Toward Probabilistic Risk Assessment of Wildland–Urban Interface Communities for Wildfires

The number of wildfire incidents affecting communities in Wildland–Urban Interface (WUI) areas has been rapidly increasing. Understanding the fire spread between structures and evaluation of the response of the communities to the possible wildfire scenarios are crucial for proper risk management in...

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Bibliographic Details
Published in:Fire technology 2023-07, Vol.59 (4), p.1379-1403
Main Authors: Masoudvaziri, Nima, Elhami-Khorasani, Negar, Sun, Kang
Format: Article
Language:English
Subjects:
Case studies
Characterization and Evaluation of Materials
Civil Engineering
Classical Mechanics
Conditional probability
Distribution functions
Engineering
Forest & brush fires
Methodology
Physics
Probabilistic risk assessment
Risk assessment
Risk management
Statistical analysis
Stochastic models
Stochasticity
Urban areas
Wildfires
Wildland-urban interface
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Summary:The number of wildfire incidents affecting communities in Wildland–Urban Interface (WUI) areas has been rapidly increasing. Understanding the fire spread between structures and evaluation of the response of the communities to the possible wildfire scenarios are crucial for proper risk management in the existing and future communities. This paper discusses a stochastic methodology to evaluate the community’s response to potential wildfire scenarios. The methodology has three primary features: (1) it is based on stochastic modeling of fire spread; (2) it breaks the wildfire incident into two consecutive segments: spread inside the wildland and spread inside the community; (3) it integrates the two spread models in the form of a conditional probability. The paper focuses on fire spread inside the community and applies the proposed methodology to two case studies in California, US. The two case studies demonstrate variations in fire spread within the communities for the given fire scenarios approaching from the wildland. The performance of communities is characterized using cumulative distribution functions of the number of ignited buildings over time.
ISSN:0015-2684
1572-8099
DOI:10.1007/s10694-023-01382-y