Exploring Fuel Spatial Heterogeneity Scales with QUIC-Fire

Abstract:

High spatial variability has been observed in many fuelbeds, accentuating the need to model the influence of fine scale variation in fuel properties on coupled-fire atmospheric interactions, particularly for low intensity fires. Relying on abstract representations of fine-scale variation may have unintended consequences for predicting larger scale fire behavior. Working with high resolution 3D datasets, application of terrestrial laser scanner information of longleaf pine forests in the Southeast US were used to create voxelized data arrays containing bulk density and fuel height for surface fuels <1m on a horizontal resolution of 0.5m². These data were used to populate the 3D vegetation, with fuel assigned to voxels depending on tree inputs including tree location, height, height to live crown, crown radius, and crown concavity. The new coupled-fire atmospheric fire behavior model QUIC-Fire was used to explore the result of aggregating this sampled variation on increasingly large cell resolutions of 2, 4, 6, 8, 16, and 32 m, as well as using a single fuel characteristic for the entire plot. QUIC-Fire simulations under a full range of wind and dead fuel moisture conditions common to prescribed and wildland fires were executed to represent potential ranges of fire intensity, since it is possible that fuel resolution is only relevant for fire intensities produced under a particular threshold of wind speed, moisture content, or some combination of each. Using QUIC-Fire in an ensemble fashion allows us to examine the inherent variability for each environmental condition and scale of resolution, and allows us to test the fire behavior model result’s sensitivity to the scale of resolution.