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Spatially Explicit Burn Probability Spatially Explicit Burn Probability across A Landscape in Extreme Fire across A Landscape in Extreme Fire

Weather YearWeather Year

Wenbin Cui, David L. MartellWenbin Cui, David L. Martell

Faculty of Forestry,Faculty of Forestry, University of TorontoUniversity of Toronto

22

Outline Outline

Burn Probability (BP) ModelBurn Probability (BP) Model

BP Model ApplicationBP Model Application Predict BP in an Extreme Fire Weather YearPredict BP in an Extreme Fire Weather Year

DiscussionsDiscussions Possible Applications, Limitations & Future Possible Applications, Limitations & Future

ResearchResearch

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Burn Probability of Next Fire SeasonBurn Probability of Next Fire Season

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Burn Probability Burn Probability CalculationCalculation

Forest Forest Burn ProbabilityBurn Probability of next fire of next fire season at location(i,j)season at location(i,j)

BPBPxyxy: Burn probability at location (x,y): Burn probability at location (x,y) N: number of years(iterations)N: number of years(iterations) NNxy: xy: number of times of having been burned at number of times of having been burned at location(i,j)location(i,j)

N

NBP xy

Nxy Lim

55

Main Factors affecting Main Factors affecting BPBP

Fuel Type

Fire Occurrence

Topography

(elevation, slopes & slope aspects)

Weather

Level of Protection

Fire

Spr

ead

66

Burn Probability ModelBurn Probability Model

Fuel Type

Fire Occurrence

Level of Protection

Fire Spread

SPATIAL

Daily Weather

Burn Probability

77

Fuel Type Fuel Type ClassificationClassification

The Canadian Forest Fire Behavior Prediction (FBP) System is used

88

Burn Probability ModelBurn Probability Model

Fuel Type

Fire Occurrence

Level of Protection

Fire Spread

Weather

Burn Probability

Fire Occurrence

99

Fire OccurrenceFire Occurrence That total number of fires will occur each That total number of fires will occur each

year follows a Poisson distribution with an year follows a Poisson distribution with an average number equal to historical average average number equal to historical average number of fires in this landscape.number of fires in this landscape.

The conditions that cause past ignition The conditions that cause past ignition pattern will continue in the next fire seasonpattern will continue in the next fire season

affected by the fuel at the location and the affected by the fuel at the location and the weather condition at the time of ignition.weather condition at the time of ignition.

Ignition Patterns differ by causeIgnition Patterns differ by cause

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Fire ignition patterns Fire ignition patterns (density)(density)

People-caused and Lightning-People-caused and Lightning-caused density mapscaused density maps

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Burn Probability ModelBurn Probability Model

Fuel Type

Fire Occurrence

Level of Protection

Fire Spread

Weather

Burn ProbabilityLevel of Protection

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Level of ProtectionLevel of Protection

Percent of forest fires controlled at initial Percent of forest fires controlled at initial attack (IA)attack (IA)

If a fire is controlled, it only “burns” one If a fire is controlled, it only “burns” one cell of the landscape. Otherwise it cell of the landscape. Otherwise it escapes IA and we used a fire growth escapes IA and we used a fire growth model to “spread” it.model to “spread” it.

Escape Index: (EI)Escape Index: (EI) HFI is the Head Fire Intensity (kW/m)HFI is the Head Fire Intensity (kW/m) RT is response time (hours)RT is response time (hours)

RTHFIEI

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Spatially Different Spatially Different Response Time to Forest Response Time to Forest

FiresFires

10 hours2 hours

3 hours

4 hours

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Burn Probability ModelBurn Probability Model

Fuel Type

Fire Occurrence

Level of Protection

Weather

Burn Probability

Fire Spread

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Fire SpreadFire Spread

The escaped fires are simulated by The escaped fires are simulated by using using WildfireWildfire program. program.

