Considerable effort is expended to determine fuel loadings and to map those loadings across the landscape, yet there is little or no work being done to determine how to incorporate those measurements into the next generation of fire behavior models, such as physics-based models. Identifying critical spatial and temporal fuel characteristics required by these models may help to refine field sampling procedures and ensure a tight coupling between how fuels are measured and how those measurements are then used to assess potential fire behavior. FFS Research Ecologist Matt Jolly, FFS Research Forester Russ Parsons and other FFS researchers at the Missoula Fire Sciences Laboratory are developing a three-part project that describes and scales the physio-chemical properties of live and dead fuels to parameterize physics-based behavior fire models.
For the first part of this project, litter and foliage samples from a variety of grass, shrub, and tree species common throughout the Rocky Mountains will be analyzed to provide a full suite of seasonal physical and chemical fuel properties and determine their flammability. This research may help to explain linkages between physical and chemical fuel properties, as well as provide much needed input parameters to support the testing and application of physics-based fire models. The second part of this project will develop methods to integrate field-measured fuels data into physics-based fire models. This will entail developing methods for integrated heterogeneous fuel beds into physics-based models, such as FIRETEC and the Wildland-Urban Fire Dynamics Simulator (WFDS), with the ultimate goal of developing a standard set of surface fuel models that allows for the flexibility of integrating a range of field measurements. This will help bridge the gap between large-scale spatial fuel mapping projects such as LANDFIRE and these emerging physics-based fire models.
The final component of this project is to perform model simulations to evaluate the sensitivity of physics-based fire models to key physio-chemical inputs at scales from leaves to plots in an effort to determine important fuel characteristics and to refine field sampling protocols to accommodate these models. Using laboratory burns, researchers will be able to determine how well physics-based models using these fuel characteristics are able to predict fire heat release.
In 2014, branch samples were collected for 11 different tree species found through the Rocky Mountains. Many physical and chemical characteristics, such as moisture content, density, heat content, surface-area-to-volume ratios, and flammability, were measured for each sample. More than 1000 samples were measured during the field season. Preliminary results are consistent with previous studies that show that canopy fuel flammability is most heavily influenced by surface area to volume ratios. However, there are significant species-level differences in the allocation of fine branchwood. These results challenge traditional assumptions used to calculate canopy fuel components such as canopy bulk density. Our results will improve both canopy bulk density calculations used to support operational fire behavior models and biomass allocations in fire models based on computational fluid dynamics. Future work will integrate these findings into WFDS to evaluate the impacts of species-specific physio chemical differences on crown fuel flammability and crown fire spread.