Assessment of erosion risk of relief based on the digital modeling

https://doi.org/10.35595/2414-9179-2021-2-27-241-252

View or download the article (Rus)

About the Authors

Mariya A. Kondrateva

Perm State Agro-Technological University,
Petropavlovskaya str., 23, 614000, Perm, Russia;
E-mail: pochva@pgsha.ru

Aleksey N. Chashchin

Perm State Agro-Technological University,
Petropavlovskaya str., 23, 614000, Perm, Russia;
E-mail: pochva@pgsha.ru

Abstract

On the basis of a digital elevation model (DEM) based on generalized data from USGS STRM DEM and ASTER GDEM with a resolution of 3″ with the help of GIS technologies, a morphometric analysis of the territory of the perm Territory at a scale of 1:2.5 million was carried out and a series of morphometric maps was created, as well as an assessment map of the erosion hazard of the relief. According to the results of morphometric analysis, the values of the index of vertical dissection of the relief in the region vary within the range of 0–623 m with an average value of 44 m. The steepness of slopes varies from 0 to 40° with average values of 3°. The horizontal dissection, determined on the basis of the thalweg network of permanent and temporary streams, varies in the range of 0.145–1.202 km/km2. Comparison of morphometric indicators in key areas with the data obtained by traditional methods of morphometric analysis revealed their coincidence at the level of gradations. The following geomorphological factions curtains: wide development of slope surfaces with elevation differences over 50 m and slopes exceeding 3°. According to the results of cartometric analysis, such conditions characterize 35 % of the region’s area. More than half of the region’s area (60 %) has an average density of erosional dissection of 0.5–0.8 km/km2, another 36 % of the area is characterized by moderate values of 0.2–0.5 km/km2.

The calculated relief energy index has a value of 3–13 points; on its basis, 4 categories of relief erosion hazard were identified. In accordance with the results obtained, most of the perm Territory (63.0 %) is characterized by a low erosion hazardous relief, 36.6 % by a medium and highly erosion hazardous. The share of land, the relief of which is characterized by zero erosion potential, is 0.4 % of the region’s area.

Keywords

erosion hazard, digital elevation model, SRTM, ASTER, GIS technologies, Perm region, morphometric analysis.

