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International Journal of Wildland Fire International Journal of Wildland Fire Society
Journal of the International Association of Wildland Fire
RESEARCH ARTICLE

Australian grassland fire danger using inputs from the GRAZPLAN grassland simulation model

A. Malcolm Gill A B C D , Karen J. King B C and Andrew D. Moore A
+ Author Affiliations
- Author Affiliations

A CSIRO Plant Industry, GPO Box 1600, Canberra, ACT 2601, Australia.

B Fenner School of Environment and Society, The Australian National University, Acton, ACT 0200, Australia.

C Bushfire Cooperative Research Centre, Albert St, East Melbourne, VIC 3002, Australia.

D Corresponding author. Email: malcolm.gill@anu.edu.au

International Journal of Wildland Fire 19(3) 338-345 https://doi.org/10.1071/WF09023
Submitted: 2 March 2009  Accepted: 18 August 2009   Published: 13 May 2010

Abstract

Assessing and broadcasting the Fire Danger Rating each day of the fire season is an important activity in fire-prone nations. For grasslands in Australia, grass curing and biomass are biological variables that are not usually archived yet as inputs, along with weather data, to the calculation of Grassland Fire Danger Index (GFDI) and potential fire intensity. To assess past changes in the index, the biological inputs for GFDI for Canberra in south-eastern Australia were obtained using a pasture simulator, GRAZPLAN. Shoot biomass (including leaf litter) and grass curing were modelled using three contrasting pasture models (exotic annual, exotic perennial and native perennial) in order to calculate two variants of McArthur’s GFDI Mark 4 (the original and a modified version which includes fuel load); values were either capped at 100 as in the original (the ‘worst possible’ condition) or left open-ended. GFDI, and the potential fire intensity for fires burning with the wind each afternoon during a 54-year period were calculated. The native perennial grass model gave contrasting results to those from the exotic perennial grass model, whereas the annual grass model usually was intermediate in behaviour. GRAZPLAN outputs allow not only retrospective examination, but also provide a basis for predicting potential fire danger and behaviour as a result of climate change.

Additional keywords: climate change, fire danger rating; fire intensity; fuel models.


Acknowledgements

Karen King thanks Dr L. Salmon for training in the use of the simulation package. Dr J. Donnelly of CSIRO Plant Industry is thanked for his encouragement. Messrs Neville Herrmann and Eric Zurcher of CSIRO kindly assisted us with programming matters within GRAZPLAN. Dr S. Rahman, Dr M. Plucinski and Dr S. Matthews of CSIRO provided useful comments on the draft manuscript.


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