@article {bnh-8375, title = {Physics-based simulations of grassfire propagation on sloped terrain at field scale: motivations, model reliability, rate of spread and fire intensity}, journal = {International Journal of Wildland Fire}, year = {2023}, month = {01/2023}, abstract = {

This study focuses on physics-based modelling of grassfire behaviour over flat and sloped terrains through a set of field-scale simulations performed using the Wildland{\textendash}urban Interface Fire Dynamics Simulator (WFDS), with varying wind speeds (12.5, 6 and 3 m s-1) and slope angles (-30{\textdegree} to +30{\textdegree}). To ensure the accuracy of this Large Eddy Simulation (LES), a sensitivity study was carried out to select the converged domain and grid sizes. Fire isochrones, locations of fire front, dynamic and quasi-steady rates of spread (RoS), and fire intensity results from the simulations are presented. Within the simulations conducted, the RoS and fire intensity were found to be higher with increasing slope angles, as well as with wind velocity. RoS comparisons are made with various empirical models. At different slope angles and driving wind velocities, different empirical quasi-steady RoS broadly match with particular dynamic maximum, minimum and averaged RoS values from this study. It appears that the ideal nature of grassfire propagation simulation and challenges related to measuring quasi-steady values in experimental studies are likely reasons for the observed differences. Additionally, for lower wind velocities, the RoS{\textendash}fire intensity relationship (Byram{\textquoteright}s) deviates from linearity for greater upslopes.

}, keywords = {Fire behaviour, fire front, grass fire, intensity, rate of spread (RoS) of fire, simulations, slope, wind speed}, doi = {https://doi.org/10.1071/WF21124}, url = {https://www.publish.csiro.au/wf/WF21124}, author = {Jasmine Innocent and Duncan Sutherland and Nazmul Khan and Khalid Moinuddin} } @article {bnh-8189, title = {Established and emerging uses of predictive services in Victoria}, number = {697}, year = {2021}, month = {08/2021}, institution = {Bushfire and Natural Hazards CRC}, address = {MELBOURNE}, abstract = {

The recent 2019-20 Black Summer bushfire season brought both sector and public attention to the important role that predictive services can play in mitigating and preventing the loss of life and assets from bushfires.

This research study focused on two key questions:

  1. What are the key features of effective relationships between Fire Behaviour Analysts (FBANs) and their users within emergency management?
  2. How might the predictive services role and predictive services outputs be developed in the future?

We explored these questions by conducting twenty-five (25) semi-structured interviews with key practitioners who either perform the FBAN role or use predictive services in Victoria.

Our findings are categorised into 7 topics:

1. Interviewee background: The interviewees included people who represent the following operational roles: FBAN, State Regional Commander, State Agency Commander, Level 3 Incident Controller, Level 3 Public Information Officer, Level 3 Planning Officer, Level 3 Operations Officer, and Level 3 Situation Officer.

2. FBAN outputs: We collected data from FBANs and other operations staff who occupy roles which interact with and/or use the outputs produced by FBANs from within the broad emergency and incident control arrangements provided for within the Australasian Inter-service Incident Management System.

We found that the FBAN advice and products are used to:

Most interviewees agreed that the design and framing of outputs should be standardised for public dissemination, however, there was less consensus that such standardisation is required for operational purposes.

3. Trust in FBAN outputs: We found that in general:

Trust is an important factor in the high-pressure contexts of incident and land management, including both interpersonal trust and trust in particular tools and systems. We found that trust seems to depend, in part, upon users{\textquoteright} perceptions of a given FBAN{\textquoteright}s skills, level of experience, and knowledge of the area or context in which they are offering predictive intelligence. For FBANs, both having fireground experience and {\textquotedblleft}local knowledge{\textquotedblright} and being able to convince users that one has fireground experience and {\textquotedblleft}local knowledge{\textquotedblright} seem to be important factors in eliciting the trust of some users.

4. Timeliness of FBAN outputs: We explored whether FBANs produced advice and outputs in a timely manner. We found that:

For example, a {\textquotedblleft}quick and dirty{\textquotedblright} map of potential fire spread was seen to be acceptable during first attack. However, the pressure related to timeliness decreases during an extended attack and is substantially decreased during pre-event planning and planned burning, or in any instance where there is potentially more time for FBANs to converse with end-users, collect and validate intelligence and tailor the outputs to the end-users{\textquoteright} needs.

