De Luis, M., Baeza, , -Hidalgo, J.C. 2004. Fuel characteristics and fire
behaviour in mature Mediterranean gorse shrublands. International Journal of Wildland Fire 13: 79-
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pine (Pinus halepensis Mill.) forests in Greece based on common stand parameters. European
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behavior in Aleppo pine (Pinus halepensis Mill.) forests. Annals of Forest Science 64(3): 287-299.
Pausas, J. C., Llovet, J., Rodrigo, A., Vallejo, R. 2008. Are wildfires a disaster in the Mediterranean
basin? -- a review. International Journal of Wildland Fire 17:713-723.
Reinhardt, E., Lutes, D., Scott J. 2006. FuelCalc: A method for estimating fuel characteristics.
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(US. Department of Agriculture, Forest Service, Rocky Mountain Research Station, Proceedings
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Rothermel, R.C. 1972. A Mathematical model for predicting fire spread in wildland fuels. USDA
Forest Service Research Paper INT-115. Odgen, UT
Scott, J.H. 1999. NEXUS: a system for assessing crown fire hazard. Fire Management Notes. 59(2):
Scott J. H., Burgan Robert E. 2005. Standard fire behavior fuel models: a comprehensive set for use
with Rothermel''s surface fire spread model. Gen. Tech. Rep. RMRS-GTR-153. Fort Collins, CO:
U.S. Department of Agriculture, Forest Service, Rocky Mountain Research Station. 72 p.
Scott, J.H., Reinhardt, E.D. 2001. Assessing crown fire potential by linking models of surface and
crown fire potential. USDA, Forest Service, Rocky Mountain Research Station, Research Paper
RMRS-29, Fort Collins, USA. 59p.
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Crown fire behaviour in a northern jack pine - black spruce forest. Canadian Journal of Forest
Research 34: 1548-1560.
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McAllister, S. 2011. Synthesis of knowledge of extreme fire behavior: volume I for fire managers.
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23, 2002. Luso-Coimbra, Portugal.
, .1, .2
, , email@example.com
(Cruz et al. 2003a, Gould et al 2011
McKinion and Baker 1982, Mayer and Butler 1993)
Rothermel and Reinhardt
(Cruz et al. 2003, Gould et al. 2011
Albini et al
Alexander and Thomas 2003a,b
(Alexander and Cruz
Rothermel 1983, Norum and Miller 1984, Lawson and Armitage 2008).
BehavePlus (Andrews et al
Athanasiou and Xanthopoulos
II 3,0 m
Dimitrakopoulos et al Dimitrakopoulos
I m V II
I, II, V VI
Athanasiou and Xanthopoulos 2014).
Table 1. The values of the parameters of the four fuel models that were used as inputs for predicting surface fire
rate of spread (ROSpredicted) and flame length (FLpredicted) with BehavePlus.
I II V VI
1 HR (MTON/HA) 9.91 17.88 3.50 4.82
10 HR (MTON/HA) 6.80 13.30 1.02 0.49
100 HR (MTON/HA) 3.60 8.5 0.28 0
LIVE HERB (MTON/HA) 0 0 0 0
LIVE WOODY (MTON/HA) 7.70 10.60 0.85 0
1 HR S/V (1/CM) 55 55 65 78
LIVE HERB S/V (1/CM) - - - -
LIVE WOODY S/V (1/CM) 55 55 65 -
FUEL BED DEPTH (CM) 102.19 203.58 40.00 27.53
EXT MOISTURE (%) 34 34 20 14
HEAT CONTENT (J/G) 20000 20000 19054 18600
Athanasiou and Xanthopoulos (2010),
Athanasiou and Xanthopoulos
Alexander and Thomas (2003b), Clements et al Athanasiou and
Dimitrakopoulos Athanasiou and
NEWMDL BEHAVE (Burgan and
hr fuel bed depth
dead fuel moisture of extinction NEWMDL
ROSpredicted FLpredicted BehavePlus.
Table 2. ROSobserved and FLobserved observations per fuel type that were compared with the corresponding
BehavePlus predictions (ROSpredicted and FLpredicted values).
