Fire model library

Fire Danger Indices used in Amicus

In Australia, two systems for calculating fire danger (as a numerical index and as a categorised rating) are used, one for grasslands and one for forests the two predominant vegetation types.

Grassland Fire Danger Index

Calculated using the McArthur Mk 4 Grassland Fire Danger Meter which was developed as a circular slide rule by Alan McArthur in the 1960s and published by the Forestry and Timber Bureau which in 1975 became the CSIRO Division of Forestry.

McArthur AG (1966) ‘Weather and grassland fire behaviour.’ Forestry and Timber Bureau Leaflet 100, Department of Natural Development, Canberra, ACT.

Forest Fire Danger Index

Calculated using the McArthur Mk 5 Forest Fire Danger Meter. This was also developed by Alan McArthur, published by the Forestry and Timber Bureau.

McArthur AG (1967) ‘Fire behaviour in eucalypt forests.’ Forestry and Timber Bureau Leaflet 107, Department of Natural Development,Canberra, ACT.

Both of these meters were converted to equations by Noble, Bary and Gill (1980) and are employed here. The Mk 4 Grassland Fire Danger Meter and the Mk 5 Forest Fire Danger Meter were metricated versions of the previous versions which appeared in the publications by McArthur listed above.

Noble IR, Bary GAV, Gill AM (1980) McArthur’s fire danger meters expressed as equations. Australian Journal of Ecology 5, 201-203.

Fire Behaviour Models used in Amicus

Amicus employs a number of fire behaviour models that have been developed by researchers from a range of organisations over the years. It is now more than 60 years since Alan McArthur became Australia’s first full time bushfire behaviour researcher. In that time, many systems have been developed for predicting the potential behaviour of bushfires in a wide variety of vegetation and fuel types. Amicus follows the analysis of the performance of these models by CSIRO (see Cruz et al 2015 in the Publications menu and the book A Guide to Rate of Spread Models for Australian Vegetation on the Home page) and provides those models recommended for particular fuel types. A brief description of and original reference for each recommended model is given below, organised by fuel types.

Grassland vegetation

Fuel types = “Continuous open”, “Woodlands” and “Open forest”.

These equations are used for fires in continuous open grasslands and woodlands and open forest with grassy understoreys. They were developed by CSIRO and were published in Cheney et al. (1998), with a more descriptive explanation of their application given in the Grassfires book (Cheney and Sullivan 2008) and Sullivan (2010).

Cheney NP, Gould JS, Catchpole WR (1998) Prediction of fire spread in grasslands. International Journal of Wildland Fire 8, 1-13.

Cheney P, Sullivan A (2008) ‘Grassfires, fuel, weather and fire behaviour.’ (CSIRO Publishing: Collingwood).

Sullivan, AL (2010) Grassland fire management in future climate. Advances in Agronomy, 106, 173-208.

Fuel type = “Spinifex”

This model was developed from two large sets of experimental fires conducted by Neil Burrows and colleagues from the Western Australian Department of Environment and Conservation (now known as the Department of Parks and Wildlife, was formerly Department of Conservation and Land Management). The paper was published in the Proceedings of the Royal Society of Queensland, after originally being presented at the Bushfire 2006 conference. It replaced an earlier version of the model published in 1990. A replacement model containing data from another series of experiments is expected soon.

Burrows ND, Ward B, Robinson A (2009) Fuel dynamics and fire spread in spinifex grasslands of the Western Desert. In ‘Proceedings of the Royal Society of Queensland’ pp. 69-76. (Royal Society of Queensland Inc.: St Lucia Australia).

Native forest vegetation

Fuel type = “Dry Eucalypt”, Condition = “Wildfire”

This version of Amicus provides three options for predicting wildfire behaviour in dry eucalypt forests during wildfire conditions. The first two of these (Vesta Mk1 and Mk2) are available in the ‘fuel type’ drop down menu within the Native Forest vegetation groups, the third option is the McArthur Mk5 Forest Fire Model, which can be activated by clicking the “Enable McArthur Mk5 Forest Fire Model in Native Forest” check box within the settings| fire models menu.

