Improving monitoring of landslide processes on mountain slopes in the presence of transport infrastructure
Abstract
Relevance. Climate change and the intensification of extreme hydrometeorological events, such as landslides, pose significant threats to the sustainability of transport infrastructure on the Black Sea coast of the Caucasus. Сorrespond the particular danger are degraded slope systems under the influence of anthropogenic load, on which highway are located, which are elements of critical infrastructure for mountainous areas of southern Russia. Visual observations remain the main primary method of geotechnical monitoring of the road network condition. At the same time, the presence of sharply changing mining and geological and hydrogeological conditions, as well as the lack of information on the condition of subsurface layers of rocks, do not allow identifying the features of the kinematics of deformation processes of landslide bodies. In this regard, the need to improve the methodology for selecting parameters of geophysical methods of geoecological monitoring is becoming more urgent. The aim of the research is to improve the methods of geophysical monitoring of landslide processes of slope systems in the mountainous areas of the Caucasus. The research methodology included an analysis of Russian and foreign sources in the field of classification of factors that initiate the occurrence of landslides; an assessment of the effectiveness of using geophysical monitoring methods, as well as the possibility of using artificial neural networks to process big data arrays. The results of the study showed that the combination of ERT and seismic studies allows for the formation of high-quality spatial models of the studied soil cover and rock massif, which, in combination with ANN, improves the accuracy of predictive analysis.
References
Бригида В.С., Мишулина С.И., Стась Г.В. Перспективные направления экологизации структурных элементов туристского продукта Краснодарского края (на примере транспортной составляющей). // Устойчивое развитие горных территорий. – 2020. – Т. 12. № 1. – С. 18–25. DOI: 10.21177/1998-4502-2020-12-1-18–25.
Бурдзиева О.Г., Мельков Д.А., Ревазов М.О., Кортиев А.Л. Активизация оползневых процессов, обусловленная урбанизацией горных территорий. // Устойчивое развитие горных территорий. – 2024а. – Т. 16. № 4. – С. 1646–1658. DOI: 10.21177/1998-4502-2024-164-1646-1658.
Бурдзиева О.Г., Ревазов М.О., Кортиев А.Л., Гогичев Р.Р. Влияние воздействия геодинамических процессов на геоэкологическую нагрузку горного региона. // Геология и геофизика Юга России. – 2024б. – Т. 14. № 4. – С. 166–179. DOI: 10.46698/VNC.2024.50.44.014.
Идармачев Ш.Г. Система непрерывного мониторинга параметров трещин в горном массиве на основе резистивных датчиков. // Геология и геофизика Юга России. – 2025. – Т. 15. № 1. – С. 82–91. DOI: 10.46698/VNC.2025.78.66.007.
Идармачев Ш.Г., Черкашин В.И., Алиев И.А., Идармачев И.Ш. Изучение динамики ширины трещины потенциально обвального скального массива струнным датчиком на горе Гуниб (Дагестан). // Геология и геофизика Юга России. – 2022. – Т. 12. № 2. – С. 78–88. DOI: 10.46698/VNC.2022.70.64.006.
Керимов И.А., Эльжаев А.С. Применение геофизических методов при изучении оползневых процессов. // Геология и геофизика Юга России. – 2024. – Т. 14. № 4. – С. 66–83. DOI: 10.46698/ VNC.2024.91.39.007.
Свалова В.Б. Управление геоэкологическим риском и проблемы устойчивого развития горных территорий. // Геология и геофизика Юга России. – 2022. – Т. 12. № 1. – С. 129–147. DOI: 10.46698/VNC.2022.48.61.010.
Яицкая Н.А., Дзагания Л.М., Бригида В.С. Геоэкологические опасности в условиях климатических изменений территорий субтропической зоны Кавказа. // Геология и геофизика Юга России. – 2023. – Т. 13. № 2. – С. 118–132. DOI: 10.46698/VNC.2023.54.85.010.
Aslam B., Zafar A., Khalil U. Comparative analysis of multiple conventional neural networks for landslide susceptibility mapping. Natural Hazards. 2023. Vol. 115. pp. 673–707. DOI: 10.1007/s11069-022-05570-x.
Bhowmik A., Kumar R., Ranganathaswamy M.K., Kumar, Y.K., Samal P., Mahapatro A. et al. Predictive modeling of the mechanical behavior of 3D-printed polylactic acid/wood composite: Comparison of GEP and ANN methods. AIP Advances. 2025. Vol. 15. Issue 4. DOI: 10.1063/5.0268653.
Highland L.M., Bobrowsky P. The landslide handbook – A guide to understanding landslides: Reston, Virginia, U.S. Geological Survey Circular. 2008. Vol. 1325. 129 p.
Hristova T., Savov N., Yanev N. Municipal solid waste and non-hazardous waste processing for sustainable circular economy through blockchain. Journal of Chemical Technology and Metallurgy. 2023. Vol. 58. Issue 3. pp. 513–521. DOI: 10.59957/jctm.v58i3.81.
Ikram R.M.A., Dehrashid A.A., Zhang B., Chen Z., Le B.N., Moayedi H. A novel swarm intelligence: Cuckoo optimization algorithm (COA) and SailFish optimizer (SFO) in landslide susceptibility assessment. Stochastic Environmental Research and Risk Assessment. 2023. Vol. 37. pp. 1717–1743.
Jaiswal P., van Westen C.J. Use of quantitative landslide hazard and risk information for local disaster risk reduction along a transportation corridor: A case study from Nilgiri district, India. Natural Hazards. 2013. Vol. 65. pp. 887–913DOI: 10.1007/s11069-012-0404-1.
