Corrigendum to: Assessing the effect of foliar moisture on the spread rate of crown fires

2013 ◽  
Vol 22 (6) ◽  
pp. 869 ◽  
Author(s):  
Martin E. Alexander ◽  
Miguel G. Cruz
Keyword(s):  
Radiant Heat ◽  
Fire Spread ◽  
Heat Fluxes ◽  
Fuel Moisture ◽  
Conifer Forests ◽  
Spread Rate ◽  
Rate Of Spread ◽  
Crown Fires ◽  
Wide Range ◽  
Live Fuel Moisture

This paper constitutes a digest and critique of the currently available information pertaining to the influence of live fuel or foliar moisture content (FMC) on the spread rate of crown fires in conifer forests and shrublands. We review and discuss the findings from laboratory experiments and field-based fire behaviour studies. Laboratory experimentation with single needles or leaves and small conifer trees has shown an unequivocal effect of FMC on flammability metrics. A much less discernible effect of FMC on crown fire rate of spread was found in the existing set of experimental crown fires carried out in conifer forests and similarly with the far more robust database of experimental fires conducted in shrubland fuel complexes. The high convective and radiant heat fluxes associated with these fires and the lack of appropriate experimental design may have served to mask any effect of FMC or live fuel moisture on the resulting spread rate. Four theoretical functions and one empirical function used to adjust rate of fire spread for the effect of foliar or live fuel moisture were also concurrently examined for their validity over a wide range of FMC conditions with varying outcomes and relevancy. None of these model functions was found suitable for use with respect to dead canopy foliage.

Assessing the effect of foliar moisture on the spread rate of crown fires

2013 ◽  
Vol 22 (4) ◽  
pp. 415 ◽  
Author(s):  
Martin E. Alexander ◽  
Miguel G. Cruz
Keyword(s):  
Radiant Heat ◽  
Fire Spread ◽  
Heat Fluxes ◽  
Fuel Moisture ◽  
Conifer Forests ◽  
Spread Rate ◽  
Rate Of Spread ◽  
Crown Fires ◽  
Wide Range ◽  
Live Fuel Moisture

This paper constitutes a digest and critique of the currently available information pertaining to the influence of live fuel or foliar moisture content (FMC) on the spread rate of crown fires in conifer forests and shrublands. We review and discuss the findings from laboratory experiments and field-based fire behaviour studies. Laboratory experimentation with single needles or leaves and small conifer trees has shown an unequivocal effect of FMC on flammability metrics. A much less discernible effect of FMC on crown fire rate of spread was found in the existing set of experimental crown fires carried out in conifer forests and similarly with the far more robust database of experimental fires conducted in shrubland fuel complexes. The high convective and radiant heat fluxes associated with these fires and the lack of appropriate experimental design may have served to mask any effect of FMC or live fuel moisture on the resulting spread rate. Four theoretical functions and one empirical function used to adjust rate of fire spread for the effect of foliar or live fuel moisture were also concurrently examined for their validity over a wide range of FMC conditions with varying outcomes and relevancy. None of these model functions was found suitable for use with respect to dead canopy foliage.

scholarly journals Live Fuel Moisture Content: The ‘Pea Under the Mattress’ of Fire Spread Rate Modeling?

Fire ◽  
2018 ◽  
Vol 1 (3) ◽  
pp. 43 ◽  
Author(s):  
Carlos Rossa ◽  
Paulo Fernandes
Keyword(s):  
Moisture Content ◽  
Fire Spread ◽  
High Heat ◽  
Heat Fluxes ◽  
Fuel Moisture ◽  
Spread Rate ◽  
Live Fuels ◽  
Live Fuel Moisture ◽  
Live Tree ◽  
Fuel Moisture Content

Currently, there is a dispute on whether live fuel moisture content (FMC) should be accounted for when predicting a real-world fire-spread rate (RoS). The laboratory and field data results are conflicting: laboratory trials show a significant effect of live FMC on RoS, which has not been convincingly detected in the field. It has been suggested that the lack of influence of live FMC on RoS might arise from differences in the ignition of dead and live fuels: flammability trials using live leaves subjected to high heat fluxes (80–140 kW m−2) show that ignition occurs before all of the moisture is vaporized. We analyze evidence from recent studies, and hypothesize that differences in the ignition mechanisms between dead and live fuels do not preclude the use of overall fine FMC for attaining acceptable RoS predictions. We refer to a simple theory that consists of two connected hypotheses to explain why the effect of live FMC on field fires RoS has remained elusive so far: H1, live tree foliage FMC remains fairly constant over the year; and H2, the seasonal variation of live shrubs’ FMC correlates with the average dead FMC. As a result, the effect of live FMC is not easily detected by statistical analysis.

