Estimating Burn Severity in California
Abstract
Wildfires in California are burning with increasing frequency, size, and severity. Burn severity, quantified by a Composite Burn Index (CBI), quantifies impacts on vegetation and soil post-fire. Factors that drive fire frequency and size are well studied, but there have been differing conclusions on increased burn severity. Drivers of increased severity at fine spatial scales have been attributed to topography, vegetation, and daily weather. However, changing climate can help explain the larger areas of high severity that we are seeing in California. Wildfire burn severity has been increasing with increased fire sizethe larger the fire, the higher the proportion that was burned in high severity. In this study, we explore the varying drivers of burn severity as classified into composite burn index fractions as well as the influence of wind on high severity burned patches. We observe that fuel availability and monthly climate can best explain burn severity fractions. By accounting for how dry fuels are during the fire season we can better estimate burn severity as climate continues to change. To model for burn severity, we use a conditional binomial approach, modeling each severity class in succession to the next. The methodology developed in this study will aim to estimate burn severity at 30m resolution for California. Estimated fine-scale burn severity maps can help inform decisions on prescribed fire treatments, as well as identify areas of high structural risk in the wildland-urban interface. Being able to predict burn severity with the changing climate will also allow for a more comprehensive understanding of vegetation changes and habitat loss.
- Publication:
-
AGU Fall Meeting Abstracts
- Pub Date:
- December 2021
- Bibcode:
- 2021AGUFM.B25M1650S