@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} } @conference {bnh-2931, title = {Effect of prescribed burning on wildfire severity - a landscape case study from the 2003 fires in Victoria}, booktitle = {AFAC16}, year = {2016}, month = {08/2016}, publisher = {Bushfire and Natural Hazards CRC}, organization = {Bushfire and Natural Hazards CRC}, address = {Brisbane}, abstract = {

This study examined the effect of previous fuel reduction burning (FRB) on the severity of the 1 million ha+ 2003 Alpine Fire in eastern Victoria, which was one of the most extensive and severe fires to have occurred in south-eastern Australia in the preceding century. Over one million hectares of largely forests, woodlands and alpine vegetation was burnt in January and February 2003 in the state of Victoria, and another contiguous 600,000 ha was burnt in New South Wales and the Australian Capital Territory, making these the most extensive fires in the area since 1939.


Some of the unusual features of this fire were that it burnt a large contiguous area stretching 180 km from east to west and 110 km from north to south in Victoria, and it burnt over a full two-month period. The size of the fire and the severity of the seasonal conditions (Bureau of Meteorology 2003) meant that about 49 per cent of the area burnt resulted in complete overstorey canopy removal, either through crown fire or scorching and resultant leaf loss. Very few areas remained unburnt within the perimeter of the fire. As the burnt area contained 100+ recent fuel reduction burns and wildfires (last 10 years, Fig. 1), this posed a rare opportunity to assess the effectiveness of prescribed burning on such a large scale and subjected to such high-intensity fires.

}, author = {Tolhurst, K.G. and G.J. McCarthy} } @conference {bnh-2932, title = {Wind speed reduction induced by post-fire vegetation regrowth}, booktitle = {AFAC16}, year = {2016}, month = {08/2016}, publisher = {Bushfire and Natural Hazards CRC}, organization = {Bushfire and Natural Hazards CRC}, address = {Brisbane}, abstract = {

In the current suite of operational fire spread models, wind speeds measured in the open environment (above the vegetation layer) are modified to represent wind speeds at {\textquoteleft}mid-flame{\textquoteright} height using adjustment factors. In general, these adjustment factors assume constant vertical wind speed profiles throughout the vegetation layer. However, empirical studies have shown that wind speeds beneath canopies can vary significantly with height above ground as well as with forest type and prevailing wind speed. Empirical wind reduction profiles have been developed for a number of different forest types in flat terrain using data collected across Victoria, Australia.


The present research aims to extend these empirical studies to better understand the impacts of topography and post-fire vegetation regrowth on the reduction of wind speeds beneath the canopy. Wind data collected over fire affected regions of rugged terrain in South Eastern Australia are used to analyse wind speed reduction induced by post-fire regrowth and complex topography. A secondary study is used to analyse wind speed reduction caused by Radiata pine plantation in undulating terrain.


Results of this study suggest that empirical wind reduction profiles perform well at the broader landscape-scale, i.e. ridge tops and valley floors. However, more complex topographical features appear to have a compounding affect on wind speed reduction within rugged terrain. Through better understanding of wind speed reduction beneath the canopy across landscapes from mountainous ranges through to flat plains, wind speed reduction models for bushfire spread prediction can be adapted to incorporate the variation observed in vertical wind speed profiles within the vegetation layer.

}, author = {Rachael Quill and Kangmin Moon and Jason J. Sharples and Leesa Sidhu and Thomas Duff and Tolhurst, K.G.} } @article {bnh-1843, title = {Erratum to {\textquotedblleft}Using discrete event simulation cellular automata models to determine multi-mode travel times and routes of terrestrial suppression resources to wildland fires"}, journal = {European Journal of Operational Research}, volume = {245}, year = {2015}, month = {08/2015}, pages = {339-340}, chapter = {339}, abstract = {

