Criteria and methodology for evaluating aerial wildfire suppression

2013 ◽  
Vol 22 (8) ◽  
pp. 1144 ◽  
Author(s):  
Matt P. Plucinski ◽  
Elsa Pastor
Keyword(s):  
Field Experiments ◽  
Cost Benefit ◽  
Fire Spread ◽  
Delivery Systems ◽  
Drop Impact ◽  
Fire Behaviour ◽  
Infrared Imagery ◽  
Causal Factors ◽  
Wildfire Suppression

Aircraft are often used to drop suppressants and retardants to assist wildfire containment. Drop effectiveness has rarely been measured due to the difficulties in collecting data from wildfires and running field experiments and the absence of definitions and measures. This paper presents a set of criteria and methodologies for evaluating the effectiveness of aerial suppression drops. These consider drop placement, coverage and effect on fire behaviour. This paper also details drop site and delivery conditions that are required for determining causal factors that influence drop effectiveness and allow drops to be compared. Examples of drop impact evaluations made during experimental fires are used to demonstrate these methodologies. The main methods proposed are based on the analysis of orthorectified airborne infrared imagery of drops, which can be used to measure drop dimensions, proximity to fire perimeter and their effect on fire spread. These evaluations can be used to compare tactics, suppressants and delivery systems and to inform cost–benefit analyses of aerial suppression.

Physical modelling of forest fire spreading through heterogeneous fuel beds

2011 ◽  
Vol 20 (5) ◽  
pp. 625 ◽  
Author(s):  
Albert Simeoni ◽  
Pierre Salinesi ◽  
Frédéric Morandini
Keyword(s):  
Field Experiments ◽  
Heterogeneous Medium ◽  
Reaction Diffusion ◽  
Physical Modelling ◽  
Fire Spread ◽  
Physical Models ◽  
Fire Intensity ◽  
Fire Behaviour ◽  
Fire Front ◽  
Fire Spreading

Vegetation cover is a heterogeneous medium composed of different kinds of fuels and non-combustible parts. Some properties of real fires arise from this heterogeneity. Creating heterogeneous fuel areas may be useful both in land management and in firefighting by reducing fire intensity and fire rate of spread. The spreading of a fire through a heterogeneous medium was studied with a two-dimensional reaction–diffusion physical model of fire spread. Randomly distributed combustible and non-combustible square elements constituted the heterogeneous fuel. Two main characteristics of the fire were directly computed by the model: the size of the zone influenced by the heat transferred from the fire front and the ignition condition of vegetation. The model was able to provide rate of fire spread, temperature distribution and energy transfers. The influence on the fire properties of the ratio between the amount of combustible elements and the total amount of elements was studied. The results provided the same critical fire behaviour as described in both percolation theory and laboratory experiments but the results were quantitatively different because the neighbourhood computed by the model varied in time and space with the geometry of the fire front. The simulations also qualitatively reproduced fire behaviour for heterogeneous fuel layers as observed in field experiments. This study shows that physical models can be used to study fire spreading through heterogeneous fuels, and some potential applications are proposed about the use of heterogeneity as a complementary tool for fuel management and firefighting.

Grassfires

2008 ◽  
Author(s):  
Phil Cheney ◽  
Andrew Sullivan
Keyword(s):  
Diffusion Flames ◽  
Fire Suppression ◽  
Fire Spread ◽  
Personal Safety ◽  
Fire Behaviour ◽  
Ecological Processes ◽  
Rate Of Spread ◽  
Turbulent Diffusion Flames ◽  
Wildfire Suppression ◽  
The Impact

Grassfires: Fuel, Weather and Fire Behaviour presents information from CSIRO on the behaviour and spread of fires in grasslands. This second edition follows over 10 years of research aimed at improving the understanding of the fundamental processes involved in the behaviour of grassfires. The book covers all aspects of fire behaviour and spread in the major types of grasses in Australia. It examines the factors that affect fire behaviour in continuous grassy fuels; fire in spinifex fuels; the effect of weather and topography on fire spread; wildfire suppression strategies; and how to reconstruct grassfire spread after the fact. The three meters designed by CSIRO for the prediction of fire danger and rate of spread of grassfires are explained and their use and limitations discussed. This new edition expands the discussion of historical fires including Aboriginal burning practices, the chemistry of combustion, and the structure of turbulent diffusion flames. It also examines fire safety, including the difficulty of predicting wind strength and direction and the impact of threshold wind speed on safe fire suppression. Myths and fallacies about fire behaviour are explained in relation to their impact on personal safety and survival. Grassfires will be a valuable reference for rural fire brigade members, landholders, fire authorities, researchers and those studying landscape and ecological processes.

