Jeanne M. Jones

Community clusters of tsunami vulnerability in the US Pacific Northwest

Significance We present an analytical framework for understanding community-level vulnerability to tsunamis that integrates population exposure, demographic sensitivity, and evacuation potential.We identify three types of communities along the US Pacific Northwest coast that are directly threatened by tsunamis associated with a Cascadia subduction zone earthquake: (i) demographically diverse with low numbers of exposed people, (ii) high numbers of exposed populations but sufficient time to evacuate, and (iii) moderate numbers of exposed populations but insufficient time to evacuate. This approach is a significant advance over current practice because traditional measures of social vulnerability do not relate population structure to specific hazard characteristics. Results help managers to develop risk reduction strategies that are tailored to local conditions and needs. Many coastal communities throughout the world are threatened by local (or near-field) tsunamis that could inundate low-lying areas in a matter of minutes after generation. Although the hazard and sustainability literature often frames vulnerability conceptually as a multidimensional issue involving exposure, sensitivity, and resilience to a hazard, assessments often focus on one element or do not recognize the hazard context. We introduce an analytical framework for describing variations in population vulnerability to tsunami hazards that integrates (i) geospatial approaches to identify the number and characteristics of people in hazard zones, (ii) anisotropic path distance models to estimate evacuation travel times to safety, and (iii) cluster analysis to classify communities with similar vulnerability. We demonstrate this approach by classifying 49 incorporated cities, 7 tribal reservations, and 17 counties from northern California to northern Washington that are directly threatened by tsunami waves associated with a Cascadia subduction zone earthquake. Results suggest three primary community groups: (i) relatively low numbers of exposed populations with varied demographic sensitivities, (ii) high numbers of exposed populations but sufficient time to evacuate before wave arrival, and (iii) moderate numbers of exposed populations but insufficient time to evacuate. Results can be used to enhance general hazard-awareness efforts with targeted interventions, such as education and outreach tailored to local demographics, evacuation training, and/or vertical evacuation refuges.

HERA: A dynamic web application for visualizing community exposure to flood hazards based on storm and sea level rise scenarios

Abstract The Hazard Exposure Reporting and Analytics (HERA) dynamic web application was created to provide a platform that makes research on community exposure to coastal-flooding hazards influenced by sea level rise accessible to planners, decision makers, and the public in a manner that is both easy to use and easily accessible. HERA allows users to (a) choose flood-hazard scenarios based on sea level rise and storm assumptions, (b) appreciate the modeling uncertainty behind a chosen hazard zone, (c) select one or several communities to examine exposure, (d) select the category of population or societal asset, and (e) choose how to look at results. The application is designed to highlight comparisons between (a) varying levels of sea level rise and coastal storms, (b) communities, (c) societal asset categories, and (d) spatial scales. Through a combination of spatial and graphical visualizations, HERA aims to help individuals and organizations to craft more informed mitigation and adaptation strategies for climate-driven coastal hazards. This paper summarizes the technologies used to maximize the user experience, in terms of interface design, visualization approaches, and data processing.

PRISM Software: Processing and Review Interface for Strong‐Motion Data

ABSTRACT A continually increasing number of high‐quality digital strong‐motion records from stations of the National Strong Motion Project (NSMP) of the U.S. Geological Survey, as well as data from regional seismic networks within the United States, calls for automated processing of strong‐motion records with human review limited to selected significant or flagged records. The NSMP has developed the Processing and Review Interface for Strong Motion data (PRISM) software to meet this need. In combination with the Advanced National Seismic System Quake Monitoring System (AQMS), PRISM automates the processing of strong‐motion records. When used without AQMS, PRISM provides batch‐processing capabilities. The PRISM software is platform independent (coded in Java), open source, and does not depend on any closed‐source or proprietary software. The software consists of two major components: a record processing engine composed of modules for each processing step, and a review tool, which is a graphical user interface for manual review, edit, and processing. To facilitate use by non‐NSMP earthquake engineers and scientists, PRISM (both its processing engine and review tool) is easy to install and run as a stand‐alone system on common operating systems such as Linux, OS X, and Windows. PRISM was designed to be flexible and extensible to accommodate implementation of new processing techniques. All the computing features have been thoroughly tested.

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

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.

Population vulnerability to tsunami hazards informed by previous and projected disasters: a case study of American Samoa

Population vulnerability from tsunamis is a function of the number and location of individuals in hazard zones and their ability to reach safety before wave arrival. Previous tsunami disasters can provide insight on likely evacuation behavior, but post-disaster assessments have not been used extensively in evacuation modeling. We demonstrate the utility of post-disaster assessments in pedestrian evacuation modeling for tsunami hazards and use the US territory of American Samoa as our case study. We model pedestrian travel times out of tsunami inundation zones recreated for the 2009 Mw 8.1 Samoa earthquake, as well as for a probable maximum tsunami zone for future threats. Modeling assumptions are guided by fatality trends and observations of 2009 evacuation behavior, including insights on departure delays, environmental cues, transportation mode, and demographic characteristics. Differences in actual fatalities from the 2009 disaster and modeled population vulnerability suggest that a single set of estimated travel times to safety does not fully characterize evacuation potential of a dispersed, at-risk population. Efforts to prepare coastal communities in American Samoa for future tsunamis may be challenging given substantial differences in wave characteristics and evacuation potential of the probable maximum hazard compared to the 2009 event.