- News
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- Research Preview: Dignity of Fragile Essential Work in a Pandemic
- Earl Lewis Awarded the National Humanities Medal by President Biden
- Earl Lewis Speaks on Reparations
- Young Speaks About Latest Book on Podcast
- Research
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- Welcome Back! A Re-Introduction to the Center for Social Solutions
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Project Announcements
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Insights and Solutions
- CSS Research Periodical | Volume 1
- Michigan Becomes First State to Repeal Right-to-Work Law
- Author Q&A: The Evolution of Race and Place in Geographies of Risk and Resilience
- Governor Whitmer Signs “Filter First” Protections into Law for Michigan Schools and Childcare Centers
- Geography Awareness Week Q&A
- CSS Data Scientist Brad Bottoms Presents at the American Association of Geographers’ Annual Convening
- Water, Equity, and Security in Nepal: CSS Data Scientist Brad Bottoms Participates in International Research
- Events
- News Features
- Staff Features
- In the Face of Resistance: Advancing Equity in Higher Education
- Greening the Road Ahead: Navigating Challenges for Just Transitions to Electric Vehicles
- In the Wake of Affirmative Action
- Center for Social Solutions Co-Produces 'The Cost of Inheritance'
- Press Release: Earl Lewis, University of Michigan, Receives the Roy Rosenzweig Distinguished Service Award from the Organization of American Historians
- Higher Admissions: The Rise, Decline, and Return of Standardized Testing
- Events
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."
Read the full story here.
