The Role of Canopy Turbulence in Wildland Fire Behavior

Numerous models and simulations exist for characterizing and predicting wildland fire behavior. The U.S. Forest Service (USFS) and other organizations have devoted decades of research to identifying the parameters that affect fire movement, rate of spread, and direction of spread across geographic terrain. While this research is invaluable to the firefighting community, due to computational constraints, these models do not run in real time or against imagery at time-of-collect, and therefore do little to assist the firefighter and first responders on the ground during a wildland fire event. We present the first part of a multi-step automated computational methodology to characterize fire behavior and rate of spread in real time across any geographic terrain. This first step is the classification and segmentation of the wildland fire in Wide Area Motion Imagery (WAMI) using Machine Learning (ML) methods. The continuation of this research, detailed herein, will involve training a more robust, purpose-built Recurrent Neural Network architecture incorporating many of the parameters the USFS has been studying for decades. The goal of this research is to deploy models using ‘lite’ ML frameworks on edge devices, mounted on collection platforms for real-time decision support for firefighting operations as imagery and other data are being collected during a wildland fire event.

Effects of slope steepness and cross-slope wind speed on fire spreading behavior for various vegetation

Interactive multimedia technology has been utilized in the development of a CD-ROM based wildland fire safety training course, Wildland Fire – Safety on the Fireline. Interactive multimedia technology allows delivery of training to a large number of students on a consistent basis. In addition, cost savings can be achieved through reduced learning time, reduced travel, minimal use of instructors, and most of all, through retention of knowledge as a result of using multimedia. The course, Wildland Fire – Safety on the Fireline, was developed and reviewed by a national team of specialists in wildland fire behavior and wildland fire safety with the intent of reducing and/or eliminating injuries and fatalities associated with the suppression of wildland fires. Wildland Fire – Safety on the Fireline focuses on due diligence, situational awareness, entrapment survival, health, equipment, and hazards encountered when working on the fireline. Each of the four sections comprising the course is followed by a board game test in preparation for a final test that is tracked by the computer. Key words: Canada, computer applications, fire behavior, fire entrapment avoidance, firefighter fatalities, firefighter physiology, fire suppression, fire survival, personal protective equipment, risk management, safe work practices, situational awareness, wildfire case studies, wildland firefighting, wildland-urban interface.

Wildland fires have an irreplaceable role in sustaining many of our forests, shrublands and grasslands. They can be used as controlled burns or occur as free-burning wildfires, and can sometimes be dangerous and destructive to fauna, human communities and natural resources. Through scientific understanding of their behaviour, we can develop the tools to reliably use and manage fires across landscapes in ways that are compatible with the constraints of modern society while benefiting the ecosystems. The science of wildland fire is incomplete, however. Even the simplest fire behaviours – how fast they spread, how long they burn and how large they get – arise from a dynamical system of physical processes interacting in unexplored ways with heterogeneous biological, ecological and meteorological factors across many scales of time and space. The physics of heat transfer, combustion and ignition, for example, operate in all fires at millimetre and millisecond scales but wildfires can become conflagrations that burn for months and exceed millions of hectares. Wildland Fire Behaviour: Dynamics, Principles and Processes examines what is known and unknown about wildfire behaviours. The authors introduce fire as a dynamical system along with traditional steady-state concepts. They then break down the system into its primary physical components, describe how they depend upon environmental factors, and explore system dynamics by constructing and exercising a nonlinear model. The limits of modelling and knowledge are discussed throughout but emphasised by review of large fire behaviours. Advancing knowledge of fire behaviours will require a multidisciplinary approach and rely on quality measurements from experimental research, as covered in the final chapters.

Wildland fires are among the most complicated environmental phenomena to model. Fire behavior models are commonly used to predict the direction and rate of spread of wildland fires based on fire history, fuel, and environmental conditions; however, more sophisticated computational fluid dynamic models are now being developed. This quantitative analysis of fire as a fluid dynamic phenomenon embedded in a highly turbulent flow is beginning to reveal the combined interactions of the vegetative structure, combustion-driven convective effects, and atmospheric boundary layer processes. This book provides an overview of the developments in modeling wildland fire dynamics and the key dynamical processes involved. Mathematical and dynamical principles are presented, and the complex phenomena that arise in wildland fire are discussed. Providing a state-of-the-art survey, it is a useful reference for scientists, researchers, and graduate students interested in wildland fire behavior from a broad range of fields.

