indices_description.pdf

8/10/2019 Indices_description.pdf

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Description of the indices implemented in EUDIC software for the

European meteorological forest fire risk mapping

by

Andrea Camia and Giovanni Bovio

AGROSELVITER University of Turin

May 2000

EUDIC is a software developed in the frame of a collaboration between the Department

AGROSELVITER of the University of Turin and the Space Application Institute of the Joint

Research Centre. The software is aimed to compute daily a number of meteorological fire

danger indices in Europe, using as input either measured meteorological data from the MARSdatabase or forecasted weather data from MeteoFrance. The output are raster maps of the

European Mediterranean basin or other portions of the European territory, showing the spatial

distribution of the fire danger level in a given day, segmented into 5 classes.

The aim of this report is to provide a synthetic description, including main formulas,

algorithms and references, of the meteorological fire danger indices implemented in EUDIC.

Notice that the thresholds used to segment the indices and define the mentioned 5 classes of

meteorological fire danger level are not reported here.

The indices are named as it follows:

Portuguese Index

ICONA Method Drouet-Sol Numerical Risk Italian Fire Danger Index Canadian Fire Weather Index (FWI)

Fine Fuel Moisture Code (FFMC) Duff Moisture Code (DMC) Drought Code (DC) Initial Spread Index (ISI) Build Up Index (BUI)

BEHAVE Dead Fine Fuel Moisture Content

To simplify the reading of the document, a common frame to illustrate the indices has been

established, covering for each index the following issues:

1. Description: brief description of the index

2. Reference: main reference from which the equations were taken3. Inputs required: meteorological variables and unit measures needed to compute the

index

4. Basic equations: formulas and algorithms


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3

PORTUGUESE INDEX

Description:the Portuguese index used in EUDIC is the index developed by the Portuguese

Meteorological and Geophysical National Institute (INMG, 1988; Gonalves and Loureno,

1990) and it is a modified version of Nesterov index, the fire danger index used in the former

Soviet Union.

It is based on the assessment of atmospheric conditions in the proximity of the fuel layer and

is composed by three numerical indicators.

The first one [I(i)] can be considered as an index of ignition

The second one [B(i-1)] is cumulative and is given by the sum of the daily indicators of the

previous days (I), starting from the beginning of the fire season, corrected by a weighting

factor (r), which is a function of precipitation (P) occurred in the previous day.

The third indicator [ifa(i)] is the final danger index that sums the previous two, introducing acorrection for wind speed, that could be considered as a weighting factor to be eventually

applied to the fire danger index.

Reference: INMG (1988) Nota explicativa sobre o Indice de Risco Meteorologico de

Incendios Rurais. Divisao de Meteorologia Agrcola, Instituto Nacional de Meteorologia e

Geofisica.

Gonalves ZJ, Loureno L (1990) Meteorological index of forest fire risk in the portuguese

mainland territory. In: Proceedings of the International Conference on Forest Fire Research,

Coimbra, B.07-1/14.

InputsrequiredT air temperature at noon, C

Td dew point at noon, % (in EUDIC derived from vapour pressure)

V wind speed at noon, Km/h

P rainfall 24 hours previous, mm

Basic equations

1) Index of ignition of ithday

I i T i T i Td i( ) ( )[ ( ) ( )]=

2)

B i r I kk i

i

( ) * ( ) ==

11

R Precipitation (mm)

1 0 < P 1

0.8 1 < P 2

0.6 2 < P 3

0.4 3 < P

4

0.2 4 < P 10

0.1 10 < P


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5

ICONA METHOD

Description: this is the only not-cumulative method among those reviewed and it rather

defines a risk of ignition.

It is the method used by the Spanish Instituto Nacional para la Conservacion da la Naturaleza

(ICONA, 1993) and it has been developed from the fine dead fuel moisture content model

developed in the US by Rothermel et Al. (1986).

It is based on litter and fine dead fuels moisture content which are quite sensible to

meteorological variation.

Air temperature and relative humidity are the basic inputs required to to derive a so called

basic moisture humidity. Basic humidity is then corrected according to period of the year,

hour of the day, terrain cover (by vegetation or clouds), aspect and slope.

Reference: - ICONA (1993) Manual de operaciones contra incendios forestales. Madrid,

5.1/65.

Inputs required:

T air temperature, (C)

H relative humidity, (%)

V wind speed, (Km/h)

tV kind of wind

Time (hour) in which the index is computed

Terrain cover by vegetation or by clouds (two classes: >50% or < 50%)

Terrain slope (two classes: >30% or < 30%)Aspect (four classes: N, E, S, W)

Basic equations

The method can be applied using a number of tables, solving 3 subsequent steps as they are

illustrated in what follows. The tables presented below refer only to the period May, June,

July, but tables exist in the referenced paper, that cover the other months of the year.

