Assessment of soil loss by universal soil loss equation (USLE) model using GIS techniques: a case study of Gumti River Basin, Tripura, India

  • Amit Bera
Original Article


Soil loss is a serious environmental threat in humid sub-tropical State Tripura. The present study is carried out in Gumti River Basin of Tripura State, North East India having an area of 2492 km2. Long term daily rainfall intensity is very high in this region and that’s why sheet erosion of soil is common phenomena. Spatial distribution of soil loss in the study area was estimated by integrating five essential parameters of universal soil loss equation model in GIS mapping platform (mainly ArcGIS 10.1). Those five parameter are runoff–rainfall erosivity factor (R), soil erodibility factor (K), slope length and steepness (LS), cropping management factor (C), and support practice factor (P). In these study ASTER digital elevation model having 30 m resolution and LISS III image have been used for estimation of LS factor and C factor. The daily rainfall data (2001–2010) of seven rain gauge stations located in the Gumti River Basin and its adjoining area have been used to predict the R factor. Predicted average annual soil loss of the basin has been classified into five categories according to intensity level of soil loss. The high rate (>45 t ha−1 year−1) of soil erosion was found along the main course of Gumti River, interhill valley portion and also the flood plain area of the basin, whereas low amount of soil loss (<10 t ha−1 year−1) was found at densely forested areas and intensely plantation area of the basin.


Soil loss Erosion risk USLE GIS Remotely sensed data Gumti River 


  1. Bera A, Namasudra P (2016) Impact of shifting cultivation on the environmental changes in Gumti River Basin, Tripura. Int J Recent Sci Res 7(6):11771–11774Google Scholar
  2. Evans R (1980). Mechanics of water erosion and their spatial and temporal controls: an empirical viewpoint. In: Soil erosion. Wiley, New York, p 109–128Google Scholar
  3. Fistikoglu O, Harmancioglu NB (2002) Integration of GIS with USLE in assessment of soil erosion. Water Resour Manag 16(6):447–467CrossRefGoogle Scholar
  4. Ganasri BP, Ramesh H (2016) Assessment of soil erosion by RUSLE model using remote sensing and GIS—a case study of Nethravathi Basin. Geosci Front 7(6):953–961. doi: 10.1016/j.gsf.2015.10.007 CrossRefGoogle Scholar
  5. Ghosh K, De SK, Bandyopadhyay S, Saha S (2013) Assessment of soil loss of the Dhalai River Basin, Tripura, India using USLE. Int J Geosci 4(1):11–23. doi: 10.4236/ijg.2013.41002 CrossRefGoogle Scholar
  6. Irvem A, Topaloğlu F, Uygur V (2007) Estimating spatial distribution of soil loss over Seyhan River Basin in Turkey. J Hydrol 336(1):30–37CrossRefGoogle Scholar
  7. Jain SK, Kumar S, Varghese J (2001) Estimation of soil erosion for a Himalayan Watershed using GIS technique. Water Resour Manag 15(1):41–54CrossRefGoogle Scholar
  8. Kim HS (2006) Soil erosion modeling using RUSLE and GIS on the IMHA Watershed, South Korea. Doctoral Dissertation, Colorado State UniversityGoogle Scholar
  9. Kumar S, Kushwaha SPS (2013) Modelling soil erosion risk based on RUSLE-3D using GIS in a Shivalik Sub-watershed. J Earth Syst Sci 122(2):389–398. doi: 10.1007/s12040-013-0276-0 CrossRefGoogle Scholar
  10. McCool DK, Brown LC, Foster GR, Mutchler CK, Meyer LD (1987) Revised slope steepness factor for the Universal Soil Loss Equation. Trans ASAE 30(5):1387–1396CrossRefGoogle Scholar
  11. McCool DK, Foster GR, Mutchler CK, Meyer LD (1989) Revised slope length factor for the Universal Soil Loss Equation. Trans ASAE 32(5):1571–1576CrossRefGoogle Scholar
  12. Miller RW, Donahue RL (1990). Soils: an introduction to soils and plant growth, 6th edn. Prentice Hall, Englewood CliffsGoogle Scholar
  13. Pandey A, Chowdary VM, Mal BC (2007) Identification of critical erosion prone areas in the small agricultural watershed using USLE, GIS and remote sensing. Water Resour Manag 21(4):729–746. doi: 10.1007/s11269-006-9061-z CrossRefGoogle Scholar
  14. Rama Rao MSV (1962) Soil conservation in India. Indian Council of Agricultural Research, New Delhi. Retrieved from Accessed 2 January 2017
  15. Renard KG, Yoder DC, Lightle DT, Dabney SM (2011) Universal soil loss equation and revised universal soil loss equation. In: Morgan RPC, Nearing MA (eds) Handbook of erosion modeling. Blackwell Publishing Ltd., Oxford, p 137–167Google Scholar
  16. Singh G, Rambabu VV, Chandra S (1981). Soil loss prediction research in India. Bulletin of Central Soil and Water Conservation Research and Training Institute, T12/D9, DehradunGoogle Scholar
  17. Toy TJ, Foster GR, Renard KG (2002) Soil erosion: processes, prediction, measurement, and control. Wiley, New YorkGoogle Scholar
  18. Tripathi RP, Singh HP (1993) Soil erosion and conservation. New Age International Publishers, New Delhi, p 10Google Scholar
  19. Vinay M, Ramu, Mahalingam B (2015) Quantification of soil erosion by water using GIS and Remote Sensing techniques: a study of Pandavapura Taluk, Mandya District, Karnataka, India. ARPN J Earth Sci 4(2):103–110Google Scholar
  20. Wischmeier WH, Smith DD (1965). Predicting rainfall-erosion losses from cropland east of the Rocky Mountains, guide for selection of practices for soil and water conservation. Agriculture handbooks, US Government Print Office, Washington, DCGoogle Scholar
  21. Wischmeier WH, Smith DD (1978) Predicting rainfall erosion losses: a guide to conservation planning. Agriculture handbook, vol 537. US Department of Agriculture, US Government Printing Office, Washington, DCGoogle Scholar

Copyright information

© Springer International Publishing Switzerland 2017

Authors and Affiliations

  1. 1.Department of Geography and Disaster ManagementTripura UniversityAgartalaIndia
  2. 2.HowrahIndia

Personalised recommendations