Pyros: a raster–vector spatial simulation model for predicting wildland surface fire spread and growth

Debora Voltolina; Giacomo Cappellini; Tiziana Apuani; Simone Sterlacchini

doi:10.1071/WF22142

RESEARCH ARTICLE (Open Access)

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Pyros: a raster–vector spatial simulation model for predicting wildland surface fire spread and growth

Debora Voltolina

^A ^B ^* , Giacomo Cappellini

^A , Tiziana Apuani

^B and Simone Sterlacchini

^A

+ Author Affiliations

- Author Affiliations

^A National Research Council, Institute of Environmental Geology and Geoengineering, Via Mario Bianco 9, 20131 Milan, Italy.

^B Department of Earth Sciences “Ardito Desio”, University of Milan, Via Luigi Mangiagalli 34, 20133 Milan, Italy.

^* Correspondence to: debora.voltolina@cnr.it

International Journal of Wildland Fire 33, WF22142 https://doi.org/10.1071/WF22142

Submitted: 2 July 2022 Accepted: 10 November 2023 Published: 8 March 2024

© 2024 The Author(s) (or their employer(s)). Published by CSIRO Publishing on behalf of IAWF. This is an open access article distributed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License (CC BY-NC-ND)

Abstract

Background

Euro–Mediterranean regions are expected to undergo a climate-induced exacerbation of fire activity in the upcoming decades. Reliable predictions of fire behaviour represent an essential instrument for planning and optimising fire management actions and strategies.

Aims

The aim of this study was to describe and analyse the performance of an agent-based spatial simulation model for predicting wildland surface fire spread and growth.

Methods

The model integrates Rothermel’s equations to obtain fire spread metrics and uses a hybrid raster–vector implementation to predict patterns of fire growth. The model performance is evaluated in quantitative terms of spatiotemporal agreement between predicted patterns of fire growth and reference patterns, under both ideal and real-world environmental conditions, using case studies in Sardinia, Italy.

Key results

Predicted patterns of fire growth demonstrate negligible distortions under ideal conditions when compared with circular or elliptical reference patterns. In real-world heterogeneous conditions, a substantial agreement between observed and predicted patterns is achieved, resulting in a similarity coefficient of up to 0.76.

Conclusions

Outcomes suggest that the model exhibits promising performance with low computational requirements.

Implications

Assuming that parametric uncertainty is effectively managed and a rigorous validation encompassing additional case studies from Euro–Mediterranean regions is conducted, the model has the potential to provide a valuable contribution to operational fire management applications.

Keywords: agent-based model, Euro–Mediterranean, fire behaviour, fire management, fire suppression, Italy, Rothermel model, Sardinia, spatial simulation model.

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