MANAGEMENT OF ACTIVE FOREST FIRES ON THE BASIS OF THEIR BEHAVIOR PREDICTION
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MANAGEMENT OF ACTIVE FOREST FIRES ON THE BASIS OF THEIR BEHAVIOR PREDICTION

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IBFRA conference presentation (August, 2011)

IBFRA conference presentation (August, 2011)

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MANAGEMENT OF ACTIVE FOREST FIRES ON THE BASIS OF THEIR BEHAVIOR PREDICTION MANAGEMENT OF ACTIVE FOREST FIRES ON THE BASIS OF THEIR BEHAVIOR PREDICTION Presentation Transcript

  • MANAGEMENT OF ACTIVE FOREST FIRES ON THE BASIS OF THEIR BEHAVIOR PREDICTION A.V. Volokitina, M.A. Korets, T.M. Sofronova Институт леса им.В.Н.Сукачева СО РАН 15 th IBFRA Conference , Boreal Forests in a Changing World, August 15-21, 2011, Krasnoyarsk, Russia
  • Broad meaning of “Forest Fire Management” :
    • Organization of forest fire protection;
    • Elimination of fire causes (propaganda, arrangement of the territory);
    • Monitoring for timely fire detection;
    • Limiting fire spread (fuel/fire breaks, fire suppression)
    • Minimizing environmental and economic damage from fires
  • Narrow meaning of “Forest Fire Management” :
    • Management of active fires on the basis of their behavior prediction. A direct forest fire management is control of each fire spread and development on the basis of its behavior (spread rate, intensity, development, and effects) prediction.
    • Our objective was to develop a system of active forest fires management in plain and mountain conditions on the example of the Krasnoyarsk krai
  • Sukachev Institute of Forest has all grounds for development of the Russian Fire Behavior Prediction System :
    • fundamental elaborations (vegetation fuel classification and methods of their mapping, a simple and practical model of fire spread, a technique of fire behavior, intensity and effects prediction);
    • a highly qualified team of fire scientists and GIS specialists.
  • Fire Behaviour Prediction (FBP) (principle scheme ) Information database Constant information Current information Pyrological description Vegetation fuel maps by periods of a fire season Current fire danger maps according to drought classes Model of fire behaviour prediction Weather data Periods of a fire season Fire behaviour prediction Fire type Fire spread Fire intensity Fire effects Forest inventory data Forest types schemes
  • State Contract # 82 (2008-2010) :
    • technology of making VF maps differentiated depending upon the kind and quality of the available forest inventory information
    • method of forest fire behavior prediction to the level of computer software
  • SOFTWARE FOR VF MAPS CREATION ( language С++; ОС Windows SE, 2000, XP, Vista)
  • VF MAP ( spring, fall ) for Chunsky ranger district ( includes primary fire carriers and pyrological description )
  • VF MAP (summer) for Chunsky ranger district ( includes primary fire carriers and pyrological description )
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    • Computer software of making VF maps and fire behavior prediction on the basis of GIS for mountain conditions were developed within the framework of the 2009 Agreement # 1263/10 between the Sukachev Institute of Forest and the Institute of Space Research (IKI) (under the auspices of the Central Airbase of Avialesookhrana) on the example of the National nature reserve “Stolby” (about 50,000 ha) in the process of forest inventory.
  • VF Map for Spring/ Fall in Nature Reserve “Stolby”
  • VF Map for Summer in Nature Reserve “Stolby”
  • FRAGMENT OF OPERATIONAL VF MAP for spring / fall in the Chunsky ranger district
  • Flow-chart of programs for creation of VF maps in language С++; OC Windows: SE,2000,XP, Vista and for fire behavior prediction in language Avenue for ESRI ArcView GIS 3.2
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  • Performance Tests Simulation of fire # 10 detected June 13, 2009 (5 ha of area burnt) and suppressed June 15, 2009 (total burnt area 60 ha) in the forest inventory unit # 89 of the Novokhaysk Ranger District
  • Conclusion
    • System of active fire management was developed on the basis of fire behavior prediction. Performance testing is needed on active fires involving the developers of this system and forest protection specialists trained in advance using the developed training software.
  • Conclusion
    • For dissemination further studies should be organized under collaboration of the Sukachev Institute of Forest (leading organization), the Central Airbase of Avialesookhrana, and the Federal State Unitary Enterprise “Roslesinforg”.
    • For this purpose, the three enumerated organizations submitted a project for consideration to the Federal Forestry Agency (Rosleshoz): “ Development of the Russian system of fire danger rating and fire behavior prediction ”.
  • THANK YOU FOR YOUR TIME! Институт леса им.В.Н.Сукачева СО РАН