Quantifying wildfire growth rates using smoke plume observations derived from weather radar
Thomas J. Duff A C , Derek M. Chong A and Trent D. Penman B
+ Author Affiliations
- Author Affiliations
A Bushfire Behaviour and Management Group, Department of Ecosystem and Forest Sciences, Faculty of Science, The University of Melbourne, Burnley, Vic. 3121, Australia.
B Bushfire Behaviour and Management Group, Department of Ecosystem and Forest Sciences, Faculty of Science, The University of Melbourne, Creswick, Vic. 3363, Australia.
C Corresponding author. Email: tjduff@unimelb.edu.au
International Journal of Wildland Fire 27(8) 514-524 https://doi.org/10.1071/WF17180
Submitted: 22 December 2017 Accepted: 4 June 2018 Published: 10 July 2018
Abstract
Fast-moving wildfires can result in substantial losses of infrastructure, property and life. During such events, real-time intelligence is critical for managing firefighting activities and public safety. The ability of fixed-site weather radars to detect the plumes from fires has long been recognised; however, quantitative methods to link properties of radar observed plumes to fire behaviour are lacking. We investigated the potential for weather radars to provide real time estimates of the growth of large fires in south-eastern Australia. Specifically, we examined whether the rate of change in fire area could be approximated using the change in volume represented by radar returns. We evaluated a series of linear mixed-effects models predicting fire-area growth using radar data representing a range of dBZ thresholds and search volumes. Models were compared using an information–theoretic approach. Radar return volume was found to be a robust predictor of fire-area change. The best model had a minimum threshold of 10 dBZ and a search radius of 60 km (R2 = 0.64). Fire area and radar relationships did not vary significantly between radar stations, suggesting broad applicability beyond the dataset. Further development of the use of weather radars for wildfire monitoring could yield substantial benefits because of their high frequency of scan and broad coverage over many populated areas.
Additional keywords: bushfire, dBZ, detection, rain radar, wildland fire.
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