Prediction of the probability of large fires in the Sydney region of south-eastern Australia using fire weather
R. A. Bradstock A B E , J. S. Cohn C , A. M. Gill A B , M. Bedward C and C. Lucas B DA Fenner School of Environment and Society, The Australian National University, Canberra, ACT 0200, Australia.
B Bushfire Co-operative Research Centre, 340 Albert St, East Melbourne, VIC 3002, Australia.
C New South Wales Department of Environment and Climate Change, PO Box 1967, Hurstville, NSW 2220, Australia.
D Australian Bureau of Meteorology, GPO Box 1289, Melbourne, VIC 3001, Australia.
E Corresponding author. Present address: Centre for Environmental Risk Management of Bushfires, University of Wollongong, NSW 2522, Australia. Email: rossb@uow.edu.au
International Journal of Wildland Fire 18(8) 932-943 https://doi.org/10.1071/WF08133
Submitted: 28 July 2008 Accepted: 17 February 2009 Published: 9 December 2009
Abstract
The probability of large-fire (≥1000 ha) ignition days, in the Sydney region, was examined using historical records. Relative influences of the ambient and drought components of the Forest Fire Danger Index (FFDI) on large fire ignition probability were explored using Bayesian logistic regression. The preferred models for two areas (Blue Mountains and Central Coast) were composed of the sum of FFDI (Drought Factor, DF = 1) (ambient component) and DF as predictors. Both drought and ambient weather positively affected the chance of large fire ignitions, with large fires more probable on the Central Coast than in the Blue Mountains. The preferred, additive combination of drought and ambient weather had a marked threshold effect on large-fire ignition and total area burned in both localities. This may be due to a landscape-scale increase in the connectivity of available fuel at high values of the index. Higher probability of large fires on the Central Coast may be due to more subdued terrain or higher population density and ignitions. Climate scenarios for 2050 yielded predictions of a 20–84% increase in potential large-fire ignitions days, using the preferred model.
Additional keywords: climate change, drought, fire danger, fire weather indices.
Acknowledgements
We thank Simon Hunter and Owen Price for diligent assistance with compilation and analysis of data and preparation of diagrams and Mick McCarthy for comprehensive advice on Bayesian analysis. We also thank Owen Price and several referees for constructive comments on draft manuscripts.
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