Evaluation of the predictive capacity of dead fuel moisture models for Eastern Australia grasslands
Miguel G. Cruz A D , Susan Kidnie B , Stuart Matthews C , Richard J. Hurley A , Alen Slijepcevic B , David Nichols B and Jim S. Gould A
+ Author Affiliations
- Author Affiliations
A CSIRO, GPO Box 1700, Canberra, ACT 2601, Australia.
B Country Fire Authority (CFA), Fire and Emergency Management, PO Box 701, Mount Waverley, Vic. 3149, Australia.
C NSW Rural Fire Service, 15 Carter Street, Lidcombe, NSW 2141, Australia.
D Corresponding author. Email: miguel.cruz@csiro.au
International Journal of Wildland Fire 25(9) 995-1001 https://doi.org/10.1071/WF16036
Submitted: 2 March 2016 Accepted: 17 May 2016 Published: 5 July 2016
Abstract
The moisture content of dead grass fuels is an important input to grassland fire behaviour prediction models. We used standing dead grass moisture observations collected within a large latitudinal spectrum in Eastern Australia to evaluate the predictive capacity of six different fuel moisture prediction models. The best-performing models, which ranged from a simple empirical formulation to a physically based process model, yield mean absolute errors of 2.0% moisture content, corresponding to a 25–30% mean absolute percentage error. These models tended to slightly underpredict the moisture content observations. The results have important implications for the authenticity of fire danger rating and operational fire behaviour prediction, which form the basis of community information and warnings, such as evacuation notices, in Australia.
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