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Modeling Earth Systems and Environment

, Volume 4, Issue 1, pp 251–262 | Cite as

GIS-based soil loss estimation using RUSLE model: a case of Kirindi Oya river basin, Sri Lanka

  • N. C. Wijesundara
  • N. S. Abeysingha
  • D. M. S. L. B. Dissanayake
Original Article

Abstract

Soil erosion is one of the main reasons for low crop productivity. Identification of areas vulnerable to soil erosion is crucial in applying soil conservation measures especially in river basin. Kirindi Oya river basin is one of the important river basins that supply irrigation for the downstream dry zone of Sri Lanka. This study assessed the soil erosion and generated soil erosion hazard map for Kirindi Oya basin using revised universal soil loss equation (RUSLE) model in Arc GIS 10.2. Predicted soil erosion rates estimated from RUSLE model ranged from 19 to 184 t ha−1 year−1 with an average 33 t ha−1 year−1 for the entire river basin. The basin was categorized into five different erosion hazard classes, low, moderate, high, very high, and extremely high. The study revealed that majority of extremely vulnerable soil erosion areas (> 60 t ha−1 year−1) belongs to Haldummulla area in Badulla district of the basin. About 47% of the basin area in the dry zone was categorized into low erosion hazard class (< 30 t ha−1 year−1). However, these soil loss rates were above the critical soil loss rates (6.7 t ha−1 year−1) stipulated to dry zone, Sri Lanka. The results of this study may help stakeholders to implement soil conservation measures in the Kirindi Oya basin.

Keywords

Kirindi Oya Revised universal soil loss equation Soil erosion Soil erosion hazard map 

Notes

Acknowledgements

We wish to thank to the Department of Meteorology and Natural Resources Management in Sri Lanka for providing rainfall data used in this study. In addition, we wish to thank staff of the IUCN (International Union for the Conservation of Nature)—country office of Sri Lanka, for providing the land use maps for this study.

