Journal of Mountain Science

, Volume 13, Issue 4, pp 569–580 | Cite as

Erosion processes in karst landscapes of the Russian plain northern taiga, based on digital elevation modeling

  • Elena PolyakovaEmail author
  • Mikhail Gofarov
  • Yuriy Kutinov
  • Vladimir Beljaev
  • Zinaida Chistova
  • Nikolay Neverov
  • Vadim Staritsyn
  • Alexandr Mineev
  • Sergey Durynin


This paper considers the problems of the potential development of erosion processes in the natural landscapes of northern taiga in the Russian plain. It is considered that in forest ecosystems, erosion processes are slow and are weakly reflected in the terrain. However, the situation changes radically if the vegetation cover integrity is violated, which is inevitable with the modern methods of developing northern territories. Furthermore, global changes in average annual temperatures and the occurrence of karst processes may be the reason behind the development of erosion processes. The authors suggest a method for determining territories with a varying occurrence probability of erosional processes, based on digital elevation modelling. The territory of the Pinezhsky Nature Reserve (Arkhangelsk region) was chosen as the test plot. Direct field studies were previously used to detect exogenous geological processes in this territory. The authors were the first to suggest digital elevation modelling as a method that allows determining the potential danger of erosion in karst landscapes of the northern taiga. The geomorphometric studies resulted in the determination of areas with the greatest and lowest occurrence probability of erosion processes in the Pinezhsky Nature Reserve. It was established that the most significant erosion type was linear erosion, represented by incised river valleys and karst ravines. Sheet erosion is less significant and occurs as sinkholes, local declines, and chasms over the valleys of subterranean rivers.


