Matt P. Plucinski

Laboratory determination of factors influencing successful point ignition in the litter layer of shrubland vegetation

Factors affecting ignition thresholds of the litter layer of shrubland vegetation were investigated using reconstructed litter beds in a laboratory. The factors investigated were fuel moisture content (FMC), litter type (primarily species), pilot ignition source, and wind. Litter beds made from 11 different litter types were ignited with point ignition sources. Litter from Allocasuarina nana (Sieber ex Spreng.) L.A.S. Johnson was used as the standard type across all experiments. Successful ignition was defined as fire spreading a fixed distance from the ignition point. Ignition success was modelled as a logistic function of FMC. Litter type had a major effect on ignitibility. The bulk density of the litter bed and the surface area of litter per volume of litter bed provided reasonably good predictors of the effect of litter type on ignition success. Low-density litter beds ignited at higher FMCs than dense litter beds. The two densest litter beds failed to ignite with the procedures used here. The ignition sources tested had significantly different effects on ignition success. Larger ignition sources were able to ignite wetter fuels than smaller sources. The presence of wind was found to have a different effect on ignition success depending on the location of the ignition source with respect to the litter bed. Wind decreased ignition success when the ignition source was located on top of the litter bed, but aided ignition when the ignition source was located within the litter bed.

The effect of aerial suppression on the containment time of Australian wildfires estimated by fire management personnel

The addition of aerial firefighting resources to wildfire suppression operations does not always result in faster fire containment. In this paper, containment times of fires with aerial suppression are compared with estimated containment times for the same fires without aerial suppression. Senior firefighting personnel who had worked on each fire estimated whether fires could have been contained within a time class if aircraft were not available. Data from 251 wildfires were analysed based on four fire-containment time classes: ≤2, 2–4, 4–8 and 8–24 h from the start of initial attack. Aircraft were perceived to reduce time to containment when firefighting conditions were more challenging owing to fuel hazard rating, weather conditions, slope, resource response times and area burning at initial attack. Comparisons of containment time with and without aircraft can be used to develop operational tools to help dispatchers decide when aircraft should be deployed to newly detected fires.

The initiation of fire spread in shrubland fuels recreated in the laboratory

Fire-prone shrub-dominated vegetation communities cover a considerable portion of Australia, including areas fringing urban development. Near urban interfaces, they are actively managed with prescribed fire to reduce the risk of wildfire (unplanned fire). Knowledge of the range of conditions that allow fires to spread or fail to do so is limited and can inconvenience fire managers when conducting prescribed burns. A series of experimental ignitions conducted in miniature shrublands reconstructed in the laboratory were used to investigate factors that influence ignition thresholds. The miniature shrublands were composed of foliage from the shrub Allocasuarina nana and were prepared over a range of moisture contents and densities. The impact of dead fuel within the aerial structure of the shrubs was also investigated, as was the presence and absence of wind and litter. The most important factors for spread initiation were identified using logistic regression analysis and classification tree modelling. The presence of litter, live fuel moisture content, shrub-layer density, presence of wind, and the amount and continuity of the dead elevated fuel were all found to influence spread sustainability. There was a negative interaction between shrub-layer density and live fuel moisture content, showing the effect of density to be less at higher moisture contents.

Criteria and methodology for evaluating aerial wildfire suppression

Aircraft are often used to drop suppressants and retardants to assist wildfire containment. Drop effectiveness has rarely been measured due to the difficulties in collecting data from wildfires and running field experiments and the absence of definitions and measures. This paper presents a set of criteria and methodologies for evaluating the effectiveness of aerial suppression drops. These consider drop placement, coverage and effect on fire behaviour. This paper also details drop site and delivery conditions that are required for determining causal factors that influence drop effectiveness and allow drops to be compared. Examples of drop impact evaluations made during experimental fires are used to demonstrate these methodologies. The main methods proposed are based on the analysis of orthorectified airborne infrared imagery of drops, which can be used to measure drop dimensions, proximity to fire perimeter and their effect on fire spread. These evaluations can be used to compare tactics, suppressants and delivery systems and to inform cost-benefit analyses of aerial suppression.