Kapanski A., Hruntovich N.V., Klyuev R.V., Brigida V.S. Identification of easily accessible urban water consumption factors for energy-efficient management of pumping stations. Water Conservation Science and Engineering. 2025. Vol. 10. Art. No. 46. DOI: 10.1007/s41101-02500372-1.
Kara M.E., Seren A., Koroglu F., Alemdag H. Ground-penetrating radar (GPR) tomographic imaging and estimation of the volumetric water content of a viaduct pillar using the simultaneous iterative reconstruction technique algorithm. NDT & E International. 2025. Vol. 156. Art. No. 103448. DOI: 10.1016/j.ndteint.2025.1034481.
Kaya A., Midilli U.M. Slope stability evaluation and monitoring of a landslide: A case study from NE Turkey. Journal of Mountain Science. 2020. Vol. 17. pp. 2624–2635. DOI: 10.1007/ s11629-020-6306-x.
Lu K., Li K., Li F. et al. Using electrical resistivity techniques (ERT and SP) for nondestructive detection of seepage channels at the Leitai heritage site, China. Scientific Reports. 2025. Vol. 15. Art. No. 904. DOI: 10.1038/s41598-025-85368-6.
Lucchese L.V., de Oliveira G.G., Pedrollo O.C. Investigation of the influence of nonoccurrence sampling on landslide susceptibility assessment using Artificial Neural Networks. Catena. 2021. Vol. 198. Art. No. 105067. DOI: 10.1016/j.catena.2020.105067.
Ma W., Dong J., Wei Z., Peng L., Wu Q., Wang X., Wu Y. Landslide susceptibility assessment using the certainty factor and deep neural network. Frontiers in Earth Science. 2023. Vol. 10. Art. No. 1091560. DOI: 10.3389/feart.2022.1091560.
Pang Y., Yu Z., Xie Z. et al. Study of 3D electrical resistivity tomography in offshore waters. Doklady Earth Sciences. 2025. Vol. 523. Art. No. 19. DOI: 10.1134/S1028334X24605698.
Prapolski D., Romanovski V. Resent advances in underground water deironing and demanganization: Comprehensive review. Journal of Water Process Engineering. 2025. Vol. 70. Art. No. 107089. DOI: 10.1016/j.jwpe.2025.107089.
Slater L., Binley A. Advancing hydrological process understanding from long-term resistivity monitoring systems. Wiley Interdisciplinary Reviews Water 2021. Vol. 8. Issue 3. Art. No. e1513. DOI: 10.1002/wat2.1513.
Tsai C.C., Lin C.H. Review and future perspective of geophysical methods applied in nearshore site characterization. Journal of Marine Science and Engineering. 2022. Vol. 10. Art. No. 344. DOI: 10.3390/jmse10030344.
Tutberidze T.V., Ryndin A.V., Besedin T.D. et al. Interrelation between growing conditions in caucasus subtropics and actinidia deliciosa ‘Hayward’ yield for the sustainable agriculture. Sustainability. 2025. Vol. 17. Art. No. 6499DOI: 10.3390/su17146499.
Uyanik O. Estimation of the porosity of clay soils using seismic P- and S-wave velocities. Journal of Applied Geophysics. 2019. Vol. 170. Art. No. 103832DOI: 10.1016/j.
jappgeo.2019.103832.
Wei L., Zeng Z., Yan J. Factors affecting the stability of Loess Landslides: A review. Applied Sciences. 2024. Vol. 14. Issue 7. Art. No. 2735. DOI: 10.3390/app14072735.
Whiteley J.S., Chambers J.E., Uhlemann S., Wilkinson P.B., Kendall J.M. Geophysical monitoring of moisture-induced landslides: A review. Reviews of Geophysics. 2019. Vol. 57. Issue1. pp. 106–145. DOI: 10.1029/2018RG000603.
Wu K., Rodriguez G.A., Zajc M., Jacquemin E., Clement M., De Coster A., Lambot S. A new drone-borne GPR for soil moisture mapping. Remote Sensing of Environment. 2019. Vol. 235. Art. No. 111456. DOI: 10.1016/j.rse.2019.111456.
Xu H., Shu B., Zhang Q., Du Y., Zhang J., We T., Xiong G.H., Dai X.L., Wang L. Site selection for landslide GNSS monitoring stations using InSAR and UAV photogrammetry with analytical hierarchy process. Landslides. 2024. Vol. 21. pp. 791–805. DOI: 10.1007/s10346-02302188-31.
Zaalishvili V., Burdzieva O., Kanukov A., Zaks T. Eco-Geophysical and Geoecological Factors in Assessing the State of the Geological Environment Based on the Analysis of Spatial Databases of the Territory of the Republic of North Ossetia-Alania. Applied Sciences. 2022. Vol. 12. Art. No. 2644. DOI: 10.3390/app12052644.
Zakharikhina L., Lesnikova P., Rogozhina E., Kerimzade V., Gorbunova D. Influence of wind direction on the elemental composition of atmospheric deposition on the Black Sea coast of Sochi, Russia. Environment and Ecology Research. 2024. Vol. 12. Issue 5. pp. 514–536. DOI: 10.13189/eer.2024.120505.
Zhu W., Biondi E., Li J. et al. Seismic arrival-time picking on distributed acoustic sensing data using semi-supervised learning. Nature Communications. 2023. Vol. 14. Art. No. 8192. DOI: 10.1038/s41467-023-43355-3.
English
Русский
