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Open Access CC BY-NC V4.0
Journal article
Environmental drivers of bushfire warning categories: insights from official records, meteorology, and drought data in Western Australia
Environmental challenges (Amsterdam, Netherlands), Vol.23, 101509
2026
Abstract
This study examines environmental drivers of issued bushfire warning categories by integrating official warning records with routinely collected meteorological observations and drought indicators, demonstrated in Western Australia under the national Australian Warning System. Data sources are harmonised into an event-level dataset linking each warning instance to concurrent environmental conditions. Supervised multi-class models are evaluated using random splits and a time-forward seasonal holdout to characterise predictive performance under differing evaluation assumptions. Association rule mining is applied to discretised predictors to extract interpretable condition-to-warning relationships. Results indicate a consistent warning structure dominated by diurnal and seasonal timing, wind-gust behaviour, and atmospheric dryness, with rule patterns highlighting combinations of heat, wind, and persistent drought context associated with higher warning levels. Overall, the study demonstrates a reproducible workflow for analysing issued warning categories that is transferable to other jurisdictions with structured public warning systems and routine environmental monitoring, providing a basis for comparative analysis of warning patterns and their environmental drivers in the context of climate adaptation (SDG 13) and urban safety and well-being (SDG 11).
Details
- Title
- Environmental drivers of bushfire warning categories: insights from official records, meteorology, and drought data in Western Australia
- Authors/Creators
- Amalia Utamima - Department of Information Systems, Institut Teknologi Sepuluh Nopember, Surabaya, IndonesiaFidela Jovita Kanedi - Department of Information Systems, Institut Teknologi Sepuluh Nopember, Surabaya, IndonesiaFerdous Sohel - Murdoch University, School of Information Technology
- Publication Details
- Environmental challenges (Amsterdam, Netherlands), Vol.23, 101509
- Publisher
- Elsevier B.V.
- Identifiers
- 991005882553107891
- Copyright
- © 2026 The Authors.
- Murdoch Affiliation
- School of Information Technology
- Language
- English
- Resource Type
- Journal article
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