Community Science-Driven Data Collection of Pennsylvania Urban Stormwater Control Measures Augmented by Machine Learning

A team of researchers is creating a comprehensive inventory of existing urban stormwater control measures through community volunteer participation and machine learning to improve urban stormwater management.

Urbanized areas with impervious surfaces generate high runoff and pollutant loads. In the United States, structural stormwater control measures (SCMs), are implemented to manage stormwater from new land development as well as part of broader municipal stormwater management efforts. SCMs, such as detention basins, retention ponds, wetland basins, vegetated swales, etc., are crucial in controlling runoff and mitigating flooding and water quality issues from urban developments. While there are thousands of urban SCMs implemented in Pennsylvania, a comprehensive inventory and map of SCMs in the State have not been prepared; lack of consistent SCM tracking is also a challenge beyond PA. The overall goal of this project is to create an inventory and web-based interactive map of urban SCMs in PA, which will help understand the effectiveness of these practices and identify the ones that require maintenance and/or retrofitting.

A one-stop master database of all the current SCMs could help researchers and policymakers use them in reliable planning, accessing, and quantifying the effectiveness of existing practices and design of climate-resilient infrastructures. This research aims to build a master database of urban SCMs in PA through community volunteer participation and explore machine learning and image processing techniques to identify SCMs from imageries and high-resolution digital elevation models (DEM).


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