Geology topics

Jamie Jones

Publications and source records attributed to Jamie Jones.

4 recordsLinked to original sources

USGS2024

Projections of multiple climate-related coastal hazards for the US Southeast Atlantic

Faced with accelerating sea level rise and changing ocean storm conditions, coastal communities require comprehensive assessments of climate-driven hazard impacts to inform adaptation measures. Previous studies have focused on flooding but rarely on other climate-related coastal hazards, such as subsidence, beach erosion and groundwater. Here, we project societal exposure to multiple hazards along the Southeast Atlantic coast of the United States. Assuming 1 m of sea level rise, more than 70% of the coastal residents and US \ $ 1 trillion in property are in areas projected to experience shallow and emerging groundwater, 15 times higher than daily flooding. Storms increase flooding exposure by an order of magnitude over daily flooding, which could impact up to ~50% of all coastal residents and US \ $ 770 billion in property value. The loss of up to ~80% of present-day beaches and high subsidence rates that currently affect over 1 million residents will exacerbate flooding and groundwater hazard risks.

Florida, Georgia, North Carolina, South Carolina, ↗

USGS2022

Multi-hazard risk analysis for the U.S. Department of the Interior: An integration of expert elicitation, planning priorities, and geospatial analysis

An integral part of disaster risk management is identifying and prioritizing hazards and their potential impacts in a meaningful way to support risk-reduction planning. There has been considerable use and subsequent criticism of threat prioritization efforts that simply compare likelihoods and consequences of plausible threats. This article summarizes a new mixed-methods and scalable approach for prioritizing risks in a multi-hazard, multi-objective, and multi-criteria organizational context. This approach integrates (1) hazard characterizations using subject-matter-expert (SME) elicitation, (2) expressed preferences in planning priorities provided by emergency managers, and (3) quantitative estimates of asset exposure to hazards using geospatial data and geographic-information-systems (GIS) software. We demonstrate this approach with a case study designed to support multi-hazard mitigation and response planning done by the U.S. Department of the Interior (DOI) Office of Emergency Management, which required a national understanding of the risks posed by 75 natural, technological, and adversarial hazards to DOI managed and administered lands, facilities, people, revenues, and resources. Results demonstrate that hazard priorities vary depending on the asset, scale, and risk-management context, thereby making the case that “one-size-fits-all” hazard rankings have limited utility or relevance to real-world, risk mitigation and response planning. Our results suggest that recognizing the risk-management context provides greater transparency, flexibility, and relevance in comparing threats than traditional likelihood-threat matrices or the use of hazard SMEs to decide for planners which hazard scenarios are emphasized in risk planning.

International Journal of Disaster Risk Reduction↗

USGS2018

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 M w 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.

American Samoa↗

USGS2018

Pedestrian evacuation modeling to reduce vehicle use for distant tsunami evacuations in Hawaiʻi

Tsunami waves that arrive hours after generation elsewhere pose logistical challenges to emergency managers due to the perceived abundance of time and inclination of evacuees to use vehicles. We use coastal communities on the island of Oʻahu (Hawaiʻi, USA) to demonstrate regional evacuation modeling that can identify where successful pedestrian-based evacuations are plausible and where vehicle use could be discouraged. The island of Oʻahu has two tsunami-evacuation zones (standard and extreme), which provides the opportunity to examine if recommended travel modes vary based on zone. Geospatial path distance models are applied to estimate population exposure a s a function of pedestrian travel time and speed out of evacuation zones. The use of the extreme zone triples the number of residents, employees, and facilities serving at-risk populations that would be encouraged to evacuate and slightly reduces the percentage of residents (98–76%) that could evacuate in less than 15 min at a plausible speed (with similar percentages for employees). Areas with lengthy evacuations are concentrated in the North Shore region for the standard zone but found all around the Oʻahu coastline for the extreme zone. The use of the extreme zone results in a 26% increase in the number of hotel visitors that would be encouraged to evacuate, and a 76% increase in the number of them that may require more than 15 min. Modeling can identify where pedestrian evacuations are plausible; however, there are logistical and behavioral issues that warrant attention before localized evacuation procedures may be realistic.

Hawai'i↗