1. Determine basic humidity of fine dead fuel from Table 1 or Table 22. In case of day time calculation, find the correction value to be added to basic humidity to

obtain fine fuel moisture content from Table 3

3. Find the probability of ignition from Table 44. An alert level can be derived from the probability of ignition, expressed by three danger

classes, considering wind velocity and direction (Table 5).

In EUDIC the site and time specific features of the ICONA method could not be completely

complied because the software has been designed to work on a square grid cell of 50x50 km2

and on a daily basis.

Thus the following simplifications have been introduced:

- the method is assumed to refer the fire danger level at noon, thus the Table 2 is never used(always Table 1), and the column of 12.00 h is used for the correction value in Table 3.

- Slope and aspect cannot be taken into account, thus the worst conditions are taken as areference, using always the minimum correction factor of Table 3 (or a similar table for

August and September).


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- The sunny/shadowed criteria of Table 3 is taken into account estimating the cloud coverfrom the direct solar radiation, compared, through some atmospheric transmissivity

coefficients, to the potential solar radiation.

- The kind of wind (from the sea or from the land Table 5) could not be considered owingto the heterogeneity of the European Mediterranean basin. Thus the worst conditions are

always taken as reference also in this case.

Two fire risk indicators are recorded: both the probability of ignition (Table 4) and the level

of alert (Table 5) which has only four values, thus it can only reach the risk class number 4.


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Table 1Basic fuel humidity in daytime (from 8.00 to 20.00, solar)

AIR HUMIDITY(%)

AIR TEMPERATURE

(C)

0

4

5

9

10

14

15

19

20

24

25

29

30

34

35

39

40

44

45

49

50

54

55

59

60

64

65

69

70

74

75

79

< 0 1 2 2 3 4 5 5 6 7 8 8 8 8 9 10 1

0 9 1 2 2 3 4 5 5 6 7 7 7 8 9 9 10 10

10 20 1 2 2 3 4 5 5 6 6 7 7 8 8 9 9 10

21 31 1 1 2 2 3 4 5 5 6 7 7 8 8 8 9 10

32 42 1 1 2 2 3 4 4 5 6 7 7 8 8 8 9 10

> 43 1 1 2 2 3 4 4 5 6 7 7 8 8 8 9 10Table 2-Basic fuel humidity at night time (from 20.00 to 8.00, solar)

AIR HUMIDITY(%)

AIR TEMPERATURE

(C)

0

4

5

9

10

14

15

19

20

24

25

29

30

34

35

39

40

44

45

49

50

54

55

59

60

64

65

69

70

74

75

79

0 9 1 2 3 4 5 6 7 8 9 9 11 11 12 13 14 16

10 20 1 2 3 4 5 6 6 8 8 9 10 11 11 12 14 16

21 31 1 2 3 4 4 5 6 7 8 9 10 10 11 12 13 15

32 42 1 2 3 3 4 5 6 7 8 9 9 10 10 11 13 14

> 43 1 2 2 3 4 5 6 8 9 8 9 9 10 11 12 14


8/31

Table 3Day corrections for May, June, July

SUNNY LAND: plus than 50% in the sun

HOURASPECT SLOPE 08.00 10.00 12.00 14.00 16.00

N 0 - 30%> 30%3

4

1

2

0

1

0

1

1

2

E 0 - 30%> 30%2

2

1

0

0

0

0

1

1

3

S 0 - 30%> 30%3

3

1

1

0

1

0

1

1

1

O 0 - 30%> 30%3

5

1

3

0

1

0

0

1

0

SHADOWED LAND: more than 50% in the shadow

HOUR OF DAY

ASPECT SLOPE 08.00 10.00 12.00 14.00 16.00

N 0% + 5 4 3 3 4

E 0% + 4 4 3 4 4

S 0% + 4 4 3 3 4

O 0% + 5 4 3 3 4

FLAT LAND =ASPECT SUD


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Table 4 Probability of ignitionFINE DEAD FUEL MOISTURE