Thermocouple probes have long been standard equipment for wildland fire scientists. But despite substantial advancements in the electronic datalogger technology necessary to read and store data from thermocouples, the effective cost per thermocouple sensor of commercial systems has not decreased such that most researchers can afford to deploy enough sensors to account for the high degree of variability in wildland fire behavior. Because the equipment must endure the extreme conditions of wildland fire, is unlikely that any thermocouple datalogger system will be considered “cheap.” However, the growing number of applications of open-source, do-it-yourself (DIY) microcontroller systems in scientific research suggests these products might be employed in thermocouple datalogging systems if (1) their performance can be shown to be comparable to commercial systems and (2) they can be protected from exposure in the wildland fire environment. In this paper, we compare the performance of an Arduino MEGA microcontroller board relative to a Campbell Scientific CR1000, reading standard K-type metal overbraided ceramic fiber insulated thermocouple probes, under the constant temperature of a drying oven and the variable flame of a Bunsen burner. In both comparisons, we found that the variability among individual thermocouples, which are known to have a $$\pm\, 2\,^{\circ }\hbox {C}{-}6\,^{\circ }\hbox {C}$$ margin of error, was greater than between the dataloggers. We also describe a compact and mobile Arduino-based system capable of recording wildland fire flame temperatures in agris. In considering these three systems, it is clear that Arduino-based open-source, DIY components can support a compact, low-cost datalogger that accommodates more sensors for lower cost than proprietary commercial systems with no sacrifice in data quality. The combination of low-cost, multi-sensor units can contribute to better understanding of variability in wildland fire behavior.

Wildland fires are a critical Earth-system process that impacts human populations in each settled continent[...]

Are the applications of wildland fire behaviour models getting ahead of their evaluation again?

New technologies have transformed our understanding of wildland fire behavior, providing a better ability to observe them from a variety of platforms, simulate their growth with computational models, and interpret their frequency and controls in a global context. These tools have shown how wildland fires are among the extremes of weather events and can produce behaviors such as fire whirls, blow-ups, bursts of flame along the surface, and winds ten times stronger than ambient conditions, all of which result from the interactions between a fire and its atmospheric environment. I will highlight current research in integrated weather -- wildland fire computational modeling, fire detection, and observation, and their application to understanding and prediction. Coupled weather-wildland fire models tie numerical weather prediction models to wildland fire behavior modules to simulate the impact of a fire on the atmosphere and the subsequent feedback of these fire-induced winds on fire behavior, i.e. how a fire creates its own weather. NCAR's CAWFE® modeling system has been used to explain fundamental fire phenomena and reproduce the unfolding of past fire events. Recent work, in which CAWFE has been integrated with satellite-based active fire detection data, addresses the challenges of applying it as an operational forecast tool. This newer generation of tools brought many goals within sight -- rapid fire detection, nearly ubiquitous monitoring, and recognition that many of the distinctive characteristics of fire events are reproducible and perhaps predictable in real time. Concurrently, these more complex tools raise new challenges. I conclude with innovative model-data fusion approaches to overcome some of these remaining puzzles.

The behaviour of wildland fires and the dispersion of smoke from those fires can be strongly influenced by atmospheric turbulent flow. The science to support that assertion has developed and evolved over the past 100+ years, with contributions from laboratory and field observations, as well as modelling experiments. This paper provides a synthesis of the key laboratory- and field-based observational studies focused on wildland fire and atmospheric turbulence connections that have been conducted from the early 1900s through 2021. Included in the synthesis are reports of anecdotal turbulence observations, direct measurements of ambient and fire-induced turbulent flow in laboratory and wildland environments, and remote sensing measurements of fire-induced turbulent plume dynamics. Although considerable progress has been made in advancing our understanding of the connections between atmospheric turbulence and wildland fire behaviour and smoke dispersion, gaps in that understanding still exist and are discussed to conclude the synthesis.

Judicial wildland fire prevention and management requires precise information on fuel characteristics and spatial distribution of the various vegetation types present in an area. The aim of this study was to present an integrated approach to forest fire management, combining local-scale fuel-type mapping from very high spatial resolution imagery with fire behavior simulation. The specific objectives were (i) to develop a detail site-specific fuel model in a Mediterranean area that is suitable for fire behavior prediction; (ii) to produce a detailed local-scale fuel-type map with an object-based approach; and (iii) to generate accurate fire behavior maps. The spatial extent of the different fuel types of a forested landscape in northern Greece characterized by heterogeneous vegetation and topography was determined using a Quickbird image. Site-specific fuel models were created by measuring fuel parameters in representative natural fuel complexes. Following necessary preprocessing of the image to compensate for geometric errors, multiscale components of the scene were delineated through a segmentation algorithm. The resulting image objects were assigned to respective fuel types using a CART statistical model with an overall accuracy over 80%. The FARSITE fire simulation model was applied to simulate potential wildland fire growth and behavior. Utilizing the spatial database capabilities of geographic information systems, FARSITE allows the user to simulate the spatial and temporal spread and behavior of a fire burning in heterogeneous terrain, fuels, and weather.

