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Community Resilience Estimates Data and Flood Insurance Rate Maps

Neighborhood-scale map showing aerial imagery of the north side of Milwaukee. The map combines Flood Insurance Rate Map data from FEMA and Community Resilience Estimates data from the U.S. Census Bureau. The map has blue shading indicating the one percent annual chance flood hazard area and orange shading indicating the zero point two percent annual chance flood hazard area. Areas of blue and red alternating stripes indicate the regulatory floodway. Areas near Lincoln Creek are in flood hazard zones. Some areas of the map are overlaid with cross-hatching to indicate census tracts where the households predominantly have three or more Community Resilience Estimates risk factors. Census tracts with hatching have households predominantly with one or two risk factors. All other areas have households with predominantly zero risk factors. There are four census tracts partially shown. Three of them are in the one to two risk factor category and one is in the three or more risk factors category.

This is one of the figures from my Master’s thesis which I completed in 2024.

I wanted to test ways to improve flood risk communication using maps, mostly for public audiences. Although I came across different flood risk maps in my research, Flood Insurance Rate Maps (FIRMs) proved to be the most commonly used and well-known flood risk map in the United States. However, a lot of research demonstrates the limitations of FIRMs, so I narrowed my flood risk communication project to just FIRMs. They were already thoroughly critiqued and have to be used by tens of thousands of communities participating in the National Flood Insurance Program. My idea was that community government workers, for example, who might use FIRMs or probationary FIRMs to communicate with local residents could use different flood risk maps to communicate more effectively.

There are already many alternatives to FIRMs, and I personally think some of the model-based maps are the best overall. However, mapping is not only about being the most comprehensive or cutting-edge. An alternative map might serve a very specific purpose or have unique strengths or share a new perspective. This philosophy drove my work, since I could never compete with a nationwide flood risk model. What I could do was propose a flood risk map that is easy to replicate and has unique but relevant data. That is how I chose to work with Community Resilience Estimates data from the U.S. Census Bureau. It was a unique dataset that used microdata, updated annually, and was freely available. It was relevant because it depicted spatial, quantitative social vulnerability data. FIRMs do not explicitly depict flood vulnerability, so adding Community Resilience Estimates data can show which areas might be more impacted by a flood as a result of social risk factors.

I ended up making a few FIRMs myself, some with Community Resilience Estimates data and some without. I asked Milwaukee County residents to answer map task questions and share what they learned about flood risk from the maps. The results of the study show that this method has some potential to improve how FIRMs communicate flood risk.