Across the world, cities are spending billions of dollars to manage urban runoff through decentralized green infrastructure (GI). This research uses an agent‐based model to explore some of the physical, social, and economic consequences of one such urban GI programs. Using the Bronx, NY, as a case study, two alternative approaches to GI application are compared. The first (Model 1) mimics NYC's current GI program by opportunistically selecting sites for GI within the city's priority combined sewer watersheds; the second (Model 2) features a more spatially flexible approach to GI siting, in which the city attempts to maximize opportunities for co‐benefits within the geographic areas considered in Model 1. The effects of both approaches, measured in terms of stormwater captured and co‐benefits (e.g., carbon sequestered) provided, are tracked over 20‐year simulations. While both models suggest it will be difficult to meet the citywide stormwater capture goals (managing the first 2.5 cm of rainfall from 10% of impervious surfaces) in the Bronx solely through public investment in GI, Model 2 shows that by integrating GI with other city initiatives (e.g., sustainability goals and resilience planning), synergistic outcomes are possible. Specifically, Model 2 produces stormwater capture rates comparable to those obtained under Model 1, but these rates are accompanied by elevated co‐benefits for Bronx communities. The results are discussed in the context of future GI policy development in NYC.
Green infrastructure (GI) practices improve stormwater quality and reduce urban flooding, but as urban hydrology is highly controlled by its associated gray infrastructure (e.g., stormwater pipe network), GI's watershed‐scale performance depends on its siting within its associated watershed. Although many stormwater practitioners have begun considering GI's spatial configuration within a larger watershed, few approaches allow for flexible scenario exploration, which can untangle GI's interaction with gray infrastructure network and assess its effects on watershed hydrology. To address the gap in integrated gray‐green infrastructure planning, we used an exploratory model to examine gray‐green infrastructure performance using synthetic stormwater networks with varying degrees of flow path meandering, informed by analysis on stormwater networks from the Minneapolis‐St. Paul Metropolitan Area, MN, USA. Superimposed with different coverage and placements of GI (e.g., bioretention cells), these gray‐green stormwater networks are then subjected to different rainfall intensities within Environmental Protection Agency's Storm Water Management Model to simulate their hydrological benefits (e.g., peak flow reduction, flood reduction). Although only limited choices of green and gray infrastructure were explored, the results show that the gray infrastructure's spatial configuration can introduce tradeoffs between increased peak flow and increased flooding, and further interacts with GI coverage and placement to reduce peak flow and flooding at low rainfall intensity. However, as rainfall intensifies, GI ceases to reduce peak flow. For integrated gray‐green infrastructure planning, our results suggest that physical constraints of the stormwater networks and the range of rainfall intensities must be considered when implementing GI.
more » « less- Award ID(s):
- 2045382
- NSF-PAR ID:
- 10479366
- Publisher / Repository:
- DOI PREFIX: 10.1029
- Date Published:
- Journal Name:
- Water Resources Research
- Volume:
- 59
- Issue:
- 12
- ISSN:
- 0043-1397
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
More Like this
-
more » « less
Abstract -
more » « less
Abstract The urban environment modifies the hydrologic cycle resulting in increased runoff rates, volumes, and peak flows. Green infrastructure, which uses best management practices (BMPs), is a natural system approach used to mitigate the impacts of urbanization onto stormwater runoff. Patterns of stormwater runoff from urban environments are complex, and it is unclear how efficiently green infrastructure will improve the urban water cycle. These challenges arise from issues of scale, the merits of BMPs depend on changes to small‐scale hydrologic processes aggregated up from the neighborhood to the urban watershed. Here, we use a hyper‐resolution (1 m), physically based hydrologic model of the urban hydrologic cycle with explicit inclusion of the built environment. This model represents the changes to hydrology at the BMP scale (~1 m) and represents each individual BMP explicitly to represent response over the urban watershed. Our study varies both the percentage of BMP emplacement and their spatial location for storm events of increasing intensity in an urban watershed. We develop a metric of effectiveness that indicates a nonlinear relationship that is seen between percent BMP emplacement and storm intensity. Results indicate that BMP effectiveness varies with spatial location and that type and emplacement within the urban watershed may be more important than overall percent.
-
null (Ed.)Green infrastructure (GI) has become a panacea for cities working to enhance sustainability and resilience. While the rationale for GI primarily focuses on its multifunctionality (e.g. delivering multiple ecosystem services to local communities), uncertainties remain around how, for whom, and to what extent GI delivers these services. Additionally, many scholars increasingly recognize potential disservices of GI, including gentrification associated with new GI developments. Building on a novel dataset of 119 planning documents from 19 U.S. cities, we utilize insights from literature on justice in urban planning to examine the justice implications of criteria used in the siting of GI projects. We analyze the GI siting criteria described in city plans and how they explicitly or implicitly engage environmental justice. We find that justice is rarely explicitly discussed, yet the dominant technical siting criteria that focus on stormwater and economic considerations have justice implications. We conclude with recommendations for centering justice in GI spatial planning.more » « less
-
null (Ed.)Green stormwater infrastructure (GSI) is increasingly used to reduce stormwater input to the subsurface stormwater network. This work investigated how GSI interacts with surface runoff and stormwater structures to affect the spatial extent and distribution of roadway flooding and subsequent effects on the performance of the traffic system using a dual-drainage model. The model simulated roadway flooding using PCSWMM (Personal Computer Stormwater Management Model) in Harvard Gulch, Denver, Colorado, and was then used in a microscopic traffic simulation using the Simulation of Urban Mobility Model (SUMO). We examined the effect of converting between 1% and 5% of directly connected impervious area (DCIA) to bioretention GSI on roadway flooding. The results showed that even for 1% of DCIA converted to GSI, the extent and mean depth of roadway flooding was reduced. Increasing GSI conversion further reduced roadway flooding depth and extent, although with diminishing returns per additional percentage of DCIA converted to GSI. Reduced roadway flooding led to increased average vehicle speeds and decreased percentage of roads impacted by flooding and total travel time. We found diminishing returns in the roadway flooding reduction per additional percentage of DCIA converted to GSI. Future work will be conducted to reduce the main limitations of insufficient data for model validation. Detailed dual-drainage modeling has the potential to better predict what GSI strategies will mitigate roadway flooding.more » « less
-
more » « less
Abstract As stormwater control measures (SCMs) capture surface runoff from impervious areas, a shift in the water balance and flow regime components may emerge in urban watersheds, but the amount of SCM treatment needed to detectably shift these components may vary. We used the Soil and Water Assessment Tool (SWAT) hydrologic model to assess the sensitivity of 16 hydrologic metrics as an increasingly dense rain garden SCM network was applied across the West Creek watershed, near Cleveland, Ohio (USA). As the area treated by SCMs increased, annual baseflow increases matched decreases in surface runoff, while water yield and evapotranspiration changes remained small. The stream's peak response to rainfall decreased with SCM implementation across storm sizes, ranging from the threshold rainfall depth (4.8 mm) to values higher than the design storm of a single rain garden (19 mm). SCM networks draining >20% of directly connected impervious area (DCIA) significantly decreased the magnitude of discharges with a return period of less than 1 year, the percentage of time above mean flow, and flashiness. Recession slopes and annual 1‐ and 7‐day low flows exhibited a slight response that fell within uncertainty limits of the model. Water balance and rainfall response metrics exhibited the greatest sensitivity to different intensities of stormwater management, while infrequent high and low flows were resistant to detectable change even at high levels of SCM treatment when model uncertainty was included.
