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"Fire behavior"
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Ninja at the firehouse
Told in rhyme, this is the story of Moby, who puts his ninja skills to work \"helping\" at the local firehouse, but ends up making more work for the fire fighters--but whose skills do come in handy when a cat needs rescuing.
Book
Slope effect on junction fire with two non-symmetric fire fronts
Background: In Pedrógão Grande on 17 June 2017, two fire fronts merged and the propagation of the fire was influenced by the interaction of these non-symmetric fire fronts.Aims: This wildfire motivated us to study a junction fire with two non-symmetrical fire fronts. The analysis of the movement of the intersection point and the angle (γ) between the bisector of the fire lines and the maximum rate of spread (ROS) direction is of particular relevance.Methods: The study was carried out at Forest Fire Laboratory of the University of Coimbra in Lousã (Portugal) with laboratory experiments.Key results: We found that, for small rotation angles (δ), the non-dimensional ROS of the intersection point depends on the slope angle (α) and the initial angle between fire fronts.Conclusions: For high α, the non-dimensional ROS was highly influenced by the convection process and γ where the maximum ROS occurred, increased when δ increased. However, the radiation process was more relevant for lower α and influenced the non-dimensional ROS. For these cases, the maximum spread direction was close to that of the fire line bisector.Implications: The present work aimed to explain fire behaviour during the Pedrógão Grande wildfire.
Journal Article
Current status and future needs of the BehavePlus Fire Modeling System
The BehavePlus Fire Modeling System is among the most widely used systems for wildland fire prediction. It is designed for use in a range of tasks including wildfire behaviour prediction, prescribed fire planning, fire investigation, fuel hazard assessment, fire model understanding, communication and research. BehavePlus is based on mathematical models for fire behaviour, fire effects and fire environment. It is a point system for which conditions are constant for each calculation, but is designed to encourage examination of the effect of a range of conditions through tables and graphs. BehavePlus is successor to BEHAVE, which was developed in 1977 and became available for field application in 1984. It was updated to BehavePlus in 2002. Updates through version 5 have added features and modelling capabilities. It is becoming increasingly difficult to expand the system. A redesign will address the need for consolidation with other systems and make it easier to incorporate new research results. This paper describes the development history and application of BehavePlus. The design, features and modelling foundation of the current system are described. Considerations for the next generation are presented.
Journal Article
cffdrs: an R package for the Canadian Forest Fire Danger Rating System
Introduction
The Canadian Forest Fire Danger Rating System (CFFDRS) is a globally known wildland fire risk assessment system, and two major components, the fire weather index system and the fire behavior prediction system, have been extensively used both nationally and internationally to aid operational wildland fire decision making.
Methods
In this paper, we present an overview of an R package cffdrs, which is developed to calculate components of the CFFDRS, and highlight some of its functionality. In particular, we demonstrate how these functions could be used for large data analysis.
Results and Discussion
With this cffdrs package, we provide a portal for not only a collection of R functions dealing with all available components in CFFDRS but also a platform for various additional developments that are useful for the understanding of fire occurrence and behavior. This is the first time that all relevant CFFDRS methods are incorporated into the same platform, which can be accessed by both the management and research communities.
Journal Article
Do mountain pine beetle outbreaks change the probability of active crown fire in lodgepole pine forests?
Disturbance interactions have received growing interest in ecological research in the last decade. Fire and bark beetle outbreaks have recently increased in severity and extent across western North America, raising concerns about their possible interactions. Although it is often presumed that bark beetle outbreaks increase probability of active crown fire by producing high loads of surface and canopy dead fuels, empirical data are scarce and results are ambivalent. We combined field measurements and modeling to address the following question: How do fuel characteristics, microclimate, and potential fire behavior change with time since a severe mountain pine beetle outbreak in
Pinus contorta
forests of Greater Yellowstone (Wyoming, USA)? We measured surface and canopy fuels, and soil surface temperature in a time-since-beetle-outbreak chronosequence (
n
== 35 sites) from undisturbed to 36 years post-outbreak, including stands in red- and gray-needle stages (respectively, 1-–2 and 3-–5 years post-outbreak). Field data were used to parameterize the fire behavior model NEXUS and predict potential fire behavior at each site.
Dead surface fuel loads of all size categories did not differ among undisturbed, red, and gray-stage stands. Compared to undisturbed sites, red and gray-stage sites had on average 53%% lower canopy bulk density, 42%% lower canopy fuel load, and 29%% lower canopy moisture content, but had similar canopy base heights (3.1 m). In subsequent decades, coarse wood loads doubled and canopy base height declined to 0 m. Modeling results suggested that undisturbed, red, and gray-stage stands were unlikely to exhibit transition of surface fires to tree crowns (torching), and that the likelihood of sustaining an active crown fire (crowning) decreased from undisturbed to gray-stage stands. Simulated fire behavior was little affected by beetle disturbance when wind speed was either below 40 km/h or above 60 km/h, but at intermediate wind speeds, probability of crowning in red- and gray-stage stands was lower than in undisturbed stands, and old post-outbreak stands were predicted to have passive crown fires. Results were consistent across a range of fuel moisture scenarios. Our results suggest that mountain pine beetle outbreaks in Greater Yellowstone may reduce the probability of active crown fire in the short term by thinning lodgepole pine canopies.
