Fire Behavior Models Research Articles

Pan-European fuel map server: An open-geodata portal for supporting fire risk assessment

Canopy fuels and surface fuel models, topographic features and other canopy attributes such as stand height and canopy cover, provide the necessary spatial datasets required by various fire behaviour modelling simulators. This is a technical note reporting on a pan-European fuel map server, highlighting the methods for the production and validation of canopy features, more specifically canopy fuels, and surface fuel models created for the European Union’s Horizon 2020 “FIRE-RES” project, as well as other related data derived from earth observation. The aim was to deliver a fuel cartography in a findable, accessible, interoperable and replicable manner as per F.A.I.R. guiding principles for research data stewardship. We discuss the technology behind sharing large raster datasets via web-GIS technologies and highlight advances and novelty of the shared data. Uncertainty maps related to the canopy fuel variables are also available to give users the expected reliability of the data. Users can view, query and download single layers of interest, or download the whole pan-European dataset. All layers are in raster format and co-registered in the same reference system, extent and spatial resolution (100 m). Viewing and downloading is available at all NUTS scales, ranging from country level (NUTS0) to province level (NUTS3), thus facilitating data management and access. The system was implemented using R for part of the processing and Google Earth Engine. The final app is openly available to the public for accessing the data at various scales.

Forest structural complexity and ignition pattern influence simulated prescribed fire effects

BackgroundForest structural characteristics, the burning environment, and the choice of ignition pattern each influence prescribed fire behaviors and resulting fire effects; however, few studies examine the influences and interactions of these factors. Understanding how interactions among these drivers can influence prescribed fire behavior and effects is crucial for executing prescribed fires that can safely and effectively meet management objectives. To analyze the interactions between the fuels complex and ignition patterns, we used FIRETEC, a three-dimensional computational fluid dynamics fire behavior model, to simulate fire behavior and effects across a range of horizontal and vertical forest structural complexities. For each forest structure, we then simulated three different prescribed fires each with a unique ignition pattern: strip-head, dot, and alternating dot.ResultsForest structural complexity and ignition pattern affected the proportions of simulated crown scorch, consumption, and damage for prescribed fires in a dry, fire-prone ecosystem. Prescribed fires in forests with complex canopy structures resulted in increased crown consumption, scorch, and damage compared to less spatially complex forests. The choice of using a strip-head ignition pattern over either a dot or alternating-dot pattern increased the degree of crown foliage scorched and damaged, though did not affect the proportion of crown consumed. We found no evidence of an interaction between forest structural complexity and ignition pattern on canopy fuel consumption, scorch, or damage.ConclusionsWe found that forest structure and ignition pattern, two powerful drivers of fire behavior that forest managers can readily account for or even manipulate, can be leveraged to influence fire behavior and the resultant fire effects of prescribed fire. These simulation findings have critical implications for how managers can plan and perform forest thinning and prescribed burn treatments to meet risk management or ecological objectives.

Effect of live/dead condition, moisture content and particle size on flammability of gorse (Ulex europaeus) measured with a cone calorimeter

Background Live fuel comprises a significant portion of the fuel consumed in forest and scrub crown fires. However, its flammability remains poorly understood. Although live fuel differs from dead fuel in moisture content, chemical composition, cellular structure and physiological characteristics, its higher moisture content masks the effect of other characteristics on its flammability. Aims The aim of the study was to delineate and assess the effects of live/dead condition, moisture content and particle size on flammability of gorse (Ulex europaeus L.). Methods Live and dead gorse material of three size classes (0–3, 3–6, and 6–10 mm in diameter) at six moisture contents (0, 10, 25, 50, 75 and 100%) was tested in a cone calorimeter to evaluate its flammability using new sample preparation and moisture conditioning techniques. Key results On average, live fuel ignited 21% slower, reached 11% higher peak heat release rate, and had a 12% shorter burn duration than dead fuel of the same moisture content. These differences were most pronounced in coarser material. Conclusions For gorse, fine dead fuels increase the likelihood of ignition, fine live fuels contribute to high burning intensities, and coarser live and dead fuels prolong combustion. Implications These findings highlight the need to account for flammability differences between live and dead fuels in fire behaviour models beyond those driven by variations in moisture content.