Development and validation of a model for predicting fire behaviour in spinifex grasslands of arid Australia

2018 ◽  
Vol 27 (4) ◽  
pp. 271 ◽  
Author(s):  
Neil Burrows ◽  
Malcolm Gill ◽  
Jason Sharples
Keyword(s):  
Prescribed Burning ◽  
Weather Conditions ◽  
Fire Spread ◽  
Flame Height ◽  
Mitigation Measures ◽  
Fire Behaviour ◽  
Rate Of Spread ◽  
Wide Range ◽  
Wildfire Suppression ◽  
Fuel Moisture Content

Large wildfires are common in spinifex grasslands of arid Australia. Threat mitigation measures including fire preparedness, prescribed burning and wildfire suppression are greatly enhanced by the ability to predict fire behaviour. The new spinifex fire behaviour model presented here was developed and validated from 186 experimental fires across a wide range of fuel and weather conditions. Because spinifex fuels are discontinuous, modelling is a two-step process; once ignition is achieved, the first step is to determine the likelihood of fire spread, which is dependent on conditions of wind speed, fuel cover and fuel moisture content. If spread thresholds are met, the second step is to predict rate of spread and flame height using the same three independent variables. Thirty-six of the 186 experimental fires not used in modelling were used to validate the model, which proved to be reasonably accurate and an improvement on the previous model.

Mantras of wildland fire behaviour modelling: facts or fallacies?

2017 ◽  
Vol 26 (11) ◽  
pp. 973 ◽  
Author(s):  
Miguel G. Cruz ◽  
Martin E. Alexander ◽  
Andrew L. Sullivan
Keyword(s):  
Wildland Fire ◽  
Original Data ◽  
Fire Spread ◽  
Empirical Models ◽  
Physical Models ◽  
Fire Behaviour ◽  
Fire Science ◽  
Current State ◽  
Valid Data ◽  
Insight Into

Generalised statements about the state of fire science are often used to provide a simplified context for new work. This paper explores the validity of five frequently repeated statements regarding empirical and physical models for predicting wildland fire behaviour. For empirical models, these include statements that they: (1) work well over the range of their original data; and (2) are not appropriate for and should not be applied to conditions outside the range of the original data. For physical models, common statements include that they: (3) provide insight into the mechanisms that drive wildland fire spread and other aspects of fire behaviour; (4) give a better understanding of how fuel treatments modify fire behaviour; and (5) can be used to derive simplified models to predict fire behaviour operationally. The first statement was judged to be true only under certain conditions, whereas the second was shown not to be necessarily correct if valid data and appropriate modelling forms are used. Statements three through five, although theoretically valid, were considered not to be true given the current state of knowledge regarding fundamental wildland fire processes.

Modelling the rate of fire spread and uncertainty associated with the onset and propagation of crown fires in conifer forest stands

2017 ◽  
Vol 26 (5) ◽  
pp. 413 ◽  
Author(s):  
Miguel G. Cruz ◽  
Martin E. Alexander
Keyword(s):  
Monte Carlo ◽  
Average Rate ◽  
Fire Spread ◽  
Prediction Errors ◽  
Crown Fire ◽  
Conifer Forest ◽  
Fire Behaviour ◽  
Crown Fires ◽  
Deterministic Modelling ◽  
Eastern Australia

Crown fires are complex, unstable phenomena dependent on feedback mechanisms between the combustion products of distinct fuel layers. We describe non-linear fire behaviour associated with crowning and the uncertainty they cause in fire behaviour predictions by running a semiphysical modelling system within a simple Monte Carlo simulation framework. The method was able to capture the dynamics of passive and active crown fire spread regimes, providing estimates of average rate of spread and the extent of crown fire activity. System outputs were evaluated against data collected from a wildfire that occurred in a radiata pine plantation in south-eastern Australia. The Monte Carlo method reduced prediction errors relative to the more commonly used deterministic modelling approach, and allowed a more complete description of the level of crown fire behaviour to expect. The method also provides uncertainty measures and probabilistic outputs, extending the range of questions that can be answered by fire behaviour models.

Project Vesta: Fire in Dry Eucalypt Forest

2008 ◽  
Author(s):  
JS Gould ◽  
WL McCaw ◽  
NP Cheney ◽  
PF Ellis ◽  
IK Knight ◽  
...  
Keyword(s):  
Wind Speed ◽  
Fire Spread ◽  
Fire Behaviour ◽  
Understorey Vegetation ◽  
Eucalypt Forest ◽  
Age Related ◽  
Vegetation Structures ◽  
Eucalypt Forests ◽  
The Relationship ◽  
New Algorithms

Project Vesta was a comprehensive research project to investigate the behaviour and spread of high-intensity bushfires in dry eucalypt forests with different fuel ages and understorey vegetation structures. The project was designed to quantify age-related changes in fuel attributes and fire behaviour in dry eucalypt forests typical of southern Australia. The four main scientific aims of Project Vesta were: To quantify the changes in the behaviour of fire in dry eucalypt forest as fuel develops with age (i.e. time since fire); To characterise wind speed profiles in forest with different overstorey and understorey vegetation structure in relation to fire behaviour; To develop new algorithms describing the relationship between fire spread and wind speed, and fire spread and fuel characteristics including load, structure and height; and to develop a National Fire Behaviour Prediction System for dry eucalypt forests. These aims have been addressed through a program of experimental burning and associated studies at two sites in the south-west of Western Australia.

