Research Article

Theoretical foundations for developing a digital soil twin for Southern Russia

Volume: 15 Number: 1 January 2, 2026
  • Yurii Litvinov *
  • Anton Mezhenkov
  • Tanwar Sudip
  • Svetlana Sushkova
  • Alexey Samoylov
  • Eduard Melnik
  • Alexander Kozlovskiy
  • Ekaterina Kuchmenko
  • Tatiana Minkina
  • Evgenyi Shuvaev
  • Anastasia Nemtseva
  • Rahila Islamzade

Theoretical foundations for developing a digital soil twin for Southern Russia

Abstract

The sustainable management of soil resources in Southern Russia has become increasingly critical due to intensifying agricultural pressures, accelerating climate variability, and cumulative anthropogenic disturbances. Rapid advances in digital technologies now enable the integration of heterogeneous soil datasets into dynamic computational environments capable of representing physical soil systems with unprecedented precision. Within this context, the digital twin (DT) paradigm—originating from engineering sciences and now rapidly expanding into agricultural and environmental domains—offers a transformational framework for real-time soil monitoring, process simulation, scenario forecasting, and risk assessment. This study establishes the theoretical and methodological foundations necessary for developing a comprehensive soil digital twin for the Rostov region by synthesizing more than eighty years of archival soil–geographical surveys, long-term agrochemical monitoring data, multi-scale cartographic sources, remote sensing products, IoT-based soil measurements, climate records, machine-learning algorithms, geostatistical models, semantic graph structures, distributed computing frameworks, federated learning, and blockchain-enabled data governance. Particular emphasis is placed on harmonizing heterogeneous soil legends, vectorizing analog soil maps, constructing unified soil ontologies, and designing a multi-layered DT architecture grounded in contemporary digital twin theory, including mirrored physical–virtual spaces, multidimensional modeling, and state-fusion mechanisms. Machine-learning experiments demonstrate high predictive accuracy for numerous soil attributes, while geostatistical modeling enhances spatial continuity and uncertainty quantification. The integrated framework presented here provides a robust foundation for constructing an operational soil digital twin capable of supporting precision agriculture, environmental monitoring, insurance modeling, and strategic land-use planning. By enabling continuous data ingestion, multi-stakeholder interaction, and dynamic model refinement, the developed digital twin concept has significant potential to strengthen climate resilience, optimize agronomic interventions, and promote sustainable agricultural development across Southern Russia.

Keywords

Supporting Institution

Ministry of Science and Higher Education of Russia

Project Number

075-15-2025-667

Thanks

The research was supported by the Strategic Academic Leadership Program of the Southern Federal University ("Priority 2030") and with the financial support of the Ministry of Science and Higher Education of Russia (Agreement No. 075-15-2025-667) using the equipment of the Soil Bioengineering Center for Collective use.

References

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  2. Bezuglova, O.S., Golozubov, O.M., Kryschenko, V.S., 2013. Soil-geographical large-scale electronic atlas of the Rostov region: principles of construction, structure, possibilities of use. SFedU, Rostov-on-Don. 146 p.
  3. Borovoy, S.E., Komarova, O.P., Kozenko, K.Yu., 2024. Concept of digital twin of irrigated agrocenosis. Izvestia of the Lower Volga Agro-University Complex 3(75): 165–174.
  4. Chen, G., Kang, X., Lin, M., Teng, S., Liu, Z., 2023. Stability prediction of soil slopes based on digital twinning and deep learning. Applied Sciences 13(11): 6470.
  5. Derzhavina, L.M., Bulgakova, D.S., 2003. Methodical guidelines for conducting comprehensive monitoring of soil fertility of agricultural lands. FSBI “Rosinformagroteh”, Moscow. 240 p.
  6. ESA, 2023. The European Space Agency. Available at [Access date: 20.03.2025]: https://www.esa.int/
  7. Eurostat, 2023. Overview: Land cover and use. Available at [Access date: 20.03.2025]: https://ec.europa.eu/eurostat/web/lucas
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Details

Primary Language

English

Subjects

Soil Sciences and Plant Nutrition (Other)

