0 100 200 300 400 500 600 700 MURRAY-DARLING BASIN COMMISSION Risks to Shared Water Resources

Impact of the 2003 Alpine Bushfires on Streamflow Summary report

December 2007

Prepared by SKM and the University of Melbourne for the Victorian Department of Sustainability and Environment, and the Murray-Darling Basin Commission. Impact of the 2003 Alpine Bushfires on Streamflow – Summary Report

Published by Murray-Darling Basin Commission Postal Address GPO Box 409, Canberra ACT 2601 Office location Level 4, 51 Allara Street, Canberra City Australian Capital Territory

Telephone (02) 6279 0100 international + 61 2 6279 0100 Facsimile (02) 6248 8053 international + 61 2 6248 8053 E-Mail [email protected] Internet http://www.mdbc.gov.au

For further information contact the Murray-Darling Basin Commission office on (02) 6279 0100

This report may be cited as: Impact of the 2003 Alpine Bushfires on Streamflow – Summary report

MDBC Publication No. 23/08

ISBN 978 1 921257 63 6

This project was funded by the Department of Sustainability and Environment, the Murray-Darling Basin Commission and the Gippsland Lakes Taskforce.

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Impact of the 2003 Alpine Bushfires on Streamflow – Summary Report

1 Introduction Following the 2003 bushfires, which burnt over a million hectares of forest and grazing land (Figure 1), a major study was commissioned to assess the likely impact of the fires on water quality and quantity. This document provides a summary of the background to, and results from, the Program.

The study was managed by the Cooperative Research Centre for Catchment Hydrology and involved Sinclair Knight Merz; CSIRO Land and Water; and the Department of Civil and Environmental Engineering and School of Forest and Ecosystem Science (formerly the Forest Science Centre) of the University of Melbourne. The work was commissioned by the Victorian Department of Sustainability and Environment and the Murray Darling Basin Commission with additional financial support from the North Eastern, West and East Gippsland Catchment Management Authorities and Gippsland Lakes Task Force.

Motivation for the work came from two obvious concerns. Firstly, fire is known to have a significant impact on water yield when a forest is killed. The initial loss of vegetation results in increased runoff (for 5-10 years), while subsequent regeneration consumes significantly more water per unit area as the new growth flourishes, thereby reducing runoff over an extended period. The maximum impact is for around 15-25 years with some impact continuing for up to 100 years. Eventually, as the forest approaches the age of the pre-fire forest, runoff returns to pre-fire levels. The impact on streamflow is most severe for Mountain Ash forests, but occurs in all native species. As will be shown, the impacts on water yield of the 2003 fires are considerable and will have to be accounted for in future water resource planning.

Secondly, a significant deterioration in water quality, and increases in nutrient loads and greatly increased sediment loads are expected following a fire. Recovery occurs as surface cover regenerates, but the timescales for this recovery are highly variable, being dependent on the severity of burn, terrain and soils, forest type, and the subsequent climatic conditions. These time scales will range from a couple of years to a decade or more. In addition, coarser sediment may be temporarily stored and potentially remobilised by large events in the future. As will be shown, the 2003 fires resulted in load increases above pre-fire conditions of up to several hundred times. Recovery is generally occurring but loads are still between two and ten times pre-fire conditions in most catchments, with some being higher. Impact of the 2003 Alpine Bushfires on Streamflow – Summary Report

Figure 1. Area affected by the 2003 bushfires, along with catchment boundaries used in water yield analyses.

The Water Yield Assessment component of the Bushfires Recovery Program was designed to quantify the impacts on water yield and water quality for the major catchments flowing to the Murray River including Dartmouth dam (on the Mitta Mitta River), the Gippsland Lakes (where the Tambo and Dargo/Mitchell Rivers were affected) and the Snowy River.

Seven tasks were undertaken in the Program and are linked as shown in Figure 2. The fundamental tasks in relation to water yield are Tasks 1 and 4. These deal with the overall impacts on annual and seasonal water yield expected for each of the 12 major catchments (identified in Figure 1). An extensive network of water quality monitoring sites was set up immediately following the fires to assess impacts and any possible recovery. Monitoring ceased in 2005. Analysis of these data was undertaken in Task 5, while Task 6 used the results along with catchment modelling to extrapolate the likely water quality impacts to the relevant catchment scales. Task 2 was to enable the Macaque model, a detailed hydrological model designed to assess the impacts on yield of land-use change over relatively small catchments, to be generally available to agencies, with appropriate documentation and support. Task 3 applied Macaque to smaller subcatchments to assess in more detail, likely yield responses. Macaque was also used to undertake numerical experiments, i.e. modelling studies, in Task 4 to test what refinements could be made to the broad- scale assessment, in particular to determine seasonal effects and any differences resulting from different catchment characteristics. Task 7 was a detailed analysis of the East Kiewa catchment.