Wildfire is a fire growth model that Wildfire is a fire growth model that incorporates GIS data, FBP System incorporates GIS data, FBP System calculations and weather data to calculations and weather data to estimate patterns of hourly fire estimate patterns of hourly fire perimeters. (Todd 1999)perimeters. (Todd 1999)

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Burn Probability ModelBurn Probability Model

Fuel Type

Fire Occurrence

Level of Protection

Fire Spread

Weather

Burn Probability

Weather

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WeatherWeather

Daily historical weather dataDaily historical weather data Each record includes:Each record includes:

Temperature, Relative Humidity, Temperature, Relative Humidity, Wind speed, wind direction, rain Wind speed, wind direction, rain fall, FFMC, DMC, DC, BUI, ISIfall, FFMC, DMC, DC, BUI, ISI

Data from more than one Data from more than one station can be used. station can be used.

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Output of the ModelOutput of the Model

BP Maps

Fire Information

Burn FractionsBP

Model

Other

1919

Application of BP Model in an Application of BP Model in an Extreme Fire Weather YearExtreme Fire Weather Year

Study area

Application of the Model

2020

Location of Location of Romeo Malette Forest Romeo Malette Forest

(RMF)(RMF)

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FBP Fuel TypesFBP Fuel Types

2,028,224 ha

C114%

C225%

C3 7%Other

3%

Mixedwood32%

NonFuel8%

Water11%

C1

C2

C3

Other

Mixedw ood

NonFuel

Water

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Fire HistoryFire History

From 1976 to 1999 there are 909 fires.

The average is 37.875/year.

The average area burned a year is 1136.15 ha.

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Historical Ignition PatternsHistorical Ignition Patterns

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Annual Burn ProbabilityAnnual Burn Probability

0.0567%

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Burn Probability in an Extreme Burn Probability in an Extreme Weather YearWeather Year

What is an EXTREME Fire Weather Year?What is an EXTREME Fire Weather Year? The year that has most ESCAPED firesThe year that has most ESCAPED fires

Burned more areaBurned more area

1991 1991 Average Number -75 (real number)Average Number -75 (real number)

Daily WeatherDaily Weather

LOP - 90.7% (Uniform response time)LOP - 90.7% (Uniform response time)

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Burn Probability under Extreme Burn Probability under Extreme Weather Conditions (1991)Weather Conditions (1991)

0. 258%

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Burn Fractions by Fuel TypeBurn Fractions by Fuel Type

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

C1 C2 C3 C4 C5 D1 S1O1a

M12

_25

M12

_50

M12

_75

NonFue

l

Water

Total

FBP Fuel Type

Bu

rn F

ract

ion

s (%

)

2828

Applications of Burn Probability Model

BP ModelFuel

Ignition

Response time(LOP)

Assessment &Decision

FireSmartHarvest

People-caused ignition control

Fuel Management

FireSmart Roads

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Used in other modelsUsed in other models

Forest Management Models Forest Management Models (FireSmart)(FireSmart)

Burn Probability by StandsBurn Probability by Stands

Burn Fractions by species, standBurn Fractions by species, stand

WUI Fire Management WUI Fire Management

Wildlife Habitat Suitability AssessmentWildlife Habitat Suitability Assessment

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Limitations and Future Limitations and Future WorkWork

Spotting is not included in fire spreadSpotting is not included in fire spread - - Prometheus with spotting capability Prometheus with spotting capability will be used in futurewill be used in future

Use of Regional Climate ModelUse of Regional Climate Model

Produce more BP maps!Produce more BP maps!

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Acknowledgement

Kelvin Hirsch, Victor Kafka, Marc-André Parisien, Bernie Todd

Canadian Forest Service, Northern Forestry Center

Jennifer Johnson, Mike B. Wotton, Ana C. Espinoza, Mariam Sanchez G, Justin Podur and Jennifer Beverly

Faculty of Forestry, University of Toronto

Sustainable Forest Management Network

Jim Caputo, Robert McAlpineOntario Ministry of Natural Resources

Tembec

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Thanks !Thanks !

Comments & Comments & Questions?Questions?

Comments & Comments & Questions?Questions?