Environmental Earth Sciences

, Volume 59, Issue 2, pp 399–410 | Cite as

Soil erosion modeling of a Himalayan watershed using RS and GIS

  • Ashish Pandey
  • Abhisekh Mathur
  • S. K. Mishra
  • B. C. Mal
Original Article

Abstract

Employing the remote sensing (RS) and geographical information system (GIS), an assessment of sediment yield from Dikrong river basin of Arunachal Pradesh (India) has been presented in this paper. For prediction of soil erosion, the Morgan-Morgan and Finney (MMF) model and the universal soil loss equation (USLE) have been utilized at a spatial grid scale of 100 m × 100 m, an operational unit. The average annual soil loss from the Dikrong river basin is estimated as 75.66 and 57.06 t ha−1 year−1 using MMF and USLE models, respectively. The watershed area falling under the identified very high, severe, and very severe zones of soil erosion need immediate attention for soil conservation.

Keywords

DEM Erosion MMF GIS Remote sensing USLE 

References

  1. Baba SMJ, Yusof KW (2001) Modeling soil erosion in tropical environments using remote sensing and geographical informations systems. Hydrol Sci J 46(1):191–198Google Scholar
  2. Barrow CJ (1991) Land degradation. Cambridge University Press, CambridgeGoogle Scholar
  3. Dabral PP, Murry RL, Lollen P (2001) Erodibility status under different land uses in Dikrong river basin of Arunachal Pradesh. Indian J Soil Conserv 29(3):280–282Google Scholar
  4. Dabral PP, Baithuri N, Pandey A (2008) Soil erosion assessment in a hilly catchment of north eastern India using USLE, GIS and remote sensing. Water Resour Manag 22:1783–1798CrossRefGoogle Scholar
  5. Dhruvanarayana VV, Rambabu (1983) Estimation of soil loss in India. J Irrig Drain Eng 109(4):419–433Google Scholar
  6. Dickinson A, Collins R (1998) Predicting erosion and sediment yield at the catchment scale. Soil erosion at multiple scales. CAB Int 317–342Google Scholar
  7. Erdogan EH, Erpul G, Bayramin I (2007) Use of USLE/GIS methodology for predicting soil loss in a semiarid agricultural environment. Environ Monit Assess 131:153–161CrossRefGoogle Scholar
  8. Fistikoglu O, Harmancioglu NB (2002) Integration of GIS with USLE in assessment of soil erosion. Water Resour Manag 16:447–467CrossRefGoogle Scholar
  9. Foster GR, Mc Cool DK, Renard KG, Moldenhauer WC (1991) Conversion of the universal soil loss equation to SI Metric Units. J Soil Water Conserv 36:355–359Google Scholar
  10. Fu G, Chen S, McCool KD (2006) Modeling the impacts of no-till practice on soil erosion and sediment yield using RUSLE, SEDD and ArcView GIS. Soil Till Res 85:38–49CrossRefGoogle Scholar
  11. Ives JD, Messerli B (1989) The Himalayan dilemma: reconciling development and conservation. Routledge, LondonGoogle Scholar
  12. Jain MK, Kothyari UC (2000) Estimation of soil erosion and sediment yield using GIS. Hydrol Sci J 45(5):771–786Google Scholar
  13. Jain SK, Kumar S, Varghese J (2001) Estimation of soil loss for a Himalayan watershed using GIS technique. Water Resour Manag 15:41–54Google Scholar
  14. Jasrotia AS, Dhiman SD, Aggarwal SP (2002) Rainfall-runoff and soil erosion modeling using remote sensing and GIS technique—a case study of tons watershed. J Indian Soc Remote Sens 30(3):167–180CrossRefGoogle Scholar
  15. Jose CS, Das DC (1982) Geomorphic prediction models for sediment production rate and intensive priorities of watershed in Mayurakshi catchment. In: Proceedings of the international symposium on hydrological aspects of mountainous watershed held at school of hydrology. University of Roorke, pp 15–23Google Scholar
  16. Julien PY, Frenette M (1987) Macroscale analysis of upland erosion. Hydrol Sci J 32(3):347–358Google Scholar
  17. Julien PY, Gonzales del Tanago M (1991) Spatially varied soil erosion under different climates. Hydrol Sci J 36(6):511–524CrossRefGoogle Scholar
  18. Kirkby MJ (1976) Hydrogical slope models: the influence of climate. In: Derbyshire E (ed) Geomorphology and climate. Wiley, London, pp 247–267Google Scholar
  19. Kouli M, Soupios P, Vallianatos F (2008) Soil erosion prediction using the revised universal soil loss equation (RUSLE) in a GIS framework, Chania, Northwestern Crete, Greece. Environ Geol. doi:10.1007/s00254-008-1318-9
  20. Lewis LA, Verstraeten G, Zhu H (2005) RUSLE applied in a GIS framework: calculating the LS factor and deriving homogeneous patches for estimating soil loss. Int J Geogr Inf Sci 7:809–829CrossRefGoogle Scholar
  21. Lim KJ, Sagong M, Engel BA, Tang Z, Choi J, Kim KS (2005) GIS based sediment assessment tool. Catena 64:61–80CrossRefGoogle Scholar