Stochastic bulk density in the fire spread model

AbstractIn this study, we investigate the impact of inherent randomness on fire spread rates, with a particular focus on the stochastic parameter ε, representing the ratio of effective to actual fuel bulk density. By employing various probability distributions, such as the beta random distribution model ε, we explore the complex interplay between wind and slope factors in determining fire behavior. Our 3D visualizations and density plots illuminate the multidimensional nature of fire spread, emphasizing the significant role of stochastic variability in enhancing the accuracy of fire behavior models. This approach not only deepens our theoretical understanding but also provides valuable insights for improving fire management strategies.

Wildland fire fuels database for Corsican - Mediterranean Forest stand types

Wildfires represent a major concern for the forests in the Mediterranean basin regions since global climate change enhances the frequency and the severity of this natural ecological disturbance agent. Wildfire models (fire spread or fire behavior models) can be of valuable help for fire risk assessment as well as for planning mitigation actions which mainly concern forest management. These models need generalized vegetation (fuel) data sets at the scales which are significant for fire/forest management. However, despite of the efforts to develop methods for generating global fuel data sets, there is a lack of fine resolution regional scale fuel data sets for the Mediterranean basin. The aim of this work is to build a fuel data set based on existing data sources for fire/forest management, risk assessment and decision-support purposes. Thus, this paper presents a database (building methods and data) of wildland fuels for Mediterranean basin vegetation stands types and in particular for those in Corsica, which gathers together most common input parameters needed by wildfire’s models at several vegetation scales (i.e., stand, elements, particles). Moreover, an example is provided where simulations are run with a specific wildfire model by using the fuel input data extracted from the database. Fuel attributes have been defined to be meaningful at regional/landscape scales and are representative of stand-level characteristics. National (French) Forest Inventory (NFI) data have been mainly used for determining the fuel attributes for forest stand types. The harmonization of European NFIs generates a reliable data source available to extend and generalize the methodology presented herein to other regions or countries.

Cone and fruit impacts on understory flammability depend on traits and forest floor coverage

BackgroundUnderstory flammability is affected by abscised plant tissue. Extensive research has shown how interspecific differences in leaf litter traits affect flammability; however, leaves represent only one component of the litter layer. Cones and fruit are also common constituents of the forest floor, yet surprisingly little is known about how flammability is affected by their presence. In this study, we ask how flammability is affected by cones and fruit trait differences, coverage differences, and varying species and coverage combinations. To address these questions, we compared cone and fruit morphological and chemical traits among longleaf pine, loblolly pine, shortleaf pine, sweetgum, post oak, and water oak. We also used burn trials to compare fire behavior of single and mixed-species treatments at three coverage levels (10% of plot area (low), 30% (medium), and 50% (high)) integrated within a common mixed-litter layer under field conditions in central Alabama, USA.ResultsLike other plant tissues, cone/fruit dry matter, carbon, and lignin content promote fuel consumption and flame height, while nitrogen suppresses flammability. Single-species treatments produced distinct patterns in fire behavior, with longleaf pine cones consistently showing higher percent fuel consumption, flame height, and maximum smoldering temperature than sweetgum capsular heads. Mixed-species treatment results were less consistent; however, at high coverage, a representative upland three-way mixture (longleaf pine + sweetgum + post oak) showed significantly greater fuel consumption and flame height relative to a bottomland three-way mixture (loblolly pine + sweetgum + water oak) at high coverage. Medium cone/fruit coverage maximized flammability in most single and multi-species treatments and produced non-additive fuel consumption in mixtures containing longleaf pine and sweetgum.ConclusionOur results confirm that individual species’ cone and fruit flammability often parallels that of litter. Fire behavior in mixture is generally driven by the most flammable constituent species, but this result changes with cone and fruit coverage. Collectively, these results indicate that cones/fruit identity and coverage play an important role in understory flammability and should be integrated into fire behavior modeling efforts in monocultures and mixtures.