Separate, detailed reports are available for each of the tasks (see figure 2 and bibliography). This document provides an overview of the key outcomes, focusing on implications for management.

Impact of the 2003 Alpine Bushfires on Streamflow – Summary Report

Figure 2. The seven major tasks in the Bushfires Recovery Program indicating the lead group and assisting groups (in parentheses). (SKM is Sinclair Knight Merz. FSC is the Forest Science Centre, now the School of Forest and Ecosystem Science at the University of Melbourne. CRCCH refers to the combination of CSIRO Land and Water and the Department of Civil and Environmental Engineering, University of Melbourne.)

2 Impacts on water yield

2.1 Broadscale Impacts Water yield impacts of the 2003 fires are significant with reductions of up to 50% in annual flow over the average conditions in the twenty years prior to 2003. Table 1 shows the expected maximum impact for the 12 catchments and the summed impacts in the Murray River and Gippsland Lakes. In general these maximum impacts would be expected to occur between 15-25 years after the fire. Results are shown in ML/year, mm of runoff per year and as a percentage of Mean Annual Flow.

Impact of the 2003 Alpine Bushfires on Streamflow – Summary Report

The results presented in this summary report are all relative to the average conditions in the twenty years prior to 2003. An alternative way of interpreting the results is to compare the conditions that would have been expected into the future had no fire occurred. This latter interpretation is included in the detailed report on Task 1 (MDBC, 2007a). In general, the relative impacts of the fires appear larger when compared to the “no-fire future”. This is because the age profile of the 2003 pre-fire vegetation would have resulted in increased runoff over time compared to the pre-fire average conditions.

Catchment Maximum reduction in streamflow

ML/year mm/year % MAF Northern Catchments Buffalo -26,000 -22 -6 Corryong -26,000 -53 -16 Dartmouth -320,000 -89 -20 Kiewa -20,000 -49 -3 Mitta Mitta (d/s of Dartmouth) -29,000 -44 -1 Ovens -65,000 -52 -12 Upper Murray -170,000 -71 -26 Other Northern -36,000 -45 River Murray (d/s of -692,000 -10 confluence with Ovens) Southern Catchments Dargo -51,000 -96 -29 Tambo -31,000 -35 -27 Wongungurra -58,000 -80 -20 Other Southern -15,000 -59 Gippsland Lakes -155,000 -6 Buchan -74,000 -87 -53 Snowy -230,000 -24 -31

Table 1. Estimated maximum impact on annual water yield for each catchment outlet (boundaries are shown in Figure 1) with respect to the average annual streamflow in the twenty years prior to the 2003 fires. Maximum yield reductions expected approximately 20 years after the fire. Results are in ML/year, mm runoff per year, and percentage of mean annual flow.

Figures 3 and 4 illustrate, for the Murray River (downstream of the confluence with the Ovens River) and the Gippsland Lakes respectively, the expected impacts and flow change over time, including the initial increase, maximum decline, and period for recovery. In general the initially higher flows have returned to pre-fire conditions within ten years and decline to a maximum reduction at around 20 years after the fire, fully recovering after approximately 100 years1.

Appendix A includes the results for the individual catchments. In appendix A, the results are also shown as a percentage of mean annual flow (MAF). Impacts range from approximately 1% MAF for the Mitta Mitta downstream of Dartmouth Dam to over 50% MAF for the Buchan River. Impacts on the Upper Murray are around 26% MAF and 20% for the flows into Dartmouth dam. Maximum

1 See later section on uncertainty for explanation of the upper and lower bounds on Figures 3 and 4 and Appendix A. Impact of the 2003 Alpine Bushfires on Streamflow – Summary Report

reductions in flows to the Gippsland Lakes are approximately 5% MAF and 10% for the Murray River downstream of the confluence with the Ovens River.

