Year of Graduation
Level of Access
Restricted Access Thesis
Department or Program
Earth and Oceanographic Science
Climate change and sea-level rise present significant challenges to low-lying, coastal communities, particularly in urban settings. In the San Francisco Bay Area, many of these vulnerable communities have witnessed rapid change associated with urbanization and often inequitable access to political influence and economic development over the last century. The combination of an uncertain and increasing flood hazard with increased vulnerability implies significant and evolving risk. To prepare for the challenges ahead, community leaders must evaluate different scenarios to get a comprehensive assessment of the various sources of vulnerability in these communities.
The starting point for most evaluations of risk is direct damages, defined as the monetary loss due to flood damage to building structures and contents. Here, we use the Stanford Urban Risk Framework (SURF) for San Mateo County, which links Census data to hazard, exposure, vulnerability, and household income to quantify direct damages resulting from coastal flooding. The main contribution of this study is to assess the degree to which these direct damages are distributed equitably among different population groups or not.
Instead of using a principal component analysis (PCA), which is commonly used in indices to identify socially vulnerable communities, we use k-means clustering to look at individual and interacting attributes of social vulnerability. The k-means clustering results revealed a complex, non-direct relationship between the high cost of damages and one or more social vulnerability factors. This analysis helps locate the cities receiving damages and identify which social vulnerabilities correlate with damages.
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