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.

Got to burn to learn: the effect of fuel load on grassland fire behaviour and its management implications

2018 ◽  
Vol 27 (11) ◽  
pp. 727 ◽  
Author(s):  
Miguel G. Cruz ◽  
Andrew L. Sullivan ◽  
James S. Gould ◽  
Richard J. Hurley ◽  
Matt P. Plucinski
Keyword(s):  
Fire Spread ◽  
Flame Height ◽  
Fuel Load ◽  
Limiting Factor ◽  
Fire Behaviour ◽  
Load Effect ◽  
Fire Propagation ◽  
Rate Of Spread ◽  
Eastern Australia ◽  
Modelling Assumptions

The effect of grass fuel load on fire behaviour and fire danger has been a contentious issue for some time in Australia. Existing operational models have placed different emphases on the effect of fuel load on model outputs, which has created uncertainty in the operational assessment of fire potential and has led to end-user and public distrust of model outcomes. A field-based experimental burning program was conducted to quantify the effect of fuel load on headfire rate of spread and other fire behaviour characteristics in grasslands. A total of 58 experimental fires conducted at six sites across eastern Australia were analysed. We found an inverse relationship between fuel load and the rate of spread in grasslands, which is contrary to current, untested, modelling assumptions. This result is valid for grasslands where fuel load is not a limiting factor for fire propagation. We discuss the reasons for this effect and model it to produce a fuel load effect function that can be applied to operational grassfire spread models used in Australia. We also analyse the effect of fuel load on flame characteristics and develop a model for flame height as a function of rate of fire spread and fuel load.

Empirical modelling of surface fire behaviour in maritime pine stands

2009 ◽  
Vol 18 (6) ◽  
pp. 698 ◽  
Author(s):  
Paulo M. Fernandes ◽  
Hermínio S. Botelho ◽  
Francisco C. Rego ◽  
Carlos Loureiro
Keyword(s):  
Wind Speed ◽  
Moisture Content ◽  
Fire Spread ◽  
Fire Intensity ◽  
Fuel Moisture ◽  
Fire Behaviour ◽  
Spread Rate ◽  
Surface Fire ◽  
Rate Of Spread ◽  
Fuel Moisture Content

An experimental burning program took place in maritime pine (Pinus pinaster Ait.) stands in Portugal to increase the understanding of surface fire behaviour under mild weather. The spread rate and flame geometry of the forward and backward sections of a line-ignited fire front were measured in 94 plots 10–15 m wide. Measured head fire rate of spread, flame length and Byram’s fire intensity varied respectively in the intervals of 0.3–13.9 m min–1, 0.1–4.2 m and 30–3527 kW m–1. Fire behaviour was modelled through an empirical approach. Rate of forward fire spread was described as a function of surface wind speed, terrain slope, moisture content of fine dead surface fuel, and fuel height, while back fire spread rate was correlated with fuel moisture content and cover of understorey vegetation. Flame dimensions were related to Byram’s fire intensity but relationships with rate of spread and fine dead surface fuel load and moisture are preferred, particularly for the head fire. The equations are expected to be more reliable when wind speed and slope are less than 8 km h–1 and 15°, and when fuel moisture content is higher than 12%. The results offer a quantitative basis for prescribed fire management.

Modelling the dynamic behaviour of junction fires with a coupled atmosphere–fire model

2017 ◽  
Vol 26 (4) ◽  
pp. 331 ◽  
Author(s):  
C. M. Thomas ◽  
J. J. Sharples ◽  
J. P. Evans
Keyword(s):  
Fire Spread ◽  
Community Safety ◽  
Fire Behaviour ◽  
Ambient Conditions ◽  
Fire Model ◽  
Fire Propagation ◽  
Dynamic Propagation ◽  
Rate Of Spread ◽  
Steady Rate ◽  
In Fire

Dynamic fire behaviour involves rapid changes in fire behaviour without significant changes in ambient conditions, and can compromise firefighter and community safety. Dynamic fire behaviour cannot be captured using spatial implementations of empirical fire-spread models predicated on the assumption of an equilibrium, or quasi-steady, rate of spread. In this study, a coupled atmosphere–fire model is used to model the dynamic propagation of junction fires, i.e. when two firelines merge at an oblique angle. This involves very rapid initial rates of spread, even with no ambient wind. The simulations are in good qualitative agreement with a previous experimental study, and indicate that pyro-convective interaction between the fire and the atmosphere is the key mechanism driving the dynamic fire propagation. An examination of the vertical vorticity in the simulations, and its relationship to the fireline geometry, gives insight into this mechanism. Junction fires have been modelled previously using curvature-dependent rates of spread. In this study, however, although fireline geometry clearly influences rate of spread, no relationship is found between local fireline curvature and the simulated instantaneous local rate of spread. It is possible that such a relationship may be found at larger scales.

scholarly journals Modelling and analyzing the surface fire behaviour in Hyrcanian forest of Iran

2014 ◽  
Vol 60 (No. 9) ◽  
pp. 353-362 ◽  
Author(s):  
H. Aghajani ◽  
A. Fallah ◽  
S. Fazlollah Emadian
Keyword(s):  
Forest Floor ◽  
Forest Litter ◽  
Fire Spread ◽  
Burned Area ◽  
Hyrcanian Forest ◽  
Fire Behaviour ◽  
Surface Fire ◽  
Contour Lines ◽  
Slope Wind ◽  
The Impact

