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Transcript of Evaluating landscape flammability through simulation modeling Marc Parisien 1, Victor Kafka 2,...
Evaluating landscape flammability through simulation modeling
Marc Parisien1, Victor Kafka2, Bernie Todd1, Kelvin Hirsch1, and Suzanne Lavoie1
1Canadian Forest Service2Parks Canada Agency
Presentation to the NCE Meeting in Toronto, Feb 11/12, 2003
Natural Resources Canada Ressources naturelles CanadaCanadian Forest Service Service canadien des forets
Presentation to the NCE Meeting in Toronto, Feb 11/12, 2003
Natural Resources Canada Ressources naturelles CanadaCanadian Forest Service Service canadien des forets
Presentation to the NCE Meeting in Toronto, Feb 11/12, 2003
Natural Resources Canada Ressources naturelles CanadaCanadian Forest Service Service canadien des forets
•Increasing knowledge of factors affecting landscape flammability
•However, predicting landscape flammability has been largely unattained
•This is even more challenging in the North American boreal forest
• Most area burned is caused by few large and intense fires
• Large spatial variations in the fire regime
Introduction
Presentation to the NCE Meeting in Toronto, Feb 11/12, 2003
Natural Resources Canada Ressources naturelles CanadaCanadian Forest Service Service canadien des forets
What we needWhat we need
• To quantatively evaluate landscape flammability (i.e., burn probability)
Introduction
What we knowWhat we know
• It is possible to predict individual fire behavior using the factors that affect physical fire spread (weather, fuels, topography)
• Larger-scale aspects of the fire regime are best predicted probabilistically (i.e., ignitions, fire weather)
What we haveWhat we have• Fire growth models simulating physical fire spread
• Historical wildfire information
Presentation to the NCE Meeting in Toronto, Feb 11/12, 2003
Natural Resources Canada Ressources naturelles CanadaCanadian Forest Service Service canadien des forets
Objective
1. To evaluate burn probabilities (BP) across a landscape using a modelling approach that combines
the physical components of fire spread
other probabilistic components of the fire regime
BURN-P3 BURN-P3 (Probability, Prediction, and (Probability, Prediction, and Planning)Planning)
Maps the probability of burning of the actual actual landscapelandscape under current burning conditionscurrent burning conditions submitted to historical variabilityhistorical variability
Presentation to the NCE Meeting in Toronto, Feb 11/12, 2003
Natural Resources Canada Ressources naturelles CanadaCanadian Forest Service Service canadien des forets
Study Area: Central Saskatchewan
Area: 15 M hectares
Presentation to the NCE Meeting in Toronto, Feb 11/12, 2003
Natural Resources Canada Ressources naturelles CanadaCanadian Forest Service Service canadien des forets
Components of the Model
PHYSICAL FIRE GROWTHPHYSICAL FIRE GROWTH
Determined from historical fire databases
The information is drawn from statistical distributions
Simulates the growth of escaped fires (200 ha)
Mec
han
isti
cM
ech
anis
tic
FIRE WEATHERFIRE WEATHER
NUMBER OF ESCAPED FIRESNUMBER OF ESCAPED FIRES
NUMBER OF FIRE SPREAD DAYSNUMBER OF FIRE SPREAD DAYS
IGNITION LOCATIONSIGNITION LOCATIONS
Pro
bab
ilis
tic
Pro
bab
ilis
tic
Presentation to the NCE Meeting in Toronto, Feb 11/12, 2003
Natural Resources Canada Ressources naturelles CanadaCanadian Forest Service Service canadien des forets
• Raster-based model
• Based on Canadian Forest Fire Danger Rating System theory
•Rate of spread equations
•Fire behavior
• Inputs•Hourly fire weather
•Forest fuels
•Topography
• Produces maps of the fire perimeter and fire behavior
WILDFIRE Fire Growth WILDFIRE Fire Growth ModelModel
Fire growth modeling
Presentation to the NCE Meeting in Toronto, Feb 11/12, 2003
Natural Resources Canada Ressources naturelles CanadaCanadian Forest Service Service canadien des forets
Components of the Model
NUMBER OF ITERATIONSNUMBER OF ITERATIONS
FIRE WEATHERFIRE WEATHER
NUMBER OF ESCAPED FIRESNUMBER OF ESCAPED FIRES
NUMBER OF FIRE SPREAD DAYSNUMBER OF FIRE SPREAD DAYS
IGNITION LOCATIONSIGNITION LOCATIONS
PHYSICAL FIRE GROWTHPHYSICAL FIRE GROWTH
SIMULATIONS STOREDSIMULATIONS STORED
Probability of burning Probability of burning ==
Number of times each cell Number of times each cell burnedburned
Number of iterationNumber of iteration
Presentation to the NCE Meeting in Toronto, Feb 11/12, 2003
Natural Resources Canada Ressources naturelles CanadaCanadian Forest Service Service canadien des forets
Presentation to the NCE Meeting in Toronto, Feb 11/12, 2003
Natural Resources Canada Ressources naturelles CanadaCanadian Forest Service Service canadien des forets
Presentation to the NCE Meeting in Toronto, Feb 11/12, 2003
Natural Resources Canada Ressources naturelles CanadaCanadian Forest Service Service canadien des forets
Presentation to the NCE Meeting in Toronto, Feb 11/12, 2003
Natural Resources Canada Ressources naturelles CanadaCanadian Forest Service Service canadien des forets
Presentation to the NCE Meeting in Toronto, Feb 11/12, 2003
Natural Resources Canada Ressources naturelles CanadaCanadian Forest Service Service canadien des forets
Presentation to the NCE Meeting in Toronto, Feb 11/12, 2003
Natural Resources Canada Ressources naturelles CanadaCanadian Forest Service Service canadien des forets
Presentation to the NCE Meeting in Toronto, Feb 11/12, 2003
Natural Resources Canada Ressources naturelles CanadaCanadian Forest Service Service canadien des forets
Presentation to the NCE Meeting in Toronto, Feb 11/12, 2003
Natural Resources Canada Ressources naturelles CanadaCanadian Forest Service Service canadien des forets
Presentation to the NCE Meeting in Toronto, Feb 11/12, 2003
Natural Resources Canada Ressources naturelles CanadaCanadian Forest Service Service canadien des forets
Presentation to the NCE Meeting in Toronto, Feb 11/12, 2003
Natural Resources Canada Ressources naturelles CanadaCanadian Forest Service Service canadien des forets
Presentation to the NCE Meeting in Toronto, Feb 11/12, 2003
Natural Resources Canada Ressources naturelles CanadaCanadian Forest Service Service canadien des forets
Presentation to the NCE Meeting in Toronto, Feb 11/12, 2003
Natural Resources Canada Ressources naturelles CanadaCanadian Forest Service Service canadien des forets
Presentation to the NCE Meeting in Toronto, Feb 11/12, 2003
Natural Resources Canada Ressources naturelles CanadaCanadian Forest Service Service canadien des forets
Burn probability (%)
Burn probability mapBurn probability map
for the 2003 fire seasonfor the 2003 fire season
Presentation to the NCE Meeting in Toronto, Feb 11/12, 2003
Natural Resources Canada Ressources naturelles CanadaCanadian Forest Service Service canadien des forets
What’s next?
