On The Mechanisms Resulting Post-Fire Flash Floods: A Case
Study From Alpine Shire, Victoria.
Lee Tryhorn1, Jillian Gallucci1, Amanda Lynch1, and Kevin Parkyn2
1 School
of Geography and Environmental Science,
Monash University
Clayton, Victoria, 3800
AUSTRALIA
2
Australian Bureau of Meteorology
Email: Lee.Tryhorn@arts.monash.edu.au
Abstract
The start of 2003 saw large areas of southeastern Australia ravaged by fire. The fires burned over a
period of nearly 60 days and were immediately followed by storms and localised flash flooding that
resulted in one fatality. An investigation of the meteorological and hydrological conditions resulting in
this extreme event has been conducted. Flash flooding occurred because of highly localised
thunderstorms and was enhanced by the recently burned landscape. The synoptic conditions
surrounding the event suggest that the major drivers of the extreme rainfall event were the high levels
of precipitable water in the atmosphere, high CAPE values, and enhanced atmospheric instability from
increased surface heating due to the reduction in surface albedo and soil moisture of the recently
burned fire surface. Hydrological modelling of the flash flooding event indicated that fire-induced soil
hydrophobicity was likely to have further intensified the flood event. With an increase in fires expected
in the Alpine Shire associated with anthropogenic climate change, the relationship between fire and
flood, even for a rare event, has implications for emergency managers and Alpine Shire residents.
1. INTRODUCTION
Fire-prone mountainous regions, such as the Victorian Alps of southeastern Australia, are especially
vulnerable to post-fire flash floods. Flash floods may occur immediately following a fire or be delayed
by several weeks, and may be causally linked to the fire event through the hydrogeological response
of catchments or fire-associated meteorological mechanisms (Potter, 2005; Tryhorn et al 2007).
February 2003 saw a post-fire flash flood event occur in the Alpine Shire of Victoria (Figure 1). This
flash flood followed Victoria’s largest bushfire since 1939. No lives were lost as a direct result of the
2003 fires, but 75,000 hectares of farmland, 241 buildings and 110,000 head of stock were destroyed.
Significantly, localised flash flooding immediately following the fires in the Dingo Creek area of Alpine
Shire caused a fire fighter to lose her life when her utility truck was swept away as she attempted a
bridge crossing.
On The Mechanisms Resulting Post-Fire Flash Floods
Tryhorn
Figure 1. The three-nested model domains used to produce the MM5 simulations Domain 3
(bold dashed). The extent of the 2003 bushfires in show in grey and the Alpine Shire boundary
is shown as a solid line.
This paper describes an analysis of the mechanisms leading to this flash flooding event. It is known
from the limited available observations that the flood event was preceded by very intense, localised
rainfall totals. Previous work on modelling extreme rainfall and surface hydrology has shown that the
representation of a burned fire area in a model can cause an enhancement of the convection (Chen et
al 2001; Tryhorn et al 2007) or an increase in runoff (Beeson et al 2001). The candidate mechanisms
we focus upon in this study are associated with both of these sets of mechanisms: the surface
modifications and their impact on the meteorological conditions preceding the flooding event, and the
hydrological response during and after the flooding event.
2. THE OBSERVED EVENT
The operational analysis at the time of the flood, valid at 0600 UTC 26 February 2003, showed an
easterly trough extending from western New South Wales into eastern Victoria. There was a blocking
high over the Tasman Sea and a subtropical ridge extended over Bass Strait. Light winds tended north
to east over Victoria (Yeo, 2003), with anabatic and valley funnelling winds dominating the surface
observations in the Alpine areas, and weak upper air winds. Values of precipitable water were also
relatively high (above 30kg/m 2) (Yeo 2003). Yeo (2003) used adjusted soundings from Melbourne and
Wagga Wagga to estimate pre-storm Convective Available Potential Energy (CAPE) values in excess
of 1000J/kg.
Thunderstorms in the Buckland River Valley (Figure 1) were first identified on the Melbourne radar at
0530 UTC. These storms are clearly visible on the water vapour image at this time (Figure 2) and are
confined to a small region in the northeast of Victoria. No large-scale precipitation was recorded
across the state at this time. These thunderstorms produced short bursts of heavy rainfall and were
most likely to be pulse wet microbursts. Redevelopment of cells in the same location meant that a
small area at the head of the Buckland River Catchment experienced intense inundation for several
hours. There are no accurate measurements of the precipitation that fell in the catchment on that
afternoon. However, the precipitation was likely to have been quite severe over the Dingo Creek area,
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as it flooded rapidly. In one hour, the Buckland River rose 1.8 metres. It was around this time that the
firefighter’s life was lost in an attempt to cross a bridge over Dingo Creek.
Figure 2. Satellite picture of water vapour over southeastern Australia taken by Geostationary
Meteorological Satellite 5 (GMS-5) on Channel 3 (6.5 - 7.0 µm) using a Visible Infrared Spin
Scan Radiometer (VISSR) Atmospheric Sounder (VAS), 0530 UTC 26 February.
