United States Rocky Mountain

Department Research Station

of Agriculture

General Technical

Forest Service Report RMRS-GTR-192

May 2007

Nomographs for 

Estimating Surface Fire 

Behavior Characteristics

Joe H. Scott
CORRECTIONS FOR 

RMRS GTR-192 

Nomographs for estimating surface fire behavior characteristics 

A pervasive mislabeling has been discovered in the wind vectoring charts within 

RMRS-GTR-192. The label for the wind direction 315 degrees clockwise from upslope 

(upper-left quadrant of the chart; 45 degrees anticlockwise) is erroneously labeled 

“305”. This error occurs on every wind vectoring chart in the report, including the 

examples. The correct label should be “315”, as shown below. 

The labels have been corrected in the electronic format of the GTR, as well as in the 

PDF files available at the website of the Fire Modeling Institute (www.fs.fed.us/fmi). 
The Author ______________________________________

Joe H. Scott is a Research Forester with Systems for Environmental Management 

in Missoula, Montana. Joe earned a B.S. in Forestry and Resource Management from 

the University of California at Berkeley, and an M.S. in Forestry from the University 

of Montana. He is a Certified ForesterTM as recognized by the Society of American 

Foresters.

Acknowledgments________________________________

I thank Don Carlton, Fire Program Solutions, for suggesting the simplified nomograph 

format; Cassie Koerner and Violet Holley, Missoula Fire Sciences Lab, for formatting and 

error-checking the charts; and Bret Butler and Dan Jimenez, Missoula Fire Sciences 

Lab, and Laurie Kurth, Fire Modeling Institute, for reviewing the draft manuscript. Funding for preparation and publication of the nomographs was provided by the U.S. Forest 

Service Washington Office fire technology transfer program, and by the Fire Modeling 

Institute, Missoula Fire Sciences Lab, Rocky Mountain Research Station, U.S. Forest 

Service. Brad Reed coined the term “hanking” fire behavior (referring to fire behavior 

between the head and flank of the fire).

Abstract _________________________________________

A complete set of nomographs for estimating surface fire rate of spread and flame length for the 

original 13 and new 40 fire behavior fuel models is presented. The nomographs allow calculation 

of spread rate and flame length for wind in any direction with respect to slope and allow for nonheading spread directions. Basic instructions for use are included.

Keywords: rate of spread, flame length, fire behavior prediction, fuel model

You 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.

Telephone (970) 498-1392

FAX (970) 498-1122

E-mail rschneider@fs.fed.us

Web site http://www.fs.fed.us/rm

Mailing Address Publications Distribution

Rocky Mountain Research Station

240 West Prospect Road

Fort Collins, CO 80526

Scott, Joe H. 2007. Nomographs for estimating surface fire behavior characteristics. Gen. 

Tech. Rep. RMRS-GTR-192. Fort Collins, CO: U.S. Department of Agriculture, Forest Service, 

Rocky Mountain Research Station. 119 p.
Contents____________________________________________

 Page

Introduction. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1

Gathering Inputs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1

Estimating Fire Behavior with Nomographs. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4

Step 1: Effective midflame wind speed . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4

Step 2: Head fire rate of spread and flame length. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5

Step 3: Non-heading rate of spread and flame length. . . . . . . . . . . . . . . . . . . . . . . . . . 8

Summary. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9

References. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10

Appendix A—Fire Behavior in Non-heading Spread Directions. . . . . . . . . . . . . . . . . . . . . 11

Non-heading Fire Behavior Nomograph . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13

Appendix B—Nomgraphs. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14

Fire Behavior Nomograph Worksheet. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14

Original 13 Fuel Models. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15

Grass (GR) Fuel Models . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 43

Grass-shrub (GS) Fuel Models. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 63

Shrub (SH) Fuel Models . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 73

Timber-understory (TU) Fuel Models. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 93

Timber Litter (TL) Fuel Models. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 105

Slash-blowdown (SB) Fuel Models . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 115
Federal Recycling Program Printed on Recycled Paper
USDA Forest Service Gen. Tech. Rep. RMRS-GTR-192. 2007 

Introduction

	 A nomograph is a visualrepresentation of numerical

relationships. Nomographs are useful for graphically

illustrating sensitivity of a model to its inputs, as well

as for estimating model outputs without a computer.

Albini (1976) produced a set of nomographs for estimating wildland fire behavior characteristics for the

original 13 fire behavior fuel models (Albini 1976,

Anderson 1982) based on Rothermel’s (1972) surface

fire spread model. Albini’s nomographs calculated

fire characteristics in the heading direction only. The

effect of wind speed could only be calculated in the

upslope direction.

