Problems of spatially distributed quantitative evaluation of soil erosion losses

Keywords: soil erosion, spatially-distributed assessment, global DEMs, cartographic DEMs

Abstract

Formulation of the problem. Water erosion of soils is the most widespread and dangerous soil degradation process in Ukraine. The development of an effective system of soil protection measures requires the use of spatially distributed mathematical models of soil erosion losses. This, in turn, highlights the problem of spatially distributed source data, which adequately reflect the spatial differentiation of factors of the erosion process, among which the main one is the relief.

The purpose of the article. Assessing the adequacy of available spatially distributed source data, including cartographic and freely distributed global digital elevation models (DEMs), for spatially distributed quantitative assessment of soil erosion losses at the local level of territorial coverage is the aim of the article.  Assessing from this point of view the scale of the original cartographic data, different global DEMs and their spatial resolution, as well as the degree of spatial generalization of the original data.

Materials and methods. The solution of the set tasks was performed by the method of simulation modeling with the use of physical-statistical GIS-realized mathematical model of soil erosion-accumulation, developed at Odessa I. I. Mechnikov National University. Source data arrays were tested with DEMs SRTM90 and SRTM30 with a spatial resolution of 3 and 1 angular seconds, respectively, and AW3D30 with a spatial resolution of 1 angular second, as well as with cartographic DEMs based on topographic maps of scale 1:10000 and 1:25000. For testing the initial data, three test plots with an area of 2.67, 0.59 and 0.21 km2 were selected. The plots are located in the Balta district of Odessa region on the southern spurs of the Podolska upland.

Results. It is established that freely distributed global digital elevation models SRTM and AW3D30 in the conditions of flat terrain do not always allow to adequately display the structure of slope runoff and, accordingly, to correctly perform calculations of soil erosion losses. The maximum deviation of the average soil erosion losses calculated for the test plots using global DEMs from the soil losses calculated using the reference DEM for SRTM30 and AW3D30 was 27%, for SRTM90 – almost 70%. The distribution of soil losses over the area of test plots obtained using different global DEMs differs even more.

When using DEM based on topographic maps, reducing the scale of the original maps from 1: 10000 to 1: 25000 leads to a decrease in the average value of soil erosion losses by about 20% due mainly to reducing the magnitude and area of distribution of maximum soil losses, and on slopes of complex shape also due to changes in the area of accumulation zones. The degree of spatial generalization of the initial data significantly affects the results of the assessment of soil erosion losses both in relation to the average values and their distribution over the area. For small areas, the use of raster cells larger than 50 m is impractical.

Scientific novelty and practical significance. It has been shown for the first time that in the conditions of flat terrain at the local level of spatial coverage, the freely distributed global DEM SRTM and AW3D30 are not always hydrologically correct. The reasons and conditions of violation of this correctness are specified. It has been established that the global DEM AW3D30 has local instrumental errors that may make it impossible to use it. The most realistic values of soil erosion losses are provided by DEM SRTM with a spatial resolution of 1 angular second.

Downloads

Download data is not yet available.

Author Biographies

Oleksandr Svіtlуchnyi, Odesa I.I. Mechnykov National University

DSc (Geography), Professor, Department of Physical Geography, Nature Management and Geoinformation Technologies

Alla Piatkova, Odesa I.I. Mechnykov National University

PhD (Geography), Associate Professor

References

Instruktsiya po opredeleniyu raschetnyih gidrologicheskih harakteristik pri proektirovanii protivoerozionnyih meropriyatiy na Evropeyskoy territorii SSSR (1979). [Instructions for determining the calculated hydrological characteristics for designing anti-erosion measures in the European territory of the USSR], Leningrad: Hydrome-teoizdat, 58 [in Russian].

Krupenikov I. A. (1990). Pochvennyiy pokrov i eroziya. Ekologicheskie aspektyi zaschityi pochv ot erozii [Soil covering and erosion. Ecological aspects of soil erosion protection. Environmental aspects of soil erosion protec-tion], Chishinau, Moldagroinformreklama, 4-16 [in Russian].