It is probable that anabatic breezes played a significant part in thunderstorm initiation, which
eventually allowed convective inhibition to be overcome. The lateness in the afternoon meant that it is
also highly likely there was time for moisture to build up in the boundary layer. The large CAPE values
would have contributed to strong updrafts within the thunderstorm capable of supporting large
quantities of suspended water droplets. Light upper winds meant that each thunderstorm cell
developed and decayed over a similar area, with rainfall from each thunderstorm likely to have fallen
over a small geographic area.
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3. DATA AND MODEL DESCRIPTIONS
3.1 Mesoscale Model Version 5
The analysis of the meteorological conditions associated with the event was performed using the
PSU/NCAR (Pennsylvania State University/National Center for Atmospheric Research) mesoscale
model version 5, denoted MM5. MM5 is a limited-area, non-hydrostatic model capable of simulating
meso- and synoptic-scale atmospheric circulations (Grell et al 1994). The initial and boundary
conditions for the model were created using the National Center for Environmental Prediction/National
Center for Atmospheric Research (NCEP/NCAR) re-analysis data at a grid spacing of 2.5o latitude by
2.5o longitude. In order to achieve sufficient horizontal resolution, a series of nested domains were
configured. Domain 1 is centred at 36.7oS latitude and 147.8oE longitude and has an extent of 1800
km x 1550 km, with a grid resolution of 50 km and 23 vertical levels. Domains 2 and 3 (Figure 1) have
resolutions of 10 km and 2 km respectively with 35 vertical levels.
3.2 The HBV1 Model
The hydrological response of the Buckland River Catchment to fire-induced surface modifications was
analysed using the HBV-96 model (Integrated Hydrological Modelling System (IHMS) version 4.5).
The HBV model, created by the Swedish Meteorological and Hydrological Institute (SMHI), is
classified as a conceptual semi-distributed model and requires input climatological (temperature,
precipitation and potential evapotranspiration) and streamflow data for calibration (Bergström, 1995;
Lindström et al 1997). The HBV model contains functionality for soil moisture accounting, snowmelt
and accumulation and runoff response (generation and routing). Input climatological data was
sourced from the Bureau of Meteorology, streamflow data from Theiss Services Pty. Ltd., and
topography data from the Department of Sustainability and Environment (DSE). The simulated
catchment encompasses the entire Buckland River Catchment in addition to the section of the Ovens
River (Wangaratta) Catchment that lies between the Harris Lane streamflow gauge and the northern
border (directly downstream) of the Buckland River Catchment (Figure 1). The studied catchment has
an area of approximately 460 km 2.
4. METHODOLOGY
The methodology used to simulate the thunderstorms is outlined in Tryhorn et al (2007) but relevant
details will be given here. A five member ensemble of five-day forecasts was performed from 1200
UTC 23 February - 1200 UTC 28 February 2003 using MM5. The flash flood occurred at around 0600
UTC on 26 February 2003. The land surface in MM5 for the area burned by the 2003 was changed to
resemble a recently burned fire surface, with decreased albedo (to resemble a blackened surface),
lowered surface roughness (reduced vegetation) and reduced soil moisture. The values were based
on previous work on modelling fire scars (Görgen et al 2006; Wendt et al 2007.) The albedo was
reduced from 0.20 to 0.08 and the roughness length from 2.65m to 0.10m. The soil moisture for the
uppermost, 10cm layer was initialised at 0.05 m 3/m3, in contrast to standard values of between 0.25
and 0.45 m3/m3. The ensemble was then compared with a simulation covering the same time period
in which no surface modifications were made (known as the unburned simulation).
The methodology used to simulate the hydrological mechanisms surrounding the flash flood event is
given in more detail in Gallucci et al (2007). The HBV model was calibrated using a 28-year period
(1972 – 1999) of streamflow data from the Harris Lane gauge. Simulations were run from 1300 UTC
24 February 2003 – 1300 UTC 4 March 2003, firstly using climatological parameter values found in
calibration, and secondly using parameter values that best represent post-fire conditions (Scott & Van
Wyk, 1990; Huffman et al 2001). Soil hydrophobicity was represented by reducing the maximum soil
moisture storage to 10mm and reducing the percolation rate to zero. These parameters were
increased post-flood in order to test whether the hydrophobic conditions were subsequently restored.
The interception canopy storage capacity was also reduced to zero to represent the post-fire decrease
in canopy interception. To explore the possible impact of each parameter on post-fire flooding,
1
Hydrologiska Byråns Vattenbalansavdelning
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sensitivity simulations were completed in which the parameters were returned to their unburned
(climatological) values.
