@article {bnh-8338, title = {A guide to reconstructing cropland wildfires {\textendash} data collection, collation and analysis for case study construction}, number = {729}, year = {2022}, month = {04/2022}, institution = {Bushfire and Natural Hazards CRC}, address = {Melbourne}, abstract = {

This guide is intended to provide the fire behaviour analyst tasked with preparing a case study of a cropland wildfire with the basic set of methods, tools and information necessary to create a meaningful summary of the behaviour and spread of that fire. While the information and examples provided are specific to the case of wildfires burning in cropland fuels, the methods and tools are such that they can be applied to wildfires burning in any vegetation type given due consideration of the differences in the applicable factors and conditions.

This guide provides background information on the importance of undertaking case studies of wildfires, particularly across the broad range of wildfire types and intensities, for developing a case study library from which a large range of lessons may be learned{\textemdash}those immediately related to the incident itself but also those that may be gained from a perspective of time and space later.

A detailed discussion of fire behaviour in cropland fuels and the factors that affect fire perimeter shape and growth are discussed. The effects of suppression efforts, their effectiveness and likely impact on fire shape and spread are also discussed. Understanding the fuels and landscape features across which a cropland wildfire burns, in particular those non-crop fuels such as roadside verges and grazing paddocks, and their condition and state, are critical to interpreting observed fire behaviour and fire propagation across the landscape. Similarly, detailed information on the weather driving the wildfire is critical to understanding how and why a fire spread the way it did.\  These data can be divided into two groups{\textemdash}those that should be collected during the fire, such as observations of fire behaviour and spotting, and those that can be collected after the fire, such as fire progression and burnt area and crop status and distribution. Assessment of the reliability of the data collected for the purpose of compiling a case study is essential to providing context and informing assessment of dependability of data used for later analysis.

Finally, the guide provides suggestions for documenting the fire event, building the chronology and development of the incident, and writing a case study that is pithy and to the point. Checklists of essential information to be collected during and immediately after the fire (including sample fire spread observation forms), suggested observations to be collected from first attack personnel and prompter questions for when doing firefighter debriefs and interviews of eyewitnesses are also provided.

}, issn = {729}, author = {Sullivan, Andrew and Cruz, Miguel G. and Matt P Plucinski} } @proceedings {BF-4341, title = {National Fire Behaviour Knowledge Base- Bringing together the best information for best decisions}, year = {2013}, url = {http://www.bushfirecrc.com/resources/research-report/national-fire-behaviour-knowledge-base-bringing-together-best-information-}, author = {J.S. Gould and Sullivan, Andrew and Cruz, Miguel G. and Rucinski, Chris and Prakash, Mahesh} } @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-3466, title = {Anatomy of a catastrophic wildfire: The Black Saturday Kilmore East fire in Victoria, Australia}, journal = {Forest Ecology and Management}, year = {2012}, month = {8/2012}, abstract = {The 7 February 2009 wildfires in south-eastern Australia burned over 450,000 ha and resulted in 173 human fatalities. The Kilmore East fire was the most significant of these fires, burning 100,000 ha in less than 12 h and accounting for 70\% of the fatalities. We report on the weather conditions, fuels and propagation of this fire to gain insights into the physical processes involved in high intensity fire behaviour in eucalypt forests. Driven by a combination of exceedingly dry fuel and near-gale to gale force winds, the fire developed a dynamic of profuse short range spotting that resulted in rates of fire spread varying between 68 and 153 m min-1 and average fireline intensities up to 88,000 kW m-1. Strong winds aloft and the development of a strong convection plume led to the transport of firebrands over considerable distances causing the ignition of spotfires up to 33 km ahead of the main fire front. The passage of a wind change between 17:30 and 18:30 turned the approximately 55 km long eastern flank of the fire into a headfire. Spotting and mass fire behaviour associated with this wide front resulted in the development of a pyrocumulonimbus cloud that injected smoke and other combustion products into the lower stratosphere. The benchmark data collected in this case study will be invaluable for the evaluation of fire behaviour models. The study is also a source of real world data from which simulation studies investigating the impact of landscape fuel management on the propagation of fire under the most severe burning conditions can be undertaken.}, issn = {03781127}, doi = {10.1016/j.foreco.2012.02.035}, author = {Cruz, Miguel G. and Sullivan, Andrew and J.S. Gould and Sims, N.C. and Bannister, A.J. and Jennifer J Hollis and Hurley, R.J.