We propose to assess community resilience by testing for linkages between community preparedness for coastal flooding and measures of economic, ecological, flood hazard, and other key characteristics. This project will take an interdisciplinary approach that combines the expertise of an environmental economist and a GIS specialist. Flood preparedness will be measured using historical data on the four series activities of the Community Rating System (CRS) in Alabama and Mississippi communities.
Hypotheses to be tested flow directly from the following objectives:
- To test the relationship between flood hazard resiliency and economic activity, environmental risk exposure, and flood hazard, over time;
- To test whether CRS activities undertaken in each series are positively or negatively correlated;
- To test whether 2013 changes to the CRS have had a significant effect on activities undertaken;
- To test the relationship between CRS participation and indicators of economic activity, environmental risk exposure, and flood hazard;
- To test the consistency of CRS scores as a measure of flood hazard resiliency to other indices of flood resiliency used along the Gulf Coast.
At present, there appears to be limited understanding of the CRS in Alabama and Mississippi communities and the impact it has on them. The main impact of this work will be to document the role the CRS plays in coastal communities and trends in participation, including those due to recent changes in the CRS. In the short term, the immediate application of the results of this project will be to inform stakeholders of the current status of CRS participation in coastal Alabama and Mississippi. The results can be used to evaluate whether, and to what extent, recent changes to the CRS are impacting community participation. In the medium and long term, the results may be used to inform future changes to the CRS.
To test the relationship between flood hazard resiliency -- as indicated by CRS activity series scores – and indicators of economic activity, environmental risk exposure, and flood hazard, across Alabama and Mississippi coastal communities, and over time.
To test whether CRS activities undertaken in each activity series are positively or negatively correlated.
To test whether 2013 changes to the CRS have had a significant effect on community choice of activities undertaken.
To test the relationship between CRS participation and indicators of economic activity, environmental risk exposure, and flood hazard.
To test the consistency of Community Rating System scores (“points earned”) as a measure of flood hazard resiliency to other indices of flood resiliency used along the Gulf Coast.
The analysis will focus primarily on time-series data of individual community CRS activity for CRS communities in Alabama and Mississippi plus a randomly-selected sample of non-CRS participating NFIP communities. The addition of non-CRS communities will add the ability of the analysis to identify what factors influence the decision to participate in the CRS program at all, in addition to what factors influence CRS point-earning activities undertaken. An additional econometric analysis will be used to estimate a binary-choice model of CRS participation. CRS activity series data will be obtained from the FEMA-FIMA Region IV CRS coordinator. Sociodemographic data are publically available via the U.S. Census Bureau’s American Community Survey, including GIS shapefiles. Geospatial flood zone data is publically available via FEMA / Esri and will be compiled by investigators. All data from the various sources cited will be integrated into a single spreadsheet and coded appropriately, and then imported into a statistical software package to carry out the analysis.
We propose to apply multiple regression econometric techniques to the data collected, following the approach taken by Brody et al. (2009), who conducted a similar analysis for the state of Florida over the 1999-2005 period. Our work will extend that of Brody et al. (2009) in four ways. First, we will apply this analysis to communities in Alabama and Mississippi, whereas Brody et al. was limited to communities in Florida. Second, Brody et al. analyzed the period 1999-2005; our work will extend this analysis to the year 2016. Third, we will incorporate additional explanatory variables into the analysis not explored by Brody et al. Fourth, Brody et al. treated activity series equations as independent of one another, potentially ignoring correlated disturbances across series; we plan to model these equations simultaneously to account for any such correlation and to identify if scores in one series are positively or negatively related (or indeed independent).
MASGC defines a resilient community as one that “has a diverse and vibrant economy, responds to and mitigates natural and technological hazards, and functions within the limits of its ecosystems.” The thing to note about this definition is that it points to the role of diversity as a defining characteristic of resiliency. This means that a resilient community will have a diverse portfolio of activity within each sector (economic activity, hazard preparedness, and environmental stewardship), as well as diversity across these sectors. In other words, a community that is resilient to flood hazard will have, all else equal, a diverse portfolio of flood preparedness activities. It will also embody a diversity activities across flood preparedness, economic, environmental activities. Finally, a resilient community will recognize and capitalize on the linkages across these sectors; i.e., they will not operate independent of, or in competition with, each other, but in unison. Thus, we hypothesize that a community’s depth (quantity) and breadth (diversity) of one sector – in this proposal, flood preparedness -- is a function of that community’s socio-economic, environmental, and other key characteristics, and this linkage, if it exists, can serve as a measure of community resiliency, because it will indicate the degree to which a community’s choices in one sector relate – positively or negatively – to activity in the other sectors.
Although a community’s overall CRS class, on which is based its flood insurance premium discount for residents and businesses, provides some indicator of preparedness, it masks a community’s diversity (and hence, resiliency) of preparedness, which is better captured by the distribution of individual CRS point-earning activities. CRS activities are subdivided into four general classes: public information (Series 300), maps and regulation (Series 400), damage reduction (Series 500), and warning and response (Series 600). Brody et al. (2009) find that, among Florida communities, public information and mapping and regulation activities tend to be pursued most frequently, with much less reliance on flood damage reduction and warning and response activities, which, while fetching more points, generally require more costly changes to community infrastructure, etc. Petrolia, Landry, and Coble (2013) find that although increased CRS participation has a positive effect on flood insurance uptake, that, in the state of Florida, it appears to have a substituting effect, i.e., that individuals living in communities with stronger CRS participation are less likely to purchase flood insurance. These kinds of unintended consequences appear to be at the center of FEMA-FIMA’s efforts to reform CRS. For example, under the 2013 changes, incentives are put in place to encourage communities to shift emphasis from information-based activities toward more structural activities. For example, some communities will now receive additional points for open space preservation (Activity 420), but receive fewer points for informational activities (e.g., Activity 320). What remains to be seen is if these new incentives will be effective in pushing communities toward a more diverse set of flood hazard mitigation activities. It is worth noting that multiple CRS activities touch on issues of importance from a community resiliency standpoint, i.e., beyond flood hazard. These include open space preservation (Activity 420), stormwater management (Activity 450), and drainage system maintenance (Activity 540). Thus, changes in how communities participate in the CRS program – and if they participate – can have significant impacts on other issues of importance to communities that affects their overall resilience.
(Brody, Samuel D., Sammy Zahran, Wesley E. Highfield, Sarah P. Bernhardt, and Arnold Vedlitz. 2009. “Policy Learning for Flood Mitigation: A Longitudinal Assessment of the Community Rating System in Florida.” Risk Analysis 29(6): 912-29.)