1.1. Integrating Prometheus in BURN-P3Integrating Prometheus in BURN-P3• More realistic fire growth modeling
• Increased functionality
• Greater user base
2.2. Creating a graphic user interface for Creating a graphic user interface for BURN-P3BURN-P3
• BURN-P3 will become one of the first fire management strategic planning tools
• Available Canada-wide, to any interested user
• Flexible, user-friendly tool (i.e., not a strict model)
• On-going process, open to suggestions from operations
Presentation to the NCE Meeting in Toronto, Feb 11/12, 2003
Natural Resources Canada Ressources naturelles CanadaCanadian Forest Service Service canadien des forets
Number of fires from 1981 to 2002
Julian Day
Nu
mb
er
of
fire
s
50 150 250 350
Spring Summer
Study area
Presentation to the NCE Meeting in Toronto, Feb 11/12, 2003
Natural Resources Canada Ressources naturelles CanadaCanadian Forest Service Service canadien des forets
1
Number of fires from 1981 to 2002
Study area
Presentation to the NCE Meeting in Toronto, Feb 11/12, 2003
Natural Resources Canada Ressources naturelles CanadaCanadian Forest Service Service canadien des forets
Fire Size Distribution
0.0 0.3 0.6 0.9 1.2 1.5
Size class (105 ha)
0.0 0.3 0.6 0.9 1.2 1.5
Pro
port
ion
of f
ires
(%)
0
25
50
75Historical fires Simulated fires
Presentation to the NCE Meeting in Toronto, Feb 11/12, 2003
Natural Resources Canada Ressources naturelles CanadaCanadian Forest Service Service canadien des forets
Reduction in BP
Reduction in BP outside the perimeterReduction in BP outside the perimeter
1.1. Large burns disrupt the paths of incoming Large burns disrupt the paths of incoming
firesfires
2.2. The chance that fires ignite nearby is The chance that fires ignite nearby is
decreaseddecreased
500 iterations
Objective #2: Heterogeneous (actual) Objective #2: Heterogeneous (actual) landscapelandscape
Peripheral reduction in BP due to:
1. Different forest fuels
2. The amount and configuration of landscape features
3. The direction of predominant winds
73,000 ha
Presentation to the NCE Meeting in Toronto, Feb 11/12, 2003
Natural Resources Canada Ressources naturelles CanadaCanadian Forest Service Service canadien des forets
Objective #2: homogeneous landscapes
Reduction in BP Reduction in BP according to:according to:•The shape of old burns
•The size of old burns• 1000 ha
• 10,000 ha
• 100,000 ha
All factors are held All factors are held constant except:constant except:
•Fire weatherFire weather
•Number of fire spread Number of fire spread daysdays
Old burn (non fuel)
100,000 ha
Boreal spruce fuel type
(most flammable)
Inside buffer
Average BP = 1.9%Average BP = 1.9%
Outside buffer
Average BP = 2.6%Average BP = 2.6%
5-km buffer
1000 iterations
1-km buffer
2 to 5-km buffer1-km buffer
Average BP = 1.5%Average BP = 1.5%
2 to 5-km buffer
Average BP = 2.0%Average BP = 2.0%
Percent difference in BP between:•The two buffers:The two buffers: 25% 25%•The 1-km buffer and outside The 1-km buffer and outside
the buffer:the buffer: 42% 42%
1000 iterations
Presentation to the NCE Meeting in Toronto, Feb 11/12, 2003
Natural Resources Canada Ressources naturelles CanadaCanadian Forest Service Service canadien des forets
Reduction in Landscape Flammability
Fires 1945 to 2002Present FBP fuels
(LANDSAT)
Non fuel
Presentation to the NCE Meeting in Toronto, Feb 11/12, 2003
Natural Resources Canada Ressources naturelles CanadaCanadian Forest Service Service canadien des forets
SELECTION OF FIRE WEATHER RECORDS
(DAYS)
Determine ISI for HFI 4000 kW/m for C-2, C-3, and C-4
12 years of historicaldaily fire weather data
(40 wx stations) Store by season (2) and weather region (8)
TOTAL =TOTAL =
16 weather files16 weather files
Retrieve days with high/extreme fire weather
(ISI 8.6)