Collaborative Research: FIRE-MODEL: Advancing Wildland Fire Modeling by Capturing Unresolved Canopy Dynamics

About This Grant

Wildfires are becoming more frequent, intense, and difficult to manage due to the shift in the global climate and expanding development into fire-prone areas. A major challenge in wildfire response is predicting how fires will behave, especially in forested areas where wind, vegetation, and fire interact in complex ways. Current fire models oversimplify forests as static blocks and fail to capture how trees sway, bend, and influence airflow. These oversights can lead to inaccurate forecasts and limit the effectiveness of prescribed burns and emergency planning. This project seeks to change that by developing more realistic, science-based tools to help land managers better anticipate fire behavior. The research team will also engage with fire professionals, students, and educators to ensure that the science gained through this research is applicable in real-world settings. The broader impacts include improving public safety, enhancing wildfire resilience, and training a new generation of interdisciplinary wildfire scientists. This project will develop and validate a new predictive modeling framework that explicitly incorporates canopy biomechanics, aerodynamics, and fire-atmosphere interactions to capture the dynamic motion of real tree canopies and their effects on fire behavior. Using multi-physics modeling and controlled laboratory experiments, the team will simulate how flexible trees interact with wind and buoyant flows during surface fires. These models will incorporate realistic canopy geometries, fire-atmosphere interactions, and turbulence to better understand key processes such as the transition from surface to crown fires. A multi-fidelity modeling approach and high-quality experimental datasets will be used to reduce uncertainties and improve model accuracy. With this, the project offers a new framework to address current limitations in realistic prediction of understory fire behavior. The resulting tools will support proactive fire management, prescribed burn planning, and risk assessment in the wildland-urban interface. Beyond wildfire science, the project advances computational modeling, biomechanics, and environmental fluid dynamics, with potential applications in agriculture, climate resilience, and natural hazard preparedness. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.