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Results for “Journal of Disaster Research”

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USGS2019

Exploring the barriers for people taking protective actions during the 2012 and 2015 New Zealand shakeout drills

To reduce future earthquake injuries and casualties, it is important that people understand how their behavior, during and immediately following earthquake shaking, exposes them to increased risk of injury or death. Research confirms that protective actions can reduce injuries and that prior training can help prepare people to take appropriate actions. In this paper, we examine barriers to participation in the ShakeOut drills in New Zealand. Through citizen science research, volunteers observed people performing the drills in 2012 and 2015. Observers reported how long it took to perform the drill and why they thought some people may not have completed it. Our findings illustrate that children, elderly, and those with both mental and physical disabilities struggled with the drill. Furthermore, embarrassment was a reported leading cause for non-participation; we recommend more inclusive messaging to address potential causes of embarrassment.

International Journal of Disaster Risk Reduction↗
USGS2023

Social vulnerability and geographic access barriers to earthquake early warning education in museums and other free choice learning environments

Given the earthquake risk on the West Coast of the United States, individuals and communities require a basic understanding of ShakeAlert earthquake early warning technology, which may provide crucial seconds of warning. Free choice learning environments (FCLEs), such as museums, public libraries, and national parks, are uniquely positioned to expand the reach of earthquake early warning through educational initiatives and resources. Earthquake education in these spaces creates awareness of earthquake hazards and risk in areas where people live or visit and may also increase engagement in preparedness behavior as they are trusted sources of information in their communities. However, population demographics within the ShakeAlert states has yet to be examined; audience segmentation theories require a better understanding of the demographics of the people the system seeks to serve. Here we build upon previous typology research that examined over 150 earthquake displays around the United States and found that most did not include information about earthquake preparedness or associated protective actions. This new research shifts to a hierarchical clustering analysis that identifies seven main population groups within the ShakeAlert states. We also find that the cost of admission and the geographic distance away from FCLEs, including the potential cost and time of transportation, may lead to an urban-rural divide in visitor access. Using audience segmentation theories as related to earthquakes, we can understand critical barriers to FCLEs and opportunities for ShakeAlert education. As earthquake early warning systems expand internationally, thoughtful and equitable education initiatives are beneficial to reach critical audiences.

International Journal of Disaster Risk Reduction↗
USGS2026

Can a physics-based fire behavior model predict burn severity and post-fire debris flow hazard?

Post-wildfire flooding and debris flows pose a threat to ecosystems and infrastructure. As the frequency and size of severe wildfires increase, there is a growing need for predictive debris flow hazard modeling in unburned but fire-prone landscapes. However, no crosswalks have been established between physics-based models of fire behavior and the remotely sensed burn severity inputs needed for debris flow modeling. Here, we explore this connection by creating a large ensemble of fire behavior simulations using QUIC-Fire – a fast-running three-dimensional fire model – in basins across five major-disaster wildfires in California and Washington. We then conducted generalized linear mixed modeling (GLMM) and Random Forest modeling to identify QUIC-Fire outputs that best predicted remotely sensed burn severity. We found that the selected linear predictors exhibited weak and unintuitive relationships with soil burn severity and differenced Normalized Burn Ratio. Moreover, model evaluations of GLMMs and Random Forests showed they were poorly predictive of both metrics of remotely sensed burn severity. This suggests that there are barriers to integrating QUIC-Fire into a wildfire-hazards modeling framework, which could include mismatches in scale between fire models and remotely sensing, or simplifications of weather data and fire initiation. Further research is needed to establish connections between the fire physics outputs of QUIC-Fire and post-fire effects to vegetation and soils that are essential for evaluating debris flow hazard.