5. Benefits of releasing FBAN outputs publicly: We explored whether participants felt predictive outputs produced by FBANs (e.g., fire spread predictions) should be released to the community (i.e., affected communities and the general public) to facilitate their decision-making and planning during periods of significantly elevated fire danger (e.g., days of {\textquotedblleft}Extreme{\textquotedblright} fire danger rating). We found that:

Participants noted that there is a moral imperative to release information to assist members of the public in their decision-making in relation to fire hazards. Further, there was a sense amongst many participants that, by releasing FBAN products publicly, emergency management organisations could support trust-building between agencies and communities and better demonstrate their transparency and accountability when working with the community to plan for and respond to bushfires.

6. Risks of releasing FBAN products publicly: We explored with the participants whether they felt that it was a risk to release FBAN outputs to the community to facilitate their decision-making and planning on days of significantly elevated fire danger. In general, participants reported that there were low levels of risk associated with releasing FBAN outputs to the community to facilitate community decision-making and planning.

We found that, where there was unease amongst participants in relation to releasing FBAN outputs publicly, it was because of:

7. The future of the FBAN role: We explored whether participants felt that the FBAN role will continue to be important within the broad emergency and incident control arrangements. We found that:

With this in mind, it is important to understand that the development of predictive services must ensure that it is further integrated into emergency management arrangements outside the State Control Centre. Specifically, viewed in relation to other project findings, it is clear that for such development and integration to be effective, FBANs will be required to spend more time interacting with users. Such interactions may sometimes occur outside fire seasons, though it is also apparent that they also need to occur throughout the fire season, on firegrounds and in Incident Management Centres and Regional Control Centres, in order to grow FBANs{\textquoteright} skillsets, maintain trust with users, educate users about their outputs and adapt those outputs to user needs. Various users had suggestions about how predictive services might better serve their needs, the vast majority of which related to the refinement of output types and modes of presentation to incidents and situations as they emerge.

Following this feedback also means exploring the different ways that FBAN skillsets and competencies can be used to assist key decision-makers such as Incident Controllers and community information and warning teams which continue to be so important in terms of planning and responding to bushfires. These skillsets and competencies - at both state and regional levels - also have relevant application to conduct of planned burning, and both users and FBANs suggest that more use can be made of FBAN skillsets and competencies to assist the states land and fire management agencies in achieving fuel management goals.

Based on these findings, we make 4 recommendations, detailed as follows:

Recommendation 1: that emergency management agencies explore which FBAN outputs could be released to the community to support their planning and decision-making during bushfire season.

Recommendation 2: that emergency management agencies explore how FBANs and predictive service outputs can be utilised to better support other relevant functions such as the conduct of planned burning and public information.

Recommendation 3: that emergency management agencies explore the ongoing training and development needs of FBANs.

Recommendation 4: that emergency management agencies work with FBANs to develop continuous learning processes which can be used to improve predictive services after bushfire and planned burning seasons.

In terms of utilisation, our recommendations will require an implementation strategy which needs to be mindful of the requirements to continue to plan for and respond to ongoing incidents that require predictive services. Accordingly, we propose a staged approach to utilisation that is channelled through the Bushfire and Natural Hazards CRC Black Summer research group.

Finally, we have confidence that these findings and recommendations are relevant to many other jurisdictions in Australia, including Western Australia, Tasmania, South Australia, Australian Capital Territory, Queensland, and New South Wales, given their similarity in bushfire hazards, incident management systems, and the role and scope of predictive services.

}, keywords = {analysts, black summer, FBANs, Fire behaviour, predictive, services, Victoria}, issn = {697}, author = {Chloe Begg and Graham Dwyer and Timothy Neale and Ian Pollock} } @article {bnh-8303, title = {Initial growth of fires in eucalypt litter, from ignition to steady-state rate of spread: laboratory studies}, journal = {International Journal of Wildland Fire}, year = {2021}, month = {12/2021}, abstract = {