5. RESULTS
5.1 MM5 Simulations
Overall the large-scale synoptic scale events were well simulated, apart from the (crucial) absence of
thunderstorm activity in northeast Victoria. A more detailed analysis of the synoptic scale events can
be found in Tryhorn et al (2007). In contrast to the large-scale simulation, the high-resolution Domain
3 simulations generated intense thunderstorms in the correct location. The Domain 3 simulation in the
24 hours before 2200 UTC 26 February, the time period associated with the flood, produced an
ensemble mean of 31.7mm and an ensemble maximum of 44.4 mm. This is in good agreement with
the closest observed rainfall of 37.2mm (Mount Hotham Airport AWS), but this is likely to be an
underestimate of the maximum totals that occurred on that day. The 6 hour totals of rainfall in Domain
3 at the time of flood reveals significant falls across the southern and south-western areas of the
domain. This difference from the large-scale simulation suggests a highly localised event.
The simulated CAPE during the storm was calculated to be 1546 J/kg, indicating an unstable
environment capable of producing deep convection. The surface energy balance for the control
ensemble mean (taken from an average of 9 grid boxes, not shown) indicated a large sensible heat
flux, caused primarily by the reduction in soil moisture (Tryhorn et al 2007) and leading to increased
lower boundary layer heating, destabilising the atmospheric column. This in turn led to an increase in
convective clouds and an increase in precipitation compared to the unburned simulation. The
unburned simulation produced little rain at the time of the flood event (3.9 mm) – this was well outside
the range of variation of the control ensemble, hence we consider the response to be significant. In
this case, the extreme rainfall event, even with, we suggest, a somewhat diminished intensity, could
not be simulated without the fire-induced modifications.
Figure 5. 6-hourly rainfall in domain 3 (mm), (a) 0600 UTC 26 February, (b) 1200 UTC 26
February,
5.2. HBV Simulations
A rainfall total for the head of the catchment was approximated using MM5 output precipitation data
and observations from Mount Hotham Airport AWS. The MM5 precipitation ensemble maximum was
44.4mm, with 9.8mm simulated at Mount Hotham Airport. This gives a difference of 34.6mm, which
when added to the observed precipitation at Mount Hotham Airport (37.2mm) gives a maximum
precipitation estimate of 71.8mm. 71.8mm was used as the input rainfall data for the HBV model.
When the parameters determined from the climatological calibration were used, the HBV simulation
yielded an underestimation of streamflow at the Harris Lane gauge on 26 February, and an
overestimation of streamflow when the front passed through on 28 February 2003. Without alterations
to the climatological parameter values, the flash flood event could not be replicated. Calibration using
the post-fire parameter values yielded maximum possible soil moisture storage of 10mm before and
during the flood event, then 250mm post-flood, percolation values of 0mm/day before and during the
flood event, and 4.4mm/day post-flood and canopy interception storage capacity of 0mm. The
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simulated and observed hydrographs are almost identical in shape and magnitude (Figure 4) and an
efficiency criterion value of 0.96 was achieved. Using this configuration, the flash flooding event was
successfully simulated using the HBV model.
Figure 4. Results of the simulation for the period 1300 UTC 24 February 2003 to 1300 UTC 4
March 2003 using the optimal parameters. The computed streamflow is shown as the dashed
line, and the observed streamflow is shown as the opaque line.
6. CONCLUSIONS
An analysis of the meteorological and hydrological factors leading to the post-fire flood event in the
Buckland Valley, Victoria, Australia in February 2003 has been conducted. It has been demonstrated
that flash flooding occurred because of highly localised thunderstorms and was likely to have been
enhanced by (1) the burned landscape, (2) the storm cells likely being pulse wet microburst, (3) cell
regeneration over the same area and (4) the steepness of the Buckland River Catchment. The
synoptic conditions surrounding the event suggest that the major drivers of the extreme rainfall event
were the high levels of precipitable water in the atmosphere, high CAPE values, and enhanced
atmospheric instability from surface heating. Our results indicate that this heating was amplified by the
reduction in surface albedo and soil moisture of the recently burned fire surface. This provided
increased instability and a greater chance that convective inhibition could be overcome. Hence, the
intensity of the event was enhanced by the preconditioning caused by the fire. The results of the
hydrological modelling suggest that the fire-induced soil hydrophobicity further contributed to the flash
flooding event.
Overall, these findings point to an increased risk of flash flooding after a severe fire. With an increase
in fires expected in the Alpine Shire associated with anthropogenic climate change (Abramson et al
2007; Hennessy et al 2005; Williams et al 2001), this causal relationship, even for a rare event, has
implications for emergency managers and residents in alpine regions. This has become particularly
relevant after a recent event in Licola where, following bushfires, residents were flooded with mud,
ash, and debris (Houghton, 2007).
7. ACKNOWLEDGEMENTS
This work would not have been possible without the participation, support and interest of the people of
Alpine Shire. This work has been supported by the Australian Research Council though FF0348550,
by Monash University through the postgraduate scholarship program, and by the CSIRO Division of
Marine and Atmospheric Research. We would also like to thank Rebecca Abramson, Klaus Görgen
and Petteri Uotila for helpful comments and assistance.
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8. REFERENCES
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