The perceived landfall location of evacuees from Hurricane Gustav

Hurricane evacuations in the United States are costly, chaotic, and sometimes unnecessary. Many coastal residents consider evacuation after viewing a forecasted graphic of where the storm is anticipated to make landfall. During the evacuation process, hurricane tracks commonly deviate from the forecasted landfall track and many evacuees may not pay attention to these track deviations after evacuating. Frequently, a disconnect may occur between the actual landfall track, the official forecasted track, and the perceived track of each individual as they made their evacuation decision. Specifically for evacuees, a shift in track may decrease the hazards associated with a landfalling hurricane since evacuees perceive their threat level to be high at the time of evacuation. Using survey data gathered during the evacuation from Hurricane Gustav (2008) in coastal Louisiana (USA), we calculated a type of Z-score to measure the distance error between each evacuee’s perceived landfall location and the actual landfall location from each evacuee’s home zip code. Results indicate a personal landfall bias in the direction of home zip code for evacuees of three metropolitan regions. Evacuees from the greater New Orleans area displayed the highest error, followed by evacuees from greater Lafayette. Furthermore, we validate the authenticity of the previous results by employing two additional methods of error assessment. A large regional error score might possibly be a predictor of evacuation complacency for a future hurricane of similar magnitude, although there are many other variables that must be considered.     

A GIS-based analysis of constraints on pedestrian tsunami evacuation routes: Cascais case study (Portugal)

Tsunami hazard in coastal areas susceptible to flooding, although reduced (in terms of probability of occurrence), may pose a high risk. Therefore, in these areas, a detailed evacuation planning of the affected population is required as a risk mitigation measure. The knowledge and enforcement of evacuation routes may reduce the population vulnerability, making it more resilient and reducing risk. This paper presents a GIS approach for modelling evacuation routes based on the optimal path search problem, of the graph theory, which is implemented on ArcCasper tool. The methodology proposed considers the elements involved in the evacuation process, the worst credible tsunami inundation scenario (hazard extent and travel time), the number of people that needs to be evacuated in different time scenarios, the safe areas or destination points of the evacuation routes, the roads network characteristics and finally the time available to evacuate. The knowledge of those elements allows predicting some possible outcomes of the evacuation, such as the arrival time of the evacuees to a shelter and the identification of congestion hot spots resulting from the application of a flocking model which simulates the path to be used by evacuees avoiding obstacles. The municipality of Cascais was used to test the methodology proposed in this study. Cascais is one of the largest urban centres located about 25 km west of Lisbon, Portugal, with a high density of infrastructure along the coastline whereby most of the population and economic activities are exposed to a tsunami. The results, presented in the form of maps, allow identifying the optimal evacuation routes as well as the unfeasible routes. This crucial information could be used to the evacuation optimization regarding the location of meeting points and vertical shelters as well as to improve the accessibility of the areas to be evacuated.     

A novel agent-based model for tsunami evacuation simulation and risk assessment

Tsunami evacuation is an effective way to save lives from the near-field tsunami. Realistic evacuation simulation can provide valuable information for accurate evacuation risk assessment and effective evacuation planning. Agent-based modeling is ideal for tsunami evacuation simulation due to its capability of capturing the emergent phenomena and modeling the individual-level interactions among agents and the agents’ interactions with the environment. However, existing models usually neglect or simplify some important factors and/or mechanisms in tsunami evacuation. For example, uncertainties in seismic damages to the transportation network are not probabilistically considered (e.g., by simply removing the damaged links (roads/bridges) from the network). Typically a relatively small population (i.e., evacuees) is considered (due to computational challenges) while neglecting population mobility. These simplifications may lead to inaccurate estimation of evacuation risk. Usually, only single traffic mode (e.g., on foot or by car) is considered, while pedestrian speed adjustment and multi-modal evacuation (e.g., on foot and by car) are not considered concurrently. Also, pedestrian–vehicle interaction is usually neglected in the multi-modal evacuation. To address the above limitations, this study proposes a novel and more realistic agent-based tsunami evacuation model for tsunami evacuation simulation and risk assessment. Uncertainties in seismic damages to all links in the transportation network as well as uncertainties in other evacuation parameters are explicitly modeled and considered. A novel and more realistic multi-modal evacuation model is proposed that explicitly considers the pedestrian–vehicle interaction, walking speed variability, and speed adjustment for both the pedestrian and car according to traffic density. In addition, several different population sizes are used to model population mobility and its impact on tsunami evacuation risk. The proposed model is applied within a simulation-based framework to assess the tsunami evacuation risk assessment for Seaside, Oregon.