Forest fires can impose substantial social, environmental and economic burdens on the communities on which they impact. Well managed and timely fire suppression can demonstrably reduce the area burnt and minimise consequent losses. In order to effectively coordinate emergency vehicles for fire suppression, it is important to have an understanding of the time that elapses between vehicle dispatch and arrival at a fire. Forest fires can occur in remote locations that are not necessarily directly accessible by road. Consequently estimations of vehicular travel time may need to consider both on and off road travel. We introduce and demonstrate a novel framework for estimating travel times and determining optimal travel routes for vehicles travelling from bases to forest fires where both on and off road travel may be necessary. A grid based, cost-distance approach was utilised, where a travel time surface was computed indicating travel time from the reported fire location. Times were calculated using a discrete event simulation cellular automata (CA) model, with the CA progressing outwards from the fire location. Optimal fastest travel paths were computed by recognising chains of parent{\textendash}child relationships. Our results achieved comparable results to traditional network analysis techniques when considering travel along roads; however the method was also demonstrated to be effective in estimating travel times and optimal routes in complex terrain.

}, doi = {doi:10.1016/j.ejor.2015.03.025}, url = {http://www.sciencedirect.com/science/article/pii/S0377221715002325}, author = {Thomas Duff and Chong, Derek and Tolhurst, K.G.} } @article {bnh-1841, title = {Using discrete event simulation cellular automata models to determine multi-mode travel times and routes of terrestrial suppression resources to wildland fires}, journal = {European Journal of Operational Research}, volume = {241}, year = {2015}, month = {03/2015}, pages = {763-770}, chapter = {763}, abstract = {

Forest fires can impose substantial social, environmental and economic burdens on the communities on which they impact. Well managed and timely fire suppression can demonstrably reduce the area burnt and minimise consequent losses. In order to effectively coordinate emergency vehicles for fire suppression, it is important to have an understanding of the time that elapses between vehicle dispatch and arrival at a fire. Forest fires can occur in remote locations that are not necessarily directly accessible by road. Consequently estimations of vehicular travel time may need to consider both on and off road travel. We introduce and demonstrate a novel framework for estimating travel times and determining optimal travel routes for vehicles travelling from bases to forest fires where both on and off road travel may be necessary. A grid based, cost-distance approach was utilised, where a travel time surface was computed indicating travel time from the reported fire location. Times were calculated using a discrete event simulation cellular automata (CA) model, with the CA progressing outwards from the fire location. Optimal fastest travel paths were computed by recognising chains of parent{\textendash}child relationships. Our results achieved comparable results to traditional network analysis techniques when considering travel along roads; however the method was also demonstrated to be effective in estimating travel times and optimal routes in complex terrain.

