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At least 451 records · Page 25Linked to original sources
USGS2011

Rainfall intensity-duration thresholds for postfire debris-flow emergency-response planning

Following wildfires, emergency-response and public-safety agencies can be faced with evacuation and resource-deployment decisions well in advance of coming winter storms and during storms themselves. Information critical to these decisions is provided for recently burned areas in the San Gabriel Mountains of southern California. A compilation of information on the hydrologic response to winter storms from recently burned areas in southern California steeplands is used to develop a system for classifying magnitudes of hydrologic response. The four-class system describes combinations of reported volumes of individual debris flows, consequences of debris flows and floods in an urban setting, and spatial extents of the hydrologic response. The range of rainfall conditions associated with different magnitude classes is defined by integrating local rainfall data with the response magnitude information. Magnitude I events can be expected when within-storm rainfall accumulations (A) of given durations (D) fall above the threshold A = 0.4D0.5 and below A = 0.5D0.6 for durations greater than 1 h. Magnitude II events will be generated in response to rainfall accumulations and durations between A = 0.4D0.5 and A = 0.9D0.5 for durations less than 1 h, and between A = 0.5D0.6 and A = 0.9D0.5 or durations greater than 1 h. Magnitude III events can be expected in response to rainfall conditions above the threshold A = 0.9D0.5. Rainfall threshold-magnitude relations are linked with potential emergency-response actions as an emergency-response decision chart, which leads a user through steps to determine potential event magnitudes and identify possible evacuation and resource-deployment levels. Use of this information in planning and response decision-making process could result in increased safety for both the public and emergency responders. ?? 2011 US Government.

Natural Hazards↗
USGS2011

Wildfire impacts on the processes that generate debris flows in burned watersheds

E very year, and in many countries worldwide, wildfires cause significant damage and economic losses due to both the direct effects of the fires and the subsequent accelerated runoff, erosion, and debris flow. Wildfires can have profound effects on the hydrologic response of watersheds by changing the infiltration characteristics and erodibility of the soil, which leads to decreased rainfall infiltration, significantly increased overland flow and runoff in channels, and movement of soil. Debris-flow activity is among the most destructive consequences of these changes, often causing extensive damage to human infrastructure. Data from the Mediterranean area and Western United States of America help identify the primary processes that result in debris flows in recently burned areas. Two primary processes for the initiation of fire-related debris flows have been so far identified: (1) runoff-dominated erosion by surface overland flow; and (2) infiltration-triggered failure and mobilization of a discrete landslide mass. The first process is frequently documented immediately post-fire and leads to the generation of debris flows through progressive bulking of storm runoff with sediment eroded from the hillslopes and channels. As sediment is incorporated into water, runoff can convert to debris flow. The conversion to debris flow may be observed at a position within a drainage network that appears to be controlled by threshold values of upslope contributing area and its gradient. At these locations, sufficient eroded material has been incorporated, relative to the volume of contributing surface runoff, to generate debris flows. Debris flows have also been generated from burned basins in response to increased runoff by water cascading over a steep, bedrock cliff, and incorporating material from readily erodible colluvium or channel bed. Post-fire debris flows have also been generated by infiltration-triggered landslide failures which then mobilize into debris flows. However, only 12% of documented cases exhibited this process. When they do occur, the landslide failures range in thickness from a few tens of centimeters to more than 6 m, and generally involve the soil and colluvium-mantled hillslopes. Surficial landslide failures in burned areas most frequently occur in response to prolonged periods of storm rainfall, or prolonged rainfall in combination with rapid snowmelt or rain-on-snow events.

