A grant from the National Science Foundation (NSF) will fund a project led by a UC Merced researcher looking into predicting behavior of wildfires.
Jeanette Cobian-Iñiguez is leading a team from UCs Merced and Irvine awarded $1,179,479 to predict the impact of forest fuel treatments on fire behavior, focusing on an improved understanding of the influence of surface-fuel attributes on fire behavior and severity, and ultimately, on forest carbon storage, according to a project summary.
The team will model the influences of wind, dryness and fuels on wildfire, as well as how forests will respond to wildfire management actions such as thinning, chipping and grinding up smaller trees and shrubs. This work will provide a better understanding and way of predicting carbon storage in the forest. Researchers have been studying the impact of wildfires on the release of carbon into the atmosphere, which is the leading cause of climate change.
"Mapping fuel types and their characterization onto projected flame length remains a weak link in valuing benefits of different fuels-treatments options; and the valuing carbon storage benefits of different fuels configurations, with and without prescribed burning, also have high uncertainty," the study investigators wrote. "As forest managers adopt a multi-benefit framework for decision making in a warming climate, new social relationships between investments in nature-based climate solutions and decisions on the ground will require the integration that this project advances."
In their NSF-funded research, the study investigators hope to achieve three goals:
- To establish the importance of having a variety of trees and shrubs left behind after wildfire mitigation efforts, reducing the density of potential fuel for ensuing fires.
- To develop and assess tools to predict wildfire severity and spread in areas that have been treated or under different meteorological conditions.
- To demonstrate the carbon storage and related benefits from fuel treatments to reduce the occurrence and impacts of high-severity wildfires.