2000000

1000000

0

Change in Streamflow Streamflow in Change -1000000 No-fire response relative to 2003(pre-fire) (ML) Lower Bound Best Estimate -2000000 Upper Bound 2000 2020 2040 2060 2080 2100 2120 2140 2160 2180 2200 Year

Figure 3. Expected differences in streamflow between fire and pre-fire average conditions for the Murray River downstream of the confluence with the Ovens River. The “no-fire” response is a result of natural aging of the forest (and is what may have occurred had the fires not happened).

400000

200000

0

Change in Streamflow -200000 No-fire response relative to 2003 (pre-fire) (ML) Lower Bound Best Estimate -400000 Upper Bound 2000 2020 2040 2060 2080 2100 2120 2140 2160 2180 2200 Year

Figure 4. Expected differences in streamflow between fire and pre-fire average conditions for the Gippsland Lakes catchments. The “no-fire” response is a result of natural aging of the forest (and is what may have occurred had the fires not happened).

Impact of the 2003 Alpine Bushfires on Streamflow – Summary Report

2.2 Seasonal Impacts The results in Table 1 are based on the annual differences in flow. Task 4 of the Program (MDBC, 2007b) explored in more detail the possible effects of seasonality and whether physiographic differences in catchments would significantly alter seasonal impacts. The results showed that the annual impacts from Table 1 are not evenly spread throughout the year.

Table 2 shows the expected reductions in seasonal flows for the major catchments as a percentage of seasonal flows. In general, summer flows are most affected (i.e. biggest percentage impact) while winter flows are least affected (proportionally). However, volumetric reductions in runoff during winter and spring are largest since streamflows are high during these periods. The modelling showed that these percentages are not significantly affected by forest type or catchment characteristics so the results can be assumed to be generally applicable to the total area burnt in the 2003 fires.

Change in streamflow (%) Catchment Summer Autumn Winter Spring

Buffalo -27% -8% -2% -7% Corryong -24% -14% -9% -12% Dartmouth -33% -24% -16% -18% Kiewa -7% -3% -3% -3% Mitta Mitta (d/s of Dartmouth) -20% -14% -7% -10% Ovens -38% -16% -6% -12% Upper Murray -48% -23% -18% -26%

Dargo -64% -29% -21% -26% Tambo -43% -26% -20% -28% Wongungarra -52% -22% -12% -19% Buchan -86% -54% -41% -51% Snowy -36% -25% -24% -36% Table 2. Average seasonal distribution of impacts on streamflow (expressed as a percentage of average seasonal flow compared to the pre-fire (2003) scenario) for the study catchments.

2.3 Detailed Macaque modelling (Mitta Mitta River) The detailed modelling results for the Mitta Mitta River above Hinnomunjie and the Tambo above Bindi broadly support the conclusions of the broad-scale study, with maximum flow decreases of similar magnitude. Seasonal impacts differed somewhat to those from Task 4 (presented in sections 2.1 and 2.2 above), with the largest proportional decreases predicted for Winter and Autumn flows in the Mitta Mitta, and Spring and Winter in the Tambo. This work also demonstrated some of the issues related to modelling responses of spatially complex mosaics of burn severity, species composition and, importantly, rainfall distribution.

3 Impacts on Water Quality

3.1 Analysis of site data Despite the considerable resources provided for water quality monitoring from 2003 to 2005, confidence in the results of load computations from Task 5 vary from catchment to catchment. This is because of both the inherent difficulties in obtaining representative samples, in particular sampling storm events, as well as actual differences between the catchments due to severity of burn and physiographical differences. Despite these difficulties (which are fully explored in MDBC, Impact of the 2003 Alpine Bushfires on Streamflow – Summary Report

2007b) the impacts on water quality were, and continue to be, very significant2. The points below summarise the best estimates of load increases in loads of Total Suspended Solids (TSS), Total Phosphorous (TP) and Total Nitrogen (TN) for each of the monitoring locations, along with a statement of confidence based on the representativeness of sampling:

ƒ Dargo River at Lower Dargo Road. Confidence in results: high. There was approximately a 20 fold increase in TSS due largely to flows from major rainfall events. Base-flow concentrations approximately doubled. Increases in TP were approximately 10 fold with TN slightly less. Base-flow concentrations are showing signs of recovery but storm event flow concentrations remain high. ƒ Kiewa River at Bandiana. Confidence in TN and TP data: high, with less confidence in TSS data. This site is downstream of several impoundments and this is reflected in the post fire water quality data. No significant increases in TN or TP loads were detected and changes in TSS are unlikely. ƒ Tambo River at Bindi. Confidence in results: high although sampling ceased 6 months after the fire. Initial increases in loads were very high – 1500 fold for TSS, 400 fold for TP and 90 fold for TN. No data on recovery was collected, however see comments on Tambo at Swifts creek. ƒ Tambo River at Swifts Creek. Confidence in results: moderate. Initial increases in loads were high, dominated by storm flows (200 fold for TSS, 30-40 fold for TP and 25-35 fold for TN). Signs of recovery are evident in the 2004-2005 data with the most recent information showing increases in TSS of 25 fold, 6 fold for TP and 3 fold for TN and trending downwards. ƒ Mitta Mitta River at Hinomunjie. Confidence in results: moderate. There were increases in TSS load of 150 to 350 fold depending on computational method, with results dominated by extreme concentrations in large events. TP load increased by approximately 40 fold while TN load increased by 20 fold. Recovery is evident in the 2004 data although it appears to have slowed in 2005. Recent data indicate approximately 30 fold increases in TSS load and 4-6 fold increases in TP and TN. These are almost ten times less than 2003, but are still high. ƒ Ovens river at Bright. Confidence in results: moderate. Increases in 2003 loads were 24 fold for TSS and 9 fold for TP and TN. High flow loads dominated the results. There is strong evidence of recovery with 2004/5 loads approximately double pre-fire values. ƒ Snowy River at Mc Killops Bridge. Confidence in results: low, due to poor coverage of post-fire events. The only result of confidence is that baseflow concentrations increased 7 fold in 2003. Sparse data coverage precludes firm conclusions but generally data indicates limited recovery from high initial post-fire loads. Anecdotal evidence indicates that water quality during high flow events is still poor. ƒ Wonnangatta River at Waterford. No confidence in results – only two minor storms were sampled following the fires and no samples were taken in subsequent years.

3.2 Water quality modelling results The results from data analysis were for specific gauging stations, relatively close to the burnt areas. In order to extrapolate these results to the major catchment outlets, modelling was required. Table 3 shows the expected impacts on loads of TSS, TN and TP for each of the major catchments in Figure 5. Table 3 shows the loads that may have been expected based on the year following the fires and three years following the fires to indicate the extent of recovery.

2 Note that the numbers represent many fold increases (eg. 10 fold, or 10 times, increases mean 1000% increases.) Impact of the 2003 Alpine Bushfires on Streamflow – Summary Report

These impacts are proportionally smaller than those based directly on gauging station data because of the inclusion of unburnt area in the larger catchments. The modelling did not represent changes in loads caused by in-stream processes (such as plant uptake or denitrification) or deposition of suspended material, so the impacts in Table 3 are at the upper end of expectations (i.e. “worst case”). The reductions in streamflow expected (Tables 1 and 2) will have a very minor mitigating effect on these catchment load estimates.

Figure 5. Catchments used for Water Quality modelling.

Impact of the 2003 Alpine Bushfires on Streamflow – Summary Report

Catchment TSS load TP load TN load TSS load 3 TP load 3 TN load 3 yr immediately immediately immediately yr post fire yr post post fire post fire post fire post fire fire Note that the numbers in this table are FACTOR increases over the mean conditions pre-fire. eg. 2 indicates that loads are twice (200%) more than pre-fire. Ovens River @ 24 9 9 2 1 2 Bright Ovens River @ 11 4 5 2 1 2 Buffalo Ovens River @ 17 6 5 2 1 2 Rocky Point Ovens River @ 16 2 2 2 1 1 Peechelba Kiewa River @ 1 1 1 - 1 1 Bandiana Mitta River @ Hinnommunjie 170 40 20 30 7 4

Mitta River @ 175 40 20 30 7 5 Dartmouth Dam* Mitta River @ 70 10 5 15 3 2 Tallandoon Snowy River@ 110 100 30 - - - McKillops Br.** Snowy River 140 160 30 - - - @Jarrahmond** Gippsland Lakes 8.5 1.8 1.6 4 1 1 Table 3. Estimated maximum impacts on catchment loads of TSS, TP and TN expressed as multiplicative factors over long term pre-fire loads. *the storages will significantly mitigate these high load increases. For example limited data from below Dartmouth indicate load increases of only 2.1 for TSS, 1.2 for TP and 1.3 for TN. **confidence in these results is very low. All that can be reliably said is that loads have substantially increased. The data on recovery is very limited and while trending downwards, anecdotal evidence indicates that event loads are still high.

