Center article selected as Editor’s Choice

A new publication in the Journal of Sustainable Engineering in the Built Environment (Shrestha and Garcia, 2023) entitled Influence of Precipitation Uncertainty and Land Use Change on the Optimal Catchment Scale Configuration of Green Stormwater Infrastructure was selected as an Editor’s Choice. Congratulations to the authors associated with the Center for Hydrologic Innovations!

  • Abstract: Adoption of green stormwater infrastructure (GSI) as a sustainable stormwater measure to manage urban flooding has gained momentum globally. Modeling and analysis tools are available to guide its design and planning. However, the impact of uncertainty in design precipitation estimates, and change in land use on the optimal configuration of GSI has not yet been assessed. The uncertainty in design precipitation estimates influences the amount and cost of GSI; and urban forms, space availability and existing drainage infrastructure influence the placement and ideal types of GSI. Further, climate change and conversion of pervious to impervious surfaces create varied impacts across cities. In this paper we investigate how such catchment scale optimal configurations of GSI, defined as ideal selection of type, amount and spatial distribution of GSI, vary (1) across uncertainty within design precipitation estimates from NOAA Atlas 14; and (2) with increasing urban imperviousness. We analyze this across two different cases of urban forms: (1) a catchment with mixed use buildings where bioretention (i.e., ground based) and green roofs (i.e., over ground based) are feasible, and (2) a catchment with only residential buildings where only bioretention is feasible. For this aim we utilize the USEPA‚Äôs stormwater management model (SWMM) to construct one-dimensional hydrologic-hydraulic models using stormwater networks of two separate locations in Phoenix, Arizona. We couple the SWMM model with nondominated sorting genetic algorithm (NSGA-II) to develop a multiobjective optimal GSI planning framework to determine amount, type and location for GSI implementation. We found that varying the design precipitation from the lower to upper bound of the confidence interval for NOAA Atlas 14, resulted in a larger difference in the amount of GSI required than the effect of land use change from 2001 to 2019. This highlights the important of accurate design storm estimates and the value of modular GSI in adapting stormwater systems under uncertainty.