References

  1. Alekseeva O.L. The total dissection of the relief of the perm region. Physical and Geographical bases of development and distribution of productive forces of the Non-Chernozem Urals: Interved. Sat. scientific. works. Perm: Izdatel’stvo Permskogo universiteta, 1982. P. 54–63 (in Russian).
  2. Bogale A. Morphometric analysis of a drainage basin using geographical information system in Gilgel Abay watershed, lake Tana Basin, upper Blue Nile Basin, Ethiopia. Appl. Water Sci. 2021. V. 11 (122). P. 1–7. DOI: 10.1007/s13201-021-01447-9.
  3. Dumit Zh.A. On the issue of errors in digital modeling of relief (morphometric aspect). Geographic studies of the Krasnodar Territory: Ser. Natural Sciences. Krasnodar: KubSU, 2007. Issue. 2. P. 49–53.
  4. Farr T.G., Rosen P.A., Caro E. and etc. The Shuttle Radar Topography Mission. Rev. Geophys. 2007. V. 45. No. 2. Art. RG2004. P. 1–33. DOI: 10.1029/2005RG000183.
  5. Ferranti J. Viewfinder Panoramas. 2014: Digital elevations data. Web resource. URL: http://viewfinderpanoramas.org/dem3.html (accessed 10.04.2021).
  6. Frey H., Paul F. On the suitability of the SRTM DEM and ASTER GDEM for the compilation of topographic parameters in glacier inventories. Int. J. Appl. Earth Obs. Geoinf. 2012. V. 18. P. 480–490. DOI: 10.1016/j.jag.2011.09.020.
  7. Kopylov I.S. Morphoneotectonic system for assessing geodynamic activity: monograph perm, 2019. 131 p. Web resource: http://www.psu.ru/files/docs/science/books/mono/kopylov-morfoneotektonicheskaya-sistema-ocenkigeodinamicheskoj-aktivnosti.pdf (accessed 20.01. 2021) (in Russian).
  8. Kurlovich D.M. Morphometric GIS analysis of the relief of Belarus. Land of Belarus. 2013. No. 4. P. 42–48 (in Russian).
  9. Kurlovich D.M. Spatial differentiation and dynamics of morphostructures of the Belarusian poozerie. Minsk: BSU, 2014. 158 p. (in Russian).
  10. Maltsev K.A., Golosov V.N., Gafurov A.M. Digital Elevation Models and Their Use for Assessing Soil Erosion Rates on Arable Lands. Proceedings of Kazan University. Natural Sciences Series. Ser. Natural Sciences. 2018. V. 160. No. 3. P. 514–530 (in Russian).
  11. Mikhailov V.A. Complex morphometric analysis of the Tarkhankut peninsula using GIS. Modern scientific research and innovations. 2015. No. 2. Web resource: http://web.snauka.ru/issues/2015/02/46640 (accessed 20.01.2021) (in Russian).
  12. Mondal A., Khare D., Kundu S., Mukherjee S., Mukhopadhyay A., Mondal S. Uncertainty of soil erosion modelling using open source high resolution and aggregated DEMs. Geosci. Frontiers. 2017. V. 8. No. 3. P. 425–436. DOI: 10.1016/j.gsf.2016.03.004.
  13. Onkov I.V., Onyanova T.Ya., Shilyaeva O.Yu. Investigation of the accuracy of radar DEMs built from ALOS PALSAR images and SRTM model, depending on the type of reflecting surface. Geomatics. 2012. No. 4. P. 33–36 (in Russian).
  14. Osintseva N.V. Assessment of the erosion hazard of the relief of the territory of Tomsk. Questions of the geography of Siberia. Issue 25. Tomsk: Tomsk state. un-t, 2003. P. 56–66 (in Russian).
  15. Papaiordanidis S., Gitas I.Z., Katagis T. Soil erosion prediction using the Revised Universal Soil Loss Equation (RUSLE) in Google Earth Engine (GEE) cloud-based platform. Dokuchaev Soil Bulletin. 2019. V. 100. P. 36–52. DOI: 10.19047/0136-1694-2019-100-36-52.
  16. Pavlova A.I. Application of digital terrain modeling methods for mapping erosional lands. In the world of scientific discoveries. 2016. No. 2 (74). P. 159–167 (in Russian).
  17. Pozachenyuk E.A., Petlyukova E.A. GIS analysis of morphometric indicators of the relief of the Central foothills of the main ridge of the Crimean mountains for the purposes of landscape planning. Scientific notes of the Crimean Federal University named after V.I. Vernadsky. geography. geology. V. 2 (68). 2016. No. 2. P. 95–111 (in Russian).
  18. Putilin A.F. Gully formation in the southeast of Western Siberia. Novosibirsk, 1988. 81 p. (in Russian).
  19. Ramesh L. Dikpal, Renuka Prasad T.J., Satish K. Evaluation of morphometric parameters derived from Cartosat-1 DEM using remote sensing and GIS techniques for Budigere Amanikere watershed, Dakshina pinakini Basin, Karnataka, India. Appl. Water Sci. 2017. V. 7. P. 4401–4414. DOI: 10.1007/s13201-017-0585-6.
  20. Reuter H.I., Neison A., Strobl P., Mehl W., Jarvis A. A first assessment of Aster GDEM tiles for absolute accuracy, relative accuracy and terrain parameters. 2009 IEEE Int. Geoscience and Remote Sensing Symposium. IEEE, 2009. V. 5. P. 240–243. DOI: 10.1109/IgARSS.2009.5417688.
  21. Scriabina O.A. Water erosion of soil and its control. Perm: Permskoye knizhnoye izdatel’stvo, 1990. 24 p. (in Russian).
  22. Shimanovskaya O.L., Shimanovsky L.A. The density of the river network of the perm region and the patterns of its formation. Physical and geographical bases of development and distribution of productive forces of the Non-Chernozem Urals. Perm: Izdatel’stvo Permskogo universiteta, 1970. P. 102–110 (in Russian).
  23. Shimanovsky L.A. Geomorphological zoning of the Perm region. Physical and geographical bases of development and distribution of productive forces of the Non-Chernozem Urals. Perm: Izdatel’stvo Permskogo universiteta, 1985. P. 66–79 (in Russian).
  24. Szabó G., Singh S.K., Szabó S. Slope angle and aspect as influencing factors on the accuracy of the SRTM and the ASTER GDEM databases. Phys. Chem. Earth. Parts A/B/C. 2015. V. 83–84. P. 137–145. DOI: 10.1016/j.pce.2015.06.003.

For citation: Kondrateva M.A., Chashchin A.N. Assessment of erosion risk of relief based on the digital modeling InterCarto. InterGIS. GI support of sustainable development of territories: Proceedings of the International conference. Moscow: MSU, Faculty of Geography, 2021. V. 27. Part 2. P. 241–252. DOI: 10.35595/2414-9179-2021-2-27-241-252 (In Russian)