	 Andrews (1986) produced a computer program for

estimating wildland fire behavior—the BEHAVE fire

behavior modeling system. At this time, computers

were not readily available to Fire Behavior Officers

while on fire assignments or for fire behavior training courses, so the nomographs continued to receive

frequent use even after the advent of BEHAVE. Today,

Fire Behavior Analysts still use Albini’s nomographs

for making simple fire behavior predictions when

a computer is not available. An additional set of 40

standard fire behavior fuel models was recently made

available (Scott andBurgan 2005).ManyFireBehavior

Analysts requested that nomographs be created for

those fuel models.

	 There are three significant changes in format and

operation with these new nomographs. First, the limitation to upslope wind direction has been eliminated

with the development of a separate chart for combining the effects of wind speed, wind direction, and

slope steepness. Second, the limitation to computing

fire behavior in the heading direction only has been

eliminated with the development of a separate chart

for reducing head fire spread rate and flame length to

appropriate values for non-heading spread directions.

Finally,the nomographs have been reformatted to focus

on primary model inputs (fuel moisture and effective

midflame wind speed) and primary outputs (rate of

spread and flame length). The original format allowed

the user to compute intermediate model results (reaction intensity and propagating flux). The new format

estimates outputs directly,withoutshowing intermediate results. For sake of completeness, nomographs for

the original 13 fuel models have been created in the

new format.

Gathering Inputs

	 Gathering the required inputs is the first step in using the nomographs (Procedures for selecting a fuel

model and estimating other input values are covered

in training courses and other reports.). Inputs are required in the following categories: fuel and moisture,

wind and slope, and spread direction. All inputs and

outputs can be recorded on the nomograph worksheet

provided in this report (p. 14).

Fuel and Moisture Inputs—The first fuel input to

specify is the fuel model. Any of the original 13 or

new 40 fire behavior fuel models may be selected.

	 Dead fuel moisture content is a required input for all

fuel models. To be consistent with predictions made

with computerized fire behavior prediction systems,

the dead fuel moisture content input should be the

surface-area-weighted average moisture content ofthe

1-, 10-, and 100-h timelag classes (Rothermel 1972).

Weighting factors vary by fuel model, but in all cases

are weighted heavily toward the 1-h timelag class

(table 1). Therefore, the moisture content of the 1-h

timelag class can be used for the dead fuel moisture

input without significant error. For more precision, or

to match the results from computerized applications,

compute the weighted-average dead fuel moisture using the weighting factors listed in table 1.

	 Live herbaceous (LHMC) and live woody moisture

content(LWMC)inputs are required only ifthe selected

fuel model contains fuel in one of those components

(see table 1). LHMC has a strong effect on predicted

fire behavior in the new fuel model set (Jolly 2005)

Nomographs for Estimating Surface Fire 

Behavior Characteristics

Joe H. Scott
USDA Forest Service Gen. Tech. Rep. RMRS-GTR-192. 2007

because dynamic load transfer is tied to LHMC (Scott

and Burgan 2005). Dynamic load transfer is the

simulation of curing in herbaceous fuels by shifting

herbaceous fuel load from the live component to dead

where ittakes on themoisture content ofthe 1-h timelag

class. The transfer of live herbaceous load to dead is a

function of LHMC (Burgan 1979), on the assumption

thatLHMCdecreases as curing takes place.ForLHMC

≥ 120 percent, no herbaceous load is transferred to 

dead; all herbaceous fuel is green and at the specified

LHMC, and fire behavior is correspondingly benign.

For LHMC ≤ 30 percent, all herbaceous load is transferred to dead; none remains in the live component,

and fire behavior is at its maximum potential for the

fuel model. For LHMC between 30 and 120 percent, a

fraction of the load is transferred to dead (fig. 1). The

degree of curing is therefore an important factor for

determining a LHMC value (see table 2).

Wind and Slope Inputs—Slope steepness for the

nomographs is measured in percent. Estimating slope

to the nearest 10 percent is sufficient.

	 An estimate of midflame wind speed is required,

and can be estimated by direct observation or by multiplying 20-ft wind speed by a wind adjustment factor

(WAF). On flat terrain, WAF can be determined using

tables based on Albini and Baughman’s(1979) models

of wind reduction. Those same models are used in

BehavePlus, FARSITE, and FlamMap. If the surface

fuelbed in question is sheltered by a forest canopy

(canopy cover greater than 5 percent), use table 3,

otherwise, use table 1.

Table 1—Weighting factors for calculating weighted-average 

dead fuel moisture content, presence of live fuel 

component, and wind adjustment factor (WAF) 

for the original 13 and new 40 fire behavior fuel 

models. Weighting factors assume all herbaceous 

load is in the 1-h class (full curing). WAF values 

were estimated using Albini and Baughman’s (1979) 

model of wind reduction over exposed fuelbeds on 

flat terrain assuming flame height is twice fuelbed 

depth. Values in this table match those used in 

BehavePlus, FARSITE, and FlamMap.

