Evaluation of FARSITE simulator in Mediterranean maquis

2007 ◽  
Vol 16 (5) ◽  
pp. 563 ◽  
Author(s):  
Bachisio Arca ◽  
P. Duce ◽  
M. Laconi ◽  
G. Pellizzaro ◽  
M. Salis ◽  
...  
Keyword(s):  
Weather Conditions ◽  
Structural Heterogeneity ◽  
Fire Spread ◽  
Mediterranean Ecosystems ◽  
Rate Of Spread ◽  
Fuel Model ◽  
Fuel Models ◽  
Mediterranean Maquis ◽  
Meteorological Input ◽  
Accuracy Of Results

In the last two decades, several models were developed to provide temporal and spatial variations of fire spread and behaviour. The most common models (i.e. BEHAVE and FARSITE) are based on Rothermel's original fire spread equation and describe fire spread and behaviour taking into account the influences of fuels, terrain and weather conditions. The use of FARSITE on areas different from those where the simulator was originally developed requires a local calibration to produce reliable results. This is particularly true for Mediterranean ecosystems, where plant communities are characterised by high specific and structural heterogeneity and complexity. To perform FARSITE calibration, an appropriate fuel model or the development of a specific custom fuel model is needed. In this study, FARSITE was employed to simulate three fire events in Mediterranean areas using different fuel models and meteorological input data, and the accuracy of results was analysed. A custom fuel model designed and developed for shrubland vegetation (maquis) provided realistic values of rate of spread, when compared with estimated values obtained using standard fuel models. Our results confirm that the use of both wind field data and appropriate custom fuel models are crucial to obtain reasonable simulations of wildfire events occurring on Mediterranean vegetation during the drought season.

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.

Behaviour and effects of prescribed fire in masticated fuelbeds

2011 ◽  
Vol 20 (8) ◽  
pp. 932 ◽  
Author(s):  
Eric E. Knapp ◽  
J. Morgan Varner ◽  
Matt D. Busse ◽  
Carl N. Skinner ◽  
Carol J. Shestak
Keyword(s):  
Pinus Ponderosa ◽  
Ponderosa Pine ◽  
Tree Mortality ◽  
Fire Hazard ◽  
Weather Conditions ◽  
Flame Length ◽  
Fire Behaviour ◽  
Prescribed Burns ◽  
Rate Of Spread ◽  
Fuel Models

Mechanical mastication converts shrub and small tree fuels into surface fuels, and this method is being widely used as a treatment to reduce fire hazard. The compactness of these fuelbeds is thought to moderate fire behaviour, but whether standard fuel models can accurately predict fire behaviour and effects is poorly understood. Prescribed burns were conducted in young ponderosa pine (Pinus ponderosa Laws.) forests at two sites in northern California where the midstorey layer dominated by shrubs had been masticated. Surface fuels were raked from the base of a subset of trees before burning. Rate of spread and flame length were estimated for both backing and heading fires, soil heating measured with thermocouples and tree fire injury recorded. Standard fuel models often over-predicted rate of spread or under-predicted flame length. Custom models generally provided a better balance between the slow rates of spread and moderate flame lengths observed in prescribed burns. Post-fire tree mortality was most strongly associated with crown scorch and tree size; raking fuels from the base of trees did not improve survival. Under severe fire weather conditions, fire behaviour and effect models as well as observations from wildfires suggest that mastication may be more effective for moderating fire behaviour than reducing residual tree mortality. Treating masticated fuels with prescribed burns could potentially improve the resilience of stands to wildfire.