There is a large degree of uncertainty in these model results, stemming from both the underlying data and the model assumptions. Nevertheless the large increases in loads and variable recovery in water quality from catchment to catchment based on the measurements, translate through to the catchment-wide impacts in Table 3. These impacts are associated with suspended and dissolved material in the streamflow. There is also evidence of coarse bedload material being deposited in streams (Harman and Stewardson, 2005) some of which will slowly move through the stream networks. These will need to be identified and monitored on a case-by-case basis (see management implications below).

3.3 Outcomes from the East Kiewa study The East Kiewa study was a detailed investigation into the impacts of the bushfires on a small, well instrumented catchment to provide some assessment of how realistic the broad scale results were and to provide more insight into the reasons for observed responses. In general the results to date support the broad scale work. TSS loads increased by 8-9 fold immediately post fire and were still 2-4 fold the pre-fire conditions in 2004 (Lane et al., 2006). The water quality data were based on combining continuous turbidity measurement with auto-samplers. This higher level of instrumentation and of management produced more reliable results than the broadscale results with estimated errors <10%. An important outcome of the project was clarification of the very high level of attentiveness required to get good data from auto-samplers and the need for continual analysis of data as it is collected to rectify problems as soon as they occur.

The initial increase in runoff expected after the fires was observed to be approximately 70% higher than what would have been expected without a fire and is consistent with the broad scale results. Impact of the 2003 Alpine Bushfires on Streamflow – Summary Report

There were no major shifts in the processes that produce the runoff. Of course there is no sign yet of yield reductions (this would not be expected until approximately 15-25 years post-fire).

Important insights into runoff and sediment generation processes from burnt and unburnt hillslopes were also gained from this study (Sheridan et al., 2007), providing good data for future modelling of generation and delivery of pollutants to streams in these landscapes. Nutrient (N and P) loads were also increased by similar or slightly greater factors at the TSS, and N exhibited a slower recovery signal than sediment.

4 Levels of uncertainty and matters for interpretation The full reports on each task include detailed discussions of uncertainty in the results. In the case of impacts on water yield, uncertainty bounds were computed and are shown in Figures 3 and 4 and Appendix A. The science that underpins water use-forest age relationships is well established so most of the uncertainty stems from the more limited knowledge on the relationship between severity of burn, species and level of recovery. Detailed satellite and aerial mapping were conducted immediately after the fire and some was repeated two years later to determine levels of recovery – classified as “regrowth”, “recovery” or “partial recovery”. The expected impacts shown in Figures 3, 4, Appendix A and Tables 1 and 2 are the best estimate of response based on expert judgement of the available data and assuming average climate into the future. The upper and lower uncertainty bounds are extremes based on assuming total regrowth or total recovery (i.e. vegetation is not killed and recovers).

For management purposes, the expected value should be used and it should be recognised that wetter or drier than average years will influence the absolute magnitude of the impacts, although proportional impacts will be approximately valid for all but extreme wet or dry years.

Uncertainty in the impacts on water quality stems from the representativeness of the sampling; variability in the measured concentrations; and the models used to compute loads from concentration and flow data and extrapolate them across catchments. MDBC 2007d describes in detail the various sources of uncertainty in relation to the data analysis and summarise the overall confidence in results as noted above. MDBC 2007c discuss the uncertainty associated with extrapolation to larger catchments. Both note high levels of uncertainty, particularly where data is limited, nevertheless it is clear that the fires resulted in greatly elevated loads of TSS, TP and TN and that while recovery has generally occurred, this has varied considerably across catchments. Most catchments are clearly recovering. However, the Dargo River has shown little recovery so far and the data on the Snowy River is too limited to confirm significant recovery. Nevertheless, in both cases recovery would be expected eventually as ground cover returns.

Impact of the 2003 Alpine Bushfires on Streamflow – Summary Report

5 Bibliography

Argent, R. M., Grayson, R. B., Fowler, K., 2005a. E2 User Guide. CRC for Catchment Hydrology. 46 pp.