Weighting factors Live fuel

Fuel model 1-h 10-h 100-h Herb Woody WAF

 1 1.00 0.00 0.00 0.36

	 2	 0.98	 0.02	 0.00	 √	 	 0.36

3 1.00 0.00 0.00 0.44

	 4	 0.95	 0.04	 0.01	 	 √	 0.55

	 5	 0.97	 0.03	 0.00	 	 √	 0.42

6 0.89 0.09 0.02 0.44

	 7	 0.89	 0.09	 0.02	 	 √	 0.44

8 0.94 0.03 0.02 0.28

9 0.99 0.01 0.00 0.28

	 10	 0.94	 0.03	 0.02	 	 √	 0.36

 11 0.77 0.17 0.06 0.36

 12 0.75 0.19 0.06 0.43

 13 0.76 0.18 0.06 0.46

	 GR1	 1.00	 0.00	 0.00	 √	 	 0.31

	 GR2	 1.00	 0.00	 0.00	 √	 	 0.36

	 GR3	 0.98	 0.02	 0.00	 √	 	 0.42

	 GR4	 1.00	 0.00	 0.00	 √	 	 0.42

	 GR5	 1.00	 0.00	 0.00	 √	 	 0.39

	 GR6	 1.00	 0.00	 0.00	 √	 	 0.39

	 GR7	 1.00	 0.00	 0.00	 √	 	 0.46

	 GR8	 0.99	 0.01	 0.00	 √	 	 0.49

	 GR9	 0.99	 0.01	 0.00	 √	 	 0.52

	 GS1	 1.00	 0.00	 0.00	 √	 √	 0.35

	 GS2	 0.97	 0.03	 0.00	 √	 √	 0.39

	 GS3	 0.99	 0.01	 0.00	 √	 √	 0.41

	 GS4	 1.00	 0.00	 0.00	 √	 √	 0.42

	 SH1	 0.97	 0.03	 0.00	 √	 √	 0.36

	 SH2	 0.90	 0.09	 0.01	 	 √	 0.36

	 SH3	 0.69	 0.31	 0.00	 	 √	 0.44

	 SH4	 0.93	 0.07	 0.00	 	 √	 0.46

	 SH5	 0.92	 0.08	 0.00	 	 √	 0.55

	 SH6	 0.93	 0.07	 0.00	 	 √	 0.42

	 SH7	 0.80	 0.18	 0.02	 	 √	 0.55

	 SH8	 0.80	 0.19	 0.01	 	 √	 0.46

	 SH9	 0.96	 0.04	 0.00	 √	 √	 0.50

	 TU1	 0.84	 0.11	 0.05	 √	 √	 0.33

	 TU2	 0.89	 0.09	 0.02	 	 √	 0.36

	 TU3	 0.99	 0.01	 0.00	 √	 √	 0.38

	 TU4	 1.00	 0.00	 0.00	 	 √	 0.32

	 TU5	 0.92	 0.07	 0.01	 	 √	 0.36

TL1 0.85 0.10 0.05 0.28

TL2 0.90 0.08 0.02 0.28

TL3 0.76 0.18 0.06 0.29

TL4 0.78 0.13 0.10 0.31

TL5 0.85 0.10 0.05 0.33

TL6 0.97 0.03 0.01 0.29

TL7 0.60 0.15 0.24 0.31

TL8 0.98 0.01 0.00 0.29

TL9 0.96 0.03 0.01 0.33

SB1 0.82 0.09 0.09 0.36

SB2 0.94 0.05 0.01 0.36

SB3 0.97 0.03 0.01 0.38

SB4 0.95 0.03 0.01 0.45

Figure 1—Transfer of live herbaceous load to dead 

herbaceous load as a function of live herbaceous moisture 

content (LHMC). If necessary, use the observed degree of 

curing (fraction of load transfer) of the herbaceous fuels to 

determine a value for LHMC. 
USDA Forest Service Gen. Tech. Rep. RMRS-GTR-192. 2007

	 Wind direction for the nomographs is the direction

the wind is pushing the fire, and is entered in degrees

clockwise from upslope. For example, a cross-slope

wind blowing from left to right (while facing upslope)

is pushing the fire in the direction 90 degrees clockwise

from upslope.

Spread Direction—Basic nomograph outputs are

rate of spread and flame length in the direction of

maximumspread—the heading direction.By assuming

fire spreads as a simple ellipse, spread rate and flame

length can also be estimated in otherspread directions

(see Appendix A). Flanking fire behavior occurs at

the widest part of the ellipse where the flame front is

Table 2—Live herbaceous moisture content 

(LHMC) values to use for various 

degrees of curing. LHMC in the 

nomographs is linked to degree of 

curing, meaning herbaceous fuel is 

transferred from live to dead as a 

function of LHMC.