Natural Hazards↗
USGS2011

Inland fields of dispersed cobbles and boulders as evidence for a tsunami on Anegada, British Virgin Islands

Marine overwash from the north a few centuries ago transported hundreds of angular cobbles and boulders tens to hundreds of meters southward from limestone outcrops in the interior of Anegada, 140 km east–northeast of Puerto Rico. We examined two of several cobble and boulder fields as part of an effort to interpret whether the overwash resulted from a tsunami or a storm in a location where both events are known to occur. One of the cobble and boulder field extends 200 m southward from limestone outcrops that are 300 m inland from the island’s north shore. The other field extends 100 m southward from a limestone knoll located 800 m from the nearest shore. In the two fields, we measured the size, orientation, and spatial distribution of a total of 161 clasts and determined their stratigraphic positions with respect to an overwash sand and shell sheet deposit. In both fields, we found the spacing between clasts increased southward and that clast long-axis orientations are consistent with a transport trending north–south. Almost half the clasts are partially buried in a landward thinning and fining overwash sand and none were found embedded in the shelly mud of a pre-overwash marine pond. The two cobble and boulder fields resemble modern tsunami deposits in which dispersed clasts extend inland as a single layer. The fields contrast with coarse clast storm deposits that often form wedge-shaped shore-parallel ridges. These comparisons suggest that the overwash resulted from a tsunami and not from a storm.

Natural Hazards↗
USGS2011

Anisotropic path modeling to assess pedestrian-evacuation potential from Cascadia-related tsunamis in the US Pacific Northwest

Recent disasters highlight the threat that tsunamis pose to coastal communities. When developing tsunami-education efforts and vertical-evacuation strategies, emergency managers need to understand how much time it could take for a coastal population to reach higher ground before tsunami waves arrive. To improve efforts to model pedestrian evacuations from tsunamis, we examine the sensitivity of least-cost-distance models to variations in modeling approaches, data resolutions, and travel-rate assumptions. We base our observations on the assumption that an anisotropic approach that uses path-distance algorithms and accounts for variations in land cover and directionality in slope is the most realistic of an actual evacuation landscape. We focus our efforts on the Long Beach Peninsula in Washington (USA), where a substantial residential and tourist population is threatened by near-field tsunamis related to a potential Cascadia subduction zone earthquake. Results indicate thousands of people are located in areas where evacuations to higher ground will be difficult before arrival of the first tsunami wave. Deviations from anisotropic modeling assumptions substantially influence the amount of time likely needed to reach higher ground. Across the entire study, changes in resolution of elevation data has a greater impact on calculated travel times than changes in land-cover resolution. In particular areas, land-cover resolution had a substantial impact when travel-inhibiting waterways were not reflected in small-scale data. Changes in travel-speed parameters had a substantial impact also, suggesting the importance of public-health campaigns as a tsunami risk-reduction strategy.

Washington↗
USGS2012

Spatial aspects of building and population exposure data and their implications for global earthquake exposure modeling

This paper discusses spatial aspects of the global exposure dataset and mapping needs for earthquake risk assessment. We discuss this in the context of development of a Global Exposure Database for the Global Earthquake Model (GED4GEM), which requires compilation of a multi-scale inventory of assets at risk, for example, buildings, populations, and economic exposure. After defining the relevant spatial and geographic scales of interest, different procedures are proposed to disaggregate coarse-resolution data, to map them, and if necessary to infer missing data by using proxies. We discuss the advantages and limitations of these methodologies and detail the potentials of utilizing remote-sensing data. The latter is used especially to homogenize an existing coarser dataset and, where possible, replace it with detailed information extracted from remote sensing using the built-up indicators for different environments. Present research shows that the spatial aspects of earthquake risk computation are tightly connected with the availability of datasets of the resolution necessary for producing sufficiently detailed exposure. The global exposure database designed by the GED4GEM project is able to manage datasets and queries of multiple spatial scales.

Natural Hazards↗
USGS2014

Tsunami impact to Washington and northern Oregon from segment ruptures on the southern Cascadia subduction zone

This paper explores the size and arrival of tsunamis in Oregon and Washington from the most likely partial ruptures of the Cascadia subduction zone (CSZ) in order to determine (1) how quickly tsunami height declines away from sources, (2) evacuation time before significant inundation, and (3) extent of felt shaking that would trigger evacuation. According to interpretations of offshore turbidite deposits, the most frequent partial ruptures are of the southern CSZ. Combined recurrence of ruptures extending ~490 km from Cape Mendocino, California, to Waldport, Oregon (segment C) and ~320 km from Cape Mendocino to Cape Blanco, Oregon (segment D), is ~530 years. This recurrence is similar to frequency of full-margin ruptures on the CSZ inferred from paleoseismic data and to frequency of the largest distant tsunami sources threatening Washington and Oregon, ~M w 9.2 earthquakes from the Gulf of Alaska. Simulated segment C and D ruptures produce relatively low-amplitude tsunamis north of source areas, even for extreme (20 m) peak slip on segment C. More than ~70 km north of segments C and D, the first tsunami arrival at the 10-m water depth has an amplitude of <1.9 m. The largest waves are trapped edge waves with amplitude ≤4.2 m that arrive ≥2 h after the earthquake. MM V–VI shaking could trigger evacuation of educated populaces as far north as Newport, Oregon for segment D events and Grays Harbor, Washington for segment C events. The NOAA and local warning systems will be the only warning at greater distances from sources.