As part of an investigation of wildfire growth and acceleration, the initial growth of incipient fires burning in uniform dry eucalypt forest (Eucalyptus rossii,\ E. macrorhyncha) litter fuel of 1.2 kg m-2\ was studied in a combustion wind tunnel with a fuel bed width of 1.5 m. Fifty-eight fires of three ignition patterns (point, 400-mm line and 800-mm line) were carried out at two air speeds (1.25 and 2.0 m s-1) and two dead fuel moisture content (FMC) groups for each air speed (<=7.5\% and \>7.5\% oven-dry weight for the low air speed and <=5\% and \>5\% for the high air speed). The fraction of steady-state rate of spread reached as a function of time was determined and fitted to two theoretical fire growth models from the literature. The best model suggests the times for a point ignition fire to reach steady-state spread rate were ~38 and 50 min under the higher FMC for 2.0 m s-1\ and 1.25 m s-1\ air speeds, respectively, and ~25 min under the lower FMC for 2.0 m s-1. Future work will extend these results to field-scale fire behaviour, which will help improve operational response to wildfire outbreaks and planning of ignition patterns for prescribed burning.

}, keywords = {acceleration, combustion wind tunnel, experiments, Fire behaviour, fire development, fire growth, Pyrotron, Rate of spread}, doi = {https://doi.org/10.1071/WF21094}, url = {https://www.publish.csiro.au/WF/WF21094}, author = {J.S. Gould and Sullivan, Andrew} } @conference {bnh-8286, title = {Predicting merging fire behaviour in Planned Burning}, booktitle = {AFAC21}, year = {2021}, month = {10/2021}, publisher = {AFAC}, organization = {AFAC}, address = {Online}, abstract = {

It was found that laboratory scale fire experiments do not replicate large scale fires, and therefore, extensive high temporal and spatial resolution experimental data at larger scales are required to fully understand how a given fire will merge and spread. Unmanned aerial vehicles (UAVs or drones) may be a useful tool in obtaining these measurements. To provide operational and management personnel with a better understanding of the dynamic nature of fire line merging, UAVs were used in this study to measure fire rate of spread throughout the burns recording linear fire rates of spread and merging fire rate of spread in a range of fuel types in western Victoria. Using special software, we were able to record the rates of spread over time and determine the effect of ignition patterns on fire behaviour. These utilisation outcomes can be used to better support decision making around ignition methods during planned burning operations, as well as maximising the information available to support firefighter training and further research and development.

}, keywords = {Fire behaviour, fire predictions, UAVs}, url = {https://www.afac.com.au/events/proceedings/05-10-21/article/predicting-merging-fire-behaviour-in-planned-burning}, author = {Alex Filkov} } @article {bnh-7472, title = {Causes and consequences of Eastern Australia{\textquoteright}s 2019{\textendash}20 season of mega-fires: A broader perspective}, journal = {Global Change Biology}, volume = {26}, year = {2020}, month = {04/2020}, pages = {pp. 3756-3758}, abstract = {

Climates{\textemdash}especially seasonal and long-term droughts{\textemdash}and fuel loads combine to determine risks of wildfires across much of Australia. Here we illustrate how long-term accumulations of fuel combined with a serious drought to drive the behaviour and extent of recent fires in South-eastern Australia.

This article is a commentary on Nolan et al. 26,\ 1039{\textendash}1041. See also the response to this letter by Bradstock et al. 26,\ e8{\textendash}e9.

}, keywords = {Bushfire, climate, Fire behaviour}, doi = { https://doi.org/10.1111/gcb.15125}, url = {https://onlinelibrary.wiley.com/doi/full/10.1111/gcb.15125}, author = {Adams, Mark A. and Majid Shadmanroodposhti and Mathias Neumann} } @article {bnh-6754, title = {Drivers of long-distance spotting during wildfires in south-eastern Australia}, journal = {International Journal of Wildland Fire}, year = {2020}, month = {03/2020}, abstract = {

We analysed the influence of wildfire area, topography, fuel, surface weather and upper-level weather conditions on long-distance spotting during wildfires. The analysis was based on a large dataset of 338 observations, from aircraft-acquired optical line scans, of spotting wildfires in south-east Australia between 2002 and 2018. Source fire area (a measure of fire activity) was the most important predictor of maximum spotting distance and the number of long-distance spot fires produced (i.e. \>500 m from a source fire). Weather (surface and upper-level), vegetation and topographic variables had important secondary effects. Spotting distance and number of long-distance spot fires increased strongly with increasing source fire area, particularly under strong winds and in areas containing dense forest and steep slopes. General vegetation descriptors better predicted spotting compared with bark hazard and presence variables, suggesting systems that measure and map bark spotting potential need improvement. The results from this study have important implications for the development of predictive spotting and wildfire behaviour models.

