Multi-stakeholder stochastic optimization of urban low impact developments for climate consistency under uncertainty

Sustainable management of urban floods can prevent damage to the city's infrastructure. In particular, low-impact developments (LIDs) collect and reuse urban stormwaters and mitigate their destructive effects. This study aims to optimize the design of urban LIDs in terms of location and surface area, considering the climatic parameters and model uncertainties. Accordingly, the urban runoff quality and quantity, in addition to the climatic parameters and their uncertainties were analyzed in the modeling by repeated execution of a rainfall-runoff model in MATLAB. Then, using the concept of conditional value at risk, the uncertainty risk consideration was incorporated in the optimal design of the LIDs. Using a non-cooperative game model, stakeholders' priorities were also considered in selecting the best design scenario. In comparison with the baseline scenario (no LID, maximum runoff quantity, and worst runoff quality), the selected scenario decreased runoff volume, and two quality indicators (i.e., total suspended solids (TSS) and biochemical oxygen demand (BOD)) by (56.1–64.6%), (22.1–27.1%), and (13.7–19.2%), respectively. This scenario is the best arrangement of LIDs (location and surface area) in different sub-basins that satisfies stakeholders' priorities. The novelty of this study lies in integrating uncertainty with social complexities in a sustainable quantitative and qualitative urban runoff management using a risk-based stochastic optimization and a flexible conflict resolution model. Incorporating conflict resolution concepts in LIDs design prevents wastage of time and money and facilitates achieving socioecological implications such as ecosystem services, neighborhood aesthetics, recreational spaces, and enhancing land values. The suggested methodology was tested in the Velenjak region, northern Tehran.