     

An agent-based evacuation model for the 2011 Brisbane City-scale riverine flood

In this study, an agent-based model is proposed in order to provide new insights into the policy analysis and strategy assessment of city-scale evacuation management. The proposed model is suitable for assessment of the influence of different departure times and communications among peer evacuees on the number of residents at risk who arrive at official shelters. A case study is applied to build a simulation model for the coastal city of Brisbane in Australia. The Brisbane River catchment experiences regular flooding almost every year; the second severest flood since the twentieth century occurred in 2011. During that event, over 15,000 properties were inundated and around 3600 households evacuated in metropolitan Brisbane alone. Making use of high-performance computing clusters, the evacuation simulation was coupled with results from a validated hydrodynamic model to test a variety of escaping scenarios based on the 2011 flood situation. This case study demonstrates the proposed model’s capacity to represent the dynamic evacuation process and also shows that the model is able to help develop flood emergency plans and evaluate response measures through exploring key elements in a range of scenarios.     

The logistics of household hurricane evacuation

Although there is a substantial amount of research on households’ hurricane evacuation decision making, there is much less research on the logistical issues involved in implementing those evacuations. The limited research on household evacuation logistics has consistently shown that most evacuees stay in the homes of friends and relatives or in commercial facilities rather than in public shelters. However, evacuation logistics—which can be defined as the activities and associated resources needed to reach a safe location and remain there until it is safe to return—encompasses a much broader range of behaviors than this. The present study extends previous research by reporting data on other aspects of evacuation logistics such as departure timing, vehicle use, evacuation routes, travel distance, shelter type, evacuation duration, and evacuation cost. Hurricane Lili evacuation data at the county level are generally consistent with the data from previous hurricanes, but there is notable variation across counties studied here. There were only modest correlations of demographic and geographic variables with the evacuation logistics variables, a result that indicates further research is needed to better understand what happens between the time an evacuation decision is made and the time re-entry is begun. Moreover, research is needed to understand the logistics of evacuation by special populations such as transients and households with disabled members.     

Wildfire evacuations in Canada 1980–2007

Evacuations represent an integral aspect of protecting public safety in locations where intense, fast-spreading forest fires co-occur with human populations. Most Canadian fire management agencies have as their primary objective the protection of people and property, and all fire management agencies in Canada recommend evacuations when public safety is in question. This study provides the first national assessment of wildfire-related evacuations in Canada and documents the loss of homes that coincided with evacuation events. The most striking finding is that despite the intensity and abundance of wildfire in Canada, wildfires have displaced a relatively small number of people. Between 1980 and 2007, the median number of evacuees and home losses per year in Canada were 3,590 and 2, respectively. Evacuees’ homes survived in 99.3% of cases. Patterns of evacuations and home losses reflected the distributions of forests, wildfire, and people across the Canadian landscape. Most evacuations occurred in boreal areas, which have relatively low population densities but among the highest percent annual area burned in Canada. Evacuations were less common in southern parts of the country, where most Canadians reside, but individual wildfires in these areas had significant impacts. Interactions between wildfire and people in Canada exhibited a unique regional pattern, and within the most densely populated regions of the country they can be considered ‘low-probability, high-consequence’ events. This Canadian context is fundamentally different from places such as California, where concentrations of fires and people overlap across large areas and therefore calls for a fundamentally different fire management response.     