California, Washington↗
USGS2016

Enabling science support for better decision-making when responding to chemical spills

Chemical spills and accidents contaminate the environment and disrupt societies and economies around the globe. In the United States there were approximately 172,000 chemical spills that affected US waterbodies from 2004 to 2014. More than 8000 of these spills involved non–petroleum-related chemicals. Traditional emergency responses or incident command structures (ICSs) that respond to chemical spills require coordinated efforts by predominantly government personnel from multiple disciplines, including disaster management, public health, and environmental protection. However, the requirements of emergency response teams for science support might not be met within the traditional ICS. We describe the US ICS as an example of emergency-response approaches to chemical spills and provide examples in which external scientific support from research personnel benefitted the ICS emergency response, focusing primarily on nonpetroleum chemical spills. We then propose immediate, near-term, and long-term activities to support the response to chemical spills, focusing on nonpetroleum chemical spills. Further, we call for science support for spill prevention and near-term spill-incident response and identify longer-term research needs. The development of a formal mechanism for external science support of ICS from governmental and nongovernmental scientists would benefit rapid responders, advance incident- and crisis-response science, and aid society in coping with and recovering from chemical spills.

Journal of Environmental Quality↗
USGS2021

Principles for collaborative risk communication: Reducing landslide losses in Puerto Rico

Landslides are frequent and damaging natural hazards that threaten the people and the natural and built environments of Puerto Rico. In 2017, more than 70,000 landslides were triggered across the island by heavy rainfall from Hurricane María, prompting requests by local professionals for landslide education and outreach materials. This article describes a novel collaborative risk communication framework that was developed to meet those requests and shaped the creation of a Spanish- and English-language Landslide Guide for Residents of Puerto Rico. Collaborative risk communication is defined here as an iterative process guided by a set of principles for the interdisciplinary coproduction of hazards information and communication products by local and external stakeholders. The process that supports this form of risk communication involves mapping out the risk communication stakeholders in the at-risk or disaster-affected location—in this case Puerto Rico—and collaborating over time to address a shared challenge, such as landslide hazards. The approach described in this article involved the formation of a core team of government and university partners that expanded in membership to conduct collaborative work with an informal network of hazards professionals from diverse sectors in Puerto Rico. The following principles guided this process: cultural competence, ethical engagement, listening, inclusive decision making, empathy, convergence research, nested mentoring, adaptability, and reciprocity. This article contributes to the field of risk communication and emergency management by detailing these principles and the associated process in order to motivate collaborative risk communication efforts in different geographic and cultural contexts. While the work described here focuses on addressing landslides, the principles and process are transferable to other natural, technological, and willful human-caused hazards. They may also serve as a roadmap for future partnerships among government agencies and university researchers to inform the cocreation of science education and outreach tools.

Puerto Rico↗
USGS2009

Integrating disparate lidar datasets for a regional storm tide inundation analysis of Hurricane Katrina

Hurricane Katrina was one of the largest natural disasters in U.S. history. Due to the sheer size of the affected areas, an unprecedented regional analysis at very high resolution and accuracy was needed to properly quantify and understand the effects of the hurricane and the storm tide. Many disparate sources of lidar data were acquired and processed for varying environmental reasons by pre- and post-Katrina projects. The datasets were in several formats and projections and were processed to varying phases of completion, and as a result the task of producing a seamless digital elevation dataset required a high level of coordination, research, and revision. To create a seamless digital elevation dataset, many technical issues had to be resolved before producing the desired 1/9-arc-second (3meter) grid needed as the map base for projecting the Katrina peak storm tide throughout the affected coastal region. This report presents the methodology that was developed to construct seamless digital elevation datasets from multipurpose, multi-use, and disparate lidar datasets, and describes an easily accessible Web application for viewing the maximum storm tide caused by Hurricane Katrina in southeastern Louisiana, Mississippi, and Alabama.

