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114

APPENDIX I

Estimating Pre-Record Bushfire Frequency

Early European Period

A very conservative estimate was made of the frequency of fire for the Kosciuszko

National Park for the early European period as follows:

• NPWS (2003) have recorded 157 definite lightning ignited fires within

Kosciuszko National Park for approximately the period 1960 to 2000, giving an

average of 4 lightning fires in a given year. These records are incomplete due to

the difficulty in determining an exact cause of ignition for many fires. Ignition

causes are known in this period for approximately 60% of fires, so assuming the

proportion of ignition causes is representative of the Park in general, it is probable

that the actual number of natural fires in KNP is on average actually 6 fires per

annum.

• Assuming no other ignition causes (a highly improbable assumption but necessary

due to the lack of data), and assuming that the quoted figure (Luke 1961) of

‘burning off’ in NSW being the cause of 8 fires for every natural fire was

representative of KNP during this earlier period; the average number of bushfires

in KNP during this period was probably about 50 fires per annum.

This can be given as:

F = FN . RH

Equation 1

Where F is the number of fires occurring in a year, FN is the number of fires that

occur in a year due to natural (non-human) ignitions, and RH is the ratio of human

ignitions to natural ignitions.

Aboriginal Management Period

As stated in the chapter examining Aboriginal fire management in the Alps, all

available dendrochronological evidence on the subject points toward a total (planned th th

and unplanned) fire frequency between 1/5 and 1/7 that of the average fire

frequency during the early European period. Using the estimates given above, this

places fire frequency during Aboriginal management as being in the range of 7 to 10

fires per annum. Considering that the recorded history of lightning strikes averages

about 6 fires per annum, this would suggest that intentional burning produced less

than 5 fires in KNP each year. Although the oral tradition for the area indicates that

great care was taken with fire, it is possible that with large numbers of groups

camping throughout the mountains, some of these fires were also unplanned events

resulting from escaped campfires, signals or other domestic fire uses.

The accuracy of this figure is reliant upon the accuracy of the early-European

frequency estimate, and the degree to which the recorded areas of fire scarring

represent the whole of the mountains.

115

APPENDIX II

The Historical Influence of Fuel Age on Fire

Extinction in the Australian Alps

Methods

ArcView GIS data (NPWS 2004) was interrogated to identify all unplanned fires in

the records for Kosciuszko National Park and its immediate surrounds that either

burnt through or into land that had already been burnt within the preceding 15 years.

Every contact with previously burnt land was then given a classification as to whether

the edge of the unplanned fire had stopped or been stopped within the burnt area, or if

it had burnt through. Where the fire appeared to have stopped within the burnt area, it

was classed as ‘effective’, and where it had burnt through it was classed as ‘not

effective’. The criteria used to decide this more precisely are given in Table 1, and an

example of each is given in figure 1.

The effectiveness of each fuel age was calculated according to:

E = NE / N

Equation 1

Where E is the effectiveness of that fuel age class, NE is the number of effective burnt

areas, and N is the total number of burnt areas encountered in that age class.

There are many other factors aside from fuel age that may have influenced the final

burnt area boundaries; for instance a fire may have been stopped within a prescription

burnt area not because the area provided any reduction in fire intensity, but because

additional resources were employed in that area for protection of assets. Alternatively

a fire may have burnt completely through an area of young fuels at very low intensity,

but had not been stopped in that area because it provided no strategic advantage.

Mapped fire boundaries are also limited in accuracy by the priorities in fire

suppression or recovery at the time of mapping, and some areas may have been

mapped as burnt by the unplanned fire when they were not. In order to account for

this, the study was carried out considering the correlation between % effectiveness

and the fuel age of:

a) all previously burnt areas within 15 years

b) only burnt areas >= 20 Ha

c) only burnt areas >= 100 Ha

d) only burnt areas >= 500 Ha

The study showing the strongest correlation between E and fuel age was used to form

a linear function describing the effect of fuel age on E.