SHADOW TEMPERATURE 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17

0 -10 40+

35-40

30-35

100

100

100

100

90

90

90

80

80

80

70

70

70

60

60

60

60

50

50

50

50

40

40

40

40

40

30

30

30

30

30

30

30

30

20

20

20

20

20

20

20

20

20

10

10

10

10

10

25-30

20-25

15-20

100

100

90

90

80

80

80

70

70

70

60

60

60

60

50

50

50

50

40

40

40

40

40

30

30

30

30

30

30

30

20

20

20

20

20

20

20

20

20

20

10

10

10

10

10

10

10

10

10-15

5-10

0-5

90

90

90

80

80

70

70

70

60

60

60

60

50

50

50

40

40

40

40

40

40

30

30

30

30

30

30

20

20

20

20

20

20

20

20

20

10

10

10

10

10

10

10

10

10

10

10

10

10-50 40+

35-40

30-35

100

100

100

100

90

90

80

80

80

70

70

70

60

60

60

60

50

50

50

40

40

40

40

40

40

40

30

30

30

30

30

30

30

20

20

20

20

20

20

20

20

20

20

10

10

10

10

10

25-30

20-25

15-20

100

100

90

90

80

80

80

70

70

70

60

60

60

50

50

50

50

50

40

40

40

40

40

30

30

30

30

30

30

20

20

20

20

20

20

20

20

20

20

10

10

10

10

10

10

10

10

10

10-15

5-10

0-5

90

90

80

80

80

70

70

70

60

60

60

50

50

50

50

40

40

40

40

40

30

30

30

30

30

30

20

20

20

20

20

20

20

20

20

10

10

10

10

10

10

10

10

10

10

10

10

10

60-90 40+35-40

30-35

100100

100

9090

90

8080

80

7070

70

6060

60

5050

50

5050

40

4040

40

4030

30

3030

30

3030

20

2020

20

2020

20

2020

10

1010

10

1010

10

25-30

20-25

15-20

100

90

90

80

80

80

70

70

70

60

60

60

60

50

50

50

50

40

40

40

40

40

30

30

30

30

30

30

30

20

20

20

20

20

20

20

20

20

10

10

10

10

10

10

10

10

10

10

10-15

5-10

0-5

90

90

80

80

70

70

70

60

60

60

50

50

50

50

50

40

40

40

40

30

30

30

30

30

30

30

20

20

20

20

20

20

20

20

20

10

10

10

10

10

10

10

10

10

10

10

10

10

100 40+

35-40

30-35

100

100

100

90

90

80

80

80

70

70

70

60

60

60

60

50

50

50

50

40

40

40

40

40

30

30

30

30

30

30

30

20

20

20

20

20

20

20

20

20

20

10

10

10

10

10

10

10

25-30

20-25

15-20

90

90

90

80

80

80

70

70

70

60

60

60

50

50

50

50

40

40

40

40

40

30

30

30

30

30

30

30

20

20

20

20

20

20

20

20

20

10

10

10

10

10

10

10

10

10

10

10

10-15

5-10

0-5

90

80

80

70

70

70

60

60

60

60

50

50

50

50

40

40

40

40

40

30

30

30

30

30

30

20

20

20

20

20

20

20

20

20

10

10

10

10

10

10

10

10

10

10

10

10

10

10


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Table 5 Alert level

NON DRYING WIND (WIND FROM THE SEA)

Wind speed (km/h)PROBABILITY OF

IGNITION, %

0-9 10-19 20-39 40

10 20 Pre-alert Pre-alert Pre-alert Alert

20 50 Pre-alert Alert Alert Alert50 < 70 Alarm Alarm Alarm Alarm

70 Alarm Alarm Alarm Extreme Alarm

DRYING WIND (WIND FROM THE LAND)

Wind speed (km/h)PROBABILITY OF

IGNITION, %

0-9 10-19 20-39 40

10 20 Pre-alert Alert Alert Extreme Alarm

20 50 Alert Alarm Alarm Extreme Alarm

50 < 70 Alarm Alarm Alarm Extreme Alarm

70 Alarm Extreme Alarm Extreme Alarm Extreme Alarm


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DROUET-SOL NUMERICAL RISK

Description:the Numerical Risk proposed by Sol (1990) and Drouet (Drouet and Sol, 1993) ,

is one of the indices that have been applied in Southern France. It is a cumulative index thatcan be applied during the whole summer.

It requires a number of input parameters such as daily values of air temperature, relative

humidity, cloud cover, wind velocity, dew point, soil and litter temperature.

Reference:Sol B (1990) Estimation du risque meteorologique dincendies de forts dans le

Sud-est de la France. Revue Forestire Franaise, Nancy, n spcial, 263-271.

Drouet J-C, Sol B (1993) Mise au point d'un indice numerique de risque meteorologique

d'incendies de forts. Fort Mediterranenne 14(2): 155-162.

