Download - DTS Tecnosylva Fire Response
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15 years supporting Wildfires
operations
From Aragón to San Diego
J Ramirez & JM Lahoz (tecnosylva)
D Buckley (dtswildfire)
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Cedar Fire, going through Sycamore Creek Neighborhood in Poway Ca., October 2003 http://youtu.be/-IG9Jhx4xIA
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Jacques Descloitres, MODIS Rapid Response System at NASA/GSFC http://youtu.be/eET7jwJOOqA
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Fires
Acres
http://www.nifc.gov/fireInfo/fireInfo_
statistics.html
fires
Lower number of fires but bigger - The better we are fighting fires, the bigger those we cannot win
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American Flight 1956-57 Yes, it is Arc !
1994 Spain fire season 437.000 ha burnt
Aragón: Villarluengo 27.000 ha
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393 forest rangers 46 engines 9 helicopters 8 helicrews 69 crews 2 advanced command posts 152 small engines + 2 canadair 1 sokol 1 Kamoc 1 BRIF
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Helicopter crash in Alcorisa, Mar 18th, 6 fatalities Total fatalities 2011:
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Geotechnologies &Wildfires
•
•
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Geotechnologies & Wildfires
Wildfire GTs
GIS
GNSS
Mobility
Sensors
Communications Predictive Services
Remote Sensing
BI & Document
Management
Artificial Inteligence
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…ok, maybe we need some help on the field ¡¡¡ do you have these trees in US?
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What is geospatial fire simulation?
1938 Honey Fire, Louisiana
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The science and art of GWS
• Where the fire is going to be in the next …?
• How is it burning process?
• When can we expect to stop it?
• What is the potential of the fire?
• Why is the fire jumping?
All these questions have spatio-temporal answers
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Who’s who in GWS
Harry T. Gisborne
First true specialist in forest fire research in the Nation
Jack S. Barrow
Director of the Missoula fire Lab
The Mann Gulch Fire (1949)
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Farsite: Mark Finney’s First complete GWS (1991-1998)
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for this problem… we need models¡
• Models help us to better understand complex systems
• Helps us to quantify the problems • Fire behavior involves (in a short
approach) – Weather – Fuel – Terrain – Human factors
• Spatial and Temporal combined analysis is needed
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Modeling fire behaviour
R. C. Rothermel, 1987
Managing Research for Success Gen. Tech. Rep. PSW-101 Berkeley, CA. Pacific Southwest Forest and Range Experiment Station, Forest Service, U.S.
Department of Agriculture; 1987
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Models are out there Models completed in period 1990-2007
12 Physical
7 quasi-physical
15 empirical
5 quasi-empirical
11 simulation
22 mathematical analogous
Andrew L. Sullivan Wildland surface fire spread modelling, 1990–2007
International Journal of Wildland Fire Volume 18 Number 4 2009
.
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FBAN’s: the guys that need tools to run the models ant the right place ¡
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Refine ignition points, active fronts,
secondary spots
Refinement of the scenario: fuels, firebreaks,
operations
Weather input review: predictions&RAWS vs in
field measurements
Atention to sensible parameters: local wind effects, fuel moisture
Evaluation of observed ROS: field observers, AVL resources, aerial imagery
Weather & Fuel ROS adjustmens
(Adapted from Stratton 2005)
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We need to take sims from the lab…
LANL Coupled Fire/Atmosphere Modeling, FIRETEC http://ees.lanl.gov/ees16/FIRETEC.shtml
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to the Incident Command Post …
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… to support operations
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Agency Wide Incident Management
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Integrated WF System Vision
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Software Vision
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Incident Lifecycle
• Includes all phases of wildland firefighting requirements, from:
• Detection
• Resource management
• Response & suppression management
• Impact analysis & damage assessment
• Documentation & tracking
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How Does it Work?
• Seamless Synchronization • Uses a data replication
approach based on transactional architecture
• Facilitates exchange of data between seamlessly between users
• Designed to ensure data synchronization occurs in the most severe operational scenarios
• Designed for EOC and related command hierarchy
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Vulnerable asset
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Dangerous side Wind will push fire toward asset
Save side Wind will push fire away asset
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Dangerous side Wind will push fire toward asset
Save side Wind will push fire away asset
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Each cell represents: the TIME a fire would take to get to the evacuation point with the given conditions…
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Alabama Forestry Commission Suppression Budget Analysis
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Fire ignition
Fire Perimeter & Origin
May 7-9, 2007 – St. Clair Stone Fire
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St. Clair Stone Fire
Wildfire Simulation – Nearby Communities
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St. Clair Stone Fire
Wildfire Simulation – Comparison
Actual Perimeter
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Accumulative Population Impacted
0
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1.200
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1.600
1.800
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16
137 160 244
479
615
1.052
1.229 1.246 1.345
1.418 1.510
1.704
Hour of Wildfire
St. Clair Stone Fire Simulation Accumulative Residential Population Impacted
By Hour Progression of Wildfire
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St. Clair Stone Fire
Wildfire Simulation – Impacted Parcels
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Total Structures Impacted
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100
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20 32
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69
258
105
21 33
49
81 89
Stru
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Hour of Wildfire
St. Clair Stone Fire Simulation Number of Structures Impacted by Wildfire
By Hour of Progression
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Accumulated Structure Loss
$0
$10
$20
$30
$40
$50
$60
$70
$80
$90
$100
4 8 12 16 20 24 28 32 36 40 44 48 52
$3,9 $7,2 $8,1
$12,8
$24,4
$32,1
$66,8
$73,7 $75,7 $77,9 $81,5
$89,0 $93,6
$ in
Mill
ion
s
Hour of Wildfire
St. Clair Stone Fire Simulation Accumulative Potential $ Loss of Structures
By Hour Progression of Wildfire
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Click the image to play the AFC YouTube video that describes
the analysis
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new uses of operational simulations
Prevention
• Observed Fire Behavior database
• Fuel management
• Analyze firebreaks efficiency
• Resources location optimization
Operations
• Every Alarm Evaluation
• Multiple incidents
• IAP support
• Integration in DSS
Post fire
• Fire Scenarios
• Impact assesment
• What if?
• Historical analysis
• New local models
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Thank you for your attention
I’ve got a question…
anyone joins the lady?
Joaquín Ramírez [email protected]
David Buckley