CONSTRUCTING A COMPOSITE HAZARDS VULNERABILITY INDEX FOR COASTAL CALIFORNIA

Vulnerability, or the potential for loss, to hazards is the subject of much ongoing hazards research. This research includes efforts involving the development and evaluation of various indices to combine and quantify physical and socioeconomic variables that will effectively characterize the relative vulnerability of places to natural hazards across a range of geographic scales. As a part of its involvement with the U.S. Geological Survey’s Southern California Multi-Hazards Demonstration Project (MHDP), the Rocky Mountain Geographic Science Center (RMGSC) is using methods and results from previous hazards vulnerability and index development research as a guide for investigating various approaches to constructing a composite hazards vulnerability index for California’s coastal areas based on combinations of attributes from multiple indices describing the natural, social, and built environments. With the aid of a geographic information system, selected variables used in existing Coastal Vulnerability (e.g., coastal slope, shoreline erosion, relative sea-level change), Social Vulnerability (e.g., poverty, age, race), and Urban Intensity (e.g., housing unit density, developed land area, road density) indices are being collected and analyzed for census tracts along the California coast. The objective is to develop a composite index to quantify and map the relative vulnerability of locations along the California coast to natural hazards associated with a winter storm scenario, ARk Storm, being developed as part of the MHDP. Challenges with index construction include the selection of appropriate variables, the standardization and combination of these variables, and the effects of geographic scale on the relationship between the selected variables and calculated index values. A well-constructed composite hazards vulnerability index could, however, assist with assessing ARk Storm scenario outcomes by providing a pre-storm baseline measure of vulnerability for comparison with post-storm patterns of vulnerability as determined from modeled changes in the natural, social, and built environment index variables resulting from the scenario storm.