Inputs requiredV wind speed (Km/h)

T air temperature (C)

Td dew point temperature (C) (in EUDIC derived from vapour pressure)

Cc cloud cover (eighths)

Rp soil water reserve(Orieux, 1979):

ETPg daily potential evapotranspiration (Thornthwaite)

ti monthly average temperature, (C)

Tmax daily maximum temperature, (C)

Tmin daily minimum temperature, (C)

L latitude

Prec rainfall, (mm)

Basic equations

RisnumFHR Cres Cvent

A= +2515

* *

Where:

FHR = False relative humidity = 100*( )

( )

Esat Td

Esat Tsol

where:

Esat(T) Vapour pressure (hPa) at temperature T

Tsol is derived with the empirical equations:

If Cc=3 Tsol=1.36*T-1.422*Cc-0.22*Td+13.42


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12

Cres (soil water reserve factor) = 3 250

25+

*TanHyp

Rp

where:

Rp= soil water reserve (Orieux method)

Cvent (wind factor) = 3 345

50+

*TanHyp

V

Ais a factor function of rate of spread (ROS) estimated with Drouet equation:

ROS=180*EXP(T*0.06)*TanHyp((100-Rp)/150)*(1+2*(0.8483+TanHyp(V/30-1.25)))

According to ROS,Acan take the following values:ROS 600 m/h A = -3600 < ROS < 1000 A = 0ROS 1000 m/h A = +2


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13

ITALIAN FIRE DANGER INDEX

Description: this is the fire danger index normally applied in Italy by the Italian State

Forestry Corps. It is derived from the Mc Arthurs models in the Australian Forest FireDanger Meter, and it is considered reliable only in the Mediterranean part of Italy.

This method is made up of 2 steps:

- computing of soil water deficit and drought index. (function of rainfall amount, days sincelast rain and air maximum temperature)

- computing of danger index (function of drought index, wind speed, relative humidity andair temperature)

Reference: Literature references of the exact algorithm used by the method cannot be found.

The tables and equations used in EUDIC were derived from the conversions of the

nomograms that the Italian State Forestry Corps use for calculations, and from the analysisand comparison with the quite similar methods described in:

Palmieri S, Cozzi R (1983) Il ruolo della meteorologia nella prevenzione e controllo degli

incendi boschivi. Riv. Meteor. Aer. XLIII, n.4.

Palmieri S, Inghilesi R, Siani AM (1993) Un indice meteorologico di rischio per incendi

boschivi. Proceedings from Seminar on fighting forest fires 26-28 April 1993 Tessaloniki.

Inputs required

Tmax daily maximum temperature (C)

N number of days since the last rainfall

T air temperature (C)

Prec rainfall of previous 24 hours (mm)U air relative humidity (%)

V wind speed (Km/h)

Basic equations

Soil water deficit is given by the formula

IS(j) = IR(j) + AS

where:

IS(j) = water deficit of today

IR(j) = reduced water deficit

AS = increase in water deficit

IR(j)= IS(j-1) Pnet

where:

IS(j-1) = water deficit of the day before

Pnet = net rainfall, excluding canopy intercept (5 mm)

Pnet = Prec - 5

if Pnet < 0 than Pnet = 0


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14

The increase in water deficit (AS) is found in Table 6 as a function of maximum temperature

and IR(j)

The drought index (Ar) is found in Tables 7-10 as a function of IS(j), number of days since

last rainfall and precipitation amount.

The meteorological danger index (IMPI) is given by the equation:

IMPI= 1.33 * Ar * 2 (0.048T -- 0.051U + 0.033V)


15/31

Table 6 - AS values

Reduced water deficit(IR)

Maximumtemperature

(C)

0to

12

13to

25

26to

38

39to

51

52to

64

65to

77

78to

90

91to

103

104to

116

117to

129

130to

142

143to

150

151to

163

42 8 8 7 7 6 6 5 5 5 5 3 2 1

40 41 6 6 6 5 5 5 4 4 3 3 2 2 1

38 39 5 5 5 4 4 4 3 3 3 2 2 2 1

36 37 5 5 4 4 4 3 3 3 2 2 2 1 1

34 35 4 4 4 3 3 3 3 2 2 2 2 1 1

32 33 3 3 3 3 3 2 2 2 2 2 1 1 0

31 3 3 3 2 2 2 2 2 2 1 1 1 0 30 3 2 2 2 2 2 2 1 1 1 1 1 0

29 2 2 2 2 2 2 1 1 1 1 1 0 0

27 28 2 2 2 2 1 1 1 1 1 1 1 0 0

26 25 2 1 1 1 1 1 1 1 1 0 0 0 0

23 24 1 1 1 1 1 1 1 1 0 0 0 0 0

21 22 1 1 1 1 1 1 0 0 0 0 0 0 0

19 - 20 1 1 1 1 0 0 0 0 0 0 0 0 0

19 1 0 0 0 0 0 0 0 0 0 0 0 0 19 0 0 0 0 0 0 0 0 0 0 0 0 0


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Table 7 Drought index (Ar) with IS = 0-50

