Modeling prescribed burns to serve as regional firebreaks to allow wildfire activity in protected areas

Citation:

Suffling, R. , Grant, A. , & Feick, R. . (2008). Modeling prescribed burns to serve as regional firebreaks to allow wildfire activity in protected areas. Forest Ecology and Management, 256(11), 1815-1824. Elsevier.

Abstract:

Management around wilderness parks ideally requires thorough fire suppression in proximate settled and commercially exploited lands and natural fire within protected areas. To satisfy these requirements, we explored a potential regional firebreak (firewall) based on a series of prescribed burns in Quetico Provincial Park in northwestern Ontario, Canada. Fire managers were recruited each to independently devise a regional firebreak using simulated prescribed burns. The experts’ five designs consisted of between 9 and 25 prescribed burns, set over periods ranging from 3 to 8 years, and covering from 7900 to 26,100 ha. Each wildlife ignition was run after the entire firebreak was created and the vegetation was reclassified to account for post-fire vegetation re-growth. The potential efficacy of each design was tested using worst-case historical weather and 100 random ignitions in the Prometheus fire growth simulation model. Without a firewall, 100 ignitions resulted in 69 fires escaping the park and consuming 483,900 ha of forest beyond the park boundary. The firewall designs were all effective, reducing the area burned outside the park to between 15,400 and 35,400 ha. There was a 77–90% reduction in the number of fires escaping the firewall areas and an average reduction of fire area beyond the park of 92%. Moreover, one can map the geographic weak points in each design, which encourages iterative firebreak design improvements. For instance, firewalls set nearer the park boundary allowed fewer fires to start between the firewall and the boundary, so increasing firebreak effectiveness. The cost of the above systems can be regarded as taking preventative measures against the risk of future economic loss, and the modeling approach reduces the uncertainties in associated decision making.

Notes:

Last updated on 10/17/2016