Vesta Mk 2 (Cruz et al. 2022)

The Vesta Mk 2 (Cruz et al. 2022) model is available in newer Amicus versions (0.7+). It was developed using a large dataset from experimental and wildfires, including the 116 experimental fires used to develop the original Vesta Mk 1 dry eucalypt forest fire model (Cheney et al. 2012). It incorporates the effects of wind speed, fine dead fuel moisture, understorey fuel structure, long term landscape dryness and slope steepness and has three phases of fire propagation associated with low, moderate to high and higher intensity fire behaviour (Cruz 2021). This model supersedes the Vesta Mk 1 model and is now the recommended model for wildfires in dry eucalypt forests, however as it is only a rate of spread model, the same flame height (Equation 11 in Cheney et al. 2012) and maximum spotting distance models (Gould et al. 2007) used for the Vesta Mk 1 fuel scenario are applied here.

This model contains different inputs to the Vesta Mk 1 model, with a wind adjustment factor used to estimate the in-forest flame-level wind speed from 10 metres in the open, Drought Factor to help determine fuel availability and the fuel load (combined surface and near-surface fuels) and understory fuel height used as fuel inputs. The understorey fuel height is the average height of understorey near-surface and elevated fuels and can be determined from the Elevated Fuel Hazard Score and elevated layer height.

Required inputs

Dead fuel moisture content: air temperature, relative humidity, date, time of day, cloud cover

Rate of spread: wind speed, wind adjustment factor, drought factor, dead fuel moisture content, load of surface and near-surface fuels, understorey fuel height (determined from Elevated Fuel Hazard Score and elevated layer height).

Flame height: rate of spread, elevated fuel height (Equation 11 in Cheney et al. 2012)

Maximum spotting distance: rate of spread, bark fuel score or hazard (Gould et al. 2007).

Primary references

Cruz, MG, Cheney, NP, Gould, JS, McCaw, WL, Kilinc, M, Sullivan, AL (2022) An empirical-based model for predicting the forward spread rate of wildfires in eucalypt forests. International Journal of Wildland Fire

Cruz, MG (2021) The Vesta Mk 2 rate of fire spread model: a user’s guide. CSIRO Client Report No. EP2021-2731, Canberra.

Additional references

Cheney NP, Gould JS, McCaw WL, Anderson WR (2012) Predicting fire behaviour in dry eucalypt forest in southern Australia. Forest Ecology and Management 280, 120-131.

Gould, JS, McCaw, WL, Cheney, NP, Ellis, PF, Matthews, S, (2007) ‘Field guide- Fuel assessment and fire behaviour prediction in dry eucalypt forest.’ (Ensis-CSIRO, Canberra ACT, and Department of Environment and Conservation, Perth WA.

Vesta Mk 1 (Cheney et al. 2012)

This model is based on a large set of experimental fires conducted under dry summer conditions by CSIRO and the Western Australian Department of Parks and Wildlife and validated against a large set of wildfire observations. It was published in the journal Forest Ecology and Management and is now been superseded by the Vesta Mk 2 (Cruz et al. 2022) model.

Amicus uses the Fuel Hazard Score version of the Vesta Mk1 Dry Eucalypt Forest Fire Model (Equation 9 in Cheney et al. 2012) for both the Fuel Hazard Rating and Fuel Hazard Score hazard input type options. Hazard ratings are converted to scores as indicated in the pop-up tables. The prediction of maximum spotting distance is based on the tables presented in Gould et al. (2007).

Required inputs

Dead fuel moisture content: air temperature, relative humidity, date, time of day, cloud cover

Rate of spread (fuel hazard score method): wind speed, dead fuel moisture content, surface fuel hazard score, near- surface fuel hazard score, near surface fuel height,

Rate of spread (fuel hazard rating method): wind speed, dead fuel moisture content, surface fuel hazard rating, near- surface fuel hazard rating, near surface fuel height,

Flame height: rate of spread, elevated fuel height

Maximum spotting distance: rate of spread, bark fuel score or hazard

Intensity: rate of spread, fuel load [heat yield is assumed to be 18600 kJ/kg]

References

Cheney NP, Gould JS, McCaw WL, Anderson WR (2012) Predicting fire behaviour in dry eucalypt forest in southern Australia. Forest Ecology and Management 280, 120-131.

