Experimental procedures characterizing firebrand generation in wildland firesAuthor(s): Mohamad El Houssami; Eric Mueller; Alexander Filkov; Jan C Thomas; Nicholas Skowronski; Michael R Gallagher; Ken Clark; Robert Kremens; Albert. Simeoni
Source: Fire Technology. 52(3): 731-751.
Publication Series: Scientific Journal (JRNL)
Station: Northern Research Station
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DescriptionThis study aims to develop a series of robust and efficient methodologies, which can be applied to understand and estimate firebrand generation and to evaluate firebrand showers close to a fire front. A field scale high intensity prescribed fire was conducted in the New Jersey Pine Barrens in March 2013. Vegetation was characterised with field and remotely sensed data, fire spread and intensity was characterised and meteorological conditions were monitored before and during the burn. Firebrands were collected from different locations in the forest and analysed for mass and size distribution. The majority were found to be bark slices (more than 70%) with substantial amounts of pine and shrub twigs. Shrub layer consumption was evaluated to supplement the firebrand generation study. Bark consumption was studied by measuring the circumference variation at several heights on each of three different pine trees. The variation was in the same order of magnitude as the bark thickness (1–5 mm). Testing and improving the protocol can facilitate the collection of compatible data in a wide range of ecosystems and fire environments, aiding in the development of solutions to prevent structural ignition at the Wildland Urban Interface.
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El Houssami, Mohamad; Mueller, Eric; Filkov, Alexander; Thomas, Jan C; Skowronski, Nicholas; Gallagher, Michael R; Clark, Kenneth; Kremens, Robert; Simeoni, Albert. 2016. Experimental procedures characterizing firebrand generation in wildland fires. Fire Technology. 52(3): 731-751.
KeywordsFirebrands, Generation, Pine forest
- Investigation of firebrand generation from an experimental fire: Development of a reliable data collection methodology
- Remotely sensed measurements of forest structure and fuel loads in the Pinelands of New Jersey
- Application of ground-based LIDAR for fine-scale forest fuel modeling
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