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’s 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.
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Data Availability Statement
All the data except stormwater infrastructure data and all the codes that support the findings of this study are available from the corresponding author upon reasonable request. Some data used to build the model is available as indicated in the text. Direct requests for other data may be made to the provider as indicated in the Acknowledgements.
Acknowledgments
This work is supported by National Science Foundation (NSF) Smart and Connected Communities Program (1831475). The data for analysis and model building had been provided by Phoenix Public Works and Flood Control District of Maricopa County.
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Journal of Sustainable Water in the Built Environment
Volume 9 • Issue 2 • May 2023
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© 2023 American Society of Civil Engineers.
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Received: Apr 29, 2022
Accepted: Oct 12, 2022
Published online: Jan 11, 2023
Published in print: May 1, 2023
Discussion open until: Jun 11, 2023
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