The document discusses operational forest fire simulation tools for supporting decision making. It outlines several models for fire propagation, including empirical Rothermel-based models and computational fluid dynamics physical models. It then describes the InfoSIM system, which integrates these propagation models, high-resolution wind data, and fuel maps into a GIS-based platform to enable real-time 3D wildfire simulation and analysis to support wildfire management. The system has been operationally implemented and validated in several regions in Spain.

1. Operational simulation of forest fires Santiago Monedero & Joaquín Ramirez Maths & Fire Zaragoza 15/06/09 Ingeniería del territorio http://www.tecnosylva.com

2. p resentation outline 2. Models 5. FFDSS GIS implementation 3. Rothermel implementation 4. Operational approach GIS 1. Introduction

3. User´s need of operational tools Page 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

4. Fire simulation use situation Page 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

5. Basic equations: Local Radiation Radiation Diffusion depends on temperature Wind effects: Depends not only on wind but also on flame tilt There is no explicit Radiation term u: temperature e: enthalpy y: fuel amount G(u): Multivalued operator for moisture f(u,y) reaction function (Arrenius type) Vertical temperature loos

6. Basic equations: Local Radiation Wind effects: Inside radiation term r u: temperature e: enthalpy y: fuel amount G(u): Multivalued operator for moisture r Explicit radiation Multivalued operator Moleding radiation and moisture content in fire spread L. 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:

7. Numerical 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

8. 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 LOCAL Non LOCAL Valid for complex surfaces External independent model Validation independent of fire equations Wind effects only on radiation

9. Empirical model: existing software 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( )

10. 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 BehavePlus Potencial risk analysis like FlamMap

11. FireLAB evolution : FSPro, FPA 1 fire Several fires 1 meteo scenario hundreds of meteo scenarios FARSITE FSPro FPA FlamMap

12. 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

13. High resolution fuel models

14. Fuel parameters OOA InfoGIS: SAD en Incendios Forestales

15. USERS ASSESSMENT RESULTS: Fuel Parameters

16. Operational need: High resolution wind High Definition Wind Field: from Hirlam =13 km data to 25 m data Page

17. Firelab 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)

18. Firelab Wind models

19. 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 punctual Wind value assimilation

20. Ferragut’s Wind model: 2.5 Model 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.)¡

21. Basic local wind effects Night.  Slope winds +Temp -Temp Day. +Temp -Temp -Day: 6 – 7 Km/h ¿? -Night: 1 – 3 Km/h ¿? Temp (time, height (x,y))

22. Synergies spread Graphs Risk Rothermel Physical FEM Wind Spread

23. FFDSS: where tools should work 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

24. InfoSIM schema 19-20 October 2006, Page Fire Platform Meeting

25. long lasting layer Fuel, Satellite images, terrain Short lasting layers Wind, moisture, etc 3D real time Output Radiation model FEM Neptuno++ G.I.S. Physical fire model Help decision system Satellite fire-front update Satellite ignition detection External Moisture model High Definition Wind field Model I Model II Rothermel model Rasterize

26. InfoSIM: operational fire propagator Original development, PREVIEW project, inside WFDSS Also ArcGIS extension One click simulations Preraster input data Firebrak effect HR Wind (Ferragut´s model Management of simulations Integration with operational resources and fires data 4D results over HR imagery Also physical model Tech Validation: 2008 Extremadura& Andalusian fires Operacional use: campaign 2009 Extremadura, UME, Andalusia & Aragón (2010)

27. Integration of InfoSIM inside InfoGIS: InfoSIM

28. Results example InfoSIM

29. Comparing with reality InfoSIM

30. Operational results: real time HR 3D GIS

31. Input s - Outputs Propagadores de Incendios Forestales - 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

32. SIGYM (METEOGRID) Integration of METEO GIS input data

33. motor de cálculo Propagadores de Incendios Forestales - Simulaciones Condiciones variables en el tiempo Humedad vivo Hora Humedad Muerto Viento Modulo Viento dirección 1 2 3 8 8 9 10 10 11 30 90 150 60

34. Firebraks trea tment Propagadores de Incendios Forestales 0 1 2 4 6 8 10 12 14 16 18 Anchura (metros) 0 R0 ROS = ROS 0 * Parameter_firebreak Null value: No effect High values : Low width, high effect

35. c alculation engine Propagadores de Incendios Forestales - Adustment regional/ local factor (Farsite) ROS = ROS * Parametro_fuel - Fuel Model Inputs Rothermel Albini Custom Burgan Changes fuel behaviour,dep. experience Comb 1 1 2 0.3 3 0.6 4 0.8 11 1.7

36. c alculation engine Propagadores de Incendios Forestales - 3 different “pathdistance” temporal evolution -Pathdistance standard 8 y 16 directions -Pathdistance 12 autoselecctable directions

37. Analisys modules Propagadores de Incendios Forestales - Post-análisis (like Farsite) Fuel surface / time Perimeter / time – for operation plans Expansion speed (Vx,Vy) Velocidad del “centro de masas” del incendio Comparation with real perimeters - Pre-análisis (like BehavePlus) ROS, Flame length, intensity depending on Moisture1, moisture10, moisture100 Moisture live, wind & slope

38. Aut omated anali sys Propagadores de Incendios Forestales - Capacity of extinction automated calculations Configurable ROS, FL,Intensity – Eficiency (vs real data) + + - Risk Indexes ROS FL Intensity

39. Operati onal use: UME 3 Level CPX December 16th-17th 2008, Page Final Review - Toulouse TOA analisys Cofrentes CPX UME Level 3 exercise (Valencia, Spain, april 2008)

40. Time for operational propagation tools ¡

41. Conclusions Several models are available for real time forest fire modelling, but lack of use in operations FFDSS GIS based systems is the mandatory frame work to use these models for practical usefulness Rothermel model is still necessary for practical usefulness, user´s confidence is increasing A great synergy is generated by having all systems together: FFDSS GIS, Physical models, Rothermel, HR Wind. Thank you for your attention