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Fire, Volume 3, Issue 1 (March 2020) – 7 articles

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Cover Story (view full-size image) Shown is a QUIC-Fire simulated smoke plume from a pine-forest wildfire. A simple, [...] Read more.
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Open AccessArticle
Decomposing the Interactions between Fire Severity and Canopy Fuel Structure Using Multi-Temporal, Active, and Passive Remote Sensing Approaches
Fire 2020, 3(1), 7; https://doi.org/10.3390/fire3010007 - 10 Mar 2020
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Abstract
Within the realms of both wildland and prescribed fire, an understanding of how fire severity and forest structure interact is critical for improving fuels treatment effectiveness, quantifying the ramifications of wildfires, and improving fire behavior modeling. We integrated high resolution estimates of fire [...] Read more.
Within the realms of both wildland and prescribed fire, an understanding of how fire severity and forest structure interact is critical for improving fuels treatment effectiveness, quantifying the ramifications of wildfires, and improving fire behavior modeling. We integrated high resolution estimates of fire severity with multi-temporal airborne laser scanning data to examine the role that various fuel loading, canopy shape, and other variables had on predicting fire severity for a complex of prescribed fires and one wildfire and how three-dimensional fuels changed as a result of these fires. Fuel loading characteristics were widely variable, and fires were ignited using a several techniques (heading, flanking, and backing), leading to a large amount of variability in fire behavior and subsequent fire effects. Through our analysis, we found that fire severity was linked explicitly to pre-fire fuel loading and structure, particularly in the three-dimensional distribution of fuels. Fire severity was also correlated with post-fire fuel loading, forest structural heterogeneity, and shifted the diversity and abundance of canopy classes within the landscape. This work demonstrates that the vertical distribution of fuel is an important factor and that subtle difference has defined effects on fire behavior and severity. Full article
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Open AccessArticle
Fire-Environment Analysis: An Example of Army Garrison Camp Williams, Utah
Fire 2020, 3(1), 6; https://doi.org/10.3390/fire3010006 - 09 Mar 2020
Viewed by 326
Abstract
The planning of fuel treatments for ecological or societal purposes requires an in-depth understanding of the conditions associated with the occurrence of free-burning fire behavior for the area of concern. Detailed fire-environment analysis for Army Garrison Camp Williams (AGCW) in north-central Utah was [...] Read more.
The planning of fuel treatments for ecological or societal purposes requires an in-depth understanding of the conditions associated with the occurrence of free-burning fire behavior for the area of concern. Detailed fire-environment analysis for Army Garrison Camp Williams (AGCW) in north-central Utah was completed as a prerequisite for fuel treatment planning, using a procedure that could be generally applied. Vegetation and fuels data, topographic and terrain features, and weather and climate data, were assessed and integrated into predictive fuel models to aid planning. A fire behavior fuel model map was developed from biophysical variables, vegetation type, and plot survey data using random forests, and resulted in an overall classification rate of 72%. The predominate vegetation type-fuel complex was grass, followed by lesser amounts of Gambel oak, Wyoming big sagebrush and Utah juniper. The majority of AGCW is mountainous in nature, characterized by slopes less than 40% in steepness with slightly more northerly and easterly aspects than south and west, and elevations that ranged from 1650 to 1950 m above mean sea level. Local fire weather data compiled from the three nearest remote automated weather stations indicated that average temperature maxima (32 °C) and relative humidity minima (12%) usually occurred between 1400 to 1500 h daily, and from July to August, seasonally. The semi-arid climate at AGCW, coupled with the corresponding preponderance of flashy fuel types and sloping terrain, constitutes a formidable fire environment in which to plan for mitigating against adverse fire behavior. Full article
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Open AccessArticle
Flash Characteristics and Precipitation Metrics of Western U.S. Lightning-Initiated Wildfires from 2017
Fire 2020, 3(1), 5; https://doi.org/10.3390/fire3010005 - 26 Feb 2020
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Abstract
This study examines 95 lightning-initiated wildfires and 1170 lightning flashes in the western United States between May and October 2017 to characterize lightning and precipitation rates and totals near the time of ignition. Eighty-nine percent of the wildfires examined were initiated by negative [...] Read more.
This study examines 95 lightning-initiated wildfires and 1170 lightning flashes in the western United States between May and October 2017 to characterize lightning and precipitation rates and totals near the time of ignition. Eighty-nine percent of the wildfires examined were initiated by negative cloud-to-ground (CG) lightning flashes, and 66% of those fire starts were due to single stroke flashes. Average flash density at the fire locations was 1.1 fl km−2. The fire start locations were a median distance of 5.3 km away from the maximum flash and stroke densities in the 400 km2 area surrounding the fire start location. Fire start locations were observed to have a smaller 2-min precipitation rate and 24-h total rainfall than non-fire start locations. The median 2-min rainfall rate for fire-starting (FS) flash locations was 1.7 mm h−1, while the median for non-fire-starting (NFS) flash locations was 4.7 mm h−1. The median total 24-h precipitation value for FS flash locations was 2.9 mm, while NFS flash locations exhibited a median of 8.6 mm. Wilcoxon–Mann–Whitney rank sum testing revealed statistically different Z-Scores/p-values for the FS and NFS flash populations. These values were −5.578/1.21 × 10−8 and −7.176/3.58 × 10−13 for the 2-min precipitation rate and 24-h total rainfall, respectively. Additionally, 24-h and 2-min precipitation rates were statistically significantly greater for holdover versus non-holdover fire events. The median distances between the fire start location and greatest 2-min precipitation rate and greatest 24-h precipitation total were 7.4 and 10.1 km, respectively. Full article
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Open AccessArticle
Predicting Emission Source Terms in a Reduced-Order Fire Spread Model—Part 1: Particulate Emissions
Fire 2020, 3(1), 4; https://doi.org/10.3390/fire3010004 - 25 Feb 2020
Viewed by 521
Abstract
A simple, easy-to-evaluate, surrogate model was developed for predicting the particle emission source term in wildfire simulations. In creating this model, we conceptualized wildfire as a series of flamelets, and using this concept of flamelets, we developed a one-dimensional model to represent the [...] Read more.
