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Fire
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Wildfire Hazard and Risk Assessment
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Wildfire Hazard and Risk Assessment

A special issue of Fire (ISSN 2571-6255).

Deadline for manuscript submissions: closed (31 January 2022) | Viewed by 87439

Printed Edition Available!
A printed edition of this Special Issue is available here.

Special Issue Editor

Dr. James R. Meldrum

E-Mail Website
Guest Editor
Fort Collins Science Center, U.S. Geological Survey, Fort Collins, CO 80526, USA
Interests: environmental economics; ecosystem services; wildfire; natural hazards; water resources

Special Issue Information

Dear Colleagues,

Wildfire risk can be conceived of as the combination of wildfire hazard (often described by likelihood and intensity) with the susceptibility of people, property, or other valued resources to that hazard. Reflecting the seriousness of wildfire risk to communities around the world, substantial resources are devoted to assessing wildfire hazard and risk. Wildfire hazard and risk assessments are conducted at a wide range of scales, from localized to nationwide, and are often intended to communicate and support decision making about risks, including the prioritization of scarce resources. Improvements in the underlying science of wildfire hazard and risk assessment and in the development, communication, and application of these assessments can support effective decisions about all aspects of societal adaptation to wildfire, including decisions about prevention, mitigation, and suppression of wildfire risks.

To support such efforts, we are soliciting contributions to a Special Issue in the journal Fire on wildfire hazard and risk assessment. We invite contributions on any aspect of wildfire hazard or risk assessment, including but not limited to:

  • Fire behavior modeling and simulation;
  • Assessment of the risks of wildfire to communities, ecosystems, critical infrastructure, and other valued resources;
  • Social aspects of wildfire risk, including socioeconomic concerns and vulnerability;
  • Case studies on the development of wildfire risk assessment products with users;
  • The role of wildfire hazard and/or risk assessment in decision making about wildfire under uncertainty;
  • Relationships between wildfire and other hazards, such as flooding and debris flows;
  • The effect of scale on wildfire hazard and risk assessment;
  • Innovative uses of wildfire hazard and risk assessment in planning for extreme events.

Dr. James R. Meldrum
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Fire is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • Fire
  • Hazards
  • Fire behavior modeling
  • Risk assessment
  • Decision making
  • Wildfire risk to communities
  • Wildfire prevention and mitigation

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Further information on MDPI's Special Issue polices can be found here.

Published Papers (10 papers)