Journal of Coastal Research↗
USGS2011

The human dimension of fire regimes on Earth

Humans and their ancestors are unique in being a fire‐making species, but ‘natural’ (i.e. independent of humans) fires have an ancient, geological history on Earth. Natural fires have influenced biological evolution and global biogeochemical cycles, making fire integral to the functioning of some biomes. Globally, debate rages about the impact on ecosystems of prehistoric human‐set fires, with views ranging from catastrophic to negligible. Understanding of the diversity of human fire regimes on Earth in the past, present and future remains rudimentary. It remains uncertain how humans have caused a departure from ‘natural’ background levels that vary with climate change. Available evidence shows that modern humans can increase or decrease background levels of natural fire activity by clearing forests, promoting grazing, dispersing plants, altering ignition patterns and actively suppressing fires, thereby causing substantial ecosystem changes and loss of biodiversity. Some of these contemporary fire regimes cause substantial economic disruptions owing to the destruction of infrastructure, degradation of ecosystem services, loss of life, and smoke‐related health effects. These episodic disasters help frame negative public attitudes towards landscape fires, despite the need for burning to sustain some ecosystems. Greenhouse gas‐induced warming and changes in the hydrological cycle may increase the occurrence of large, severe fires, with potentially significant feedbacks to the Earth system. Improved understanding of human fire regimes demands: (1) better data on past and current human influences on fire regimes to enable global comparative analyses, (2) a greater understanding of different cultural traditions of landscape burning and their positive and negative social, economic and ecological effects, and (3) more realistic representations of anthropogenic fire in global vegetation and climate change models. We provide an historical framework to promote understanding of the development and diversification of fire regimes, covering the pre‐human period, human domestication of fire, and the subsequent transition from subsistence agriculture to industrial economies. All of these phases still occur on Earth, providing opportunities for comparative research.

Journal of Biogeography↗
USGS2021

Conservation of northwestern and southwestern pond turtles: Threats, population size estimates, and population viability analysis

Accurate status assessments of long-lived, widely distributed taxa depend on the availability of long-term monitoring data from multiple populations. However, monitoring populations across large temporal and spatial scales is often beyond the scope of any one researcher or research group. Consequently, wildlife managers may be tasked with utilizing limited information from different sources to detect range-wide evidence of population declines and their causes. When assessments need to be made under such constraints, the research and management communities must determine how to extrapolate from variable population data to species-level inferences. Here, using three different approaches, we integrate and analyze data from the peer-reviewed literature and government agency reports to inform conservation for northwestern pond turtles (NPT) Actinemys marmorata and southwestern pond turtles (SPT) Actinemys pallida . Both NPT and SPT are long-lived freshwater turtles distributed along the west coast of the United States and Mexico. Conservation concerns exist for both species; however, SPT may face more severe threats and are thought to exist at lower densities throughout their range than NPT. For each species, we ranked the impacts of 13 potential threats, estimated population sizes, and modeled population viability with and without long-term droughts. Our results suggest that predation of hatchlings by invasive predators, such as American bullfrogs Lithobates catesbeianus and Largemouth Bass Micropterus salmoides, is a high-ranking threat for NPT and SPT. Southwestern pond turtles may also face more severe impacts associated with natural disasters (droughts, wildfires, and floods) than do NPT. Population size estimates from trapping surveys indicate that SPT have smaller population sizes on average than do NPT ( P = 0.0003), suggesting they may be at greater risk of local extirpation. Population viability analysis models revealed that long-term droughts are a key environmental parameter; as the frequency of severe droughts increases with climate change, the likelihood of population recovery decreases, especially when census sizes are low. Given current population trends and vulnerability to natural disasters throughout their range, we suggest that conservation and recovery actions first focus on SPT to prevent further population declines.

Journal of Fish and Wildlife Management↗
USGS2019

A process-based model of pre-eruption seismicity patterns and its use for eruption forecasting at dormant stratovolcanoes

Using long-term data sets, the eruptive size, timing and style can typically be successfully forecast for dormant volcanoes using current monitoring data and knowledge of precursory eruptive patterns. The USAID-USGS Volcano Disaster Assistance Program (VDAP) utilizes seismic data over multiple eruption cycles and across volcano types to successfully forecast eruption size, style and onset times, as well as changes within ongoing eruptions. From millions of seismic event observations, we show that seismic data, a proxy for rate-dependent strain changes in the magmatic system, combined with a process-based conceptual geologic model enables eruption forecasting, especially for stratovolcanoes dormant >20 years. We show that this model often works for some open systems, ones that sufficiently reseal to plug the conduit, and also where a deep intrusion occurs after phreatic or phreatomagmatic explosions have begun. This model is divided into four seismicity and geologic stages. We describe each of the four stages of seismicity in detail and how they relate to the ongoing geologic process of that stage: Stage 1. Deep intrusion and seismicity occurring at 10 to 40 + km depth below the volcanic edifice; Stage 2. Distal VT seismicity induced at distances from 2 to >30 km laterally from the summit by magma intruding into and inflating the upper-crustal magma storage region; Stage 3. Vent-clearing seismicity associated with the initial vent creation and clearing phase of eruptive activity. Stage 4. Repetitive event seismicity associated with the final ascent of magma from 2 km to the surface. We present 36 examples of this seismic progression from 26 volcanoes. We believe that this progression generally correlates with the magma flux and the eventual explosivity and is invaluable for forecasting eruptions.

