Forest Fire Detection in the Wildland-Urban Interface James Barnier Wisconsin Department of Natural...

Forest Fire Detection in the

Wildland-Urban Interface

James Barnier

Wisconsin Department of Natural Resources

Division of Forestry

FERIC Wildfire Detection Workshop

March 25 – 27, 2003

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Alaska

Alaska

QUEBEC

ONTARIO

ALBERTAMANITOBA

BRITISH COLUMBIA

NUNAVUT

SASKATCHEWAN

NORTHWEST TERRITORIES

NEWFOUNDLAND

NEW BRUNSWICK

YUKON TERRITORIES

Several Detection Options:

• Public reporting

• Fixed lookouts

• Ground patrols

• Air patrols

• Lightning detectors

• Satellite imagery

911 Availability

Choice of a Detection Method:

• Risk

• Hazard

• Value

Research Objective:

• Evaluate the performance and cost-effectiveness of public and organized wildfire detection methods in the wildland-urban interface

The Study Area:

Forest covertypes

Maple-Birch26%

Aspen-Birch29%

Spruce-Fir6%

Pine9%

Other30%

Socio-economic importance

• 90 thousand direct jobs

• $3.3 billion in wages

• $5.4 billion in value added

• 2+ million hectares of parks and conservation areas

• Over 8 million visitors annually

Settlement patterns

• 1.5 million residents

• 16 persons per square kilometre

• $45.8 billion in property values

Wisconsin’s detection system

• 95 fixed lookouts

• Public reporting

• Air patrols

• Ground patrols

Wildfire causes

Humans69%

Lightning2%

Railroads8%

Other21%

Suppression techniques

• Ground attack

• Type VII-X engines and/or Type IV engines with Type IV tractor plows

Analytical Methods:

• Cost-benefit analyses

• Tukey’s multiple comparison tests of performance measures

Costs & benefits of lookout detection

Costs Benefits

• Maintenance • Suppression Costs

• Labor • Property Damage

• Depreciation • Resource Values

• Deterrence Values

A benefit function

• Lookout benefits assessed relative to public detection

PLLPL VVCCB

Data:

• Two separate but linked datasets

• 4,690 individual fire reports (1987-1995)

• 711 addendum reports from (1992-1995)

A suppression cost model

• Model estimated for three covertype/ fuel model combinations

• Data included only those observations when lookouts were staffed

Results – Economic EffectivenessStatewide

• Protected 238 ha from wildfire damage

• Reduced suppression costs by $12 k

• Prevented $591 k in property damage

• Each $1 cost => $6 savings

A closer look

0

200

400

600

800

1000

1200

$ (0

00's

)

1992 1993 1994 1995

Year

Lookout Cost

Suppression Savings

Damage Prevention

• Protected 1.6 ha from wildfire

• Saved $86 in suppression costs

• Prevented $4,100 in property damage

Per fire

Administrative region

• Area saved and suppression costs saved were not statistically different

• Property damage prevented and number of wildfires detected differed significantly

A closer look

0

1

2

3

4

5C

-B R

atio

Area

Individual lookouts

• Lookout performance was highly variable

• Lookouts that detected more fires saved area and generated more benefits

A closer look

0

25

50

75

100

0 25 50 75 100

Percentage of Lookouts

Cu

mu

lati

ve P

erce

nt

Sightings

Area Saved

Total Savings

Results – Detection Performance:Wildfire sightings

Public62%

Air Patrol4%

Lookout34%

Detection lag

0

5

10

15

20

Min

ute

s

Public Lookout Air Patrol

AA

Final size

0.0

0.5

1.0

1.5

2.0

Hec

tare

s

Public Lookout Air Patrol

A

B

AB

Suppression cost

0

50

100

150

200

250

300

1995

$

Public Lookout Air Patrol

A

B

AB

Conclusions:

• Fixed lookouts were cost-effective

• Majority of benefits attributable to property damage prevention

• Performance highly variable

Conclusions (Continued):

• Small number of lookouts generated majority of benefits

• Public and lookouts see different wildfires

• Opportunities exist to enhance wildfire detection