Transcript Slide 1

Forest Fire Detection in
Ontario
Rob McAlpine
Program Leader, Forest Fire Science and Technology
Ontario Ministry of Natural Resources
Aviation and Forest Fire Management Branch
Talk Outline
Outline of Fire Management in Ontario
History of Fire Detection
Current Detection operations
Detection Results
Challenges
Ontario’s Fire Management Program
Forests cover 85% of Ontario’s land area
and forest fires have shaped much of this
environment.
Land cover composed primarily
of Boreal and Mixedwood Forests.
Ontario averages roughly 1,300
fires annually.
$94 million spent annually to protect
communities and natural resources.
$4.1 billion in Gross Provincial Income
annually attributed to forest fire protection.
Policy
Fire Management Strategies
•
•
•
•
•
•
6 Fire Management Zones
Southern Ontario
Parks
Great Lakes/St. Lawrence
Boreal
Northern Boreal
Hudson Bay
• Ecoregion-based planning
rather than zones based on
geographically or politically
based
Policy
Fire Management Strategy
• Emphasizes the need to balance fire response and fire
use
• Performance targets are aligned to policy objectives
• Balancing fire response against risk and ecological benefits.
• New performance measures have been developed:
• Forest Depletion Area Burned
• Hazard Reduction Area Burned
• Ecosystem Renewal Area Burned
• A flexible response to fires through the concept of
Managed Fire.
Performance
The key performance measure is
Initial Attack Success
Target is 96% IA Success
Annual Number of Fires
2500
10 year average - 1,283
Number of Fires
2000
1500
1000
500
0
1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005
Year
Number of Fires
10 Year Average
5 Year Average
Annual Hectares Burned
700,000
10 year average – 152,188
Area in Hectares
600,000
500,000
400,000
300,000
200,000
100,000
0
1995
1996
1997
Area in Hectares
1998
1999
2000
2001
Year
10 Year Average
2002
2003
2004
5 Year Average
2005
Organization
•
•
• Two Regional Fires Centers direct day-to
day operations
• A Provincial Fire Centre oversees two
Fire Region Centres
• 29 Attack bases
• 225 Permanent staff and 760 seasonal
positions
District Office
Response Centre
Detection in Ontario
At the turn of the century Ontario began to
build towers
Most towers were erected between 1920
and 1950
At the peak there were 320 active towers
During the late 1960’s and early 1970’s
most towers were decommissioned –
replaced with Aerial detection
Current Fire Detection Program
• Aerial - Fleet of 15 Contract Aircraft
• Public - Common reporting system
• Reports direct to Fire Centres
Detection Planning
Aerial Detection
advantage is flexibility
Detection planning is
based on risk, expected
fire starts, and expected
fire behavior
Detection Costs
Basing fees = $675,000 for 15 contract
aircraft
Positioning Fees = $225,000
Flying costs = $325 to $635 /hour/aircraft.
Average 270 hours per aircraft for
approximate flying costs $2,000,000
Spend around $3.0 million annually on
organized detection
Results
Or:
– What did we buy with that $3,000,000?
Or:
– Some Embarrassing Statistics
Other
3%
Random Aerial
26%
Organized
Detection
23%
Random Ground
48%
Sources of Fire Reports
Percent Discovery By Type
FWI Class
Organized Detection
Random Detection
Low
53%
Moderate
55%
High
51%
Extreme
50%
47%
45%
49%
50%
Lightning Fires Only
Discovery Size (ha)
FWI Class
Low
Moderate
High
Extreme
Organized Detection
0.37
0.51
0.69
1.01
Random Detection
0.50
0.43
0.60
0.71
Challenges
Performance measures
Investment level
Integration of new technology
Performance Measures
Audit Results
Working towards A robust performance
measure
Recognize Detection as Part of a larger
system
Life Cycle of a Forest Fire
Detection Performance
Goal of Forest Fire Detection:
Deliver Fires to Suppression
Organization at a state that guarantees
a high probability of IA success at a
minimum cost.
Draft Goal
Detection Performance
Goal of Organized Forest Fire Detection:
Deliver Fires to Suppression
Organization at a state that guarantees
a high probability of IA success without
competing with other detection sources
Draft Goal
Conceptual Detection Target
Expected Fire Behavior
96% likely successful
Initial Attack
Different Suppression
Weights
Detection Size
Detection Performance
Complicating Factors
Cost Trade Offs
– Suppression weight vs additional detection
Build in “Random Detection” into system
– do not want to compete
Summary
Ontario’s Fire Management Strategy allows for Managed
Fire
Fire load and area burned is highly variable
Ontario uses a fleet of contract aircraft for fire detection
Most fires are detected by “random” sources
Working towards a robust performance measure
Thank You