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Research

23 pages, 4774 KiB  
Article
Predicting Wildfire Fuels and Hazard in a Central European Temperate Forest Using Active and Passive Remote Sensing
by Johannes Heisig, Edward Olson and Edzer Pebesma
Fire 2022, 5(1), 29; https://doi.org/10.3390/fire5010029 - 20 Feb 2022
Cited by 24 | Viewed by 6600
Abstract
Climate change causes more extreme droughts and heat waves in Central Europe, affecting vegetative fuels and altering the local fire regime. Wildfire is projected to expand into the temperate zone, a region traditionally not concerned by fire. To mitigate this new threat, local [...] Read more.
Climate change causes more extreme droughts and heat waves in Central Europe, affecting vegetative fuels and altering the local fire regime. Wildfire is projected to expand into the temperate zone, a region traditionally not concerned by fire. To mitigate this new threat, local forest management will require spatial fire hazard information. We present a holistic and comprehensible workflow for quantifying fuels and wildfire hazard through fire spread simulations. Surface and canopy fuels characteristics were sampled in a small managed temperate forest in Northern Germany. Custom fuel models were created for each dominant species (Pinus sylvestris, Fagus sylvatica, and Quercus rubra). Canopy cover, canopy height, and crown base height were directly derived from airborne LiDAR point clouds. Surface fuel types and crown bulk density (CBD) were predicted using random forest and ridge regression, respectively. Modeling was supported by 119 predictors extracted from LiDAR, Sentinel-1, and Sentinel-2 data. We simulated fire spread from random ignitions, considering eight environmental scenarios to calculate fire behavior and hazard. Fuel type classification scored an overall accuracy of 0.971 (Kappa = 0.967), whereas CBD regression performed notably weaker (RMSE = 0.069; R2 = 0.73). Higher fire hazard was identified for strong winds, low fuel moisture, and on slopes. Fires burned fastest and most frequently on slopes in large homogeneous pine stands. These should be the focus of preventive management actions. Full article
(This article belongs to the Special Issue Wildfire Hazard and Risk Assessment)
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21 pages, 1980 KiB  
Article
Parcel-Level Risk Affects Wildfire Outcomes: Insights from Pre-Fire Rapid Assessment Data for Homes Destroyed in 2020 East Troublesome Fire
by James R. Meldrum, Christopher M. Barth, Julia B. Goolsby, Schelly K. Olson, Adam C. Gosey, James (Brad) White, Hannah Brenkert-Smith, Patricia A. Champ and Jamie Gomez
Fire 2022, 5(1), 24; https://doi.org/10.3390/fire5010024 - 12 Feb 2022
Cited by 11 | Viewed by 5596
Abstract
Parcel-level risk (PLR) describes how wildfire risk varies from home to home based on characteristics that relate to likely fire behavior, the susceptibility of homes to fire, and the ability of firefighters to safely access properties. Here, we describe the WiRē Rapid Assessment [...] Read more.
Parcel-level risk (PLR) describes how wildfire risk varies from home to home based on characteristics that relate to likely fire behavior, the susceptibility of homes to fire, and the ability of firefighters to safely access properties. Here, we describe the WiRē Rapid Assessment (RA), a parcel-level rapid wildfire risk assessment tool designed to evaluate PLR with a small set of measures for all homes in a community. We investigate the relationship between 2019 WiRē RA data collected in the Columbine Lake community in Grand County, Colorado, and whether assessed homes were destroyed in the 2020 East Troublesome Fire. We find that the overall parcel-level risk scores, as well as many individual attributes, relate to the chance that a home was destroyed. We also find strong evidence of risk spillovers across neighboring properties. The results demonstrate that even coarsely measured RA data capture meaningful differences in wildfire risk across a community. The findings also demonstrate the importance of accounting for multiple aspects of PLR, including both hazards and susceptibility, when assessing the risk of wildfire to homes and communities. Finally, the results underscore that relatively small actions by residents before a fire can influence wildfire outcomes. Full article
(This article belongs to the Special Issue Wildfire Hazard and Risk Assessment)
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24 pages, 13206 KiB  
Article
Assessing Potential Safety Zone Suitability Using a New Online Mapping Tool
by Michael J. Campbell, Philip E. Dennison, Matthew P. Thompson and Bret W. Butler
Fire 2022, 5(1), 5; https://doi.org/10.3390/fire5010005 - 7 Jan 2022
Cited by 10 | Viewed by 5410
Abstract
Safety zones (SZs) are critical tools that can be used by wildland firefighters to avoid injury or fatality when engaging a fire. Effective SZs provide safe separation distance (SSD) from surrounding flames, ensuring that a fire’s heat cannot cause burn injury to firefighters [...] Read more.
