1. Fuel State Need copyright info of photos.
Grassland photo copyright Felicity Gamble.

2. Why be interested? Fuel State effects Fire Danger and is important in
Fire Weather Warning decisions.
People may decide to:
Stay and defend property or
Go early
Fire and Emergency Agencies may decide to
Impose Fire Bans
Put resources on stand by

3. Module Goals At the end of this Module, you’ll be able to:
Describe the main fuel types for your region
Describe the relevant indices and their limitations for assessing the state of those fuel types
Locate and interpret current fuel state indices for your region
Assess sensitivity of fuel state to change over the next four days

4. What fuel types and indices are referred to in our region?
In order for plant material to burn, it must be at least partly dry. The drier it is, the more easily it burns.
Fuel dryness is assessed differently for different fuel types, with some indices varying according to local preferences.
What fuel types and indices are referred to in our region?
Photo copyright?
For detailed vegetation maps of Australia regions see

5. Jump Slide Continue Tasmania Victoria New South Wales Queensland
South Australia
Northern Territory
Western Australia
Continue

6. Jump Slide
Mount SDI
KBDI
Drought Factor
Curing
Continue

7. So now, can you… End Slide Show
Describe the main fuel types for our region?
Describe the relevant indices and their limitations?
Locate and interpret current fuel state indices?
Assess sensitivity of fuel state to change over the next four days?
End Slide Show

8. Fuel Types in Tasmania
For fire management purposes, the fuel types are classified as:
Forest
Grass
Moorland
Scrub/Heathland
Grassland is not currently referred to in fire danger calculations.
Image from Department of Tourism Parks, Heritage and the Arts; Tasmania Parks and Wildlife Service

9. Fuel State Indices used in Tasmania
Forest
Mount Soil Dryness Index
Drought Factor
Moorland
24 hour rainfall (incorporated within Fire Danger Meter)
Heathland
Return to Index Slide

10. Fuel State Indices used in Victoria
Forest
Keetch-Byram Drought Index
Drought Factor
Grassland
Curing
Return to Index Slide

11. Fuel State Indices used in NSW
Forest
Keetch-Byram Drought Index
Drought Factor
Grassland
Curing
Return to Index Slide

12. Fuel State Indices used in Queensland
Forest
Keetch-Byram Drought Index
Drought Factor
Grassland
Curing
Return to Index Slide

13. Fuel State Indices used in South Australia
Forest
Mount Soil Dryness Index
Drought Factor
Grassland
Curing
Return to Index Slide

14. Fuel State Indices used in NT
Grassland
Curing
Return to Index Slide

15. Fuel State Indices used in WA
Grassland
Curing
Forest - Managed by CALM rather than us
Return to Index Slide

16. Mount Soil Dryness Index
Mount SDI estimates the amount of rainfall (in mm) needed to saturate the soil profile. It is a measure of the long term dryness.
SDI = when the ground is saturated
SDI = 200 represents extremely dry conditions
SDI estimates the “long-term (heavy fuel) drying” and integrates effects of rain since last time the index zeroed (in principle, last winter, in practice anytime from yesterday to several years ago).

17. SDI Processes The SDI is calculated as:
Previous value + evaporation + transpiration
- (Precipitation – canopy interception – runoff)
Diagrams of the processes modeled in the SDI calculations.
Copyright of diagrams?

18. SDI parameters
Canopy interception is parameterised according to canopy type.
The regional Fire Weather Forecaster will have selected a canopy class for each station in conjunction with clients.
Where a “secondary SDI” is calculated this may be for a second canopy class.
Evapo-transpiration calculations include information about location. This is set for each station by the regional Fire Weather Forecaster.