 Degree of curing LHMC (percent)

Fully cured 30

Two-thirds cured 60

One-half cured 75

One-third cured 90

Uncured (fully green) 120

Table 3—Wind adjustment factor (WAF) for 

surface fuel sheltered by a forest 

canopy (canopy cover greater than 

5 percent), as a function of canopy 

cover (CC). WAF values were 

stylized for this table based on 

output from Albini and Baughman’s 

(1979) model of wind reduction by 

a forest canopy. See table 1 for 

WAF values to use for unsheltered 

fuelbeds.

Canopy cover

(percent) WAF

CC ≤ 5	 use table 1

5 < CC ≤ 10	 0.30

10 < CC ≤ 15	 0.25

15 < CC ≤ 30	 0.20

30 < CC ≤ 50	 0.15

CC > 50 0.10

Figure 2—Locations of heading, hanking, 

flanking, and backing spread calculations 

around an elliptical fire. Heading fire 

calculations are made for the direction of 

maximum spread. Flanking fire calculations 

are made for the widest part of the ellipse, 

where the fire front is oriented perpendicular 

to the maximum spread direction. Backing 

fire calculations are made for the rear of the 

fire, directly opposite the maximum spread 

direction. Hanking fire calculations are made 

for the point on the perimeter where the 

flame front is oriented 45 degrees away from 

the maximum spread direction (The term 

“hanking” refers to fire behavior between the 

head and flank of a fire.).

oriented perpendicular to the heading direction, while

backing fire behavior occurs at the rear (directly opposite the heading direction). The chart also allows

calculation of “hanking” fire behavior—fire behavior

between the head and flank of a fire—where the flame

front is oriented 45 degrees off the heading direction

(fig. 2).
USDA Forest Service Gen. Tech. Rep. RMRS-GTR-192. 2007

Estimating Fire Behavior 

With Nomographs

	 Once the inputs are gathered, estimating fire behavior

with nomographsis a three-step process. The firststep

isto estimate effective midflame wind speed using the

wind vectoring chart provided with each nomograph.

The next step is to estimate rate of spread and flame

length in the direction of maximum spread. For this

step, nomograph format and use depends on whether

the selected fuel model contains a live fuel component

(either herbaceous or woody). In the new fuel model

set, only the timber litter (TL) and slash/blowdown

(SB) fuel models do not have a live fuel component;

the grass(GR), grass-shrub (GS),shrub (SH), and timber-understory (TU) fuel models contain herbaceous

and/or woody fuel. Original fuel models 2, 4, 5, 7, and

10 contain live fuel; 1, 3, 6, 8, 9, and 11 through 13 do

not. The final step, if necessary, is to estimate rate of

spread and flame length in a non-heading direction.

This is accomplished with a single chart applicable

to all fuel models. These three steps are described

separately in the following sections.

Step 1: Effective Midflame 

Wind Speed

	 The procedure for estimating effective midflame

wind speed is the same for all fuel models, but there

is a unique pair of wind vectoring charts for each fuel

model, one for low wind speeds and another for high.

If you are not certain whether the effective wind speed

will be low or high, start with the chart for low wind

speeds and switch to the higher one if necessary. For

fuel models without a live fuel component, both vectoring charts are on the same page. For fuel models

with a live herbaceous or live woody fuel component,

the vectoring charts are on separate pages.

	 Estimation of midflame wind speed will be demonstrated with the following example: fuel model TL5,

slope steepness 60 percent, midflame wind speed

7 mi/h, and wind direction 135 degrees clockwise

from uphill. Inputs and results for this and following examples are shown in a nomograph worksheet

(fig. 3).

	 1)	 Select the nomograph and wind vectoring chart.

	 Select the nomograph for TL5, and then locate the

vectoring chart for low wind speeds (the upper “bullseye” chart on the nomograph page).

2)	 Determine the effective midflame wind speed.

	 a.	 Draw a vertical line from the origin of the

concentric circles to the point on the line corresponding to the slope steepness. Interpolate

between tick marks as necessary (fig. 4, line

a).Thisline representsthe slope vector(direction and magnitude of the effect of slope on

fire spread).

	 b.	 Draw a line from the origin of the concentric

circlesin the direction the wind is pushing the

fire. Stop the line at the circle representing

the midflame wind speed (fig. 4, line b). Each

circle represents 1 mi/h wind speed (2 mi/h

for high wind speed nomographs). Interpolate between circles as necessary. Faint gray

diagonal and horizontal lines aid in drawing

lines along common wind directions: quarter

up-slope, cross-slope, and quarter down-slope.