Number of days Rainfall amount (mm)

since last rainfall 0 3 4 5 6 7 8 9 10 15 20 30

0 6 6 5 4 3 3 3 2 2 2 1 1

1 6 6 5 5 4 3 3 3 2 2 2 1

2 6 6 6 6 5 5 4 4 3 3 3 2

3 6 6 6 6 6 6 5 5 4 4 4 3

4 6 6 6 6 6 6 6 6 5 5 4 4

5 6 6 6 6 6 6 6 6 6 5 5 4

6 6 6 6 6 6 6 6 6 6 6 5 5

7 6 6 6 6 6 6 6 6 6 6 6 5

8 6 6 6 6 6 6 6 6 6 6 6 5

9 6 6 6 6 6 6 6 6 6 6 6 5 10 6 6 6 6 6 6 6 6 6 6 6 6

12 6 6 6 6 6 6 6 6 6 6 6 6

15 6 6 6 6 6 6 6 6 6 6 6 6

20 6 6 6 6 6 6 6 6 6 6 6 6


17/31




0 7 7 7 6 5 4 3 3 2 2 1 1 1 7 7 7 7 6 5 4 4 3 2 2 1

2 7 7 7 7 7 7 6 5 5 4 4 3

3 7 7 7 7 7 7 7 7 6 6 5 4

4 7 7 7 7 7 7 7 7 7 7 6 5

5 7 7 7 7 7 7 7 7 7 7 7 6

6 7 7 7 7 7 7 7 7 7 7 7 6

7 7 7 7 7 7 7 7 7 7 7 7 7

8 7 7 7 7 7 7 7 7 7 7 7 7

9 7 7 7 7 7 7 7 7 7 7 7 7

10 7 7 7 7 7 7 7 7 7 7 7 7

12 7 7 7 7 7 7 7 7 7 7 7 7

15 7 7 7 7 7 7 7 7 7 7 7 7

20 7 7 7 7 7 7 7 7 7 7 7 7


18/31




0 9 9 9 8 7 6 5 4 4 3 2 1 1 9 9 9 9 8 7 6 5 5 4 3 2

2 9 9 9 9 9 9 8 7 7 6 5 4

3 9 9 9 9 9 9 9 9 8 8 7 6

4 9 9 9 9 9 9 9 9 9 9 8 7

5 9 9 9 9 9 9 9 9 9 9 9 8

6 9 9 9 9 9 9 9 9 9 9 9 8

7 9 9 9 9 9 9 9 9 9 9 9 9

8 9 9 9 9 9 9 9 9 9 9 9 9

9 9 9 9 9 9 9 9 9 9 9 9 9

10 9 9 9 9 9 9 9 9 9 9 9 9

12 9 9 9 9 9 9 9 9 9 9 9 9

15 9 9 9 9 9 9 9 9 9 9 9 9

20 9 9 9 9 9 9 9 9 9 9 9 9


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0 10 10 10 9 8 7 6 5 5 4 3 1 1 10 10 10 10 9 8 7 7 6 5 4 3

2 10 10 10 10 10 10 10 9 8 8 7 5

3 10 10 10 10 10 10 10 10 10 9 9 8

4 10 10 10 10 10 10 10 10 10 10 10 9

5 10 10 10 10 10 10 10 10 10 10 10 10

6 10 10 10 10 10 10 10 10 10 10 10 10

7 10 10 10 10 10 10 10 10 10 10 10 10

8 10 10 10 10 10 10 10 10 10 10 10 10

9 10 10 10 10 10 10 10 10 10 10 10 10

10 10 10 10 10 10 10 10 10 10 10 10 10

12 10 10 10 10 10 10 10 10 10 10 10 10

15 10 10 10 10 10 10 10 10 10 10 10 10

20 10 10 10 10 10 10 10 10 10 10 10 10


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20

CANADIAN FIRE WEATHER INDEX (FWI)

Description: FWI is an index composed by six sub-indices referring respectively the daily

variation of water content for fuels with different response time changes in weatherconditions, the initial rate of spread for propagation, the quantity of fuel and the expected

intensity of the flame front.

A schematic structure of the Fire Weather Index is illustrated in the following figure:

the Fire Weather Indexrepresents the intensity of the propagating flame front depending on

the quantity of energy released from a linear unit of the front itself. The indices that make up

FWI will be described in what follows.

Reference: Van Wagner CE, Pickett TL (1987) Equations and Fortran program for the

Canadian Forest Fire Weather Index System. Canadian Forestry Service, Forestry Technical

Report 33, Ottawa.