Larionov H. A. (1993). Eroziya i deflyatsiya pochv. [Soil erosion and deflation], Moscow, Moscow University pub-lishing house, 200 [in Russian].

Maltsev K. A., Golosov V. N., Gafurov A. M. (2018). Tsifrovyie modeli relefa i ih ispolzovanie v raschYotah tempov smyiva pochv na pahotnyih zemlyah [Digital elevation models and their use in calculating the rate of soil washout on arable land] Scient. Not, Kazan. un-t. Ser. Natural Science,160, 3, 514–530.

Balyuk S. A., Medvedev V. V., Tarariko O. G. etc. (2010), Natsionalna dopovid pro stan rodiuchosti gruntiv Ukrainy [National report about soil fertility state in Ukraine] Kyiv, RPO "VYK PRYNT", 111 [in Ukrainian].

Pyatkova, A. V. (2008). Osobennosti modelirovaniya vodnoy erozii s uchetom prostranstvennoy izmenchivosti ee faktorov [Features of soil water erosion modeling taking into account spatial changeability of its factors] Odessa National University Herald, Series geographical and geological sciences, 13, 6, 156-163 [in Russian].

Pyatkova, A.V. (2011). Prostorove modeliuvannia vodnoi erozii gruntu yak osnova naukovoho obgruntuvannia ratsionalnoho vykorystannia eroziino-nebezpechnykh zemel [The Spatial Modelling of Water Soil Erosion as the Basis of Scientific Justification of the Rational Use of Erosion Dangerous Lands] Extended abstract of candi-date’s thesis, Odesa: PPO Popova N.M., 20 [in Ukrainian].

Piatkova, A. V. (2014). Problemy kilkisnoi otsinky eroziinykh vtrat gruntu [Problems of the assessment of the ero-sion soil loses] Odessa National University Herald, Series Geography and Geology, 19, 4 (23), 28-37 [in Ukrainian].

Svetlitchnyi, A. A. (1999). Printsipyi sovershenstvovaniya empiricheskih modeley smyiva pochvyi [Principles of improving empirical soil loss models] Pochvovedenie, 8, 1015-1023 [in Russian].

Svitlychnyi O. O., Ivanova A. V. (2003). Pryntsypy prostorovoho modeliuvannia hidrometeorolohichnykh umov zlyvovoho zmyvu gruntu [Principles of spatial modelling of hydrometeorological conditions of soil storm wash off] Odessa National University Herald. Series geographical and geological sciences, 8, 77-82 [in Ukrainian].

Svetlitchnyi A. A. (2020). Pro vykorystannia vilno poshyriuvanykh hlobalnykh tsyfrovykh modelei reliefu vysokoi prostorovoi rozdilnoi zdatnosti dlia rozrakhunkiv vodnoi erozii hruntu [On the use of freely distributed global digital elevation models of the high spatial resolution for calculations of water erosion of soil], Odessa National University Herald. Series geographical and geological sciences, 25, 2(37), 44-65 [in Ukrainian].

Svetlitchnyi, A. A., Cherny, S. G., Shvebs, H. I., (2004). Eroziovedenie: teoreticheskie i prikladnyie aspektyi [Soil erosion science: theoretical and applied aspects], Sumy: VTD “University Book”, 410 [in Russian].

Shvebs, H. I. (1974). Formirovanie vodnoy erozii, stoka nanosov i ih otsenka [Formation of water erosion, sedi-ment yield and their evaluation], Leningrad: Hydrometeoizdat, 184 [in Russian].

Shvebs, H. I. (1981). Teoreticheskie osnovyi eroziovedeniya [The theoretical foundations of soil erosion science], Kiev-Odessa: Vyshcha shkola, 223 [in Russian].