Regional differences in cognitive dissonance in evacuation behavior at the time of the 2011 Japan earthquake and tsunami

This paper constructs an evacuation decision-making model that takes cognitive dissonance into consideration. The purpose of this construction is to clarify the psychological mechanism for the evacuation behavior of residents during an emergency, based on Akerlof and Dickens (Akerlof and Dickens Am Econ Rev 72:307–319, 1982) "The economic consequences of cognitive dissonance". Specifically, we empirically explore people’s psychological mechanism (e.g., cognitive dissonance) for evacuation behavior when a tsunami disaster occurs. As a result, we show that the level of anxiety depends on the area where residents live and that the average anxiety of residents is mostly correlated with the level of damage of past disasters, and that it is affected also by the ages of residents. Since the level of anxiety largely affects an individual’s evacuation behavior, this result can indicate for what kinds of people intervention and assistance are required based on the level of anxiety. A high level of anxiety basically promotes evacuation. Since our results show that anxiety is increased by the experience of tsunamis, education having people virtually experience tsunamis may increase evacuation rates efficiently.

     

Evacuees’ reentry concerns and experiences in the aftermath of Hurricane Ike

Managing evacuees’ reentry into their communities after an evacuation can be a major challenge for emergency managers, especially in instances when evacuees return before the official all-clear message. Despite the frequency of post-evacuation reentry into evacuated areas, there have been few studies of this process and the issues returnees expect and experience during the return phase. A survey of evacuees after Hurricane Ike indicates that household compliance with reentry plans was low, with only a minority of returnees (38 %) complying with official reentry plans. An examination of reentry concerns shows that minority ethnicity, lower education, and lower income were associated with higher levels of reentry concerns and, to a lesser extent, with problems experienced after returning. Results also indicate that none of the demographic variables correlated significantly with compliance with official reentry plans and only higher income predicted later entry. However, concerns about reentry traffic predicted earlier reentry and concern about physical risk was related to reentry plan compliance. This study provides insight into the concerns that motivate households’ reentry decisions and can inform the creation of return strategies that account for people’s concerns about their hurricane-impacted communities.     

Pre-landfall evacuee perception of the meteorological hazards associated with Hurricane Gustav

In this study, evacuees from the path of Hurricane Gustav were surveyed to determine which meteorological hazards most influenced their decision to leave. Surveys were conducted along two major evacuation routes on August 30 and 31, 2008, to collect time-sensitive data on individual evacuation decisions related to the meteorological hazards from Hurricane Gustav. The regions of New Orleans, Houma, and Lafayette were represented most frequently, as determined by zip code data collected from the surveys. Responses were evaluated first by meteorological hazard for the entire dataset and then by three-digit zip code region. Overall, storm surge was the most important meteorological variable, followed by the size of the storm, wind, rain, and tornadoes. When separated into three-digit zip code regions, analyses revealed evacuees from in and around New Orleans were driven to evacuate as a result of the perceived threat from storm surge and storm size; residents in the Houma, Louisiana region were motivated to leave due to the threat from storm surge; and Lafayette and the surrounding areas were most-concerned with the threats posed by hurricane-force winds. Given the forecast track and intensity, survey respondents understood the meteorological hazards from Gustav and were motivated to leave based on personal evaluations of risk associated with the storm.     

A hurricane evacuation management decision support system (EMDSS)

This article describes the challenges confronting local authorities who must decide if and when to initiate evacuations from tropical cyclones. This problem can be decomposed into the behavior of the hurricane that is relevant to evacuation and the behavior of evacuees that is relevant to the hurricane. The uncertain behavior of these two systems can be modeled in an evacuation management decision support system (EMDSS). The hurricane EMDSS described here displays information about the minimum, most, and maximum probable evacuation time estimates (ETEs) in comparison to the earliest, most, and latest probable estimated times of arrival (ETAs) for storm conditions. In addition, EMDSS calculates the cost of false positive (the economic cost of an evacuation) and false negative (lives lost in a late evacuation) decision errors. EMDSS is being used in experiments to assess different information displays, team compositions, community characteristics, and hurricane scenarios. In addition, it will be used in training and actual hurricane operations. Finally, definition of the program’s requirements has identified further research needed to build a better empirical base for its input data.     