Tick marks around the perimeter of the chart

indicate 15 degree increments of wind direction. The line you have just drawn represents

the wind vector (direction and magnitude of

the effect of wind on fire spread).

	 c.	 Draw a vertical line from the end of the wind

vector(fig. 4,line c).Use the vertical gray lines

on the chart to assist in drawing the line.

	 d.	 Draw a line parallel to the wind vector, beginning from the tip of the slope vector and

continuing to (or beyond) the vertical line

drawn in line c above (fig. 4, line d).

	 e.	 Draw a line from the origin to the intersection

of lines c and d. Thisline isthe effective wind

vector (fig. 4, line e).

	 f.	 The direction of the effective wind vector indicates the direction of maximum fire spread.

Trace thisline to the outer circle, and then read

thedirectiontowithin5degreesclockwisefrom

upslope. For this example, the result is 110 degrees clockwise from upslope (fig. 4, point f).

	 g.	 The length of the effective wind vector indicatesthe effectivemidflamewind speed.Read

that value by interpolating between circles.

For this example, the result is 5.8 mi/h (see

fig. 4).
USDA Forest Service Gen. Tech. Rep. RMRS-GTR-192. 2007

Figure 3—Example Fire Behavior Nomograph Worksheet for recording inputs and 

outputs for the examples in the text. See text for complete instructions.

Step 2: Head Fire Rate of 

Spread and Flame Length

	 The procedure for estimating head fire rate ofspread

and flame length depends on whether the selected

fuel model contains a live fuel component. For fuel

models without live fuel, nomographs for low and

high wind speeds are printed on the same page, and

the only inputs needed are effective midflame wind

speed (from previous step) and dead fuel moisture

content. For fuel models with a live fuel component,

charts for low wind speeds and high wind speeds

are on separate pages. An additional input, live fuel

moisture content, is required to use these charts. The

different procedures for using these nomographs are

presented in the following sections.

Fuel Models Without a Live Component—The

use of a nomograph to estimate fire behavior in the

heading direction for a fuel model without a live

fuel component will be illustrated by continuing the

previous example: Fuel model TL5; slope steepness

60 percent; midflame wind speed 7 mi/h; and wind

direction 135 degrees clockwise fromupslope (quarterdownslope). Resulting effective midflame wind speed

was 5.8 mi/h. Additionally, we will use a dead fuel

moisture content of 5 percent. Inputs and outputs for

this example are displayed on a Fire Behavior Nomograph Worksheet (fig. 3, Projection Point A).

	 1)	 Determine head fire rate of spread and flame

length.

	 a.	 Drawaverticallinebeginningfromthebottom

axis of the chart at a value corresponding to

the dead fuel moisture content—5 percent in

this example (fig. 4, line g).
USDA Forest Service Gen. Tech. Rep. RMRS-GTR-192. 2007

Figure 4—Example nomograph for estimating effective midflame wind speed and head fire rate of spread and flame length 

for fuel model TL5. Inputs: slope steepness = 60 percent; midflame wind speed = 7 mi/h; wind direction = 135 degrees 

clockwise from uphill; and dead fuel moisture content = 5 percent. Results: effective midflame wind speed = 5.8 mi/h; 

direction of maximum spread = 110 degrees; head fire rate of spread = 6 ch/h; and head fire flame length = 2.5 feet. 

Annotations refer to instructions in text.
USDA Forest Service Gen. Tech. Rep. RMRS-GTR-192. 2007

	 b.	 Mark the pointwhere this vertical line crosses

the line forthe effectivemidflame wind speed

determined in the previous example (5.8mi/h).

If necessary, interpolate between lines for effective midflame wind speed. The lines are

labeled at the right-hand axis. For example,

place the mark 80 percent of the way between

the lines for 5 and 6 mi/h effective midflame

wind speeds. Draw a horizontal line from this

point to the left-hand axis. Use the faint gray

lines as a guide (fig. 4, line h).

	 c.	 Read the head fire rate of spread (ch/h) from

the left-hand axis (fig. 4, point i). The result

for this example is 6 ch/h.

	 d.	 Read the head fire flame length (feet) by

interpolating between the curving gray lines

representing flame length (fig. 4, point j). The

result for this example is 2.5 ft.

Fuel Models With a Live Component—The following example inputs will be used to illustrate the use of

a nomograph to estimate head fire behavior for a fuel

model with a live fuel component: Fuel model SH5;

slope steepness 60 percent; no canopy cover; 20-ft

wind speed 7mi/h; upslope wind direction; livewoody

moisture content 110 percent; and dead fuel moisture

content 5 percent. Input and outputs are recorded on a

FireBehaviorNomographWorksheet(fig. 3,Projection

Point B). For this example we will repeat the firststep,

vectoring wind and slope, to illustrate the process for

the upslope wind direction.

	 1)	 Select the nomograph and wind vectoring chart.

	 Select the nomograph for SH5, low wind speeds.

