A Modelling Framework for Householder Decision-Making for Wildfire Emergencies

Published

August 14, 2019

Author(s)

Ruggiero Lovreglio, Erica D. Kuligowski, Steve Gwynne, Ken Strahan

Abstract

The occurrence of wildfire threats has dramatically increased in the last few decades creating serious challenges for hundreds of thousands of communities around the world. Understanding the physical and social dynamics characterizing wildfires is fundamental to assess the risk to different communities and take actions to reduce the threat posed by wildfire. Although, several studies investigating household wildfire risk perception and decision-making are available in the literature, modelling solutions to predict household behaviour in wildfire are still in their early stages given the lack of a behavioural model suitable for embedding within a simulation tool. In this paper, we propose a mathematical framework aimed at simulating how householders perceive the risk associated to wildfires and how they take protective actions to respond to such threats. A conceptual Wildfire Decision Model based on nine assumptions derived from existing literature on human behaviour in wildfires is introduced. A mathematical framework is then proposed to implement such a model within a simulation tool. The proposed modelling solution can help identify the information required to generate new dynamic and behavioural travel demand models for wildfire evacuation.

Citation

International Journal of Disaster Risk Reduction

Volume

41

Pub Type

Journals

Download Paper

https://doi.org/10.1016/j.ijdrr.2019.101274

Local Download

Keywords

wildland-urban interface fires, human behavior, modeling, decision-making, wildfire

Citation

Lovreglio, R. , Kuligowski, E. , Gwynne, S. and Strahan, K. (2019), A Modelling Framework for Householder Decision-Making for Wildfire Emergencies, International Journal of Disaster Risk Reduction, [online], https://doi.org/10.1016/j.ijdrr.2019.101274, https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=925605 (Accessed October 3, 2024)