, School of Environment, Beijing Normal University, Beijing 100875, PR China.
State Key Laboratory of Water Environment Simulation, School of Environment, Beijing Normal University, Beijing 100875, PR China.
Sci Total Environ. 2022 Mar 20;813:151901. doi: 10.1016/j.scitotenv.2021.151901. Epub 2021 Nov 24.
Global climate change has necessitated the update of urban stormwater management measures (SMMs), but this task is extremely difficult due to the deficiency of evaluation caused by discreteness and the limitation of selected storm events, the ignorance of antecedent dry day (ADD) and lack of suitable stochastic storm generation method. In this study, a new framework that considers both stochastic precipitation and ADD is introduced to evaluate urban SMMs more adequately. Gamma distribution fitting, the space discarding method, the production of probability density distribution maps and multiple nonlinear regression were combined with a physical-based model to assess the effectiveness of SMMs under changing climates. Taking low impact development practices (LIDs) as an example of SSMs, the case study showed that the proposed framework provided effectiveness probability density distribution map and regression equations with more evaluation details by increasing the number and type of storm events compared with current monitoring. Moreover, it is demonstrated that ADD should be considered as one important factor in the design of LIDs, especially for controlling urban non-point source pollution. The value of ADD will significantly affect the control effect of LIDs on pollutant loads and event mean concentration in runoff, which varied for different pollutants. Through case study, it shows there is a risk that LIDs would be less effective at controlling runoff and non-point source pollution in future climate scenarios, especially for RCP 8.5 which is more extreme. Therefore, adaptation capacity of climate change should be considered in the design of SMMs. The proposed framework will be a useful tool in the assessment, design and planning of urban SMMs considering climate change.
全球气候变化要求更新城市雨水管理措施（SMMs），但由于离散性导致评估不足，以及所选暴雨事件的局限性、忽视前期干燥天数（ADD）和缺乏合适的随机暴雨生成方法，这项任务极其困难。在本研究中，引入了一种同时考虑随机降水和 ADD 的新框架，以更充分地评估城市 SMMs。伽马分布拟合、空间丢弃方法、概率密度分布图的生成和多元非线性回归与基于物理的模型相结合，用于评估气候变化下 SMMs 的有效性。以低影响开发实践（LIDs）为例，案例研究表明，与当前监测相比，通过增加暴雨事件的数量和类型，所提出的框架提供了更详细的有效性概率密度分布图和回归方程，从而提供了更多的评估细节。此外，研究表明，ADD 应被视为 LIDs 设计中的一个重要因素，特别是在控制城市非点源污染方面。ADD 的值将显著影响 LIDs 对径流中污染物负荷和事件平均浓度的控制效果，不同污染物的控制效果不同。通过案例研究表明，在未来气候情景下，LIDs 控制径流和非点源污染的效果可能会降低，特别是在更为极端的 RCP8.5 情景下。因此，在 SMMs 的设计中应考虑气候变化的适应能力。所提出的框架将成为评估、设计和规划考虑气候变化的城市 SMMs 的有用工具。
