Search

Background: Wildfire propagation is inherently non-steady, although forecasts of their spread focus on a pseudo-steady state assumption. Aims: To investigate the variability in rate of fire spread of wildfires in southern Australian grassland landscapes, and the effect of landscape features in inhibiting fire propagation. To evaluate the adequacy of grassfire rate of spread models currently used in Australia. Methods: We reconstructed the propagation of six wildfires in grassland fuels and characterised the unsteady nature of rate of spread. We also analysed the effect of barriers to fire spread in slowing or halting wildfire propagation. Key results: Headfire rate of spread in wildfires was observed to be non-steady, with peaks in forward rate of spread being on average 2.6-times higher than mean values. The rate of spread had an average coefficient of variation of 88%. Areas of fuel discontinuity, such as roads, did not stop fires under moderate burning conditions, but resulted in slowing the average rate of fire spread. Conclusions: Analysis of wildfire observations is key to understand fire behaviour features that are not replicable in experimental or modelling environments. Findings from the analysis can support fire-fighting safety awareness and inform landscape fire propagation modelling. This study uses detailed wildfire observation data to describe non-steady headfire rate of spread and the effect of barriers to fire propagation, such as roads, on halting or inhibiting spread. We discuss the implications for wildfire spread modelling and fireline safety. [ABSTRACT FROM AUTHOR]

Background: Development of the Australian Fire Danger Rating System began in 2017 with a project aimed at demonstrating the feasibility of a new fire danger rating system through a Research Prototype (AFDRSRP) that accounted for variability in Australian vegetation types, was nationally applicable, modular and open to continuous improvement. Aims: In this manuscript, we identify and define transition points and categories for the AFDRSRP. We discuss user responses to the categorisation during a live trial evaluation of the AFDRSRP and reflect on limitations and potential improvements. Methods: A review of available literature, broad consultation with stakeholders and reanalysis of fire impact data were used to determine suitable thresholds for categorising fire danger within the AFDRSRP. Key results: Fire danger categories within the AFDRSRP reflect transitions in fire behaviour that result in application of different fire management strategies or are associated with variation in serious consequences and impacts. Conclusions: The AFDRSRP incorporated the best available science, supported by a well-defined framework for categorising and defining fire danger making it suitable for application across Australian fire jurisdictions and range of fuel types. Implications: The framework allows fire managers to assess the accuracy and appropriateness of forecasted fire danger. We identify and present defined categories and thresholds for the Australian Fire Danger Rating System: Research Prototype based on reflecting transitions in fire behaviour that result in application of different fire management strategies or associated with variation in potential for serious consequences and impacts. This article belongs to the Collection Australian Fire Danger Rating System. [ABSTRACT FROM AUTHOR]

Abstract: This paper describes the development of two empirical models to predict the potential spread of an established line of fire in dry eucalypt forest with a shrubby understorey. These models use inputs of fine fuel moisture, wind speed, near-surface fuel height, and either a numerical fuel hazard score or a descriptive fuel rating for the surface and near-surface fuel. A model to predict flame height from rate of spread and elevated fuel height is also presented as a guide to suppression difficulty. Models were developed using data from a series of simultaneous experimental fires in fuels of different fuel ages ranging from 2 to 22years since last fire. They were tested against data from independent experimental fires and well documented wildfires that were assigned reliability ratings for fuel, weather and spread rate. Models performed reliably when the reliability of wildfire data ratings for fuel and weather were also high. Models predict the potential rate of spread and are likely to over-predict the spread of fires starting from a point ignition during the early stages of development when the headfire is less than 120m wide. Existing guides should be used for prescribed burning operations based on point ignition, and the models described here can be used to predict rate of spread from line ignition. Predictions from the new models will be more reliable when rate of spread is averaged over an interval of 30min or longer. The reliability will be low when compared to observations made over short time intervals, at specific points in the topography, or when very large fires interact to produce wind speeds that are very different to the ambient wind in the open. [Copyright &y& Elsevier]

Abstract. 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. [ABSTRACT FROM AUTHOR]