} } @article {BF-3467, title = {Fire behaviour modelling in semi-arid mallee-heath shrublands of southern Australia}, journal = {Environmental Modelling \& Software}, year = {2012}, month = {8/2012}, abstract = {Knowledge of fire behaviour potential is necessary for proactive management of fire prone shrublands. Data from two experimental burning programs in mallee-heath shrublands in semi-arid southern Australia were used to develop models for the sustainability of fire spread, fire type, i.e., surface or crown fire, forward spread rate and flame height. The dataset comprised 61 fires burned under a wide range of weather conditions. Rates of fire spread and fireline intensity varied between 4 and 55 m min-1 and 735 and 17,200 kW m-1 respectively. Likelihood of sustained fire spread and active crown fire propagation were modelled using logistic regression analysis. Fire spread sustainability was primarily a function of litter fuel moisture content with wind speed having a secondary but still significant effect. The continuity of fine fuels close to ground level was also significant. Onset of active crowning was mostly determined by wind speed. Rate of fire spread was modelled separately for surface and crown fires through nonlinear regression analysis with wind speed, litter fuel moisture content and overstorey canopy cover as significant variables. Flame height was modelled as a function of fireline intensity. A model system to predict the full range of fire behaviour in mallee-heath shrubland is proposed relying on a combined method that links the surface and crown fire rate of spread models. This model system was evaluated against independent data from large scale prescribed burns and wildfires with encouraging results. The best models for fire-spread sustainability and active crown fire propagation predicted correctly 75\% and 79\% respectively of the fires in the evaluation dataset. Rate of spread models produced mean absolute percent errors between 53\% and 58\% with only small bias. The models have applicability in planning and conducting prescribed fire operations but can also be extended to produce first order predictions of wildfire behaviour.}, issn = {13648152}, doi = {10.1016/j.envsoft.2012.07.003}, author = {Cruz, Miguel G. and Lachlan W. McCaw and Wendy R. Anderson and J.S. Gould} } @article {BF-3088, title = {Behind the flaming zone: Predicting woody fuel consumption in eucalypt forest fires in southern Australia}, journal = {Forest Ecology and Management}, volume = {261}, year = {2011}, month = {6/2011}, pages = {2049 - 2067}, abstract = {Pre-fire woody fuel (diameter > 0.6 cm) structure and its consumption by fire were measured at experimental/prescribed fires and high intensity wildfires in eucalypt forests in southern Australia in order to better understand and model the dynamics of woody fuel consumption. Two approaches were used in model development: (1) a fire or plot level analysis, based on a dataset which includes the proportion of the pre-fire woody fuel load consumed at each fire; and (2) a stage level analysis, based on a dataset where woody fuel consumption was measured at a woody fuel particle level (i.e. pre-fire and post-fire diameter). For the plot level analysis a generalised linear model (GLM) approach identified the Forest Fire Danger Index (FFDI) as the best predictor of the proportion of woody fuel consumed, with an R2 of 0.58 and mean absolute error of 10\%. The stage level analysis recognised the various combustion stages through which a burning woody particle would pass, but failed to develop an accurate model that predicted the ignition, partial and full consumption of woody fuels based on fuel, fire behaviour and environmental variables. Analysis showed that consumption of woody fuel particles is highly variable and that variation in fire behaviour potentially has a greater impact on woody fuel consumption, than does variation in fuel characteristics (e.g. state of decay, fuel suspension and interactions with other fuel particles). The FFDI GLM provides forest and fire managers with a tool to manage woody fuel consumption objectives and may assist fire managers with forecasting post-frontal fire behaviour. The FFDI GLM may also assist forest and fire managers to better meet land management goals and to comply with air quality and emission targets.}, doi = {10.1016/j.foreco.2011.02.031}, author = {Jennifer J Hollis and Stuart Matthews and Wendy R. Anderson and Cruz, Miguel G. and Burrows, N.D.} } @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} } @article {BF-2793, title = {Project FuSE Aerial Suppression Final Report}, year = {2011}, institution = {CSIRO}, type = {Bushfire CRC Research Report}, abstract = {Three experimental fires were conducted to demonstrate the effectiveness of different fire suppression chemicals delivered by aircraft in March 2008. The fires were conducted in mallee heath fuels in Ngarkat Conservation Park, South Australia, at a site being used for an existing fuel and fire dynamics research project. Each fire was started from a long ignition line and allowed to fully develop before being attacked by suppression. The only suppression applied to these fires came from two single engine air tankers (Airtractor AT-802F) dropping a single suppressant type in each experiment. A water enhancing gel was directly applied to the fire edge in one experiment, while a foam suppressant was applied in another. The third experimental plot involved a fire burning into a pre-laid retardant line. The different suppression chemicals used in the experiments could not be directly compared. This was because the time taken for fire to burn through most of the drops could not be determined as they were breached by spotting or burnt around and because of the range of conditions experienced for the different drops. The