Current approaches to modelling the spread of wildland fire: a review

1998 ◽  
Vol 22 (2) ◽  
pp. 222-245 ◽  
Author(s):  
G. L.W. Perry
Keyword(s):  
Information Technologies ◽  
Spatial Information ◽  
Wildland Fire ◽  
Fire Risk ◽  
Fire Spread ◽  
Physical Models ◽  
Accurate Estimation ◽  
Fire Event ◽  
Fire Modelling ◽  
Modelling Techniques

This review considers the development of some of the models and modelling approaches designed to predict the spread and spatial behaviour of wildland fire events. Such events and their accurate prediction are of great importance to those seeking to understand and manage fire-prone ecosystems. The key problem which fire modelling seeks to address is outlined. Models predicting the rate of fire spread may be classified as physical, semi-physical or empirical according to the nature of their construction. The benefits and shortcomings of each type of model are considered with reference to specific examples of each type. It is shown that there are problems with current operational models which restrict their effective use. However, the development of rigorous physical models as replacements is impeded by conceptual and practical difficulties. Accurate estimation of the rate of spread and the intensity of a fire allows prediction of the final shape and area of a fire event. The modelling techniques used to estimate the shape and area of a fire are considered including the development of sophisticated computer-based simulations of fire spread. Spatial information technologies such as remote sensing and geographic information systems (GIS) offer great potential for the effective modelling of wildland fire behaviour. While such spatial information technologies have been frequently used in the evaluation of fire danger risk, their use for the simulation of the spatiotemporal behaviour of wildland fire is not common. The way in which spatial information technologies and decision-support systems are used for fire risk evaluation and fire spread simulation is discussed. Two research areas of great importance if fire modelling techniques are to improve are a better understanding of fire-dependent phenomena and the development of a ‘new generation’ of fire spread models; current trends in these areas of research are evaluated.

Mantras of wildland fire behaviour modelling: facts or fallacies?

2017 ◽  
Vol 26 (11) ◽  
pp. 973 ◽  
Author(s):  
Miguel G. Cruz ◽  
Martin E. Alexander ◽  
Andrew L. Sullivan
Keyword(s):  
Wildland Fire ◽  
Original Data ◽  
Fire Spread ◽  
Empirical Models ◽  
Physical Models ◽  
Fire Behaviour ◽  
Fire Science ◽  
Current State ◽  
Valid Data ◽  
Insight Into

Generalised statements about the state of fire science are often used to provide a simplified context for new work. This paper explores the validity of five frequently repeated statements regarding empirical and physical models for predicting wildland fire behaviour. For empirical models, these include statements that they: (1) work well over the range of their original data; and (2) are not appropriate for and should not be applied to conditions outside the range of the original data. For physical models, common statements include that they: (3) provide insight into the mechanisms that drive wildland fire spread and other aspects of fire behaviour; (4) give a better understanding of how fuel treatments modify fire behaviour; and (5) can be used to derive simplified models to predict fire behaviour operationally. The first statement was judged to be true only under certain conditions, whereas the second was shown not to be necessarily correct if valid data and appropriate modelling forms are used. Statements three through five, although theoretically valid, were considered not to be true given the current state of knowledge regarding fundamental wildland fire processes.

Analysis of the uncertainty of fuel model parameters in wildland fire modelling of a boreal forest in north-east China

2019 ◽  
Vol 28 (3) ◽  
pp. 205 ◽  
Author(s):  
Longyan Cai ◽  
Hong S. He ◽  
Yu Liang ◽  
Zhiwei Wu ◽  
Chao Huang
Keyword(s):  
Monte Carlo ◽  
Wildland Fire ◽  
Time Lag ◽  
Fire Spread ◽  
Model Parameters ◽  
Spread Rate ◽  
North East ◽  
Fire Modelling ◽  
Fuel Model ◽  
Model Parameter Uncertainty

