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Effects of spatial configuration of imperviousness and green infrastructure networks on hydrologic response in a residential sewershed

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Date

2017-09-01

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American Geophysical Union

Abstract

Green infrastructure (GI) is an approach to stormwater management that promotes natural processes of infiltration and evapotranspiration, reducing surface runoff to conventional stormwater drainage infrastructure. As more urban areas incorporate GI into their stormwater management plans, greater understanding is needed on the effects of spatial configuration of GI networks on hydrological performance, especially in the context of potential subsurface and lateral interactions between distributed facilities. In this research, we apply a three-dimensional, coupled surface-subsurface, land-atmosphere model, ParFlow.CLM, to a residential urban sewershed in Washington DC that was retrofitted with a network of GI installations between 2009 and 2015. The model was used to test nine additional GI and imperviousness spatial network configurations for the site and was compared with monitored pipe-flow data. Results from the simulations show that GI located in higher flow-accumulation areas of the site intercepted more surface runoff, even during wetter and multiday events. However, a comparison of the differences between scenarios and levels of variation and noise in monitored data suggests that the differences would only be detectable between the most and least optimal GI/imperviousness configurations.

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Keywords

Physical Sciences, Environmental Sciences, Limnology, Water Resources, Environmental Sciences & Ecology, Marine & Freshwater Biology, green infrastructure, stormwater management, imperviousness, spatial configuration, urban hydrology, ParFlow, CLM, LOW IMPACT DEVELOPMENT, STORMWATER MANAGEMENT, CATCHMENT-SCALE, HYDRAULIC CONDUCTIVITY, FIELD PERFORMANCE, UNITED-STATES, WATER, SURFACE, BIORETENTION, SIMULATIONS, 0406 Physical Geography and Environmental Geoscience, 0905 Civil Engineering, 0907 Environmental Engineering, Environmental Engineering

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