References

  1. Abeysingha NS, Jayasekara JMNS., Meegastenna TJ (2017) Stream flow trends in up and mid-stream of Kirindi Oya river basin in Sri Lanka and its linkages to rainfall. MAUSAM 68(1):99–110Google Scholar
  2. Adhami M, Sadeghi SH (2016) Sub-watershed prioritization based on sediment yield using game theory. J Hydrol 541:977–987CrossRefGoogle Scholar
  3. Amsalu T, Mengaw A (2014) GIS based soil loss estimation using RUSLE model: the case of Jabi Tehinan woreda ANRS, Ethiopia. Nat Resour 5:616–626Google Scholar
  4. Biswas SS, Pani P (2015) Estimation of soil erosion using RUSLE and GIS techniques: a case study of Barakar River basin, Jharkhand, India. Model Earth Syst Environ 1:42CrossRefGoogle Scholar
  5. Dharmasena PB (1992) Rainfall erosivity and potential erosion in the central dry zone. Trop Agric 148:111–120Google Scholar
  6. Dharmasena PB (2014) Current status of land degradation in Kandy district. Academia. https://www.academia.edu/17509154/Current_Status_of_Land_Degradation_in_Kandy_District. Accessed 13 Aug 2017
  7. El-Swaify SA, Krishnarajah P (1983) What erosion by water is and what it does. In: Carpenter RA (ed) Natural systems for development: what planners need to know. Macmillan, New York, pp 99–161Google Scholar
  8. 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 7:953–961CrossRefGoogle Scholar
  9. Gelagay HS, Minale AS (2016) Soil loss estimation using GIS and Remote sensing techniques: case of Koga watershed, Northwestern Ethiopia. Int Soil Water Conserv Res 4(2):126–136Google Scholar
  10. Gunatilake HM, Vieth GR (2000) Estimation of on-site cost of soil erosion: a comparison of replacement and productivity change methods. J Soil Water Conserv 55:197–204Google Scholar
  11. Gunawan G, Sutjiningsih D, Soeryantono H, Sulistioweni W (2013) Soil erosion estimation based on GIS and remote sensing for supporting integrated water resources conservation management. Int J Technol 2:147–156CrossRefGoogle Scholar
  12. Jayarathne KDBL., Dayawansa NDK, De Silva RP (2010) GIS based analysis of biophysical and socio-economic factors for land degradation in Kandeketiya DS division. Trop Agric Res 21(4):361–367CrossRefGoogle Scholar
  13. Joshua WD (1977) Soil erosive power of rainfall in the different climatic zones of Sri Lanka. In: Erosion and Solid Matter Transport in Inland Waters, Proceedings of Symposium Publication, No. 122. IAHSAISH, Paris, pp 51–61Google Scholar
  14. Kumar S, Gupta S (2016) Geospatial approach in mapping soil erodibility using CartoDEM—a case study in hilly watershed of lower Himalayan range. J Earth Syst Sci 125(7):1463–1472CrossRefGoogle Scholar
  15. Mapa RB, Dassanayake AR, Nayakekorale HB (2005) Soils of the intermediate zone of Sri Lanka. In: Morphology, Characterization and Classification, Special Publication No.4. Soil science society of Sri LankaGoogle Scholar
  16. Mapa RB, Somasiri S, Dassanayake AR (2010) Soils of the Dry zone of Sri Lanka. In: Morphology, Characterization and Classification, Special Publication No.7. Soil science society of Sri LankaGoogle Scholar
  17. Ministry of Agriculture (2012) Soil conservation programme. Ministry of Agriculture Battaramulla Sri Lanka. http://www.agrimin.gov.lk/web/index.php/our-services/88-soil-conservation. Accessed 27 June 2017
  18. Ministry of Environment and Renewable Energy in Sri Lanka (2014) National action programme (NAP) for combating land degradation in Sri Lanka 2015–2024. Natural Resources Management Division, Ministry of Environment and Renewable Energy, Sri Lanka. http://www.unccd.int/ActionProgrammes/Sri%20Lanka-2015-2024-eng.pdf. Accessed 12 Aug 2017
  19. Munasinghe MAK, Pushpakumara V, Bandara TMJ, Herath HMB (2001) Use of information systems for soil erosion hazard assessment of the central province of Sri Lanka. Ann Dep Agric 3:148Google Scholar
  20. Pimentel D, Harvey C, Resosudarmo P et al (1995) Environmental and economic costs of soil erosion and conservation benefits. Science 267:1117–1123CrossRefGoogle Scholar
  21. Prasannakumar V, Vijith H, Abinod S, Geetha N (2012) Estimation of soil erosion risk within a small mountainous sub-watershed in Kerala, India using revised universal soil loss equation (RUSLE) and geo-information technology. Geosci Front 3(2):209–215CrossRefGoogle Scholar
  22. Praveen R, Kumar U (2012) Integrated approach of universal soil loss equation (USLE) and geographical information system (GIS) for soil loss risk assessment in upper south Koel basin, Jharkhand. J Geogr Inf Syst 4:588–596Google Scholar
  23. Premalal (1986) Development of an erosivity map for Sri Lanka. A research report submitted for the B.Sc. degree. Department of Agricultural Engineering, University Peradeniya, Sri LankaGoogle Scholar
  24. Remortel V, Hamilton RM, Hickey R (2001) Estimating the LS factor for RUSLE through iterative slope length processing of digital elevation data. Cartography 30(1):27–35CrossRefGoogle Scholar
  25. Renard KG, Foster GR, Weesies GA, McCool DK, Yoder DC (1997) Predicting soil erosion by water: a guide to conservation planning with revised universal soil loss equation (RUSLE). United States Department of Agriculture, Washington, D.C. (Agricultural Handbook No. 703) Google Scholar
  26. Senanayake SS, Munasinghe MAK, Wickramasinghe WMADB. (2013) Use of erosion hazard assessments for regional scale crop suitability mapping in the Uva Province. Ann Sri Lanka Dep Agric 15:127–141Google Scholar
  27. Singh G, Panda RK (2017) Grid-cell based assessment of soil erosion potential for identification of critical erosion prone areas using USLE, GIS and remote sensing: a case study in the Kapgari watershed, India. Int Soil Water Conserv Res 5(3):202–211Google Scholar
  28. Udayakumara EPN, Shrestha RP, Samarakoon L, Schmidt-vogt D (2010) People’s perception and socioeconomic determinants of soil erosion: a case study of Samanalawewa watershed. Sri Lanka Int J Sediment Res 25:323–339CrossRefGoogle Scholar
  29. Wijesekara S, Samarakoon L (2002) Application of a soil erosion model in a grid-based GIS environment. Asian J Geo Inf 3(1):49–54Google Scholar
  30. Wischmeier WH, Smith DD (1978) Predicting rainfall erosion losses: a guide to conservation planning. Agricultural hand book No. 537, United States Department of Agriculture, Washington, D.C.Google Scholar
  31. Zeng C, Wang S, Bai X, Li Y, Tian Y, Li Y, Wu L, Luo G (2017) Soil erosion evolution and spatial correlation analysis in a typical karst geomorphology using RUSLE with GIS. Solid Earth 8:721–736CrossRefGoogle Scholar

Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Department of Agricultural Engineering and Soil Science, Faculty of AgricultureRajarata University of Sri LankaAnuradhapuraSri Lanka
  2. 2.Department of Environmental Management, Faculty of Social Science and HumanitiesRajarata University of Sri LankaAnuradhapuraSri Lanka

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