Inputs required

T temperature at noon, C

H relative humidity at noon, %W wind speed at noon, km/h

ro daily rain, mm

Basic equations

Symbols used:

f(D) duff humidity factor

R initial spread index (ISI)

U build up index (BUI)

B FWI (intermediate form)

S FWI (form final)

Temperature Wind Temperature Temperature

Fire Weather Relative Humidity Relative Humidity Rain

Observations Wind Rain

Rain

Fuel MoistureFine Fuel Duff Drought

Codes Moisture Code Moisture Code Code

Initial Spread Build up

Index Index

Fire Behaviour

Indexes

Fire Weather

Index


21/31

21

1. Compute f(D)

if U 80 than f(D) = 0.626 U0.809+ 2

if U > 80 than f(D) = 1000 / (25 + 108.64 e-0.023U)

2. Compute B

B = 0.1 R f(D)

3. compute S

if B > 1 than S = EXP(2.72 (0.434 ln(B))0.647

)if B 1 than S = B

Fine Fuel Moisture Code (FFMC)

Description: the Fine Fuel Moisture Code is part of the Canadian FWI. The code is the

expression of the water content of litter and fine dead fuels. It indicates the relative ease of

ignition and flammability of fine dead fuels.

Reference: Van Wagner CE, Pickett TL (1987) Equations and Fortran program for theCanadian Forest Fire Weather Index System. Canadian Forestry Service, Forestry Technical

Report 33, Ottawa.

Inputs required


H relative humidity at noon, %

W wind speed at noon, km/h

ro daily rain, mm

Basic equationsSimbols used in the equations:

mo water content in fine fuel of the previous day

mr water content in fine fuel after the rain

m water content in fine fuel after the drainage

rf real rain, FFMC

Ed TEE (equilibrium water content) of fine fuel after the drainage

Ew TEE (equilibrium water content) of fine fuel after moistening

ko intermediate value of kd

kd logarithmic drainage speed, FFMC, Log10m/day

kl intermediate value of kW


22/31

22

kw logarithmic moisture speed, Log10m/day

F FFMC

Fo FFMC of the previous day

1. F of the previous day is Fo

2. Compute mo

mo= 147.2 (101 - Fo) / (59.5 + Fo)

3a. if 0.5 mm than r0=rf

if ro> 0.5 mm than rf= ro- 0.5

3b. Compute mr in function of rfand mo

if mo 150 mr= mo+ 42.5 rf(e -100/(251-mo))(1 - e - 6.93/rf)

if mo> 150 mr= mo+ 42.5 rf(e -100/(251-mo))(1 - e - 6.93/rf) + 0.0015 (mo- 150)2 rf0.5

if mr> 250 than mr= 250

3c. mr= mo.

4. Compute Ed

Ed= 0.942 H0.679+ 11e(H - 100)/10+ 0.18 (21.1 - T) (1 - e- 0.115H)

5a. if mo> Ed than kd

ko= 0.424 [1 - (H/100)1.7] + 0.0694 W 0.5[1 - (H/100)8]

kd= ko* 0.581 e0.0365T

5b. Compute m

m = Ed+ (mo- Ed) * 10-k

d


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6. if mo< Edthan Ew

Ew= 0.618 H0.753+ 10e(H - 100)/10+ 0.18 (21.1 - T) (1 - e- 0.115H)

7a. if mo< Ewthan kw

kl= 0.424 {1 - [(100 - H)/100]1.7}+ 0.0694 W0.5{1- [(100 - H)/100]8}

kw= kl* 0.581 e0.0365T

7b. Compute m

m = Ew

- (Ew

- mo

) * 10 -kd

8. if EdmoEwthan m = mo

9. Compute F as a function of m

F = 59.5 (250 - m) / (147.2 + m)

Duff Moisture Code (DMC)

Description: the Duff Moisture Code is part of the Canadian FWI. The code represents the

water content of a moderately thick organic layer. It also provides an estimate of the amount

of fuel of medium size available for combustion.

Reference:Van Wagner CE (1987) Development and structure of the Canadian Forest Fire

Weather Index System. Canadian Forestry Service, Technical Report 35, pp 37.

Van Wagner CE, Pickett TL (1987) Equations and Fortran program for the Canadian Forest

Fire Weather Index System. Canadian Forestry Service, Forestry Technical Report 33,Ottawa.

Inputs required




ro daily rain, mm

Basic equations

Symbols used for computing:


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Mo water content in duff of the previous day

Mr water content in duff after the rain

M water content in duff after the drainage

K logarithmic drainage speed, DMC, Log10m/day

re real rain, DMC

Le effective day length DMC, hours

b slope factor in DMC

Po DMC of the previous day

Pr DMC after the rain

P DMC

2a. if ro 1.5 than r0=re

if ro> 1.5 than re= 0.92ro- 1.27

2b. Compute Moin function of Po

Mo= 20 + e(5.6348 - P

o/43.43)

2c. Compute b

if Po 33 b = 100 / (0.5 + 0.3 Po)

if 33 < Po 65 b = 14 - 1.3 ln Po

if Po> 65 b = 6.2 ln Po- 17.2

2d. Compute Mr

Mr= Mo+ 1000 re/ (48.77 + bre)