}, keywords = {Transport; Network; environment and climate change; Routing; Simulation}, doi = {doi:10.1016/j.ejor.2014.09.019}, url = {http://www.sciencedirect.com/science/article/pii/S0377221714007401}, author = {Thomas Duff and Chong, Derek and Tolhurst, K.G.} } @article {BF-4281, title = {Quantifying spatio-temporal differences between fire shapes: Estimating fire travel paths for the improvement of dynamic spread models}, journal = {Environmental Modelling \& Software}, volume = {46}, year = {2013}, month = {08/2013}, pages = {33-43}, chapter = {33}, abstract = {Dynamic fire spread models are a recent development in landscape management that provide for the simulation of the spread of fires through time under complex weather conditions. These allow risks to be assessed and resources to be strategically managed. The need for reliable and accurate fire models is of particular importance in the face of recent catastrophic wildfires in Australia, Europe and the United States. However, while fire spread models are developed using physical knowledge and empirical observations, there are few techniques which can be used to objectively assess the {\textquoteleft}goodness of fit{\textquoteright} of spatial predictions of fire spread. We propose a new method to allow the comparison of fire perimeters, providing for the discrimination of sources of simulation error and assisting in the collection of empirical spread data from observed fires. Differences between fire perimeters are quantified using linear vectors aligned with the direction of spread of the perimeter being sampled. These can provide an indication of difference in terms of the fire spread distance on the ground. The location, direction and length of these vectors can be used to assess spread rates to assist with model calibration. We demonstrated the utility of this method using a case study which assessed differences between the observed and simulated progression of an Australian wildfire. The new indices were found to be effective descriptors of differences in fire shape and hold potential for the spatial evaluation of fire spread models. The indices can be used to compare similar fire shapes; however they are unsuited for cases where there are large differences between perimeters.}, keywords = {Bushfire, Morphometrics, Perimeter, Shape analysis, Spatial validation, Wildfire}, doi = {http://dx.doi.org/10.1016/j.envsoft.2013.02.005}, url = {http://www.sciencedirect.com/science/article/pii/S1364815213000455}, author = {Thomas Duff and Chong, Derek and Tolhurst, K.G.} } @article {BF-4295, title = {Sensitivity Analysis of PHOENIX RapidFire}, year = {2013}, month = {05/2013}, abstract = {An analysis of the sensitivity of the outputs of PHOENIX Rapidfire (PHOENIX) to a range of inputs and simulation parameters was undertaken. This was done using two separate methods; assessment of model response in an artificially generated idealised landscape and assessment using case-studies of real fires. The ideal landscape was used to evaluate model sensitivity in response to temperature, relative humidity, wind speed, fuel type and wind direction relative to slope. The model was evaluated under two sets of weather conditions, mild (representing moderate fire spread potential) and extreme (representing high fire spread potential). Each scenario was evaluated for each of two fuel types, forest and grass. Sensitivity was evaluated in terms of the gross area burnt when the input of interest was systematically changed while all other inputs were held constant. For all evaluations except relative wind direction, model sensitivities were compared to an equivalent area burnt using the corresponding McArthur Forest or grassland fire danger meter (assuming an elliptical fire shape). The combination of wind direction and slope resulted in simulated fires that were not elliptical, so comparisons with shapes generated with the fire danger meters were not valid. PHOENIX predictions differed from those generated using point estimates for some circumstances; however without further investigation it is unclear on what is causing these differences. Differences in predictive performance are not necessarily representative of model error, as there are a number of differing assumptions between the systems used. However, specific situations have been flagged for follow up work. Two case study areas were used for PHOENIX model sensitivity evaluation; Wangary and Kilmore. Case study fires were simulated using observations from the day that the fires occurred with one input systematically varied. Three inputs were evaluated using the case studies; simulation resolution, start time (simulating fire ignition to occur earlier and later than observed) and start location (varying the ignition location in space). Sensitivity was evaluated by considering the change in the Area Difference Index (ADI, an index of the ratio between incorrectly predicted burnt area and the correctly predicted burnt area) from the baseline scenario (simulation resolution of 180m, ignition location and time as observed. Predictive performance varied wide with changing inputs. In general as the difference in input value to the {\textquoteleft}best estimate{\textquoteright} increased, predictive performance degraded.