A simple, easy-to-evaluate, surrogate model was developed for predicting the particle emission source term in wildfire simulations. In creating this model, we conceptualized wildfire as a series of flamelets, and using this concept of flamelets, we developed a one-dimensional model to represent the structure of these flamelets which then could be used to simulate the evolution of a single flamelet. A previously developed soot model was executed within this flamelet simulation which could produce a particle size distribution. Executing this flamelet simulation 1200 times with varying conditions created a data set of emitted particle size distributions to which simple rational equations could be tuned to predict a particle emission factor, mean particle size, and standard deviation of particle sizes. These surrogate models (the rational equation) were implemented into a reduced-order fire spread model, QUIC-Fire. Using QUIC-Fire, an ensemble of simulations were executed for grassland fires, southeast U.S. conifer forests, and western mountain conifer forests. Resulting emission factors from this ensemble were compared against field data for these fire classes with promising results. Also shown is a predicted averaged resulting particle size distribution with the bulk of particles produced to be on the order of 1 μm in size. Full article
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Open AccessEditorial
Acknowledgement to Reviewers of Fire in 2019
Fire 2020, 3(1), 3; https://doi.org/10.3390/fire3010003 - 21 Jan 2020
Viewed by 369
Abstract
The editorial team greatly appreciates the reviewers who have dedicated their considerable time and expertise to the journal’s rigorous editorial process over the past 12 months, regardless of whether the papers are finally published or not [...] Full article
Open AccessArticle
Resistance and Representation in a Wildland–Urban Interface Fuels Treatment Conflict: The Case of the Forsythe II Project in the Arapaho-Roosevelt National Forest
Fire 2020, 3(1), 2; https://doi.org/10.3390/fire3010002 - 24 Dec 2019
Viewed by 578
Abstract
Land treatments in wildland–urban interface (WUI) areas are highly visible and subject to public scrutiny and possible opposition. This study examines a contested vegetation treatment—Forsythe II—in a WUI area of the Arapaho-Roosevelt National Forest in Colorado. An initial phase of the research found [...] Read more.
Land treatments in wildland–urban interface (WUI) areas are highly visible and subject to public scrutiny and possible opposition. This study examines a contested vegetation treatment—Forsythe II—in a WUI area of the Arapaho-Roosevelt National Forest in Colorado. An initial phase of the research found vocal opposition to Forsythe II. The purpose of the present study was to understand how well the resistance narrative represented the broader community in the WUI area affected by the Forsythe II treatments. More than one third (36%) of households responded to a census survey focused on Forsythe II, demographics, wildfire risk perceptions, and variables associated with generic land management activities and place attachment. Overall, while public opposition to Forsythe II has resulted in a nearly 25% reduction in the project’s size, the survey data demonstrate that just over a quarter of respondents (27%) opposed or strongly opposed the Forsythe II project, and the majority of survey respondents reported broad support for forest management approaches similar to those detailed in the project plans. Notably, a similar portion (28%) did not report an opinion on the project. Results include a systematic comparison of opinion/no opinion respondents. Full article
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Open AccessTechnical Note
Frequency of Dynamic Fire Behaviours in Australian Forest Environments
Fire 2020, 3(1), 1; https://doi.org/10.3390/fire3010001 - 18 Dec 2019
Viewed by 929
Abstract
Wildfires can result in significant social, environmental and economic losses. Fires in which dynamic fire behaviours (DFBs) occur contribute disproportionately to damage statistics. Little quantitative data on the frequency at which DFBs occur exists. To address this problem, we conducted a structured survey [...] Read more.
Wildfires can result in significant social, environmental and economic losses. Fires in which dynamic fire behaviours (DFBs) occur contribute disproportionately to damage statistics. Little quantitative data on the frequency at which DFBs occur exists. To address this problem, we conducted a structured survey using staff from fire and land management agencies in Australia regarding their experiences with DFBs. Staff were asked which, if any, DFBs were observed within fires greater than 1000 ha from the period 2006–2016 that they had experience with. They were also asked about the nature of evidence to support these observations. One hundred thirteen fires were identified. Eighty of them had between one and seven DFBs with 73% (58 fires) having multiple types of DFBs. Most DFBs could commonly be identified through direct data, suggesting an empirical analysis of these phenomena should be possible. Spotting, crown fires and pyro-convective events were the most common DFBs (66%); when combined with eruptive fires and conflagrations, these DFBs comprise 89% of all cases with DFBs. Further research should be focused on these DFBs due to their high frequencies and the fact that quantitative data are likely to be available. Full article
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