Key message: We have explored the impacts of forest thinning on wildland fire behavior using a process based model. Simulating different degrees of thinning, we found out that forest thinning should be conducted cautiously as there could be a wide range of outcomes depending upon the post-thinning states of fuel availability, fuel connectivity, fuel moisture and micrometeorological features such as wind speed. Context: There are conflicting reports in the literature regarding the effectiveness of forest thinning. Some studies have found that thinning reduces fire severity, while some studies have found that thinning might lead to enhanced fire severity. Aims: Our goal was to evaluate if both of these outcomes are possible post thinning operations and what are the limiting conditions for post thinning fire behavior. Methods: We used a process based model to simulate different degrees of thinning systematically, under two different conditions, where the canopy fuel moisture was unchanged and when the canopy fuel moisture was also depleted post thinning. Both of these scenarios are reported in the literature. Results: We found out that a low degree of thinning can indeed increase fire intensity, especially if the canopy fuel moisture is low. A high degree of thinning was effective in reducing fire intensity. However, thinning also increased rate of spread under some conditions. Interestingly, both intensity and rate of spread were dependent on the competing effects of increased wind speed, fuel loading and canopy fuel moisture. Conclusion: We were able to find the limits of fire behavior post thinning and actual fire behavior is likely to be somewhere in the middle of the theoretical extremes explored in this work. The actual fire behavior post thinning should depend on the site specific conditions which would determine the outcome of the interplay among the aforementioned conditions. The work also highlights that policymakers should be careful about fine scale canopy architectural attributes and micrometeorological aspects when planning fuel treatment operations.

Wildland fires, especially the large ones, are becoming a growing problem in the climate changing world. More frequent and long-lasting drought conditions accompanied by high temperatures and heat waves, significantly increase fuel flammability, particularly during the summer period. The wildland fire occurrence and behaviour are to a large degree weather driven and thus strongly depend on the meteorological parameters such as humidity, temperature, precipitation, and wind speed, as well as on the amount of fuel load. The relationship between weather and fire occurrence and behaviour is included in Canadian Fire Weather Index system, which has been used in Croatia for fire risk assessment since 1982. In this paper, the characteristics of the Fire Weather Index components are analysed for large fires in the Adriatic region of Croatia. Fire weather indices were evaluated for 103 wildland fires with a burned area over 400 ha that occurred during summer fire seasons in the period from 2003 to 2021. Obtained median values of the moisture indices, as well as the fire behaviour indices (FFMC 93, DMC 139, DC 649, ISI 13, BUI 182 and FWI 45) showed values designated as high and very high in the available literature. The climate change will continue to increase the fire risk, and thus the possibility of large fires, so this analysis can provide a baseline for improvements and recalibration of the fire danger classes in the Adriatic area of Croatia. Along with the improved fire weather warnings, this will give a better and more accurate information about the increased wildland fire risk and the possibility of large fires.

Wildland fire spread and behaviour are complex phenomena owing to both the number of involved physico-chemical factors, and the non-linear relationship between variables. Spain is plagued by forest and brush fires every summer, when the extremely dry weather sets in along with high temperatures. The use of fire behaviour models requires the availability of high resolution environmental and fuel data; in the absence of real data, errors on the simulated fire spread can be compounded to affect the spatial and temporal accuracy of predicted data. The effect of input values on the accuracy of WRF-FIRE simulations was evaluated to assess the capabilities of the new system for wildland fire in accurately forecasting fire behaviour. The results confirm that the use of accurate meteorological data and a custom fuel moisture content model is crucial to obtain precise simulations of fire behaviour.

Wildfires are growing in destructive power, and accurately predicting the spread and intensity of wildland fire is essential for managing ecological and societal impacts. No current operational models used for fire behavior prediction resolve critical fire-atmospheric coupling or nonlocal influences of the fire environment, rendering them inadequate in accounting for the range of wildland fire behavior scenarios under increasingly novel fuel and climate conditions. Here, we present a new perspective on a dominant fire-atmospheric feedback mechanism, which we term wildland fire entrainment (WFE). WFE is the fluid motion associated with air movement toward the fire driven by pressure gradients created by buoyant updrafts, and through integration of nonlocal influences on fire behavior, it plays a pivotal role in predicting wildland fire spread. WFE dynamically integrates all aspects of a fire's surrounding environment, fuels, topography, winds and fire line geometry to rate and pattern of fire spread and energy release. Because WFE explicitly incorporates fire-induced buoyancy, it links recent advances in idealized combustion research to the dynamic and highly variable wildland fire environment. Incorporating WFE into emerging fire models will allow more robust predictions of fire behavior and spread.