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Fine fuel hazard levels are converted to an equivalent fine fuel load (t/ha). While coarser fuels are consumed during a fire, the combustion of fine fuels is the process that predominantly determines spread rates. Fuels are considered as three separate strata; surface (which includes near-surface fuels), elevated fuel and bark, in accordance with forest fuel measurement standards in Southern Australia (McCarthy et al. 1999; Hines et al. 2010). Fuel classes that have no elevated or bark fuels are considered by PHOENIX as grasslands and are processed using functions derived from the CSIRO grassland fire spread model (Cheney et al. 1998).

Table 3. PHOENIX fuel types currently recognised in southern Australia.

Veg Type	Code	FuelCode	Description	Fuel Characteristics
Forest	F01	15	Rainforest	dense vegetation with little dead material, epiphytes, vines, ferns, rarely dry
	F02	32	Wet Forest with rainforest understory	wet sclerophyll forest with a mesic understorey
	F03	13	Riparian Forest shrub	dense vegetation but with a small proportion of dead material
	F04	11	Wet Forest shrub & wiregrass	high biomass forest, but with little dead suspended material unless wiregrass present
	F05	12	Damp Forest shrub	dense understorey and potentially high bark hazard (karri)
	F06	40	Semi-mesic Sclerophyll forest	forest with semi-mesic shrubs and flammable grasses, sedge understorey
	F07	33	Swamp Forest	dense Melaleuca forest with little understorey
	F08	6	Forest with shrub	potentially high bark hazard, shrubs moderate flammability (mixed jarrah/karri)
	F09	7	Forest herb-rich	potentially high bark hazard, little elevated fuel
	F10	45	Dry Forest shrubs	dry forest with continuous understorey, (southern jarrah)
	F11	8	Dry Open Forest shrub/herbs	dry forest with open understorey (northern jarrah)
Grass/sedges	G01	16	High Elevation Grassland	dense sward of tussock grasses or herbs, high cover
	G02	4	Moist Sedgeland / Grassland	dense sward, potentially high dead component, button grass
	G03	29	Ephemeral grass/sedge/herbs	dense grass and sedges with potentially high levels of dead suspended material
	G04	20	Temperate Grassland / Sedgeland	grasses and sedges widespread, but varying in biomass
	G05	44	Hummock grassland	hummock grassland, discontinuous surface fuels
Herbs	H01	30	Moorland / Feldmarks	low flammability cushion plants
	H02	36	Alpine herbland	dense, upright, low flammability herbs
	H03	34	Wet herbland	freshwater herbs on mud flats
	H03	37	Wet herbland	low herbs in seasonally inundated lakebeds or wetlands
Mallee	M01	27	Mallee chenopod	low flammability except after exceptional rain bringing grasses
	M02	42	Mallee grass	mallee woodland with predominantly grass understorey
	M03	25	Mallee shrub/heath	continuous shrub layer but amount of dead material depending on species present
	M04	26	Mallee spinifex	discontinuous fuels, very flammable under windy conditions
Bare	NIL	0	Water, sand, no vegetation	fuel absent
Plantations	P01	98	Softwood Plantation	dense canopy with continuous surface fuels
	P02	99	Hardwood Plantation	uniform canopy with continuous surface fuels
Shrubs	S01	17	High Elevation Shrubland/Heath	dense cover of shrubs with surface fuel largely under plants
	S02	14	Riparian shrubland	dense vegetation with little dead material
	S03	35	Wet Scrub	flammable shrubland with high level of dead elevated fuels
	S04	1	Moist Shrubland	dense shrubland, salt affected
	S05	31	Dry Closed Shrubland	tea-tree or paperbark thickets, little understorey
	S06	21	Broombush / Shrubland / Tea-tree	dense shrubland, but with relatively low level of dead material
	S07	10	Sparse shrubland	sparse shrubby vegetation with discontinuous surface fuels
	S08	3	Low flammable Shrubs	low flammability except after exceptional rain bringing grasses
	S09	38	Mangroves / Aquatic Herbs	trees, shrubs and herbs in permanent water, unburnable
Heaths	S10	23	Wet Heath	dense heath possibly with dense sedgy undergrowth
	S11	24	Dry Heath	dense heath with significant amounts of dead material
Woodland	W01	18	High Elevation Woodland shrub	wooded area with shrubby understorey
	W02	19	High Elevation Woodland grass	wooded area with continuous grass tussocks
	W03	97	Orchard / Vineyard	orchard or vineyard
	W04	2	Moist Woodland	low trees, shrubby, sedgy understorey, bark hazard
	W05	22	Woodland bracken/shrubby	wooded area with varying understorey, but not heathy
	W06	9	Woodland Grass/Herb-rich	surface fuels dominated by grass and herbs
	W07	5	Woodland Heath	flammable shrubs and high bark hazard
	W08	41	Gum Woodland heath/shrub	gum woodland with moderate bark hazard, heath/shrub understorey
	W09	43	Gum Woodland grass/herbs	gum woodland with moderate bark hazard, herbaceous understorey
	W10	39	Savanna grasslands	tall flammable grasses in an open woodland
	W11	28	Woodland Callitris/Belah	low flammability except after exceptional rain bringing grasses