ASTER GDEM Validation Team (2009). ASTER Global DEM Validation: Summary Report, METI & NASA. 28. Available at: https://pdfs.semanticscholar.org/5606/ead88307ae1700c3db6744c6be5aedc4935c.pdf?_ga=2.258449996.738829358.1594921941-993585188.1594921941

Jeiner Yobany Buitrago E., Luis Joel Martínez M. (2016). Digital elevation models (DEM) used to assess soil ero-sion risks: a case study in Boyaca, Colombia. Agronomía Colombiana, 34, 2, 239-249. https://doi.org/10.15446/agron.colomb.v34n2.56145.

Khal M., Algouti A., Algouti A., Akdim N., Stankevich S.A, Menenti M. (2020). Evaluation of open Digital Elevation Models: estimation of topographic indices relevant to erosion risk in the Wadi M’Goun watershed, Morocco. AIMS Geosciences, 6(2), 231–257. https://doi.org/10.3934/geosci.2020014

Kovalchuk I. P., Lukianchuk K. A., Bogdanets V. A. (2019). Assessment of open source digital elevation models (SRTM-30, ASTER, ALOS) for erosion processes modeling. Journ.Geol.Geograph. Geoecology, 28(1), 95-105. https://doi.org/10.15421/111911

Mondal A., Khare D., Kundu S. (2016). Uncertainty analysis of soil erosion modeling using different resolution of open source DEMs. Geocarto International, 32(3), 334-349. http://dx.doi.org/10.1080/10106049.2016.1140822

PCRaster: Software for Environmental Modeling (2018). Available at: http://pcraster.geo.uu.nl/downloads/latest-release//

Rabus, B., Eineder, M., Roth, A. and Bamler, R. (2003). The Shuttle Radar Topography Mission – A New Class of Digital Elevation Models Acquired by Spaceborne Radar. ISPRS Journal of Photogrammetry and Remote Sensing, 57, 241-262. DOI: http://dx.doi.org/10.1016/S0924-2716(02)00124-7.

Renard K.G, Foster G.R, Weesies G.A, McCool D.K, Yoder D.C (1997). Predicting soil erosion by water: a guide to conservation planning with the Revised Universal Soil Loss Equation (RUSLE). U.S. Dept. of Agriculture, Agric. Handbook 703, 404 Available at: https://www.ars.usda.gov/ARSUserFiles/64080530/RUSLE/AH_703.pdf.

Shan L., Yang X., Zhu Q. (2019), Effects of DEM resolutions on LS and hillslope erosion estimation in a burnt landscape. Soil Research, 57(7), 797-804. DOI: http://dx.doi.org/10.1071/SR19043

Svetlitchnyi А.A., Piatkova A.V. (2019). Spatially distributed gis-realized mathematical model of rainstorm erosion losses of soil. Journal of Geology, Geography and Geomorphology, 28(3), 562-571. DOI: https://doi.org/10.15421/111953

Takaku, J., Tadono, T., Tsutsui, K. (2014). Generation of High Resolution Global DSM from ALOS PRISM. The In-ternational Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, ISPRS, XL-4, 243-248. DOI: http://dx.doi.org/10.5194/isprsarchives-XL-4-243-2014

Vijith H, Seling L.W., Dodge-Wan D (2015). Comparison and Suitability of SRTM and ASTER Digital Elevation Data for Terrain Analysis and Geomorphometric Parameters: Case Study of Sungai PatahSubwatershed (Baram River, Sarawak, Malaysia). Environ Res Eng Manag, 71, 23–35. Available at: https://www.researchgate.net/deref/http%3A%2F%2Fdx.doi.org%2F10.5755%2Fj01.erem.71.3.12474

Wischmeier, W. H.; Smith D. D. (1978). Predicting rainfall erosion losses; a guide to consevation planning. The USDA Agricultural Handbook, 537, Washington DC, 58. Available at: https://naldc.nal.usda.gov/download/CAT79706928/PDF

Published
2022-06-01
Cited
How to Cite
SvіtlуchnyiO., & Piatkova, A. (2022). Problems of spatially distributed quantitative evaluation of soil erosion losses. Visnyk of V. N. Karazin Kharkiv National University, Series "Geology. Geography. Ecology", (56), 184-197. https://doi.org/10.26565/2410-7360-2022-56-13