}, keywords = {Fire behaviour, line scan, spot fire}, doi = {https://doi.org/10.1071/WF19124}, url = {https://www.publish.csiro.au/wf/WF19124}, author = {Michael Storey and Owen Price and Jason J. Sharples and Ross Bradstock} } @article {bnh-7475, title = {Exploring the key drivers of forest flammability in wet eucalypt forests using expert-derived conceptual models}, journal = {Landscape Ecology}, volume = {35}, year = {2020}, month = {06/2020}, pages = {1775{\textendash}1798}, abstract = {

Context

Fire behaviour research has largely focused on dry ecosystems that burn frequently, with far less attention on wetter forests. Yet, the impacts of fire in wet forests can be high and therefore understanding the drivers of fire in these\ systems\ is vital.

Objectives

We sought to identify and rank by importance the factors plausibly driving flammability in wet eucalypt forests, and describe relationships between them. In doing so, we formulated a set of research priorities.

Methods

Conceptual models of forest flammability in wet eucalypt forests were elicited from 21 fire experts using a combination of elicitation techniques. Forest flammability was defined using fire occurrence and fireline intensity as measures of ignitability and heat release rate, respectively.

Results

There were shared and divergent opinions about the drivers of flammability in wet eucalypt forests. Widely agreed factors were drought, dead fine fuel moisture content, weather and topography. These factors all influence the availability of biomass to burn, albeit their effects and interactions on various dimensions of flammability are poorly understood. Differences between the models related to lesser understood factors (e.g. live and coarse fuel moisture, plant traits, heatwaves) and the links between factors.

Conclusions

By documenting alternative conceptual models, we made shared and divergent opinions explicit about flammability in wet forests. We identified four priority research areas: (1) quantifying drought and fuel moisture thresholds for fire occurrence and intensity, (2) modelling microclimate in dense vegetation and rugged terrain, (3) determining the attributes of live vegetation that influence forest flammability, (4) evaluating fire management strategies.

}, keywords = {Cognitive mapping, Conceptual models, Expert elicitation, Fire behaviour, fire intensity, flammability, Structured decision-making, Structured expert judgement, Wet forest, Wildfire}, doi = {https://doi.org/10.1007/s10980-020-01055-z}, url = {https://link.springer.com/article/10.1007/s10980-020-01055-z}, author = {Jane Cawson and Victoria Hemming and Ackland, A and Wendy R. Anderson and David Bowman and Ross Bradstock and Brown, T and Jamie Burton and Geoffrey J. Cary and Thomas Duff and Alex Filkov and Furlaud, James M. and Tim Gazzard and Kilinc, Musa and Petter Nyman and Ross Peacock and Mike Ryan and Jason J. Sharples and Gary J. Sheridan and Tolhurst, K.G. and Tim Wells and Phil Zylstra and Trent Penman} } @article {bnh-7708, title = {Leaf traits predict global patterns in the structure and flammability of forest litter beds}, journal = {Journal of Ecology}, year = {2020}, month = {12/2020}, abstract = {
  1. Fallen plant material such as leaves, needles and branches form litter beds which strongly influence fire ignition and spread. Traits of the dominant species influence litter flammability directly by determining how individual leaves burn and indirectly through the structure of the litter bed. However, we are yet to determine the relative importance of these different drivers across a range of plant species from different biomes.
  2. We undertook a meta-analysis, combining leaf trait, litter structure and flammability data for 106 species from North America, South America, Europe, Asia and Australia. The dataset encompassed broad-leaved and coniferous species from seven different experimental studies. Relationships between leaf traits, litter structure and key flammability metrics{\textemdash}sustainability, combustibility and consumability{\textemdash}were analysed using bivariate and piecewise structural equation modelling (SEM).
  3. Traits which characterise the three-dimensional nature of the leaf and how much space a leaf occupies showed much stronger associations to litter structure and flammability than other morphological traits. Leaf curl, surface area to volume ratio (SAV) and SLA predominately influence litter flammability indirectly via litter structure with SLA being the only leaf trait which had a negative direct effect on flame duration. Packing ratio and bulk density were influenced by different combinations of leaf traits and, in turn, they aligned with different flammability metrics. Bulk density predicted flame spread rate and flame duration whereas packing ratio predicted consumption.
  4. Synthesis. We identified key leaf and litter traits which influence different components of litter bed flammability. Importantly, we show that the effects of these leaf and litter traits are consistent across a wide range of taxa and biomes. Our study represents a significant step towards developing trait-based models for predicting surface wildfire behaviour. Such models will more flexibly accommodate future shifts in the composition of plant species triggered by altered fire regimes and climate change.
}, keywords = {Fire behaviour, flammability, leaf traits, litter properties, meta-analysis, surface fuel}, doi = {https://doi.org/10.1111/1365-2745.13561}, url = {https://besjournals.onlinelibrary.wiley.com/doi/full/10.1111/1365-2745.13561}, author = {Jamie Burton and Jane Cawson and Alex Filkov and Trent Penman} } @conference {bnh-6410, title = {ACCESS-Fire: coupled fire-atmosphere modelling}, booktitle = {Bushfire and Natural Hazards CRC Research Day AFAC19}, year = {2019}, month = {12/2019}, address = {Melbourne}, abstract = {

