Assessment of Climate, Sizing, and Location Controls on Green Infrastructure Efficacy: A Timescale Framework

Abstract

We investigate how the effectiveness of green infrastructure (GI) to mitigate the frequency and magnitude of significant discharge events and combined sewer overflows (CSOs) depend on both climate and sewershed characteristics and propose a theoretical framework for a holistic assessment of GI's efficacy. The framework is based on the comparison of three characteristic timescales that control the production of peak discharge: rainfall duration (t r ), travel time in the sewer network (t n ), and the duration of rain that would be required to fill the GI's storage (t GI ). Storm events can then be characterized by two ratios of these timescales: T n = t n /t GI and T r = t r /t GI . A third dimensionless number characterizes critical storms during which adverse events (such as CSOs) occur and allows us to identify the combinations of T n and T r for which GI may substantially mitigate those events. The results of numerical experiments with the model demonstrate that the storms for which GI can substantially reduce peak discharge and CSO volume typically occur in a narrow band of T n and T r . Within that band, the efficacy of GI may depend on the location of GI within the sewershed if network routing substantially affects the timing and magnitude of flood peaks. The proposed framework is applied to examine the efficacy of GI using historical precipitation data from two major U.S. cities: Philadelphia, PA, and Seattle, WA, and the results of this comparative analysis suggest that GI location is an important control on catchment-scale GI efficacy in Philadelphia, but less so in Seattle.Plain Language Summary Combined sewer overflows (CSO) occur when storm rainfall exceeds the capacity of the sewer system to drain it. Green infrastructure (GI) is intended to mitigate the occurrence and severity of CSOs. But how effective will it be in helping to manage CSOs? Here we present a theoretical framework to address this question, by focusing on the major physical controls on the efficacy of GI for managing CSOs, including the relative roles of climate, the size of the sewershed, and the location of the GI within it. The framework is based on three characteristic timescales: storm duration, travel time to the overflow location, and time required to fill GI storage. We use the framework to explore how GI might work differently in different places. The results show that GI is most effective under certain combinations of climate and sewershed conditions, and that the location of GI within the sewershed can be very critical. The latter effect was found to be more evident, for example, in Philadelphia, PA, than in Seattle, WA, due to differences in storm duration and intensity between these two places. In these ways, the proposed framework can support green infrastructure planning by providing insights on location-effectiveness tradeoffs.

Effects of Design and Climate on Bioretention Effectiveness for Watershed-Scale Hydrologic Benefits

“…We did not consider how benefits vary by location. Many studies have shown that GSI location can significantly influence performance (Epps and Hathaway 2019;Fry and Maxwell 2017;Hung et al 2020), and many optimization techniques are being developed to find the best locations for GSI installation (Giacomoni and Joseph 2017).…”

“…Research using either field monitoring (Li et al 2009;Stander et al 2010;Winston et al 2016) or numerical modeling (Jennings 2016;Olszewski and Davis 2013;Sun et al 2019;Wadzuk et al 2017) has shown that, when properly designed and maintained, bioretention areas can reduce runoff volumes and peak flow rates, potentially improving stream integrity (Wright et al 2018). A number of factors affect bioretention performance, including design choices (e.g., surface area, soil depth, infiltration capacity) (Jennings 2016;Lewellyn and Wadzuk 2019) and climate (Cook et al 2019;Hung et al 2020;Jennings 2016). Design standards for bioretention areas vary by state and city (McPhillips et al 2020), with some focusing on capturing a certain runoff volume and others incorporating more sophisticated methods to achieve some peak flow reduction.…”

Impacts of Rainstorm Characteristics on Runoff Quantity and Quality Control Performance Considering Integrated Green Infrastructures

“…The hydrological and environmental benefits of GI are usually achieved through green roofs (GR), vegetative swale (VS), bio-retention units (BR), permeable pavement (PP), and other green measures [15]. These GIs' benefits have been confirmed by field studies [16][17][18], laboratory experiments [19], and modeling simulations [10,[20][21][22][23]. The effectiveness of GI practices can be measured by several indexes, such as flood control and pollution reduction, by comparing a base case with various scenarios [9].…”

“…To manage the urban water problems, many countries have proposed solutions, such as Best Management Practices in the United States, Water Sensitive Urban Design in Australia, and Sponge City (SPC) in China [6][7][8]. Although these solutions are distinctive, they all regard green infrastructure (GI) as essential [9][10][11][12]. Compared with the traditional drainage system, which removes water quickly, GI can collect rainwater from the source, reduce runoff, and improve water quality [13,14].…”

Green stormwater infrastructure: A critical review of the barriers and solutions to widespread implementation

“…From the mid‐2000s, scientific field studies reported on the success of GSI practices in reducing stormwater volume and pollutant loads (Davis, 2007; Dietz, 2007), culminating in an increasingly rich body of literature (Eckart et al, 2017; C. Li et al, 2019; T. Liu et al, 2021) and databases, for example, International Best Management Practices (BMP) Database (Water Research Foundation, 2020), centered around their hydrologic and water quality treatment performance at the site scale. Since then, the impacts of networks of GSI practices at larger spatial scales have gained academic and practical interest (Golden & Hoghooghi, 2018; Hung et al, 2020; Jefferson et al, 2017; Pennino et al, 2016; Woznicki et al, 2018). Along these lines, many modeling studies have reported on the potential of GSI to reduce stream pollution at the neighborhood scale (Heidari et al, 2022; Leonard et al, 2019; Seo et al, 2017) and flooding impact at the city scale (Green et al, 2021; Jack et al, 2021).…”