}, author = {Chong, Derek and Tolhurst, K.G. and Thomas Duff and Brett Cirulis} } @article {BF-4292, title = {Evaluation of weather data at different spatial and temporal scales on fire behaviour prediction using PHOENIX RapidFire 4.0 - Kilmore Case Study}, year = {2012}, abstract = {High resolution models might be expected to produce more accurate predictions, but in the case of weather forecasting data used to predict the spread of the 2009 Kilmore fire, this was not found to be true. Current weather forecasts are available on a 3600 m grid at hourly intervals. In time, computing power will enable finer spatial and temporal forecast weather to be produced operationally. This study was undertaken to understand what benefit finer scaled data might be to fire spread prediction. PHOENIX RapidFire was used to model the 2009 Kilmore fire with different spatial and temporal weather inputs. Because the fire of this size interacts with the local weather, it was found that courser level weather inputs performed better than very fine resolution data. Overall, weather forecasts at 30 minutes intervals and 1200 m spacing provided the best inputs for matching the progression of the fire. Once the fire had reached about 100,000 ha, 60 minute, 3600 m data gave the best predictions. Modelling weather at 400 m resolutions and at 5 minute intervals provides good insights into the dynamics of the weather which assists a weather forecaster, but that additional detail is not of the same benefit to fire spread predictions because large fires "smooth" the weather, terrain and fuel in the landscape. More case-studies need to be undertaken, including smaller fires burning under milder conditions to better understand the relationship between weather data scale and fire spread prediction.}, author = {Chong, Derek and Thomas Duff and Tolhurst, K.G.} } @article {BF-4291, title = {Incorporating Vertical Winds into PHOENIX RapidFire{\textquoteright}s Ember Dispersal Model}, year = {2012}, month = {12/2012}, abstract = {PHOENIX RapidFire is a fire simulation model developed in Australia as part of the Bushfire CRC. One unique aspect of the modelling process is the way spotfires are modelled and incorporated into fire spread. Part of the spotting process requires modelling of ember release, transport and spotfire ignition. In the first iteration of spotfire modelling, surface wind (10 m in the open) was used to estimate the distance and spread of embers falling ahead of a fire. However, it is acknowledged that upper-winds usually differ in speed and direction from surface winds. It was therefore thought that that fire modelling could be improved by using the wind speed and direction data produced by the numerical weather prediction models. PHOENIX was modified to incorporate multi-level wind data, however, the forecast data had an uncorrected bias that results in incorrect ember transport modelling results. The lack of systematic, high resolution and comprehensive upper-wind observations makes bias correction and fire model testing impossible at the current time. It was therefore not possible to develop an improved ember transport model for PHOENIX. This report describes the process and results obtained from this research. In the end, a version of PHOENIX that can use a single layer of upper-wind data as input was developed. This will allow some theoretical testing of PHOENIX, but cannot be used for operational fire predictions with the currently available data.}, author = {Chong, Derek and Tolhurst, K.G. and Thomas Duff} } @article {BF-4294, title = {PHOENIX RapidFire 4.0 Convection and Ember Dispersal Model}, year = {2012}, month = {12/2012}, abstract = { PHOENIX RapidFire is unique in the way it models and incorporates the spotting process in bushfires. There are three main components to the spotting process modelled: lofting, transport, and spotfire ignition. The method of modelling these three processes is described. Lofting is related to the convective strength of the fire and the amount of available ember material, transport is related to wind speed and direction, and spotfire ignition is related to the available fine fuel on the ground and its moisture content. An absence of reliable ember transport and spotfire data has necessitated an empirical approach using the Black Saturday fires in Victoria for model development. As a result, there may be some aspects of the spotting process not well captured in PHOENIX, but to date, the results on new fires have been encouraging. The effective rate of spread of bushfires can be a factor of two or three times greater if the spotting process is well developed compared with a fire, burning under generally similar conditions, but without spotting contributing to the effective rate of spread. Being able to effectively model the spotting process has dramatically increased our ability to model bushfires in eucalypt forests. Modelling the conditions associated with the spotting process has also improved our ability to model potential house loss.