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2012 | 21 | 6 |
Tytuł artykułu

Application of USLE, GIS, and remote sensing in the assessment of soil erosion rates in Southeastern Serbia

Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
The assessment of soil erosion rate and its spatial distribution in the hilly-mountainous Nisava River basin was conducted by Universal Soil Loss Equation (USLE) model through a GIS-based approach. A Landsat 7 Enhanced Thematic Mapper (ETM+) image and normalized difference vegetation index (NDVI) were used for the determination of crop management factor. The average annual soil loss was estimated at 13.1 t·ha⁻¹·yr⁻¹, classifying the Nisava River basin under the high erosion rate category. About 44.1% of the watershed area was characterized by slight erosion rate (< 5 t·ha-1·yr⁻¹), 15.5% of the area was found to be under moderate erosion rate (5-10 t·ha⁻¹), 18.9% of the area was under high erosion rate (10-20 t·ha⁻¹), while around 14.4% of the area was under a very high erosion rate (20-40 t·ha-1·yr⁻¹). Severe erosion rates (40-80 t·ha-1·yr⁻¹) were observed at 5.9% of the study area (168 k²), whereas very severe erosion rate (>80 t·ha-1·yr⁻¹) described about 1.3% of the watershed (35.9 km²). The highest erosion was found on a sloppy terrain with agricultural activity. The results of this work are in agreement with previous studies conducted in the watershed, which indicates the presented methodology could be applied with eventual further improvements for the evaluation of erosion factors on soil resources in Serbia when limited data are available.
Słowa kluczowe
Wydawca
-
Rocznik
Tom
21
Numer
6
Opis fizyczny
p.1929-1935,fig.,ref.
Twórcy
autor
  • Faculty of Agriculture, University of Belgrade, Nemanjina 6, 11080 Zemun, Serbia
autor
  • Institute of Soil Science, Teodora Drajzera 7, 11000 Belgrade, Serbia
autor
  • Institute of Soil Science, Teodora Drajzera 7, 11000 Belgrade, Serbia
autor
  • Faculty of Agriculture, University of Belgrade, Nemanjina 6, 11080 Zemun, Serbia
autor
  • Faculty of Mining and Geology, University of Belgrade, Djusina 7, 11000 Belgrade, Serbia
autor
  • CIHEAM – Mediterranean Agronomic Institute of Bari, Via Ceglie 9, Valenzano (BA) 70010, Italy
Bibliografia
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  • 2. KOULI M., SOUPIOS P. Soil erosion prediction using the revised Universal Soil Loss Equation (RUSLE) in a GIS framework, Chania, Northwestern Crete, Greece. Environ Geol 57, 483, 2009.
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  • 4. LASTORIA B., MISEROCCHI F., LANCIANI A., MONACELLI G. An Estimated Erosion Map for Aterno-Pescara River Basin. European Water 21-22, 29, 2010.
  • 5. ŞTEFĂNESCU L., CONSTANTIN V., SURD V., OZUNU A., VLAD Ş-N. Assessment of soil erosion potential by the USLE method in Roşia montană mining area and associated natech events. Carpath. J. Earth Env., 6, (1), 35, 2011.
  • 6. BATHRELLOS G.D., SKILODIMOU H.D., CHOUSIANITIS K.G. Soil Erosion Assessment in Southern Evia Island Using USLE and GIS. Bulletin of the Geological Society of Greece. Proceedings of the 12th International Congress, Patras, May, XLIII, (3), 1572, 2010.
  • 7. ONORI F., DE BONIS P., GRAUSO S. Soil erosion prediction at the basin scale using the revised universal soil loss equation (RUSLE) in a catchment of Sicily (southern Italy). Environ. Geol. 50, 1129, 2006.
  • 8. ARGHIUS C., ARGHIUS V. The quantitative estimation of the soil erosion using USLE type ROMSEM model. Casestudy - the Codrului Ridge and Piedmont (Romania). Carpath. J. Earth Env., 6, (2), 59, 2011.
  • 9. KARABURUN A. Estimation of C factor for soil erosion modeling using NDVI in Buyukcekmece watershed. Ozean Journal of Applied Sciences 3, (1), 2010.
  • 10. FISTIKOGLU O., HARMANCIOGLU N.B. Integration of GIS with USLE in Assessment of Soil Erosion. Water Resour. Manage. 16, 447, 2002.
  • 11. SHEPARD D. A two-dimensional interpolation function for irregularly-spaced data, Proc. 23rd National Conference ACM, ACM, pp. 517-524, 1968.
  • 12. RENARD K.G., FOSTER G.R., WEESIES G.A., RUSLE: revised universal soil loss equation. J Soil Water Conserv 46, (1), 30, 1991.
  • 13. MOORE I.D., WILSON J.P. Length-slope factors for the revised universal soil loss equation: simplified method of estimation. J Soil Water Conserv 47, (5), 423, 1992.
  • 14. MCCOOL D.K., BROWN L.C., FOSTER G.R. Revised slope steepness factor for the universal soil loss equation. Trans ASAE 30, 1387, 1987.
  • 15. HICKEY R., SMITH A., JANKOWSKI P. Slope length calculations from a DEM within Arc/Info GRID. Comput Environ Urban 18, (5), 365, 1994.
  • 16. VAN REMORTEL R., MAICHLE R., HICKEY R. Computing the RUSLE LS Factor based on Array-based Slope Length Processing of Digital Elevation Data Using a C++ Executable. Comput. Geosci. 30, (9-10), 1043, 2004.
  • 17. DE JONG S.M., RIEZEBOS H.T. SEMMED: a distributed approach to soil erosion modelling. In: Spiteri, A. (Ed.), Remote Sensing ’96: Integrated Applications for Risk Assessment and Disaster Prevention for the Mediterranean. Balkema, Rotterdam, pp. 199-204, 1997.
  • 18. VAN DER KNIJFF J., JONES R.J.A., MONTANARELLA L. Soil erosion risk assessment in Italy. European Soil Bureau, Joint Research Center of European Commission. EUR 19022EN, 2000.
  • 19. JENSEN J.R. Remote Sensing of the Environment: An Earth Resource Perspective. Prentice Hall, New Jersey, 2000.
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  • 21. MUSTAFIĆ S., KOSTADINOV S., MANOJLOVIĆ P. Risk of artificial lake “Zavoj” to processes of erosion – methodological, knowing and protecting aspect. Bulletin of the Serbian Geographical Society, Tome LXXXVIII, 2008 [In Serbian].
  • 22. KOSTADINOV S. Erosion in River Visočica watershed. Erozija, 30, 69-76, 2003 [In Serbian].
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  • 24. WU S., LI J., HUANG G., An evaluation of grid size uncertainty in empirical soil loss modeling with digital elevation models, Department of Agriculture, Regina, Saskatchewan, Canada. Environ Model Assess, 10, (1), 33, 2005.
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Typ dokumentu
Bibliografia
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