Selection of the Methodology for Predicting the Forest Fires Risks


According to the Federal Forestry Agency, the area of forestry on the territory of the Russian Federation covers approximately two-thirds of the entire area of the country - 1.146 billion hectares.  In terms of the forest area in the world in the boreal zone, the leader is the Russian Federation. A distinctive feature of such forests is the inaccessibility and extreme susceptibility to fires. The group of countries in the boreal zone also includes Canada, the USA, Norway, Finland, and Sweden, which makes it possible to refer to their research on selecting the optimal model for calculating fire risks.
Due to the abnormally hot weather and the lack of precipitation, a significant fire hazard in the number of the subjects of the Russian Federation in 2020 was recorded from April to September (in 2019, even until November). Weather conditions contributed to the emergence of forest fires in the Urals, Far East, Siberian and Southern federal districts.
Monitoring and forecasting of fires in the forest area is poorly developed in the Russian Federation, therefore, it is required to select the optimal method using modern achievements of science and technology to minimize the human contact with the force of nature and the girth of a larger area.
The purpose of the study is to select the optimal methodology for predicting the risks of forest fires occurrence. Russian, Canadian, American, and Australian fire risk assessment methodology were identified. In the process of the analysis of the functional features of forest fire forecasting models, the models were compared. As a result, the advantages and disadvantages of the considered models, the scope and versatility of application, as well as their functionality are noted. A further mechanism of work is proposed to create an optimal methodology for calculating risks as the result of forest fires in relation to the features of the relief.

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DOI: 10.24000/0409-2961-2022-4-69-74
Year: 2022
Issue num: April
Keywords : prediction methodology weather phenomena forest fires forecasting model comparison
  • Safonova T.V.
    Safonova T.V.
    Senior Lecturer Russian State Hydrometeorological University, Saint-Petersburg, Russia
  • Yagotinceva N.V.
    Yagotinceva N.V.
    Cand. Sci. (Eng.), Assoc. Prof. Russian State Hydrometeorological University, Saint-Petersburg, Russia
  • Kolbina O.N.
    Kolbina O.N.
    Cand. Sci. (Eng.), Assoc. Prof. Russian State Hydrometeorological University, Saint-Petersburg, Russia
  • Mokryak A.V.
    Mokryak A.V.
    Research Associate Saint-Petersburg University of the State Fire Service of the EMERCOM of Russia, Saint-Petersburg, Russia