Other papers and guides associated with this model include:

Gould, J. S.; McCaw, W. L. & Cheney, N. P. 2011. Quantifying fine fuel dynamics and structure in dry eucalypt forest (Eucalyptus marginata) in Western Australia for fire management. Forest Ecology and Management, 262, 531-546.

McCaw, L. W.; Gould, J. S.; Cheney, N. P.; Ellis, P. F. & Anderson, W. R. 2012. Changes in behaviour of fire in dry eucalypt forest as fuel increases with age. Forest Ecology and Management, 271, 170-181.

Wotton, B. M.; Gould, J. S.; McCaw, W. L.; Cheney, N. P. & Taylor, S. W. 2011. Flame temperature and residence time of fires in dry eucalypt forest. International Journal of Wildland Fire, 21, 270-281.

McArthur Mk 5 Forest Fire Model

Originally published as a table on the back of the Mk 4 Forest Fire Danger Meter (McArthur 1967) this model was retro-engineered into equations by Noble et al. (1980). This model has been superseded by the Vesta Mk 1 and Mk 2 models (Cheney et al. 2012, Cruz et al. 2022). The McArthur Mk5 Forest Fire model has been shown to consistently underpredict the spread of wildfires by a factor of 2 to 3 (Burrows 1999, McCaw et al. 2008).

Required inputs:

Rate of spread: air temperature, relative humidity, wind speed, drought factor, fuel load

Flame height and Maximum spotting distance: rate of spread and fuel load

References

Burrows, ND (1999) Fire behaviour in jarrah forest fuels: 2 Field experiments. CALMScience 3, 57-84.

Cheney NP, Gould JS, McCaw WL, Anderson WR (2012) Predicting fire behaviour in dry eucalypt forest in southern Australia. Forest Ecology and Management 280, 120-131.

McArthur AG (1967) ‘Fire behaviour in eucalypt forests.’ Forestry and Timber Bureau Leaflet 107, Department of Natural Development, Canberra, ACT.

McCaw, WL, Gould, JS, Cheney, NP (2008) Existing fire behaviour models under-predict the rate of spread of summer fires in open jarrah (Eucalyptus marginata) forest. Australian Forestry 71, 16-26.

Noble IR, Bary GAV, Gill AM (1980) McArthur’s fire danger meters expressed as equations. Australian Journal of Ecology 5, 201-203.

Fuel type = “Wet Eucalypt”, Condition = “Wildfire”

There are two models available for wildfires in this fuel type. Both are adaptations of models developed for dry eucalypt forests. There are no flame height and maximum spotting distance models for this fuel type.

Vesta Mk 2 (Cruz et al. 2022)

The Vesta Mk 2 (Cruz et al. 2022) model is available in newer Amicus versions (0.7+). The adaptation for wet forests follows the detailed instructions proved in the model’s user guide (Cruz 2021). This model supersedes the adaptation of the Vesta Mk 1 model and is now the recommended model for wildfires in wet eucalypt forests.

Required inputs

Dead fuel moisture content: air temperature, relative humidity, date, time of day, cloud cover, understorey type

Rate of spread: wind speed, wind adjustment factor, adjusted drought factor (wind adjustment factor, slope and aspect), dead fuel moisture content, load of surface and near-surface fuels, understorey fuel height (determined from Elevated Fuel Hazard Score and elevated layer height).

References

Cruz, MG (2021) The Vesta Mk 2 rate of fire spread model: a user’s guide. CSIRO Client Report No. EP2021-2731, Canberra.

