University of Wollongong Research Online University of Wollongong Thesis Collection 2017+ University of Wollongong Thesis Collections 2018 Fire prevention treatments to mitigate wildfire risk Kathryn May Collins University of Wollongong Follow this and additional works at: https://ro.uow.edu.au/theses1 University of Wollongong Copyright Warning You may print or download ONE copy of this document for the purpose of your own research or study. The University does not authorise you to copy, communicate or otherwise make available electronically to any other person any copyright material contained on this site. You are reminded of the following: This work is copyright. Apart from any use permitted under the Copyright Act 1968, no part of this work may be reproduced by any process, nor may any other exclusive right be exercised, without the permission of the author. Copyright owners are entitled to take legal action against persons who infringe their copyright. 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For further information contact the UOW Library: [email protected] Fire prevention treatments to mitigate wildfire risk Kathryn May Collins Supervisors Dr Owen Price, University of Wollongong A/Prof Trent Penman, University of Melbourne This thesis is presented as part of the requirement for the conferral of the degree: Doctor of Philosophy This research has been conducted with the support of the Australian Government Research Training Program Scholarship The University of Wollongong School of Biological Sciences November 2018 Abstract Wildfires can have devastating impacts on life, property and the environment. Increasingly people are living in areas that place them at risk from wildfires. Fire management agencies use a range of strategies to reduce wildfire risk. The aim of this thesis was to investigate the effectiveness of fire prevention and response treatments to mitigate wildfire risk in south- eastern Australia. This was achieved by (i) investigating the drivers of ignitions and the relationship between social and biophysical variables on the probability of ignition; (ii) determining if ignitions are equal or whether some ignition causes pose more risk than others; (iii) investigating the factors that influence the containment of wildfires; and (iv) determining the relative effectiveness of mitigation and response strategies to mitigate the risk of house losses. The spatial patterns of wildfire ignitions were investigated at a bioregional scale in New South Wales and Victoria using generalised linear models and a combination of social and biophysical variables. Human-caused ignitions are the dominant source of ignitions for wildfires in south-eastern Australia. The number of accidental and deliberate ignitions increased with increasing population density and decreasing mean elevation. Lightning ignition probability increased as the number of hot days and mean elevation decreased which reflects that fewer lightning ignitions occurred in the western arid and semiarid areas. In future years, more ignitions are predicted in the coastal and hinterland areas due to population increases and climate change effects. A dataset of wildfires that destroyed houses in New South Wales and Victoria was compiled to determine which ignition causes are more likely to result in destroyed houses and whether there are associated weather conditions that increase the probability of a destroyed house. Powerlines, lightning and deliberate ignitions are the main causes of wildfires that destroyed houses. Fire weather was an important driver for deliberate- and powerline-caused wildfires that destroyed houses with temperature, wind speed and forest fire danger index all significantly higher and relative humidity significantly lower (P < 0.05) on the day of ignition for wildfires that destroyed houses compared with wildfires where no houses were destroyed. For all powerline-caused wildfires the first house destroyed always occurred on the day of ignition. In contrast, the first house destroyed was after the day of ignition for 78% of lightning- ii caused wildfires. Lightning-caused wildfires that destroyed houses were significantly larger (P < 0.001) in area than human-caused wildfires that destroyed houses. Targeting fire prevention strategies around ignition causes, such as improving powerline safety and arson reduction programmes, and fuel reduction treatments may decrease the number of wildfires that destroy houses. Over 2200 forest and 4600 grass fires in New South Wales were investigated to determine the dominant influences on the containment of wildfires. A random forest modelling approach was used to analyse the effect of a range of human and environmental factors. The number of suppression resources per area of fire were the dominant influence on the containment of both forest and grass fires. As fire weather conditions worsened the probability of containment decreased across all fires and as fuel loads and slope increased the probability of containment decreased for forest fires. Slope and response time had only a minor influence on the probability of containment of grass fires. Environmental controls limit the effectiveness of wildfire management, however, results suggest investment in suppression resources and strategic fuel management will increase the probability of containment. A Bayesian Network model was developed to quantify the relative effects of mitigation and response strategies on the likelihood of house loss from forest and grass fires in New South Wales bioregions. Existing datasets and empirical models were used to determine the likelihood of ignition, containment and impact on houses. The relative reduction in risk from investment in arson and powerline ignition prevention strategies, prescribed burning, suppression resources and suppression response time was investigated. Within bioregions, the annual risk of house losses was 3 or 4 times higher for forest fires than grass fires. A 20% increase in tankers per ha of fire, followed by 20% reduction in powerline ignitions produced the greatest reduction in annual house loss risk for both forest and grass fires. Increasing the prescribed burning effort was the least effective treatment for reducing house loss from forest fires. The risk of house losses increased and the effectiveness of mitigation and suppression treatments decreased when the forest fire danger index was > 50. Increasing the number of suppression resources available may not be possible or practicable given the financial cost involved in tanker purchase, recruitment and training of firefighters and the extra burden this may place of volunteer firefighters. Investing in preventing powerline ignitions should be considered further as this was the ignition cause with the highest likelihood of house loss for both forest and grass fires. iii Findings from this thesis identify several directions for future research on prevention treatments to mitigate wildfire risk. Consistent data collection standards by fire agencies is required to underpin models for analysing wildfire risk and investigate the effectiveness of wildfire prevention treatments. The Bayesian Network could be modified to develop a spatially explicit model and extended to include an economic evaluation of each prevention and suppression strategy and mitigation strategies around houses. Wildfire risk to other assets could also be investigated. iv Acknowledgements I thank my supervisors, Dr Owen Price and A/Prof Trent Penman for their support, guidance and encouragement throughout my PhD journey. Despite always being busy, you made yourselves available for countless discussions about my research and always provided constructive criticism in a positive and optimistic manner, for which I am most grateful. I thank my university colleagues at the Centre for Environmental Risk Management of Bushfires for their support and encouragement throughout my time at Wollongong. In particular, Prof. Ross Bradstock for allowing me the opportunity to undertake a PhD within the Centre and Michael Bedward for his enduring encouragement and support with R programming. I thank my fellow post-grad students at the University of Wollongong. It was always a pleasure to walk into the room and work alongside such a group of dedicated students. I would particularly like to thank Robert Sawyer and Heather Simpson for their enthusiasm, encouragement and friendship. I thank the NSW Rural Fire Service and the Victorian Department of Sustainability and Environment for provision of data on wildfire ignitions. I thank my manager, Dr Simon Heemstra and colleagues at the NSW Rural Fire Service for their encouragement and backing me to pursue my dream. I am especially grateful that my