tsyl zaragoza maths fire jun 2009

Operational Operational s imulation of fores t s imulation of fores t

firesfires

Santiago Monedero & Joaquín RamirezMaths & Fire Zaragoza 15/06/09Ingeniería del territorio http://www.tecnosylva.com

pp res entation outline res entation outline

2. Models

5. FFDSS GIS implementation

3. Rothermel implementation

4. Operational approach GIS

1. Introduction

Us er´s need of operational tools Us er´s need of operational tools

•Many command centers has up to 30 fires a day in risk campaign

•Real need of quick fire dangerousness evaluation

•EVERY ALARM NEEDS A TECHNICAL EVALUATION OF DANGER

Galice, (SP) 2006

Fire s imulation us e s ituation Fire s imulation us e s ituation

✂ Low use in European FF services of this kind of tools, unless in prevention phase, and in a few cases only (EUFIRELAB, 2005)1

Fires in euromediterranean countries are very fast, and a lot at the same time Actual tools are difficult to feed, and use data not fitted to the needs of the users Results needs of high skill users to get the best of them, and are difficult to evaluate

Use of propagator in PREVENTION and mainly USA – big fires

Bad perception of their utility, (lot of solutions, main approach of years of GIS developments in FF)

Input data hard to process and not appropiate scales

Results oriented more to laboratory than to real fire fighting

: Bas ic equations Local Radiation : Bas ic equations Local Radiation

RadiationDiffusion depends on temperature

Wind effects:Depends not only on wind but also on flame tilt

There is no explicitRadiation term

u: temperaturee: enthalpyy: fuel amountG(u): Multivalued operator for moisturef(u,y) reaction function (Arrenius type)

Vertical temperature loos

: Bas ic equations Local Radiation : Bas ic equations Local Radiation

Wind effects:Inside radiation term r

u: temperaturee: enthalpyy: fuel amountG(u): Multivalued operator for moisturer Explicit radiation

Multivalued operator

Moleding radiation and moisture content in fire spreadL. Ferragut, M. Asensio, S. Monedero Commun. Numer. Meth. Engng 2007; 23:819–833 Published online 19 October 2006 in Wiley InterScience (www.interscience.wiley.com). DOI: 10.1002/cnm.927

Radiation and moisture method presented in:

NumericalNumerical

•Mesh

•The resolution is done by the Finite Element Method with mesh adaptativity, we use the library Neptuno++ developed by Prof. Ferragut.

•Solution

•FEM example with 4 ignition points

Radiation models Radiation models

•Diffusion included: more complex

•Convection included in ff equation

•Diffusion included: slower

•Empirical model: hard to validate

•Not valid for complex surface

PROS CONS

LO

CA

LN

on L

OC

AL

•Valid for complex surfaces

•External independent model

•Validation independent of fire equations

•Wind effects only on radiation

: Empirical model exis ting s oftware : Empirical model exis ting s oftware

http://www.firemodels.org/

Rothermel

Potential fire risk analysis Table, graph, and diagram output

2-dimensional fire growth model

•ROS (Rate Of Spread)

•Fire line intensity

•Flame length

•Fuel type•Wind•Terrain•Moisture

f( )

Rothermel Implementation Rothermel Implementation

mdt

moisture

Fuel

V average

Rothermel(Behaveplus) ROS

Cost layer=time= L/ROS

Rate of Spread Implemented based on Rothermels, Albini paper

Time evolution Implemented based on an enhaced Esri’s Pathdistance function (Where the time variable is the accumulative cost)

With no extra hard work we obtain:graphs for homogeneus conditions like BehavePlusPotencial risk analysis like FlamMap

FireLAB FireLAB evolutionevolution : , FSPro FPA: , FSPro FPA

1 fire Several fires

1 meteo scenario

hundreds of meteo scenarios

FARSITE

FSPro FPA

FlamMap

Empirical model Empirical model

•Widely known used and tested

•Based on experimental data•NFFL fuel types •European fuel types

•Very quick resolution

•FREE!

•Surface fire, crown fire, spotting, Fire acceleration

•Very technical Only user with training may use it.

•Based experimental data•Bad exportability •No new effects are expected

•No FFDSS embeded GIS:•Data conversion•No operational layers•Tedious file configurations•No enhanced GIS capabilities

PROS CONS

High res olution fue l models High res olution fue l models

InfoGIS: SAD en Incendios Forestales

Fuel parameters OOA

USERS ASSESSMENT RESULTS: USERS ASSESSMENT RESULTS: Fuel ParametersFuel Parameters

: Operational need High res o lution wind : Operational need High res o lution wind

• High Definition Wind Field: from Hirlam =13 km data to 25 m data

Fire lab Wind models Fire lab Wind models

Comparation of a Farsite simulation for low and high wind resolution (in white the actual perimeter of the fire).

Reference:The impact of high resolution wind field simulations on the accuracy of fire growth predictions (B. Butler, J. Forthofer, M. Finney)

Fire lab Wind models Fire lab Wind models

High Definition Wind High Definition Wind

Simulacion por FIRETEC. Referen ia: J. L. Winterkamp, R. R. Linn, Jonah J. Colman, William S. Smith

M.I Asensio, L. Ferragut, J. Simon, (2005). "A convective model for fire spread simulation."

Applied Mathematical Letters 18, pp. 673-677, 2005

Initial model presented on:

Enhaced with punctualWind value assimilation

’ : 2.5 Ferragut s Wind model’ : 2.5 Ferragut s Wind modelModelModel

•Should be valid for real time modeling•Takes into account: Vegetation friction and Temperature•Temperature dependent

•Fires own temperature (physical modeling of fire behaviour)•Sea breeze•Slope wind

•Punctual measurements•Fast calculations (400 x400 grid= 30 s.)¡

Bas ic local wind effec ts Bas ic local wind effec ts

Night.