aerial suppression experiments presented here allowed for the development and testing of aerial suppression assessment methodologies and have produced data that can be used to develop training material. This data highlights the importance of drop placement with regard to fire behaviour and location. Footage captured using a hand held airborne infrared camera in an aerial platform demonstrated some important aerial suppression tactical issues, such as drop coverage, drop accuracy and drop placement. Fire burning through one of the retardant drops highlighted the importance of adequate ground coverage levels for stopping fire propagation. }, url = {http://www.bushfirecrc.com/resources/research-report/project-fuse-aerial-suppression-final-report}, author = {Matt P Plucinski and Cruz, Miguel G. and J.S. Gould} } @article {BF-2466, title = {Assessing crown fire potential in coniferous forests of western North America: a critique of current approaches and recent simulation studies}, journal = {International Journal of Wildland Fire}, volume = {19}, year = {2010}, month = {2010}, pages = {377}, abstract = {To control and use wildland fires safely and effectively depends on creditable assessments of fire potential, including the propensity for crowning in conifer forests. Simulation studies that use certain fire modelling systems (i.e. NEXUS, FlamMap, FARSITE, FFE-FVS (Fire and Fuels Extension to the Forest Vegetation Simulator), Fuel Management Analyst (FMAPlus{\textregistered}), BehavePlus) based on separate implementations or direct integration of Rothermel{\textquoteright}s surface and crown rate of fire spread models with Van Wagner{\textquoteright}s crown fire transition and propagation models are shown to have a significant underprediction bias when used in assessing potential crown fire behaviour in conifer forests of western North America. The principal sources of this underprediction bias are shown to include: (i) incompatible model linkages; (ii) use of surface and crown fire rate of spread models that have an inherent underprediction bias; and (iii) reduction in crown fire rate of spread based on the use of unsubstantiated crown fraction burned functions. The use of uncalibrated custom fuel models to represent surface fuelbeds is a fourth potential source of bias. These sources are described and documented in detail based on comparisons with experimental fire and wildfire observations and on separate analyses of model components. The manner in which the two primary canopy fuel inputs influencing crown fire initiation (i.e. foliar moisture content and canopy base height) is handled in these simulation studies and the meaning of Scott and Reinhardt{\textquoteright}s two crown fire hazard indices are also critically examined.}, doi = {10.1071/WF08132}, author = {Cruz, Miguel G. and Alexander, ME} } @article {BF-2578, title = {Fire Dynamics in Mallee Heath Vegetation}, year = {2010}, author = {Cruz, Miguel G. and Stuart Matthews and J.S. Gould and Ellis, Peter and Henderson, M. K. and Knight, IK and Watters, J} } @conference {BF-2460, title = {Fuel and fire behaviour in semi-arid mallee-heath shrublands}, booktitle = { 6th International Forest Fire Research Conference}, year = {2010}, month = {November 2010}, publisher = {ADAI}, organization = {ADAI}, address = {Coimbra, Portugal}, abstract = {An experimental burning program was set up in South Australia aimed at characterizing fuel dynamics and fire behaviour in mallee-heath woodlands. Fuel complexes in the experimental area comprised mallee and heath vegetation with ages (time since fire) ranging from 7 to 50 years old. Dominant overstorey mallee vegetation comprised Eucalyptus calycogona, E. diversifolia, E. incrassate and E. leptophylla. A total of 66 fires were completed. The range of fire environment conditions within the experimental fire dataset were: air temperature 15 to 39{\textdegree}C; relative humidity 7 to 80\%; mean 10-m open wind speed 3.6 to 31.5 km/h; Forest Fire Danger Index 1.7 to 46. Total fuel load ranged from 0.38 kg/m2 in young (7-year old) mallee to 1.0 kg/m2 in mature stands. Fire behaviour measurements included rate of spread, flame geometry, residence time and fuel consumption. Measured rate of spread ranged between 0.8 and 55 m/min with fireline intensity between 144 and 11,000 kW/m. The dataset provided insight into the threshold environment conditions necessary for the development of a coherent flame front able to overcome the fine scale fuel discontinuities that characterise the semi-arid mallee-heath fuel types and support self-sustained fire propagation. The data also provided a better understanding of the variables determining the behaviour of selfsustained fires, including rate of fire spread, flame dimensions, crowning and spotting activity.}, isbn = {978-989-20-2157-7}, author = {Cruz, Miguel G. and J.S. Gould} } @article {BF-2465, title = {Monte Carlo-based ensemble method for prediction of grassland fire spread}, journal = {International Journal of Wildland Fire}, volume = {19}, year = {2010}, month = {2010}, pages = {521}, abstract = {The operational prediction of fire spread to support fire management operations relies on a deterministic approach where a single {\textquoteleft}best-guess{\textquoteright} forecast is produced from the best estimate of the environmental conditions driving the fire. Although fire can be considered a phenomenon of low predictability and the estimation of input conditions for fire behaviour models is fraught with uncertainty, no error component is associated with these forecasts. At best, users will derive an uncertainty bound to the model outputs based on their own personal experience. A simple ensemble method that considers the uncertainty in the estimation of model input values and Monte Carlo sampling was applied with a grassland fire-spread model to produce a probability density function of rate of spread. This probability density function was then used to describe the uncertainty in the fire behaviour prediction and to produce probability-based outputs. The method was applied to a grassland wildfire case study dataset. The ensemble method did not improve the general statistics describing model fit but provided complementary information describing the uncertainty associated with the predictions and a probabilistic output for the occurrence of threshold levels of fire behaviour.