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.

A generic, empirical-based model for predicting rate of fire spread in shrublands

2015 ◽  
Vol 24 (4) ◽  
pp. 443 ◽  
Author(s):  
Wendy R. Anderson ◽  
Miguel G. Cruz ◽  
Paulo M. Fernandes ◽  
Lachlan McCaw ◽  
Jose Antonio Vega ◽  
...  
Keyword(s):  
Moisture Content ◽  
Experimental Studies ◽  
Fire Spread ◽  
Fuel Moisture ◽  
Fire Behaviour ◽  
Weather Factors ◽  
Vegetation Height ◽  
Rate Of Spread ◽  
Wide Range ◽  
Fuel Moisture Content

A shrubland fire behaviour dataset was assembled using data from experimental studies in Australia, New Zealand, Europe and South Africa. The dataset covers a wide range of heathlands and shrubland species associations and vegetation structures. Three models for rate of spread are developed using 2-m wind speed, a wind reduction factor, elevated dead fuel moisture content and either vegetation height (with or without live fuel moisture content) or bulk density. The models are tested against independent data from prescribed fires and wildfires and found to predict fire spread rate within acceptable limits (mean absolute errors varying between 3.5 and 9.1 m min–1). A simple model to predict dead fuel moisture content is evaluated, and an ignition line length correction is proposed. Although the model can be expected to provide robust predictions of rate of spread in a broad range of shrublands, the effects of slope steepness and variation in fuel quantity and composition are yet to be quantified. The model does not predict threshold conditions for continuous fire spread, and future work should focus on identifying fuel and weather factors that control transitions in fire behaviour.

A laboratory-based quantification of the effect of live fuel moisture content on fire spread rate

2016 ◽  
Vol 25 (5) ◽  
pp. 569 ◽  
Author(s):  
Carlos G. Rossa ◽  
Ricardo Veloso ◽  
Paulo M. Fernandes
Keyword(s):  
Moisture Content ◽  
Laboratory Experiments ◽  
Fire Spread ◽  
Fuel Moisture ◽  
Drying Process ◽  
Spread Rate ◽  
Rate Of Spread ◽  
Live Fuels ◽  
Fuel Moisture Content ◽  
Content Range

Observational evidence of an effect of live vegetation moisture content on fire spread rate remains extremely scarce despite the significance of fire activity in fuel complexes dominated by live components. This study assessed the moisture content effect of quasi-live fuels on fire spread rates measured in laboratory experiments. Fuel beds were built by vertically placing vegetation clippings to reproduce the natural upright fuel structure. The fuel drying process during storage resulted in a wide moisture content range (13–180%). An exponential damping function was fitted to rate of spread observations in four fuel types, indicating that rate of spread is halved by an increase in live moisture content from 50 to 180%. This effect, especially at higher moisture contents, was weaker than that predicted by theoretical formulations and from studies in mixtures of dead and live fuel.

scholarly journals Short communication: On the effect of live fuel moisture content on fire-spread rate

2018 ◽  
Vol 26 (3) ◽  
pp. eSC08 ◽  
Author(s):  
Carlos G. Rossa ◽  
Paulo M. Fernandes
Keyword(s):  
Moisture Content ◽  
Short Communication ◽  
Experimental Studies ◽  
Fire Spread ◽  
Fuel Moisture ◽  
Rate Of Spread ◽  
Mediterranean Shrubland ◽  
Live Fuels ◽  
Live Fuel Moisture ◽  
Fuel Moisture Content