Journal of Volcanology and Geothermal Research↗
USGS2008

Scientific and public responses to the ongoing volcanic crisis at Popocatépetl Volcano, Mexico: Importance of an effective hazards-warning system

Volcanic eruptions and other potentially hazardous natural phenomena occur independently of any human actions. However, such phenomena can cause disasters when a society fails to foresee the hazardous manifestations and adopt adequate measures to reduce its vulnerability. One of the causes of such a failure is the lack of a consistent perception of the changing hazards posed by an ongoing eruption, i.e., with members of the scientific community, the Civil Protection authorities and the general public having diverging notions about what is occurring and what may happen. The problem of attaining a perception of risk as uniform as possible in a population measured in millions during an evolving eruption requires searching for communication tools that can describe—as simply as possible—the relations between the level of threat posed by the volcano, and the level of response of the authorities and the public. The hazards-warning system adopted at Popocatépetl Volcano, called the Volcanic Traffic Light Alert System (VTLAS), is a basic communications protocol that translates volcano threat into seven levels of preparedness for the emergency-management authorities, but only three levels of alert for the public (color coded green–yellow–red). The changing status of the volcano threat is represented as the most likely scenarios according to the opinions of an official scientific committee analyzing all available data. The implementation of the VTLAS was intended to reduce the possibility of ambiguous interpretations of intermediate levels by the endangered population. Although the VTLAS is imperfect and has not solved all problems involved in mass communication and decision-making during a volcanic crisis, it marks a significant advance in the management of volcanic crises in Mexico.

Popocatepetl Volcano↗
USGS2019

Using a process-based model of pre-eruptive seismic patterns to forecast evolving eruptive styles at Sinabung Volcano, Indonesia

Most volcanoes worldwide are not monitored in real-time; for those that are, patterns of pre-eruptive earthquakes coupled with conceptual models of magma ascent enable short-term forecasting of eruption onset. Basic event locations, characterization of background seismicity, and recognition of changes in earthquake types and energy release are most important to successful eruption forecasting. During renewed activity at Sinabung volcano, Indonesia, this approach was used by the Center for Volcanology and Geological Hazards Mitigation (CVGHM) and the USGS Volcano Disaster Assistance Program to forecast eruption onset, identify changes in eruptive styles and raise or lower alert levels and extend or contract evacuation zones. After > 400 years of quiescence, Sinabung began erupting in August 2010. The volcano was unmonitored at the onset of these eruptions, which were phreatic, but soon after a monitoring network was installed by CVGHM. Increasing swarms of high-frequency volcano tectonic (VT) earthquakes were used to forecast continuing phreatic eruptions. Volcanic activity decreased in mid-September 2010, while additional intrusions at depth (inferred from continued distal VT swarms) continued through September 2013, when explosive phreatic eruptions recurred. Explosive eruptions were forecast based on increases in real-time seismic amplitude measurement (RSAM) and VT seismicity. Seismicity changed markedly in late November and early December 2013 with the occurrence of deep earthquakes and an overall transition from low-frequency (LF) dominated and irregular (in time and magnitude) earthquakes to more regular LF and hybrid seismicity – a transition that accompanied the continued rise, eventual emergence and growth of a lava dome in the summit crater. This lava dome was first observed on 18 December. In late December 2013 to early January 2014, the eruptive style changed again as additional ascending magma deformed the summit and the dome grew beyond the capacity of the summit crater, resulting in the en masse collapse of the lava dome (2 Mm3) on 11 January and the largest pyroclastic flow to date. The collapse was forecast on the basis of a several order of magnitude increase in RSAM, continued strong distal VT seismicity, an increase in proximal seismicity, and large-scale observed deformation of the summit area. Similarly, a later collapse of a second summit lava dome on 1 February 2014 was forecast on the basis of increased distal seismicity. Here, we demonstrate how a process-based volcano seismicity model was used in combination with real-time data to forecast the time and magnitude of eruptions, as well as changes in eruption style.

