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Background <p>Wildfires increasingly threaten structures and communities in the wildland-human interface of forested biomes. We present an integrated fuel break placement optimization model that is designed to assist with the planning of landscape scale fuel break configuration to mitigate wildfire risk to structures.</p> Method <p>The model combines three components: a burn probability simulation model, a structural loss rate model, and a network-based optimization model for fuel break placement. We applied the models to a fire-prone forest landscape encompassing a military training base with frequent ignitions and restricted access zones, and its surrounding communities and residential structures.</p> Results <p>We evaluated 198 scenarios with different budget levels, management priorities, and jurisdictional constraints to find optimal fuel break placement solutions. Our results show significant fire hazard and risk reduction potential even at modest fuel treatment budgets. Fire risk to structures is reduced most when fuel breaks are placed inside and outside the jurisdiction of the military base.</p> Conclusions <p>The proposed framework offers a workable decision-support tool for land managers and allows accommodating for real-world jurisdictional constraints, budget limitations, and risk reduction priorities in fire-prone regions.</p>

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Optimizing fuel break placement to mitigate wildland fire risk to communities

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年7月17日

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  • Vittorio Nicoletta,
  • Raphaël D. Chavardès,
  • Denys Yemshanov,
  • Valérie Bélanger,
  • Anne Cotton-Gagnon,
  • Jonathan Boucher

摘要

Background

Wildfires increasingly threaten structures and communities in the wildland-human interface of forested biomes. We present an integrated fuel break placement optimization model that is designed to assist with the planning of landscape scale fuel break configuration to mitigate wildfire risk to structures.

Method

The model combines three components: a burn probability simulation model, a structural loss rate model, and a network-based optimization model for fuel break placement. We applied the models to a fire-prone forest landscape encompassing a military training base with frequent ignitions and restricted access zones, and its surrounding communities and residential structures.

Results

We evaluated 198 scenarios with different budget levels, management priorities, and jurisdictional constraints to find optimal fuel break placement solutions. Our results show significant fire hazard and risk reduction potential even at modest fuel treatment budgets. Fire risk to structures is reduced most when fuel breaks are placed inside and outside the jurisdiction of the military base.

Conclusions

The proposed framework offers a workable decision-support tool for land managers and allows accommodating for real-world jurisdictional constraints, budget limitations, and risk reduction priorities in fire-prone regions.