Research leader

A/Prof Trent Penman Research Leader
Dr Thomas Duff Research Leader

Research team

Dr Alexander Filkov Research Team
Prof Jason Sharples
Prof Jason Sharples Research Team

End User representatives

Laurence McCoy End-User
Musa Kilinc End-User
Tim Wells End-User
Andrew Stark
Andrew Stark End-User
Mark Chladil
Mark Chladil End-User
Matt Chesnais End-User
Mike Wouters
Mike Wouters End-User
Jeff Kepert
Dr Jeff Kepert End-User
Dr Neil Burrows
Dr Neil Burrows End-User
Jackson Parker End-User
Brad Davies End-User

While a number of advances have been made in understanding bushfire development under extreme conditions, these have not been quantified in a manner that is suitable for inclusion in fire behaviour modelling framework. This project aims is to develop statistical models that allow for the inclusion of dynamic effects when they are important – that is, when fires grow sufficiently large and complex.

The study is identifying the thresholds beyond which dynamic fire behaviour becomes a dominant factor, the effects that these dynamic effects have on the overall power output of a fire, and the impacts that such dynamic effects have on fire severity. This will necessarily include consideration of other factors such as how fine fuel moisture varies across a landscape.

The research team is investigating the conditions and processes under which bushfire behaviour undergoes major transitions, including fire convection and plume dynamics, evaluating the consequences of eruptive fire behaviour (spotting, convection driven wind damage, rapid fire spread) and determining the combination of conditions for such behaviours to occur (unstable atmosphere, fuel properties and weather conditions).

There are three overlapping research activities:

  1. Collating fire behaviour observations - creating a database of observations of extreme fire behaviour to use in model development and verification, working with government agencies to develop reconstructions of past fires.
  2. Understanding extreme fire weather and fire behaviour - determining the thresholds in fire and environmental conditions (weather, fuel, topography) that lead to extreme fire phenomena, such as fire tornados and ember storms.
  3. Factors linked to extreme fire behaviour - developing simple statistical equations to represent dynamic fire phenomena that can be integrated into existing fire-behaviour models.

It is expected that both the research and operational management communities will benefit by greatly improving knowledge of extreme bushfires. Currently, there is limited information with which to develop new models or test theories about extreme fire behaviour.

This project will create new observational datasets of such fires and use them to describe empirical relationships between fire phenomena and the key environmental conditions that drive them. These relationships could be incorporated into existing fire simulation systems and generate further research, including the verification of physics-based models and the development of new theories of fire propagation.

The research will be utilised through the development of guidelines for identifying environmental conditions causing the extreme fire behaviour phenomena during operational fire behaviour analysis and improved fire behaviour simulators through the inclusion of extreme fire behaviours.

These outputs will result in improved prediction of fire behaviour at the point where damage to property and loss of life is more likely. Improved predictions will improve the knowledge base of fire managers and their ability to make informed decisions during fires and about landscape vulnerability. This will include improving the efficiency and safety of fire suppression activities, better targeting of public information and warnings, and an improved understanding of the potential effectiveness strategies for managing landscape fire risk.

