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

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.

2017 ◽  
Vol 26 (4) ◽  
pp. 331 ◽  
Author(s):  
C. M. Thomas ◽  
J. J. Sharples ◽  
J. P. Evans

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.


2018 ◽  
Vol 27 (4) ◽  
pp. 271 ◽  
Author(s):  
Neil Burrows ◽  
Malcolm Gill ◽  
Jason Sharples

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.


2008 ◽  
Author(s):  
JS Gould ◽  
WL McCaw ◽  
NP Cheney ◽  
PF Ellis ◽  
S Matthews

An effective response to bushfires relies on accurate predictions of fire behaviour, particularly the rate of spread, intensity and ‘spotting’. This field guide has been developed to provide a systematic method for assessing fuel hazard and predicting potential fire behaviour in dry eucalypt forest. It will assist in making vital decisions that ensure the protection of fire crews and the community. This guide integrates Project Vesta research findings with the Victorian Overall Fuel Hazard Guide and is applicable to dry eucalypt forests throughout southern Australia. Fuel assessment is based on the hazard scoring system employed during Project Vesta which investigated the effects of fuel age and understorey vegetation structure on fire behaviour in these forests. Information provided in this guide can be used to: Define and identify different fuel layers and components of fuel structure and hazard; Determine the hazard score of surface and near-surface fuel layers and the height of the near-surface fuel for fire spread prediction; Determine elevated fuel height for flame height prediction; and determine surface fuel hazard score and bark hazard score for spotting distance prediction. The Field Guide provides tables to predict the potential rate of spread of a bushfire burning in dry eucalypt forest under summer conditions, and can also be used to predict flame height and maximum spotting distance. The guide also allows users to determine the moisture content of fine dead fuels throughout the day, and to account for the effect of slope on the rate of spread of a fire.


2000 ◽  
Vol 30 (6) ◽  
pp. 889-899 ◽  
Author(s):  
Paulo M Fernandes ◽  
Wendy R Catchpole ◽  
Francisco C Rego

Fire behaviour modelling has been based primarily on experiments involving the measurement of a certain number of fires, where each variable is represented by an average value per fire. The main objective of this study was to examine if data collected from a microplot sampling design could be used to derive meaningful fire behaviour models. Three burns were conducted in low shrubland of Erica umbellata Loefl., and Chamaespartium tridentatum (L.) P. Gibbs in northeastern Portugal. Wind speed and aerial dead fuel moisture content varied from 5 to 27 km/h and from 14 to 21%, respectively. Rate of spread and flame length ranged from 0.3 to 14.1 m/min and from 0.2 to 3.1 m, respectively. Rate of fire spread could be described effectively in terms of an empirical model with wind speed and fuel height as independent variables. The coefficients that describe the effects of wind speed and fuel height on fire propagation were consistent with published values for similar fuel types. Flame length was strongly related to Byram's fireline intensity. Microplot sampling is not free from methodological problems, which are discussed, but can be effectively used in field studies of fire behaviour.


2017 ◽  
Vol 26 (5) ◽  
pp. 413 ◽  
Author(s):  
Miguel G. Cruz ◽  
Martin E. Alexander

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.


2007 ◽  
Vol 16 (5) ◽  
pp. 619 ◽  
Author(s):  
Beatriz Duguy ◽  
José Antonio Alloza ◽  
Achim Röder ◽  
Ramón Vallejo ◽  
Francisco Pastor

