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A digital forecasting model for snowdrifts extent on transport routes in the subarctic zone

https://doi.org/10.31660/0445-0108-2025-4-100-114

EDN: PUCNUT

Abstract

This paper presents a specific area within engineering geodynamics: the processes of snowdrift and their impact on the efficiency of engineering and economic development in the Arc-tic regions of Russia. Snow deposits are analogous to soil of aeolian genesis, representing complex and dynamic systems. Extreme forms of snow cover, commonly referred to as «snowdrifts», are partly induced by human engineering activities. The authors used data from official meteorological stations to estimate the volume of accumulated snow. The calculations build on direct measurements of snow transport volumes. The core methodological principles are grounded in a conceptual analysis of wind-driven snow processes, viewed as the geological functions of wind. As such, snowdrifts extent is treated as an engineering-geological process, and snow deposits are regarded as analogous to aeolian soils. The wind-driven snow processes study employs principles of engineering geodynamics, aerodynamics, information technologies, and mathematical tools, along with operational experience from northern transport systems, to ensure high reliability of the results. The authors conducted a geodynamic zoning of the territory, classifying different types of snow deposits based on various factors. The paper`s authors proposed a digital forecasting model of snowdrifts extent on Norilsk–Talnakh highway. This model will serve to ensure the safe operation of vehicles, transport systems, and essential services for the population and industries in the Norilsk region. It reflects the patterns of snow deposits under urban subarctic conditions of Russian Federation. The model aims to support both civilian and military infrastructure in the harsh climate zones of Russia by providing reliable forecasts of snowdrifts extent. These forecasts facilitate the estimation of snow volume on specific highway sections over any given period.

About the Authors

I. S. Belyaev
N.M. Fedorovsky Polar State University
Russian Federation

Igor S. Belyaev, Candidate of Economic Sciences, Associate Professor, Acting Head of the Department of Information Systems and Technologies

Norilsk



O. P. Ryseva
N.M. Fedorovsky Polar State University
Russian Federation

Olga P. Rysyeva, Candidate of Engineering, Associate Professor, Associate Professor at the Department of Construction and Heat and Gas Supply

Norilsk



V. A. Gromov
N.M. Fedorovsky Polar State University
Russian Federation

Vladimir A. Gromov, Assistant of the Department of Information Systems and Technologies

Norilsk



V. A. Ruzhev
St. Petersburg State Agrarian University
Russian Federation

Ruzhev А. Vyacheslav, Candidate of Engineering, Director of the Engineer-ing and Technology Institute, Head of the Department of Technical Systems in Agribusiness

Pushkin



С. P. Pirogov
Industrial University of Tyumen
Russian Federation

Sergey P. Pirogov, Doctor of Engineering, Professor at the Department of Applied Mechanics

Tyumen



References

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For citations:


Belyaev I.S., Ryseva O.P., Gromov V.A., Ruzhev V.A., Pirogov С.P. A digital forecasting model for snowdrifts extent on transport routes in the subarctic zone. Oil and Gas Studies. 2025;(4):100-114. (In Russ.) https://doi.org/10.31660/0445-0108-2025-4-100-114. EDN: PUCNUT

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ISSN 0445-0108 (Print)