Fire propagation is inevitably affected by fuel-model parameters during wildfire simulations and the uncertainty of the fuel-model parameters makes forecasting accurate fire behaviour very difficult. In this study, three different methods (Morris screening, first-order analysis and the Monte Carlo method) were used to analyse the uncertainty of fuel-model parameters with FARSITE model. The results of the uncertainty analysis showed that only a few fuel-model parameters markedly influenced the uncertainty of the model outputs, and many of the fuel-model parameters had little or no effect. The fire-spread rate is the driving force behind the uncertainty of other fire behaviours. Thus, the highly uncertain fuel-model parameters associated with spread rate should be used cautiously in wildfire simulations. Monte Carlo results indicated that the relationship between model input and output was non-linear and neglecting fuel-model parameter uncertainty of the model would magnify fire behaviours. Additionally, fuel-model parameters have high input uncertainty. Therefore, fuel-model parameters must be calibrated against actual fires. The highly uncertain fuel-model parameters with high spatial-temporal variability consisted of fuel-bed depth, live-shrub loading and 1-h time-lag loading are preferentially chosen as parameters to calibrate several wildfires.

scholarly journals Fitting a stochastic fire spread model to data

2019 ◽  
Vol 5 (1) ◽  
pp. 57-66
Author(s):  
X. Joey Wang ◽  
John R. J. Thompson ◽  
W. John Braun ◽  
Douglas G. Woolford
Keyword(s):  
Wildland Fire ◽  
Data Extraction ◽  
Fire Risk ◽  
Fire Spread ◽  
Small Scale ◽  
Intermediate Step ◽  
Spread Model ◽  
Recorded Data ◽  
Model Variability ◽  
Fire Spread Model

Abstract. As the climate changes, it is important to understand the effects on the environment. Changes in wildland fire risk are an important example. A stochastic lattice-based wildland fire spread model was proposed by Boychuk et al. (2007), followed by a more realistic variant (Braun and Woolford, 2013). Fitting such a model to data from remotely sensed images could be used to provide accurate fire spread risk maps, but an intermediate step on the path to that goal is to verify the model on data collected under experimentally controlled conditions. This paper presents the analysis of data from small-scale experimental fires that were digitally video-recorded. Data extraction and processing methods and issues are discussed, along with an estimation methodology that uses differential equations for the moments of certain statistics that can be derived from a sequential set of photographs from a fire. The interaction between model variability and raster resolution is discussed and an argument for partial validation of the model is provided. Visual diagnostics show that the model is doing well at capturing the distribution of key statistics recorded during observed fires.

High-resolution infrared thermography for capturing wildland fire behaviour: RxCADRE 2012

2016 ◽  
Vol 25 (1) ◽  
pp. 62 ◽  
Author(s):  
Joseph J. O'Brien ◽  
E. Louise Loudermilk ◽  
Benjamin Hornsby ◽  
Andrew T. Hudak ◽  
Benjamin C. Bright ◽  
...  
Keyword(s):  
Wildland Fire ◽  
Radiant Energy ◽  
Fire Spread ◽  
Fire Effects ◽  
Fire Behaviour ◽  
Oblique View ◽  
Fire Modelling ◽  
Radiative Power ◽  
Fire Front ◽  
Research Experiment

Wildland fire radiant energy emission is one of the only measurements of combustion that can be made at wide spatial extents and high temporal and spatial resolutions. Furthermore, spatially and temporally explicit measurements are critical for making inferences about fire effects and useful for examining patterns of fire spread. In this study we describe our methods for capturing and analysing spatially and temporally explicit long-wave infrared (LWIR) imagery from the RxCADRE (Prescribed Fire Combustion and Atmospheric Dynamics Research Experiment) project and examine the usefulness of these data in investigating fire behaviour and effects. We compare LWIR imagery captured at fine and moderate spatial and temporal resolutions (from 1 cm2 to 1 m2; and from 0.12 to 1 Hz) using both nadir and oblique measurements. We analyse fine-scale spatial heterogeneity of fire radiant power and energy released in several experimental burns. There was concurrence between the measurements, although the oblique view estimates of fire radiative power were consistently higher than the nadir view estimates. The nadir measurements illustrate the significance of fuel characteristics, particularly type and connectivity, in driving spatial variability at fine scales. The nadir and oblique measurements illustrate the usefulness of the data for describing the location and movement of the fire front at discrete moments in time at these fine and moderate resolutions. Spatially and temporally resolved data from these techniques show promise to effectively link the combustion environment with post-fire processes, remote sensing at larger scales and wildland fire modelling efforts.

scholarly journals Wildland Fire Behaviour Case Studies and Fuel Models for Landscape-Scale Fire Modeling

