Andrew L. Sullivan

Wildland surface fire spread modelling, 1990-2007. 1: Physical and quasi-physical models.

In recent years, advances in computational power have led to an increase in attempts to model the behaviour of wildland fires and to simulate their spread across the landscape. The present series of articles endeavours to comprehensively survey and precis all types of surface fire spread models developed during the period 1990–2007, providing a useful starting point for those readers interested in recent modelling activities. The current paper surveys models of a physical or quasi-physical nature. These models are based on the fundamental chemistry and physics, or physics alone, of combustion and fire spread. Other papers in the series review models of an empirical or quasi-empirical nature, and mathematical analogues and simulation models. Many models are extensions or refinements of models developed before 1990. Where this is the case, these models are also discussed but in much less detail.

Wildland surface fire spread modelling, 1990–2007. 2: Empirical and quasi-empirical models

In recent years, advances in computational power have led to an increase in attempts to model the behaviour of wildland fires and to simulate their spread across landscape. The present series of articles endeavours to comprehensively survey and precis all types of surface fire spread models developed during the period 1990–2007. The current paper surveys models of an empirical or quasi-empirical nature. These models are based on the statistical analysis of experimentally obtained data with or without some physical framework for the basis of the relations. Other papers in the series review models of a physical or quasi-physical nature, and mathematical analogues and simulation models. The main relations of empirical models are those of wind speed and fuel moisture content with rate of forward spread. The focus of the discussion is on the treatment of the wind speed and fuel moisture functions by the models.

Wildland surface fire spread modelling, 1990–2007. 3: Simulation and mathematical analogue models

In recent years, advances in computational power have led to an increase in attempts to model the behaviour of wildland fires and to simulate their spread across landscape. The present series of articles endeavours to comprehensively survey and precis all types of surface fire spread models developed during the period 1990–2007. The present paper surveys models of a simulation or mathematical analogue nature. Most simulation models are implementations of existing empirical or quasi-empirical models and their primary function is to convert these generally one-dimensional models to two dimensions and then simulate the propagation of a fire perimeter across a modelled landscape. Mathematical analogue models are those that are based on some mathematical concept (rather than a physical representation of fire spread) that coincidentally represents the spread of fire. Other papers in the series survey models of a physical or quasi-physical nature, and empirical or quasi-empirical nature. Many models are extensions or refinements of models developed before 1990. Where this is the case, these models are also discussed but much less comprehensively.In recent years, advances in computational power and spatial data analysis (GIS, remote sensing, etc) have led to an increase in attempts to model the spread and behvaiour of wildland fires across the landscape. This series of review papers endeavours to critically and comprehensively review all types of surface fire spread models developed since 1990. This paper reviews models of a simulation or mathematical analogue nature. Most simulation models are implementations of existing empirical or quasi-empirical models and their primary function is to convert these generally one dimensional models to two dimensions and then propagate a fire perimeter across a modelled landscape. Mathematical analogue models are those that are based on some mathematical conceit (rather than a physical representation of fire spread) that coincidentally simulates the spread of fire. Other papers in the series review models of an physical or quasi-physical nature and empirical or quasi-empirical nature. Many models are extensions or refinements of models developed before 1990. Where this is the case, these models are also discussed but much less comprehensively.

Climate change, fuel and fire behaviour in a eucalypt forest

A suite of models was used to examine the links between climate, fuels and fire behaviour in dry eucalypt forests in south-eastern Australia. Predictions from a downscaled climate model were used to drive models of fuel amount, the moisture content of fuels and two models of forest fire behaviour at a location in western Sydney in New South Wales, Australia. We found that a warming and drying climate produced lower fine fuel amounts, but greater availability of this fuel to burn due to lower moisture contents. Changing fuel load had only a small effect on fuel moisture. A warmer, drier climate increased rate of spread, an important measure of fire behaviour. Reduced fuel loads ameliorated climate-induced changes in fire behaviour for one model. Sensitivity analysis of the other fire model showed that changes in fuel amount induced changes in fire behaviour of a similar magnitude to that caused directly by sensitivity to climate. Projection of changes in fire risk requires modelling of changes in vegetation as well as changes in climate. Better understanding of climate change effects on vegetation structure is required.

A semi-transparent model of bushfire flames to predict radiant heat flux

The radiation emitted by a body is related through the Stefan-Boltzmann equation to the temperature of the emitting element. In the case of flame, the emitting elements are carbon particles. Existing models of bushfire flame radiation assume, however, that the flame radiates as a surface with an emissivity of 1 (i.e. a blackbody). This is only true when the flame is thick enough to provide a continuous wall of radiating carbon particles. In this paper we propose a semi-physical model of radiant heat flux from bushfire flame that calculates the emissivity of the flame front based on its geometry and the optical properties of the flame. This model is calibrated using conservation of energy principles and empirical information about the radiant heat energy as a percentage of total energy of the flame. Comparisons are made with the flames generated by a propane-fuelled bushfire flame front simulator.

