Stuart Matthews

A process-based model of fine fuel moisture

This paper presents the first complete process-based model for fuel moisture in the litter layer. The model predicts fuel moisture by modelling the energy and water budgets of the litter, intercepted precipitation, and air spaces in the litter. The model was tested against measurements of fuel moisture from two sets of field observations, one made in Eucalyptus mallee-heath under dry conditions and the other during a rainy period in Eucalyptus obliqua forest. The model correctly predicted minimum and maximum fuel moisture content and the timing of minima and maxima in the mallee-heath. Under wet conditions, wetting and drying of the litter profile were correctly predicted but wetting of the surface litter was over-predicted. The structure of the model and the dependence of predictions on model parameters were examined using sensitivity and parameter estimation studies. The results indicated that it should be possible to adapt the model to any forest type by specifying a limited number of parameters. A need for further experimental research on the wetting of litter during rain was also identified.

A generic, empirical-based model for predicting rate of fire spread in shrublands

A shrubland fire behaviour dataset was assembled using data from experimental studies in Australia, New Zealand, Europe and South Africa. The dataset covers a wide range of heathlands and shrubland species associations and vegetation structures. Three models for rate of spread are developed using 2-m wind speed, a wind reduction factor, elevated dead fuel moisture content and either vegetation height (with or without live fuel moisture content) or bulk density. The models are tested against independent data from prescribed fires and wildfires and found to predict fire spread rate within acceptable limits (mean absolute errors varying between 3.5 and 9.1 m min–1). A simple model to predict dead fuel moisture content is evaluated, and an ignition line length correction is proposed. Although the model can be expected to provide robust predictions of rate of spread in a broad range of shrublands, the effects of slope steepness and variation in fuel quantity and composition are yet to be quantified. The model does not predict threshold conditions for continuous fire spread, and future work should focus on identifying fuel and weather factors that control transitions in fire behaviour.

Dead fuel moisture research: 1991-2012

The moisture content of dead fuels is an important determinant of many aspects of bushfire behaviour. Understanding the relationships of fuel moisture with weather, fuels and topography is useful for fire managers and models of fuel moisture are an integral component of fire behaviour models. This paper reviews research into dead fuel moisture for the period 1991–2012. The first half of the paper deals with experimental investigation of fuel moisture including an overview of the physical processes that affect fuel moisture, laboratory measurements used to quantify these processes, and field measurements of the dependence of fuel moisture on weather, vegetation structure and topography. The second set of topics examine models of fuel moisture including empirical models derived from field measurements, process-based models of vapour exchange and fuel energy and water balance, and experimental testing of both types of models. Remaining knowledge gaps and future research problems are also discussed. Opportunities for exciting research in the future exist for basic fuel moisture processes, developing new methods for applying models to fire behaviour prediction, and linking fuel moisture and weather forecast models.

Effect of drying temperature on fuel moisture content measurements

Oven-drying of fuel samples is often used to determine fuel moisture content. In this study, laboratory measurements are used to demonstrate that drying temperature has a significant effect on the oven-dry mass of dead grass, pine and eucalyptus fuels. Differences between oven-dry masses of fuels dried at 60 and 105°C of up to 3.5% were measured. This is a large enough difference to have a significant effect on fire behaviour predictions. Samples should be dried at 105°C.

Simple models for predicting dead fuel moisture in eucalyptus forests.

Fire behaviour prediction requires models of dead fuel moisture that are both accurate and suitable for use for operational applications. The paper investigates two methods of developing a simple operational fine fuel moisture model from a more complex process-based model. The first simple model is a table of fuel moisture predictions for values of air temperature, relative humidity, wind speed and solar radiation. The second model reduces the original model to a single differential equation, which may be used on low-powered computers. The simple models are tested against the output of the original model and against observations from two case studies in dry eucalyptus forest in south-western Australia. The single differential equation model was capable of reproducing the prediction of the process-based model at all times of the day, with mean error (ME) in predictions of –0.1% and mean absolute error (MAE) of 0.6%. The table model performed less well, with ME = –0.7% and MAE = 1.1% at 1500 hours, and ME = –1.2% and MAE = 3.0% at other times of the day.

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.

Flow over Small Heat Islands: A Numerical Sensitivity Study

Abstract A two-dimensional nonlinear model with physical parameterizations was applied to simulate the observed diurnal variation on the 5-km-wide flat tropical island of Nauru in the trade wind zone. Both the model and Atmospheric Radiation Measurement (ARM) campaign aircraft observations indicate vigorous mixing in the typical sunny daytime conditions, leading to a warm plume downstream of the island. The models afternoon wind field displayed rising motion downstream and downwash ahead of the island with gravity wave structure, in accordance with linear models of steady flow over a heated island. The roughness difference between sea and land added local rising motion above the windward coast and sinking motion above the lee. Without large-scale wind U, a weakish sea-breeze (SB) pattern develops during the day in this model over the 5-km-wide island/peninsula. This pure SB circulation intensifies with increasing island width up to 40 km. When large-scale wind is present, the morning leeside SB cell is a...

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.

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.

Modelling fuel moisture under climate change

Purpose – Fuel moisture is an important determinant of fire behaviour. Changes in climate will result in changes in fuel moisture and this will impact fire management by modifying the length and severity of the fire season and by changing opportunities for prescribed burning. This paper aims to examine the effect of climate on fuel moisture in Eucalypt forests.Design/methodology/approach – A climate model is used to predict weather for five Australian cities from 1961 to 2100 under a high‐emissions scenario. Time series are extracted from the model and used as boundary conditions for a process‐based fuel moisture model. Fuel moisture predictions are used to examine two management variables: the number of days suitable for prescribed burning in spring, and the number of days when fire could burn in summer.Findings – There were significantly more fire days in warmer‐drier years. The number of days with extremely low fuel moisture was also higher in warmer‐drier years. Variation in the number of burning days...