Spatial and temporal variations in the incidence of dust events over Iran

Large near-field tsunamis pose a significant threat to the Canadian West Coast due to its proximity to the circum-Pacific belt where a significant tsunami-inducing earthquake event from the Cascadia subduction zone is expected. This study investigated the risks associated with such an event in terms of pedestrian evacuation needs and plans for the Town of Tofino, a small community located on the West Coast of Vancouver Island. The population-at-risk within the hazard zone and its ability to evacuate to safety is evaluated using anisotropic path-distance modelling. Mitigation measures, such as vertical evacuation buildings, are quantitatively evaluated. Site-specific inundation modelling was not performed as part of this study; tsunami hazard and safe zones were computed using a range of run-ups varying between 3 and 25 m. It was established that up to 80% of the population is within the maximum hazard zone considered. This evacuation modelling exercise indicates that a maximum of 13% of the population would have insufficient time to reach safety when using a mobility-impaired ambulatory speed. The use of three vertical evacuation buildings can reduce the risk of losing population in this category by 99%. Although some conservative assumptions were used (vertical datum at higher high water, reductions in safe zones by generalization process and mobility-impaired evacuation speeds), the evacuation potential is likely overestimated due to the coarseness of the topographic data used in the evacuation modelling and from an overestimated first wave arrival time. This is the first Canadian study which used anisotropic evacuation modelling to evaluate the vulnerability of a Canadian community to tsunami inundation.

     

WUIVAC: a wildland-urban interface evacuation trigger model applied in strategic wildfire scenarios

An evacuation trigger is a point on the landscape that, once crossed by a wildfire, triggers an evacuation for a community. The Wildland-Urban Interface Evacuation (WUIVAC) model can be used to create evacuation trigger buffers around a community using fuels, weather, and topographic inputs. A strategic, community-scale application of WUIVAC for the town of Julian, California was investigated. Eight years of wind measurements were used to determine the worst-case (strongest) winds in 16 directions. Surface fire rate of spread was used to calculate evacuation trigger buffers for the communities of Julian and nearby Whispering Pines, and for three potential evacuation routes. Multiple trigger buffers were combined to create fire planning areas, and trigger buffers that predict the closure of all evacuation routes were explored. WUIVAC trigger buffers offer several potential benefits for strategic evacuation planning, including determination of when to evacuate and locating potential evacuation routes.     

Simulation-based optimization of emergency evacuation strategy in ultra-high-rise buildings

Emergency evacuation in high-rise buildings is a crucial problem. The evacuation strategy of using stairs and evacuation elevators should be optimized. In this paper, simulation-based optimization method is used to optimize the evacuation strategy of using stairs and elevators in high-rise buildings. The stair simulation is based on a cellular automata model, and several typical pedestrians’ walk preferences are considered in this model. In the simulation, evacuation elevators can arrive at the refuge floors, and the scheduling of the elevators is optimized based on the GA algorithm. The simulation-based optimization is designed as a two-level problem: The upper level is a strategy level; the lower level is an operation level. In the study case, the evacuation strategy of a 100-floor ultra-high-rise office building is optimized. We find that if evacuees follow the traditional stair evacuation strategy, the evacuation time is 42.6 min. After optimization, the evacuation time of optimal strategy by using both stairs and elevators is 25.1 min. Compared with the traditional stair evacuation strategy, the efficiency of evacuation is improved by 41.1%. It is also found that the merging behavior in stairwells will decrease the velocity of the pedestrian flow. Stairs are still the main egress, and evacuation elevators are an assistant egress during high-rise building evacuation.     

