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Abstract The paper examines relationships between stormwater control measure (SCM) priorities and environmental value orientations among stormwater managers in Cleveland, Ohio and Denver, Colorado, metro regions with contrasting environmental conditions and policy contexts. While studies show that governance explains differences in broad SCM priorities, less is known about what motivates individual “street level bureaucrats” who influence decisions at the project level. Drawing from cognitive social science perspectives, this study surveyed stormwater professionals (n = 185) about primary and co‐benefit SCM priorities and environmental value orientation. Results revealed different primary SCM priorities by region: Cleveland and Denver respondents prioritized quantity and quality goals, respectively, reflecting regional context. Co‐benefit priorities correlated to two environmental value orientation clusters — “Traditional Technocrats” with relatively anthropocentric orientations and “Champions” with relatively ecocentric orientations — who were equally abundant in both regions. Findings suggest that environmental value orientation influences co‐benefit priorities, which may have implications for project level articulation of policy. 

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. 

Abstract Decades of research has concluded that the percent of impervious surface cover in a watershed is strongly linked to negative impacts on urban stream health. Recently, there has been a push by municipalities to offset these effects by installing structural stormwater control measures (SCMs), which are landscape features designed to retain and reduce runoff to mitigate the effects of urbanisation on event hydrology. The goal of this study is to build generalisable relationships between the level of SCM implementation in urban watersheds and resulting changes to hydrology. A literature review of 185 peer‐reviewed studies of watershed‐scale SCM implementation across the globe was used to identify 52 modelling studies suitable for a meta‐analysis to build statistical relationships between SCM implementation and hydrologic change. Hydrologic change is quantified as the percent reduction in storm event runoff volume and peak flow between a watershed with SCMs relative to a (near) identical control watershed without SCMs. Results show that for each additional 1% of SCM‐mitigated impervious area in a watershed, there is an additional 0.43% reduction in runoff and a 0.60% reduction in peak flow. Values of SCM implementation required to produce a change in water quantity metrics were identified at varying levels of probability. For example, there is a 90% probability (high confidence) of at least a 1% reduction in peak flow with mitigation of 33% of impervious surfaces. However, as the reduction target increases or mitigated impervious surface decreases, the probability of reaching the reduction target also decreases. These relationships can be used by managers to plan SCM implementation at the watershed scale. 

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.