Argent, R. M., Grayson, R. B., Podger, G. D., Rahman, J. M., Seaton, S. P., Perraud, J.-M., 2005b. E2 - A flexible framework for catchment modelling, MODSIM 05 International Congress on Modelling and Simulation. Melbourne 12-15 December. Modelling and Simulation Society of Australia.

Department of Sustainability and Environment, 2007. Impact of the 2003 Alpine Bushfires on Streamflow - Modelling the impacts of the 2003 bushfires on water quality in the Gippsland Lakes catchments. Feikema P.M, Sheridan G.J, Argent R.M, Lane P.N.J and Grayson R.B, School of Forest and Ecosystem Science, University of Melbourne.

Freebairn, A., Peel, M and P. Feikema, 2006. Macaque user manual. Catchment Modelling Toolkit www.toolkit.net.au/macaque.

Grayson, R.B., and R. M. Argent, 2002. A tool for investigating broad-scale nutrient and sediment sources from the catchments of the Gippsland Lakes, CEAH report 1/ 02, 45p.

Harmon C and Stewardson M (2004) Post-fire coarse sediment yield in the upper Tambo River Basin: results and analysis pf a preliminary field survey and literature review. Unpublished report for East Gippsland Catchment Management Authority.

Kuczera, G. A. 1985., Prediction of water yield reductions following a bushfire in Ash- Mixed Species Eucalypt Forest. Melbourne Metropolitan Board of Works, Water Supply Catchment Hydrology Research, Rep. No. MMBW-W-0014

Lane PNJ, Sheridan GJ, Noske PJ 2006. Changes in sediment loads and discharge from small mountain catchments following wildfire in south eastern Australia. Journal of Hydrology, 331: 495- 510.

Langford, K. J., 1976. Change in yield of water following a bushfire in a forest of Eucalyptus reganas. Journal of Hydrology, 29: 87-114.

Munday, S., Nathan, R., Daamen, C. and Cornish, P., 2001. Development and Application of an Operations Model to Assess the Impact of Plantation Forestry on Water Yields. ModSim 2001, International Congress on Modelling and Simulation. ANU, Australia.

Murray-Darling Basin Commission, 2007a. Impact of the 2003 Alpine Bushfires on Streamflow - Broadscale water yield assessment. Prepared by Sinclair Knight Merz for the Victorian Department of Sustainability and Environment and the Murray-Darling Basin Commission.

Murray-Darling Basin Commission, 2007b. Impact of the 2003 Alpine Bushfires on Streamflow - Seasonal streamflow response. Prepared by Sinclair Knight Merz for the Victorian Department of Sustainability and Environment and the Murray-Darling Basin Commission.

Murray-Darling Basin Commission, 2007c. Impact of the 2003 Alpine Bushfires on Streamflow - Modelling the impacts of the 2003 bushfires on water quality in catchments in Victoria and New South Wales. Feikema P.M, Sheridan G.J, Argent R.M, Lane P.N.J and Grayson R.B., School of Forest and Ecosystem Science, University of Melbourne.

Murray-Darling Basin Commission, 2007d. Impact of the 2003 Alpine Bushfires on Streamflow - Estimated changes in stream exports of sediment, phosphorus and nitrogen following the 2003 Impact of the 2003 Alpine Bushfires on Streamflow – Summary Report

bushfires in Eastern Victoria. Sheridan G.J, Lane P.N.J, Grayson R.B, Noske P.J, Feikema P.M and Sherwin C., University of Melbourne.

Peel, M., Watson, F., Vertessy, R., Lau, A., Watson, I., Sutton. M. & Rhodes, B., 2000., Predicting the water yield impacts of forest disturbance in the Maroondah and Thomson catchments using the Macaque model. CRC for Catchment Hydrology Technical Report 00/14

Sheridan, G.J., Lane, P.N.J., and Noske, P.J., 2007. Quantification of hillslope runoff and erosion processes before and after wildfire in a wet Eucalyptus forest. Journal of Hydrology, 343: 12-28.

Watson, F.G.R., R.A. Vertessy and R.B. Grayson 1999. Large scale modelling of forest hydrological processes and their long term effect on water yield. Hydrological Processes 13:689- 700.

Zhang, L., Dawes, W. R & Walker, G. R., 1999, Predicting the effect of vegetation changes on catchment average water balance. Cooperative Research Centre for Catchment Hydrology, Technical Report, No. 99/12, Monash University, Victoria, Australia. 35pp

Impact of the 2003 Alpine Bushfires on Streamflow – Summary Report

Appendix A – Difference between streamflow estimates for fire and pre-fire scenarios for each major catchment.