Fire behaviour in wheat crops – effect of fuel structure on rate of fire spread

2020 ◽  
Vol 29 (3) ◽  
pp. 258 ◽  
Author(s):  
Miguel G. Cruz ◽  
Richard J. Hurley ◽  
Rachel Bessell ◽  
Andrew L. Sullivan
Keyword(s):  
Experimental Study ◽  
Prediction Models ◽  
Fire Spread ◽  
Propagation Rate ◽  
Forward Rate ◽  
Fire Behaviour ◽  
Natural Grass ◽  
Spread Model ◽  
Crop Condition ◽  
Fire Spread Model

A field-based experimental study was conducted in 50×50m square plots to investigate the behaviour of free-spreading fires in wheat to quantify the effect of crop condition (i.e. harvested, unharvested and harvested and baled) on the propagation rate of fires and their associated flame characteristics, and to evaluate the adequacy of existing operational prediction models used in these fuel types. The dataset of 45 fires ranged from 2.4 to 10.2kmh−1 in their forward rate of fire spread and 3860 and 28000 kWm−1 in fireline intensity. Rate of fire spread and flame heights differed significantly between crop conditions, with the unharvested condition yielding the fastest spreading fires and tallest flames and the baled condition having the slowest moving fires and lowest flames. Rate of fire spread in the three crop conditions corresponded directly with the outputs from the models of Cheney et al. (1998) for grass fires: unharvested wheat → natural grass; harvested wheat (~0.3m tall stubble) → grazed or cut grass; and baled wheat (<0.1m tall stubble) → eaten-out grass. These models produced mean absolute percent errors between 21% and 25% with reduced bias, a result on par with the most accurate published fire spread model evaluations.

Ignition and fire spread thresholds in gorse (Ulex europaeus)

2010 ◽  
Vol 19 (5) ◽  
pp. 589 ◽  
Author(s):  
Stuart A. J. Anderson ◽  
Wendy R. Anderson
Keyword(s):  
Moisture Content ◽  
Field Experiments ◽  
Fire Management ◽  
Fire Spread ◽  
Operational Experience ◽  
Management Planning ◽  
Near Surface ◽  
Ulex Europaeus ◽  
Fuel Layer ◽  
Major Variable

Field experiments were carried out in stands of gorse (Ulex europaeus L.) in New Zealand to determine the conditions under which fires would both ignite and spread. Research and operational experience in shrub fuels suggest that there is a clear difference between conditions that support ignition only (fuel ignites but does not spread beyond a single bush or clump) and conditions that are conducive to fire spread (fuel ignites and develops into a spreading fire). It is important for fire management agencies to be equipped with knowledge of these thresholds, because the different conditions require different levels of preparedness and response. Results indicate that the major variable influencing both fire ignition and fire spread development in gorse is the moisture content of the elevated dead fine fuel layer. Fires were observed to spread successfully in this elevated fuel layer only, independently of the surface fuels and the near-surface fuels. Elevated dead fuels failed to ignite at a moisture content of greater than 36%, and ignition only resulted in a spreading fire at moisture contents below 19%. The results correlate well with field observations and fire practitioners’ experience in these fuels, and provide reliable guidelines for fire management planning.

Sensitivity of a surface fire spread model and associated fire behaviour fuel models to changes in live fuel moisture

2007 ◽  
Vol 16 (4) ◽  
pp. 503 ◽  
Author(s):  
W. Matt Jolly
Keyword(s):  
Fire Spread ◽  
Fuel Moisture ◽  
Fire Behaviour ◽  
Surface Fire ◽  
Fuel Model ◽  
Spread Model ◽  
Fuel Models ◽  
Live Fuel Moisture ◽  
Behaviour Models ◽  
Fire Spread Model

Fire behaviour models are used to assess the potential characteristics of wildland fires such as rates of spread, fireline intensity and flame length. These calculations help support fire management strategies while keeping fireline personnel safe. Live fuel moisture is an important component of fire behaviour models but the sensitivity of existing models to live fuel moisture has not been thoroughly evaluated. The Rothermel surface fire spread model was used to estimate key surface fire behaviour values over a range of live fuel moistures for all 53 standard fuel models. Fire behaviour characteristics are shown to be highly sensitive to live fuel moisture but the response is fuel model dependent. In many cases, small changes in live fuel moisture elicit drastic changes in predicted fire behaviour. These large changes are a result of a combination of the model-calculated live fuel moisture of extinction, the effective wind speed limit and the dynamic load transfer function of some of the fuel models tested. Surface fire spread model sensitivity to live fuel moisture changes is discussed in the context of predicted fire fighter safety zone area because the area of a predicted safety zone may increase by an order of magnitude for a 10% decrease in live fuel moisture depending on the fuel model chosen.

Measuring fire spread rates from repeat pass airborne thermal infrared imagery

2014 ◽  
Vol 5 (9) ◽  
pp. 803-812 ◽  
Author(s):  
Douglas A. Stow ◽  
Philip J. Riggan ◽  
Emanual J. Storey ◽  
Lloyd L. Coulter
Keyword(s):  
Thermal Infrared ◽  
Fire Spread ◽  
Infrared Imagery ◽  
Thermal Infrared Imagery
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