Investigating Fire–Atmosphere Interaction in a Forest Canopy Using Wavelets

Wildland fire–atmosphere interaction generates complex turbulence patterns, organized across multiple scales, which inform fire-spread behaviour, firebrand transport, and smoke dispersion. Here, we utilize wavelet-based techniques to explore the characteristic temporal scales associated with coherent patterns in the measured temperature and the turbulent fluxes during a prescribed wind-driven (heading) surface fire beneath a forest canopy. We use temperature and velocity measurements from tower-mounted sonic anemometers at multiple heights. Patterns in the wavelet-based energy density of the measured temperature plotted on a time–frequency plane indicate the presence of fire-modulated ramp–cliff structures in the low-to-mid-frequency band (0.01–0.33 Hz), with mean ramp durations approximately 20% shorter and ramp slopes that are an order of magnitude higher compared to no-fire conditions. We then investigate heat- and momentum-flux events near the canopy top through a cross-wavelet coherence analysis. Briefly before the fire-front arrives at the tower base, momentum-flux events are relatively suppressed and turbulent fluxes are chiefly thermally-driven near the canopy top, owing to the tilting of the flame in the direction of the wind. Fire-induced heat-flux events comprising warm updrafts and cool downdrafts are coherent down to periods of a second, whereas ambient heat-flux events operate mainly at higher periods (above 17 s). Later, when the strongest temperature fluctuations are recorded near the surface, fire-induced heat-flux events occur intermittently at shorter scales and cool sweeps start being seen for periods ranging from 8 to 35 s near the canopy top, suggesting a diminishing influence of the flame and increasing background atmospheric variability thereat. The improved understanding of the characteristic time scales associated with fire-induced turbulence features, as the fire-front evolves, will help develop more reliable fire behaviour and scalar transport models.

Australian Fire Danger Rating System: implementing fire behaviour calculations to forecast fire danger in a research prototype†

Background The Australian Fire Danger Rating System (AFDRS) was implemented operationally throughout Australia in September 2022, providing calculation of fire danger forecasts based on peer-reviewed fire behaviour models. The system is modular and allows for ongoing incorporation of new scientific research and improved datasets. Aims Prior to operational implementation of the AFDRS, a Research Prototype (AFDRSRP), described here, was built to test the input data and systems and evaluate the performance and potential outputs. Methods Fire spread models were selected and aligned with fuel types in a process that captured bioregional variation in fuel characteristics. National spatial datasets were created to identify fuel types and fire history in alignment with existing spatial weather forecast layers. Key results The AFDRSRP demonstrated improvements over the McArthur Forest and Grass Fire Danger systems due to its use of improved fire behaviour models, as well as more accurately reflecting the variation in fuels. Conclusions The system design was robust and allowed for the incorporation of updates to the models and datasets prior to implementation of the AFDRS.

Fuel Drivers of Fire Behaviour in Coastal Mallee Shrublands

Coastal mallee shrubland wildfires present challenges for accurately predicting fire spread sustainability and rate of spread. In this study, we assess the fuel drivers contributing to coastal mallee shrubland fires. A review of shrubland fire behaviour models and fuel metrics was conducted to determine the current practice of assessing shrubland fuels. This was followed by workshops designed to elicit which fuel structural metrics are key drivers of fire behaviour in coastal mallee shrublands. We found that height is the most commonly used fuel metric in shrubland fire models due to the ease of collection in situ or as a surrogate for more complex fuel structures. Expert workshop results suggest that cover and connectivity metrics are key to modelling fire behaviour in coastal mallee shrublands. While height and cover are frequently used in fire models, we conclude that connectivity metrics would offer additional insights into fuel drivers in mallee shrublands. Future research into coastal mallee fire behaviour should include the measurements of fuel height, cover, and horizontal and vertical connectivity.