Safety zones (SZs) are critical tools that can be used by wildland firefighters to avoid injury or fatality when engaging a fire. Effective SZs provide safe separation distance (SSD) from surrounding flames, ensuring that a fire’s heat cannot cause burn injury to firefighters within the SZ. Evaluating SSD on the ground can be challenging, and underestimating SSD can be fatal. We introduce a new online tool for mapping SSD based on vegetation height, terrain slope, wind speed, and burning condition: the Safe Separation Distance Evaluator (SSDE). It allows users to draw a potential SZ polygon and estimate SSD and the extent to which that SZ polygon may be suitable, given the local landscape, weather, and fire conditions. We begin by describing the algorithm that underlies SSDE. Given the importance of vegetation height for assessing SSD, we then describe an analysis that compares LANDFIRE Existing Vegetation Height and a recent Global Ecosystem Dynamics Investigation (GEDI) and Landsat 8 Operational Land Imager (OLI) satellite image-driven forest height dataset to vegetation heights derived from airborne lidar data in three areas of the Western US. This analysis revealed that both LANDFIRE and GEDI/Landsat tended to underestimate vegetation heights, which translates into an underestimation of SSD. To rectify this underestimation, we performed a bias-correction procedure that adjusted vegetation heights to more closely resemble those of the lidar data. SSDE is a tool that can provide valuable safety information to wildland fire personnel who are charged with the critical responsibility of protecting the public and landscapes from increasingly intense and frequent fires in a changing climate. However, as it is based on data that possess inherent uncertainty, it is essential that all SZ polygons evaluated using SSDE are validated on the ground prior to use. Full article
(This article belongs to the Special Issue Wildfire Hazard and Risk Assessment)
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20 pages, 3936 KiB  
Article
Considerations for Categorizing and Visualizing Numerical Information: A Case Study of Fire Occurrence Prediction Models in the Province of Ontario, Canada
by Den Boychuk, Colin B. McFayden, Douglas G. Woolford, Mike Wotton, Aaron Stacey, Jordan Evens, Chelene C. Hanes and Melanie Wheatley
Fire 2021, 4(3), 50; https://doi.org/10.3390/fire4030050 - 18 Aug 2021
Cited by 3 | Viewed by 4245
Abstract
Wildland fire management decision-makers need to quickly understand large amounts of quantitative information under stressful conditions. Categorization and visualization “schemes” have long been used to help, but how they are done affects the speed and accuracy of interpretation. Using traditional fire management schemes [...] Read more.
Wildland fire management decision-makers need to quickly understand large amounts of quantitative information under stressful conditions. Categorization and visualization “schemes” have long been used to help, but how they are done affects the speed and accuracy of interpretation. Using traditional fire management schemes can unduly restrict the design of new products. Our design process for Ontario’s fine-scale, spatially explicit, daily fire occurrence prediction (FOP) models led us to develop guidance for designing new schemes. We show selected historical fire management schemes and describe our method. It includes specifying goals and requirements, exploring design options and making trade-offs. The design options include gradient continuity, hue selection, range completeness and scale linearity. We apply our method to a case study on designing the scheme for Ontario’s FOP models. We arrived at a smooth, nonlinear scale that accommodates data spanning many orders of magnitude. The colouring draws attention according to levels of concern, reveals meaningful spatial patterns and accommodates some colour vision deficiencies. Our method seems simple now but reconciles complex considerations and is useful for mapping many other datasets. Our method improved the clarity and ease of interpretation of several information products used by fire management decision-makers. Full article
(This article belongs to the Special Issue Wildfire Hazard and Risk Assessment)
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17 pages, 8417 KiB  
Article
A Surrogate Model for Rapidly Assessing the Size of a Wildfire over Time
by Ujjwal KC, Jagannath Aryal, James Hilton and Saurabh Garg
Fire 2021, 4(2), 20; https://doi.org/10.3390/fire4020020 - 23 Apr 2021
Cited by 11 | Viewed by 4240
Abstract
Rapid estimates of the risk from potential wildfires are necessary for operational management and mitigation efforts. Computational models can provide risk metrics, but are typically deterministic and may neglect uncertainties inherent in factors driving the fire. Modeling these uncertainties can more accurately predict [...] Read more.
Rapid estimates of the risk from potential wildfires are necessary for operational management and mitigation efforts. Computational models can provide risk metrics, but are typically deterministic and may neglect uncertainties inherent in factors driving the fire. Modeling these uncertainties can more accurately predict risks associated with a particular wildfire, but requires a large number of simulations with a corresponding increase in required computational time. Surrogate models provide a means to rapidly estimate the outcome of a particular model based on implicit uncertainties within the model and are very computationally efficient. In this paper, we detail the development of a surrogate model for the growth of a wildfire based on initial meteorological conditions: temperature, relative humidity, and wind speed. Multiple simulated fires under different conditions are used to develop the surrogate model based on the relationship between the area burnt by the fire and each meteorological variable. The results from nine bio-regions in Tasmania show that the surrogate model can closely represent the change in the size of a wildfire over time. The model could be used for a rapid initial estimate of likely fire risk for operational wildfire management. Full article
(This article belongs to the Special Issue Wildfire Hazard and Risk Assessment)
