Flatland in flames: a two-dimensional crown fire propagation model

The canopy bulk density metric is used to describe the fuel available for combustion in crown fire models. We propose modifying the Van Wagner crown fire propagation model, used to estimate the critical rate of spread necessary to sustain active crown fire, to use foliar biomass per square metre instead of canopy bulk density as the fuel input. We tested the efficacy of our proposed model by comparing predictions of crown fire propagation with Van Wagner’s original data. Our proposed model correctly predicted each instance of crown fire presented in the seminal study. We then tested the proposed model for statistical equivalence to the original Van Wagner model using two contemporary techniques to parameterize canopy bulk density. We found the proposed and original models to be statistically equivalent when canopy bulk density was parameterized using the method incorporated in the Fire and Fuels Extension to the Forest Vegetation Simulator (difference < 0.5 km h–1, α = 0.05, n = 2626), but not when parameterized using the method of Cruz and others. Use of foliar biomass per unit area in the proposed model makes for more accurate and easily obtained fuel estimates without sacrificing the utility of the Van Wagner model.

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Evaluating the 3-m tree crown spacing guideline for the prevention of crowning wildfires in lodgepole pine forests, Alberta

The Forestry Chronicle ◽

10.5558/tfc2020-021 ◽

2020 ◽

Vol 96 (02) ◽

pp. 165-173

Author(s):

Martin E. Alexander ◽

Miguel G. Cruz

Keyword(s):

Bulk Density ◽

Pinus Contorta ◽

Lodgepole Pine ◽

Pine Forests ◽

Crown Fire ◽

Conifer Forest ◽

Fire Propagation ◽

Current State ◽

General Recommendation ◽

Canopy Bulk Density

A 3-m between crown spacing is a commonly cited criterion found in the wildland-urban interface fire literature for minimizing the likelihood of a fully-developed crown fire from occurring in a conifer forest on level terrain. The validity of this general recommendation is examined here in light of our current state-of-knowledge regarding crown fire propagation in relation to canopy bulk density. Given the characteristics of the overstory structure for 20 lodgepole pine (Pinus contorta Dougl. ex Loud. var. latifolia Engelm.) stands located in Alberta, as sourced from the literature, the canopy fuel properties following a virtual thinning to a 3-m crown spacing and then to a targeted canopy bulk density of 0.05 kg/m3 were computed. On the basis of these computations, crown fire potential was then analyzed and interpreted. The conclusion reached is that, in the majority of cases, a less widely spaced stand would be adequate for preventing crown fire development in lodgepole pine forests.

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Development and testing of models for predicting crown fire rate of spread in conifer forest stands

Canadian Journal of Forest Research ◽

10.1139/x05-085 ◽

2005 ◽

Vol 35 (7) ◽

pp. 1626-1639 ◽

Cited By ~ 97

Author(s):

Miguel G Cruz ◽

Martin E Alexander ◽

Ronald H Wakimoto

Keyword(s):

Bulk Density ◽

Fire Behavior ◽

Fire Regimes ◽

Management Decision ◽

Crown Fire ◽

Conifer Forest ◽

Data Set ◽

Rate Of Spread ◽

Spread Model ◽

Canopy Bulk Density

The rate of spread of crown fires advancing over level to gently undulating terrain was modeled through nonlinear regression analysis based on an experimental data set pertaining primarily to boreal forest fuel types. The data set covered a significant spectrum of fuel complex and fire behavior characteristics. Crown fire rate of spread was modeled separately for fires spreading in active and passive crown fire regimes. The active crown fire rate of spread model encompassing the effects of 10-m open wind speed, estimated fine fuel moisture content, and canopy bulk density explained 61% of the variability in the data set. Passive crown fire spread was modeled through a correction factor based on a criterion for active crowning related to canopy bulk density. The models were evaluated against independent data sets originating from experimental fires. The active crown fire rate of spread model predicted 42% of the independent experimental crown fire data with an error lower then 25% and a mean absolute percent error of 26%. While the models have some shortcomings and areas in need of improvement, they can be readily utilized in support of fire management decision making and other fire research studies.

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Estimating canopy fuel characteristics for predicting crown fire potential in common forest types of the Atlantic Coastal Plain, USA

International Journal of Wildland Fire ◽

10.1071/wf18025 ◽

2018 ◽

Vol 27 (11) ◽

pp. 742 ◽

Cited By ~ 1

Author(s):

Anne G. Andreu ◽

John I. Blake ◽

Stanley J. Zarnoch

Keyword(s):

Bulk Density ◽

Coastal Plain ◽

Canopy Cover ◽

Atlantic Coastal Plain ◽

Theoretic Approach ◽

Crown Fire ◽

Prescribed Burns ◽

Stand Height ◽

Atlantic Coastal ◽

Canopy Bulk Density

We computed four stand-level canopy stratum variables important for crown fire modelling – canopy cover, stand height, canopy base height and canopy bulk density – from forest inventory data. We modelled the relationship between the canopy variables and a set of common inventory parameters – site index, stem density, basal area, stand age or stand height – and number of prescribed burns. We used a logistic model to estimate canopy cover, a linear model to estimate the other canopy variables, and the information theoretic approach for model selection. Coefficients of determination across five forest groups were 0.72–0.91 for stand height, 0.36–0.83 for canopy base height, 0.39–0.80 for canopy cover, and 0.63–0.78 for canopy bulk density. We assessed crown fire potential (1) for several sets of environmental conditions in all seasons, and (2) with increasing age, density and number of prescribed burns using our modelled canopy bulk density and canopy base height variables and local weather data to populate the Crown Fire Initiation and Spread model. Results indicated that passive crown fire is possible in any season in Atlantic coastal plain pine stands with heavy surface fuel loads and active crown fire is most probable in infrequently burned, dense stands at low fuel moistures.

