Date post: | 16-Jan-2015 |
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Technology |
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15 years supporting Wildfires
operations
From Aragón to San Diego
J Ramirez & JM Lahoz (tecnosylva)
D Buckley (dtswildfire)
Cedar Fire, going through Sycamore Creek Neighborhood in Poway Ca., October 2003 http://youtu.be/-IG9Jhx4xIA
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
American Flight 1956-57 Yes, it is Arc !
1994 Spain fire season 437.000 ha burnt
Aragón: Villarluengo 27.000 ha
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
Helicopter crash in Alcorisa, Mar 18th, 6 fatalities Total fatalities 2011:
Geotechnologies &Wildfires
•
•
Geotechnologies & Wildfires
Wildfire GTs
GIS
GNSS
Mobility
Sensors
Communications Predictive Services
Remote Sensing
BI & Document
Management
Artificial Inteligence
…ok, maybe we need some help on the field ¡¡¡ do you have these trees in US?
What is geospatial fire simulation?
1938 Honey Fire, Louisiana
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
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)
Farsite: Mark Finney’s First complete GWS (1991-1998)
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
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
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
.
FBAN’s: the guys that need tools to run the models ant the right place ¡
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)
We need to take sims from the lab…
LANL Coupled Fire/Atmosphere Modeling, FIRETEC http://ees.lanl.gov/ees16/FIRETEC.shtml
to the Incident Command Post …
… to support operations
Agency Wide Incident Management
Integrated WF System Vision
Software Vision
Incident Lifecycle
• Includes all phases of wildland firefighting requirements, from:
• Detection
• Resource management
• Response & suppression management
• Impact analysis & damage assessment
• Documentation & tracking
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
Vulnerable asset
Dangerous side Wind will push fire toward asset
Save side Wind will push fire away asset
Dangerous side Wind will push fire toward asset
Save side Wind will push fire away asset
Each cell represents: the TIME a fire would take to get to the evacuation point with the given conditions…
Alabama Forestry Commission Suppression Budget Analysis
Fire ignition
Fire Perimeter & Origin
May 7-9, 2007 – St. Clair Stone Fire
St. Clair Stone Fire
Wildfire Simulation – Nearby Communities
St. Clair Stone Fire
Wildfire Simulation – Comparison
Actual Perimeter
Accumulative Population Impacted
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479
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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
St. Clair Stone Fire
Wildfire Simulation – Impacted Parcels
Total Structures Impacted
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81 89
Stru
ctu
res
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Hour of Wildfire
St. Clair Stone Fire Simulation Number of Structures Impacted by Wildfire
By Hour of Progression
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
Click the image to play the AFC YouTube video that describes
the analysis
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
Thank you for your attention
I’ve got a question…
anyone joins the lady?
Joaquín Ramírez [email protected]
David Buckley