Fuel Models and Fire Potential From Satellite and Surface Observations

1998 ◽  
Vol 8 (3) ◽  
pp. 159 ◽  
Author(s):  
RE Burgan ◽  
RW Klaver ◽  
JM Klaver
Keyword(s):  
Mediterranean Ecosystems ◽  
Fire Danger ◽  
Fire Occurrence ◽  
Ground Sample ◽  
Potential Index ◽  
Fuel Model ◽  
Sample Data ◽  
Fuel Models ◽  
The U.S

A national 1-km resolution fire danger fuel model map was derived through use of previously mapped land cover classes and ecoregions, and extensive ground sample data, then refined through review by fire managers familiar with various portions of the U.S. The fuel model map will be used in the next generation fire danger rating system for the U.S., but it also made possible immediate development of a satellite and ground based fire potential index map. The inputs and algorithm of the fire potential index are presented, along with a case study of the correlation between the fire potential index and fire occurrence in California and Nevada. Application of the fire potential index in the Mediterranean ecosystems of Spain, Chile, and Mexico will be tested.

scholarly journals Building Rothermel fire behaviour fuel models by genetic algorithm optimisation

2015 ◽  
Vol 24 (3) ◽  
pp. 317 ◽  
Author(s):  
Davide Ascoli ◽  
Giorgio Vacchiano ◽  
Renzo Motta ◽  
Giovanni Bovio
Keyword(s):  
Goodness Of Fit ◽  
Fire Spread ◽  
Validation Dataset ◽  
Model Parameters ◽  
Initial Population ◽  
Fire Behaviour ◽  
Continuous Space ◽  
Fuel Model ◽  
Spread Model ◽  
Fuel Models

A method to build and calibrate custom fuel models was developed by linking genetic algorithms (GA) to the Rothermel fire spread model. GA randomly generates solutions of fuel model parameters to form an initial population. Solutions are validated against observations of fire rate of spread via a goodness-of-fit metric. The population is selected for its best members, crossed over and mutated within a range of model parameter values, until a satisfactory fitness is reached. We showed that GA improved the performance of the Rothermel model in three published custom fuel models for litter, grass and shrub fuels (root mean square error decreased by 39, 19 and 26%). We applied GA to calibrate a mixed grass–shrub fuel model, using fuel and fire behaviour data from fire experiments in dry heathlands of Southern Europe. The new model had significantly lower prediction error against a validation dataset than either standard or custom fuel models built using average values of inventoried fuels, and predictions of the Fuel Characteristics Classification System. GA proved a useful tool to calibrate fuel models and improve Rothermel model predictions. GA allows exploration of a continuous space of fuel parameters, making fuel model calibration computational effective and easily reproducible, and does not require fuel sampling. We suggest GA as a viable method to calibrate custom fuel models in fire modelling systems based on the Rothermel model.

scholarly journals Modeling surface fire rate of spread within a thinned Anatolian black pine stand in Turkey

2018 ◽  
Vol 27 (2) ◽  
pp. e007
Author(s):  
Omer Kucuk ◽  
Ertugrul Bilgili ◽  
Rifat Uzumcu
Keyword(s):  
Wind Speed ◽  
Weather Conditions ◽  
Fire Spread ◽  
Pinus Nigra ◽  
Small Scale ◽  
Black Pine ◽  
Fuel Loading ◽  
Surface Fire ◽  
Rate Of Spread ◽  
Northwestern Turkey

Aim of the study: To develop regression models for estimating the rate of surface fire spread in a thinned even-aged black pine stand (Pinus nigra J.F. Arnold subsp. nigra var. caramanica (Loudon) Rehder).Area of the study: The study was carried out within a thinned black pine forest located in the Kastamonu Forest District, northwestern Turkey. The study area is located at 546819, 4577880 UTM.Material and methods: A total of 33 small scale surface fires were ignited under varying weather and fuel conditions. Line ignition was used during the burnings. Surface fuels consisted generally of thinned material (needle+branches).Main results: Within the stand, surface fuel loading ranged from 3.0 to 10.2 kg/m2. Wind speed ranged from 0.3 to 8.4 km/h. Needle moisture content ranged from 8 to 15%. The rate of fire spread ranged from 0.47 to 6.92 m/min. Relationships between the rate of fire spread and fuel and weather conditions were determined through regression analyses.Research highlights: Wind speed was the most important factor on the rate of fire spread and explained 85% of the observed variation in the surface fire rate of spread within a stand.

