11 forest fire - moisture content of mediterranean...
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FOREST FOCUS symposium, Brussels, October 22nd 2007 1Moisture content of wildland fuel
Towards assessmentand optimisation
of the French network "Moisture content of Mediterranean wildland fuels"
INRA: C MORO, D PORTIER, E RIGOLOT, JC VALETTECEMAGREF / CIRAD / ENGREF: C DELENNE, M DESHAYES
Météo-France: B SOL, E BERTRANDONF – Mission Zonale DFCI: Y DUCHE, R SAVAZZI
MTDA: D ALEXANDRIAN, M ALEXANDRIAN
The ignorant asserts, the savant doubts and the wise thinksAristote
FOREST FOCUS symposium, Brussels, October 22nd 2007 2Moisture content of wildland fuel
Content
1. Context2. Objectives3. French Mediterranean network 4. Material and Methods5. Results 6. Conclusions and Perspectives
FOREST FOCUS symposium, Brussels, October 22nd 2007 3Moisture content of wildland fuel
Context: Importance of wildland fires
FOREST FOCUS symposium, Brussels, October 22nd 2007 4Moisture content of wildland fuel
Context: Weather conditions
FOREST FOCUS symposium, Brussels, October 22nd 2007 5Moisture content of wildland fuel
Context: Weather conditions
FOREST FOCUS symposium, Brussels, October 22nd 2007 6Moisture content of wildland fuel
Context: Weather conditions
FOREST FOCUS symposium, Brussels, October 22nd 2007 7Moisture content of wildland fuel
Context: Flammability and FMC
FOREST FOCUS symposium, Brussels, October 22nd 2007 8Moisture content of wildland fuel
Objectives
1. To standardise and disseminate the methods and procedures for:– collecting, storing and transporting the wildland fuel samples from the field to the
laboratory– determining in the laboratory the fuel moisture content of each sample– entering the data in the wildland fuel data base available under the Web site
2. To enhance the quality of the data collected on the plots and the pertinence of the French Mediterranean network
3. To improve the analysis of the temporal and spatial variations of the specific moisture content of wildland fuels:
– for determining the specific rates of moisture content decreases and consequently– for better predicting the contribution of the wildland fuel to wildland fire risk ignition
and initial propagation4. To establish statistical relationships between FMC of wildland fuel and:
– climatic parameters like Soil Water Reserve and– codes like Duff moisture code DMC and Drought code DC
FOREST FOCUS symposium, Brussels, October 22nd 2007 9Moisture content of wildland fuel
Objectives
5. To determine the nature and pertinence of biological data to the prevention and the prediction of wildland fires danger
6. To look for linkages between FMC, wildland fires occurrences and data extracted from satellite images
7. To replace progressively and partially the field measures by automatic analysis of the satellites images for enhancing the location of wildlandfire risk
8. To provide pertinent information in term of wildland fire risks of ignition and initial propagation towards
– managers of wildland areas, – wildland fires fighting organisations – the teams in charge of predicting the wildland fire danger
9. To made these data available to end-users and stakeholders through an user-friendly Web site
FOREST FOCUS symposium, Brussels, October 22nd 2007 10Moisture content of wildland fuel
French Mediterranean network: plots30
plo
ts +
3 IN
RA
plo
tsin
itial
ly 2
per
dep
artm
ent
now
, 3 p
lots
in m
ore
thre
aten
ed
area
s (0
6, 2
A, 2
B, 8
3)
FOREST FOCUS symposium, Brussels, October 22nd 2007 11Moisture content of wildland fuel
French Mediterranean network: species
Species PlotsCistus monspelliensis 10 Erica arborea 7 + 2Rosmarinus officinalis 6Cistus albidus 5 Arbutus unedo 3 + 2Quercus coccifera 5 Quercus ilex 4 + 1Erica scoparia 3Genista cinerea 3 Juniperus oxycedrus 3Buxus sempervirens 1 + 1
Species PlotsAcacia dealbata 1 Calluna vulgaris 1 Cistus salvaefolius 1Cytisus scoparius 1Cytisus sessiliflora 1Erica cinerea 1 Genista purgens 1Genista scorpius 1Quercus lanuginosa 1
FOREST FOCUS symposium, Brussels, October 22nd 2007 12Moisture content of wildland fuel
French Mediterranean network: databases
1. FMC (per plot, per species and per date)Up to five validated values FMC1 to FMC5FMC: the average of the validated valuesavailable on the WEB site
2. Soil Water Reserve SWR (daily calculation)Using the data of the four nearest weather stations to each plotInterpolating the values following a 1/d2 lawDetermining a “local” SWR for each plotStoring the values of each plot and for each date