Oregon;Washington↗
USGS2016

Intra-community implications of implementing multiple tsunami-evacuation zones in Alameda, California

Tsunami-evacuation planning in coastal communities is typically based on maximum evacuation zones for a single scenario or a composite of sources; however, this approach may over-evacuate a community and overly disrupt the local economy and strain emergency-service resources. To minimize the potential for future over-evacuations, multiple evacuation zones based on arrival time and inundation extent are being developed for California coastal communities. We use the coastal city of Alameda, California (USA), as a case study to explore population and evacuation implications associated with multiple tsunami-evacuation zones. We use geospatial analyses to estimate the number and type of people in each tsunami-evacuation zone and anisotropic pedestrian evacuation models to estimate pedestrian travel time out of each zone. Results demonstrate that there are tens of thousands of individuals in tsunami-evacuation zones on the two main islands of Alameda, but they will likely have sufficient time to evacuate before wave arrival. Quality of life could be impacted by the high number of government offices, schools, day-care centers, and medical offices in certain evacuation zones and by potentially high population density at one identified safe area after an evacuation. Multi-jurisdictional evacuation planning may be warranted, given that many at-risk individuals may need to evacuate to neighboring jurisdictions. The use of maximum evacuation zones for local tsunami sources may be warranted given the limited amount of available time to confidently recommend smaller zones which would result in fewer evacuees; however, this approach may also result in over-evacuation and the incorrect perception that successful evacuations are unlikely.

California↗
USGS2016

A comparison of observed and predicted ground motions from the 2015 M W 7.8 Gorkha, Nepal, earthquake

We use 21 strong motion recordings from Nepal and India for the 25 April 2015 moment magnitude (M W ) 7.8 Gorkha, Nepal, earthquake together with the extensive macroseismic intensity data set presented by Martin et al. (Seism Res Lett 87:957–962, 2015 ) to analyse the distribution of ground motions at near-field and regional distances. We show that the data are consistent with the instrumental peak ground acceleration (PGA) versus macroseismic intensity relationship developed by Worden et al. (Bull Seism Soc Am 102:204–221, 2012 ), and use this relationship to estimate peak ground acceleration from intensities (PGA EMS ). For nearest-fault distances (R RUP < 200 km), PGA EMS is consistent with the Atkinson and Boore (Bull Seism Soc Am 93:1703–1729, 2003 ) subduction zone ground motion prediction equation (GMPE). At greater distances (R RUP > 200 km), instrumental PGA values are consistent with this GMPE, while PGA EMS is systematically higher. We suggest the latter reflects a duration effect whereby effects of weak shaking are enhanced by long-duration and/or long-period ground motions from a large event at regional distances. We use PGA EMS values within 200 km to investigate the variability of high-frequency ground motions using the Atkinson and Boore (Bull Seism Soc Am 93:1703–1729, 2003 ) GMPE as a baseline. Across the near-field region, PGA EMS is higher by a factor of 2.0–2.5 towards the northern, down-dip edge of the rupture compared to the near-field region nearer to the southern, up-dip edge of the rupture. Inferred deamplification in the deepest part of the Kathmandu valley supports the conclusion that former lake-bed sediments experienced a pervasive nonlinear response during the mainshock (Dixit et al. in Seismol Res Lett 86(6):1533–1539, 2015 ; Rajaure et al. in Tectonophysics, 2016 . Ground motions were significantly amplified in the southern Gangetic basin, but were relatively low in the northern basin. The overall distribution of ground motions and damage during the Gorkha earthquake thus reflects a combination of complex source, path, and site effects. We also present a macroseismic intensity data set and analysis of ground motions for the M W 7.3 Dolakha aftershock on 12 May 2015, which we compare to the Gorkha mainshock and conclude was likely a high stress-drop event.