Risk analysis of tripping accidents of power grid caused by typical natural hazards based on FTA-BN model

As the scale of the power grid becomes larger, the requirements for transmission reliability are getting higher. Due to the large geographical span and the harsh environment of the power transmission line, it has become the most severely affected equipment of the power grid by natural factors. However, the quantitative assessment of transmission line tripping accidents caused by multiple natural hazards has rarely been investigated. In this study, a risk analysis method to probabilistically analyze the tripping accidents of power transmission lines caused by wildfire, lightning, strong wind and ice storm was proposed. The analysis process consists of comprehensively identifying the risk of tripping accidents based on fault tree analysis and dynamically performing the predictive analysis of tripping accident evolution process in transmission line from causes to consequences based on Bayesian network. Critical risk evolution paths corresponding to four natural hazards are determined through a 72-node BN. The source risks of the four critical risk evolution paths are artificial ignition source from the wildfire path, aging from the lightning path, thoughtless of surrounding environment from the strong wind path and wind effect from the ice storm path. The countermeasures of tripping accidents are derived through the source risks and synergy between risks in three scenario analysis. This study is expected to examine the key challenges of risk management in power grid tripping accidents, which provides technical supports for accident preventing, handling and recovering of tripping accidents of the power transmission line according to “scenario–response”-based hazard response strategy.

     

Fusain in Carboniferous shallow marine sediments, Donegal, Ireland: the sedimentological effects of wildfire

Evidence from fusain deposits in Lower Carboniferous rocks of western Ireland indicates that a catastrophic wildfire destroyed thousands of square kilometres of Carboniferous ‘forest’. In addition to yielding large quantities of charcoal, this wildfire event resulted in increased surface water runoff which affected sedimentation in an adjacent estuarine environment where the fusain is now preserved. This is the oldest documented evidence for a catastrophic palaeowildfire and a clear example of the sedimentological effects of large-scale fires. The Lower Carboniferous (Visean) rocks in the Largymore Syncline of western Donegal, Ireland, are shallow marine sandstones, mudstones and limestones. The Upper Shalwy Beds are mudstones and cross-bedded sandstones which show bi-polar cross-stratification and mud drapes on cross-bed foresets indicating deposition in a tidal environment, probably a large estuary. In three coastal exposures a bed containing up to 20% fusain is found at the same stratigraphic horizon. The fusain is interpreted as fossil charcoal produced by palaeowildfire in a land area to the north-west. The volume of fusain present in the unit can be estimated and by comparison with charcoal production in modern wildfires it has been calculated that around 95 000 km² (more than the present land area of Ireland) was burnt. Along with the fusain, other effects of the wildfire can be seen in the deposits, which are poorly sorted compared to the rest of the Upper Shalwy Beds and are characterized by inclined heterolithic stratification produced by the draping of underlying bedforms. These features are considered to be due to a considerably increased sediment load in the estuary, resulting from enhanced surface runoff and soil erosion due to the wildfire.     

Characteristics,mechanisms, and post-disaster lessons of the delayed semi-diagenetic landslide in Hanyuan,Sichuan, China

Landslides following rainfall occurrence are a widespread phenomenon. The neglect of this phenomenon leads to serious loss of life when disasters occur. At 03:45 (GMT?+?8) on August 21, 2020, a semi-diagenetic landslide occurred in Zhonghai Village, Hanyuan County, China, which occurred 42 h after earlier rainfall. Nine people privately returned to their homes after evacuation of the dangerous area. In this disaster, eight people were lost and one injured. This study explores the failure characteristics, inducement, and mechanisms of the landslide via field investigations, resident interviews, multi-temporal images, field drilling, and geotechnical tests. Hydrological numerical calculations were also performed to uncover the seepage and transfer processes of the groundwater in the slope. Finally, problems in the current community early warning system were analyzed and corresponding suggestions put forward. The results show that the maximum sliding depth of the landslide was 27.5 m, the total area was 80,000 m², and the sliding volume was about 58,0000 m³, making it a medium-sized deep landslide. In addition to the vertical seepage of rainfall in the landslide area, the downward movement of rainfall in the back and upper catchment areas along the silt sand strata also affected the stability of the landslide. More needs to be done to make the population aware of this lag phenomenon to achieve scientific disaster reduction. This study not only provides a case study of a lagging semi-diagenetic landslide, but also provides insight into hydrological boundary determination and landslide early warning system construction.