Vesta Mk 1 (Cheney et al. 2012)

This model is the same as the application of the Vesta Mk 1 model in dry eucalypt forests except that it uses wind speed correction factors (i.e. three coefficients that modify the wind speed in the open to that under the canopy) taken from the Forest Fire Behaviour Tables for Western Australia developed and published by the Western Australian Department of Conservation and Land Management.

Required inputs

Dead fuel moisture content: air temperature, relative humidity, date, time of day, cloud cover, understorey type

Rate of spread (fuel hazard score method): wind speed, understorey type, dead fuel moisture content, surface fuel hazard score, near- surface fuel hazard score, near surface fuel height,

Rate of spread (fuel hazard rating method): wind speed, understorey type, dead fuel moisture content, surface fuel hazard rating, near- surface fuel hazard rating, near surface fuel height,

Intensity: rate of spread, fuel load [heat yield is assumed to be 18600 kJ/kg]

References

Cheney NP, Gould JS, McCaw WL, Anderson WR (2012) Predicting fire behaviour in dry eucalypt forest in southern Australia. Forest Ecology and Management 280, 120-131.

Sneeuwjagt RJ, Peet GB (1985) ‘Forest fire behaviour tables for Western Australia.’ (WA Department of Conservation and Land Management: Perth)

Shrubland vegetation

Fuel type = “Temperate shrubland”

This model was developed from a combined dataset from a range of different locations and conditions from a large set of authors.

Anderson W, Cruz M, Fernandes PM, McCaw WL, Antonio Vega J, Bradstock RA, Fogarty L, Gould JS, McCarthy GJ, Marsden-Smedley JB, Matthews S, Mattingley G, Pearce HG, van Wilgen B (2015) A generic, empirical-based model for predicting rate of fire spread in shrublands. International Journal of Wildland Fire, in press.

Fuel type = “Buttongrass”

This model was developed by Jon Marsden-Smedley (University of Tasmania) and Wendy Anderson (formerly Catchpole, University of NSW). This fuel type is mainly only present in western Tasmania.

Marsden-Smedley JB, Catchpole WR (1995) Fire modelling in Tasmanian buttongrass moorlands II. Fire behaviour. International Journal of Wildland Fire 5, 215-228.

Fuel type = “Semi –arid heath”

Cruz MG, Matthews S, Gould J, Ellis P, Henderson M, Knight I, Watters J (2010) ‘Fire dynamics in mallee-heath; fuel weather and fire behaviour prediction in South Australian semi-arid shrublands.’ Bushfire Cooperative Research Centre Technical Report A.10.01, East Melbourne, Victoria.

Fuel type = “Semi –arid mallee-heath”

Cruz MG, McCaw WL, Anderson WR, Gould JS (2013) Fire behaviour modelling in semi-arid mallee-heath shrublands of southern Australia. Environmental Modelling & Software 40, 21-34.

Plantations vegetation

Fuel type = “pine”

Cruz MG, Alexander ME, Fernandes PAM (2008) Development of a model system to predict wildfire behaviour in pine plantations. Australian Forestry 71, 113-121.

Fuel type = “blue gum”

There are no formal models specifically for fire spread in blue gum plantations. Instead, the fire spread model to be employed depends on the age and productivity of the plantation. If the plantation is relatively young and the ground cover is dominated by grass then the grassland fire spread model of Cheney et al. (1998) is used (with a user-defined wind correction factor). . If the plantation is more well established with dominate litter ground cover then the model for wildfires in dry eucalypt forests (Cheney et al. 2012) will be used.

Other models used in Amicus

Slope correction

For correction factors for fire spread on slopes, Amicus employs the McArthur rule of thumb of doubling the flat ground rate of spread for every ten degrees on positive slopes. For fire spread on negative slopes, Amicus uses the slope correction factor model kataburn developed by Sullivan et al. (2014). Slope is calculated as that sensed in the direction of the wind.

Sullivan AL, Sharples JJ, Matthews S. and Plucinski MP (2014) A downslope fire spread correction factor based on landscape-scale fire behaviour. Environmental Modelling & Software 62, 153-163.