	 2)	 Determine the effective midflame wind speed.

	 We first need to determine midflame wind speed

from the 20-ft wind speed. Because there is no canopy

cover,WAF is determined fromtable 1. For SH5,WAF

is 0.55. Therefore, midflame wind speed is 7 x 0.55, or

3.9 mi/h. Manual vectoring of wind and slope effects

is most difficult with wind blowing directly upslope

or downslope, as it is in this example.

	 a.	 Draw a vertical line from the origin of the

concentric circles to the point on the line

corresponding to the slope steepness.Interpolate between tick marks as necessary (fig. 5,

line a).

	 b.	 Draw another vertical line from the origin of

the concentric circlesto the circle representing

the midflame wind speed. To avoid overlapping the line drawn in 2a, you may need to

offset this line slightly (fig. 5, line b).

	 c.	 Now, draw a clone of line a (same length)

beginning at the upper end of line b (fig. 5,

line c).

	 d.	 Read the effective midflame wind speed by

noting where the tip of line c falls (fig. 5,

point d). In this example, the effective midflame wind speed is 5.9 mi/h. With upslope

winds, direction ofmaximumspread is always

upslope.

	 3)	 Select a specific chart on the page.

	 The nomograph pages for fuel models with live fuel

consist of five separate charts, each for a different live

fuel moisture content. For fuel models with both herbaceous and woody live fuel load, live fuel moisture

refers to the live herbaceous moisture content. Live

woody moisture content is assumed to be 30 percent

higher than live herbaceous fuel. Select the chart

matching the live moisture content value and follow

steps a through d for the “no live fuel” nomographs to

determine spread rate and flame length. If you need to

determine spread rate orflame length for a livemoisture

content value between the values for which a chart is

available, make the calculations using the two charts

that bracket the value and interpolate. The following

example illustrates the interpolation process.

	 4)	 Determine the head fire rate ofspread and flame

length.

	 a.	 Draw a vertical line from the bottom of the

nomograph corresponding to the specified

dead fuelmoisture content.In this example,we

need to interpolate between two nomographs,

so draw this vertical line on the two charts

that bracket the desired LWMC (fig. 5, lines

e).

	 b.	 On both charts, mark the point where this

vertical line crosses the line for the effective

midflame wind speed estimated above (5.9

mi/h in this example).If necessary,interpolate

between lines (labeled at the right-hand axes)

for effectivemidflamewind speed.Drawhorizontal lines from these points to the common

y-axis. Use the faint gray lines as a guide. Do

this for both charts (fig. 5, lines f).

	 c.	 Read the rate of spread (ch/h) for both charts

and then interpolate between them. In this

example,rate ofspread for 100 percentLWMC

is about 66 ch/h, and for 120 percent LWMC

is about 56 ch/h. Therefore, rate of spread for

110 percent LWMC would be about halfway

between those two estimates, or 61 ch/h (fig. 5,

point g).
USDA Forest Service Gen. Tech. Rep. RMRS-GTR-192. 2007

	 d.	 Read the flame length for each chartseparately

by interpolating between the curving gray

linesrepresenting flame length. The separate

flame length estimates are about 14.5 ft for

100 percent LWMC and about 13.5 ft for 120

percentLWMC;the resulting interpolation for

110 percent LWMC is therefore 14 ft (fig. 5,

points h).

Step 3: Non-heading Rate of 

Spread and Flame Length

	 We determined potential head fire rate ofspread and

flame length in previous examples. In this section we

will demonstrate how to adjust those predictions for

other parts of an ellipticalfire using the “FireBehavior

in Non-heading Directions Nomograph” (p. 13). The

equations used for estimating non-heading rate of

spread and flame length are documented in Appendix A. For this example, we will use the results from

the example (fuel models with a live component) to

estimate rate of spread and flame length at the flank

of the fire. In that example, effective midflame wind

speed was 5.9 mi/h; head fire rate of spread was 61

ch/h; and head fire flame length was 14 ft.

	 a.	 Beginning with the right-hand chart of the

nomograph, draw a vertical line from the bottom axis to the top at the effective midflame

wind speed (fig. 6, line a).