Buffalo

80000 No-fire response Lower Bound 15 Best Estimate 40000 Upper Bound 10

5 nnual Flow (%) Flow nnual A 0 0

-5 Change in Streamflow tion of Mean of Mean tion

-40000 r -10 relative to 2003 (pre-fire) (ML) opo r

-15 P -80000 2000 2020 2040 2060 2080 2100 2120 2140 2160 2180 2200 Year

Corryong

60000 No-fire response Lower Bound 25 Best Estimate 40000 Upper Bound 20 15

20000 10 nnual Flow(%) A 5

0 0

-5 Change in Streamflow tion of Mean r -20000 -10 relative to 2003 (pre-fire) (ML) opo r

-15 P -40000 2000 2020 2040 2060 2080 2100 2120 2140 2160 2180 2200 Year

Dartmouth

800000 50 No-fire response Lower Bound 40 Best Estimate Upper Bound 30 400000 20 10 0 0 -10 -20 Change in Streamflow in Streamflow Change tion of Mean Annual Flow (%) Flow Annual Mean of tion

-400000 r -30 relative to 2003 (pre-fire) (ML) opo r

-40 P

-800000 -50 2000 2020 2040 2060 2080 2100 2120 2140 2160 2180 2200 Year Impact of the 2003 Alpine Bushfires on Streamflow – Summary Report

Kiewa

80000 No-fire response Lower Bound Best Estimate 20 Upper Bound 40000 10 nnual Flow (%) A 0

0 -10 Change in Streamflow tion of Mean r relative to 2003 (pre-fire) (ML) (pre-fire) to 2003 relative

-20 opo r P

-40000 2000 2020 2040 2060 2080 2100 2120 2140 2160 2180 2200 Year

Mitta MItta

80000 No-fire response Lower Bound Best Estimate 20 Upper Bound 40000 10 nnual Flow (%) Flow nnual A 0 0

-10 Change in Streamflow tion of Mean

-40000 r relative to 2003 (pre-fire) (ML) (pre-fire) 2003 to relative

-20 opo r P

-80000 2000 2020 2040 2060 2080 2100 2120 2140 2160 2180 2200 Year

Ovens

200000 No-fire response Lower Bound 30 Best Estimate Upper Bound 20 100000

10

0 0

-10 Change in Streamflow tion of Mean Annual Flow (%) Flow of Mean Annual tion

-100000 r -20 relative to 2003 (pre-fire) (ML) (pre-fire) to 2003 relative opo r

-30 P -200000 2000 2020 2040 2060 2080 2100 2120 2140 2160 2180 2200 Year

Impact of the 2003 Alpine Bushfires on Streamflow – Summary Report

Upper Murray

400000 No-fire response Lower Bound 60 Best Estimate Upper Bound 40 200000

20

0 0

-20 Change in Streamflow in Streamflow Change tion of Mean Annual Flow (%) Flow Annual Mean of tion

-200000 r -40 relative to 2003 (pre-fire) (ML) opo r -60 P -400000 2000 2020 2040 2060 2080 2100 2120 2140 2160 2180 2200 Year

Buchan 150000 100

80 100000 60

50000 40 20

0 0

-20 Change in Streamflow tion of Mean Annual Flow (%) Flow of Annual Mean tion No-fire response r -50000 relative to 2003 (pre-fire) (ML) Lower Bound -40 opo r

Best Estimate P -60 Upper Bound -100000 2000 2020 2040 2060 2080 2100 2120 2140 2160 2180 2200 Year

Dargo 120000 No-fire response 60 Lower Bound 80000 Best Estimate 40 Upper Bound 40000 20

0 0

-40000 -20 Change in Streamflow Streamflow Change in tion of Mean Annual Flow (%) Flow of Mean Annual tion -40 r relative to 2003 (pre-fire) (ML) (pre-fire) to 2003 relative -80000 opo r P -60 -120000 2000 2020 2040 2060 2080 2100 2120 2140 2160 2180 2200 Year

Impact of the 2003 Alpine Bushfires on Streamflow – Summary Report

Snowy 400000 No-fire response 50 Lower Bound 40 Best Estimate Upper Bound 30 200000 20 10 0 0 -10 -20 Change in Streamflow Streamflow Change in tion of Mean Annual Flow (%) Flow of Annual Mean tion