Empirical-based models for predicting head-fire rate of spread in Australian fuel types

Summary The knowledge of a free-burning fire’s potential rate of spread is critical for safe and effective bushfire control and use. A number of models for predicting the head-fire rate of spread in various types of Australian vegetation have been developed over the past 60 years or so since Alan G. McArthur began his pioneering research into bushfire behaviour. Most of the major Australian vegetation types have had more than one model developed for operational use. These include grassland, shrubland, both dry and wet eucalypt forests, and pine plantation fuel types. A better understanding of the technical basis for each of these models and their utility is essential for the correct selection and application of the most appropriate models. This review provides a systematic overview of 22 models of the rate of fire spread and their applicability in prescribed burning and wildfire operations. Background information and a description of each model is given. This includes information on the data used in the model development that defines the bounds of its application. The mathematical equations that represent each model are given along with a discussion of model form and behaviour, the main input variables and their influence, and evaluations of model performance undertaken to date. This review has enabled the identification of those models that constitute the current state of knowledge with respect to bushfire behaviour science in Australia. We recommend the models that should underpin best practice in the near term in the operational prediction of fire behaviour and those that should no longer be used, and provide reasons for these recommendations.

Predicting the radiant heat flux from burning logs in a forest following a fire

Summary The radiant heat flux resulting from burning logs on the forest floor determines how soon after the passage of a bushfire people can survive on the burnt-out ground. A method to predict this flux was developed from the burn-out time of logs expressed as a function of initial log diameter and a given size-class distribution of logs and branches. This gives an estimate of the fraction of total power emitted per unit area, and an estimate of the radiant heat flux. In jarrah (Eucalyptus marginata) forest, 7 years after the last prescribed burn and carrying 36.51 ha-1 of log and branch material, it takes 15 min before the radiant heat flux drops below the threshold for near-instantaneous pain and 31 min before it drops below the threshold value for long-term survival. Examples of minimum times to thresholds for other forest type groups are given, along with field observations that support the estimates.

Effects of spatial and temporal variation in environmental conditions on simulation of wildfire spread

Environmental conditions, such as fuel load and moisture levels, can influence the behaviour of wildfires. These factors are subject to natural small-scale variation which is usually spatially or temporally averaged for modelling fire propagation. The effect of including this variation in propagation models has not previously been fully examined or quantified. We investigate the effects of incorporating three types of variation on the shape and rate of propagation of a fire perimeter: variation in combustion conditions, wind direction and wind speed. We find that increasing the variation of combustion condition decreases the overall rate of propagation. An analytical model, based on the harmonic mean, is presented to explain this behaviour. Variation in wind direction is found to cause the development of rounded flanks due to cumulative chance of outward fluctuations at the sides of the perimeter. Our findings may be used to develop improved models for fire spread prediction. Display Omitted Implementation of a wildfire spread model based on the level set method.Investigation of wildfire propagation under stochastic wind and fuel conditions.Local variation in combustion condition slows the rate of propagation.Local variation in wind direction is found to increase flank spread.A harmonic mean is preferential for spatially varying parameters in spread models.

A downslope fire spread correction factor based on landscape-scale fire behaviour

There is currently no fundamental understanding of the effects of topography on the behaviour of fires burning over a landscape. While a number of empirical models are employed operationally around the world, the effects of negative slopes on fire spread are ignored in all but one prediction system which may result in incorrect predictions. The general observation that large fires burning for some time over undulating topography can be approximated by assuming fire spread over flat ground is used to construct a quasi-empirical model framework for downslope rate of spread correction called kataburn. Kataburn is formulated for two alternative interpretations of slope spread-planar and linear-and can be applied to any empirical upslope spread correction model. Versions of kataburn derived using such models from Australia, the US and Canada are compared against experimental downslope data from the literature and found to better represent downslope spread than the existing operational downslope function. Topography has a significant effect on the spread of fire across the landscape.Appropriate treatment of negative (lee) slope fire spread effects is important.A new model framework, kataburn, is developed from functional considerations of fire spread across the landscape.Kataburn can be used to construct negative slope spread corrections for any fire spread prediction system.Kataburn is shown to perform much better than the only existing operational downslope model.

Improving the reliability and utility of operational bushfire behaviour predictions in Australian vegetation

Fire behaviour and spread predictions guides suppression strategies and public warnings during wildfires. The scientific understanding of fire behaviour forms the core of these predictions, but is incomplete, and expert judgement and experience are required to augment the evidence based knowledge. Amicus is a new decision support system that implements contemporary, published and operationalised bushfire behaviour models (e.g. rate of spread, flame height, fireline intensity, spotting distance) in the Australian bushfire context. It enables the inclusion of expert judgement and local knowledge, allows users to analyse temporal trends and uncertainty in inputs, and facilitates reliable and practical predictions. This paper provides a comprehensive overview of Amicus, including its operation and functionality, identifies the boundaries of the current understanding of fire science, discusses the major limitations in existing knowledge, and provides a framework for allowing deterministic and anecdotal/local knowledge to be incorporated into formal fire behaviour predictions. Fire behaviour predictions inform suppression strategies and public warnings.Expert judgement and experience can augment fire science.Amicus combines science and expert knowledge for robust transparent predictions.Amicus highlights operational domains and the limits of model reliability.Users can investigate the impact of uncertainty in input data on outputs.