Coupled models are a class of fire prediction models that integrate a fire component with an atmospheric component, to examine how the energy released by a fire modifies the surrounding atmosphere. Coupled models can resolve complex interactions between the fire, topography and atmosphere, which subsequently manifest on fire behaviour. Results from simulations promote understanding of the driving processes in dynamic fire events. This can inform development of predictive tools that may be used to anticipate extreme fire behaviour and mitigate against the impacts of significant fires.

Globally, several coupled models have been developed; mostly by meteorological institutions for application in a research capacity. They can be broadly separated as taking either physical or empirical modelling approaches. We are running ACCESS-Fire; an empirical coupled model. It links the research version of the Australian Community Climate and Earth System Simulator (ACCESS) Numerical Weather Prediction (NWP) to a set of empirically derived fire spread equations. In this presentation we will describe the coupled fire-atmosphere model ACCESS Fire and report on progress on simulations of recent significant fire events.

In Australia and overseas, the imperative for accurate, flexible and timely predictions for prescribed (fuel reduction) burns and bushfires will only increase. Incorporating complex, dynamical meteorological fields is a critical component in building fire prediction systems that can resolve some of the most destructive elements of fire behaviour. Although coupled fire-atmosphere models are currently limited in producing timely operational output due to computational requirements, these restrictions will diminish as technology capabilities continue to increase.

}, keywords = {coupled models, Fire behaviour, fire-atmosphere, Forecasting, modelling}, url = {https://knowledge.aidr.org.au/resources/australian-journal-of-emergency-management-monograph-series/}, author = {Mika Peace and Jeffrey Kepert and Harvey Ye} } @conference {bnh-6504, title = {Experiences with the global impacts of climate change}, booktitle = {AFAC19 powered by INTERSCHUTZ - Bushfire and Natural Hazards CRC Research Forum}, year = {2019}, month = {12/2019}, publisher = {Australian Institute for Disaster Resilience}, organization = {Australian Institute for Disaster Resilience}, address = {Melbourne}, abstract = {

Textbox Australia{\textquoteright}s emergency managers are in the grips of climate change. The climate is changing in Canberra, where I work. In turn that is affecting the spectrum of incidents that we as emergency managers are responding to. This involves the community through the risks to the community (that we seek to mitigate).

I seek to explore this through my direct experiences on the job: as an emergency manager, as a technical expert and as a research scientist. Our climate in Canberra has changed, and has changed dramatically, starting with the 1997 El Ni{\~n}o event when our climate started following what is termed the {\textquotedblleft}Hockey Stick Curve{\textquotedblright} (Mann et al, 1999). A typical summer now involves: extreme heat, extreme atmospheric moisture, extreme storms and extreme raised dust. By using the hockey stick concept it is clear that this is not the {\textquotedblleft}New Norm{\textquotedblright}, rather that the situation may deteriorate quickly.

Looking more widely, across the nation, we have seen challenging wildfire outbreaks in Queensland, Tasmania (twice) and other areas. My work as a fire behaviour analyst (FBAN) makes it clear that our prior expectations are losing their validity. What do we replace them with? Looking globally, I have deployed to Canada as an FBAN and I am collaborating as part of a global atmospheric research project looking at the growing impact of fire thunderstorms (pyroCbs). This required monitoring of smoke impact on the Greenland Ice Cap, and its potential impacts. I was in the IMT for two of the world{\textquoteright}s most significant pyroCb events. We are seeing this new wildfire problem occur in new regions, starting with Australia in 2001, but now expanding rapidly every year.