The purpose of this study was to assess the forest fire behaviour and investigate the impact of different parameters on the spread of surface fire in the Hyrcanian forest of Iran. Surface fire was simulated using mathematical models in Microsoft Visual Basic 6.0 environment during a 30-minute time period. Several parameters that contributed to the speed of surface fire such as slope, wind velocity and litter thickness in the forest floor and various types of forest litter associated with hornbeam (Carpinus betulus L.), Persian ironwood (Parrotia persica C.A.M), beech (Fagus orientalis L.) and maple (Acer velutinum L.) were investigated. The results indicated that the maximum burned area was associated with beech litter. Forest surface fire demonstrated similar behaviour for the litter types of beech and Ironwood, whereas in the case of maple and hornbeam litters, the fire spread parallelly and perpendicularly to contour lines, respectively. The burned area increased in an irregular pattern as the forest floor slope gradient was increased. Moreover, the skewed pattern of the burned area for the forest floor composed of maple, beech, ironwood andhornbeam litter was described as high, low, moderate and low, respectively. The fire spread angle in forest floor associated with maple and beech litters changed with litter thickness. Finally, litter thickness had a significant effect on the direction of fire spread and this was more prominent with hornbeam litter.  

scholarly journals Defining fire spread event days for fire-growth modelling

2011 ◽  
Vol 20 (4) ◽  
pp. 497 ◽  
Author(s):  
Justin Podur ◽  
B. Mike Wotton
Keyword(s):  
Forest Fire ◽  
Growth Models ◽  
Fire Spread ◽  
Fire Growth ◽  
Fire Behaviour ◽  
Area Burned ◽  
Rate Of Spread ◽  
Definition Of ◽  
Intensity Spread

Forest fire managers have long understood that most of a fire’s growth typically occurs on a small number of days when burning conditions are conducive for spread. Fires either grow very slowly at low intensity or burn considerable area in a ‘run’. A simple classification of days into ‘spread events’ and ‘non-spread events’ can greatly improve estimates of area burned. Studies with fire-growth models suggest that the Canadian Forest Fire Behaviour Prediction System (FBP System) seems to predict growth well during high-intensity ‘spread events’ but tends to overpredict rate of spread for non-spread events. In this study, we provide an objective weather-based definition of ‘spread events’, making it possible to assess the probability of having a spread event on any particular day. We demonstrate the benefit of incorporating this ‘spread event’ day concept into a fire-growth model based on the Canadian FBP System.

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.

scholarly journals Resolving vorticity-driven lateral fire spread using the WRF-Fire coupled atmosphere–fire numerical model

2014 ◽  
Vol 14 (9) ◽  
pp. 2359-2371 ◽  
Author(s):  
C. C. Simpson ◽  
J. J. Sharples ◽  
J. P. Evans
Keyword(s):  
High Spatial Resolution ◽  
Wildland Fire ◽  
Fire Spread ◽  
Weather Research And Forecasting ◽  
Grid Spacing ◽  
Fire Behaviour ◽  
Model Framework ◽  
Rate Of Spread ◽  
Fire Front ◽  
Vertical Grid

Abstract. Vorticity-driven lateral fire spread (VLS) is a form of dynamic fire behaviour, during which a wildland fire spreads rapidly across a steep leeward slope in a direction approximately transverse to the background winds. VLS is often accompanied by a downwind extension of the active flaming region and intense pyro-convection. In this study, the WRF-Fire (WRF stands for Weather Research and Forecasting) coupled atmosphere–fire model is used to examine the sensitivity of resolving VLS to both the horizontal and vertical grid spacing, and the fire-to-atmosphere coupling from within the model framework. The atmospheric horizontal and vertical grid spacing are varied between 25 and 90 m, and the fire-to-atmosphere coupling is either enabled or disabled. At high spatial resolutions, the inclusion of fire-to-atmosphere coupling increases the upslope and lateral rate of spread by factors of up to 2.7 and 9.5, respectively. This increase in the upslope and lateral rate of spread diminishes at coarser spatial resolutions, and VLS is not modelled for a horizontal and vertical grid spacing of 90 m. The lateral fire spread is driven by fire whirls formed due to an interaction between the background winds and the vertical circulation generated at the flank of the fire front as part of the pyro-convective updraft. The laterally advancing fire fronts become the dominant contributors to the extreme pyro-convection. The results presented in this study demonstrate that both high spatial resolution and two-way atmosphere–fire coupling are required to model VLS with WRF-Fire.

Techniques for evaluating wildfire simulators via the simulation of historical fires using the AUSTRALIS simulator

2015 ◽  
Vol 24 (6) ◽  
pp. 784 ◽  
Author(s):  
Joel K. Kelso ◽  
Drew Mellor ◽  
Mary E. Murphy ◽  
George J. Milne
Keyword(s):  
High Performance ◽  
Fire Spread ◽  
Sensitivity Analyses ◽  
Vegetation Coverage ◽  
Multiple Time ◽  
Fire Behaviour ◽  
Simulation Accuracy ◽  
Rate Of Spread ◽  
Simulation Input ◽  
Multiple Time Points

A methodology for validating fire spread simulation systems using historical fire data is presented. The key features of this methodology are (a) quantitative comparison between simulator-generated fire perimeters and fire perimeters from an independently produced fire reconstruction at multiple time points during the fire, and (b) extensive sensitivity analyses on simulation variables including simulation spatial resolution, weather, vegetation coverage and fire behaviour model selection to determine the effect of each simulation input on the simulation output. The methodology is demonstrated in a case study in which the ability of the Australis high-performance wildfire simulator to replicate a large wildfire in Western Australia was examined. Simulation accuracy was found to be lower in extreme fire danger conditions and exhibited under-prediction of the head fire rate of spread. This was caused by inaccuracies in at least one of wind speed data, vegetation data or the fire behaviour model applied; however, the source of the inaccuracy could not be further diagnosed with the available data. The gathering of accurate data during and after active wildfires would facilitate more rigorous simulator and fire behaviour model validation studies as well as more accurate prediction of ‘live’ wildfires.

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