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Green Infrastructure Placement Strategy in Urban Stormwater Network

Authors: Xiating Chen, Xue Feng, UMN Twin Cities/Saint Anthony Falls Laboratory

Abstract: Although effective in reducing upstream inland flooding, urban gray infrastructure increases flooding downstream and leads to a sharper peak flow in the hydrograph. With the increasing concerns around outlet stormwater qualities, engineers are considering retrofitting nature-based solutions in stormwater controls, both to treat runoff locally and to attenuate flow downstream. Currently, green infrastructure is implemented at a project scale, not a regional scale. If we were to scale up and plan nature-based solutions and green infrastructure for an entire watershed with mixed land covers, are there optimal locations where we may expect the most flood control benefits?

In this project, we simulate rainfall-runoff models to examine the effects of the connectivity and topography of nature-based solutions on flow control in stormwater networks. We randomly generate tree networks using the Python NetworkX package to recreate urban stormwater networks, and randomly assign permeable nodes to the networks to represent nature-based solutions and green infrastructure. Using SWMM, we can model the performance of these stormwater networks over the course of a simulated storm event, under changing rainfall intensities and antecedent soil moisture. To distill the effects of network structures on flow control outcome, we have defined and calculated the connectivity of above-ground nature-based solutions among each other and with underground stormwater pipes, and the distance of these green infrastructure to watershed outlets. In the near future, our investigation on the relationship between network structure and flood control outcome may serve as theoretical guidelines for nature-based green infrastructure watershed master planning.