Staggering changes, devastating impacts and massive challenges - are we adapting correctly? I offer some take-home messages to help, covering observing, sharing, preparing and adapting.

Download the full peer reviewed research proceedings\ from the Bushfire and Natural Hazards CRC Research Forumhere.

}, keywords = {Climate change, Emergency management, Fire behaviour, fire impacts, fire management, global impact, Wildfire}, url = {https://knowledge.aidr.org.au/resources/australian-journal-of-emergency-management-monograph-series/}, author = {Rick McRae} } @conference {bnh-6411, title = {Fire weather and prototype fire danger ratings for the Gell River fire, Tasmania}, booktitle = {Bushfire and Natural Hazards CRC Research Day AFAC19}, year = {2019}, month = {12/2019}, address = {Melbourne}, abstract = {

We provide a preliminary analysis of the meteorology of key aspects of the Gell River fire in Tasmania during late December 2018 and early January 2019, including the lightning storm that ignited the fire, and conditions on 4 January 2019, when the fire increased substantially in size. We also briefly assess the performance of the Australian National Fire Danger Rating System (AFDRS) Research Prototype available on 4 January against observations of fire spread and routine McArthur Forest Fire Danger forecasts.

The Gell River fire occurred within a context of declining October {\textendash} April rainfall in western Tasmania over the last two decades, in comparison to the average rainfall for the period since 1900 (Fig. 1, Bureau of Meteorology and CSIRO (2018)). It was one of several large fires that competed for fire management resources over an extended period during the 2018-2019 Tasmanian fire season. The fire impacted natural values including those of the Tasmanian Wilderness World Heritage Area (TWWHA) and risked spreading into parts of the iconic Mt Field National Park, as well as threatening a number of communities in the Derwent Valley, particularly Maydena. The Gell River fire also threatened major electrical transmission infrastructure connecting the large Gordon-Pedder power generation facility in the west of Tasmania to population centres in the east, and burnt approximately 500 ha of a 5,000 ha pine plantation. On 4 January, thick smoke from the fire crossed over the Greater Hobart area, sparking concern and raising awareness within the wider community about the fire activity (Fig. 2).

}, keywords = {Fire behaviour, Fire weather, modelling}, url = {https://knowledge.aidr.org.au/resources/australian-journal-of-emergency-management-monograph-series/}, author = {Paul Fox-Hughes and Stuart Matthews and Chris Collins and Saskia Grootemaat and Jennifer J Hollis and Alexander Holmes and Belinda Kenny and John Runcie and Samuel Sauvage} } @conference {bnh-6527, title = {Fuels3D: barking up the wrong tree and beyond}, booktitle = {AFAC19 powered by INTERSCHUTZ - Bushfire and Natural Hazards CRC Research Forum}, year = {2019}, month = {12/2019}, publisher = {Australian Institute for Disaster Resilience}, organization = {Australian Institute for Disaster Resilience}, address = {Melbourne}, abstract = {

Improvement of the understanding of how fuel characteristics correlate with fire behaviour and severity is critical to the ongoing handling of risk and recovery in fire-prone environments. Current standards and protocols for describing fuel hazard (for example, {\textquoteleft}Overall Fuel Hazard Assessment Guide{\textquoteright}, Victorian Department of Sustainability and Environment) and post-burn severity (for example, {\textquoteleft}Fire Severity Assessment Guide{\textquoteright}, Victorian Department of Sustainability and Environment) were written for collection of information in the field. The data collected are largely subjective descriptions of the landscape. The ability of information from these assessment techniques to be adapted to modern risk assessment tools such as fire behavior models, or for the calibration and validation of datasets, is limited. Quantitative data-rich methods of measuring and assessing fuel load and structure are the missing link between the knowledge of land management personnel in the field, and the model drivers and decision makers at organizational level.