Year Type Citation
2022 Book Chapter Filkov, A., Cawson, J., Swan, M. & Penman, T. Handbook of Fire and the Environment The Society of Fire Protection Engineers Series, (Springer, 2022).
2022 Report Filkov, A., Duff, T. & Penman, T. Determining threshold conditions for extreme fire behaviour - final project report. (Bushfire and Natural Hazards CRC, 2022).
2021 Conference Paper Filkov, A. Predicting merging fire behaviour in Planned Burning. AFAC21 (AFAC, 2021). at <https://www.afac.com.au/events/proceedings/05-10-21/article/predicting-merging-fire-behaviour-in-planned-burning>
2020 Journal Article Cawson, J. et al. Exploring the key drivers of forest flammability in wet eucalypt forests using expert-derived conceptual models. Landscape Ecology 35, 1775–1798 (2020).
2020 Journal Article Filkov, A., Ngo, T., Matthews, S., Telfer, S. & Penman, T. Impact of Australia's catastrophic 2019/20 bushfire season on communities and environment. Retrospective analysis and current trends. Journal of Safety Science and Resilience (2020). doi:https://doi.org/10.1016/j.jnlssr.2020.06.009
2020 Journal Article Burton, J., Cawson, J., Filkov, A. & Penman, T. Leaf traits predict global patterns in the structure and flammability of forest litter beds. Journal of Ecology (2020). doi:https://doi.org/10.1111/1365-2745.13561
2020 Journal Article Prohanov, S., Filkov, A., Kasymov, D. P., Agafontsev, M. & Reyno, V. Determination of Firebrand Characteristics Using Thermal Videos. Fire 3, (2020).
2020 Report Filkov, A., Duff, T. & Penman, T. Determining threshold conditions for extreme fire behaviour - annual report 2019-2020. (Bushfire and Natural Hazards CRC, 2020).
2019 Conference Paper Filkov, A., Cirulis, B. & Penman, T. Quantifying dynamic fire behaviour phenomena using Unmanned Aerial Vehicle technology . 23rd International Congress on Modelling and Simulation (2019). at <https://www.researchgate.net/publication/338412609_Quantifying_dynamic_fire_behaviour_phenomena_using_Unmanned_Aerial_Vehicle_technology>
2019 Journal Article Penman, T. & Cirulis, B. Cost effectiveness of fire management strategies in southern Australia. International Journal of Wildland Fire 29, 427-439 (2019).
2019 Journal Article Filkov, A., Duff, T. & Penman, T. Frequency of Dynamic Fire Behaviours in Australian Forest Environments. Fire 3, (2019).
2019 Report Filkov, A., Duff, T. & Penman, T. Determining threshold conditions for extreme bushfire behaviour annual report 2018-2019. (Bushfire and Natural Hazards CRC, 2019).
2019 Report Filkov, A., Duff, T. & Penman, T. Determining Threshold Conditions for Extreme Fire Behaviour Annual Report 2017-2018. (Bushfire and Natural Hazards CRC, 2019).
2018 Conference Paper Bates, J. Research proceedings from the 2018 Bushfire and Natural Hazards CRC and AFAC Conference. Bushfire and Natural Hazards CRC & AFAC annual conference 2017 (Bushfire and Natural Hazards CRC, 2018).
2018 Conference Paper Filkov, A., Duff, T. & Penman, T. Extreme fire behaviours: Surveying fire management staff to determine behaviour frequencies and importance. AFAC18 (Bushfire and Natural Hazards CRC, 2018).
2018 Journal Article Filkov, A. & Prohanov, S. Particle tracking and detection software for firebrands characterization in wildland fires. Fire Technology 55, 817-836 (2018).
2018 Journal Article Filkov, A., Duff, T. & Penman, T. Improving Fire Behaviour Data Obtained from Wildfires. Forests 9, (2018).
2018 Journal Article Read, N., Duff, T. & Taylor, P. A lightning-caused wildfire ignition forecasting model for operational use. Agricultural and Forest Meteorology 253-254, 16 (2018).
2018 Journal Article Matvienko, O. V., Kasymov, D. P., Filkov, A., Daneyko, O. I. & Gorbatov, D. A. Simulation of fuel bed ignition by wildland firebrands. International Journal of Wildland Fire 27, (2018).
2018 Report Filkov, A., Duff, T. & Penman, T. Determining threshold conditions for extreme fire behaviour. (Bushfire and Natural Hazards CRC, 2018).
