________________________________________This report describes a new set of standard fire behavior fuel models for use with Rothermel's surface fire spread model and the relationship of the new set to the original set of 13 fire behavior fuel models. To assist with transition to using the new fuel models, a fuel model selection guide, fuel model crosswalk, and set of fuel model photos are provided.Keywords: fire behavior prediction, fire modeling, surface fuel, dynamic fuel model The Authors _____________________________________ Joe H. Scott has been a Forester with Systems for Environmental Management, a nonprofit research group based in Missoula, MT, since 1996. He is the lead developer of NEXUS, a system for assessing crown fire potential; lead developer of FireWords, an annotated, electronic glossary of fire science terminology; and codeveloper of FuelCalc, a system for computing, summarizing, and formatting ground, surface, and crown fuel characteristics from standard inventory methods. Scott has participated in several investigations of surface and canopy fuel characteristics. He has a B.S. degree in forestry and resource management from the University of California at Berkeley and an M.S. degree in forestry from the University of Montana. On page 45, the description for the high load, dry climate shrub stated that "The moisture of extinction is high. " It was corrected to say "The moisture of extinction is low. " Robert E. Burgan retired as a SupervisoryYou may order additional copies of this publication by sending your mailing information in label form through one of the following media. Please specify the publication title and number.

PMS 439-1 MAY 1984 NFES 0275 This file was created by scanning the printed publication. Errors identified by the software have been corrected; however, some errors may remain.

This paper was presented at the conference ‘Integrating spatial technologies and ecological principles for a new age in fire management’, Boise, Idaho, USA, June 1999 Fuel maps are essential for computing spatial fire hazard and risk and simulating fire growth and intensity across a landscape. However, fuel mapping is an extremely difficult and complex process requiring expertise in remotely sensed image classification, fire behavior, fuels modeling, ecology, and geographical information systems (GIS). This paper first presents the challenges of mapping fuels: canopy concealment, fuelbed complexity, fuel type diversity, fuel variability, and fuel model generalization. Then, four approaches to mapping fuels are discussed with examples provided from the literature: (1) field reconnaissance; (2) direct mapping methods; (3) indirect mapping methods; and (4) gradient modeling. A fuel mapping method is proposed that uses current remote sensing and image processing technology. Future fuel mapping needs are also discussed which include better field data and fuel models, accurate GIS reference layers, improved satellite imagery, and comprehensive ecosystem models.

The National Fire-Danger Rating System (NFDRS), implemented in 1972, was revised during a 3-year project (1975 to 1978) and reissued as the 1978 NFDRS. This report describes the developmental history of the NFDRS and its technical foundation. Detailed information is provided on modeling forest fuels and fuel moisture, and on development of the NFDRS components and indexes. The report presents equations used in the 1978 NFDRS and an extensive bibliography.

We present a probability-based model for estimating fire risk. Risk is defined using three probabilities: the probability of fire occurrence; the conditional probability of a large fire given ignition; and the unconditional probability of a large fire. The model is based on grouped data at the 1 km2-day cell level. We fit a spatially and temporally explicit non-parametric logistic regression to the grouped data. The probability framework is particularly useful for assessing the utility of explanatory variables, such as fire weather and danger indices for predicting fire risk. The model may also be used to produce maps of predicted probabilities and to estimate the total number of expected fires, or large fires, in a given region and time period. As an example we use historic data from the State of Oregon to study the significance and the forms of relationships between some of the commonly used weather and danger variables on the probabilities of fire. We also produce maps of predicted probabilities for the State of Oregon. Graphs of monthly total numbers of fires are also produced for a small region in Oregon, as an example, and expected numbers are compared to actual numbers of fires for the period 1989–1996. The fits appear to be reasonable; however, the standard errors are large indicating the need for additional weather or topographic variables.

National Fire-Danger Rating System does not work well in the humid environment of the Eastern United States. System modifications to correct problems and their operational impact on System users are described. A new set of 20 fuel models is defined and compared graphically with the 1978 fuel models. Technical documentation of System changes is provided.

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The basic concepts of fuel modeling were presented in the fuel subsystem of BEHAVE. This report expands on these concepts in an attempt to provide a better understanding of the technical details of constructing sitespecific fire behavior fuel models. The discussion is mathematical. It is aimed at fire managers who are familiar with the fire model and who may be dealing with difficult fuels situations.