116

TABLE 1. Criteria used to decide the effectiveness of burnt areas in fire suppression.

An area was considered effective if:

a) An unplanned fire has burnt into the previously burnt area and that part of the

front has stopped within its boundaries (figure 1)

b) An unplanned fire has burnt through a previously burnt area but has stopped

at a control line such as a watercourse or road bounding the other side of the

burnt area. This allows the possibility that the younger fuels reduced the

intensity of the fire so that the control line was able to hold it.

c) An unplanned fire has started within a previously burnt area, but not burnt a

final area greater than 1 Ha.

d) An unplanned fire has burnt up to the edge of a previously burnt area and

stopped at that point rather than entering. The exception to this is if contact

with the burnt area was prevented by a road, waterbody or some other control

line, or if evidence suggests that the previously burnt edge was the source of

ignition and the unplanned fire burnt away from it.

An area was considered not effective if:

a) An unplanned fire has burnt through it and come out the other side (figure 1)

b) An unplanned fire has burnt into it and stopped, but fire suppression records

show that back-burning was used as a containment strategy at that point rather

than relying on the potential reduced intensity provided by the younger fuels.

c) More of the unplanned burn has burnt within the block than outside of it

Tests for Significance

Fuel age classes were grouped to analyse statistically significant difference between

“old” and “young” fuels. Comparison between

a) 1-2 y.o. and 8-15 y.o. fuels

b) 1-2 y.o. and 3-7 y.o. fuels

c) 1-3 y.o. and 9-15 y.o. fuels

d) 1-3 y.o. and 4-8 y.o. fuels

e) 1-5 y.o. and 10-15 y.o. fuels, and

f) 1-8 y.o. and 10-15 y.o. fuels

Tests were carried out for burnt blocks >=100 Ha and blocks >= 500 Ha. Analysis

was performed using an unpaired Student’s t-test.

117

Figure 1. The area of 1 year old fuels t hat nearly spans t he 1964 Ravine Fire was ineffective in preventing its

south-east spread despite the fact that it was 5 km deep and 5648 Ha in size. Part of the south-eastern spread of the

fire was however halted in another area of both 1 year old and 3 year old fuels.

118

Results

Results for burnt areas >= 100 Ha and >= 500 Ha are given in tables 2 and 3 below,

and the effectiveness summary for all sized blocks is given in table 4 along with the

coefficient of correlation ρ. The results of Table 3 are given graphically in figure 2.

TABLE 2. Effectiveness of fuel age in fire suppression considering only burnt areas >=100 Ha

Fuel age class 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15

Number 'Effective' 9 8 7 3 7 0 8 3 4 6 2 2 8 3 3

Number 'Not

Effective'

10 10 6 4 5 5 8 2 9 5 6 6 7 6 7

Number Samples 19 18 13 7 12 5 16 5 13 11 8 8 15 9 10

% Effective 47% 44% 54% 43% 58% 0% 50% 60% 31% 55% 25% 25% 53% 33% 30%

TABLE 3. Effectiveness of fuel age in fire suppression considering only burnt areas >=500 Ha

Fuel age class 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15

Number 'Effective' 8 5 6 3 4 0 8 2 3 5 2 1 6 1 3

Number 'Not

Effective'

8 9 5 4 4 1 7 1 6 4 4 5 7 5 7

Number Samples 16 14 11 7 8 1 15 3 9 9 6 6 13 6 10

% Effective 50% 36% 55% 43% 50% 0% 53% 67% 33% 56% 33% 17% 46% 17% 30%

Impact of Time Since Fire on

the Extinction Likelihood of Unplanned Fire Events

E

xti

nc

tio

n l

ike

lih

oo

d

100%

90%

80%

70%

60%

50%

40%

30%

20%

10%

0%

36%

55%

43%

50%

53%

67%

33%

56%

33%

17%

46%

17%

30%

50% 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15

0% Fuel age

Figure 2. The impact of Burnt areas >=500 Ha in extinction likelihood

119

TABLE 4. Effectiveness of fuel age in fire suppression as affected by the size of the burnt area.