The number of large fires increased in the 1970s in the Valencia region (eastern Spain), as in most northern Mediterranean countries, owing to the fuel accumulation that affected large areas as a consequence of an intensive land abandonment. The Ayora site (Valencia province) was affected by a large fire in July 1979. We parameterised the fire growth model FARSITE for the 1979 fire conditions using remote sensing-derived fuel cartography. We simulated different fuel scenarios to study the interactions between fuel spatial distribution and fire characteristics (area burned, rate of spread and fireline intensity). We then tested the effectiveness of several firebreak networks on fire spread control. Simulations showed that fire propagation and behaviour were greatly influenced by fuel spatial distribution. The fragmentation of large dense shrubland areas through the introduction of wooded patches strongly reduced fire size, generally slowing fire and limiting fireline intensity. Both the introduction of forest corridors connecting woodlands and the promotion of complex shapes for wooded patches decreased the area burned. Firebreak networks were always very effective in reducing fire size and their effect was enhanced in appropriate fuel-altered scenarios. Most firebreak alternatives, however, did not reduce either rate of fire spread or fireline intensity.


2009 ◽  
Vol 18 (6) ◽  
pp. 698 ◽  
Author(s):  
Paulo M. Fernandes ◽  
Hermínio S. Botelho ◽  
Francisco C. Rego ◽  
Carlos Loureiro

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.


1995 ◽  
Vol 5 (3) ◽  
pp. 153 ◽  
Author(s):  
JL Dupuy

Laboratory fire experiments were conducted in both Pinus pinaster and Pinus halepensis litters in order to investigate the effect of slope on fire behaviour for different levels of fuel load. Simulated slopes ranged between -30 degrees and +30 degrees. The results are reported in terms of rate of spread and rate of mass loss when observed fire was quasi-steady. Upslope fires were observed, on the present devices, to be unsteady, and their flame to be three-dimensionnal, when slope and fuel load exceeded certain limits. The heat transfers involved in the explanation of the observed behaviours are discussed, especially on the base of the quite different results obtained in the two tested fuel. beds.


1995 ◽  
Vol 5 (1) ◽  
pp. 43 ◽  
Author(s):  
T Beer

A simple geometrical model of fire spread through arrays of vertically mounted fuel elements performs well in the absence of wind. The theory assumes that an adjacent fuel element ignites when the flame from the previous fuel element moves downward sufficiently that its temperature isotherm corresponding to the temperature of ignition intersects the top of the adjacent fuel element. This simple geometrical model is extended to incorporate the effects of wind, and its predictions are compared to wind tunnel observations of burning arrays. The model performs well at low wind speeds, but underestimates the wind speed at which the flame makes contact with adjacent fuel elements. The reason for this underestimate is likely to arise because of a weakness in one or more of the assumptions concerning, (1) the laminar nature of the flame, (2) the constancy of the flame height as the wind increases, or (3) the existence of a constant ignition temperature. The most significant finding is that this simple conceptual theory indicates that the rate of spread of a fire front as a result of wind is unlikely to be a simple function such as a power-law or an exponential, but is likely to be the solution to a set of differential equations that can be approximated by such simple functions over a portion of their range.


2016 ◽  
Vol 25 (10) ◽  
pp. 1048 ◽  
Author(s):  
Michael Storey ◽  
Owen Price ◽  
Elizabeth Tasker

We analysed the influence of weather, time since fire (TSF) and topography on the occurrence of crown fire, as mapped from satellite imagery, in 23 of the largest wildfires in dry sclerophyll forests in eastern Australia from 2002 to 2013. Fires were analysed both individually and as groups. Fire weather was the most important predictor of crown consumption. TSF (a surrogate for fuel accumulation) had complex nonlinear effects that varied among fires. Crown fire likelihood was low up to 4 years post-fire, peaked at ~10 years post-fire and then declined. There was no clear indication that recent burning became more or less effective as fire weather became more severe. Steeper slope reduced crown fire likelihood, contrary to the assumptions of common fire behaviour equations. More exposed areas (ridges and plains) had higher crown fire likelihood. Our results suggest prescribed burning to maintain an average of 10 years’ TSF may actually increase crown fire likelihood, but burning much more frequently can be effective for risk reduction. Our results also suggest the effects of weather, TSF and slope are not adequately represented in the underlying equations of most fire behaviour models, potentially leading to poor prediction of fire spread and risk.


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