4.2 Wind reduction factors

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4.3.1 Purpose

Fuel types are used in conjunction with the fire history layer to generate fuel levels at the time of the simulation. Based on the time of ignition specified by the user, fuel levels are calculated through the combination of fuel type and the time since the last fire using fuel accumulation curves defined in the fuel type conversion file.

4.3.2 Basis

This layer is based upon fire history provided by the user.

4.3.3 Assumptions and limitations

In the case of overlapping fire histories, PHOENIX only uses the most recent fire occurrence.

4.3.4 User interactions

PHOENIX uses the fuel accumulation model (see Section 5.7: Fuel Accumulation) to calculate fine fuel hazard classes which are then converted to an equivalent fuel load (t/ha) for surface, elevated and bark fuels. The accumulation curves are part of the fuel type conversion file.

The user can upload a supplementary fire history layer to PHOENIX to capture recent fire events or to explore the effect of hypothetical fires in the landscape.

4.3.5 Description

Fuel types are used in conjunction with a user-provided fire history layer to create fuel layer information used in PHOENIX simulations and stored in the Fire Grid. The time since the most recent fire is used to estimate fuel levels using negative exponential accumulation curves (discussed in Section 5.7: Fuel Accumulation). As data is retained for only the most recent fires (see Figure 9), where historic fires are being simulated, the fire history layer must be adjusted to be representative of the appropriate conditions.

Figure 9. Diagram of how PHOENIX treats overlapping fire history. On the left, two fires have been mapped, one in 1972 and the other in 1985. On the right, a new fire in 2008 has overlapped these earlier fires and has replaced their fire history in the overlapping areas.

ESRI Shapefiles can be used to supplement the baseline fire history layer for particular simulation runs. This provision is made to account for fires that have occurred since the baseline fire history was processed or to enable hypothetical prescribed burning scenarios to be quickly evaluated. The supplementary fire history is added to any existing fire history layer and processed in the same manner as the fire history stored in the Fire Grid.

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Alternatively, a string of weather data can be specified. Values for the air temperature (oC), relative humidity (%), wind direction (deg), wind speed (km/h), drought factor (0-10), degree of grass curing (%) and cloud cover (%) for specified times must be provided as specified in Table 4. An example is provided in Table 5.

Table 4. Standard weather attributes

Attribute	Comments
Date/Time	Date and time of weather condition
Temperature	10 minute average in °C measured at 1.5 metres in a screen
Relative Humidity	10 minute average as a %, measured at 1.5 metres in a screen
Wind Direction	10 minute average in degrees, measured at 10 metres in the open
Wind Speed	10 minute average in km/h, measured at 10 metres in the open
Drought Factor	Fine fuel availability 0-10
Curing	Grass curing level as a % (0-100)
Cloud	Cloud cover as a % (0-100)

Table 5. An example of user-provided point stream weather inputs that are time-stamped

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4.8.5.1 Upper-level winds

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Spot forecast, gridded forecast and automatic weather station data are often temporally quite coarse. If used in this raw form, weather data would result in instantaneous condition changes at the supplied date and time, which (apart from a frontal system) would not be realistic. To emulate real-world weather behaviour, weather conditions are linearly interpolated between entries.

Figure 11. Raw versus interpolated temperature values (in degrees Celsius).

A simple linear interpolation is used to derive continuous weather conditions for:

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