Comparison of Different Models to Simulate Forest Fire Spread: A Case Study

With the development of computer technology, forest fire spread simulation using computers has gradually developed. According to the existing research on forest fire spread, the models established in various countries have typical regional characteristics. A fire spread model established in a specific region is only suitable for the local area, and there is still a great deal of uncertainty as to whether or not the established model is suitable for fire spread simulation for the same fuel in other regions. Although many fire spread models have been established, the fuel characteristics applicable to each model, such as the fuel loading, fuel moisture content, combustibility, etc., are not similar. It is necessary to evaluate the applicability of different fuel characteristics to different fire spread models. We combined ground investigation, historical data collection, model improvements, and statistical analysis to establish a multi-model forest fire spread simulation method (FIRER) that shows the burning time, perimeter, burning area, overlap area, and spread rate of fire sites. This method is a large-scale, high-resolution fire growth model based on fire spread in eight directions on a regular 30 m grid. This method could use any one of four different physical models (McArthur, Rothermel, FBP, and Wang Zhengfei (China)) for fire behavior. This method has an option to represent fire breaks from roads, rivers, and fire suppression. We can evaluate which model is more suitable in a specific area. This method was tested on a single historical lightning fire in the Daxing’an Mountains. Different scenarios were tested and compared: using each of the four fire behavior models, with fire breaks on or off, and with a single or suspected double fire ignition location of the historical fire. The results show that the Rothermel model is the best model in the simulation of the Hanma lightning fire; the overlap area is 5694.4 hm2. Meanwhile, the real fire area in FIRER is 5800.9 hm2; both the Kappa and Sørensen values exceed 0.8, providing high accuracy in fire spread simulations. FIRER performs well in the automatic identification of fire break zones and multiple ignited points. Compared with FARSITE, FIRER performs well in predicting accuracy. Compared with BehavePlus, FIRER also has advantages in simulating large-scale fire spread. However, the complex data preparation stage of FIRER means that FIRER still has great room for improvement. This research provides a practical basis for the comparison of the practicability and applicability of various fire spread models and provides more effective practical tools and a scientific basis for decision-making and the management of fighting forest fires.

Introduction to the Australian Fire Danger Rating System†

Background Fire danger rating systems are used daily across Australia to support fire management operations and communications to the general public regarding potential fire danger. Aims In this paper, we introduce the Australian Fire Danger Rating System (AFDRS), providing a short historical account of fire danger rating in Australia as well as the requirements for an improved forecast system. Methods The AFDRS combines nationally consistent, spatially explicit fuel information with forecast weather and advanced fire behaviour models and knowledge to produce locally relevant ratings of fire behaviour potential. Key results A well-defined framework is essential for categorising and defining fire danger based on operational response, the potential for impact and observable characteristics of fire incidents. The AFDRS is modular, supporting continuous and incremental improvements and allowing upgrades to components in response to new science. Conclusions The AFDRS provides a new method to estimate fire danger based on the best available fire behaviour models, leading to potentially significant improvements in the way fire danger is calculated, forecast and interpreted. Implications The Australian Fire Danger Rating System was implemented in 2022, the most significant change to fire danger forecasting in Australia in more than 50 years.

Branching out: species-specific canopy architecture limits live crown fuel consumption in Intermountain West USA conifers

BackgroundAccurate estimates of available live crown fuel loads are critical for understanding potential wildland fire behavior. Existing crown fire behavior models assume that available crown fuels are limited to all tree foliage and half of the fine branches less than 6 mm in diameter (1 h fuel). They also assume that this relationship is independent of the branchwood moisture content. Despite their widespread use, these assumptions have never been tested, and our understanding of the physiochemical properties that govern live crown flammability and consumption remains limited. To test these assumptions, we sampled branches from 11 common Intermountain West USA conifers and determined the corrected available fuel estimates using physiochemical measurements, diameter subsize class distributions, and a bench-scale consumption experiment. Additional branches were air-dried to explore interaction between moisture content and consumption. Corrected available live crown fuel was compared to existing models across species and then used to determine potential differences in crown fire energy release.ResultsAcross the 11 common conifers, distinct patterns of sub 1 h fuel distributions were strong predictors of whether the existing available live crown fuel models overestimated, approximately correctly estimated, or underestimated available live fuel. Fine branchwood distributions generally fell into three archetypes: fine skewed, normally distributed, and coarse skewed. Based on our corrected estimates, existing models overestimated the potential canopy energy by 34% for an average-sized western larch and underestimated it by 18.8% for western hemlock. The critical fine branchwood consumption diameter varied with species and moisture content. Larger proportions of fine branches were consumed as the branchwood dried, and nearly all the 1 h fuel was consumed when the branches were completely dry.ConclusionsThese results suggest that available live canopy fuel load estimates should consider species and moisture content to accurately assess and map fuel loads across landscapes. This work has implications for forest and fire management in conifer-dominated forests throughout western North America, and in other similar forests worldwide.