3. Duff Moisture Code DMC and Drought Code DC (daily) Following the same procedure as SWR
FOREST FOCUS symposium, Brussels, October 22nd 2007 13Moisture content of wildland fuel
Materials and methods
1. To collect wildland fuel
To prepare containers, bags, balance, forms, and tools
To sample the wildland fuel
To fill and store the containers
To fill the form
FOREST FOCUS symposium, Brussels, October 22nd 2007 14Moisture content of wildland fuel
Materials and methods
2. Back to the laboratory, –to determine the mass of the container and of the fuel (FM +T)
–to store the opened container in the oven at 60°C during 24h
–to separately determine the oven-dried mass of the fuel ODM and of the container T
FOREST FOCUS symposium, Brussels, October 22nd 2007 15Moisture content of wildland fuel
Materials and methods
2. Back to the laboratory, – to enter these parameters and
comments in the form availableunder the Web site and, consequently, update the database
FM +T ODM T FMC
Indicate here local observations, precipitation, and any useful information
Validating/invalidating
the data
Determiningthe average of the validated
data
100 * ((FM+T) – T ) – ODM TEf = ------------------------------------
(FM+T) – T
100 * ((FM+T) – T ) – ODMFMC= -----------------------------------
ODM
FOREST FOCUS symposium, Brussels, October 22nd 2007 16Moisture content of wildland fuel
Materials and methods
3. To register local weather conditions,
– Air temperature and humidity
– Wind speed and direction
4. To determine– Soil water reserve
SWR– Duff Moisture Code
DMC– Drought Code DC SWR
If Precipitationj-1 > 50 mm then Precipitationj-1 = 50 mm
SWRj = SWRj-1 + Precipitationj-1 - PETthj-1 * SWRj-1 / 150If SWRj > 150 mm then SWRj = 150 mm
FOREST FOCUS symposium, Brussels, October 22nd 2007 17Moisture content of wildland fuel
Materials and methods
Canadian Fire Weather Index
– Duff Moisture Code DMC
– Drought Code DC
http://fire.nofc.cfs.nrcan.gc.ca/
FOREST FOCUS symposium, Brussels, October 22nd 2007 18Moisture content of wildland fuel
Results 1: Fuel Moisture Content DatabasePlot D2BS1
SpeciesYear
Five moisture contents Tef Average
Modifyingthe row
Deletingthe row
Protectingthe row
Printingthe row (PDF file)
Adding a comment
No measure due to rain
Invalidateddata
FOREST FOCUS symposium, Brussels, October 22nd 2007 19Moisture content of wildland fuel
Results 2: Variation of Fuel Moisture Content
Seasonalvariation
One of the fivevalid values
Invalidatedvalue
Averagevalue
FOREST FOCUS symposium, Brussels, October 22nd 2007 20Moisture content of wildland fuel
Results 2: Variation of Fuel Moisture Content
Seasonalvariation
with a long drought period:
one local rain between
August 20th
andAugust 24th
FOREST FOCUS symposium, Brussels, October 22nd 2007 21Moisture content of wildland fuel
Results 2: Variation of fuel moisture contentS
patia
l var
iatio
n of
the
aver
age
four
plo
ts D
13S
1, D
13S
2, D
04S
1, D
84S
2
FOREST FOCUS symposium, Brussels, October 22nd 2007 22Moisture content of wildland fuel
Results 2: Variation of fuel moisture contentY
early
var
iatio
nfo
ur y
ears
: 200
3, 2
004,
200
6, 2
007
2006’s spring is drier than 2003’s one;
Erica arborea’s FMC is lower
FOREST FOCUS symposium, Brussels, October 22nd 2007 23Moisture content of wildland fuel
Results 3: FMC and SWR versus time
FMC decrease laws
FOREST FOCUS symposium, Brussels, October 22nd 2007 24Moisture content of wildland fuel
Results 4: FMC versus SWR, DC, DMCD
84S
4, 2
007,
Arb
utus
une
do, E
rica
arbo
rea
FMC=f(dmc)FMC=f(dmc)
FMC=f(swr) FMC=f(dc)
FOREST FOCUS symposium, Brussels, October 22nd 2007 25Moisture content of wildland fuel
Results 5: FMC thresholds and wildland fire risks
Rule of thumb, for all species
Level FMC TEfLow if the two moisture content are higher than 70 40Medium if at least one moisture content is between 70-55 40-35High if at least one moisture content is between 55-40 35-30Extreme if at least one moisture content is lower than 40 30
FOREST FOCUS symposium, Brussels, October 22nd 2007 26Moisture content of wildland fuel
Twice a week synthesisResults 5: FMC thresholds and wildland fire risks
Five valuesand average
Previousaverage
Difference= if Idif I < 0.5
- or + if 0.5 < Idif I < 5-- or ++ if idif I > 5
Minimum value on this plot and for
this species
since the beginning
of the network
Minimum value on this plot and for
this species
during the current ten
days period
since the beginning
of the network
LowMediumHighExtremeUnknownRain
FOREST FOCUS symposium, Brussels, October 22nd 2007 27Moisture content of wildland fuel
Results 5: FMC thresholds and wildland fire risksW
ildla