A downslope fire spread correction factor based on landscape-scale fire behaviour

There is currently no fundamental understanding of the effects of topography on the behaviour of fires burning over a landscape. While a number of empirical models are employed operationally around the world, the effects of negative slopes on fire spread are ignored in all but one prediction system which may result in incorrect predictions. The general observation that large fires burning for some time over undulating topography can be approximated by assuming fire spread over flat ground is used to construct a quasi-empirical model framework for downslope rate of spread correction called kataburn. Kataburn is formulated for two alternative interpretations of slope spread-planar and linear-and can be applied to any empirical upslope spread correction model. Versions of kataburn derived using such models from Australia, the US and Canada are compared against experimental downslope data from the literature and found to better represent downslope spread than the existing operational downslope function. Topography has a significant effect on the spread of fire across the landscape.Appropriate treatment of negative (lee) slope fire spread effects is important.A new model framework, kataburn, is developed from functional considerations of fire spread across the landscape.Kataburn can be used to construct negative slope spread corrections for any fire spread prediction system.Kataburn is shown to perform much better than the only existing operational downslope model.

Improving the reliability and utility of operational bushfire behaviour predictions in Australian vegetation

Fire behaviour and spread predictions guides suppression strategies and public warnings during wildfires. The scientific understanding of fire behaviour forms the core of these predictions, but is incomplete, and expert judgement and experience are required to augment the evidence based knowledge. Amicus is a new decision support system that implements contemporary, published and operationalised bushfire behaviour models (e.g. rate of spread, flame height, fireline intensity, spotting distance) in the Australian bushfire context. It enables the inclusion of expert judgement and local knowledge, allows users to analyse temporal trends and uncertainty in inputs, and facilitates reliable and practical predictions. This paper provides a comprehensive overview of Amicus, including its operation and functionality, identifies the boundaries of the current understanding of fire science, discusses the major limitations in existing knowledge, and provides a framework for allowing deterministic and anecdotal/local knowledge to be incorporated into formal fire behaviour predictions. Fire behaviour predictions inform suppression strategies and public warnings.Expert judgement and experience can augment fire science.Amicus combines science and expert knowledge for robust transparent predictions.Amicus highlights operational domains and the limits of model reliability.Users can investigate the impact of uncertainty in input data on outputs.

Predicting the number of daily human-caused bushfires to assist suppression planning in south-west Western Australia

Data from bushfire incidents in south-west Western Australia from the Departments of Parks and Wildlife and Fire and Emergency Services were used to develop models that predict the number of human-caused bushfires within 10 management areas. Fire incident data were compiled with weather variables, binary classifications of day types (e.g. school days) and counts of the number of fires that occurred over recent days. Models were developed using negative binomial regression with a dataset covering 3 years and evaluated using data from an independent year. A common model form that included variables relating to fuel moisture content, the number of recent human-caused bushfires, work day (binary classification separating weekends and public holidays from other days) and rainfall was applied to all areas. The model had reasonable fit statistics across all management areas, but showed enough day-to-day prediction variability to be of practical use only in the more densely populated management areas, which were dominated by deliberate ignitions. The findings of this study should be of interest to fire managers in Mediterranean climatic regions where a variety of practices are used to manage wildfires.

Got to burn to learn: the effect of fuel load on grassland fire behaviour and its management implications

The effect of grass fuel load on fire behaviour and fire danger has been a contentious issue for some time in Australia. Existing operational models have placed different emphases on the effect of fuel load on model outputs, which has created uncertainty in the operational assessment of fire potential and has led to end-user and public distrust of model outcomes. A field-based experimental burning program was conducted to quantify the effect of fuel load on headfire rate of spread and other fire behaviour characteristics in grasslands. A total of 58 experimental fires conducted at six sites across eastern Australia were analysed. We found an inverse relationship between fuel load and the rate of spread in grasslands, which is contrary to current, untested, modelling assumptions. This result is valid for grasslands where fuel load is not a limiting factor for fire propagation. We discuss the reasons for this effect and model it to produce a fuel load effect function that can be applied to operational grassfire spread models used in Australia. We also analyse the effect of fuel load on flame characteristics and develop a model for flame height as a function of rate of fire spread and fuel load.