2e. Compute Prin function of Mr

Pr= 244.72 - 43.43 ln (Mr- 20)

if Pr< 0 than Pr= 0

Pr= Po

3. Search Lein next table

Month Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec


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Le 6.5 7.5 9.0 12.8 13.9 13.9 12.4 10.9 9.4 8.0 7.0 6.0

4. Compute K

K = 1.894 (T + 1.1)(100 - H) Le* 10-6

if T < -1.1 Than T = -1.1

5. Compute P in function of Po

P = Po+ 100K

Drought Code (DC)

Description: theDrought Codeis part of the Canadian FWI. It represent a rating of the water

content of a deep, compact organic layer in the soil. It is a good indicator of seasonal drought

effect on large size fuels.


Canadian Forest Fire Weather Index System. Canadian Forestry Service, Forestry TechnicalReport 33, Ottawa.

Inputs required:




ro daily rain, mm

Basic equations

symbols used for computing:

Q equivalent humidity of DC, multiple di 0.254 mmQo equivalent humidity of DC of the previous day

Qr equivalent humidity after the rain

rd real rain, DC

V Potential evapotranspiration, multiplie of 0.254 mm of water/dayLf effective day length DC, hours

Do DC of the previous day

Dr DC after the rain

D DC


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2a. if ro 2.8 than r0= rd

if ro> 2.8 than rd = 0.83ro- 1.27

2b. Compute Qoin function of Do

Qo= 800 e-D

o/400

2c. Compute Qr

Qr= Qo+ 3.937rd

2d. Compute Drin function of Qr

Dr= 400 ln(800 / Qr)

ifDr< 0; than Dr= 0

Dr= Do

3. Search for Lfin next table

Month Jan Feb Mar Apr May Jiu Jul Aug Sep Oct Nov Dec

Lf -1.6 -1.6 -1.6 0.9 3.8 5.8 6.4 5.0 2.4 0.4 -1.6 -1.6

4. Compute V

V = 0.36 (T + 2.8) + Lf

if T < -2.8 Than T = -2.8if V < 0 thanV = 0

5. Compute D in function of Do

D = Do+ 0.5V


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Initial Spread Index (ISI)

Description:TheInitial Spread Indexis part of the Canadian FWI. It provides an estimate of

the expected propagation of the flame front, without considering the fuel variability. It

combines the effect of FFMC and of wind.



Report 33, Ottawa.

Inputs required




ro

daily rain, mm

Basic equations


f(W) wind factor

f(F) fine fuel humidity factor

m water content in fine fuel after the drainage

R ISI

1. f(W) = e0.05039W

2. f(F) = 91.9e-0.1386m[1 + m5.31/ (4.93 * 107)]

3. R = 0.208 f(W) f(F)

Build Up Index (BUI)

Description:theBuild up Indexis part of the Canadian FWI. It represent a rating of the totalfuel available for burning. It combines the two codes DMC and DC.



Report 33, Ottawa.

Inputs required




ro daily rain, mm


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Basic equations


U build up index (BUI)

P DMCD DC

1a. if P 0.4D than U = 0.8 PD/(P + 0.4D)

1b. if P > 0.4D than U = P - [1 - 0.8D / (P + 0.4D)] [0.92 + (0.0114P)1.7]

BEHAVE DEAD FINE FUEL MOISTURE CONTENT

Description: it is the component of the BEHAVE system (Andrews, 1986) which estimates

the moisture content of fine dead fuels. It is based on the Canadian FFMC except for a

correction of some parameters introduced because of the greater solar heating of the lower

USA latitude, to better express the air temperature and relative humidity at the fuel-

atmosphere interface.

In addition, the rainfall correction routine applied in BEHAVE is slightly different from the

updated FFMC rainfall routine, being an early version of the latter.

Reference:Rothermel R C, Wilson RA, Morris GA, Sackett SS (1986) Modelling moisture

content of fine dead wildland fuels: input to BEHAVE fire prediction system. USDA Forest

Service, Research Paper INT-359, Intermountain Research Station, Odgen, Utah, pp 61. In:

Viney NR (1991) A Review of Fine Fuel Moisture Modelling. The International Journal of

Wildland Fire 1(4):215-234.

Inputs required

temperature at noon, C

relative humidity at noon, %

wind speed at noon, km/h

daily rainfall amount (mm)

Basic equations

The corrections for air temperature and relative humidity at the fuel surface take into account

a number of site dependent factors such as slope, aspect and shading that could not be

considered in the computations because of the spatial resolution addressed by EUDIC.

Nevertheless air temperature and relative humidity were adjusted at the fuel level, introducing

a correction factor, function of direct solar radiation (Byram and Jemison, 1943). The wind

speed was also adjusted at the ground level, applying a standard reduction factor of 0.5.