Development of fuel models for fire behaviour prediction in maritime pine (Pinus pinaster Ait.) stands

2008 ◽  
Vol 17 (2) ◽  
pp. 194 ◽  
Author(s):  
Miguel G. Cruz ◽  
Paulo M. Fernandes
Keyword(s):  
Pinus Pinaster ◽  
Complex Structure ◽  
Fire Spread ◽  
Maritime Pine ◽  
Validation Dataset ◽  
Fire Behaviour ◽  
Functional Relationships ◽  
Rate Of Spread ◽  
Pinus Pinaster Ait ◽  
Fuel Models

A dataset of 42 experimental fires in maritime pine (Pinus pinaster Ait.) stands was used to develop fuel models to describe pine litter and understorey surface fuel complexes. A backtracking calibration procedure quantified the surface fuel bed characteristics that best explained the observed rate of fire spread. The study suggested the need for two distinct fuel models to adequately characterise the variability in fire behaviour in this fuel type. In these heterogeneous fuel beds the fuel models do not necessarily represent the inventoried average fuel conditions. Evaluation against the modelling data produced mean absolute errors of 0.8 and 0.6 m min–1 in rate of spread, respectively, for the litter and understorey fuel models, with little evidence of bias. The fuel models predicted the rate of spread of a validation dataset with comparable error. Comparison of the behaviour and evaluation statistics produced by the study fuel models with fuel models developed from inventoried fuel data alone revealed an improvement on model performance for the current study approach for the litter fuel model and comparable behaviour for the understorey one. We examined model behaviour through comparative analysis with models used operationally to predict fire spread in pine stands. Large departures from model behaviour essentially occur when the models are exercised outside the range of the model development dataset. The discrepancies in predicted fire behaviour were hypothesised to arise not from differences in fuel complex structure but from the selected functional relationships that determine the effect of wind and fuel moisture on rate of spread.

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.

scholarly journals BUILDING FUEL MODELS AND SIMULATING THEIR SURFACE FIRE BEHAVIOR IN THE “SERRA DE ITABAIANA” NATIONAL PARK, SERGIPE, BRAZIL

FLORESTA ◽  
2013 ◽  
Vol 43 (1) ◽  
pp. 27 ◽  
Author(s):  
Benjamin Leonardo Alves White ◽  
Adauto Souza Ribeiro ◽  
Genésio Tâmara Ribeiro ◽  
Rosemeri Melo Souza
Keyword(s):  
Tropical Forests ◽  
National Park ◽  
Unit Area ◽  
Fire Behavior ◽  
Flame Length ◽  
Vegetation Types ◽  
Destructive Sampling ◽  
Rate Of Spread ◽  
Fuel Model ◽  
Fuel Models

  The objectives of this research were, for scientific and management purposes, to build fuel models and simulate their fire behavior. Three different vegetation types (shrublands, grass fields and tropical forests) of the “Serra de Itabaiana” National Park were analyzed. The fuel models were developed by destructive sampling and the collected data was inserted in the software “BehavePlus 5.0”. The results revealed that the fuel model for the shrublands presented the longest flame length, the highest fireline intensity and the greatest heat release per unit area. The fuel model for the grass fields presented the fastest surface rate of spread; and the fuel model for the tropical forests the lower fire intensity.Keywords: Fire simulator; BehavePlus; conservation units.ResumoConstruindo modelos de material combustível e simulando o seu comportamento de fogo no Parque Nacional Serra de Itabaiana, SE. Este estudo foi desenvolvido com o objetivo de construir modelos de material combustível para três diferentes formações vegetacionais (florestas arbustivas, campos graminosos e florestas tropicais), localizadas dentro do Parque Nacional Serra de Itabaiana, e simular o comportamento do fogo dentro dessas fitofisionomias, para efeitos de pesquisa e manejo. Para tal, modelos foram construídos através de amostragem destrutiva e os dados coletados inseridos no programa "BehavePlus 5.0". De acordo com os resultados, o modelo para as florestas arbustivas apresentou o maior comprimento de chamas, a maior intensidade do fogo e a maior quantidade de energia liberada por unidade de área. O modelo para os campos graminosos apresentou maior velocidade de propagação do fogo e, no modelo para as florestas tropicais, o fogo simulado apresentou menor intensidade.Palavras-chave: Manejo do fogo; BehavePlus; unidades de conservação.    

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.

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.

Sign in / Sign up

Export Citation Format

Share Document