19. SDI algorithm SDI (today) = SDI (yesterday) + Evapotranspiration*
- Effective Rainfall**
*Evapotranspiration a function of shape C1T-C2 where C1, C2 vary with SDI, and location.
**Rainfall except for that intercepted by the canopy and flash runoff.
Canopy interception a proportion of rain to a maximum value (proportion of up to 60% and maximum of up to 4mm according to forest class).
Flash runoff a proportion of rain (up to 5% according to forest class)

20. SDI Calculations
SDI is calculated daily from 9am observations of rainfall and temperature in the AIFS Ground Moisture Module.
Values are tabulated and available to view in the AIFS Product Store.
Exercise: Find the current data for our region.
Exercise: Is current data available in any other format?
How is data made available to local fire agencies?

21. SDI as an indicator of fire behaviour
As a rough indicator…
SDI 0-13: Most fuels unlikely to burn
SDI 14-25: Fine aerial fuels may burn with breeze
SDI 26-50: Fires possible during day
SDI 50+: Fires may be sustained overnight.
For fire weather purposes, SDI is used within calculation of the Drought Factor.
The Drought Factor estimates “short-term” or fine-fuel drying.
Where do these figures come from? Are they generally accepted? Have I reworded Paul’s table in a fair way?

22. SDI Variation - Temporal
This graph shows how SDI varied over two seasons at Mount Gambier (September 2003 to August 2005)
Note the gradual drying with sharp wetting due to rain events.

23. SDI Variation - Spatial
This map shows the SDI across Tasmania on 24 May 2005.
The pattern reflects the seasonal rainfall pattern.

24. Average SDI Values Early July Early Sept Early Nov Early May Early Jan
Gridded 30 year averages for SE Australia based on the 10km Australian Daily Rainfall Analysis grid have been calculated by Klara Finkele (2005).
Note the drying from September right through to May, followed by wetting.
Early July
Early Sept
Early Nov
Early May
Early Jan
Early Sept
Early Nov
Early March

25. Prediction of SDI
The index increases (dries) at up to 3mm a day in warm, wet-underfoot conditions.
Cooler conditions dry more slowly.
Dry-underfoot conditions have decreased capacity for further drying.
After the first 5-10mm, more than 95% of a rain event will decrease (wet) the index. So a 50mm rain event will decrease the SDI by about 45mm (though not to below 0, saturation of the soil).
As a rule of thumb (for up to 4-day forecasts):
If no rain is expected generally expect little change in SDI.
If rain is expected, expect the SDI to decrease (wet) by any rainfall exceeding 10mm.

26. SDI Problems Return to Index Slide SDI assumes a uniform soil profile
(Exercise: think of the two locations in our region with different soil profiles)
No account of wind, RH, insolation, slope etc. in calculating evapotranspiration
All of the above variables will vary even in the local area of a station for which SDI is calculated
Note that SDI is an index, not a measure. The regional Fire Weather forecaster may reset it at various times in conjunction with local fire agencies.
Return to Index Slide

27. Keetch Byram Drought Index
KBDI estimates the amount of rainfall (in mm) needed to saturate the soil profile. It is a measure of the long term dryness.
KBDI = when the ground is saturated
KBDI = 200 represents extremely dry conditions
KBDI estimates the “long-term (heavy fuel) drying” and integrates effects of rain since last time the index zeroed (in principle, last winter, in practice anytime from yesterday to several years ago).

28. KBDI Processes The KBDI is calculated as:
Previous value + evaporation + transpiration
- (Precipitation – canopy interception)
Copyright of diagrams?

29. KBDI parameters
Canopy interception is the first 5mm of any rain event (consecutive days with more than 2mm rain).
Evapo-transpiration calculations are parameterised by the annual rainfall.

30. KBDI algorithm KBDI (today) = KBDI (yesterday) + Evapotranspiration*
- Rainfall over 5mm**
*Evapotranspiration a function of KBDI, maxT, and annual average rainfall R as shown below.
**Consecutive days with >2mm rain counts as one rain event. Only the first 5mm rain for the event is discarded.