-200000 r -30 relative to 2003 (pre-fire) (ML) (pre-fire) to 2003 relative opo -40 r P -50 -400000 2000 2020 2040 2060 2080 2100 2120 2140 2160 2180 2200 Year

Tambo 80000 No-fire response Lower Bound 60 Best Estimate Upper Bound 40 40000

20 nnual Flow (%) Flow nnual A 0 0

-20 Change in Streamflow tion of Mean

-40000 r -40 relativeto 2003 (pre-fire) (ML) opo r -60 P -80000 2000 2020 2040 2060 2080 2100 2120 2140 2160 2180 2200 Year Wongungurra 150000 No-fire response 50 Lower Bound 40 Best Estimate 100000 Upper Bound 30

20 50000 10

0 0

-10 Change in Streamflow Streamflow Change in tion of Mean Annual Flow (%) Flow of Mean Annual tion -50000 r relative to 2003 (pre-fire) (ML)

-20 opo r P -30 -100000 2000 2020 2040 2060 2080 2100 2120 2140 2160 2180 2200 Year

Impact of the 2003 Alpine Bushfires on Streamflow – Summary Report

Appendix B Notes on technical aspects of the tasks.

The following is a summary of the methods used in each of the tasks. Interested readers are referred to the full reports for further details.

Task 1 utilised the BISY (Bushfires Impact on Streamflow Yield) model. This was developed by Sinclair Knight Merz and is based on the observations of streamflow changes resulting from fires noted by Kuczera (1985) and generalised by Watson et al. (1999) as well as the work of Zhang et al (1999) on water yield changes due to land use change. BISY is a spatial model and in this application a pixel size of 1km2 was used. The model required information on severity of burn and subsequent recovery. This was derived from aerial mapping and satellite imagery taken immediately after the fires and in 2005. This was used to establish the levels of recovery for different severity of burn in each catchment and for each forest type (Mountain Ash, Alpine Ash, Snowgum and Mixed Eucalypt). Long term simulations were based on use of average climatic conditions.

Tasks 2 and 3 used the Macaque model of Watson et al. (1999). Macaque is a detailed, physically based eco-hydrological model that represents the growth of vegetation and its effects on runoff. Macaque enables a high level of spatial and temporal detail to be represented, requiring a large amount of input data. Macaque was converted to TIME (The Invisible Modelling Environment) and developed as a product for the Catchment Modelling Toolkit and includes user manuals, software to assist in data preparation and support information (Freebairn et al., 2006). Macaque was applied to the Tambo and Mitta Mitta catchments to determine whether the broad scale results from BISY were sound and could assist in providing information to Task 4.

Macaque was used in Task 4 to explore likely avenues for improvement of the broad scale assessment via BISY. The detailed response of Macaque summed to equivalent annualised results from BISY, but it became clear that the within-year impacts were quite variable. It was concluded that the most important improvement to be made to the broad scale methods was to represent the seasonality of likely impacts. Variation in catchment physiographic characteristics not represented in BISY were shown to have little effect on the overall yield impacts.

Task 5 was based on data from auto samplers installed immediately after the 2003 fires that operated until late 2005. The analysis included a range of methods for the computation of loads from concentration and flow data – interpolation (where temporal resolution made this possible), regression (between discharge and concentration), averaging (using arithmetic and geometric means) and Monte Carlo simulation based on distributional properties of the data. A comprehensive assessment of uncertainty was also undertaken.

Task 6 used the results from Task 5 along with two catchment models for extrapolation of results to larger catchments. The model for the Gippsland Lakes catchments was from Grayson and Argent (2002) and the Catchment Modelling Toolkit’s E2 model (Argent et al., 2005) was used for the other catchments. The modelling utilised Event Mean Concentration and Dry Weather Concentration estimates calibrated from a combination of the literature and Task 5. Modelling used a monthly time step over a 20 year period to establish long-term mean estimates. The reports by DSE 2007 and MDBC 2007c discuss the levels of confidence in the results and sources of uncertainty. Clearly there is considerable uncertainty in the estimated impacts on loads of TSS, TN and TP due to both data and modelling limitations. Nevertheless, the estimates are sufficiently accurate to enable management implications to be established.