2011 ◽  
Vol 2011 ◽  
pp. 1-12 ◽  
Author(s):  
Paul-Antoine Santoni ◽  
Jean-Baptiste Filippi ◽  
Jacques-Henri Balbi ◽  
Frédéric Bosseur
Keyword(s):  
Case Studies ◽  
Fire History ◽  
Spatial Information ◽  
Wildland Fire ◽  
Meteorological Data ◽  
Fire Behavior ◽  
Fire Spread ◽  
Landscape Scale ◽  
Three Dimensions ◽  
Fuel Models

This work presents the extension of a physical model for the spreading of surface fire at landscape scale. In previous work, the model was validated at laboratory scale for fire spreading across litters. The model was then modified to consider the structure of actual vegetation and was included in the wildland fire calculation system Forefire that allows converting the two-dimensional model of fire spread to three dimensions, taking into account spatial information. Two wildland fire behavior case studies were elaborated and used as a basis to test the simulator. Both fires were reconstructed, paying attention to the vegetation mapping, fire history, and meteorological data. The local calibration of the simulator required the development of appropriate fuel models for shrubland vegetation (maquis) for use with the model of fire spread. This study showed the capabilities of the simulator during the typical drought season characterizing the Mediterranean climate when most wildfires occur.

scholarly journals Managing Fragmented Fire-Threatened Landscapes with Spatial Externalities

2019 ◽  
Vol 66 (4) ◽  
pp. 443-456 ◽  
Author(s):  
Christopher J Lauer ◽  
Claire A Montgomery ◽  
Thomas G Dietterich
Keyword(s):  
Spatial Information ◽  
Dynamic Game ◽  
Fire Risk ◽  
Landscape Fragmentation ◽  
Fire Spread ◽  
Optimal Timing ◽  
Value Functions ◽  
Management Actions ◽  
Expected Benefits ◽  
Southwest Oregon

Abstract Accounting for externalities generated by fire spread is necessary for managing fire risk on landscapes with multiple owners. In this paper, we determine the optimal management of a synthetic landscape parameterized to represent the ecological conditions of Douglas-fir (Pseudotsuga menziesii) plantations in southwest Oregon. The problem is formulated as a dynamic game, where each agent maximizes their own objective without considering the welfare of the other agents. We demonstrate a method for incorporating spatial information and externalities into a dynamic optimization process. A machine-learning technique, approximate dynamic programming, is applied to determine the optimal timing and location of fuel treatments and timber harvests for each agent. The value functions we estimate explicitly account for the spatial interactions that generate fire risk. They provide a way to model the expected benefits, costs, and externalities associated with management actions that have uncertain consequences in multiple locations. The method we demonstrate is applied to analyze the effect of landscape fragmentation on landowner welfare and ecological outcomes.

scholarly journals Estimation of wildfire size and risk changes due to fuels treatments

2012 ◽  
Vol 21 (4) ◽  
pp. 357 ◽  
Author(s):  
M. A. Cochrane ◽  
C. J. Moran ◽  
M. C. Wimberly ◽  
A. D. Baer ◽  
M. A. Finney ◽  
...  
Keyword(s):  
Wildland Fire ◽  
Fire Severity ◽  
Fire Risk ◽  
Fire Spread ◽  
Prescribed Fires ◽  
Fuel Treatments ◽  
Human Land Use ◽  
Trade Offs ◽  
Management Policies ◽  
Fuels Treatments

Human land use practices, altered climates, and shifting forest and fire management policies have increased the frequency of large wildfires several-fold. Mitigation of potential fire behaviour and fire severity have increasingly been attempted through pre-fire alteration of wildland fuels using mechanical treatments and prescribed fires. Despite annual treatment of more than a million hectares of land, quantitative assessments of the effectiveness of existing fuel treatments at reducing the size of actual wildfires or how they might alter the risk of burning across landscapes are currently lacking. Here, we present a method for estimating spatial probabilities of burning as a function of extant fuels treatments for any wildland fire-affected landscape. We examined the landscape effects of more than 72 000 ha of wildland fuel treatments involved in 14 large wildfires that burned 314 000 ha of forests in nine US states between 2002 and 2010. Fuels treatments altered the probability of fire occurrence both positively and negatively across landscapes, effectively redistributing fire risk by changing surface fire spread rates and reducing the likelihood of crowning behaviour. Trade offs are created between formation of large areas with low probabilities of increased burning and smaller, well-defined regions with reduced fire risk.