Journal Article
Meteorological Analysis of the 2021 Extreme Wildfires in Greece: Lessons Learned and Implications for Early Warning of the Potential for Pyroconvection
The 2021 fire season in Greece was the worst of the past 13 years, resulting in more than 130,000 ha of burnt area, with about 70% consumed by five wildfires that ignited and spread in early August. Common to these wildfires was the occurrence of violent pyroconvection. This work presents a meteorological analysis of this outbreak of extreme pyroconvective wildfires. Our analysis shows that dry and warm antecedent weather preconditioned fuels in the fire-affected areas, creating a fire environment that alone could effectively support intense wildfire activity. Analysis of surface conditions revealed that the ignition and the most active spread of all wildfires coincided with the most adverse fire weather since the beginning of the fire season. Further, the atmospheric environment was conducive to violent pyroconvection, as atmospheric instability gradually increased amid the breakdown of an upper-air ridge ahead of an approaching long-wave trough. In summary, we highlight that the severity and extent of the 2021 Greek wildfires were not surprising considering the fire weather potential for the period when they ignited. Continuous monitoring of the large- and local-scale conditions that promote extreme fire behavior is imperative for improving Greece’s capacity for managing extreme wildfires.
Journal Article
Consistent, high-accuracy mapping of daily and sub-daily wildfire growth with satellite observations
Background: Fire research and management applications, such as fire behaviour analysis and emissions modelling, require consistent, highly resolved spatiotemporal information on wildfire growth progression.Aims: We developed a new fire mapping method that uses quality-assured sub-daily active fire/thermal anomaly satellite retrievals (2003–2020 MODIS and 2012–2020 VIIRS data) to develop a high-resolution wildfire growth dataset, including growth areas, perimeters, and cross-referenced fire information from agency reports.Methods: Satellite fire detections were buffered using a historical pixel-to-fire size relationship, then grouped spatiotemporally into individual fire events. Sub-daily and daily growth areas and perimeters were calculated for each fire event. After assembly, fire event characteristics including location, size, and date, were merged with agency records to create a cross-referenced dataset.Key results: Our satellite-based total fire size shows excellent agreement with agency records for MODIS (R2 = 0.95) and VIIRS (R2 = 0.97) in California. VIIRS-based estimates show improvement over MODIS for fires with areas less than 4047 ha (10 000 acres). To our knowledge, this is the finest resolution quality-assured fire growth dataset available.Conclusions and Implications: The novel spatiotemporal resolution and methodological consistency of our dataset can enable advances in fire behaviour and fire weather research and model development efforts, smoke modelling, and near real-time fire monitoring.
Journal Article
A comprehensive taxonomy for forest fire risk assessment: bridging methodological gaps and proposing future directions
Forest fire risk assessment plays a crucial role in the environmental management of natural hazards, serving as a key tool in the prevention of forest fires and the protection of various species. As these risks continue to evolve with environmental changes, the pertinence of contemporary research in this field remains undiminished. This review constructs a comprehensive taxonomic framework for classifying the existing body of literature on forest fire risk assessment within forestry studies. The developed taxonomy categorizes existing studies into 8 primary categories and 23 subcategories, offering a structured perspective on the methodologies and focus areas prevalent in the domain. We categorize a sample of 170 articles to present recent trends and identify research gaps in forest fire risk assessment literature. The classification facilitates a critical evaluation of the current research landscape, identifying areas in need of further exploration. Particularly, our review identifies underrepresented methodologies such as optimization modeling and some advanced machine learning techniques, which present routes for future inquiry. Moreover, the review underscores the necessity for model development that is tailored to specific regional data sets but also adaptable to global data resources, striking a balance between local specificity and broad applicability. Emphasizing the dynamic nature of forest fire behavior, we advocate for models that integrate the burgeoning field of machine learning and multi-criteria decision analysis to refine predictive accuracy and operational effectiveness in fire risk assessment. This study highlights the great potential for new ideas in modeling techniques and emphasizes the need for increased collaboration among research communities to improve the effectiveness of assessing forest fire risks.
Journal Article
On the intermittent nature of forest fire spread – Part 2
Based on analysis of the interaction between a spreading fire and its surrounding environment, in nominally constant and uniform boundary conditions, it is observed that the evolution of the fire front is characterised by fluctuations of its properties, including (in particular) its rate of spread (ROS). Using a database with a wide range of fires with different time–space scales, it is shown that the amplitude of the fluctuation in ROS is proportional to the average value of the ROS and that the frequency of oscillation varies with the type of fire, and for a given fuel, increases with the average ROS. In fast-spreading fires, the large amplitude of ROS increase and sudden decrease promote the intermittent behaviour of the fire. In general, the amplitude and period required for the ROS increase are larger than for its decrease. However, the acceleration and deceleration phases in junction fires do not follow this rule, suggesting the existence of different convective processes of interaction between the flow and fire. This oscillation explains the variability in many fires at all scales and challenges the current interpretation based on the three factors affecting fire spread and the classification of wind or topography-driven fires.
Journal Article
What determines variation in remotely sensed fire severity? Consideration of remote sensing limitations and confounding factors
Analyses of the effects of topography, weather, land management, and fuel on fire severity are increasingly common, and generally apply fire severity indices derived from satellite optical remote sensing. However, these indices are commonly interpreted with insufficient appreciation for their limitations and may be inappropriately invoked as representing physical fire effects and fire behaviour. For a large wildfire in southeast Australia, we investigated three considerations for inferring robust insights from fire severity analyses – the potentially confounding influences of pre-fire vegetation height and tall vegetation cover, and the choice of fire severity response variable. Using nonparametric regression, we found that different fire severity indices gave rise to substantially different modelled relationships with commonly invoked environmental predictors, as is consistent with dissimilarities in index design. Further, pre-fire vegetation height was a strong control of fire severity, with equivalent importance to weather. Importantly, strong covariation between vegetation height and environmental predictors suggests that modelled fire severity effects are strongly influenced by variation in vertical distance between flames and vegetation, and this confounds fire behaviour insights. To enable more robust and mechanistic insights into the determinants of fire severity, we recommend greater consideration of the meaning and limitations of optical remote sensing indices.
Journal Article