14Dec 2017


  • Laboratory of Hydrology and Morphology, Cheikh Anta Diop University of Dakar.
  • Faculty of Arts and Social Sciences, Cheikh Anta Diop University of Dakar.
Crossref Cited-by Linking logo
  • Abstract
  • Keywords
  • References
  • Cite This Article as
  • Corresponding Author

Mapping of erosive risk is a prerequisite in an erosion control approach. It makes it possible to locate the sectors most vulnerable to erosive processes. The establishment of the erosive risk map results from the spatialization of the Revised Universal Soil Loss Equation (Rusle). This equation is combined with Geographic Information Systems (GIS) and Remote Sensing techniques to estimate and map average rates of soil loss. This study was conducted in the Diarha watershed and its sub-basins to determine their morphometric characteristics and map the main factors involved in soil erosion processes. The results showed that soil erosion risk varies according to the topographic and climatic gradients of the watershed. The Diarha catchment area covers an area of 759.3 km?. Its compactness index of 1.5 indicates an elongated shape SE-NW. The altitudes vary from 576 m in the South to 55 m in the North with an average of 315.5 m. The LS topographic factor varies from 0 to 30. Potential soil losses vary between 0 and 1873 t/ha/year depending on the sector. The assessment yielded an average of 36.4t/ha/year and a standard deviation of 105.3t/ha/year. Annual soil losses in the entire Diarha catchment area are estimated at 31.882t/year; with a specific degradation of 42t/km?/year.

