The effectiveness of green infrastructure at improving water quality and reducing flooding at the watershed scale

Green infrastructure (GI) is a stormwater management strategy designed to capture rain where it falls and allow it to soak into the ground rather than running off into a stream channel. By encouraging the infiltration of rainwater, GI strategies such as green roofs, rain gardens, and porous pavement can help to reduce flooding and improve water quality. While there has been a lot of research on the performance of individual GI projects, much less is known about their performance at larger, regional (i.e. watershed) scales. This project uses the EPA SWMM5 stormwater rainfall-runoff model to examine the effectiveness of GI at improving water quality and reducing flooding at the watershed scale. The objectives of this project are summarized as follows: (1) Use a stormwater model to examine the impacts of GI, such as green roofs and porous pavement, along with wetlands and soil management best practices on water quality and flooding at the watershed scale. (2) Identify performance differences between centralized versus decentralized GI at the watershed scale. These objectives are examined in a urban/suburban 213 acre subwatershed of the Kromma Kill, located in Albany County NY. Results highlight significant performance differences between the model scenarios. While a large centralized stormwater wetland is most effective at reducing flooding, decentralized GI can effectively reduce runoff volumes and subsequently greatly improve water quality. However, the most effective management strategy to maximize water quantity and quality benefits is a combination of centralized and decentralized GI. The results of this project have important implications for stormwater managers and watershed practitioners. GI is promoted around the world, including New York State, as an effective solution to mitigate flooding and improve water quality. But GI may not be a “one size fits all solution” and may work to meet some management objectives at some scales, but may not serve as the most effective, and therefore economical, solution for every management objective (Meierdiercks et al. [2017]). The results of this project can help practitioners identify the most appropriate type of GI and most effective scale to implement that GI to meet their management objectives.

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