  22. McCool DK, Foster GR, Mutchelor CK, Mayer LD (1987) Revised slope length factor for the universal soil loss equation. Trans ASAE 32:1387–1396Google Scholar
  23. Meyer LD, Wischmeier WH (1969) Mathematical simulation of the process of soil erosion by water. Trans Am Soc Agr Eng 12:754–758, 762Google Scholar
  24. Misra N, Satyanarayana T, Mukherjee RK (1984) Effect of topo elements on the sediment production rate from subwatersheds in upper Damodar valley. J Agr Eng (ISAE) 21(3):65–70Google Scholar
  25. Morgan RPC (1986) Soil erosion and conservation. Longman, EnglandGoogle Scholar
  26. Morgan RPC (2000) A simple approach to soil loss prediction: a revised Morgan-Morgan–Finney model. Catena 44:305–322CrossRefGoogle Scholar
  27. Morgan RPC, Morgan DDV, Finney HJ (1984) A predictive model for the assessment for the soil erosion risk. J Agr Eng Res 30:245–253CrossRefGoogle Scholar
  28. Onori F, De BonisP, Grauso S (2006) Soil erosion prediction at the basin scale using the revised universal soil loss equation (RUSLE) in a catchment of Sicily (southern Italy). Environ Geol 50:1129–1140CrossRefGoogle Scholar
  29. Onyando JO, Kisoyan P, Chemelil MC (2005) Estimation of potential soil erosion for river perkerra catchment in Kenya. Water Resour Manage 19:133–143CrossRefGoogle Scholar
  30. 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 Manage 21:729–746Google Scholar
  31. Pandey A, Dabral PP, Chowdary VM, Yadav NK (2008a) Landslide hazard zonation using remote sensing and GIS: a case study of Dikrong river basin, Arunachal Pradesh, India. Env Geol 54:1517–1529CrossRefGoogle Scholar
  32. Pandey A, Chowdary VM, Mal BC, Billib M (2008b) Runoff and sediment yield modeling from a small agricultural watershed in India using the WEPP model. J Hydrol (Elsevier) 348(3–4):305–319CrossRefGoogle Scholar
  33. Rao YP (1981) Evaluation of cropping management factor in universal soil loss equation under natural rainfall condition of Kharagpur, India. In: Proceedings of Southeast Asian regional symposium on problems of soil erosion and sedimentation. Asian Institute of Technology, Bangkok, pp 241–254Google Scholar
  34. Renschler C, Diekkruger B, Mannaerts C (1997) Regionalization in surface runoff and soil erosion risk evaluation. In: Regionalization of hydrology, vol 254. IAHS Publishers, UK, pp 233–241Google Scholar
  35. Saha AK, Gupta RP, Arora MK (2002) GIS-based landslide hazard zonation in the Bhagirathi (Ganga) Valley, Himalayas. Int J Remote Sens 23(2):357–369CrossRefGoogle Scholar
  36. Satpathy KK, Dutta KK (1999) Re-vegetation of eroded hill slopes-an experience with geo-jute in Arunachal Pradesh. Indian J Soil Conserv 27(3):227–233Google Scholar
  37. Sfeir-Younis A (1986) Soil conservation in developing countries. Western Africa Projects Department/The World Bank, Washington, DCGoogle Scholar
  38. Singh S (1999) A resources atlas of Arunachal Pradesh. Government of Arunachal pradesh, Itanagar, pp 141–143Google Scholar
  39. Singh G, Babu R, Narain P, Bhusan LS, Abrol IP (1992) Soil erosion rates in India. J Soil Water Conserv 47(1):97–99Google Scholar
  40. Thampapillai DA, Anderson JR (1994) A review of the socio-economic analysis of soil degradation problem for developed and developing countries. Rev Marketing Agr Econ 62:291–315Google Scholar
  41. Williams JR, Berndt HD (1972) Sediment yield computed with universal equation. J Hydrol Div, ASCE 98(12):2087–2098Google Scholar
  42. Williams JR, Berndt HD (1977) Sediment yield prediction based on watershed hydrology. Trans ASAE 20:1100–1104Google Scholar
  43. Wilson JP, Gallant JC (1996) EROS: a grid-based program for estimating spatially distributed erosion indices. Comp Geosci 22(7):707–712CrossRefGoogle Scholar
  44. Wischmeier WH, Smith DD (1978) Predicting rainfall erosion losses. USDA agricultural research services handbook 537. USDA, Washington, DCGoogle Scholar
  45. Wu S, Li J, Huang G (2005) An evaluation of grid size uncertainty in empirical soil loss modelling with digital elevation models. Environ Model Assess 10:33–42CrossRefGoogle Scholar
  46. Yoshino K, Ishioka Y (2005) Guidelines for soil conservation towards integrated basin management for sustainable development: a new approach based on the assessment of soil loss risk using remote sensing and GIS. Paddy Water Environ 3:235–247CrossRefGoogle Scholar

Copyright information

© Springer Verlag 2009

Authors and Affiliations

  • Ashish Pandey
    • 1
  • Abhisekh Mathur
    • 2
  • S. K. Mishra
    • 1
  • B. C. Mal
    • 2
  1. 1.Department of Water Resource Development and ManagementIIT RoorkeeRoorkeeIndia
  2. 2.Department of Agricultural and Food EngineeringIIT KharagpurKharagpurIndia

Personalised recommendations