Structural Engineering

Wildfire Engineering: Integrating Models with Data to Advance Solutions

May 21, 2025 - 12:00 pm

Speaker: Hamed Ebrahimian

Wildland fires are a critical part of a healthy ecosystem. However, the rapid expansion of the wildland-urban interface, coupled with climate change and human activities, has dramatically increased wildfire hazards in recent decades. Today, wildfires rank among the most significant natural threats to social, economic, ecological, and infrastructure systems. This presentation introduces the wildfire challenge to the engineering community and highlights our team’s recent advancements in wildfire simulation, data analysis, and risk assessment.

Simulating wildfires is a complex, multi-physics, and multi-scale process essential for both pre-fire risk assessment and active-fire emergency response. This presentation provides an overview of state-of-the-art wildland fire modeling techniques, emphasizing our contributions to fuel characterization and modeling fire spotting. To address the challenges of collecting observational wildfire data, we have developed a deep learning method that enhances the spatial resolution of satellite data. This new development supports the integration of computational models and data, advancing capabilities for wildfire digital twinning and enabling near real-time wildfire monitoring for emergency response.

Additionally, the presentation outlines the development of a probabilistic wildfire risk assessment framework, inspired by decades of progress in earthquake risk engineering. This framework accounts for uncertainties across different systems to quantify wildfire risk as the probability of loss. Finally, we explore key technical challenges in wildfire monitoring, simulation, and data assimilation and present a forward-looking vision for wildfire engineering research. The objective is to engage the engineering community in addressing this critical and evolving challenge through innovative contributions.