Two methods for calculating wildland fire rate of forward spread

2020 ◽  
Vol 29 (3) ◽  
pp. 272 ◽  
Author(s):  
Jim S. Gould ◽  
Andrew L. Sullivan
Keyword(s):  
Wind Tunnel ◽  
Field Experiments ◽  
Prediction Models ◽  
Wildland Fire ◽  
Model Development ◽  
Laboratory Data ◽  
Fire Spread ◽  
Accurate Estimation ◽  
Spread Rate ◽  
Eucalypt Forest

Accurate estimation of a wildland fire’s progression is critical for the development of robust fire spread prediction models and their validation. Two methods commonly used to determine spread rate are the cumulative spread rate, calculated as the total distance travelled by a fire divided by the total time of travel, and the interval spread rate, calculated using the minimum time and maximum distance between observations. This paper analyses the differences between these two methods using experimental fires conducted in dry eucalypt forest leaf litter in either a combustion wind tunnel or large (4ha) field sites. Fires were ignited from a point, 400-mm and 800-mm line ignitions in the wind tunnel, and point and 120-m line ignitions in the field experiments. A total of 312 and 397 observations of distance travelled and time taken were made during the laboratory and field experiments respectively, along with associated environmental variables. Mean spread rates and standard deviations were significantly greater for the interval method than those of the cumulative method for all the laboratory data and the field point ignition fires, and the difference between them varied with distance and time since ignition. These findings have important implications for fire spread and acceleration model development.

Examination of the wind speed limit function in the Rothermel surface fire spread model

2013 ◽  
Vol 22 (7) ◽  
pp. 959 ◽  
Author(s):  
Patricia L. Andrews ◽  
Miguel G. Cruz ◽  
Richard C. Rothermel
Keyword(s):  
Wind Speed ◽  
Wildland Fire ◽  
Fire Spread ◽  
Speed Limit ◽  
Limit Function ◽  
Surface Fire ◽  
Rate Of Spread ◽  
Fire Modelling ◽  
Spread Model ◽  
Fire Spread Model

The Rothermel surface fire spread model includes a wind speed limit, above which predicted rate of spread is constant. Complete derivation of the wind limit as a function of reaction intensity is given, along with an alternate result based on a changed assumption. Evidence indicates that both the original and the revised wind limits are too restrictive. Wind limit is based in part on data collected on the 7 February 1967 Tasmanian grassland fires. A reanalysis of the data indicates that these fires might not have been spreading in fully cured continuous grasslands, as assumed. In addition, more recent grassfire data do not support the wind speed limit. The authors recommend that, in place of the current wind limit, rate of spread be limited to effective midflame wind speed. The Rothermel model is the foundation of many wildland fire modelling systems. Imposition of the wind limit can significantly affect results and potentially influence fire and fuel management decisions.

scholarly journals Evaluating wildland fire liability standards – does regulation incentivise good management?

2020 ◽  
Vol 29 (7) ◽  
pp. 572
Author(s):  
Christopher J. Lauer ◽  
Claire A. Montgomery ◽  
Thomas G. Dietterich
Keyword(s):  
Spatial Information ◽  
Wildland Fire ◽  
Strict Liability ◽  
Dynamic Game ◽  
Spatial Location ◽  
Timber Harvest ◽  
Fire Spread ◽  
Land Values ◽  
Management Activity ◽  
Increase Risk

Fire spread on forested landscapes depends on vegetation conditions across the landscape that affect the fire arrival probability and forest stand value. Landowners can control some forest characteristics that facilitate fire spread, and when a single landowner controls the entire landscape, a rational landowner accounts for spatial interactions when making management decisions. With multiple landowners, management activity by one may impact outcomes for the others. Various liability regulations have been proposed, and some enacted, to make landowners account for these impacts by changing the incentives they face. In this paper, the effects of two different types of liability regulations are examined – strict liability and negligence standards. We incorporate spatial information into a model of land manager decision-making about the timing and spatial location of timber harvest and fuel treatment. The problem is formulated as a dynamic game and solved via multi-agent approximate dynamic programming. We found that, in some cases, liability regulation can increase expected land values for individual land ownerships and for the landscape as a whole. But in other cases, it may create perverse incentives that reduce expected land value. We also showed that regulations may increase risk for individual landowners by increasing the variability of potential outcomes.

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