WILDFIRE MODELING

The entire Roaring Fork watershed lies within the Wildland–Urban Interface (WUI), which means there's an increased wildfire risk. We know that improving our wildfire resiliency means that we must plan the most effective forest thinning and home hardening efforts, but where should we start? How should we prioritize our efforts given limited resources and capacity? 

To answer these questions, the Wildfire Collaborative partnered with Dr. Hussam Mahmoud and his team at Vanderbilt University to gain a deeper understanding of where our greatest wildfire risks—and opportunities for resilience—exist. 

Dr. Hussam Mahmoud has spent more than a decade developing a model that helps us understand how fire spreads through communities—not just how it ignites a single home. 

His work builds on earlier research by Dr. Jack Cohen, who introduced the concept of the Home Ignition Zone. Cohen’s model was groundbreaking: it showed that most homes burn because of embers and radiant heat within 100 feet, not from the main wall of flames. That insight transformed how we think about defensible space and home hardening. Importantly, Dr. Mahmoud asked a new set of questions: What happens once fire enters a neighborhood? Why does one home burn while the one next door survives? How does fire move from structure to structure?

To answer these questions, Mahmoud’s team developed a model based on graph theory. Imagine every building, tree, or fuel patch as a “node” in a network, connected by the ways fire can travel—through convection, radiation, and ember spotting. Each community has its own unique network because no two neighborhoods are arranged the same way. Because Mahmoud’s model adapts to the real world—it’s the opposite of one-size-fits-all. 

The model simulates fire progression, calculates the relative vulnerability of every structure, and identifies the most likely fire boundary. By identifying the homes and areas most likely to ignite and transmit fire, the model helps communities invest limited mitigation dollars where they’ll make the biggest difference.