Russian plain Erosion processes Karst Northern taiga Digital elevation model Geomorphometric parameters 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. Blanco-Canqui H, Lal R (2008) Soil and water conservation. In: Principles of Soil Conservation and Management. Springer. p 617. DOI: 10.1007/978-1-4020-8709-7Google Scholar
  2. Chikishev AG (1978) Karst in the Russian Plain. Nauka, Moscow, Russia. p 192. (In Russian)Google Scholar
  3. Osipov VI, Kutepov VM, Zverev VL (1999) Dangerous exogenous processes. GEOS, Moscow, Russia. p 290 (In Russian)Google Scholar
  4. De Carvalho OA, Guimarães RF, Montgomery DR, Gillespie AR, Trancoso Gomes RA, de Souza Martins É, Silva NC (2014) Karst depression detection using ASTER, ALOS/PRISM and SRTM-Derived Digital Elevation Models in the Bambuí Group, Brazil. Remote Sensing 6: 330–351. DOI: 10.3390/rs6010330CrossRefGoogle Scholar
  5. Doctor DH, Young JA(2013) An Evaluation of Automated GIS Tools for Delineating Karst Sinkholes and Closed Depressions from 1-Meter LIDAR-derived Digital Elevation Data. In Proceedings of the 13th Multidisciplinary Conference on Sinkholes and the Engineering and Environmental Impacts of Karst, Carlsbad, NM, USA, held in Tampa, South Florida, USA, 2013. pp 449–458.Google Scholar
  6. Elsakov VV, Teteryuk LV (2012) The role of terrain in the formation of vegetation in karst landscapes of the European Northeastern Russia. Earth and Universe Investigations 3: 78–93. (In Russian)Google Scholar
  7. Ford DC, Williams P (2007) Karst Hydrogeology and Geomorphology. John Wiley & Sons Ltd, Chichester, UK. P 243.CrossRefGoogle Scholar
  8. Glotov AA (2013) Using digital elevation models for efficient environmental management. Geomatics 4: 32–36 (In Russian).Google Scholar
  9. Glotov, A.A. 2014. Using methods of geoinformatic terrain modeling for municipal management. Geomatics 2: 38–41(In Russian).Google Scholar
  10. Gofarov MY, Bolotov IN, Kutinov YG (2006) Landscapes of the Belomorsko-Kuloyskoe plateau: tectonics, bedrocks, terrain and vegetation cover. Ural Branch of the Russian Academy of Sciences, Yekaterinburg, Russia. p 156. (In Russian)Google Scholar
  11. Hengl T, Reuter H (2009) Geomorphometry: Concepts, Software, Applications. In: Developments in Soil Science, vol. 33, Elsevier. pp 698–765.Google Scholar
  12. Hutchinson MF, Stein JL, Stein JA, Anderson H, Tickle PK (2008) GEODATA 9 Second DEM and D8: Digital Elevation Model and Flow Direction Grid, User Guide. Geoscience Australia, Canberra, ACT, Australia. p 43.Google Scholar
  13. Hutchinson MF, Xu T, Stein JA (2011) Recent Progress in the ANUDEM Elevation Gridding Procedure. In: Hengl T, Evans IS, Wilson JP, Gould M (eds.), Geomorphometry. Redlands, California, USA. pp 19–22.Google Scholar
  14. Julien PY (2010) Erosion and Sedimentation. Cambridge University Press, Cambridge, UK. p 371.CrossRefGoogle Scholar
  15. Kheir B, Abdallah C, Khawlie M (2008) Assessing soil erosion in Mediterranean karst landscapes of Lebanon using remote sensing and GIS. Engineering Geology 99: 239–254. DOI: 10.1016/j.enggeo.2007.11.012CrossRefGoogle Scholar
  16. Malkov VN, Gurkalo YI, Monakhova LB, Shavrina VY (2001) Karst and caves of the Prionezhsky District. Ecost Association, Moscow, Russia. p 208. (In Russian)Google Scholar
  17. Mashimbye ZE, de Clercq WP, van Niekerk A (2014) An evaluation of digital elevation models (DEMs) for delineating land components. Geoderma 213: 312–319. DOI: 10.1016/j.geoderma.2013.08.023CrossRefGoogle Scholar
  18. Maune DF (2001) Digital Elevation Model Technologies and Applications: The DEM Users Manual. In: American Society for Photogrammetry and Remote Sensing, Bethesda, Maryland, USA. p 539.Google Scholar
  19. Menz G, Richters J (2005) Quantitative classification of landscape units in Northern Namibia using an ASTER digital elevation model. In: Bollig M, Gruntkowski N (eds.), Landscape in Interdisciplinary Research, Kluwer. pp 179–202.Google Scholar
  20. Mikhailov SA (2000) Diffuse pollution of water ecosystems. In: Assessment methods and mathematical models. Day, Barnaul, Russia. pp 243–354. (In Russian)Google Scholar
  21. Minár J, Evans IS (2008) Elementary forms for land surface segmentation: the theoretical basis of terrain analysis and geomorphological mapping. Geomorphology 95(3-4): 236–259CrossRefGoogle Scholar
  22. Mineev AL, Kutinov YG, Chistova ZB, Polyakova EV (2015) Preparing a digital elevation model to study exogenous processes in the northern areas of the Russian Federation. Space and Time 3(21): 278–291. (In Russian)Google Scholar
  23. Minyaev AP, Yudakhin FN (1996) Environmental problems of the Arkhangelsk region. In Environmental problems of the European North: Collection of research papers. Russian Academy of Sciences, Ural Branch publishing house, Yekaterinburg, Russia. pp 3–9. (In Russian)Google Scholar
  24. Möller M et al (2012) Plausibility test of conceptual soil maps using relief parameters. Catena 88(1): 57–67. DOI: 10.1016/j.catena.2011.08.002CrossRefGoogle Scholar
  25. Moore ID, Grayson RB, Ladson AR (1991) Digital terrain modelling: A review of hydrological, geomorphological, and biological applications. Hydrological Processes 5(1): 3–30. DOI: 10.1002/hyp.3360050103CrossRefGoogle Scholar
  26. Musin AG, Gubeyeva SK (2012) The role of terrain-forming processes in karst formation. Modern Problems of Science and Education 4: 1–4. (In Russian)Google Scholar
  27. Pardo-Igúzquiza E, Durán JJ, Dowd PA (2013) Automatic detection and delineation of karst terrain depressions and its application in geomorphological mapping and morphometric analysis. ActaCarsoligica 42: 17–24.Google Scholar
  28. Polyakova EV (2012) Strontium in the underground water of the Mezensyneclise. Academic Publishing, Hamburg, Germany. p 185.Google Scholar
  29. Polyakova EV, Gofarov MY (2014) Morphometric analysis of the Vaygach Island terrain, according to the data of Earth remote sensing. Current Problems in Remote Sensing of the Earth from Space 11: 226–234. (In Russian)Google Scholar
  30. Poznanin VL (2012) Erosion processes in permafrost. Space and Time 1(7): 127–132. (In Russian)Google Scholar
  31. Puchnina LV (2000) The structure and dynamics of natural components in the Pinezhsky Nature Reserve (northern taiga of the European Russia, Arkhangelsk region). In: Biodiversity and geodiversity in karst areas. SOLTI, Arkhangelsk, Russia, pp 183–267. (In Russian)Google Scholar
  32. Puchnina LV (2008) Ecosystem components and biodiversity of the European Northern Russia karst territories (by the example of the Pinezhsky Nature Reserve).SOLTI, Arkhangelsk, Russia. p 186. (In Russian)Google Scholar
  33. Riley SJ, De Gloria SD, Elliot R (1999) A Terrain Ruggedness Index that Quantifies Topographic Heterogeneity. Intermountain Journal of Science 5(1-4): 23–27.Google Scholar
  34. Rychagov GI (2006) General geomorphology. Nauka, Moscow, Russia. p 235. (In Russian)Google Scholar
  35. Shary PA (2006) Geomorphometrics in geosciences and environmental sciences, survey of methods and applications. Russian Academy of Sciences Samara Research Center 8(2): 458–473. (In Russian)Google Scholar
  36. Shary PA, Sharaya LS, Mitusov AV (2002) Fundamental quantitative methods of land surface analysis. Geoderma 107(1-2): 1–32. (In Russian)CrossRefGoogle Scholar
  37. Siart C (2009) Combining digital elevation data (SRTM/ASTER), high resolution satellite imagery (Quickbird) and GIS for geomorphological mapping: a multi-component case study on Mediterranean karst in Central Crete. Geomorphology 112: 106–121.DOI: 10.1016/j.geomorph.2009.05.010CrossRefGoogle Scholar
  38. Smith de M, Goodchild M, Longley P (2013) Geospatial Analysis–A Comprehensive Guide to Principles, Techniques and Software Tools. Troubador Publishing Ltd, Leicester, UK. P 418.Google Scholar
  39. Theilen-Willige B, Ait M, Halima C, Abdessamad B, Fatima E, Chaïbi M(2014) Remote Sensing and GIS Contribution to the Investigation of Karst Landscapes in NW-Morocco. Geosciences 4: 50–72. DOI: 10.3390/geosciences4020050CrossRefGoogle Scholar
  40. Tokarev SV (2011) On the methodology of karstological and geomorphological charting by means of satellite data regarding the terrain of the Earth. Science notes of the Taurida National V.I. Vernadsky University. “Geography” series 24 (63): 185–193. (In Russian)Google Scholar
  41. Toy TJ, Foster GR, Renard KG (2008) Soil Erosion: Processes, Prediction, Measurement, and Control. John Wiley & Sons, New York, USA. p 338.Google Scholar
  42. Waren SD, Hohmann MG, Auerswald K, Mitášová H (2004) An evaluation of methods to determine slope using digital elevation data. Catena 58: 215–233.CrossRefGoogle Scholar
  43. Wilson JP, Gallant JC (2000) Terrain Analysis: Principles and Applications. John Wiley and Sons, New York, USA. p 479.Google Scholar
  44. Wood J (1996) The geomorphological characterisation of digital elevation models. Ph.D. Thesis. Department of Geography. University of Leicester, Leicester, UK. P 185.Google Scholar
  45. Yakuch L (1979) Morphogenesis of karst areas.Progress, Moscow, Russia. p 388. (In Russian)Google Scholar
  46. Yokoyama R, Shirasawa M, Pike RJ (2002) Visualizing topography by openness: a new application of image processing to digital elevation models. Photogrammetric Engineering and Remote Sensing 68 (3): 251–266.Google Scholar
  47. Zevenbergen LW, Thorne CR (1987) Quantitative analysis of land surface topography. Earth Surface Processes and Landforms 12(1): 47–56.CrossRefGoogle Scholar
  48. Zhang WH, Montgomery DR (1994) Digital elevation model grid size, landscape representation, and hydrologic simulations. Water Resources Research 30(4): 1019–1028.CrossRefGoogle Scholar
  49. Zhang Z, Xu W, Zhou W, et al. (2014) Integrating remote sensing with GIS-based multi-criteria evaluation approach for Karst rocky desertification assessment in Southwest of China. In: 8th International Symposium of the Digital Earth (ISDE8), held in Kuching, Sarawak, Malaysia, 26–29 August 2013. pp 1–6. DOI: 10.1088/1755-1315/18/1/012038Google Scholar

