LB 18-184 - Modeling changes in wildfire occurrence and risk to homes in the Southern Rocky Mountains, USA

Background/Question/Methods:

Changes in climate and vegetation have increased the potential for large and destructive wildfires across much of the western U.S. concurrently with increased housing development in the wildland-urban interface since the 1990s. In response to these changes, vegetation management to reduce wildland fire risk to communities is now a focus of public agencies. However, it is unclear how changes in climate, wildfire occurrence, and housing growth have affected risk to homes. Therefore, we estimated risk by combining predicted burn probabilities with housing density across the Southern Rocky Mountains from 1990 through 2019. We fit a random forests model using weather, land cover, topography, and past fire history to predict burn probabilities and uncertainty intervals on a monthly time step. We summed the predicted burn probabilities and risk across the study area to determine the expected burned area and homes risk, compared them to observed burned area and number of homes exposed, and quantified trends over time. Finally, we evaluated the individual and combined impacts of housing growth and changing burn probability on risk to homes.

Results/Conclusions:

From 1990 – 2019, fires burned 9,055 km² and exposed more than 8,500 homes. Observed mean annual area burned increased 632% from the 1990s to the 2000s, which combined with housing growth resulted in a 1342% increase in homes exposed. Increases continued in the 2010s but at lower rates; burned area by 65% and exposure by 32%. The random forests model had excellent fit and high correlation with observations (AUC=0.88 and r=0.9) and observed values were within the 95% uncertainty interval for all years except 2016 (burned area) and 2000 (exposure). Increases in risk between the 1990s and 2000s were primarily due to warmer and drier weather conditions and secondarily because of housing growth. However, increases in risk between the 2000s and 2010s were primarily due to housing growth. Our modeling approach identifies spatial and temporal patterns of wildfire potential and risk, which is critical information to guide where agencies and communities could prioritize vegetation management and other risk mitigation efforts, or to help evaluate the tradeoffs between risk and the ecological benefits of fires in wildlands. Because the drivers behind risk shift over time, efforts to assess and mitigate risk may need to account for multiple drivers simultaneously.