Modelling the effects of landscape fuel treatments on fire growth and behaviour in a Mediterranean landscape (eastern Spain)

2007 ◽  
Vol 16 (5) ◽  
pp. 619 ◽  
Author(s):  
Beatriz Duguy ◽  
José Antonio Alloza ◽  
Achim Röder ◽  
Ramón Vallejo ◽  
Francisco Pastor
Keyword(s):  
Spatial Distribution ◽  
Fire Spread ◽  
Fire Growth ◽  
Fire Size ◽  
Fire Propagation ◽  
Area Burned ◽  
Rate Of Spread ◽  
Mediterranean Countries ◽  
Fuel Accumulation ◽  
Fire Characteristics

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.

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.

Calculation of fire spread rates across random landscapes

2003 ◽  
Vol 12 (2) ◽  
pp. 167 ◽  
Author(s):  
Mark A. Finney
Keyword(s):  
Travel Time ◽  
Growth Rates ◽  
Fire Spread ◽  
Harmonic Mean ◽  
Fire Growth ◽  
Fire Size ◽  
Spread Rate ◽  
Fuel Treatments ◽  
Fuel Mixtures

An approach is presented for approximating the expected spread rate of fires that burn across 2-dimensional landscapes with random fuel patterns. The method calculates a harmonic mean spread rate across a small 2-dimensional grid that allows the fire to move forward and laterally. Within this sample grid, all possible spatial fuel arrangements are enumerated and the spread rate of an elliptical fire moving through the cells is found by searching for the minimum travel time. More columns in the sample grid are required for accurately calculating expected spread rates where very slow-burning fuels are present, because the fire must be allowed to move farther laterally around slow patches. This calculation can be used to estimate fire spread rates across spatial fuel mixtures provided that the fire shape was determined from wind and slope. Results suggest that fire spread rates on random landscapes should increase with fire size and that random locations of fuel treatments would be inefficient in changing overall fire growth rates.

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.

The Rhode Island Nightclub Fire: Some Calculations Related to the Evolution of Fire and Smoke

2006 ◽  
Author(s):  
David G. Lilley
Keyword(s):  
Rhode Island ◽  
Scientific Information ◽  
Fire Spread ◽  
Generation Rate ◽  
Fire Growth ◽  
Fire Size ◽  
Smoke Generation ◽  
Key Features

The recent fire at a Rhode Island nightclub unfortunately made it very clear that catastrophic fires still occur, and that many people still don’t realize just how quickly a seemingly simple fire can grow rapidly into an inescapable furious inferno. Discussion centers on the rapidity of fire growth in many situations, how experiments and modeling have helped to characterize the events, and how the population at large still does not appreciate the immense fire dangers. The technical and scientific information about ignition, fire spread and analysis helps us to understand the amalgamation of key features of the incident. Calculations are shown of how the fire size, total evolution of smoke, smoke generation rate, and smoke level all vary with time, for situations of various rates of fire growth.

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.

Fire Growth and Acceleration

1997 ◽  
Vol 7 (1) ◽  
pp. 1 ◽  
Author(s):  
NP Cheney ◽  
JS Gould
Keyword(s):  
Equilibrium State ◽  
Weather Conditions ◽  
Fire Growth ◽  
Fire Size ◽  
Acceleration Phase ◽  
Characteristic Curves ◽  
Rate Of Spread ◽  
Steady Rate ◽  
In Fire ◽  
Practical Implications

The use of the terms "growth" and "acceleration" appears to be inconsistent in the literature and we believe this inconsistency has hindered our understanding of behaviour in the early stages of a fire. The development of a fire from a point ignition to some equilibrium state and the associated increase in fire size and intensity has been referred to variously as the fire growth (Pyne 1984); build-up (Luke and McArthur 1978); or acceleration (Chandler et al. 1983) phase of the fire. More specifically the "acceleration phase" has been used to describe the increase in rate of spread from ignition to a quasi-steady rate of spread (Luke and McArthur 1978, McAlpine and Wakimoto 1991). Characteristic curves showing the increase in rate of spread are illustrated for different fuel and weather conditions (Luke and McArthur 1978). Hypothetical models to describe these curves have been proposed by Cheney and Bary (1969), Van Wagner (unpublished) and McAlpine and Wakimoto (1991). They have been called acceleration curves and acceleration models. The terms growth and acceleration, however, represent different concepts that are not interchangeable. We would like to clarify these concepts and discuss the practical implications for fire managers.