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17 pages, 1665 KiB  
Article
Building Loss in WUI Disasters: Evaluating the Core Components of the Wildland–Urban Interface Definition
by Michael D. Caggiano, Todd J. Hawbaker, Benjamin M. Gannon and Chad M. Hoffman
Fire 2020, 3(4), 73; https://doi.org/10.3390/fire3040073 - 20 Dec 2020
Cited by 40 | Viewed by 6526
Abstract
Accurate maps of the wildland–urban interface (WUI) are critical for the development of effective land management policies, conducting risk assessments, and the mitigation of wildfire risk. Most WUI maps identify areas at risk from wildfire by overlaying coarse-scale housing data with land cover [...] Read more.
Accurate maps of the wildland–urban interface (WUI) are critical for the development of effective land management policies, conducting risk assessments, and the mitigation of wildfire risk. Most WUI maps identify areas at risk from wildfire by overlaying coarse-scale housing data with land cover or vegetation data. However, it is unclear how well the current WUI mapping methods capture the patterns of building loss. We quantified the building loss in WUI disasters, and then compared how well census-based and point-based WUI maps captured the building loss. We examined the building loss in both WUI and non-WUI land-use types, and in relation to the core components of the United States Federal Register WUI definition: housing density, vegetation cover, and proximity to large patches of wildland vegetation. We used building location data from 70 large fires in the conterminous United States, which cumulatively destroyed 54,000 buildings from 2000 through to 2018. We found that: (1) 86% and 97% of the building loss occurred in areas designated as WUI using the census-based and point-based methods, respectively; (2) 95% and 100% of all of the losses occurred within 100 m and 850 m of wildland vegetation, respectively; and (3) WUI components were the most predictive of building loss when measured at fine scales. Full article
(This article belongs to the Special Issue Wildfire Hazard and Risk Assessment)
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15 pages, 23357 KiB  
Article
Predicting Fire Propagation across Heterogeneous Landscapes Using WyoFire: A Monte Carlo-Driven Wildfire Model
by Cory W. Ott, Bishrant Adhikari, Simon P. Alexander, Paddington Hodza, Chen Xu and Thomas A. Minckley
Fire 2020, 3(4), 71; https://doi.org/10.3390/fire3040071 - 11 Dec 2020
Cited by 10 | Viewed by 5085
Abstract
The scope of wildfires over the previous decade has brought these natural hazards to the forefront of risk management. Wildfires threaten human health, safety, and property, and there is a need for comprehensive and readily usable wildfire simulation platforms that can be applied [...] Read more.
The scope of wildfires over the previous decade has brought these natural hazards to the forefront of risk management. Wildfires threaten human health, safety, and property, and there is a need for comprehensive and readily usable wildfire simulation platforms that can be applied effectively by wildfire experts to help preserve physical infrastructure, biodiversity, and landscape integrity. Evaluating such platforms is important, particularly in determining the platforms’ reliability in forecasting the spatiotemporal trajectories of wildfire events. This study evaluated the predictive performance of a wildfire simulation platform that implements a Monte Carlo-based wildfire model called WyoFire. WyoFire was used to predict the growth of 10 wildfires that occurred in Wyoming, USA, in 2017 and 2019. The predictive quality of this model was determined by comparing disagreement and agreement areas between the observed and simulated wildfire boundaries. Overestimation–underestimation was greatest in grassland fires (>32) and lowest in mixed-forest, woodland, and shrub-steppe fires (<−2.5). Spatial and statistical analyses of observed and predicted fire perimeters were conducted to measure the accuracy of the predicated outputs. The results indicate that simulations of wildfires that occurred in shrubland- and grassland-dominated environments had the tendency to over-predict, while simulations of fires that took place within forested and woodland-dominated environments displayed the tendency to under-predict. Full article
(This article belongs to the Special Issue Wildfire Hazard and Risk Assessment)
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20 pages, 11008 KiB  
Article
In the Line of Fire: Consequences of Human-Ignited Wildfires to Homes in the U.S. (1992–2015)
by Nathan Mietkiewicz, Jennifer K. Balch, Tania Schoennagel, Stefan Leyk, Lise A. St. Denis and Bethany A. Bradley
Fire 2020, 3(3), 50; https://doi.org/10.3390/fire3030050 - 7 Sep 2020
Cited by 65 | Viewed by 37883
Abstract
With climate-driven increases in wildfires in the western U.S., it is imperative to understand how the risk to homes is also changing nationwide. Here, we quantify the number of homes threatened, suppression costs, and ignition sources for 1.6 million wildfires in the United [...] Read more.