}, doi = {10.1071/WF08195}, author = {Cruz, Miguel G.} } @conference {BF-2461, title = {National Fire Behaviour Presiction System}, booktitle = {Biennial Conference of the Institute of Foresters of Australia, Caloundra, 2009}, year = {2010}, month = {2010}, publisher = {IFA}, organization = {IFA}, address = {Caloundra}, abstract = {The estimation of fire behaviour is an important component of any fire management approach, allowing the determination of the impacts of fire on ecosystem components and supporting forest fire management decision-making. Fire behaviour prediction combines quantitative and qualitative information based on experience and scientific principles of describing the combustion and behaviour of fire influence by topography, weather and fuel. Predictions are based on mathematical models that integrate important factors in a consistent way. The National Fire Behaviour Prediction (NFBP) system will consist of four primary components (fuel models, fuel moisture models, wind models, and fire behaviour models) to predict fire characteristics (e.g., rate of spread, flame height, fireline intensity, onset of crowning spotting potential, etc). This paper will focus on the fire behaviour component of the NFBP system. This component integrates a suite of models covering the main fuel types of Australia, eucalyptus forests, exotic pine plantations, grasslands, shrublands and Mallee-heath. The desired accomplishments of the proposed National Fire Behaviour Prediction Systems is to provide fire managers with better operating models to implement prescribed burning programs, suppression resources, risk and biodiversity management programs. The fuel type specificity of the fire models, its greater accuracy and updated calculation methods allow also for more accurate simulations of the impact of hypothetical climate change scenarios on fire potential and risk in Australia.}, author = {Cruz, Miguel G. and J.S. Gould} } @conference {BF-2462, title = {Field-based fire behaviour research: past and future roles}, booktitle = {MODSIM Congress}, year = {2009}, month = {2009}, url = {http://www.mssanz.org.au/modsim09/A4/cruz.pdf}, author = {Cruz, Miguel G. and J.S. Gould} } @article {BF-2379, title = {Development of fuel models for fire behaviour prediction in maritime pine ( Pinus pinaster Ait.) stands}, journal = {International Journal of Wildland Fire}, volume = {17}, year = {2008}, month = {2008}, pages = {194}, abstract = {A dataset of 42 experimental fires in maritime pine (Pinus pinaster Ait.) stands was used to develop fuel models to describe pine litter and understorey surface fuel complexes. A backtracking calibration procedure quantified the surface fuel bed characteristics that best explained the observed rate of fire spread. The study suggested the need for two distinct fuel models to adequately characterise the variability in fire behaviour in this fuel type. In these heterogeneous fuel beds the fuel models do not necessarily represent the inventoried average fuel conditions. Evaluation against the modelling data produced mean absolute errors of 0.8 and 0.6 m min{\textendash}1 in rate of spread, respectively, for the litter and understorey fuel models, with little evidence of bias. The fuel models predicted the rate of spread of a validation dataset with comparable error. Comparison of the behaviour and evaluation statistics produced by the study fuel models with fuel models developed from inventoried fuel data alone revealed an improvement on model performance for the current study approach for the litter fuel model and comparable behaviour for the understorey one. We examined model behaviour through comparative analysis with models used operationally to predict fire spread in pine stands. Large departures from model behaviour essentially occur when the models are exercised outside the range of the model development dataset. The discrepancies in predicted fire behaviour were hypothesised to arise not from differences in fuel complex structure but from the selected functional relationships that determine the effect of wind and fuel moisture on rate of spread. }, doi = {10.1071/WF07009}, author = {Cruz, Miguel G. and Fernandes, Paulo M.} } @proceedings {BF-2429, title = {Fuel dynamics and fire behaviour in Australian mallee and heath vegetation}, year = {2007}, url = {http://www.treesearch.fs.fed.us/pubs/28563}, author = {Myers, Juanita and J.S. Gould and Cruz, Miguel G. and Henderson, M. K.} } @article {BF-1004, title = {Evaluating a model for predicting active crown fire rate of spread using wildfire observations.}, journal = {Canadian Journal of Forest Research}, number = {36}, year = {2006}, month = {11/30/2006}, pages = {3015-3028}, url = {http://www.ingentaconnect.com/content/nrc/cjfr/2006/00000036/00000011/art00030}, author = {Alexander, ME and Cruz, Miguel G.} }