Preprints
https://doi.org/10.5194/nhess-2021-179
https://doi.org/10.5194/nhess-2021-179

  01 Jul 2021

01 Jul 2021

Review status: this preprint is currently under review for the journal NHESS.

ABWiSE v1.0: Toward and Agent-Based Approach to Simulating Wildfire Spread

Jeffrey Katan and Liliana Perez Jeffrey Katan and Liliana Perez
  • Laboratory of Environmental Geosimulation (LEDGE), Department of Geography, Université de Montréal, Montreal, QC, Canada, 1375, Avenue Thérèse Lavoie-Roux, Montréal (QC), H2V 0B3

Abstract. Wildfires are a complex phenomenon emerging from interactions between air, heat, and vegetation, and while they are an important component of many ecosystems’ dynamics, they pose great danger to those ecosystems, and human life and property. Wildfire simulation models are an important research tool that help further our understanding of fire behaviour and can allow experimentation without recourse to live fires. Current fire simulation models fit into two general categories: empirical models and physical models. We present a new modelling approach that uses agent-based modelling to combine the complexity found in physical models with the ease of computation of empirical models. Our model represents the fire front as a set of moving agents that respond to, and interact with, vegetation, wind, and terrain. We calibrate the model using two simulated fires and one real fire, and validate the model against another real fire and the interim behaviour of the real calibration fire. Our model successfully replicates these fires, with a Figure of Merit on par with simulations by the Prometheus simulation model. Our model is a stepping-stone in using agent-based modelling for fire behaviour simulation, as we demonstrate the ability of agent-based modelling to replicate fire behaviour through emergence alone.

Jeffrey Katan and Liliana Perez

Status: open (until 25 Aug 2021)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on nhess-2021-179', Anonymous Referee #1, 16 Jul 2021 reply
    • CC1: 'Reply on RC1', Liliana Perez, 24 Jul 2021 reply

Jeffrey Katan and Liliana Perez

Jeffrey Katan and Liliana Perez

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Short summary
Wildfires are an integral part of ecosystems the world over, but also pose a serious risk to human life and property. To further our understanding of wildfires and allow experimentation without recourse to live fires, this study presents an agent-based modelling approach to combine the complexity found in physical models with the ease of computation of empirical models. Model calibration and validation shows bottom-up simulation encompasses the core elements of complexity of fire across scales.
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