Abstract
Sea level is projected to rise over the coming decades, further increasing the extent of flooding hazards in coastal communities. Efforts to address potential impacts from climate-driven coastal hazards have called for collaboration among communities to strengthen the application of best practices. However, communities currently lack practical tools for identifying potential partner communities based on similar hazard exposure characteristics. This study uses statistical cluster analysis to identify similarities in community exposure to flooding hazards for a suite of sea level rise and storm scenarios. We demonstrate this approach using 63 jurisdictions in the San Francisco Bay region of California (USA) and compare 21 distinct exposure variables related to residents, employees, and structures for six hazard scenario combinations of sea level rise and storms. Results indicate that cluster analysis can provide an effective mechanism for identifying community groupings. Cluster compositions changed based on the selected societal variables and sea level rise scenarios, suggesting that a community could participate in multiple networks to target specific issues or policy interventions. The proposed clustering approach can serve as a data-driven foundation to help communities identify other communities with similar adaptation challenges and to enhance regional efforts that aim to facilitate adaptation planning and investment prioritization.
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Acknowledgements
The authors would like to thank Sandrine Dudoit for early discussions about clustering stability. Any use of trade, product, or firm names is for descriptive purposes only and does not imply endorsement by the US Government.
Funding
This study is part of the Resilient Infrastructure as Seas Rise (RISeR) project, supported by the National Science Foundation Critical Resilient Interdependent Infrastructure Systems and Processes (CRISP) Award 1541181.
US Geological Survey (USGS)-affiliated authors are supported by the USGS Land Change Science Program and the USGS Coastal and Marine Geology Program.
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ESM 1
Study area of the San Francisco Bay region in California (USA), including boundaries for the 55 incorporated cities and 8 counties with land in flood-hazard zones that reflect various storm and sea level rise scenarios summarized by Jones et al. (2016). San Francisco is considered both a city and a county and thus contains no unincorporated land (EPS 6200 kb)
ESM 2
Cluster analysis of population exposure to coastal-flooding hazards with 50 cm, 100 cm, and 150 cm of SLR, assuming (a) no storm and (b) 100-year storm. Variables in each graph of z-scores and clustering group assignments include the number and community percentages of residents and employees in hazard zones. Tables identify the communities that are included in each group, organized in geographical order by county (clockwise around San Francisco Bay, starting with Marin County) (EPS 1818 kb)
ESM 3
Cluster analysis of built environment exposure to coastal-flooding hazards with 50 cm, 100 cm, and 150 cm of SLR, assuming (a) no storm and (b) 100-year storm. Variables in each graph of z-scores and clustering group assignments include the number of critical infrastructure and critical facilities in hazard zones. Tables identify the communities that are included in each group (EPS 2520 kb)
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Hummel, M.A., Wood, N.J., Schweikert, A. et al. Clusters of community exposure to coastal flooding hazards based on storm and sea level rise scenarios—implications for adaptation networks in the San Francisco Bay region. Reg Environ Change 18, 1343–1355 (2018). https://doi.org/10.1007/s10113-017-1267-5
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DOI: https://doi.org/10.1007/s10113-017-1267-5