Mathematical modelling of erosion processes in the Middle Zarafshan highland plains

DOI: 10.35595/2414-9179-2025-1-31-599-613

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About the Authors

Bekzod Eshkuvvatov

Samarkand State University named after Sharof Rashidov, Faculty of Geography and Ecology,
15, Universitetsky blvd., Samarkand, 140104, Uzbekistan,
E-mail: netgeo.suhail@gmail.com

Bakhtiyor Meliev

Samarkand State University named after Sharof Rashidov, Faculty of Geography and Ecology,
15, Universitetsky blvd., Samarkand, 140104, Uzbekistan,

Mohammad Suhail

Samarkand State University named after Sharof Rashidov, Faculty of Geography and Ecology,
15, Universitetsky blvd., Samarkand, 140104, Uzbekistan,
E-mail: netgeo.suhail@gmail.com

Ibrohim Bekkulov

Samarkand State University named after Sharof Rashidov, Faculty of Geography and Ecology,
15, Universitetsky blvd., Samarkand, 140104, Uzbekistan,

Mekhribon Sharipova

Samarkand State University named after Sharof Rashidov, Faculty of Geography and Ecology,
15, Universitetsky blvd., Samarkand, 140104, Uzbekistan,

Fatima Zareen

Samarkand State University named after Sharof Rashidov, Faculty of Geography and Ecology,
15, Universitetsky blvd., Samarkand, 140104, Uzbekistan,

Abstract

This article delves into the mathematical modeling of erosion processes affecting the Oktov mountain plains in the Middle Zarafshan Region, a geomorphologically intricate and relatively inaccessible terrain. By utilizing high-resolution satellite imagery, the study aims to enhance the understanding of erosion dynamics in this geomorphologically complex area, where traditional ground-based observations are challenging. Satellite images are processed and analyzed to extract critical data on topographical changes, sediment displacement, and vegetation cover, which are vital indicators of erosion activity. Satellite-derived metrics—such as digital elevation models (DEMs), normalized difference vegetation index (NDVI), and sediment transport estimates—are synthesized to quantify erosion susceptibility. The mathematical models developed in this study are grounded in multivariate geostatistical techniques and erosion prediction equations akin to the Revised Universal Soil Loss Equation (RUSLE), adapted for remote sensing applications. The model employs algorithms that account for various erosive factors such as rainfall intensity, soil composition, slope gradient, and land use practices. The model was validated using ground truthing, ensuring their robustness and accuracy in predicting erosion trends. Through a combination of spatial analysis and numerical simulations, the research identifies the most vulnerable areas to erosion and provides insights into the underlying mechanisms driving these processes. It underscores the significant impact of both natural and anthropogenic factors on the erosion dynamics of the Oktov mountain plains. The findings delineate erosion-prone zones and correlate intensification patterns with both natural gradients and unsustainable agricultural practices, echoing concerns raised in contemporary erosion literature regarding land degradation in semi-arid upland systems.

Keywords

erosion modelling, soil and land degradation, sediment displacement, semi-arid uplands, spatial analysis

