At the October California Fire Chiefs Association conference, Fire Chief (Ret.) Dave Winnacker presented Rethinking Wildfire Risk: Bridging the Gap Between Insurance and Mitigation. His presentation explored why only a few fires cause most of California’s structure loss and how new modeling approaches can close the gap between mitigation and insurance.
Just four fires have accounted for half of all structures lost in California, revealing that traditional wildfire models, which focus on wildland intensity and exposure, fail to explain how fires spread within communities. XyloPlan’s framework reframes the problem around time, showing how fire moves from wildland to urban areas and how structure-to-structure spread amplifies loss.
A New Framework for Understanding Risk
XyloPlan models wildfire behavior across three domains:
- Fire Pathways Modeling: Predicts where fire will move fastest across the landscape.
- Transition Modeling: Identifies where wildland fire is most likely to ignite structures.
- Urban Fire Spread Modeling: Simulates structure-to-structure fire spread under realistic wind and fuel conditions.
This multi-layered approach helps fire agencies, insurers, and communities understand not only where fire will go but how to slow it down.
From Insight to Action
In communities like Fallbrook, California, Fire Pathways analysis aligns with historical fire activity, showing how weather, terrain, and vegetation combine to drive fire into the built environment. These insights help prioritize hardening and defensible space investments that reduce ignition probability and limit conflagration spread.
XyloPlan’s Conflagration Initiation Rating and Conflagration Basin models measure where mitigations deliver the greatest benefit. In case studies, hardening the top 50 to 90 percent of high-risk structures reduced hundreds of potential ignitions with strong ROI.
Building Measurable Resilience
By connecting wildfire behavior with urban spread, XyloPlan helps communities and insurers move from reactive response to proactive prevention. The result is a data-driven approach that measures real risk reduction and strengthens insurability.