Thus the BEHAVE model was applied in EUDIC following the FFMC routines (see

equations for FFMC), using as input air temperature, relative humidity and wind speed

corrected at the fuel level, and introducing the BEHAVE rainfall model. The rainfall model is


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29

intended to be applied only when rainfall exceeds 0.5 mm, but assumes that none of the rain is

intercepted by the canopy.

The model is the following:

( )Mr

Mo

f r e

Mo

=

+

min ; ..

101100

100

101 0 000110

0 1117

Where:

Mr= rain-corrected moisture content (%)

Mo= moisture content of fine fuels (%) of the previous day

f(r) is computed as follows:

if 0.5< r 1.45f(r) = 123.85-55.6 ln(r+1.016)

if 1.45< r 5.75f(r) = 57.87-18.2 ln(r-1.016)

if 5.75< r

f(r) = 40.69-8.25 ln(r-1.905)

REFERENCES

Andrews P L (1986) - BEHAVE: Fire Behavior Prediction and Fuel Modeling System - Burn

Subsystem, Part 1 - Gen. Tech. Rep. INT-194, USDA For. Serv., Intermountain ResearchStation, Odgen UT, p. 130.

Drouet J-C, Sol B (1993) Mise au point d'un indice numerique de risque meteorologique

d'incendies de forts. Fort Mediterranenne 14(2): 155-162.

Gonalves ZJ, Loureno L (1990) Meteorological index of forest fire risk in the portuguese

mainland territory. In: Proceedings of the International Conference on Forest Fire

Research, Coimbra, B.07-1/14.

ICONA (1993) Manual de operaciones contra incendios forestales. Madrid, 5.1/65.

INMG (1988) Nota explicativa sobre o Indice de Risco Meteorologico de Incendios Rurais.

Divisao de Meteorologia Agrcola, Instituto Nacional de Meteorologia e Geofisica.

Orieux A (1979) Conditions mtorologiques et incendies di forts en rgion

mditerranenne. Ministre des Transports, Direction de la Mtorologie, NoteTechnique du Service Mtorologie Mtropolitain.

Palmieri S, Cozzi R (1983) Il ruolo della meteorologia nella prevenzione e controllo degli

incendi boschivi. Riv. Meteor. Aer. XLIII, n.4.

Palmieri S, Inghilesi R, Siani AM (1993) Un indice meteorologico di rischio per incendi

boschivi. Proceedings from Seminar on fighting forest fires 26-28 April 1993

Tessaloniki.

Rothermel R C, Wilson RA, Morris GA, Sackett SS (1986) Modelling moisture content of

fine dead wildland fuels: input to BEHAVE fire prediction system. USDA Forest Service,

Research Paper INT-359, Intermountain Research Station, Odgen, Utah, pp 61.

Sol B (1990) Estimation du risque meteorologique dincendies de forts dans le Sud-est de la

France. Revue Forestire Franaise, Nancy, n spcial, 263-271.


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30

Van Wagner CE, (1972) Equilibrium moisture contents of some fine forest fuels in eastern

Canada, Canadian Forestry Service, Information Report PS-X-36, Petawa Forest

Experimental Station, Chalk River, Ontario, pp 11.

Van Wagner CE (1987) Development and structure of the Canadian Forest Fire Weather

Index System. Canadian Forestry Service, Technical Report 35, pp 37.Van Wagner CE, Pickett TL (1987) Equations and Fortran program for the Canadian Forest

Fire Weather Index System. Canadian Forestry Service, Forestry Technical Report 33,

Ottawa.

Viney NR (1991) A Review of Fine Fuel Moisture Modelling. The International Journal of

Wildland Fire 1(4):215-234.


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Index Danger Class From To

Canadian FWI very low - 5.6

low 5.6 13.3

moderate 13.3 19.8

high 19.8 29.8

very high 29.8 -

BEHAVE very low 14.2 -

low 13.2 14.2

moderate 12.5 13.2high 8.9 12.5

very high - 8.9

Spanish ICONA very low - 20.0

low 20.0 30.0

moderate 30.0 40.0

high 40.0 50.0

very high 50.0 -

Italian FDI very low - 1.8

low 1.8 2.5

moderate 2.5 3.8

high 3.8 6.8

very high 6.8 -Portuguese very low - 6.0

low 6.0 7.0

moderate 7.0 8.0

high 8.0 14.0

very high 14.0 -

Sol Numerical Risk very low - 5.2

low 5.2 7.0

moderate 7.0 12.9

high 12.9 16.3

Class interval

Class intervals identified for the meteorological indices analyzed

(lower bound included, upper bound excluded)

indices_description.pdf

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