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Canopy bulk density and canopy base height equations for assessing crown fire hazard in Pinus radiata plantations

Canadian Journal of Forest Research ◽

10.1139/x10-237 ◽

2011 ◽

Vol 41 (4) ◽

pp. 839-850 ◽

Cited By ~ 16

Author(s):

Ana Daría Ruiz-González ◽

Juan Gabriel Álvarez-González

Keyword(s):

Bulk Density ◽

Pinus Radiata ◽

Fire Hazard ◽

Direct Action ◽

Quantitative Information ◽

Wildlife Habitat ◽

Vertical Profiles ◽

Crown Fire ◽

Crown Fires ◽

Canopy Bulk Density

Crown fires combine high rates of spread, flame lengths, and intensities, making it virtually impossible to control them by direct action and having significant impact on soils, vegetation, and wildlife habitat. For these reasons, fire managers have great interest in preventive silviculture of forested landscapes to avoid the initiation and propagation of crown fires. The minimum conditions necessary to initiate and propagate crown fires are assumed to be strongly influenced by the stand structural variables canopy bulk density (CBD) and canopy base height (CBH). However, there is a lack of quantitative information on these variables and how to estimate them. To characterize the aerial fuel layers of Pinus radiata D. Don, the vertical profiles of canopy fuel in 180 sample plots of pure and even-aged P. radiata plantations were analysed. Effective CBD and CBH were obtained from the vertical profiles, and equations relating these variables to common stand variables were fitted simultaneously. Inclusion of the fitted equations in existing dynamic growth models, together with the use of current fire behaviour and hazard prediction tools, will provide a decision support system for assessing the crown fire potential of different silvicultural alternatives for this species.

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Parameter Estimation for the Forest Fire Propagation Model

Tatra Mountains Mathematical Publications ◽

10.2478/tmmp-2020-0001 ◽

2020 ◽

Vol 75 (1) ◽

pp. 1-22

Author(s):

Martin Ambroz ◽

Karol Mikula ◽

Marek Fraštia ◽

Marián Marčiš

Keyword(s):

Data Assimilation ◽

Forest Fire ◽

Hausdorff Distance ◽

Small Time ◽

Propagation Model ◽

Model Parameters ◽

Normal Velocity ◽

Fire Propagation ◽

Rate Of Spread ◽

Fire Front

AbstractThis paper first gives a brief overview of the Lagrangian forest fire propagation model [Ambroz, M.—Balažovjech, M.—Medl’a, M.—Mikula, K.: Numerical modeling of wildland surface fire propagation by evolving surface curves, Adv. Comput. Math. 45 (2019), no. 2, 1067–1103], which we apply to grass-field areas. Then, we aim to estimate the optimal model parameters. To achieve this goal, we use data assimilation of the measured data. From the data, we are able to estimate the normal velocity of the fire front (rate of spread), dominant wind direction and selected model parameters. In the data assimilation process, we use the Hausdorff distance as well as the Mean Hausdorff distance as a criterion. Moreover, we predict the fire propagation in small time intervals.

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Evaluating regression model estimates of canopy fuel stratum characteristics in four crown fire-prone fuel types in western North America

International Journal of Wildland Fire ◽

10.1071/wf10066 ◽

2012 ◽

Vol 21 (2) ◽

pp. 168 ◽

Cited By ~ 7

Author(s):

Miguel G. Cruz ◽

Martin E. Alexander

Keyword(s):

North America ◽

Bulk Density ◽

Ponderosa Pine ◽

Stand Structure ◽

Coniferous Forest ◽

Fuel Load ◽

Regression Equations ◽

Western North America ◽

Crown Fire ◽

Canopy Bulk Density

Two evaluations were undertaken of the regression equations developed by M. Cruz, M. Alexander and R. Wakimoto (2003, International Journal of Wildland Fire 12, 39–50) for estimating canopy fuel stratum characteristics from stand structure variables for four broad coniferous forest fuel types found in western North America. The first evaluation involved a random selection of 10 stands each from the four datasets used in the original study. These were in turn subjected to two simulated thinning regimes (i.e. 25 and 50% basal area removal). The second evaluation involved a completely independent dataset for ponderosa pine consisting of 16 stands sampled by T. Keyser and F. Smith (2010, Forest Science 56, 156–165). Evaluation statistics were comparable for the thinning scenarios and independent evaluations. Mean absolute percentage errors varied between 13.8 and 41.3% for canopy base height, 5.3 and 67.9% for canopy fuel load, and 20.7 and 71% for canopy bulk density. Bias errors were negligible. The results of both evaluations clearly show that the stand-level models of Cruz et al. (2003) used for estimating canopy base height, canopy fuel load and canopy bulk density in the assessment of crown fire potential are, considering their simplicity, quite robust.