Handheld devices with high quality sensors, in the form of offthe-shelf cameras, are increasingly ubiquitous, as is the availability of 3D point cloud data collected from active sensing instruments on terrestrial and aerial platforms. Rapid and comprehensive capture of information by these devices, coupled with the use of computer vision techniques, allows for the 3D description of the surrounding environment to be exploited to provide robust measurement of metrics that can be built into existing fuel hazard assessment frameworks. Providing key metrics as data products rather than a single product enables flexibility across jurisdictions and ecosystem types, and capacity to adapt as end-user requirements change.

The Fuels3D project has created a suite of tools and methods for image capture in the field during fuel hazard assessments. 3D point clouds are generated using computer vision and photogrammetry techniques. From these 3D point clouds, scale is added, and decision rules are programmed to calculate quantifiable surface / near-surface metrics that replicate those
used in current fuel hazard visual assessment guides. Case studies are highlighted here.

Download the full non-peer reviewed research proceedings\ from the Bushfire and Natural Hazards CRC Research Forumhere.

}, keywords = {data collection, Fire behaviour, fuel hazard, risk management, technology}, url = {https://knowledge.aidr.org.au/resources/australian-journal-of-emergency-management-monograph-series/}, author = {Karin Reinke and Luke Wallace and Samuel Hillman and Bryan Hally and Simon Jones} } @article {bnh-4427, title = {Analysis of the physical processes associated with junction fires at laboratory and field scales}, journal = {International Journal of Wildland Fire }, volume = {27}, year = {2018}, month = {01/2018}, abstract = {

Junction fires, which involve the merging of two linear fire fronts intersecting at a small angle, are associated with very intense fire behaviour. The dynamic displacement of the intersection point of the two lines and the flow along the symmetry plane of the fire are analysed for symmetric boundary conditions. It is observed that the velocity of displacement of this point increases very rapidly owing to strong convective effects created by the fire that are similar to those of an eruptive fire. The change of fire geometry and of its associated flow gradually blocks the rate of spread increase and creates a strong deceleration of the fire, which ends up behaving like a linear fire front. Results from laboratory and field-scale experiments, using various fuel beds and slope angles and from a large-scale fire show that the processes are similar at a wide range of scales with little dependence on the initial boundary conditions. Numerical simulation of the heat flux from two flame surfaces to an element of the fuel bed show that radiation can be considered as the main mechanism of fire spread only during the deceleration phase of the fire.

}, keywords = {accelerating fires, convective effects, dynamic fire behaviour, extreme fire behaviour, Fire behaviour, merging fires.}, doi = {10.1071/WF16173}, url = {http://www.publish.csiro.au/WF/WF16173}, author = {J. R. Raposo and D. X. Viegas and X. Xie and M. Almeida and A. R. Figueiredo and L. Porto and Jason J. Sharples} } @article {bnh-4458, title = {Improving Fire Behaviour Data Obtained from Wildfires}, journal = {Forests}, volume = {9}, year = {2018}, month = {02/2018}, abstract = {

Organisations that manage wildfires are expected to deliver scientifically defensible decisions. However, the limited availability of high quality data restricts the rate at which research can advance. The nature of wildfires contributes to this: they are infrequent, complex events, occur with limited notice and are of relatively short duration. Some information is typically collected during wildfires, however, it is often of limited quantity and may not be of an appropriate standard for research. Here we argue for a minimum standard of data collection from every wildfire event to enhance the advancement of fire behaviour research and make research findings more internationally relevant. First, we analyse the information routinely collected during fire events across Australia. Secondly, we review research methodologies that may be able to supplement existing data collection. Based on the results of these surveys, we develop a recommended list of variables for routine collection during wildfires. In a research field typified by scarce data, improved data collection standards and methodologies will enhance information quality and allow the advancement in the development of quality science.

}, keywords = {data collection and management, Fire behaviour, research utilization, standard.}, doi = {10.3390/f9020081}, url = {http://www.mdpi.com/1999-4907/9/2/81}, author = {Alex Filkov and Thomas Duff and Trent Penman} } @article {bnh-6927, title = {JASMIN: A prototype high resolution soil moisture analysis system for Australia}, year = {2017}, month = {10/2017}, institution = {Bureau of Meterology}, address = {Canberra}, abstract = {