Gorkha District↗
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↗
USGS2016

Community disruptions and business costs for distant tsunami evacuations using maximum versus scenario-based zones

Well-executed evacuations are key to minimizing loss of life from tsunamis, yet they also disrupt communities and business productivity in the process. Most coastal communities implement evacuations based on a previously delineated maximum-inundation zone that integrates zones from multiple tsunami sources. To support consistent evacuation planning that protects lives but attempts to minimize community disruptions, we explore the implications of scenario-based evacuation procedures and use the California (USA) coastline as our case study. We focus on the land in coastal communities that is in maximum-evacuation zones, but is not expected to be flooded by a tsunami generated by a Chilean earthquake scenario. Results suggest that a scenario-based evacuation could greatly reduce the number of residents and employees that would be advised to evacuate for 24–36 h (178,646 and 159,271 fewer individuals, respectively) and these reductions are concentrated primarily in three counties for this scenario. Private evacuation spending is estimated to be greater than public expenditures for operating shelters in the area of potential over-evacuations ($13 million compared to $1 million for a 1.5-day evacuation). Short-term disruption costs for businesses in the area of potential over-evacuation are approximately $122 million for a 1.5-day evacuation, with one-third of this cost associated with manufacturing, suggesting that some disruption costs may be recouped over time with increased short-term production. There are many businesses and organizations in this area that contain individuals with limited mobility or access and functional needs that may have substantial evacuation challenges. This study demonstrates and discusses the difficulties of tsunami-evacuation decision-making for relatively small to moderate events faced by emergency managers, not only in California but in coastal communities throughout the world.

Natural Hazards↗
USGS2018

ShakeMap-based prediction of earthquake-induced mass movements in Switzerland calibrated on historical observations

In Switzerland, nearly all historical Mw ~ 6 earthquakes have induced damaging landslides, rockslides and snow avalanches that, in some cases, also resulted in damage to infrastructure and loss of lives. We describe the customisation to Swiss conditions of a globally calibrated statistical approach originally developed to rapidly assess earthquake-induced landslide likelihoods worldwide. The probability of occurrence of such earthquake-induced effects is modelled through a set of geospatial susceptibility proxies and peak ground acceleration. The predictive model is tuned to capture the observations from past events and optimised for near-real-time estimates based on USGS-style ShakeMaps routinely produced by the Swiss Seismological Service. Our emphasis is on the use of high-resolution geospatial datasets along with additional local information on ground failure susceptibility. Even if calibrated on historic events with moderate magnitudes, the methodology presented in this paper yields sensible results also for low-magnitude recent events. The model is integrated in the Swiss ShakeMap framework. This study has a high practical relevance to many Swiss ShakeMap stakeholders, especially those managing lifeline systems, and to other global users interested in conducting a similar customisation for their region of interest.

Natural Hazards↗
USGS2019

Predicting surf zone injuries along the Delaware coast using a Bayesian network

Personnel at Beebe Healthcare in Lewes, Delaware, collected surf zone injury (SZI) data for eight summer seasons from 2010 through 2017. Data include, but are not limited to, time of injury, gender, age, and activity. More than 2000 SZI events, including 196 spinal injuries and 6 fatalities, occurred at the five most populated beaches along the 25 miles of Atlantic-fronting coast. SZI are predominantly wave related incidents associated with wading (50.1%), body surfing (18.4%), and body boarding (13.3%). The episodic nature of SZI indicate the importance of linking the environmental conditions and human behavior in the surf zone to predict days with high injury rates. Higher order statistics are necessary to effectively consider all associated factors related to SZI. Two Bayesian networks (BN) were constructed to model SZI and predict changes in injury rate (proportion of injuries to bathers) and injury likelihood (probability of at least one injury occurrence) on an hourly basis. The models incorporate environmental data collected by weather stations, wave gauges, and researcher personnel on the beach. The models include prior (e.g., historic) information to infer relationships between provided parameters. Sensitivity analysis determined the most influential parameters related to injury rates were significant wave height, foreshore slope, and water temperature. Exposure parameters (e.g., air temperature) influenced the number of people in the water, resulting in strong correlation between injury likelihood and the related meteorological conditions (variance reduction > 0.4%). Log likelihood ratio (LLR) scores indicate the network predicts SZI likelihood during any specified hour with more skill than prior predictions with the best performing model improving prediction 69.1% of the time (LLR = 69.1%). An alternative BN predicting injury rate performed worse with the prior probability model out predicting the injury rate network (positive LLR = 36.7%). Issues persist with predicting SZI that have an LLR ≪ -1 (< 5% of 2017 injuries) and occur in conditions different than when most other SZI occur. Better understanding of SZI will improve awareness techniques to both educate beachgoers and assist beach patrol decision making during high risk conditions.