Aim of study: To reconcile the effects of live fuel moisture content (FMC) on fire rate of spread (ROS) derived from laboratory and field fires.Methods: The analysis builds on evidence from previous fire-spread experimental studies and on a comparison between two functions for the FMC damping effect: one derived from field burns, based on dead FMC, and another derived from laboratory trials, based on a weighted FMC (dead and live fuels).Main results: In a typical Mediterranean shrubland, laboratory and field-derived FMC damping functions are linearly related, which is explained by the correlation between monthly average live and dead FMC variation throughout the year. This clarifies why the effect of live FMC on real-world fires ROS has remained elusive.Research highlights: By providing evidence that the most significant effect of FMC on ROS is independent of vegetation phenology (dead or live condition), and explaining why in specific situations dead FMC is sufficient to provide satisfactory ROS predictions, our results can assist future modelling efforts.

scholarly journals Dimensional analysis on forest fuel bed fire spread

2018 ◽  
Vol 48 (1) ◽  
pp. 105-110
Author(s):  
Jiann C. Yang
Keyword(s):  
Dimensional Analysis ◽  
Fire Spread ◽  
Fuel Particle ◽  
Wind Condition ◽  
Spread Rate ◽  
Fuel Loading ◽  
Rate Of Spread ◽  
Dimensionless Groups ◽  
Dimensionless Correlations ◽  
Fuel Moisture Content

A dimensional analysis was performed to correlate the fuel bed fire rate of spread data previously reported in the literature. Under wind condition, six pertinent dimensionless groups were identified, namely dimensionless fire spread rate, dimensionless fuel particle size, fuel moisture content, dimensionless fuel bed depth or dimensionless fuel loading density, dimensionless wind speed, and angle of inclination of fuel bed. Under no-wind condition, five similar dimensionless groups resulted. Given the uncertainties associated with some of the parameters used to estimate the dimensionless groups, the dimensionless correlations using the resulting dimensionless groups correlate the fire rates of spread reasonably well under wind and no-wind conditions.

A cellular automata model to link surface fires to firebrand lift-off and dispersal

2013 ◽  
Vol 22 (4) ◽  
pp. 428 ◽  
Author(s):  
Holly A. Perryman ◽  
Christopher J. Dugaw ◽  
J. Morgan Varner ◽  
Diane L. Johnson
Keyword(s):  
Wind Speed ◽  
Wildland Fire ◽  
Fire Spread ◽  
Fuel Moisture ◽  
Fuel Loading ◽  
Cellular Automata Model ◽  
Rate Of Spread ◽  
Lift Off ◽  
Fuel Moisture Content ◽  
Spot Fires

In spite of considerable effort to predict wildland fire behaviour, the effects of firebrand lift-off, the ignition of resulting spot fires and their effects on fire spread, remain poorly understood. We developed a cellular automata model integrating key mathematical models governing current fire spread models with a recently developed model that estimates firebrand landing patterns. Using our model we simulated a wildfire in an idealised Pinus ponderosa ecosystem. Varying values of wind speed, surface fuel loading, surface fuel moisture content and canopy base height, we investigated two scenarios: (i) the probability of a spot fire igniting beyond fuelbreaks of various widths and (ii) how spot fires directly affect the overall surface fire’s rate of spread. Results were averages across 2500 stochastic simulations. In both scenarios, canopy base height and surface fuel loading had a greater influence than wind speed and surface fuel moisture content. The expected rate of spread with spot fires occurring approached a constant value over time, which ranged between 6 and 931% higher than the predicted surface fire rate of spread. Incorporation of the role of spot fires in wildland fire spread should be an important thrust of future decision-support technologies.

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.

Prediction of Fire Spread in Grasslands

1998 ◽  
Vol 8 (1) ◽  
pp. 1 ◽  
Author(s):  
NP Cheney ◽  
JS Gould ◽  
WR Catchpole
Keyword(s):  
Wind Speed ◽  
Linear Relationship ◽  
Power Function ◽  
Fire Spread ◽  
Fuel Moisture ◽  
Critical Wind Speed ◽  
Rate Of Spread ◽  
The Relationship ◽  
Potential Rate

This pager describes a model to predict fire spread in grasslands from wind speed at 10 m, dead fuel moisture, and degree of grass curing in three defined pasture types, The model was developed from spread measurements of experimental fins that were adjusted to their potential rate of spread at wide fronts. Extrapolations of the model were compared with spread data from 20 major wildfires in Australia. This model uses different functions to describe the relationship between rate of spread and wind speed above and below a critical wind speed of 5 km h-1. A linear relationship is used below 5 km h-1; above 5 km h-1 rate of spread is described by a power function of wind speed with an exponent of less than 1.

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