SCC-CIVIC-PG Track B: Helping Rural Counties to Enhance Flooding and Coastal Disaster Resilience and Adaptation

In the United States, flooding is a leading cause of natural disasters, with congressional budget office estimates of $54 billion in loss each year. Although both urban and rural areas are highly vulnerable to flood hazards, most natural disaster resilience studies have focused on urban areas, often overlooking rural communities. One such area that has been overlooked are the many rural communities bordering the Great Lakes.

These communities are facing unprecedented challenges due to rising water levels, particularly since 2012, which have resulted in significant coastal flood hazards to the communities. Flood hazard assessments are a critical tool that is used support communities in determining how to mitigate flooding; however, data gaps in current flood hazard modeling tools render them inaccurate for rural communities.

This project will use various strategies, including sensors and crowdsourced information, to fill critical information gaps required to improve flood hazard modeling in rural communities bordering the Great Lakes.

This project aims to bring together community-university partners to understand the data gaps in addressing flooding and coastal disaster in three Northern Michigan Counties. The rural coastal and inland counties in the Great Lakes states face an unprecedented challenge due to rising water levels. While these rural communities are vulnerable to flooding, they lack flood hazard assessments and inundation maps due to the lack of resources.

The Federal Emergency Management Agency (FEMA) and the Department of Homeland Security (DHS) commonly recommend counties to use a freely available tool—called HAZUS to develop hazard mitigation plans and enhance community resilience and adaptation. However, the usage of HAZUS for rural communities could potentially have some serious deficiencies unless augmented with additional data and analyses.

These severe deficiencies are due to the data gaps in analyzing the hazards in rural communities. The use of standard datasets for HAZUS analysis by rural counties could likely leave the communities underprepared for future flood events of significant magnitude. The proposed project’s vision is to develop methods that use remote sensing data resources and citizen engagement (crowdsourcing) to address current data gaps for improved flood hazard modeling and visualization that is transferable to rural communities.

This project is in response to the Civic Innovation Challenge program, Track B—Resilience to Natural Disasters—and is a collaboration between NSF and the Department of Homeland Security.

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.