}, author = {Chong, Derek and Tolhurst, K.G. and Thomas Duff} } @article {BF-4293, title = {PHOENIX RapidFire 4.0{\textquoteright}s Convective Plume Model}, year = {2012}, month = {12/2012}, abstract = {Bushfires are a 3-dimensional phenomenon with significant interaction between the surface and the atmosphere. Complex coupled fire-atmosphere models have been produced and give amazingly realistic results, however the computational complexity means that they take many times real-time to run, even on super computers, and are therefore restricted to small areas and short periods of time. PHOENIX RapidFire is primarily a 2-dimensional fire model and only takes a few minutes to run fires in excess of 100,000 ha. This report describes how PHOENIX RapidFire has been developed to include elements of plume development and ember transport resulting in spot fires. This was done to try and capture some of the important 3-dimensional aspects of bushfires without large computational overheads. Development of the plume rise and spotting components of PHOENIX has been done with the knowledge of some of the key thermodynamic processes, but a number of assumptions have been made. Validation of the plume rise and spotting model is difficult because there are no detailed observations recorded for the plume, embers, spotfires and upper-level winds. Ground-based weather radar data was found to be a useful validation dataset for the plume model. The plume model in PHOENIX was calibrated against weather radar data recorded on Black Saturday, 2009. Early indications are that there has been a significant improvement in the simulation of the Black Saturday fires with the incorporation of the plume and spotting models. Further testing will be required to fully understand the limitations of the model.}, author = {Chong, Derek and Tolhurst, K.G. and Thomas Duff} } @article {BF-3174, title = {Procrustes based metrics for spatial validation and calibration of two-dimensional perimeter spread models: A case study considering fire}, journal = {Agricultural and Forest Meteorology}, volume = {160}, year = {2012}, month = {7/2012}, pages = {110 - 117}, abstract = {A number of phenomena in natural systems exhibit spread from a point source facilitated by a transport vector. Such occurrences are an important focus of landscape management, and include fires, wind driven disease and pollutant spills. Two-dimensional dynamic spread models are used to simulate the impacts of such events, determine risks and optimise responses. These models produce spatially coherent outputs that are not easily verified through traditional regression approaches. Validation of predictions is an essential part of model development and is necessary for the improvement of predictive performance. Current methods of evaluation are rarely systematic and are typically undertaken through subjective comparison of simulation outputs with observed features. There are few methods suitable for the objective analysis of freeform spread patterns, and it is proposed that a pseudo-landmark approach be adopted to allow the use of landmark based analysis methods. Vector driven spread patterns exhibit a degree of spatial structure, with distinct origin points and elongate shapes resulting from the predominant vector trajectory. These can be used as references to generate analogous landmarks for perimeter comparison. To describe differences, three indices derived from Procrustes analysis are proposed. These provide metrics to evaluate differences in perimeter orientation, size and shape. A case study simulating wildfire spread was used to demonstrate the proposed methodology. It was found to be effective for the description of perimeter differences and has potential for the validation and calibration of spread models. A number of assumptions were recognised and limitations in assigning pseudo-landmarks considered.}, issn = {01681923}, doi = {10.1016/j.agrformet.2012.03.002}, author = {Thomas Duff and Chong, Derek and Peter Taylor and Tolhurst, K.G.} } @proceedings {BF-3042, title = {Assessing Potential House Losses Using PHOENIX RapidFire}, year = {2011}, month = {2011}, publisher = {Bushfire CRC}, address = {Sydney, Australia}, issn = {978-0-9806759-9-3}, url = {http://www.bushfirecrc.com/resources/pages-74-86-assessing-potential-house-losses}, author = {Tolhurst, K.G. and Chong, Derek} } @article {BF-3087, title = {The Effect of Fireline Intensity on Woody Fuel Consumption in Southern Australian Eucalypt Forest Fires}, journal = {Australian Forestry}, volume = {74}, year = {2011}, pages = {81-96}, abstract = {The relationship between woody fuel consumption and fireline intensity was assessed using data collected at controlled fires and wildfires in south-western Western Australia, central Victoria and south-eastern New South Wales. The combined dataset consisted of fires in a range of dry eucalypt forests. Fire behaviour varied from slow, self-extinguishing prescribed burns to intense, fast-moving fires burning under conditions of extreme fire danger. Fireline intensity ranged from 50 kW m-1 to > 31 000 kW m-1. Woody fuel consumption ranged from 31\% to 100\%, and generally increased with fire intensity. Percentage consumption was highest for small woody fuels where the diameter was between 0.6 cm and 2.5 cm. Fireline intensity had a statistically significant, positive relationship with the proportion of woody fuel consumed by both controlled fires and wildfires. Two generalised linear models (GLM) describing woody fuel consumption as a function of fireline intensity were developed, one applicable to the prescribed fire environment (with fireline intensities typically < 750 kW m-1) and the other to the full range of fireline intensities. The prescribed burning model produced the best fit and lowest error statistics. The findings of this research have important practical implications for the management of fire to reduce fuel loads, maintain habitat and manage carbon stocks in fire-prone eucalypt forests. The woody fuel consumption models presented may assist the assessment of potential climate change impacts on coarse woody debris in Australian southern eucalypt forests. The results of this research suggest that predicted changes to fire regimes and fire intensity associated with climate change in southern Australia could result in greater woody fuel consumption and carbon release during bushfires and a reduction in woody fuel loads in dry eucalypt forests. Use of low-intensity prescribed fires may provide a practical way of managing woody fuel stocks to achieve particular land management objectives.