Assessing Crown Fire Potential by Linking Models of Surface and Crown Fire Behavior
By Joe H. Scott, E. Reinhardt. 2003
637 citations recorded by the source corpus.
Assessing crown fire potential by linking models of and behavior. Fire managers are increasingly concerned about the threat of crown fires, yet only now are quantitative methods for assessing crown fire hazard being developed. Links among existing mathematical models of fire behavior are used to develop two indices of crown fire hazard—the Torching Index and Crowning Index. These indices can be used to ordinate different forest stands by their relative susceptibility to crown fire and to compare the effectiveness of crown fire mitigation treatments. The coupled model was used to simulate the wide range of fire behavior possible in a forest stand, from a low-intensity surface fire to a high-intensity active crown fire, for the purpose of comparing potential fire behavior. The hazard indices and behavior simulations incorporate the effects of surface fuel characteristics, dead and live fuel moistures (surface and crown), slope steepness, canopy base height, canopy bulk density, and wind reduction by the canopy. Example simulations are for western Montana Pinus ponderosa and Pinus contorta stands. Although some of the models presented here have had limited testing or restricted geographic applicability, the concepts will apply to models for other regions and new models with greater geographic applicability. studies of fuel tree and This paper presents a method of assessing crown fire potential by linking separate models of surface fire spread and intensity, crown fire spread rate, and transition to crown fire. Three indices of crown fire potential are computed from a description of surface fuels, canopy fuels, and site characteristics. The Torching Index is the open windspeed at which the transition from surface to crown fire is expected. The Crowning Index is the open windspeed at which fully active crown fire is possible. The Surfacing Index is the open windspeed at which an active crown fire is expected to cease, either from failure to meet the minimum mass-flow rate or from failure of the after-crowning contribution of surface fuels to fireline intensity to meet the minimum necessary for crown fire initiation. From The accuracy simulations improved model results onsite
Subfields: Global and Planetary Change, Ocean Engineering, Safety, Risk, Reliability and Quality
View Paper: https://www.semanticscholar.org/paper/40927f4e1edc3b499095e13af47292ac48a9ea46
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In Global and Planetary Change
In Ocean Engineering
- A. Ager
- Mark Finney
- Peter Z. Fulé
- M. Passovoy
- T. Hamilton
- Carl N. Skinner
- N. Vaillant
- Martin Ritchie
In Safety, Risk, Reliability and Quality
- A. Ager
- Mark Finney
- Peter Z. Fulé
- M. Passovoy
- T. Hamilton
- Carl N. Skinner
- N. Vaillant
- Martin Ritchie
Citations in the corpus
- Estimating forest canopy bulk density using six indirect methods (2005, methodology): “To reduce the total number of possible equations, we selected only one canopy metric, CBDmax (maximum CBD across all 1-m canopy layers, Table 3), because it best represented the CBD needed to model crown fire behavior ( Scott and Reinhardt 2001, 2002; van Wagner 1977).”
- Snag and woody debris dynamics following severe wildfires in northern Arizona ponderosa pine forests (2006, methodology): “Contemporary fire behavior models commonly used in the United States such as Behave (Andrews, 1986), Farsite (Finney, 1998), and Nexus (Scott and Reinhardt, 2001) are based on Rothermel’s (1972) surface fire behavior model, which is primarily influenced by fine fuels ( 7.6 cm diameter).”
- Estimating canopy fuel characteristics in five conifer stands in the western United States using tree and stand measurements (2006, background): “Canopy bulk density is an important determinant of crown-fire occurrence in fire-modeling systems such as FARSITE (Finney 1998), NEXUS (Scott 1998), and BehavePlus (Andrews et al. 2005).”
- Crown fire behaviour in a northern jack pine-black spruce forest (2004, methodology): “This realization, coupled with the need to improve upon the predictive capability of the (Rothermel 1991) crown fire rate of spread model (Scott and Reinhardt 2001; Pastor et al. 2003), were principal factors in the genesis of the International Crown Fire Modelling Experiment (ICFME).”
- Evaluating wildland fire danger and prioritizing vegetation and fuels treatments (2007, methodology): “…(CBH) represents the level above the ground at which there is enough aerial fuel to carry the fire into the canopy, and it is defined as the height from the ground to the bottom of the live canopy (Scott and Reinhardt, 2001) but may also include dense, dead crown material that can carry a fire.”
- Modeling wildfire risk to northern spotted owl (Strix occidentalis caurina) habitat in Central Oregon, USA (2007, methodology): “FVS-FFE uses several fire behavior models as described in Andrews (1986), Van Wagner (1977) and Scott and Reinhardt (2001) to predict fire spread, intensity and crown fire initiation.”
- Invasive grasses: A new perfect storm for forested ecosystems? (2020, background): “It is well known that tree torching (individual tree burning) and forest crown fire initiation generally requires a substantial surface fire (Wagner, 1977; Scott and Reinhardt, 2001).”
- Probability of tree survival after wildfire in an interior pine forest of northern California: Effects of thinning and prescribed fire (2007, methodology): “Stand height is the average height of the five tallest trees on each plot ( Scott and Reinhardt, 2001 ).”
- Perpetuating old ponderosa pine (2007, background): “Understory trees have the potential to torch and increase crown scorch to old trees during prescribed burning (Scott and Reinhardt, 2001).”
- A comparison of landscape fuel treatment strategies to mitigate wildland fire risk in the urban interface and preserve old forest structure (2010, positive): “FVS-FFE incorporates several fire behavior models as described in Andrews (1986), Van Wagner (1977), and Scott and Reinhardt (2001) to predict rate of spread, intensity, and crown fire initiation.”