With climate-driven increases in wildfires in the western U.S., it is imperative to understand how the risk to homes is also changing nationwide. Here, we quantify the number of homes threatened, suppression costs, and ignition sources for 1.6 million wildfires in the United States (U.S.; 1992–2015). Human-caused wildfires accounted for 97% of the residential homes threatened (within 1 km of a wildfire) and nearly a third of suppression costs. This study illustrates how the wildland-urban interface (WUI), which accounts for only a small portion of U.S. land area (10%), acts as a major source of fires, almost exclusively human-started. Cumulatively (1992–2015), just over one million homes were within human-caused wildfire perimeters in the WUI, where communities are built within flammable vegetation. An additional 58.8 million homes were within one kilometer across the 24-year record. On an annual basis in the WUI (1999–2014), an average of 2.5 million homes (2.2–2.8 million, 95% confidence interval) were threatened by human-started wildfires (within the perimeter and up to 1-km away). The number of residential homes in the WUI grew by 32 million from 1990–2015. The convergence of warmer, drier conditions and greater development into flammable landscapes is leaving many communities vulnerable to human-caused wildfires. These areas are a high priority for policy and management efforts that aim to reduce human ignitions and promote resilience to future fires, particularly as the number of residential homes in the WUI grew across this record and are expected to continue to grow in coming years. Full article
(This article belongs to the Special Issue Wildfire Hazard and Risk Assessment)
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25 pages, 7357 KiB  
Article
Mitigating Source Water Risks with Improved Wildfire Containment
by Benjamin M. Gannon, Yu Wei and Matthew P. Thompson
Fire 2020, 3(3), 45; https://doi.org/10.3390/fire3030045 - 21 Aug 2020
Cited by 9 | Viewed by 5326
Abstract
In many fire-prone watersheds, wildfire threatens surface drinking water sources with eroded contaminants. We evaluated the potential to mitigate the risk of degraded water quality by limiting fire sizes and contaminant loads with a containment network of manager-developed Potential fire Operational Delineations (PODs) [...] Read more.
In many fire-prone watersheds, wildfire threatens surface drinking water sources with eroded contaminants. We evaluated the potential to mitigate the risk of degraded water quality by limiting fire sizes and contaminant loads with a containment network of manager-developed Potential fire Operational Delineations (PODs) using wildfire risk transmission methods to partition the effects of stochastically simulated wildfires to within and out of POD burning. We assessed water impacts with two metrics—total sediment load and frequency of exceeding turbidity limits for treatment—using a linked fire-erosion-sediment transport model. We found that improved fire containment could reduce wildfire risk to the water source by 13.0 to 55.3% depending on impact measure and post-fire rainfall. Containment based on PODs had greater potential in our study system to reduce total sediment load than it did to avoid degraded water quality. After containment, most turbidity exceedances originated from less than 20% of the PODs, suggesting strategic investments to further compartmentalize these areas could improve the effectiveness of the containment network. Similarly, risk transmission varied across the POD boundaries, indicating that efforts to increase containment probability with fuels reduction would have a disproportionate effect if prioritized along high transmission boundaries. Full article
(This article belongs to the Special Issue Wildfire Hazard and Risk Assessment)
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23 pages, 6189 KiB  
Article
Integrating Remote Sensing Methods and Fire Simulation Models to Estimate Fire Hazard in a South-East Mediterranean Protected Area
by Panteleimon Xofis, Pavlos Konstantinidis, Iakovos Papadopoulos and Georgios Tsiourlis
Fire 2020, 3(3), 31; https://doi.org/10.3390/fire3030031 - 19 Jul 2020
Cited by 16 | Viewed by 4068
Abstract
Unlike low intensity fire which promotes landscape heterogeneity and important ecosystem services, large high-intensity wildfires constitute a significant destructive factor despite the increased amount of resources allocated to fire suppression and the improvement of firefighting tactics and levels of organization. Wildfires also affect [...] Read more.
Unlike low intensity fire which promotes landscape heterogeneity and important ecosystem services, large high-intensity wildfires constitute a significant destructive factor despite the increased amount of resources allocated to fire suppression and the improvement of firefighting tactics and levels of organization. Wildfires also affect properties, while an increasing number of fatalities are also associated with wildfires. It is now widely accepted that an effective wildfire management strategy can no longer rely on fire suppression alone. Scientific advances on fire behavior simulation and the increasing availability of remote sensing data, along with advanced systems of fire detection can significantly reduce fire hazards. In the current study remote sensing data and methods, and fire behavior simulation models are integrated to assess the fire hazard in a protected area of the southeast Mediterranean region and its surroundings. A spatially explicit fire hazard index was generated by combining fire intensity estimations and proxies of fire ignition probability. The results suggest that more than 50% of the study area, and the great majority of the protected area, is facing an extremely high hazard for a high-intensity fire. Pine forest formations, characterized by high flammability, low canopy base height and a dense shrub understory are facing the most critical hazard. The results are discussed in relation to the need for adopting an alternative wildfire management strategy. Full article
(This article belongs to the Special Issue Wildfire Hazard and Risk Assessment)
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