Sinabung Volcano↗
USGS2019

Mapping cropland extent of Southeast and Northeast Asia using multi-year time-series Landsat 30-m data using Random Forest classifier on Google Earth Engine

Cropland extent maps are useful components for assessing food security. Ideally, such products are a useful addition to countrywide agricultural statistics since they are not politically biased and can be used to calculate cropland area for any spatial unit from an individual farm to various administrative unites (e.g., state, county, district) within and across nations, which in turn can be used to estimate agricultural productivity as well as degree of disturbance on food security from natural disasters and political conflict. However, existing cropland extent maps over large areas (e.g., Country, region, continent, world) are derived from coarse resolution imagery (250 m to 1 km pixels) and have many limitations such as missing fragmented and\or small farms with mixed signatures from different crop types and\or farming practices that can be, confused with other land cover. As a result, the coarse resolution maps have limited useflness in areas where fields are small (<1 ha), such as in Southeast Asia. Furthermore, coarse resolution cropland maps have known uncertainties in both geo-precision of cropland location as well as accuracies of the product. To overcome these limitations, this research was conducted using multi-date, multi-year 30-m Landsat time-series data for 3 years chosen from 2013 to 2016 for all Southeast and Northeast Asian Countries (SNACs), which included 7 refined agro-ecological zones (RAEZ) and 12 countries (Indonesia, Thailand, Myanmar, Vietnam, Malaysia, Philippines, Cambodia, Japan, North Korea, Laos, South Korea, and Brunei). The 30-m (1 pixel = 0.09 ha) data from Landsat 8 Operational Land Imager (OLI) and Landsat 7 Enhanced Thematic Mapper (ETM+) were used in the study. Ten Landsat bands were used in the analysis (blue, green, red, NIR, SWIR1, SWIR2, Thermal, NDVI, NDWI, LSWI) along with additional layers of standard deviation of these 10 bands across 1 year, and global digital elevation model (GDEM)-derived slope and elevation bands. To reduce the impact of clouds, the Landsat imagery was time-composited over four time-periods (Period 1: January- April, Period 2: May-August, and Period 3: September-December) over 3-years. Period 4 was the standard deviation of all 10 bands taken over all images acquired during the 2015 calendar year. These four period composites, totaling 42 band data-cube, were generated for each of the 7 RAEZs. The reference training data (N = 7849) generated for the 7 RAEZ using sub-meter to 5-m very high spatial resolution imagery (VHRI) helped generate the knowledge-base to separate croplands from non-croplands. This knowledge-base was used to code and run a pixel-based random forest (RF) supervised machine learning algorithm on the Google Earth Engine (GEE) cloud computing environment to separate croplands from non-croplands. The resulting cropland extent products were evaluated using an independent reference validation dataset (N = 1750) in each of the 7 RAEZs as well as for the entire SNAC area. For the entire SNAC area, the overall accuracy was 88.1% with a producer’s accuracy of 81.6% (errors of omissions = 18.4%) and user’s accuracy of 76.7% (errors of commissions = 23.3%). For each of the 7 RAEZs overall accuracies varied from 83.2 to 96.4%. Cropland areas calculated for the 12 countries were compared with country areas reported by the United Nations Food and Agriculture Organization and other national cropland statistics resulting in an R 2 value of 0.93. The cropland areas of provinces were compared with the province statistics that showed an R 2 = 0.95 for South Korea and R 2 = 0.94 for Thailand. The cropland products are made available on an interactive viewer at www.croplands.org and for download at National Aeronautics and Space Administration’s (NASA) Land Processes Distributed Active Archive Center (LP DAAC): https://lpdaac.usgs.gov/node/1281 .

International Journal of Applied Earth Observation↗