Figure 5—Example nomograph for estimating effective midflame wind speed and head fire rate of spread and flame 

length for fuel model SH5. Inputs: slope steepness = 60 percent; midflame wind speed 3.9 = mi/h; wind direction = 

upslope; dead fuel moisture content 5 percent; and live woody fuel moisture content = 110 percent. Results: effective 

midflame wind speed = 5.9 mi/h; head fire rate of spread = 61 ch/h; and head fire flame length = 14 feet. Annotations 

refer to instructions in the text.
USDA Forest Service Gen. Tech. Rep. RMRS-GTR-192. 2007

Figure 6—Example nomograph for estimating rate of spread and flame length in non-heading directions. Annotations 

refer to instructions in text. Inputs: effective midflame wind speed = 5.9 mi/h (see fig. 5); spread direction = flanking fire; 

head fire rate of spread = 61 ch/h (see fig. 5); and head fire flame length = 14 ft (see fig. 5). Results: length-to-breadth 

ratio = 2.5; fraction of head fire rate of spread = 0.21; rate of spread in flanking direction = 13 ch/h; fraction of head fire 

flame length = 0.49; and flame length at flank of fire = 7 ft.

b.	 Read the corresponding value for length-tobreadth ratio from the top axis. The lengthto-breadth ratio for this example is 2.5 (fig. 6,

point b). This value will be useful in plotting

a point-source fire on a map.

	 c.	 Next, drawa horizontal line fromthe intersection of the vertical line drawn in step 5a and

the line corresponding to the desired spread

direction. Ensure the line goes all the way

to the left-axis of the left-hand chart (fig. 6,

line c).

	 d.	 Read the resulting fraction of head fire rate

of spread from the left-axis of the left-hand

chart. Multiply the head fire rate of spread

by this fraction (0.21 in this example) to

estimate flanking spread rate. The result for

this example is 13 ch/h (figure 6, point d).

	 e.	 Draw a vertical line from the intersection of

line 5c and the curving line in the left-hand

chart to the bottom axis (fig. 6, line e).

	 f.	 Read the resulting fraction of head fire flame

length from the bottom axis. Multiply the

head fire flame length by this fraction (0.49

in this example) to estimate flame length in

the chosen spread direction. The result for

this example is 7 ft (fig. 6, point f).

Summary

	 Nomographs are useful for estimating surface fire

behavior characteristicsin situationswhere a computer

is not available and for visually depicting the relationships among input and output variables. The recent

development of 40 standard fire behavior fuel models

required that additional nomographs be created.Amore

straight-forward nomograph formatwas designed.The

new format can be used to estimate effectivemidflame

wind speed when wind direction is not upslope and

to estimate fire behavior in non-heading directions.

Nomographsfor the original 13 fuel models have been

created in the new format.
10 USDA Forest Service Gen. Tech. Rep. RMRS-GTR-192. 2007

References

Albini, F. A. 1976. Estimating wildfire behavior and effects. Gen.

Tech. Rep. INT-30. Ogden, Utah: Department of Agriculture,

Forest Service, Intermountain Forest and Range Experiment

Station. 92 p.

Albini, F. A.; Baughman, R. G. 1979. Estimating windspeeds for

predicting wildland fire behavior. Res. Pap. INT-221. Ogden,

Utah: U.S. Department of Agriculture, Forest Service, Intermountain Forest and Range Experiment Station. 12 p.

Anderson, D. H.; Catchpole, E. A.; de Mestre, N. J.; Parkes, T.

1982. Modelling the spread of grass fires. J. Aust. Math. Soc.

(Ser. B) 23: 451-466.

Anderson, H. E. 1982. Aids to determining fuel models for estimating fire behavior. Gen. Tech. Rep. INT-122. Ogden, UT:

U.S. Department ofAgriculture, Forest Service,Intermountain

Forest and Range Experiment Station. 22 p.

Andrews, P. L. 1986. BEHAVE: Fire behavior prediction and

fuel modeling system — BURN Subsystem, Part 1. Gen. Tech.

Rep. INT-194. Ogden, UT: U.S. Department of Agriculture,

Forest Service, Intermountain Forest and Range Experiment

Station. 130 p.

Burgan, R. E. 1979. Estimating live fuel moisture for the 1978

nationalfire dangerrating system.GTR-INT-226,USDAForest

Service, Ogden, UT. 17 p.

Byram, G. M. 1959. Combustion of forest fuels. In: Forest fire:

Control and use, 2nd edition. New York, NY: McGraw-Hill:

chapter 1, 61-89.

Catchpole, E. A.; Alexander, M. E.; Gill, A. M. 1992. Ellipticalfire perimeter- and area-intensity distributions. Can. J. For.

Res. 22: 968-972.

Catchpole, E. A.; de Mestre, N. J.; Gill, A. M. 1982. Intensity of

fire at its perimeter. Aust. For. Res. 12: 47-54.

Jolly, W. M. 2005. Sensitivity of a fire behavior model to changes

in live fuel moisture. In: Proceedings of the Sixth Symposium

on Fire and Forest Meteorology, Canmore, AB, Canada.

Rothermel, R. C. 1972. A mathematical model for predicting

fire spread in wildland fuels. Res. Pap. INT-115. Ogden, UT:

U.S. Department of Agriculture, Forest Service,Intermountain

Forest and Range Experiment Station. 40 p.