2017 Journal Article Mueller, E. et al. Utilization of remote sensing techniques for the quantification of fire behavior in two pine stands. Fire Safety Journal 91, 845-854 (2017).
2017 Journal Article Fateev, V., Agafontsev, M., Volkov, S. & Filkov, A. Determination of smoldering time and thermal characteristics of firebrands under laboratory conditions. Fire Safety Journal 91, 791-799 (2017).
2017 Journal Article Filkov, A. et al. Investigation of firebrand production during prescribed fires conducted in a pine forest. Proceedings of the Combustion Institute 36, 3270 (2017).
2017 Journal Article Thomas, J. et al. Investigation of firebrand generation from an experimental fire: development of a reliable data collection methodology. Fire Safety Journal 91, 864-871 (2017).
2017 Report Filkov, A., Duff, T. & Penman, T. Determining threshold conditions for extreme fire behaviour: annual project report 2016-17. (Bushfire and Natural Hazards CRC, 2017).
2016 Conference Paper Tolhurst, K. G. & McCarthy, G. J. Effect of prescribed burning on wildfire severity - a landscape case study from the 2003 fires in Victoria. AFAC16 (Bushfire and Natural Hazards CRC, 2016).
2016 Report Duff, T., Penman, T. & Filkov, A. Determining threshold conditions for extreme fire behaviour: Annual project report 2015-2016. (Bushfire and Natural Hazards CRC, 2016).
2015 Presentation Duff, T. & Penman, T. Determining threshold conditions for extreme fire behaviour. (2015).
2015 Report Duff, T. & Penman, T. Determining threshold conditions for extreme fire behaviour: Annual project report 2014-2015. (Bushfire and Natural Hazards CRC, 2015).
Date Title Download Key Topics
27 Oct 2014 Environmental thresholds for dynamic fire propagation fire, propagation
04 Dec 2014 Threshold conditions for extreme fire behaviour PDF icon 610.43 KB (610.43 KB) fire, fire severity, modelling
22 Mar 2016 Severe and High Impact Weather - cluster overview File 0 bytes (0 bytes) fire, modelling, scenario analysis
24 Oct 2016 Determining threshold conditions for extreme fire behaviour PDF icon 1.88 MB (1.88 MB) fire severity, mitigation, severe weather
25 Oct 2016 Next generation fire modelling PDF icon 1.35 MB (1.35 MB) fire impacts, fire severity, fire weather
07 Jul 2017 Building bushfire predictive services capability PDF icon 9.97 MB (9.97 MB) fire, fire weather, modelling
07 Jul 2017 Building bushfire predictive services capability - Simon Heemstra File 0 bytes (0 bytes) fire, fire impacts, modelling
31 Oct 2017 Determining threshold conditions for extreme fire behaviour: standardising data obtained from wildfires PDF icon 567.23 KB (567.23 KB) fire, fire impacts, fire severity
19 Sep 2018 The development of a pyrocumulonimbus prediction tool PDF icon 2.01 MB (2.01 MB) fire impacts, fire severity
23 Nov 2018 Determining threshold conditions for extreme fire behaviour PDF icon 868.87 KB (868.87 KB) fire, fire impacts
18 Jun 2019 Interactions between climate, vegetation and fuel PDF icon 3.16 MB (3.16 MB) environments, fire weather, severe weather
17 Oct 2019 Thresholds for dynamic fire behaviours PDF icon 5.88 MB (5.88 MB) fire, fire severity
01 Dec 2020 PHOENIX RapidFire fire, fire impacts, fire severity
18 Feb 2022 Understanding what happens when bushfires merge PDF icon 1.28 MB (1.28 MB) fire, fire impacts, fire severity
Trent Penman Conference Poster 2016
14 Aug 2016
The bushfire behaviour and management group of the University of Melbourne is conducting a project to...
Kevin Tolhurst Conference Poster 2016
14 Aug 2016
This project aims to better describe the nature of bushfires, especially very severe ones, and the effect of...
Trent Penman Conference Poster 2016
14 Aug 2016
Bushfire management involves making decisions about complex issues that involve people, communities,...
Extreme fire behaviours: Surveying fire management staff to determine behaviour frequencies and importance
19 Sep 2018
Extreme fire behaviours (EFBs) are phenomena that occur within intense fires that have been shown to...
31 Aug 2020
Key findings: The validity of using dynamic heating regimes and VHFlux apparatus as a standardised method has...