References

  1. Arnold J.G., Srinivasan R., Muttiah R.S., Williams J.R. Large Area Hydrologic Modeling and Assessment. Part I: Model Development. Journal of the American Water Resources Association, 1998. V. 34. No. 1. P. 73–89.
  2. Auerswald K., Fiener P., Martin W., Elhaus D. Use and Misuse of the K Factor Equation in Soil Erosion Modeling: An Alternative Equation for Determining USLE Nomograph Soil Erodibility Values. CATENA, 2014. V. 118. P. 220–225. DOI: 10.1016/j.catena.2014.01.008.
  3. Ayres Q.C. Soil Erosion and its Control. Soil Science, 1937. V. 43. No. 5. P. 391.
  4. Barnes G. Land and Geographic Information Systems. The Surveying Handbook. Boston, MA: Springer, 1995. DOI: 10.1007/978-1-4615-2067-2_35.
  5. Belyaev V.R., Wallbrink P.J., Golosov V.N., Murray A.S., Sidorchuk A.Y. A Comparison of Methods for Evaluating Soil Redistribution in the Severely Eroded Stavropol Region, Southern European Russia. Geomorphology, 2005. V. 65. No. 3–4. P. 173–193.
  6. Blanco-Canqui H., Lal R. Principles of Soil Conservation and Management. Springer Science & Business Media, 2008.
  7. Borrelli P., Robinson D.A., Fleischer L.R., Lugato E., Ballabio C., Alewell C., Meusburger K., Modugno S., Schütt B., Ferro V., Bagarello V. An Assessment of the Global Impact of 21st Century Land Use Change on Soil Erosion. Nature communications, 2017. V. 8. No. 1. P. 2013.
  8. Burrough P.A. Principal of Geographical Information Systems for Land Resources Assessment. Oxford: Clarendon Press, 1988. 194 p.
  9. Christine A., Pasquale B., Katrin M., Panos P. Using the USLE: Chances, Challenges and Limitations of Soil Erosion Modelling. International Soil and Water Conservation Research, 2019. V. 7. Iss. 3. P. 203–225. DOI: 10.1016/j.iswcr.2019.05.004.
  10. DeJong S.M. Derivation of Vegetative Variables from a Landsat TM Image for Modelling Soil Erosion. Earth Surface Processes and Landforms, 1994. V. 19. No. 2. P. 165–178.
  11. DeVente J., Poesen J. Predicting Soil Erosion and Sediment Yield at the Basin Scale: Scale Issues and Semi-Quantitative Models. Earth-science reviews, 2005. V. 71. No. 1–2. P. 95–125.
  12. Eichhorn G. Land Information Systems: Invited Papers and Discussions During the Symposium of the Federation Internationale Des Géomètres. October 16–21, 1978, Technical University of Darmstadt. Technical University, 1979.
  13. Eshkuvvatov B.B. Microzoning and Economic Assessment of Foothills and Propagated Landscape Complexes (by the example of Middle Zarafshan). Author’s abstract of dissertation. Samarkand, 2020.
  14. Eshkuvvatov B.B., Yarashev K.S. Scientific and Practical Measures of Analysis of Plains and Landscapes. Marsland Press: Nature and Science, 2020. V. 18 (3). P. 60–62.
  15. Gvozdetsky N.A. Landscape Map as a Basis for Physical-Geographical Zoning (Using the Example of the Syr Darya Region of the Inner and Central Tien Shan). Riga: Scientific Papers of University of Latvia, 1961. V. 37. P. 93–100.
  16. Horton E. Erosion Development of Rivers and Drainage Basins, 1948. 158 p.
  17. Ibragimov L., Sherxolov O., Musayev B., Boboyev S., Sobirova M., Boratova G. Industrial Development and Assessment of its Impact in Samarkand Region—a GIS Mapping-Based Study. E3S Web of Conferences (EDP Sciences), 2024. V. 590. P. 06002.
  18. LeBas C., Jamagne M. Soil Databases to Support Sustainable Development. Joint Research Center (IRSA), 1996. 149 p.
  19. McEntyre J.G. Land Information Systems. Springer, Boston, MA: The Surveying Handbook, 1987. DOI: 10.1007/978-1-4757-1188-2_35.
  20. Meliev B.A. Issues of Studying the Landscapes of the Zarafshan Basin Based on Space Data and Mapping Them. Scientific and Theoretical Foundations of Creating the National Atlas of Uzbekistan. Tashkent, 2009.
  21. Meliev B.A. Use of Aerospace, Mathematical and Geoinformation Methods in the Research of Middle Zarafshan Landscapes. Author’s abstract of dissertation. Samarkand, 2019.
  22. Mukhamedov O., Usmanov M. Sattarov A. Model of Birth Rate in Uzbekistan and its Geographical Aspects. AIP Conference Proceedings, 2024. No. 3147 (1).
  23. Padma V.V.L., Suhail M., Ibragimov L. Sodiyev B. A Comparative Study of Three Supervised Algorithms for Mixed Crop Classification. 6th Annual International Scientific Conference on Geoinformatics—GI 2024: “Sustainable Geospatial Solutions for a Changing World”. E3S Web of Conferences, 2024. V. 590. P. 01004. DOI: 10.1051/e3sconf/202459001004.
  24. Pasquale B., Christine A., Pablo A., Jamil A.A.A., Jantiene B. et al. Soil Erosion Modelling: A Global Review and Statistical Analysis. Science of The Total Environment, 2021. V. 780. P. 146494. DOI: 10.1016/j.scitotenv.2021.146494.
  25. Ravshanov A.X., Suhail M., Komilova K., Ravshanov S. Medical Geographical Zoning in Part of Uzbekistan—A Regional Synthesis. Regional Science Policy & Practice, 2024. V. 16. No. 12. P. 100142. DOI: 10.1016/j.rspp.2024.100142.
  26. Suhail M. Assessment of Water Footprint Under Wheat Cultivation in Purvanchal Uttar Pradesh, Northern India. Environment Development and Sustainability, 2023. V. 26. P. 24957–24969. DOI: 10.1007/s10668-023-03665-4.
  27. Suhail M., Khan M.N., Ravshanov A.X., Usmanov M. Suitability Assessment of Wind Energy Farming in the Desert Landscape of Zarafshan Valley, Uzbekistan. InterCarto. InterGIS, 2024. V. 30. Part 1. P. 179–192. DOI: 10.35595/2414-9179-2024-1-30.
  28. UNEP. GIS awareness in agricultural research. Environment Information and Assessment Tech, 1997. 946 p.
  29. Viktorov A.S., Kapralova V.N., Arkhipova M.V. Dynamic Modeling for the Morphological Pattern of Thermokarst Plains with Fluvial Erosion on the Base of Remote Sensing Data. Earth Research from Space, 2019. No. 2. P. 55–64. DOI: 10.31857/S0205-96142019255-64.
  30. Victorov A.S., Kapralova V.N., Orlov T.V., Trapeznikova O.N., Arkhipova M.V., Berezin P.V., Zverev A.V., Sadkov S.A., Panchenko E.G. Mathematical Morphology of Cryolithozone Landscapes. Moscow: RUDN Publishing, 2016. 232 p. (in Russian).
  31. Yarashev Q. Meliyev B. Problems of Studying and Mapping Paragenetic Landscape Complexes in Surkhandarya Region. European Sciences review, 2015. V. 3–4. No. 14. P. 7–19.

For citation: Eshkuvvatov B., Meliev B., Suhail M., Bekkulov I., Sharipova M., Zareen F. Mathematical modelling of erosion processes in the Middle Zarafshan highland plains. InterCarto. InterGIS. Moscow: MSU, Faculty of Geography, 2025. V. 31. Part 1. P. 599–613. DOI: 10.35595/2414-9179-2025-1-31-599-613