nd fi
re ri
sk c
lass
esac
cord
ing
to fo
ur F
MC
leve
ls,
the
map
is u
pdat
ed tw
ice
a w
eek
durin
g ea
ch S
umm
er c
ampa
ign
Risk classeslowmediumhighextremeunknownno measure
rainy period
FOREST FOCUS symposium, Brussels, October 22nd 2007 28Moisture content of wildland fuel
Results 6: FMC and satellite data
To compare FMC data to data delivered by MODIS satelliteMajor constraints
Spatial resolution of MODIS images is not enough accurate compare to local heterogeneities
Temporal resolution of MODIS images (every 16 days) is not adapted to FMC weekly variations
Daily MODIS data are adequate but directional effects of the sensor are not corrected and atmospheric effects are not well corrected
Most of Mediterranean shrub species are adapted to summer drought, amplitude of FMC variations is of the same order of magnitude as the surrounding noise
FOREST FOCUS symposium, Brussels, October 22nd 2007 29Moisture content of wildland fuel
Results 6: FMC and satellite data
To compare FMC data to satellites dataNeeds
Improvement of the characteristics of MODIS and SPOT-4 HVR1 data
To select and monitor species on homogeneous large area (1 km2)To select plots where the shrub cover is total (100%)To focus on drought sensitive species
FOREST FOCUS symposium, Brussels, October 22nd 2007 30Moisture content of wildland fuel
Conclusions and Perspectives
Positive
1. Methods and procedures have been successfully standardised and disseminated towards the professionals:
- they collect, store and transport the wildland fuel samples from the field to the laboratories and
- some of them determine by themselves the fuel moisture content of each sample and enter the data in the wildland fuel data base available under the Web site
- but, this effort must be maintained during the future campaigns
2. Thanks common efforts, the quality of the collected data and FMC, and the pertinence of the French Mediterranean network have been enhanced
3. An user-friendly, operational and innovative Web site has been implemented and able to be used during the following campaigns
FOREST FOCUS symposium, Brussels, October 22nd 2007 31Moisture content of wildland fuel
Conclusions and Perspectives
Equal
4. The analysis of temporal and spatial variations of the specific FMC of wildland fuels is still on going:
– fitting the data with polynomial equations permits to determine yearly and specific laws of FMC decreases and consequently
– elaborating models easy to be used by professionals for predicting the contribution of the wildland fuel to wildland fire risk ignition and initial propagation
5. Statistical relationships between FMC, SWR and DC have been established per plot, species and year, the synthesis is on going; the relation with DMC is not so regular
6. The nature of the contribution of biological data to the prevention and the prediction of wildland fires danger has been identified
7. The pertinence of the information in term of wildland fire risks provided towards foresters and wildland fires fighters and those predicting the wildland fire danger, has been recognised by these end-users
FOREST FOCUS symposium, Brussels, October 22nd 2007 32Moisture content of wildland fuel
Conclusions and Perspectives
Negative
8. The added value of biological data to the prevention and the prediction of wildland fires danger is not clear compared to those of meteorological parameters
9. No clear linkages between FMC, wildland fires occurrences and data extracted from satellite images mainly due to:
• the occurrence and location of catastrophic wildland fires is not a relevant indicator
• spatial and temporal resolution of satellite images is not adapted to the heterogeneities of the French Mediterranean wildland areas which are largely structured by human activities, and this, since many centuries
FOREST FOCUS symposium, Brussels, October 22nd 2007 33Moisture content of wildland fuel
Conclusions and Perspectives
In the future
1. To improve the rules on thumbs and adjust them to the behaviours and traits of the most important species
2. To identify and focus on “sentinel” species like Rosmarinus officinalis3. Monitoring species developing superficial roots4. Monitoring species presenting a FMC closely related to DC5. To elaborate biological risk indexes based on FMC decrease laws6. To compare the advantages and disadvantages of destructive methods
to non-destructive ones for determining FMC, and to substitute the first by the second if the balance is positive for the second ones
7. To maintain active the Web site for following summer campaigns