Copyright information

© Science Press, Institute of Mountain Hazards and Environment, CAS and Springer-Verlag Berlin Heidelberg 2016

Authors and Affiliations

  • Elena Polyakova
    • 1
    • 2
    Email author
  • Mikhail Gofarov
    • 3
  • Yuriy Kutinov
    • 1
    • 2
  • Vladimir Beljaev
    • 4
  • Zinaida Chistova
    • 4
  • Nikolay Neverov
    • 4
  • Vadim Staritsyn
    • 4
  • Alexandr Mineev
    • 4
  • Sergey Durynin
    • 4
  1. 1.Institute of Ecological Problems of the North, Ural Branch of Russian Academy of SciencesGeological Structure and Dynamics of the Lithosphere LaboratoryArkhangelskRussia
  2. 2.Space Monitoring of the Arctic Centre of the Northern Arctic Federal University namedafter M.V. LomonosovArkhangelskRussia
  3. 3.Institute of Ecological Problems of the North, Ural Branch of Russian Academy of SciencesMolecular Ecology and Biogeography LaboratoryArkhangelskRussia
  4. 4.Institute of Ecological Problems of the North, Ural Branch of Russian Academy of SciencesGeological Structure and Dynamics of the Lithosphere LaboratoryArkhangelskRussia

Personalised recommendations