Bushfire simulators and analysis in Australia: insights into an emerging sociotechnical practice

ABSTRACT

The present context of escalating environmental risks places increased pressure and importance on our technical ability to predict and mitigate the potential consequences and occurrence of major natural hazards such as bushfire (or ‘wildfire’). Over the past decade, bushfire prediction in Australia, as in many other fire-prone countries, has increasingly come to involve both trained fire behaviour analysts and complex computer-based two-dimensional bushfire simulation models. During this transitional moment in bushfire management, there is a clear need to better understand the ways in which such predictive technologies and practitioners influence how we anticipate, encounter and manage this natural hazard and its effects. In this paper, the authors seek to prepare the ground for studies of the social dimensions of bushfire prediction by investigating how simulators and predictive practitioners have been mobilised and represented in Australia to date. The paper concludes by posing several questions that bushfire practitioners, policy-makers and researchers alike in Australia and elsewhere will need to address as our flammable future emerges.

KEYWORDS:

• Bushfire
• wildfire
• simulation
• disaster prediction
• risk

Acknowledgements

We would like to thank Malcolm Gill, Andrew Sullivan, and our peer reviewers for comments that improved earlier versions of this article. We also acknowledge the research assistance of Sophia Piscitelli and the support received from the Alfred Deakin Institute for Citizenship and Globalisation and the Australasian Fire and Emergency Service Authorities Council’s (AFAC) Predictive Services Group.

Disclosure statement

No potential conflict of interest was reported by the authors.

ORCID

Timothy Neale http://orcid.org/0000-0003-4703-5801

Daniel May http://orcid.org/0000-0002-4749-3637

Notes

1 The authors use ‘natural hazards’ advisedly, as such phenomena are hazardous precisely because they impact upon and are shaped by social worlds. Nonetheless, ‘natural hazards’ is the default term of both the literature and professional sector.

2 In this paper, we put aside any questions about fire spread algorithms and their use, however, see Cruz et al. (2015).

3 Throughout this paper we use the term ‘FBAn’ as it is the dominant name for such practitioners in Australia.

4 It was used by the Victorian government in 1997 to undertake a cost–benefit analysis of fire management activities (Bennetton, Cashin, Jones, & Soligo, 1998).

5 It is possible that a 2006 international workshop on fire spread simulators was also influential in bringing simulators into sector practice (Opperman et al., 2006).

6 The specific units are ‘PUAFIR512: Develop and analyse the behaviour and suppression options for a Level 2 wildfire’ and ‘PUAFIR414 – Interpret and analyse fire weather information’.

7 News media data was collected through Dow Jones’ Factiva database and Google using keyword searches (‘bushfire’ and ‘PHOENIX’, ‘Australis,’ ‘Spark,’ ‘simulator,’ or ‘model’) targeted at Australian print and online news media publications within relevant date ranges (1 January 2000 to 1 April 2017). A total of 36 relevant sources were ultimately collected and coded according to their attitudes towards simulators. This section provides a representative overview of these sources.

8 For the Great Divide Complex fires, a special Strategic Planning Unit convened including FBAns, who provided fire spread forecasts ‘ranging downwards from “possible worst case” to “probable worst case” to “average worst case”’ (R. Smith, 2007, p. 48).

9 The Bicheno and Lake Repulse fires were also included in the investigation.

10 Evidence suggests the Wambelong fire exhibited an atypical dynamic behaviour (known as Vorticity-Driven Lateral Spread) where the fire front travels perpendicular to the prevailing wind (McRae, Sharples, & Fromm, 2015).

Additional information

Funding

This work was supported by a Research Development and Seeding Grant from Deakin University.