Min Fuel 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 ρ burnt Age

area Class

(Ha)

0 48% 40% 33% 22% 26% 25% 50% 36% 28% 60% 23% 22% 41% 25% 27% -0.22

20 45% 42% 37% 31% 45% 29% 44% 56% 41% 62% 30% 27% 50% 30% 30% -0.17

100 47% 44% 54% 43% 58% 0% 50% 60% 31% 55% 25% 25% 53% 33% 30% -0.26

500 50% 36% 55% 43% 50% 0% 53% 67% 33% 56% 33% 17% 46% 17% 30% -0.32

The results of the Student’s t-test for the different age categories taken from blocks >=

100Ha are given in Table 5, and for blocks >= 500 Ha, Table 6.

TABLE 5. Student’s t-test results for fuel age categories using blocks >=100Ha in area

Group 1 Group 2 Mean 1 Mean 2 Variance 1 Variance 2 Significance

1-2 yrs 8-15yrs 45.5% 39.0% 4.5% 209.4% N.S.

1-2 yrs 3-7 yrs 45.5% 41.0% 4.5% 556.0% N.S.

1-3 yrs 9-15 yrs 48.3% 36.0% 26.3% 160.3 90%

1-3 yrs 4-8 yrs 48.3% 42.2% 26.3% 602.2% N.S.

1-5 yrs 10-15 yrs 49.2% 36.8% 42.7% 186.6% 95%

1-8 yrs 10-15 yrs 44.5% 36.8% 361.7% 186.6% N.S.

TABLE 6. Student’s t-test results for fuel age categories using blocks >=500Ha in area

Group 1 Group 2 Mean 1 Mean 2 Variance 1 Variance 2 Significance

1-2 yrs 8-15yrs 43.0% 37.4% 98.0% 317.4% N.S.

1-2 yrs 3-7 yrs 43.0% 40.2% 98.0% 525.7% N.S.

1-3 yrs 9-15 yrs 47.0% 33.1% 97.0% 203.1% 90%

1-3 yrs 4-8 yrs 47.0% 42.6% 97.0% 643.3% N.S.

1-5 yrs 10-15 yrs 46.8% 33.1% 54.7% 243.8% 90%

1-8 yrs 10-15 yrs 44.2% 33.1% 400.5% 243.8% N.S.

Great variation was shown between individual age classes (not grouped), with 8 year

old fuels being effective most often, and 6 year old fuels having never been recorded

as effective. As it is unrealistic to expect that there would be such difference between

these two age classes, the class groupings provided a valuable comparison.

Similar trends were apparent in the studies of both the blocks 100Ha and greater and

the blocks 500Ha and greater. Examination of grouped fuel age classes showed that in

all groups blocks were effective less than half the time, that is, fire burnt through

those blocks more often than it stopped or was stopped within them. 1 and 2 year old

fuels showed no significant advantage over either 3 to 7 year old or 8 to 15 year old

fuels. Both 1 to 3 year old and 1 to 5 year old fuels showed slightly significantly

greater effect than older fuels (9 to 15 and 10 to 15 years old).

120

Linear Regression

Linear regression of the data for burnt areas >=500 Ha gave a likelihood of

suppression effectiveness within a burnt area based on fuel age as:

E = -0.01Tf + 0.49, where 1 <= Tf <= 15

Equation 2

Where E is the likelihood of fire extinction within the burnt area, and Tf is the age of

the fuels in years.

Discussion

The study demonstrates that fuel age has had an impact on fire extinction in the Alps,

albeit a small one. The strongest correlation was that between fire extinction and age

of burnt areas >=500 Ha, although using the value of ρ 2 this only accounted for 10.4%

of the suppression effectiveness. Results however demonstrate that there is a slight

advantage in fuels less than 5 years old, suggesting that there is nearly a 1 in 2 chance

of fire extinction in such fuels, compared to a 1 in 3 chance in fuels 9 to 15 years old.