V 26 26
VI 18 16
h (Andrews et al
h Live Woody
p-value <0.001) (Athanasiou and Xanthopoulos 2014):
ROSobserved = 0.165 + 0.886 * ROSpredicted, adjusted R2 (1)
ROSobserved = 0.127 + 0.709 * ROSpredicted, adjusted R2 (2)
ROSobserved = 0.101 + 0.783 * ROSpredicted, adjusted R2 (3)
ROSobserved = -0.023 + 1.562 * ROSpredicted, adjusted R2 (4)
value1=0.052, p-value3=0.266 and p-value4
FLobserved (FLpredicted BehavePlus
V BehavePlus. FLobserved FLpredicted
FLpredicted (Athanasiou and Xanthopoulos 2014).
Athanasiou and Xanthopoulos
I V BehavePlus
Table 3. Solution of equations (1)-(4) for a range of values of ROSpredicted.
0 0.165 0.127 0.101 -0.023
1 1.051 0.836 0.884 1.539
2 1.937 1.545 1.667 3.101
3 2.823 2.254 2.450 4.663
4 3.709 2.963 3.233 6.225
5 4.595 3.672 4.016 7.787
6 5.481 4.381 4.799 9.349
7 6.367 5.09 5.582 10.911
8 7.253 5.799 6.365 12.473
9 8.139 6.508 7.148 14.035
10 9.025 7.217 7.931 15.597
(Deeming et al. 1977, Hirsch and Martell FLpredicted
Athanasiou and Xanthopoulos 2014).
V BehavePlus Cistus
spp Live Woody
Athanasiou and Xanthopoulos
(International Association of Wildland Fire
(Doctoral Student Scholarship Award
Wildfires in Mediterranean Shrublands, Phrygana, and Grasslands, in Greece:
Comparisons of Observed Fire Behaviour to Behaveplus Predictions
Athanasiou M.1and Xanthopoulos G.2
13673 Acharnes, Greece,
Terma Alkmanos, 11528, Athens, Greece, firstname.lastname@example.org
This paper presents a comparison of ninety five (95) Rate Of Spread (ROSobserved) and seventy(70)
Flame Length (FLobserved) observations of surface wildfire behavior in Greece with predictions from the
BehavePlus fire behavior prediction system for tall and short Mediterranean shrublands (maquis),
phryganic lands dominated by the small xeric shrub Sarcopoterium spinosum, and grass.
Four fuel models, which had been developed for Greece, were used to describe the four fuel types: a)
-schlerophyllous shrublands (1.5 -
ROSobserved values and BehavePlus ROSpredicted values, were correlated via linear regression for each of
the data subsets. The resulting four linear regression equations, with ROSobserved as the dependent
variable and ROSpredicted as the dependent, are statistically significant (p<0.001) and can be used for
More specifically, BehavePlus ROS predictions were close to ROSobserved so adjustment is not
considered as necessary. On the other hand, in the case of grasslands, BehavePlus under-predicts ROS
by approximately 50%. As the grass adjustment equation is statistically significant and its adjusted R 2
value is high (R2adjusted = 0.847), it should be used for adjusting BehavePlus ROS predictions in these
The analysis also shows that the equations for short maquis and Sarcopoterium spinosum phrygana
should also be used to adjust ROSpredic ted values to the lower expected values, but this should be done
with caution due to weaknesses of the equations.
In regard to flame length (FL) predictions from BehavePlus significant deviations were found for all
four fuel types. The most important finding of this analysis was that BehavePlus consistently under
predicted flame length for the Sarcopoterium spinosumdominated phrygana.The under prediction was
significant and its importance is even greater because the underestimation takes place in a band of FL
values that includes the threshold value of 1.2 m which is considered as the limit for direct attack on
the flames with hand tools. In ten (10) out of N=26 cases, the prediction was for FL<1,2 m while the
observed FL value was well above this threshold. This is an important result that can be very useful for
the safety of firefighters and it should be seriously taken into consideration in operational firefighting
in the country.
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