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Curvature effects in the dynamic propagation of wildfires

International Journal of Wildland Fire ◽

10.1071/wf16070 ◽

2016 ◽

Vol 25 (12) ◽

pp. 1238 ◽

Cited By ~ 11

Author(s):

J. E. Hilton ◽

C. Miller ◽

J. J. Sharples ◽

A. L. Sullivan

Keyword(s):

Propagation Model ◽

Computationally Efficient ◽

Local Curvature ◽

Fire Propagation ◽

Curvature Effects ◽

Dynamic Propagation ◽

Rate Of Spread ◽

Complex Interactions ◽

Curvature Parameter ◽

Curvature Dependence

The behaviour and spread of a wildfire are driven by a range of processes including convection, radiation and the transport of burning material. The combination of these processes and their interactions with environmental conditions govern the evolution of a fire’s perimeter, which can include dynamic variation in the shape and the rate of spread of the fire. It is difficult to fully parametrise the complex interactions between these processes in order to predict a fire’s behaviour. We investigate whether the local curvature of a fire perimeter, defined as the interface between burnt and unburnt regions, can be used to model the dynamic evolution of a wildfire’s progression. We find that incorporation of curvature dependence in an empirical fire propagation model provides closer agreement with the observed evolution of field-based experimental fires than without curvature dependence. The local curvature parameter may represent compounded radiation and convective effects near the flame zone of a fire. Our findings provide a means to incorporate these effects in a computationally efficient way and may lead to improved prediction capability for empirical models of rate of spread and other fire behaviour characteristics.

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A convective–radiative propagation model for wildland fires

International Journal of Wildland Fire ◽

10.1071/wf19103 ◽

2020 ◽

Vol 29 (8) ◽

pp. 723

Author(s):

Jacques Henri Balbi ◽

François Joseph Chatelon ◽

Dominique Morvan ◽

Jean Louis Rossi ◽

Thierry Marcelli ◽

...

Keyword(s):

Heat Transfer ◽

Laboratory Experiments ◽

Propagation Model ◽

Model Parameters ◽

Large Set ◽

Operational Conditions ◽

Rate Of Spread ◽

Proposed Model ◽

Fuel Particles ◽

Fuel Elements

The ‘Balbi model’ is a simplified steady-state physical propagation model for surface fires that considers radiative heat transfer from the surface area of burning fuel particles as well as from the flame body. In this work, a completely new version of this propagation model for wildand fires is proposed. Even if, in the present work, this model is confined to laboratory experiments, its purpose is to be used at a larger scale in the field under operational conditions. This model was constructed from a radiative propagation model with the addition of a convective heat transfer term resulting from the impingement of packets of hot reacting gases on unburnt fuel elements located at the base of the flame. The flame inside the fuel bed is seen as the ‘fingers of fire’ described in the literature. The proposed model is physics-based, faster than real time and fully predictive, which means that model parameters do not change from one experiment to another. The predicted rate of spread is applied to a large set of laboratory experiments (through homogeneous pine needles and excelsior fuel beds) and is compared with the predictions of both a very simple empirical model (Catchpole) and a detailed physical model (FireStar2D).

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Neuro-Fuzzy Transformation with Minimize Entropy Principle to Create New Features for Particulate Matter Prediction

Applied Sciences ◽

10.3390/app11146590 ◽

2021 ◽

Vol 11 (14) ◽

pp. 6590

Author(s):

Krittakom Srijiranon ◽

Narissara Eiamkanitchat

Keyword(s):

Particulate Matter ◽

Fuzzy Model ◽

Original Data ◽

Northern Region ◽

National Standard ◽

Minimum Entropy ◽

Fuzzy Transformation ◽

Neuro Fuzzy ◽

Proposed Model ◽

Entropy Principle

Air pollution is a major global issue. In Thailand, this issue continues to increase every year, similar to other countries, especially during the dry season in the northern region. In this period, particulate matter with aerodynamic diameters smaller than 10 and 2.5 micrometers, known as PM10 and PM2.5, are important pollutants, most of which exceed the national standard levels, the so-called Thailand air quality index (T-AQI). Therefore, this study created a prediction model to classify T-AQI calculated from both types of PM. The neuro-fuzzy model with a minimum entropy principle model is proposed to transform the original data into new informative features. The processes in this model are able to discover appropriate separation points of the trapezoidal membership function by applying the minimum entropy principle. The membership value of the fuzzy section is then passed to the neural section to create a new data feature, the PM level, for each hour of the day. Finally, as an analytical process to obtain new knowledge, predictive models are created using new data features for better classification results. Various experiments were utilized to find an appropriate structure with high prediction accuracy. The results of the proposed model were favorable for predicting both types of PM up to three hours in advance. The proposed model can help people who are planning short-term outdoor activities.

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