  1. WISCHMEIER W.H. AND SMITH D.D. (1978). Predicting rainfall erosion losses ? a guide for conservation planning. U.S. Department of Agriculture, Agriculture Handbook, Washington
  2. FOTSING, 1993. Erosion of cultivated land and proposals for conservatory soil management in Bamileke country (West Cameroon), House of Remote Sensing, ORSTOM Laboratory 500, rue J. F. Breton 34093 MontpellierFrance,http://horizon.documentation.ird.fr/exl-doc/pleins_textes/cahiers/PTP/10009100.PDF
  3. IBRAHIMA THIAW. Rainfall Variability and Water Supplies in the Diarha Watershed (Tributary of Gambia River). Vol.5.No. 4, 2017, pp. 41-57. doi:10.11648/j.hyd.20170504.11
  4. JAH, M.K. AND R.C. PAUDEL, 2010, ??Erosion Predictions by Empirical Models in a Mountainous Watershed??,?Journal of Spatial Hydrology, vol.?10, n??.1, 14?p.
  5. ARNOLD, J.G., J.R. WILLIAMS, R. SRINIVASAN, K.W. KING ET R.H. GIGGS, 1995, SWAT Soil and Water assessment Tool : draft user manual, US department of Agriculture, Agriculture Service, Temple, TX.
  6. ROOSE, E., 1967. 10 years of measuring erosion and runoff in Senegal, Tropical Agronomy, Extract No 2 February 1967-ORSTOM
  7. RENARD K. G., G. R. FOSTER, G. A. WEESIES, D. K. MCCOOL AND D. C. YODER (1997). Predicting Soil Erosion by Water: A Guide to Conservation Planning with the Revised Universal Soil Loss Equation (RUSLE), Agricultural Handbook No. 703, US Department of Agriculture, Washington DC.
  8. ROOSE, E., 1994. Introduction to the conservative management of water, biomass and soil fertility, FAO Soil Bulletin,70p. http://horizon.documentation.ird.fr/exl-doc/pleins_textes/divers11-03/41504.pdf
  9. MCCOOL D, BROWN L, FOSTER G, MUTCHLER C AND MEYER L (1987). ? Revised Slope steepness factor for the Universal Soil Loss Equation??. Trans. Am.Soc. Ag. Eng. 30 p. 1387-1396.
  10. HUDSON, N.W., 1973,?Soil conservation, Batsford, London, 320?p.
  11. MATI, B.M., R.P.C. MORGAN, F.N. GICHUKI, J.N. QUINTON, T.R. BREWER ET H.P. LINIGER, 2000, ??Assessment of erosion hazard with the USLE and GIS? : A case study of the Upper EwasoNg?iro North basin of Kenya?? International Journal of Applied Earth Observation and Geoinformation?, vol.?2, n??.2, pp.?78-86.
  12. RENARD K.G AND G.R FOSTER 1983. Soil Conservation: Principles of erosion by water. In H.E Dregne and W.O Willis, eds. Dryland Agriculture pp. 155-176. Agronomy Monogr. 23, Am. Soc. Agron., Crop Sci. Soc. Am., and Soil sci. Soc. Am. Madison, Wisconsin.
  13. FAO/IIASA/ISRIC/ISS-CAS/JRC, 2009. Harmonized World Soil Database (version 1.1). FAO, Rome, Italy and IIASA, Laxenburg, Austria.
  14. BROWN, R.B., 2003,?Soil Texture, Soil and Water Science Department, Florida Cooperative Extension Service, Institute of Food and Agricultural Sciences, University of Florida, Fact Sheet SL29, 8?p.
  15. STONE, R.P. ET D. HILLBORN, 2000, Universal Soil Loss Equation, Ontario, Canada, Ontario Ministry of Agriculture and Food (OMAFRA), ?http://www.giser.be/wp-content/uploads/2012/05/USLE-infosCanada.pdf.
  16. EL GAROUANI, A., H. CHEN, L. LEWIS, A. TRIBACK ET M. ABAHROUR, 2008, \\\\\\\"Mapping of land use and net erosion from satellite images and IDRISI GIS in North-East Morocco\\\\\\\", Remote sensing,vol.?8, n??3,p.?193201,http://www.teledetection.net/upload/TELEDETECTION/pdf/Vol8No3_193_201.pdf
  17. ARNOLDUS H.M. 1980. An approximation of the rainfall factor in the Universal Soil Loss Equation. In Assessments of Erosion, de Boodts M, Gabriels D (Eds). John Wiley and Sons Ltd, Chichester 127?132
  18. OLIVEIRA JR, R.C., MEDINA, B.F. 1990. The erosivity of rainfall in Manaus (AM). Rev. Bras. Solo 14, 235?239
  19. RENARD, K. G. AND FREIMUND, J. R. 1994.Using Monthly Precipitation Data to Estimate the R factor in the Revised USLE. Hydrol. 157: 287?306.
  20. ROOSE, E., 1977, ??Application of the Universal Soil Loss Equation of Wischmeier and Smith in West Africa??,?Soil Conservation Society of America,Ankeny, Iowa, pp.?50-71,http://horizon.documentation.ird.fr/exl-doc/pleins_textes/pleins_textes_5/b_fdi_08-09/09135.pdf
  21. FICK, S.E AND R.J. HIJMANS, 2017. Wordclim 2: New 1 km spatial resolution climate surfaces for global land areas. International Journal of Climatology.
  22. SCHONBRODT, S.; SAUMER, P.; BEHRENS, T.; SEEBER, C.; SCHOLTEN, T., 2010. Assessing the USLE crop and management factor C for soil erosion modeling in a large, mountainous watershed in Central China. Journal of Earth Science, v.21, p.835-845, 2010. DOI: 10.1007/s12583-010-0135-8.
  23. DURIGON, V.L.; CARVALHO, D.F.; ANTUNES, M.A.H.; OLIVEIRA, P.T.S.; FERNANDES, M.M, 2014. NDVI time series for monitoring RUSLE cover management factor in a tropical watershed. International Journal of Remote Sensing, v.35, p.441-453.DOI: 10.1080/01431161.2013.871081.
  24. CARVALHO D.F, DURIGON V. L, ANTUNES M.A.H, ALMEIDA W.S, AND OLIVEIRA P.T.S. Predicting soil erosion using Rusle and NDVI time series from TM Landsat 5; Pesq. agropec. bras., Bras?lia, v.49, n.3, p.215-224,mar.2014;DOI:10.1590/S0100-204X2014000300008
  25. GANASRI, B.P., RAMESH, H., Assessment of soil erosion by RUSLE model using remote sensing and GIS - A case study of Nethravathi Basin, Geoscience Frontiers (2015), http://dx.doi.org/10.1016/j.gsf.2015.10.007
  26. MORSCHEL J. AND FOX D. A method of mapping erosive risk: Application to the hills of Terrefort Lauragais.M@ppemonde76(2004,4)http://mappemonde.mgm.fr/num4/articles/art04404.html
  27. LERIQUE J., 1975. Solid suspended transports in the Gambia at Kedougou and Gouloumbou stations. Results of the 1974 campaign. ORSTOM report, Dakar, multigr., 11p
  28. BAMBA S. B., 1987. Assessment of water and matter in the Upper Guinean Basin of the Gambia River. UCAD doctoral thesis.http://horizon.documentation.ird.fr/exl-doc/pleins_textes/divers16-09/24301.pdf

[Ibrahima Thiaw, Honore Dacosta, Anastasie Mendy and Amadou Abdoul Sow. (2017); TOPOGRAPHIC CHARACTERIZATION AND MAPPING OF SOIL EROSION IN THE DIARHA WATERSHED USING RUSLE, RS AND GIS. Int. J. of Adv. Res. 5 (12). 657-675] (ISSN 2320-5407). www.journalijar.com

Laboratory of Hydrology and Morphology, Cheikh Anta Diop University of Dakar


Article DOI: 10.21474/IJAR01/6005       DOI URL: http://dx.doi.org/10.21474/IJAR01/6005

Share this article