New framework for assessing urban stormwater management measures in the context of climate change

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.