A record number of floods have struck the U.S. over the past decade, devastating communities across the nation. In particular, millions of low-income, predominately minority-owned households remain most at risk — an inequality that is predicted to grow worse as climate change intensifies.

The Center for Social Solutions (CSS) has been working with the Real-Time Water Systems Lab at the University of Michigan to improve data networks so that burdened communities can more effectively respond to major flood events. In September, CSS researchers Brad Bottoms and Julie Arbit presented their most recent findings — “Equity in Flood Risk” — at a national emergency management conference in Grand Rapids, MI.

“Studies show that historically disadvantaged communities are both most at risk to flooding, as well as less likely to be able to recover,” research associate Julie Arbit explained. “Improving data networks that forecast and assess flooding can help track the extent of disasters in these communities."


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