RAPID: Quantifying the fluvial response to cascading dam failures at Edenville and Sanford, Michigan

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Our understanding of how floodplains and river channels respond to dam removal mostly comes from coordinated removal where the process is slow and predictable rather than from catastrophic dam breaks. Studies of coordinated removal are limited, and virtually no data exist on river response to dam failure. These are knowledge gaps are of practical significance because many dams in the United States are aging and at risk of failure. The work will advance understanding of the impacts of large floods and an aging infrastructure in the United States, which presents an increasing hazard to communities built downstream of dams. Such understanding is necessary for quantifying risk to best inform stakeholders. The work will also provide valuable research experience for two graduate students, one from an underrepresented group in geosciences. Finally, the team will disseminate the results of the work at conferences, in manuscripts, and openly host the data on Open Topography.The intellectual merit of this project is the ability to gather high resolution topographic data using an UAV lidar to characterize the aftermath of dam failure on the river and floodplain and how the river responds in the next year. The lidar data generated by this project will provide an important baseline dataset for models aimed at predicting river response to dam failure. The work will advance understanding of the impacts of large floods and an aging infrastructure in the United States, which presents an increasing hazard to communities built downstream of dams. The results will be presented at the annual meeting of the Society for Advancement of Chicanos/Hispanics and Native Americans in Science.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.