Evaluation of Handheld Mobile Laser Scanner Systems for the Definition of Fuel Types in Structurally Complex Mediterranean Forest Stands

The exposure of Mediterranean forests to large wildfires requires mechanisms to prevent and mitigate their negative effects on the territory and ecosystems. Fuel models synthesize the complexity and heterogeneity of forest fuels and allow for the understanding and modeling of fire behavior. However, it is sometimes challenging to define the fuel type in a structurally heterogeneous forest stand due to the mixture of characteristics from the different types and limitations of qualitative field observations and passive and active airborne remote sensing. This can impact the performance of classification models that rely on the in situ identification of fuel types as the ground truth, which can lead to a mistaken prediction of fuel types over larger areas in fire prediction models. In this study, a handheld mobile laser scanner (HMLS) system was used to assess its capability to define Prometheus fuel types in 43 forest plots in Aragón (NE Spain). The HMLS system captured the vertical and horizontal distribution of fuel at an extremely high resolution to derive high-density three-dimensional point clouds (average: 63,148 points/m2), which were discretized into voxels of 0.05 m3. The total number of voxels in each 5 cm height stratum was calculated to quantify the fuel volume in each stratum, providing the vertical distribution of fuels (m3/m2) for each plot at a centimetric scale. Additionally, the fuel volume was computed for each Prometheus height stratum (0.60, 2, and 4 m) in each plot. The Prometheus fuel types were satisfactorily identified in each plot and were compared with the fuel types estimated in the field. This led to the modification of the ground truth in 10 out of the 43 plots, resulting in errors being found in the field estimation between types FT2–FT3, FT5–FT6, and FT6–FT7. These results demonstrate the ability of the HMLS systems to capture fuel heterogeneity at centimetric scales for the definition of fuel types in the field in Mediterranean forests, making them powerful tools for fuel mapping, fire modeling, and ultimately for improving wildfire prevention and forest management.

Atmospheric turbulence observed during a fuel-bed-scale low-intensity surface fire

Abstract. The ambient atmospheric environment affects the growth and spread of wildland fires, whereas heat and moisture released from the fires and the reduction of the surface drag in the burned areas can significantly alter local atmospheric conditions. Observational studies on fire–atmosphere interactions have used instrumented towers to collect data during prescribed fires, but a few towers in an operational-scale burn plot (usually > 103 m2) have made it extremely challenging to capture the myriad of factors controlling fire–atmosphere interactions, many of which exhibit strong spatial variability. Here, we present analyses of atmospheric turbulence data collected using a 4 × 4 array of fast-response sonic anemometers during a fire experiment on a 10 m × 10 m burn plot. In addition to confirming some of the previous findings on atmospheric turbulence associated with low-intensity surface fires, our results revealed substantial heterogeneity in turbulent intensity and heat and momentum fluxes just above the combustion zone. Despite the small plot (100 m2), fire-induced atmospheric turbulence exhibited strong dependence on the downwind distance from the initial line fire and the relative position specific to the fire front as the surface fire spread through the burn plot. This result highlights the necessity for coupled atmosphere–fire behavior models to have 1–2 m grid spacing to resolve heterogeneities in fire–atmosphere interactions that operate on spatiotemporal scales relevant to atmospheric turbulence. The findings here have important implications for modeling smoke dispersion, as atmospheric dispersion characteristics in the vicinity of a wildland fire are directly affected by fire-induced turbulence.

