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FLAME – Fireline Assessment Method | Print |

Image: FLAME logoThere is a clear need for a practical and systematic method of assessing fire behavior and of predicting impending changes, based on fire science.

The FireLine Assessment MEthod (FLAME) provides a fireline-practical tool for predicting significant changes in fire rate-of-spread (ROS) and actual spread times, using a minimum of inputs and a simple process. It is based on standard fire models and actual observations. FLAME addresses the dominant drivers of large, short-term change: effective wind speed, fuel type, and fine-fuel moisture. Primary output is the ROS-ratio, expressing the degree of change in ROS. The ROS-ratio can be applied to observed fire spread to provide a timeline of future fire spread.  For more information please contact the NWCG Fire Behavior Subcommittee.

PRINCIPAL INVESTIGATOR

Jim Bishop, Retired CalFire

CO-INVESTIGATOR

Wayne Cook, Retired USDA Forest Service

GOALS AND OBJECTIVES

The need, in brief—There are two important things to do, and the application of FLAME in training and on the fireline supports both needs.
1. Provide a systematic, practical, and effective tool to firefighters for evaluating fire behavior on the fireline…a tool that can be learned in the classroom and then taken right into the field.
2. More effectively communicate and instill the important points of basic fire behavior training (as in S-290 Intermediate Fire Behavior) by active application in realistic exercises by the students.

KEY RESULTS

What does it tell you?—To support the needs of a firefighter in making safety and suppression decisions FLAME application yields these three important results:

1. First, the identity and timing of the ‘next big change’—Knowing the nature and timing of the pending change allows firefighters, first of all, to be aware of that potential, and also to better monitor the environment and maximize the value of fireline lookouts.

2. Next, the magnitude of that change (expressed as the ROS-ratio, the degree of relative increase or decrease in ROS)—knowing the magnitude of the impending change alerts the firefighter to the level of possible danger. A large ROS-ratio might well be viewed as a universal “common denominator”.

3. Finally, an estimate of the timing of the fire’s advance—knowing the fire spread-time allows rational planning of escape routes and timing, as well as informing well-chosen tactics.

All in all, the FLAME information provides a solid basis for the implementation of LCES (Lookouts, Communications, Escape routes, Safe zones), and enhances “situational awareness”. It is, first and foremost, a tool for making sound safety decisions on the fireline, but also provides relevant information for tactical decisions.

FUNDING ORGANIZATIONS

U.S. Forest Service, Rocky Mountain Research Station, Fire, Fuel, and Smoke Science Program and National Wildfire Coordinating Group, Fire Environment Working Team, Fire Behavior Committee

PUBLICATIONS AND PRODUCTS

Parts 1 and 2 of the FLAME publication pdf_iconcan be read independently, but share the Appendices and References.

Part 1
The application process guides and instills a systematic methodology, utilizing a simple worksheet. The information developed provides a basis for safety judgments and for applying LCES. Compared to four BehavePlus examples FLAME and four fireline-fatality cases FLAME produces realistic predictions, and in every fatality case could have foretold the rapid changes that impacted the crews. Adjustment factors account for variations of wind speed across terrain, and for flame height and sheltering by vegetation. Field application of FLAME is explained and demonstrated with examples.

Part 2
The characteristic magnitudes of the ROS changes for all factors are assessed quantitatively, and for short-term change effective wind speed (EWS) and fuel-type dominate ROS change, with fine-fuel moisture (FFM) a secondary influence. The curves that define the relationship between ROS and EWS for each fuel-type are derived from a combination of model outputs and observations, and expressed as power functions. The equation for the ROS-ratio is derived from those power functions. Both analytical and data-based sources of error are quantitatively assessed. Compared to four BehavePlus examples FLAME matches within an average of 14%. In four fireline-fatality cases FLAME predictions match reconstructed ROS-ratios with an average error of 9%. Adjustment factors are derived to account for variations of wind speed across terrain, and for flame height and sheltering by vegetation. Application sheet of the FLAME Field Guide is illustrated.