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Improving the reliability and utility of operational bushfire behaviour predictions in Australian vegetation.

Authors :
Plucinski, Matt P.
Sullivan, Andrew L.
Rucinski, Chris J.
Prakash, Mahesh
Source :
Environmental Modelling & Software. May2017, Vol. 91, p1-12. 12p.
Publication Year :
2017

Abstract

Fire behaviour and spread predictions guides suppression strategies and public warnings during wildfires. The scientific understanding of fire behaviour forms the core of these predictions, but is incomplete, and expert judgement and experience are required to augment the evidence based knowledge. Amicus is a new decision support system that implements contemporary, published and operationalised bushfire behaviour models (e.g. rate of spread, flame height, fireline intensity, spotting distance) in the Australian bushfire context. It enables the inclusion of expert judgement and local knowledge, allows users to analyse temporal trends and uncertainty in inputs, and facilitates reliable and practical predictions. This paper provides a comprehensive overview of Amicus, including its operation and functionality, identifies the boundaries of the current understanding of fire science, discusses the major limitations in existing knowledge, and provides a framework for allowing deterministic and anecdotal/local knowledge to be incorporated into formal fire behaviour predictions. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
13648152
Volume :
91
Database :
Academic Search Index
Journal :
Environmental Modelling & Software
Publication Type :
Academic Journal
Accession number :
121997048
Full Text :
https://doi.org/10.1016/j.envsoft.2017.01.019