Delaware↗
USGS2021

Would you like to know more? The effect of personalized wildfire risk information and social comparisons on information-seeking behavior in the wildland–urban interface

Private landowners are important actors in landscape-level wildfire risk management. Accordingly, wildfire programs and policy encourage wildland–urban interface homeowners to engage with local organizations to properly mitigate wildfire risk on their parcels. We investigate whether parcel-level wildfire risk assessment data, commonly used to inform community-level planning and resource allocation, can be used to “nudge” homeowners to engage further with a regional wildfire organization. We sent 4564 households in western Colorado a letter that included varying combinations of risk information about their community, their parcels, and their neighbors’ parcels, and we measured follow-up visits to a personalized “Web site”. We find that the effect of providing parcel-specific information depends on baseline conditions: Informing homeowners about their property’s wildfire risk increases information-seeking among homeowners of the highest-risk parcels by about 5 percentage points and reduces information-seeking among homeowners of lower-risk parcels by about 6 percentage points. Parcel-specific information also increases the overall response in the lowest risk communities by more than 10 percentage points. Further, we find evidence of a 6-percentage point increase in response rate associated with receiving a social comparison treatment that signals neighboring properties as being either low or moderate risk on average. These results, especially considered against the 13 percent overall average response rate, offer causal evidence that providing parcel-specific wildfire risk information can influence behavior. As such, we demonstrate the effectiveness of simple outreach in engaging wildland–urban interface homeowners with wildfire risk professionals in ways that leverage existing data.

Natural Hazards↗
USGS2023

Learnings from rapid response efforts to remotely detect landslides triggered by the August 2021 Nippes earthquake and Tropical Storm Grace in Haiti

On August 14, 2021, a Mw 7.2 earthquake struck the Tiburon Peninsula of western Haiti triggering thousands of landslides. Three days after the earthquake on August 17, 2021, Tropical Storm Grace crossed shallow waters offshore of southern Haiti triggering more landslides worsening the situation. In the aftermath of these events, several organizations with disaster response capabilities or programs activated to provide information on the location of landslides to first responders on the ground. Utilizing remote sensing to support rapid response, one organization manually mapped initiation point of landslides and three automatically detected landslides. The 2021 Haiti event also provided a unique opportunity to test different automated landslide detection methods that utilized both SAR and optical data in a rapid response scenario where rapid situational awareness was critical. As the methods used are highly replicable, the main goal of this study is to summarize the landslide rapid response products released by the organizations, detection methods, quantify accuracy and provide guidelines on how some of the shortcomings encountered in this effort might be addressed in the future. To support this validation, a manually mapped polygon-based landslide inventory covering the entire affected area was created and is also released through this effort.

Natural Hazards↗
USGS2024

Deterministic, dynamic model forecasts of storm-driven coastal erosion

The U.S. Atlantic and Gulf of Mexico coasts are vulnerable to storms, which can cause significant erosion of beaches and dunes that protect coastal communities. Real-time forecasts of storm-driven erosion are useful for decision support, but they are limited due to demands for computational resources and uncertainties in dynamic coastal systems and storm forcings. Current methods for coastal change forecasts are based on empirical calculations for wave run-up and conceptual models for erosion, which do not represent sediment transport and morphological change during the storm. However, with continued advancements in high-resolution geospatial data and computational efficiencies, there is an opportunity to apply morphodynamic models for forecasts of beach and dune erosion as a storm approaches the coast. In this study, we implement a forecast system based on a deterministic, dynamic model. The morphodynamic model is initialized with digital elevation models of the most up-to-date conditions and forced with hydrodynamics from wave and circulation model forecasts, and its predictions are categorized based on impact to the primary dune, defined in this study as the first ridge of sand landward of the beach. Results are compared spatially to the observed post-storm topography using changes to dune crest elevations and volumes, and temporally to the predicted total water level at the forecasted moment of dune impact.