}, url = {http://search.informit.com.au/documentSummary;dn=365294696940897;res=IELHSS}, author = {Jennifer J Hollis and Wendy R. Anderson and Lachlan W. McCaw and Cruz, Miguel G. and Burrows, N.D. and Ward, B. and Tolhurst, K.G. and J.S. Gould} } @proceedings {BF-3092, title = {Assessing woody fuel consumption models for application in Australian forest fires}, year = {2010}, author = {Jennifer J Hollis and Stuart Matthews and Ottmar, R.D. and S.J. Prichard and Slijepcevic, A. and Burrows, N.D. and Ward, B. and Tolhurst, K.G. and Wendy R. Anderson and J.S. Gould} } @article {BF-2410, title = {Sampling downed coarse woody debris in fire-prone eucalypt woodlands}, journal = {Forest Ecology and Management}, volume = {259}, year = {2010}, month = {01/2010}, pages = {440 - 445}, abstract = {Downed coarse woody debris (DCWD) plays an important role in ecosystem processes and should be considered in land management decisions. Unfortunately accurate quantification of its abundance is difficult, due to its patchy distribution. This is especially problematic in woodland ecosystems where DCWD is relatively scarce, unevenly distributed and smaller in size than in other forest types. This study compared the efficacy of the line intersect and strip plot methods to sample properties of DCWD at woodland sites with differing fire histories. Although measures of abundance using the two methods did not differ statistically, the line intersect method had 20\% less variability in the data, was quicker to perform and made it easier to locate individual pieces of DCWD than the strip plot method. The results of this study indicate that transects of 100 m or less are insufficient for estimating DCWD volume in woodlands. An acceptable level of precision was reached at approximately 450 m at very recently burnt sites and 700 m at long unburnt sites when only transect length was considered. However when taking both transect length and number of replicates into account, an acceptable level of precision was reached at 500 m when sampling a minimum of 20 sites. It is therefore recommended that pilot studies should be conducted to determine appropriate sampling intensities in previously unsampled areas as DCWD volume estimates are sensitive to the rate at which variance changes with increasing transect length. This is particularly important when there is variation in the disturbance history of the sites. However, if it is not possible to conduct pilot studies, the requirement would be to sample line intersect transects of at least 500 m, at a minimum of 20 sites in woodland systems.}, doi = {10.1016/j.foreco.2009.10.041}, author = {Miehs, Anne and York, Alan and Tolhurst, K.G. and Di Stefano, J and Bell, Tina} } @article {BF-2582, title = {Testing woody fuel consumption models for application in Australian southern eucalypt forest fires}, journal = {Forest Ecology and Management}, volume = {260}, year = {2010}, month = {08/2010}, pages = {948 - 964}, abstract = {Five models for the consumption of coarse woody debris or woody fuels with a diameter larger than 0.6 cm were assessed for application in Australian southern eucalypt forest fires including: CONSUME models for (1) activity fuels, (2) natural western woody and (3) natural southern woody fuels, (4) the BURNUP model and (5) the recommendation by the Australian National Carbon Accounting System which assumes 50\% woody fuel consumption. These models were assessed using field data collected as part of the woody fuel consumption project (WFCP) in south-west Western Australia and northern-central Victoria. Three additional datasets were also sourced to increase variability in forest type, fuel complex and fire characteristics. These datasets comprised data from south-west Western Australia collected as part of Project Aquarius, the Warra Long Term Ecological Research site in Tasmania and Tumbarumba in south-eastern New South Wales. Combined the dataset represents a range of fire behaviour characteristic of prescribed burning conditions with a maximum fireline intensity of almost 4000 kW m-1. Woody fuel consumption was found to be highly variable between sites ranging from 9.1\% to 89.9\%. Relationships between woody fuel consumption and the primary model drivers were weak (maximum R2 = 0.097). Model evaluation statistics were best for the National Carbon Accounting Systems assumption of 50\% with a mean absolute error of 11.1\% fuel consumption and minimal bias (0.12). Nonetheless, this assumption does not capture large deviations where woody fuel consumption has been particularly high or low. The BURNUP model yielded the largest level of error when used with natural fuels however its predictive capacity improved when used with large modified fuel loads resulting from clearcut operations.}, doi = {10.1016/j.foreco.2010.06.007}, author = {Jennifer J Hollis and Stuart Matthews and Ottmar, R.D. and S.J. Prichard and Slijepcevic, A. and Burrows, N.D. and Ward, B. and Tolhurst, K.G. and Wendy R. Anderson and J.S. Gould} } @article {BF-2350, title = {Woody fuel consumption experiments in an undisturbed forest}, journal = {Forest Ecology and Management}, volume = {234}, year = {2006}, month = {11/2006}, pages = {S109 - S109}, doi = {10.1016/j.foreco.2006.08.145}, author = {Tolhurst, K.G. and Wendy R. Anderson and J.S. Gould} }