A climatologically based long-range fire growth model

2010 ◽  
Vol 19 (7) ◽  
pp. 879 ◽  
Author(s):  
Kerry Anderson
Keyword(s):  
Long Range ◽  
Growth Model ◽  
Deterministic Model ◽  
Probabilistic Approach ◽  
Fire Spread ◽  
Weather Data ◽  
Fire Season ◽  
Fire Growth ◽  
Probability Of Survival ◽  
Wood Buffalo National Park

A long-range fire growth model was developed to predict the potential size or probable extent of a wildfire if it was allowed to grow unimpeded for the course of the fire season. The model combines the probabilities of fire spread and of survival to produce a probable fire extent map. Probability of spread is determined from exponential distributions of potential rates of spread for various fuel types and eight compass directions, based on 30 years of fire weather data and elliptical fire growth. Probability of survival is determined from the probable evolution of the duff moisture code over the fire season predicted with Markov chains and a duff moisture code of extinction. A comparative study was conducted within Wood Buffalo National Park. The long-term model was compared with a distribution of fire perimeters predicted by repeated simulations using an hourly based, deterministic fire growth model. The study was conducted in stages, starting with a homogeneous fuel type and weather from one station. Later, fuels and weather were introduced to determine their effects on the model. The study showed a close agreement between the long-range model and the deterministic model, supporting the probabilistic approach used by the long-range model.

Fire-growth modelling using meteorological data with random and systematic perturbations

2007 ◽  
Vol 16 (2) ◽  
pp. 174 ◽  
Author(s):  
Kerry Anderson ◽  
Gerhard Reuter ◽  
Mike D. Flannigan
Keyword(s):  
Wind Speed ◽  
Growth Model ◽  
Forest Fires ◽  
Meteorological Data ◽  
Random Perturbation ◽  
Weather Forecast ◽  
Fire Spread ◽  
Fire Growth ◽  
Hourly Data ◽  
Systematic Perturbation

The focus of this investigation is to quantify the effects of perturbations in the meteorological data used in a fire-growth model. Observed variations of temperature, humidity, wind speed, and wind direction are applied as perturbations to hourly values within a simulated weather forecast to produce several forecasts. In turn, these are used by a deterministic eight-point fire-growth model to produce an ensemble of possible final fire perimeters. Two studies were conducted to assess the value of applying perturbations. In the first study, fire growth using detailed, one-minute data was compared to growth based on the more commonly used hourly data. Results showed that the detailed weather produced fire growth larger and wider than the hourly based data. By applying perturbations, variations in the flank and back-fire spread were captured by the random-perturbation model while the forward spread fell within the 20 to 30% probability prediction. A sensitivity analysis based on the observed variations showed that wind speed accounted for a 44% difference in area burned, while temperature accounted for only a 16% difference. In the second study, case studies were conducted on four observed forest fires in Wood Buffalo National Park. Results showed that daily fire-growth predictions using simulated weather forecasts over-predicted fire growth using actual hourly weather observations by 27%. Systematic-perturbation models best compensated for this with most fire growth falling within the predicted range of the models (52 out of 63 days).

scholarly journals Precipitation dominates fire occurrence in Greece (1900–2010): its dual role in fuel build-up and dryness

2013 ◽  
Vol 1 (2) ◽  
pp. 693-720 ◽  
Author(s):  
F. Xystrakis ◽  
A. S. Kallimanis ◽  
P. Dimopoulos ◽  
J. M. Halley ◽  
N. Koutsias
Keyword(s):  
Fire Spread ◽  
Dual Role ◽  
Weather Data ◽  
Fire Season ◽  
Dominant Factor ◽  
Negative Events ◽  
Fire Occurrence ◽  
Spring Precipitation ◽  
Burnt Area ◽  
Area Burned

Abstract. Historical fire records and meteorological observations spanning over one century (1894–2010), were assembled in a database to collect long-term fire and weather data in Greece. Positive/negative events of fire occurrence on an annual basis were considered the years where the annual values of the examined parameters were above (positive values) or below (negative values) the 95% confidence limits around the trend line of the corresponding parameter. To analyze the association of positive/negative events of fire occurrence and meteorological extremes, we proceeded with a cross-tabulation analysis based on a Monte Carlo randomization. Positive/negative values of total annual precipitation were randomly associated with the corresponding values of burned areas, and significant associations were observed for seasonal precipitation totals (spring and fire season). Fire season precipitation is the dominant factor coinciding with negative values of area burned, while years with high spring precipitation coincide with large burnt area burned. These results demonstrate the dual role of precipitation in controlling a fire's extent through fuel build-up and dryness. Additionally, there is a clear outperformance of precipitation-related against temperature-related weather variables revealing that, at least in Greece, fire spread is controlled by precipitation totals rather than air temperature.

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.

