Risk, Resilience, and Vulnerability

Risk Data Collection

The data we used for the National Risk Index (NRI) were obtained online through FEMA Data Resources | National Risk Index (fema.gov). For our analysis, we clipped these nationwide data sets at both the county and census tract level to our area of interest (the CRBAS boundaries).  

We did not modify the underlying methods of the National Risk Index or the component indices (Community Resilience and Social Vulnerability). Since the methods for the NRI and component indices are too complex to discuss in detail here, we point the reader to full documentation available from the sources of these data products. The best one-stop source for detailed descriptions of the data and methodologies behind the NRI and sub-indicators is FEMA’s 2021 National Risk Index – Technical Information. The Community Resilience sub-index is based on the Baseline Resilience Indicators for Communities (BRIC), which “…includes a set of 49 indicators that represent six types of resilience: social, economic, community capital, institutional capacity, housing/infrastructure, and environmental” (FEMA 2021). More information about the BRIC methods and a list papers utilizing BRIC are available at BRIC – College of Arts and Sciences | University of South Carolina. Readers interested in the Social Vulnerability Index (SoVI) project and its methodology can find more information at the University of South Carolina Hazards and Vulnerability Research Institute’s website, which includes a short methods guide, The SoVI® Recipe (Bureau, U. S. C., and Engine, C. D. (2016). The SoVI ® Recipe. September, 8–9).   

County and Census tract level NRI data was clipped to the CRBAS outline and summarized.

What is the FEMA National Risk Index?

In order to interpret the results, it is important to understand a little about what the NRI is. For a deeper dive, see the Additional Resources at the end of this chapter and data dashboard. The NRI is a holistic quantification of the potential for negative impacts resulting from natural hazards. It is comprised of three sub-indicators: Social Vulnerability Index (SoVI) (SV); Community Resilience (CR); and the estimated annual economic losses (EAL) associated with 18 different kinds of natural hazards.25 The relationships among the three component values are captured in the equation: 

 (EAL x SoVI) / CR = NRI 

The first two terms—Estimated Annual Loss and Social Vulnerability—are “consequence enhancing” components of risk, meaning that all else equal, the higher the score, the higher the NRI for a given community and thus the greater the risk level. Community Resilience has the opposite effect: it reduces the negative consequence of hazards by mitigating the first two variables. All else equal, the greater a community’s resilience score, the lower its NRI will be and the lower the overall degree of risk. 

NRI Limitations

It is important to recognize that the meaning of the concepts of risk, vulnerability, and resilience are heavily debated in the research community. They are highly complex phenomena that are difficult if not impossible to quantify due to their qualitative nature and/or a lack of readily available data. Thus, even though the scientific community has thoroughly vetted the indicators of risk, vulnerability, and resilience we utilize in this chapter, they represent particular, not universal, definitions of these concepts. So they are necessarily reductive and somewhat partial because they exclude factors—for example, the diversity of a water provider’s water portfolio, or the relative security of a water user’s water rights. 

Scale is another limitation of these indicators. While aggregating data to the level of census tracts and counties is useful and necessary for comparing different regions, it can obscure important local-level variations, such as statistical outlier communities. This is especially important in the western U.S., where many counties are very large and socially and environmentally heterogeneous. As noted by FEMA, the NRI is appropriate for broad comparisons but is not a substitute for localized risk analysis.26 It is useful as a high-level diagnostic tool and to identify where more information is needed to better understand risk in specific localities.