ξ

Slope winds

+Temp

-Temp

Day.

+Temp

-Temp

-Day: 6 – 7 Km/h ¿?

-Night: 1 – 3 Km/h ¿?Temp (time, height (x,y))

SynergiesSynergies

spread Graphs Risk

RothermelPhysical FEM

Wind Spread

: FFDSS where tools s hould: FFDSS where tools s houldworkwork• InfoGIS is being used in operational way as the central

decission support system in the main spanish forest fires agencies since 1997– Castilla y León 1997 – Toledo 2000– Extremadura 2001– Aragón 2005– Andalucía 2006– Cantabria 2008

CENTRAL AUTONÓMICA

CENTRALESPROVINCIALES

CLIENTESLIGEROS

SERVICIOS ASOCIADOS (GPS, METEO)

SERVIDORCARTOGRAFÍA

WEB

19-20 October 2006,

Fire Platform Meeting

FFDSS

PROPAGATOR

INPUT DATA PROCESSOR

FIRE BEHAVIOUR

MODEL

OUTPUT DATA INTERFACE

InfoSIMInfoSIM s chemas chema

long lasting layerFuel, Satellite images, terrainShort lasting layersWind, moisture, etc

3D real timeOutput

Radiationmodel

FEMNeptuno++

G.I.S.

Physical fire model

•Help decision system•Satellite fire-front update•Satellite ignition detection

External

Moisturemodel

High DefinitionWind field

Model IModel II

Rothermel model

Rasterize

: InfoSIM operational fire propagator: InfoSIM operational fire propagator

• , , Original deve lopment PREVIEW projec t ins ide WFDSS

• Als o ArcGIS extens ion• One click s imulations

• Preras ter input data• Firebrak effec t• ( HR Wind Ferragut´s mode l• Management of s imulations• Integration with operational res ources

and fires data• 4 D res ults over HR imagery• Als o phys ical model

• : 2008 Tech Validation Extremadura& Andalus ian fires

• : 2009 Operacional us e campaign, , Extremadura UME Andalus ia & Aragón

(2010)

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Incendios registrados

( )Superficie total ha

< 1

1 - 5

5 - 10

10 - 50

> 50

## Conatos

:Integration of InfoSIM ins ide InfoGIS

InfoSIMInfoSIM

Res ults example

InfoSIMInfoSIM

Comparing with reality

InfoSIMInfoSIM

: 3 Operational res ults real time HR D : 3 Operational res ults real time HR DGISGIS

Propagadores de Incendios Forestales31

InputInputss - Outputs- Outputs

- Nationwide spatial database- HR fuel data – next steps: LIDAR ¡- HR firebreaks: BCN25- Formats

-Raster-Vector- Imagery (MODIS NDVI)

-Generic GIS, 3D OGC KML and FIRELAB (Farsite)-Generation of graphics, reports, (same as Farsite, Behaveplus & Flammap)

INPUTS

OUTPUTS

( )SIGYM METEOGRID

Integration of METEO GIS input data Integration of METEO GIS input data


motor de cálculo motor de cálculo

-Simulaciones Condiciones variables en el tiempo

Humedad vivo

Hora

Humedad Muerto

VientoModulo

Vientodirección

1 2 3

8 8 9

10 10 11

30 90 150

60


Firebraks trea Firebraks trea tmenttment

0 1 2 4 6 8 10 12 14 16 18 Anchura (metros)

0

R0

ROS = ROS0 * Parameter_firebreak

Null value: No effectHigh values : Low width, high effect


cc alculation engine alculation engine

-Adustment regional/ local factor (Farsite)

ROS = ROS * Parametro_fuel

- Fuel Model Inputs

Rothermel Albini

Custom

Burgan

Changes fuel behaviour,dep. experienceComb 1 12 0.33 0.64 0.811 1.7


cc alculation engine alculation engine

-3 different “pathdistance” temporal evolution

-Pathdistance standard8 y 16 directions

-Pathdistance 12 autoselecctable directions


Analis ys modules Analis ys modules

- Post-análisis (like Farsite)

Fuel surface / timePerimeter / time – for operation plansExpansion speed (Vx,Vy)Velocidad del “centro de masas” del incendioComparation with real perimeters

- Pre-análisis (like BehavePlus)

ROS, Flame length, intensitydepending on

Moisture1, moisture10, moisture100Moisture live, wind & slope


AutAut omated omated analianalis yss ys

- Capacity of extinction automated calculations

Configurable ROS, FL,Intensity – Eficiency (vs real data)

+ +

- Risk Indexes

ROSFLIntensity

December 16th-17th 2008,

Final Review - Toulouse

OperatiOperati : 3 onal us e UME Level : 3 onal us e UME LevelCPXCPX

TOA analisysCofrentes CPX UME Level 3 exercise (Valencia, Spain, april 2008)

Time for operational propagation tools ¡ Time for operational propagation tools ¡

Conclus ionsConclus ions

• Several models are available for real time fores t fire, modelling but lack of us e in operations

• FFDSS GIS bas ed s ys tems is the mandatory frame work to us e thes e models for practical us efulnes s

• Rothermel model is s till neces s ary for practical, us efulnes s us er´s confidence is increas ing

• A great s ynergy is generated by having all s ys tems:together

– , , , .FFDSS GIS Phys ical models Rothermel HR Wind

Thank you for y

our atte

ntion

tsyl zaragoza maths fire jun 2009

Technology