Application of artificial intelligence methods to model the effect of grass curing level on spread rate of fires

Artificial intelligence (AI) enables new approaches to fire behaviour models of operational relevance, including prescribed burns. This is particularly important in modelling of processes that are poorly understood, such as live fuel's effect on fire propagation. The objective of this study was to apply AI algorithms to quantify the effect of the proportion of dead fuels in a senescing grassland, the curing level, on reducing the rate of fire spread relative to the fully cured condition. We applied three different machine learning (ML) models, regression trees, support vector regression (SVR) and Gene expression programming (GEP), two ensemble ML methods, Random Forest and GEP Forest, and non-linear regression analysis to an experimental fire dataset. Results show SVR and GEP as the best ML methods to model the curing level impact on fire spread. No differences in model fit were observed between the best ML methods and non-linear regression analysis.

Synoptic and Mesoscale Aspects of Exceptional Fire Weather during the New Year Period 2019–20 in Southeastern New South Wales, Australia

Abstract Extreme fire weather and fire behavior occurred during the New Year’s Eve period 30–31 December 2019 in southeast New South Wales, Australia. Fire progressed rapidly during the late evening and early morning periods, and significant extreme pyrocumulonimbus behavior developed, sometimes repeatedly in the same area. This occurred within a broader context of an unprecedented fire season in eastern Australia. Several aspects of the synoptic and mesoscale meteorology are examined, to identify contributions to fire behavior during this period. The passage of a cold front through the region was a key factor in the event, but other processes contributed to the severity of fire weather. Additional important features during this period included the movement of a negatively tilted upper-tropospheric trough, the interaction of the front with topography, and the occurrence of low-level overnight jets and of horizontal boundary layer rolls in the vicinity of the fireground. Significance Statement Wildfires and the weather that promotes their ignition and spread are a threat to communities and natural values globally, even in fire-adapted landscapes such as the western United States and Australia. In particular, savanna in the north of Australia regularly burns during the dry season while forest and grassland in the south burn episodically, mostly during the summer. Here, we examine the weather associated with destructive fires that occurred in southeast New South Wales, Australia, in late 2019. Weather and climate factors at several scales interacted to contribute to fire activity that was unusually dangerous. For meteorologists and emergency managers, case studies such as this are valuable to highlight conditions that may lead to future similar events. This case study also identified areas where improvements in fire weather service can be made, including the incorporation of more detailed weather information into models of fire behavior.

Modeling spatial patterns of longleaf pine needle dispersal using long-term data

BackgroundPredicting patterns of fire behavior and effects in frequent fire forests relies on an understanding of fine-scale spatial patterns of available fuels. Leaf litter is a significant canopy-derived fine fuel in fire-maintained forests. Litter dispersal is dependent on foliage production, stand structure, and wind direction, but the relative importance of these factors is unknown.ResultsUsing a 10-year litterfall dataset collected within eighteen 4-ha longleaf pine (Pinus palustris Mill.) plots varying in canopy spatial pattern, we compared four spatially explicit models of annual needle litter dispersal: a model based only on basal area, an overstory abundance index (OAI) model, both isotropic and anisotropic litter kernel models, and a null model that assumed no spatial relationship. The best model was the anisotropic model (R2 = 0.656) that incorporated tree size, location, and prevailing wind direction, followed by the isotropic model (R2 = 0.612), basal area model (R2 = 0.488), OAI model (R2 = 0.416), and the null model (R2 = 0.08).ConclusionsAs with previous studies, the predictive capability of the litter models was robust when internally validated with a subset of the original dataset (R2 = 0.196–0.549); however, the models were less robust when challenged with an independent dataset (R2 = 0.122–0.319) from novel forest stands. Our model validation underscores the need for rigorous tests with independent, external datasets to confirm the validity of litter dispersal models. These models can be used in the application of prescribed fire to estimate fuel distribution and loading, as well as aid in the fine tuning of fire behavior models to better understand fire outcomes across a range of forest canopy structures.

