Geology topics

Kevin Henry

Publications and source records attributed to Kevin Henry.

6 recordsLinked to original sources

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↗

USGS2020

Variations in community evacuation potential related to average return periods in probabilistic tsunami hazard analysis

Tsunami risk management requires strategies that can address multiple sources with different recurrence intervals, wave-arrival times, and inundation extents. Probabilistic tsunami hazard analysis (PTHA) provides a structured way to integrate multiple sources, including the uncertainties due to the natural variability and limited knowledge of sources. PTHA-based products relate to specific average return periods (ARP) and while there has been considerable attention paid to ARP choice for building codes, guidance on ARP choice to support evacuation planning and related land use is lacking. We use the State of California (USA) coastal communities as a case study to explore the use of geospatial analysis and pedestrian-evacuation modeling for comparing the societal implications of tsunamis based on evacuation areas that reflect inundation from 475-year, 975-year, and 2475-year ARPs. Results demonstrate that changes in PTHA ARP had a substantial effect on the number of tax-lot parcels in PTHA evacuation areas, but not on the primary land use of these parcels or which communities had the largest number of exposed parcels. Composite PTHA maps provided high-level insights on hazard exposure and identified dominant sources; however, disaggregated PTHA outputs that reflect single source parameters (e.g., wave-arrival time) were necessary to quantify evacuation potential from local and distant tsunamis. Framing changes in ARP assumption based on changes in the number, land-use type, and potential evacuation challenges of parcels in evacuation areas can provide valuable insight on the real-world implications of which ARP to use in land use or evacuation planning.

California↗

USGS2020

Influence of demand and capacity in transportation simulations of short-notice, distant-tsunami evacuations

Distant tsunamis require short-notice evacuations in coastal communities to minimize threats to life safety. Given the available time to evacuate and potential distances out of hazard zones, coastal transportation planners and emergency managers can expect large proportions of populations to evacuate using vehicles. A community-wide, short-notice, distant-tsunami evacuation is challenging because it creates a sudden, significant, and concentrated demand on road-network systems. Transportation planners and emergency managers need methods to help them determine if a road network can handle an evacuation surge and if not, where interventions can best reduce overall clearance times. We use the coastal community of Bay Farm Island (City of Alameda, California, USA) and the distant-tsunami threat posed by Aleutian-Alaskan earthquakes as a case study to explore the use of agent-based, transportation simulation to support short-notice, tsunami-evacuation planning. Results demonstrate how vehicle simulation can characterize network performance during a tsunami evacuation in the absence of real-world measurements of vehicle demand and flow. Changes in vehicle demand had the greatest influence on reductions in clearance times and recommended reductions varied based on time of day. Doubling the capacity of certain road segments based on traditional vehicle-capacity ratios and level-of-service thresholds reduced overall clearance time in some cases but increased it in other cases. The proposed simulation approach can serve as an analytical foundation for future efforts to characterize distant-tsunami evacuations in other coastal communities throughout the world.

California↗

USGS2019

Assessing hazards and risks at the Department of the Interior—A workshop report

On February 27–28, 2018, the U.S. Geological Survey and Department of the Interior (DOI) Office of Emergency Management (OEM) hosted a workshop to gather input from DOI subject matter experts (SMEs), resource managers, facility managers, emergency managers, and law enforcement personnel. Workshop goals were to (1) determine how DOI Bureaus and Offices use risk information for strategic planning and decision-making; (2) understand what types of information are most useful to DOI Bureaus and Offices; (3) establish what data, information, and products are desired; (4) identify the most effective methods for delivery and visualization; and (5) collect ideas for future project directions. The workshop findings presented in this report will influence the development of risk-information products created by the Strategic Hazard Identification and Risk Assessment of Department of the Interior Resources (SHIRA) Project team.

Circular↗

USGS2017

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

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.

Computers & Geosciences↗

USGS2016

Influence of road network and population demand assumptions in evacuation modeling for distant tsunamis

Tsunami evacuation planning in coastal communities is typically focused on local events where at-risk individuals must move on foot in a matter of minutes to safety. Less attention has been placed on distant tsunamis, where evacuations unfold over several hours, are often dominated by vehicle use and are managed by public safety officials. Traditional traffic simulation models focus on estimating clearance times but often overlook the influence of varying population demand, alternative modes, background traffic, shadow evacuation, and traffic management alternatives. These factors are especially important for island communities with limited egress options to safety. We use the coastal community of Balboa Island, California (USA), as a case study to explore the range of potential clearance times prior to wave arrival for a distant tsunami scenario. We use a first-in–first-out queuing simulation environment to estimate variations in clearance times, given varying assumptions of the evacuating population (demand) and the road network over which they evacuate (supply). Results suggest clearance times are less than wave arrival times for a distant tsunami, except when we assume maximum vehicle usage for residents, employees, and tourists for a weekend scenario. A two-lane bridge to the mainland was the primary traffic bottleneck, thereby minimizing the effect of departure times, shadow evacuations, background traffic, boat-based evacuations, and traffic light timing on overall community clearance time. Reducing vehicular demand generally reduced clearance time, whereas improvements to road capacity had mixed results. Finally, failure to recognize non-residential employee and tourist populations in the vehicle demand substantially underestimated clearance time.

California↗