Scott,J. H.; R. E. Burgan. 2005. Standard fire behavior fuel models: a comprehensive set for use with Rothermel’s surface fire

spread model. Gen. Tech. Rep. RMRS-GTR-153. Ft. Collins,

CO: U.S. Department of Agriculture, Forest Service, Rocky

Mountain Research Station. 72 p.
USDA Forest Service Gen. Tech. Rep. RMRS-GTR-192. 2007 11

Appendix A—Fire Behavior in Non-heading Spread Directions

	 Assuming fire spreads as a simple ellipse (Anderson and others 1982), the fraction of headfire rate of spread

(Rψ/Rhead) expected for a flame front oriented any direction with respect to the direction of maximum spread

(fig. A1) can be estimated following Catchpole and others (1982) as:

R

R c COS a COS b SIN

head

ψ = ∗ ( ) ψ + ∗ ( ) ψ + ∗ ( ) ψ 2 2 2 2 [1]

where ψ is the normal angle (fig. A1), and following Catchpole and others (1992)

a

LB

= + − −

1

1 1 2 [2]

b a

LB

= [3]

c a = − LB

− 1 2 [4]

where LB is the length-to-breadth ratio of the ellipse, which can be estimated as a simple function of effective

midflame wind speed (Andrews 1986)

L U B = +1 0 25 m . [5]

where Um is the effective midflame wind speed. Rate of spread for flame front oriented in any direction relative

to the direction of maximum spread (Rψ) is therefore

Figure A1—Elliptical dimensions a, b, and c, and graphical 

illustration of calculations for non-heading fire behavior. Lengthto-breadth ratio (LB) = 2 for the ellipse shown. The point shown 

on the ellipse is oriented 45 degrees from the heading direction. 

At that point, a = 0.536, b = 0.268, c = 0.464, Rfraction = 0.752, 

and FLfraction = 0.877.
12 USDA Forest Service Gen. Tech. Rep. RMRS-GTR-192. 2007

R R R

head Rhead ψ

ψ = ∗ 



 



 [6]

where Rhead is the spread rate in the direction of maximum spread.

	 Using Byram’s (1959) relationship between flame length and fireline intensity, the fraction of head fire flame

length that would occur at the same flame front orientation, FLψ/FLhead, is

FL

FL

I R

R

head

head

head ψ

ψ





 



 =

∗



 



 



  0 4. 5 

( )

0 46

0 46

0 45

.

.

. Ihead

	 	 [7]

which reduces to

FL FL R

head Rhead ψ

ψ = 



 





0 4. 6

[8]
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notes:

A B C

(1) Fuel model category

(2) dead woody fuel moisture percent

(3) live herbaceous fuel moisture percent

(4) live woody fuel moisture percent

(5) slope steepness percent

(6) percent

(7) 20-ft wind speed mi/h

(8) Wind Adjustment Factor fraction (table 3 or 4)

(9) midflame wind speed mi/h (direct entry or [7] x [8])

(10) wind direction degrees clockwise from upslope

(11) spread direction (heading, hanking, flanking, or backing)

(12) effective midflame wind speed mi/h

(13) direction of maximum spread degrees clockwise from upslope

(14) head fire rate of spread ch/h

(15) head fire flame length ft

(16) length-to-breadth ratio ratio

(17) fraction of head fire rate of spread fraction

(18) fraction of head fire flame length fraction

(19) rate of spread in spread direction ch/h ([14] x [17])

(20) flame length in spread direction ft ([15] x [18])

Results

Spread Direction

Wind and Slope

Fire Behavior Nomograph Worksheet

Fuel and Moisture

analyst name:

project name:

projection date and time:

notes: Projection Point

canopy cover

Appendix B—Nomographs
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Grass

GR
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Grass-shrub

GS
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Shrub

SH
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Timber-understory

TU
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Timber litter

TL
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Slash-blowdown

SB
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Notes


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Rights, 1400 Independence Avenue, S.W., Washington, DC 20250-9410, or call 

(800) 795-3272 (voice) or (202) 720-6382 (TDD). USDA is an equal opportunity 

provider and employer.

The Rocky Mountain Research Station develops scientific information and technology to improve management, protection, and use of 

the forests and rangelands. Research is designed to meet the needs 

of National Forest managers, Federal and State agencies, public and 

private organizations, academic institutions, industry, and individuals. 

Studies accelerate solutions to problems involving ecosystems, 

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use economics, wildlife and fish habitat, and forest insects and diseases. 

Studies are conducted cooperatively, and applications may be found 

worldwide.

Research Locations

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Fort Collins, Colorado* Albuquerque, New Mexico

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*Station Headquarters, Natural Resources Research Center,

2150 Centre Avenue, Building A, Fort Collins, CO 80526 

 

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ROCKY MOUNTAIN RESEARCH STATION