Material characterisation tests of ultra‐high‐strength steels S960QL and S1100M under natural fire conditions

AbstractFire hazards represent one of the most important threats to the built environment with serious economic consequences for society and most dangerous threats to life. Fire engineering is the key discipline to improve fire safety in the building environment in a cost‐effective manner. Comprehensive knowledge of the material behavior is the basis for a thorough understanding and a realistic modeling of the structural fire behavior of steel structures. For state‐of‐the‐art buildings with increasing requirements, the utilization of high‐strength steels is favorable, as they can contribute to resource and energy efficiency due to their good strength‐to‐weight ratio. Modern production processes enable the production of structural steels with very high nominal yield strengths. For those ultra‐high‐strength steels there are currently no experimental results available regarding the material behavior in case of fire and the post fire residual strengths. The paper provides experimental data of the first test program regarding the constitutive material behavior of ultra‐high‐strength steels of grades S960QL and S1100M in the case of fire, taking into account the entire fire progress including the heating and cooling phases and the post fire range.

Vertical and Horizontal Crown Fuel Continuity Influences Group-Scale Ignition and Fuel Consumption

A deeper understanding of the influence of fine-scale fuel patterns on fire behavior is essential to the design of forest treatments that aim to reduce fire hazard, enhance structural complexity, and increase ecosystem function and resilience. Of particular relevance is the impact of horizontal and vertical forest structure on potential tree torching and large-tree mortality. It may be the case that fire behavior in spatially complex stands differs from predictions based on stand-level descriptors of the fuel distribution and structure. In this work, we used a spatially explicit fire behavior model to evaluate how the vertical and horizontal distribution of fuels influences the potential for fire to travel from the surface into overstory tree crowns. Our results support the understanding that crown fuels (e.g., needles and small-diameter branchwood) close to the surface can aid in this transition; however, we add important nuance by showing the interactive effect of overstory horizontal fuel connectivity. The influence of fuels low in the canopy space was overridden by the effect of horizontal connectivity at surface fire-line intensities greater than 1415 kW/m. For example, tree groups with vertically continuous fuels and limited horizontal connectivity sustained less large-tree consumption than tree groups with a significant vertical gap between the surface and canopy but high-canopy horizontal connectivity. This effect was likely the result of reduced net vertical heat transfer as well as decreased horizontal heat transfer, or crown-to-crown spread, in the upper canopy. These results suggest that the crown fire hazard represented by vertically complex tree groups is strongly mediated by the density, or horizontal connectivity, of the tree crowns within the group, and therefore, managers may be able to mitigate some of the torching hazard associated with vertically heterogenous tree groups.

Burning Rate of Wood Cribs with Controlled Airflow

AbstractThere is a dire need to improve our prediction capabilities of wildland fire behavior in a range of conditions from marginal burning to the most extreme. In order to develop a more physically-based operational wildland fire behavior model, we need to improve our understanding of the effect of ventilation on burning rate of fuel beds. In this work, wood cribs are used as a simplified fuel bed. A variety of crib designs were tested with stick sizes ranging from 0.32 cm to 1.27 cm and porosities ranging from densely packed to loosely packed. A pressurized box was built that allowed for a controlled flow rate of air through the cribs from 100 LPM to 1000 LPM. The mass loss rates with forced ventilation were compared to tests conducted outside of the box under unrestricted quiescent conditions. For the flow rates tested here, the burning rate was generally observed to increase with flow. The amount of air naturally induced into a crib while burning was deduced to be best related to the vent area and the square root of the stick spacing (Avs1/2). It was seen that the air-to-fuel ratio inside a fuel bed burning in quiescent conditions is approximately 1.11, indicating that over 75% of the air required to completely combust the pyrolysis gases is entrained in the plume. When the supplied air is less than the amount normally entrained in ambient burning, the crib is under-ventilated and the proportional reduction in the burning rate does not seem to depend on the crib characteristics. When the crib is over-ventilated, however, the relative increase in the burning rate does vary with crib design. Simple physical arguments were used to correlate the data. Future work will include testing at higher flow rates, different moisture contents, and with cribs built with multiple stick thicknesses.