Accurate soil dryness information is essential for the calculation of accurate fire danger ratings, fire behavior prediction, flood forecasting and landslip warnings. Soil dryness also strongly influences temperatures and heatwave development by controlling the partitioning of net surface radiation into sensible, latent and ground heat fluxes. Rainfall forecasts are crucial for many applications and many studies suggest that soil dryness can significantly influence rainfall. Currently, soil dryness for fire danger prediction in Australia is estimated using very simple water balance models developed in the 1960s that ignore many important factors such as incident solar radiation, soil types, vegetation height and root depth. This work presents a prototype high resolution soil moisture analysis system based around the Joint UK Land Environment System (JULES) land surface model. This prototype system is called the JULES based Australian Soil Moisture INformation (JASMIN) system. The JASMIN system can include data from many sources; such as surface observations of rainfall, temperature, dew-point temperature, wind speed, surface pressure as well as satellite derived measurements of rainfall, surface soil moisture, downward surface short-wave radiation, skin temperature, leaf area index and tree heights. The JASMIN system estimates soil moisture on four soil layers over the top 3 meters of soil, the surface layer has a thickness of 10 cm. The system takes into account the effect of different vegetation types, root depth, stomatal resistance and spatially varying soil texture. The analysis system has a one hour time-step with daily updating. For the surface soil layer, verification against ground based soil moisture observations from the OzNet, CosmOz and OzFlux networks shows that the JASMIN system is significantly more accurate than other soil moisture analysis system used at the Bureau of Meteorology. For the root-zone, the JASMIN system has similar skill to other commonly used soil moisture analysis systems. The Extended Triple Collocation (ETC) verification method also confirms the high skill of the JASMIN system.

}, keywords = {Fire behaviour, fire danger ratings, flood forecast, soil dryness}, issn = { Bureau Research Report {\textendash} BRR026}, url = {http://www.bom.gov.au/research/publications/researchreports/BRR-026.pdf}, author = {Imtiaz Dharssi and Vinod Kumar} } @article {BF-4267, title = {Uncertainty associated with model predictions of surface and crown fire rates of spread}, journal = {Environmental Modelling \& Software}, volume = {47}, year = {2013}, month = {2013}, pages = {16-28}, chapter = {16}, abstract = {The degree of accuracy in model predictions of rate of spread in wildland fires is dependent on the model{\textquoteright}s applicability to a given situation, the validity of the model{\textquoteright}s relationships, and the reliability of the model input data. On the basis of a compilation of 49 fire spread model evaluation datasets involving 1278 observations in seven different fuel type groups, the limits on the predictability of current operational models are examined. Only 3\% of the predictions (i.e. 35 out of 1278) were considered to be exact predictions according to the criteria used in this study. Mean percent error varied between 20 and 310\% and was homogeneous across fuel type groups. Slightly more than half of the evaluation datasets had mean errors between 51 and 75\%. Under-prediction bias was prevalent in 75\% of the 49 datasets analysed. A case is made for suggesting that a 35\% error interval (i.e. approximately one standard deviation) would constitute a reasonable standard for model performance in predicting a wildland fire{\textquoteright}s forward or heading rate of spread. We also found that empirical-based fire behaviour models developed from a solid foundation of field observations and well accepted functional forms adequately predicted rates of fire spread far outside of the bounds of the original dataset used in their development.}, keywords = {bushfire behaviour, bushfire spread, Fire behaviour, fire spread}, doi = {http://dx.doi.org/10.1016/j.envsoft.2013.04.004}, author = {Cruz, Miguel G. and Alexander, ME} } @article {BF-2070, title = {Computing forest fires aerial suppression effectiveness by IR monitoring}, journal = {Fire Safety Journal}, year = {2010}, month = {07/2010}, abstract = {This paper describes the methodology developed to analyse IR images obtained during the aerial suppression experiments that were conducted in Ngarkat Conservation Park, South Australia, on 3{\textendash}5 March 2008. This methodology has been specifically developed in order to extract the maximum information from the IR images taken from an observing helicopter, in those tests where chemical suppressants are applied directly on the fire, although it could eventually be applied to other similar situations. The information obtained after applying this methodology allows quantifying the aerial suppression effectiveness.}, keywords = {Airborne monitoring, Chemical suppressants drops, Fire behaviour, Mallee woodland, Project FuSE}, issn = {03797112}, doi = {10.1016/j.firesaf.2010.06.004}, author = {P{\'e}rez, Yolanda and Pastor, Elsa and Planas, Eul{\`a}lia and Matt P Plucinski and J.S. Gould} }