Development of a quantitative Wildland Urban Interface fire resilience assessment model

Wildland-Urban Interface (WUI) fires are growing in frequency and intensity as communities continue to develop in wildland areas and climate change increases fire season severity, posing a great risk to people and structures within these communities. In the United States, risk mitigation is typically handled through a prescriptive approach that establishes an intended level of resilience, i.e., the adoption of codes and standards. However, a disconnect exists between intended resilience and actual resilience observed during fire events. Intended resilience reflects system performance as agreed upon by code developers, while actual resilience emerges from complex interactions during a fire. Often, these complex interactions are not covered by prescriptive codes and are difficult to accurately represent through performance-based modeling (PBD). This research aims to bridge the gap between intended and actual resilience through a novel conceptual modeling approach to visualize and quantify both intended and actual resilience in WUI communities. Two conceptual maps were developed using qualitative analysis: one from WUI codes, standards, and guidelines (intended resilience), and another from fire investigation reports from the 2018 Camp Fire and 2023 Lahaina Fire (actual resilience). Each map visualizes the relationships between resilience concepts, allowing the user to better understand the complexity of code requirements as well as interactions during a real WUI fire event. These two maps were implemented into a Microsoft® Excel®-based tool that includes a computational framework for quantifying resilience. By assigning performance scores, weighting factors, and a directional constant, the tool propagates the scores through the conceptual hierarchy to calculate the overall resilience scores for a community. The models allow authorities in WUI communities to assess community resilience, compare intended versus actual resilience, and identify how to best use resources to improve their community’s resilience scores. The models are intended to continuously evolve through field testing, expert feedback, and incorporation of additional literature. The findings highlight a mismatch between prescriptive intent and real-world outcomes, with actual fires containing much more complex interactions. Also, a noticeable lack of the recovery phase of emergency management is present in both the codes and reports. The proposed tool allows WUI communities to step away from a purely prescriptive approach and towards a more performance-based approach to WUI fire risk mitigation that better represents the complex interactions that occur during WUI fires. This research advances fire safety and emergency management theory and offers a practical solution to assess community resilience.