Florida, Georgia, South Carolina↗
USGS2025

Factors influencing landslide occurrence in low-relief formerly glaciated landscapes: Landslide inventory and susceptibility analysis in Minnesota, USA

In landscapes recently impacted by continental glaciation, landslides may occur where topographic relief has been generated by the drainage of glacial lakes and ensuing post-glacial fluvial network development into unconsolidated glacially derived sediments and exhumed bedrock. To investigate linkages among environmental variables, post-glacial landscape development, and landslides, we created a landslide inventory of nearly 10,000 landslides in five regions of the formerly glaciated low-relief state of Minnesota, USA. Multivariate logistic regression indicates the importance of slope angle, lithology, and the development of stream valleys to landslide distribution. Areas underlain by fine-grained glaciolacustrine and nearshore deposits that are incised by streams are particularly prone to shallow (<1-2 m depth) landslides. Landslides also occur in a wide range of glacial and fluvial deposits, and as rockfall in layered Paleozoic sedimentary rocks in central and southern Minnesota and Precambrian igneous and sedimentary rocks in northeastern Minnesota. Although no more than 1-2% of the studied regions are susceptible to landslides, they can pose risk to life and safety, damage infrastructure, and impact water quality. The combination of recently generated low-relief steep slopes, extensive unconsolidated sediments, and layered sedimentary bedrock make this formerly glaciated landscape more susceptible to landslides than current national-scale models indicate.

Minnesota↗
USGS2026

Effects of storm surge exceedance value on overwash and inundation forecasts

Hurricane induced sediment transport and flooding can cause catastrophic damage to coastal communities. Forecasts test our understanding of the drivers of sediment transport and flooding, as well as quantify potential storm effects on coastlines. Real-time availability of forecasts allows emergency response and management decisions to be made with additional information. This study analyzed the skill of probabilistic forecasts of overwash and inundation along the Louisiana coastline from back-to-back Hurricanes Laura and Delta in 2020. To test skill, forecasts were compared with observations of mean water level relative to beach elevations and evidence of overwash and inundation identified in post-storm aerial imagery. We found that probabilistic forecasts accurately identified areas where overwash and inundation were likely to occur. In some cases, forecasts also produced a conservative estimation of overwash and inundation. For the first time, we explored the role of exceedance value in probabilistic forecasts of overwash and inundation and found that choice of exceedance value can influence forecasts. Additionally, we found that waves contributed up to 27% of the mean water level and up to 63% of the extreme water level during Hurricanes Laura and Delta.

Louisiana, Texas↗
USGS2019

When the earth doesn’t stop shaking: How experiences over time influenced information needs, communication, and interpretation of aftershock information during the Canterbury Earthquake Sequence, New Zealand

The Canterbury Earthquake Sequence (CES) began with the Darfield earthquake on 4 September 2010. Continual large and small aftershocks since that time have meant communities have cycled through repeated periods of impact, response and recovery. Scientific communication about aftershocks during such a prolonged sequence has faced distinct challenges. We conducted research to better understand aftershock information needs for agencies and the public, and how people interpreted and responded to such information. We found that a wide range of information was needed from basic facts about aftershocks through to more technical information, and in different formats (e.g. maps, tables, graphs, text, analogies). Information needs also evolved throughout the sequence, and differed depending on people’s roles and experiences, and the phase of impact, response and recovery communities were in. Interpretation of aftershock information was influenced by a variety of factors including how understandable and relevant the information was, whether people had prior knowledge or experience of aftershocks, whether the information was personalised or contextualised, emotions and feelings, credibility and trust, and external influences. Given that such a diversity of evolving information is required, it is imperative that geoscientists strategize how to provide such information before a significant earthquake occurs.

Natural Hazards↗