Preliminary Study of Fire Spread in Cities and Forests, Using PMMA Specimen as a Fuel in CFD Simulations

2009 ◽  
Author(s):  
Koyu Satoh ◽  
Naian Liu ◽  
Qiong Liu ◽  
K. T. Yang
Keyword(s):  
Laboratory Experiment ◽  
Forest Fires ◽  
Three Dimensional ◽  
Fire Spread ◽  
Weather Data ◽  
Strong Wind ◽  
Cfd Simulations ◽  
Worst Case ◽  
Fire Propagation ◽  
Fire Spreading

It is important to examine the behavior of forest fires and city fires to mitigate the property damages and victims by fires. There have been many previous studies on forest fires where the fire spreading patterns were investigated, utilizing artificial satellite pictures of forest fires, together with the use of corresponding weather data and GIS data. On the other hand, large area city fires are very scarce in the world, particularly in modern cities where high-rise concrete buildings are constructed with sufficient open spaces. Thus, the examples of city fires to be referred are few and detailed investigations of city fires are limited. However, there have still been existing old cities where traditional houses built with flammable material such as wood, maybe historically important, only separated with very small open spacing. Fires may freely spread in those cities, once a big earthquake happens there and then water supply for the fire brigade is damaged in the worst case along with the effect of strong wind. There are some fundamental differences between the forest fires and city fires, as the fuel may distribute either continuously or discretely. For instance, in forest fires, the dead fallen leaves, dry grasses and trees are distributed continuously on the ground, while the wooden houses in cities are discretely distributed with some separation of open spacing, such as roads and gardens. Therefore, the wooden houses neighboring the burning houses with some separation are heated by radiation and flames to elevate the temperatures, thus causing the ignition, and finally reaching a large city fire. The authors have studied the forest fire spread and are planning to start a laboratory experiment of city fire spreading. In the preliminary investigation, a numerical study is made to correlate with the laboratory experiment of city fire propagation, utilizing the three-dimensional CFD simulations. Based on the detailed experimental analysis, the authors are attempting to modify the three dimensional CFD code to predict the forest fires and city fires more precisely, taking into account the thermal heating and ignition processes. In this study, some fundamental information on the city fire propagation has been obtained, particularly to know the safe open spacing distances between the houses in the cities and also the wind speed.

DEVS-FIRE: design and application of formal discrete event wildfire spread and suppression models

SIMULATION ◽  
2011 ◽  
Vol 88 (3) ◽  
pp. 259-279 ◽  
Author(s):  
Xiaolin Hu ◽  
Yi Sun ◽  
Lewis Ntaimo
Keyword(s):  
Fire Suppression ◽  
Discrete Event ◽  
Fire Spread ◽  
New Method ◽  
Weather Data ◽  
System Specification ◽  
Cellular Space ◽  
Scheduling Method ◽  
Wildfire Spread ◽  
Formal Design

DEVS-FIRE is a discrete event system specification (DEVS) model for simulating wildfire spread and suppression. It employs a cellular space model to simulate fire spread and agent models that interact with the cellular space to simulate fire suppression with realistic tactics. The complex interplay among forest cells and agents calls for formal treatment of the fire spread and fire suppression models to verify the correctness of DEVS-FIRE. This paper gives formal design specifications of fire spread and suppression agent models used in DEVS-FIRE and applies DEVS-FIRE to both artificially generated and real topography, fuels and weather data for a study area located in the US state of Texas. The paper also develops a new method, called pre_Schedule, for scheduling ignition events of forest cells more efficiently than the original onTime_Schedule event scheduling method used in DEVS-FIRE. Simulation results show the performance improvement of the new method, and demonstrate the utility of DEVS-FIRE as a viable discrete event model for wildfire simulations.

Nonthermal Fire Damage

1992 ◽  
Vol 10 (3) ◽  
pp. 188-242 ◽  
Author(s):  
Archibald Tewarson
Keyword(s):  
Long Range ◽  
Surface Characteristics ◽  
Fire Spread ◽  
Fire Damage ◽  
Research Corporation ◽  
Fire Initiation

This paper deals with the general relationships between nonther mal damage and fire initiation, fire spread, generation of fire products, en vironmental conditions, and orientation and surface characteristics of targets. Data reported in the literature by various researchers have been used in the paper to discuss the relationships. Tests currently being used to assess corro sion in various laboratories and the long-range nonthermal damage research at Factory Mutual Research Corporation are reviewed.

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 Seamless climate change projections and seasonal predictions for bushfires in Australia

2020 ◽  
Vol 70 (1) ◽  
pp. 120
Author(s):  
Andrew J. Dowdy
Keyword(s):  
Climate Change ◽  
Long Range ◽  
Time Scales ◽  
Weather Conditions ◽  
Weather Data ◽  
Future Climate Change ◽  
Data Sets ◽  
Fire Weather ◽  
Climate Change Projections ◽  
Different Time Scales

Spatio-temporal variations in fire weather conditions are presented based on various data sets, with consistent approaches applied to help enable seamless services over different time scales. Recent research on this is shown here, covering climate change projections for future years throughout this century, predictions at multi-week to seasonal lead times and historical climate records based on observations. Climate projections are presented based on extreme metrics with results shown for individual seasons. A seasonal prediction system for fire weather conditions is demonstrated here as a new capability development for Australia. To produce a more seamless set of predictions, the data sets are calibrated based on quantile-quantile matching for consistency with observations-based data sets, including to help provide details around extreme values for the model predictions (demonstrating the quantile matching for extremes method). Factors influencing the predictability of conditions are discussed, including pre-existing fuel moisture, large-scale modes of variability, sudden stratospheric warmings and climate trends. The extreme 2019–2020 summer fire season is discussed, with examples provided on how this suite of calibrated fire weather data sets was used, including long-range predictions several months ahead provided to fire agencies. These fire weather data sets are now available in a consistent form covering historical records back to 1950, long-range predictions out to several months ahead and future climate change projections throughout this century. A seamless service across different time scales is intended to enhance long-range planning capabilities and climate adaptation efforts, leading to enhanced resilience and disaster risk reduction in relation to natural hazards.

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