scholarly journals Shrubland fire behaviour modelling with microplot data

2000 ◽  
Vol 30 (6) ◽  
pp. 889-899 ◽  
Author(s):  
Paulo M Fernandes ◽  
Wendy R Catchpole ◽  
Francisco C Rego
Keyword(s):  
Wind Speed ◽  
Field Studies ◽  
Fire Spread ◽  
Flame Length ◽  
Fire Behaviour ◽  
Fire Propagation ◽  
Average Value ◽  
Behaviour Modelling ◽  
Rate Of Spread ◽  
Behaviour Models

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.

Fire Growth in Grassland Fuels

1995 ◽  
Vol 5 (4) ◽  
pp. 237 ◽  
Author(s):  
NP Cheney ◽  
JS Gould
Keyword(s):  
Wind Speed ◽  
Fire Spread ◽  
Small Scale ◽  
Fire Growth ◽  
Spread Rate ◽  
Wind Speeds ◽  
Rate Of Spread ◽  
Steady Rate ◽  
Scale Field ◽  
Wildfire Spread

The development of grass fires originating from both point and line ignitions and burning in both open grasslands and woodlands with a grassy understorey was studied using 487 periods of fire spread and associated fuel, weather and fire-shape observations. The largest fires travelled more than 1000 m from the origin and the fastest 2-minute spread rate was over 2 m s-1. Given continuous fuel of uniform moisture content, the rate of forward spread was related to both the wind speed and the width of the head fire measured normal to the direction of fire travel. The head fire width required to achieve the potential quasi-steady rate of forward spread for the prevailing conditions increased with increasing wind speeds. These findings have important implications for relating small-scale field or laboratory measurements of fire spread to predictions of wildfire spread. The time taken to reach the potential quasi-steady rate of spread at any wind speed was highly variable. This time was strongly influenced by the frequency of changes in wind direction and the rate of development of a wide head fire.

scholarly journals Reconstruction of Grenfell Tower fire. Part 3—Numerical simulation of the Grenfell Tower disaster: Contribution to the understanding of the fire propagation and behaviour during the vertical fire spread

2019 ◽  
Vol 44 (1) ◽  
pp. 35-57 ◽  
Author(s):  
Eric Guillaume ◽  
Virginie Dréan ◽  
Bertrand Girardin ◽  
Faiz Benameur ◽  
Maxime Koohkan ◽  
...  
Keyword(s):  
Numerical Simulation ◽  
Fire Spread ◽  
Fire Propagation

Fine-Scale Fire Spread in Pine Straw

Fire ◽  
2021 ◽  
Vol 4 (4) ◽  
pp. 69
Author(s):  
Daryn Sagel ◽  
Kevin Speer ◽  
Scott Pokswinski ◽  
Bryan Quaife
Keyword(s):  
Fire Spread ◽  
Small Scale ◽  
Natural Setting ◽  
Fine Scale ◽  
Prescribed Burn ◽  
Fire Dynamics ◽  
Rate Of Spread ◽  
Scale Models ◽  
Fire Front ◽  
Visible Images

Most wildland and prescribed fire spread occurs through ground fuels, and the rate of spread (RoS) in such environments is often summarized with empirical models that assume uniform environmental conditions and produce a unique RoS. On the other hand, representing the effects of local, small-scale variations of fuel and wind experienced in the field is challenging and, for landscape-scale models, impractical. Moreover, the level of uncertainty associated with characterizing RoS and flame dynamics in the presence of turbulent flow demonstrates the need for further understanding of fire dynamics at small scales in realistic settings. This work describes adapted computer vision techniques used to form fine-scale measurements of the spatially and temporally varying RoS in a natural setting. These algorithms are applied to infrared and visible images of a small-scale prescribed burn of a quasi-homogeneous pine needle bed under stationary wind conditions. A large number of distinct fire front displacements are then used statistically to analyze the fire spread. We find that the fine-scale forward RoS is characterized by an exponential distribution, suggesting a model for fire spread as a random process at this scale.

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