31. KBDI Calculations
KBDI is calculated daily from 9am observations of rainfall and temperature in the AIFS Ground Moisture Module.
Values are tabulated and available to view in the AIFS Product Store.
Exercise: Find the current data for our region.
Exercise: Is current data available in any other format?
How is data made available to local fire agencies?

32. KBDI as an indicator of fire behaviour
As a rough indicator…
KBDI 0-13: Most fuels unlikely to burn
KBDI 14-25: Fine aerial fuels may burn with breeze
KBDI 26-50: Fires possible during day
KBDI 50+: Fires may be sustained overnight.
For fire weather purposes, KBDI is used within calculation of the Drought Factor.
The Drought Factor estimates “short-term” or fine-fuel drying.
Are these figures sensible for KBDI???

33. KBDI Variation - Temporal
This graph shows how KBDI varied over two seasons at Horsham (May 2003 to May 2005).
Note the gradual drying with sharp wetting due to rain events.

34. Average KBDI Values 1 Sept 1 July 1 May 1 Nov 1 Sept 1 Jan 1 March
Gridded 30 year averages for Australia based on the 25km Australian Daily Rainfall Analysis grid as calculated by Klara Finkele (2005).
Note wetting after March in the south, and after November in the north.
1 Sept
1 July
1 May
1 Nov
1 Sept
1 Jan
1 March

35. Prediction of KBDI
The index increases (dries) at up to 3mm a day in warm, wet-underfoot conditions.
Cooler conditions dry more slowly.
Dry-underfoot conditions have decreased capacity for further drying.
After the first 5mm, a rain event will decrease (wet) the index. So a 50mm rain event will decrease the SDI by about 45mm subject to not decreasing below 0 (saturation of the soil).
As a rule of thumb (for up to 4-day forecasts):
If no rain is expected expect only gradual change in KBDI.
If rain is expected, expect the KBDI to decrease (wet) by any rainfall exceeding 5mm.

36. KBDI Problems Return to Index Slide
KBDI assumes a uniform soil profile
(Exercise: think of the two locations in our region with different soil profiles)
KBDI assumes forest type related to annual rainfall with no allowance for plantations.
No account of wind, RH, insolation, slope etc. in calculating evapotranspiration
All of the above variables will vary even in the local area of a station for which KBDI is calculated
Note that KBDI is an index, not a measure. The regional Fire Weather forecaster may reset it at various times in conjunction with local fire agencies.
Return to Index Slide

37. Drought Factor
The (Forest) Drought Factor estimates “short-term” or fine-fuel drying.
The DF estimates the proportion (in tenths) of the fine fuels (<6mm) in a forest that will burn in a fire.
DF=0 all fuels wet, no fires possible
DF=5 half the fine fuel will burn
DF=10 all fuels dry and ready to burn, including peat/logs

38. Drought Factor Calculations
Forest DF is calculated daily from 9am observations of rainfall in the AIFS Ground Moisture Module.
DF calculations use the Mount SDI or KBDI as the Drought Index input parameter (according to regional preference).
Current data is available on the same web page as the Drought Index (MSDI/KBDI) in the AIFS Product Store.
Exercise: Is current data available in any other format?
How is data made available to local fire agencies?

39. Drought Factor Calculation
DF is a function of the long term Drought or Dryness Index (MSDI or KBDI) and recent rainfall.
For example…
If MSDI/KBDI  25, the DF  6.
A DF of 10 requires MSDI/KBDI >100
The more rainfall, and the more recent it has been, the smaller the DF will be.

40. Drought Factor Algorithm
I = BKDI or Mount SDI (according to regional preference)
Ignore days with less than 2mm rain.
Consider any recent rain events. For each rain event, note the total rain (P mm) and the number of days ago that it occurred (N). An event is only said to be 0 days ago if it includes rain since 9am on the day in question.
The formula (almost) in use (for P>2, N>0) is
but with an upper limit of 6 for I<25; 7 for I <42; 8 for I <65; 9 for I <100; and 10 for all I.
Use the lowest DF calculated from the relevant rain events.