Even in the youngest fuels, fire in KNP has been more likely to pass through the burnt

area than stop or be stopped within its bounds, and the variability suggests that 90%

of the effectiveness in suppression is due to factors unrelated to fuel age. It is probable

that this variability relates to suppression activities, ambient weather and long-term

climatic conditions, and the response of different plant communities to fire of

different frequencies. If this last factor is the case, some vegetation types will show

greater rates of fire extinction at low fuel ages than this study suggests, where others

will show significantly less.

References

NPWS (2004). Snowy Mountains Region fire history database. Unpublished

GIS database

121

APPENDIX III

Estimating Pre-Record Bushfire Extent

“Bushfire extent” here refers to the regularity of fire events of a particular size. The

indicative size used here is fires of 100,000Ha or larger. Such events are very rare,

and as explained in the main text rely on a confluence of events, the main limiting

factor being that of multiple, widespread ignitions. In the recent 40 – 50 years of

recorded fire history, such an event has only occurred once (2 simultaneous fires in

2003), and there are no other records of comparable natural ignition patterns.

Natural events such as bushfires and floods occur with a definable statistical

probability. Terminology such as a “one in one hundred year flood” refers to the size

of the flood that could be expected to occur on average every 100 years. It is of

course possible that such floods may occur in 2 consecutive years, but the likelihood

is very low (1 chance in 100). The likelihood can then be said to increase with every

year that goes by without such a flood. Such classifications are meaningful when

averaged over a long period of time, and are useful for characterising historical

periods.

The obvious difference between floods and fires is that fires have a residual effect

upon the landscape that affects the probability of future fires. The removal of fuels by

burning reduces the likelihood and potentially the spread of fires until those fuels

have re-accumulated. Similarly, an imposed fire regime that acts to increase fuels can

increase the likelihood and spread of fires for an area. This is discussed in detail for

the Alps in Appendix II. When considering fires, the incidence of a fire occurring

increases with the area being studied.

A statistical estimate of the frequency or return period per Ha (RPHa) of a 100,000 Ha

or larger fire can be made using the following data:

a) p - The current probability of such a fire

b) f- The frequency of bushfires for the period in question

c) E - The likelihood of fire to extinguish in fuels of a given age

d) Tf - The average age of the fuels for the period and area being examined

e) α - Adjustment factor to correct for the difference in average fuel age

compared to present day conditions

f) A – The area within which data was collected (Ha)

As given in Appendix II, E (probability of extinction) can be found from Tf according

to:

E = -0.01Tf + 0.49

Equation 1

Where 1 <= Tf <= 15. A value of 0.3 can be assumed for Tf vales greater than 15.

The return period per Ha RPHa can then be found using the relationship:

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A RPHa =

pf (1− Eα ) Equation 2

The return period RP for a study area of S Ha can then be found according to:

RP RP = Ha

S Equation 3

Estimates for the Early European and Aboriginal Management Periods.

Using the above process, the return period of a 100,000 Ha fire can be calculated for

the Alps as follows:

Analysis of NSW and ACT records for bushfire occurrence in the Alps since regular

records have been kept reveals that for the period 1959 to 2003, 1467 fires were

recorded within the total park area of 805,800 Ha. Of these, only 2 fires exceeded

100,000 Ha, both produced by the same lightning event in 2003. This gives a

probability of 2/1467 or

p = 0.0014. Also:

A = 805,800 and

S for the entire Alps = 1,611,660 Ha

For the early European period:

f was estimated in Appendix I to be 50

Tf was found from fire scar records to be 3.5

E (from Appendix II) for fuels 3.5 years old = 0.448

Giving RPHa = 18,672,160 years

And a value of RP for the Alps of 12 years.

For the Aboriginal Management period:

f was estimated in Appendix I to be 10

Tf was found from fire scar records to be 25

E (from Appendix II) = 0.3

Giving RPHa = 78,384,690 years

And a value of RP for the Alps of 49 years.

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APPENDIX IV

Maps

124