     

Linking wildfire effects on soil and water chemistry of the Marão River watershed,Portugal, and biomass changes detected from Landsat imagery

Wildfires transform the landscape, leading to changes in surface cover and, potentially, in water quality. The purpose of this study was to assess changes in the chemical composition of soils and surface water as a result of a wildfire that burned in 2006 in the Marão Mountains, NE Portugal, by comparing pre- and post-fire hydrochemical data and burned/unburned soil data, and to examine the recovery of vegetation over time using Landsat TM imagery. Studies that have access to pre-fire data are rare and even fewer studies document changes in biomass as a result of fire and during the postfire recovery period. Samples of ash, soil and water, from within and outside the burned area, were collected 5 months, and one year after the fire, for chemical analyses. Landsat TM Images were downloaded and transformed into a vegetation index, in order to analyze landcover dynamics and to calculate biomass. The wildfire effects on the Marão River water quality, resulted in an increase in the total mineralization of water. Five months after the wildfire the electrical conductivity (E.C.) at the mainstem was about 56% higher than pre-fire values (E.C. increased from 25 to 39 μS/cm) and still higher one year after (36 μS/cm). Cations of Ca, Na, Mg and Mn showed the greatest increase. This increase was probably triggered by the movement of ash to the watercourses. This disturbance had already attenuated one year after wildfire to values closer to pre-fire data except for manganese. Manganese had anomalous concentrations in the water within the burned area. The concentration of Mn in ash samples reached values up to 5 times more than values found in underlying soils. One year after the wildfire, almost all the burned area had recovered with herbaceous vegetation and patches of shrub vegetation. The wildfire burned 1194.7 dry tons of biomass which means, on average, 4.9 dry ton/ha. Based on the mass of burned biomass, we calculated approximately 350 g/ha of Mn were released as a result of the fire. We suggest that this type of calculation can be conducted before a fire to help resource managers understand worst-case scenarios for changes in water quality that have the potential to affect aquatic biotic and the suitability of water for drinking water purposes and agriculture.     

Computer-based Model for Flood Evacuation Emergency Planning

A computerized simulation model for capturing human behavior during flood emergency evacuation is developed using a system dynamics approach. It simulates the acceptance of evacuation orders by the residents of the area under threat; number of families in the process of evacuation; and time required for all evacuees to reach safety. The model is conceptualized around the flooding conditions (physical and management) and the main set of social and mental factors that determine human behavior before and during the flood evacuation. The number of families under the flood threat, population in the process of evacuation, inundation of refuge routes, flood conditions (precipitation, river elevation, etc.), and different flood warnings and evacuation orders related variables are among the large set of variables included in the model. They are linked to the concern that leads to the danger recognition, which triggers evacuation decisions that determine the number of people being evacuated. The main purpose of the model is to assess the effectiveness of different flood emergency management procedures. Each procedure consists of the choice of flood warning method, warning consistency, timing of evacuation order, coherence of the community, upstream flooding conditions, and set of weights assigned to different warning distribution methods. Model use and effectiveness are tested through the evaluation of the effectiveness of different flood evacuation emergency options in the Red River Basin, Canada.     

Time to leave: an analysis of travel times during the approach and landfall of Hurricane Irma

Hurricane Irma caused widespread evacuation activity across Florida and some of its neighboring states in September of 2017. The researchers gathered estimated travel times from the Google Distance Matrix API over about a month to identify and analyze evacuation periods on roads in Florida, Georgia, and South Carolina during this time. Travel time data were mathematically adjusted to show more realistic estimations. Both sets of travel times were then graphed, with the assumption that elevated travel times prior to and during hurricane landfall were indicative of evacuation activity. The study generally corroborated the well-established daytime evacuation preference. However, not all evacuation periods followed the daytime travel preference, and at least one nighttime evacuation may have been caused by flooding. In another case, later elevated travel coincided with significant power loss. Finally, the Florida data suggest that most of the evacuation traffic departed before local jurisdictions’ recommended evacuation start times.