Examining the effects of tree structure on wildfire using voxelized terrestrial remote sensing data and computational fluid dynamics fire modeling

Background/Question/Methods

Forests are experiencing an increase in both wildfire severity and frequency, especially in the Western United States. While forested ecosystems span over landscapes, individual tree structure can have profound effects on localized fire behavior. The total biomass of trees is frequently measured as input to fire behavior models, but little specific information about the vertical and horizontal distribution of biomass is included in these models. Detailed and easily acquired structural data from terrestrial laser scanning (TLS), as well as advancements in computational fluid dynamics fire models have opened opportunities to closely study the fuel-fire relationship at a tree-level. We utilized voxelized TLS data with the Wildland Urban Interface Fire Dynamics Simulator (WFDS) to examine how horizontal and vertical fuel variability in a tree changes its energy release and fuel as a result of wildfire. We hypothesized that increased vertical and horizontal discontinuity would lower relative energy release and fuel consumption in all studied species. TLS data were collected at two field sites in Northern California (mixed conifer and oak woodland), in 2020 and 2021. The study sites had either management (thinning) or a natural wildfire between data collection years, allowing for both pre- and post- disturbance variability in tree structure.

Results/Conclusions

Initial results suggest that while general horizontal and vertical fuel discontinuity reduced relative energy release and fuel consumption, this relationship is not the same across species and forest types. In particular, pine and fir species in the mixed conifer forest showed the largest reduction in energy release and fuel consumption with increased horizontal and vertical discontinuity. Model outputs in oak woodland species were less sensitive to fuel distribution, except when relatively rare conifer species were present. This study supports the idea that diverse and heterogeneous tree structure may be important to reduce both fire intensity and severity, and should be considered when developing management strategies in light of wildfire. Additionally, the effective combination of TLS and WFDS highlights the potential value in utilizing remote sensing datasets in combination with computational fluid dynamics fire models.