41. DF Behaviour - example A rain event of about 35mm over 4 days.
Long term Dryness Index (MSDI) in blue.
Drought Factor response shown in pink.
Note the more dramatic response than for the long term Dryness Index and the quicker recovery to a value limited by the long term Dryness Index.

42. Drought Factor Prediction
The DF increases rapidly as rain events become more distant.
The DF decreases markedly with rain.
If 5mm or more rain is expected, or if recent rain is of the order of 10mm in the last 2 days, 20mm in the last week or 50mm in the last 3 weeks, then the DF may vary significantly over the forecast period.
This is automated within the forecast process for Tas & SA & VIC. For others?
What tools are available to all regions?

43. Drought Factor Nowcasting
Note that the DF calculated with 9am data is valid until 9am the next day unless there is further rain.
Rain since 9am can reduce the DF.
In calculations, rain since 9am is treated as occurring 0 days ago.

44. Average Drought Factor Values
Gridded 30 year averages for Australia based on the 25km Australian Daily Rainfall Analysis grid and KBDI as calculated by Klara Finkele (2005).
Wettest northern and southern day shown.
22 Feb
14 Sept

45. Drought Factor Problems
DF algorithms developed in ACT/Tas??? And applied to other regions…
KBDI/SDI inputs may be inaccurate representations of long-term or heavy fuel drying.
Localized rain events can give large local variations in DF, making a spot location unrepresentative of a region.
Return to Index Slide

46. Curing
Most grass species have a life cycle in which the plants mature annually, dies and/or becomes dormant then loses moisture content. This is called the drying or curing process.
In Southern Australia curing occurs in early Summer. In Northern Australia curing occurs at the beginning of the dry season.
Photo copyright???

47. Curing
Measurements of curing, by cutting and drying grass and noting the change in weight, have led to guidelines for visual estimation of curing.
Algorithms have been developed for estimating curing from satellite data. This data has not replaced ground observations but is used in conjunction them.
0% cured: totally green
100% cured: totally dry
Curing can have significant local variation. This needs to be taken into account in selecting representative values.

48. Normalised Difference Vegetation Index
Using AVHRR on NOAA polar orbiting satellites.
NDVI=(Ch2-Ch1)/(Ch2+Ch1)
Ch1 is 0.58 to 0.68 (Visible channel)
Ch 2 is to 1.0  (Near infrared channel)
NDVI image: Normalised Difference Vegetation Index (NDVI) produced by the Bureau of Meteorology using measurements from the Advanced Very High Resolution Radiometer (AVHRR) on board the USA's NOAA polar orbiting meteorological satellites. NDVI = (Ch2-Ch1)/(Ch2+Ch1) where Channel 1 is visible ( microns) and Channel 2 is near infrared ( microns).

49. Automated Grassland Curing Index developed by CSIRO.
Inputs: AVHRR satellite data
LAPS moisture fields
NVAP moisture field (CSIRO climatology)
Available daily for SA and Vic from
From

50. Other charts Charts from http://www.longpaddock.qld.gov.au/
No information about algorithm
QLD image: From No information about algorithm.

51. Curing
Exercise: who is responsible for estimating curing in our region? How often is it updated.
Exercise: find current curing values for our state.

52. Curing
Typically curing estimates are updated once a week during the curing cycle.
Changes in curing between 75% and 100% are often critical in estimating fire danger. Fire Weather Forecasters may request frequent updates during this part of the curing cycle.

53. Greening
With rains at the end of the dry season, new growth can occur within 100% cured grass.
When new growth makes up a significant proportion of the total fuel it will impact on fire behaviour. An adjusted curing figure may be negotiated with the local fire agencies to allow for this situation.

54. Grass Fuel Load Return to Index Slide
The quantity of fuel may also be monitored.
It may be expressed in t/ha or in descriptive terms such as Sparse/Abundant.
Exercise: Is grass fuel quantity monitored in our region?
Return to Index Slide