Journal Section

Research Article

Authors

Yurii Litvinov * This is me
0000-0001-7204-2734
Russian Federation

Anton Mezhenkov This is me
0000-0002-5733-8796
Russian Federation

Tanwar Sudip This is me
0000-0002-1776-4651
Russian Federation

Svetlana Sushkova This is me
0000-0003-3470-9627
Russian Federation

Alexey Samoylov This is me
0000-0003-0783-377X
Russian Federation

Eduard Melnik This is me
0000-0002-4947-6718
Russian Federation

Alexander Kozlovskiy This is me
0000-0001-7181-9900
Russian Federation

Ekaterina Kuchmenko This is me
0009-0008-4234-4625
Russian Federation

Evgenyi Shuvaev This is me
0009-0009-8093-5327
Russian Federation

Anastasia Nemtseva This is me
0009-0006-5486-9459
Russian Federation

Publication Date

January 2, 2026

Submission Date

May 3, 2025

Acceptance Date

December 8, 2025

Published in Issue

Year 2026 Volume: 15 Number: 1

APA
Litvinov, Y., Mezhenkov, A., Sudip, T., Sushkova, S., Samoylov, A., Melnik, E., Kozlovskiy, A., Kuchmenko, E., Minkina, T., Shuvaev, E., Nemtseva, A., & Islamzade, R. (2026). Theoretical foundations for developing a digital soil twin for Southern Russia. Eurasian Journal of Soil Science, 15(1), 141-148. https://doi.org/10.18393/ejss.1841018
AMA
1.Litvinov Y, Mezhenkov A, Sudip T, et al. Theoretical foundations for developing a digital soil twin for Southern Russia. EJSS. 2026;15(1):141-148. doi:10.18393/ejss.1841018
Chicago
Litvinov, Yurii, Anton Mezhenkov, Tanwar Sudip, et al. 2026. “Theoretical Foundations for Developing a Digital Soil Twin for Southern Russia”. Eurasian Journal of Soil Science 15 (1): 141-48. https://doi.org/10.18393/ejss.1841018.
EndNote
Litvinov Y, Mezhenkov A, Sudip T, Sushkova S, Samoylov A, Melnik E, Kozlovskiy A, Kuchmenko E, Minkina T, Shuvaev E, Nemtseva A, Islamzade R (January 1, 2026) Theoretical foundations for developing a digital soil twin for Southern Russia. Eurasian Journal of Soil Science 15 1 141–148.
IEEE
[1]Y. Litvinov et al., “Theoretical foundations for developing a digital soil twin for Southern Russia”, EJSS, vol. 15, no. 1, pp. 141–148, Jan. 2026, doi: 10.18393/ejss.1841018.
ISNAD
Litvinov, Yurii - Mezhenkov, Anton - Sudip, Tanwar - Sushkova, Svetlana - Samoylov, Alexey - Melnik, Eduard - Kozlovskiy, Alexander et al. “Theoretical Foundations for Developing a Digital Soil Twin for Southern Russia”. Eurasian Journal of Soil Science 15/1 (January 1, 2026): 141-148. https://doi.org/10.18393/ejss.1841018.
JAMA
1.Litvinov Y, Mezhenkov A, Sudip T, Sushkova S, Samoylov A, Melnik E, Kozlovskiy A, Kuchmenko E, Minkina T, Shuvaev E, Nemtseva A, Islamzade R. Theoretical foundations for developing a digital soil twin for Southern Russia. EJSS. 2026;15:141–148.
MLA
Litvinov, Yurii, et al. “Theoretical Foundations for Developing a Digital Soil Twin for Southern Russia”. Eurasian Journal of Soil Science, vol. 15, no. 1, Jan. 2026, pp. 141-8, doi:10.18393/ejss.1841018.
Vancouver
1.Yurii Litvinov, Anton Mezhenkov, Tanwar Sudip, Svetlana Sushkova, Alexey Samoylov, Eduard Melnik, Alexander Kozlovskiy, Ekaterina Kuchmenko, Tatiana Minkina, Evgenyi Shuvaev, Anastasia Nemtseva, Rahila Islamzade. Theoretical foundations for developing a digital soil twin for Southern Russia. EJSS. 2026 Jan. 1;15(1):141-8. doi:10.18393/ejss.1841018