MIDAS, the Michigan Institute for Data Science, is a University of Michigan (U-M)-wide institute with 420 affiliated faculty from 60 departments. Each year MIDAS awards a series of pilot-study grants for research in data science and artificial intelligence, known as PODS grants (Propelling Original Data Science). This year, four researchers in SEAS received three of these 17 awards. One of the awards was to SEAS faculty member Runzi Wang, in collaboration with Yang Chen and Bill Currie. In this project, new data-science and modeling methods are being developed to use existing stream water quality datasets (nutrients and sediments) for streams that pass through U.S. urban areas and link those to specific sub-watersheds. In the sub-watersheds, we investigate metrics of urban form such as spatial patterns and connectivity of impervious surfaces and how they relate to road networks and built structures. We use data-driven modeling to investigate relationships between urban form and its effects, through storm runoff, on stream water quality. We are also developing methods to include other social outcomes that derive from urban form, including housing density and access to green space. The results from this research will have relevance for urban planning, including identifying synergies or tradeoffs in joint outcomes. Read more about the MIDAS PODS grants in this SEAS press release.