Integrative Approaches to Wildland Fire Research: From Fundamental Fuel Behavior to Advanced Technological Solutions

A special issue of Fire (ISSN 2571-6255). This special issue belongs to the section "Fire Research at the Science–Policy–Practitioner Interface".

Deadline for manuscript submissions: 30 September 2026 | Viewed by 1134

Special Issue Editor


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Guest Editor
Department of Mechanical and Aerospace Engineering, University of California Davis, Davis, CA, USA
Interests: heat transfer; fluid mechanics; wildfires; data science

Special Issue Information

Dear Colleagues,

Wildland fires are a complex and multifaceted phenomenon that has significant impacts on ecosystems, human communities, and global climate. The scientific background of wildland fire research encompasses a wide range of disciplines, including fire ecology, atmospheric science, forest management, and engineering. Developing a fundamental understanding of fire behavior—specifically how fires ignite, spread, and interact with the environment—is crucial for predicting and managing wildland fires. This knowledge is essential for developing effective fire management strategies, protecting natural resources, and safeguarding human lives and property. The importance of this research area cannot be overstated, as wildland fires are becoming more frequent and severe due to climate change, land-use changes, and other anthropogenic factors. Integrative approaches that combine fundamental research on fuel behavior with advanced technological solutions are needed to address these challenges effectively.

The aim of this Special Issue is to bring together cutting-edge research that explores the integrative approaches to wildland fire research. By focusing on both fundamental fuel behavior and advanced technological solutions, this issue seeks to bridge the gap between basic science and practical applications.

Innovative approaches to fire behavior research, studies leveraging artificial intelligence and machine learning in fire behavior studies, cross-scale and cross-disciplinary studies, and related work.

Dr. Jeanette Cobian-Iñiguez
Guest Editor

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Keywords

  • wildland fire behavior
  • prescribed burning
  • fuel behavior
  • fire detection
  • data science
  • artificial intelligence

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Published Papers (1 paper)

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Research

29 pages, 25330 KB  
Article
Beyond Static Barriers: Modelling the Effects of Water Drop Suppression on Wildfire Spread
by Leonardo Martins, António Maia and Pedro Vieira
Fire 2026, 9(2), 71; https://doi.org/10.3390/fire9020071 - 6 Feb 2026
Viewed by 875
Abstract
Wildfire suppression is often represented in fire spread simulators as static barriers that completely stop fire propagation and are placed at the start of the simulation. Recent works have begun to simulate barriers introduced at different time frames, but these normally act as [...] Read more.
Wildfire suppression is often represented in fire spread simulators as static barriers that completely stop fire propagation and are placed at the start of the simulation. Recent works have begun to simulate barriers introduced at different time frames, but these normally act as static barriers. In reality, many water-based suppression tactics (aerial and ground) only slow the fire spread by temporarily increasing fuel moisture and cooling the fuel bed. To address this limitation, we present a new simulation feature: the Dynamic Water Barrier. Unlike static barriers, this representation captures the temporal transient effect of water application, since it is modeled using a simplified water load and evaporation dynamics to estimate changes in live fuel moisture content (LFMC). Implemented using the Fire Area Simulator (FARSITE), the Dynamic Water Barrier reduces the rate of spread and fireline intensity, delaying but not fully preventing fire propagation, providing a transient influence of water-based suppression. The approach was tested on one North American (NA) and one Portuguese fire, where suppression missions were available. The dynamic barriers led to reductions in Relative Area Difference, reaching 0.234 for the Portuguese fire and 0.006 for the NA fire, outperforming the scenario of no combat and having a comparable performance with the full static barrier (RAD 0.108 and 0.024, respectively), while limiting the creation of unburned areas behind the firefront. Although the validation is limited, these findings illustrate the potential to improve tactical decision support and dynamic suppression planning in wildfire management, requiring further studies of other fires and controlled fire suppression missions. Full article
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