Advertisement

Journal of Mountain Science

, Volume 16, Issue 7, pp 1606–1615 | Cite as

Mapping surface water erosion potential in the Soummam watershed in Northeast Algeria with RUSLE model

  • Youcef Sahli
  • Elhadj Mokhtari
  • Belkacem MerzoukEmail author
  • Benoit Laignel
  • Christophe Vial
  • Khodir Madani
Article
  • 16 Downloads

Abstract

The present study aims to estimate the annual soil loss in the Soummam watershed in the northeast of Algeria, using the Revised Universal Soil Loss Equation (RUSLE), geographic information system (GIS), and remote sensing (RS). RUSLE model has been used for modelling the main factors involved in erosive phenomena. The Soummam watershed covers a surface area of 9108.45 km2 of irregular shape, northeast —southwest towards southeast. It is characterized by an altitude varying between 2 m in the northeast and 2308 m in the northwest. Results showed that the average erosivity factor (R) is 70.64 (MJ·mm)/(ha·h·year) and the maximum value reaches 140 (MJ·mm)/(ha·h·year), the average soil erodibility factor (K) is 0.016 (t·h·ha)/(MJ·ha·mm) and maximum values reach 0.0204 (t·h·ha)/(MJ·ha·mm) in the southeast regions of the watershed, the average slope length and steepness factor (LS) is 9.79 and the mean C factor is estimated to be 0.62. Thematic maps integration of different factors of RUSLE in GIS with their database, allowed with a rapid and efficient manner to highlight complexity and factors interdependence in the erosion risk analyses. The resulting map for soils losses, with an average erosion rate of 6.81 t/(ha·year) shows a low erosion (<7.41 t/(ha·year)) which covers 73.46% of the total area of the basin, and a medium erosion (7.42 to 19.77 t/(ha·year)), which represents 17.66% of the area. Areas with extreme erosion risk exceeding 32.18 t/(ha·year) cover more than 3.54% of the basin area. The results can certainly aid in implementation of soil management and conservation practices to reduce the soil erosion in the Soummam watershed.

Keywords

Soummam watershed Soil erosion Revised Universal Soil Loss Equation Remote sensing Normalized Difference Vegetation Index 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

Notes

Acknowledgement

The authors acknowledge the Personnel of the National Agency of Water Resource (NAWR — Algiers) and their respective Universities for their assistance.

Supplementary material

11629_2018_5325_MOESM1_ESM.pdf (875 kb)
Mapping of surface water erosion potential using the Revised Universal Soil Loss Equation in the Soummam watershed, Northeast Algeria

References

  1. Abu Hammad A (2011) Watershed erosion risk assessment and management utilizing revised universal soil loss equation-geographic information systems in the Mediterranean environments. Water and Environment Journal 25: 149–162.  https://doi.org/10.1111/j.1747-6593.2009.00202.x CrossRefGoogle Scholar
  2. Agapiou A. and Hadjimitsis DG (2011) Vegetation Indices and Field Spectroradiometric Measurements for Validation of Buried Architectural Remains: Verification under Area Surveyed with Geophysical Campaigns. Journal of Applied Remote Sensing 5: 1–15.  https://doi.org/10.1117/1.3645590 CrossRefGoogle Scholar
  3. Allili Ch, Laignel B, Adjeroud N, et al. (2015) Particulate Flow at the Mouth of the Soummam Watershed (Algeria). Environmental Progress & Sustainable Energy 35 (1): 204–211.  https://doi.org/10.1002/ep.12210 CrossRefGoogle Scholar
  4. Arnoldus HMJ (1980) An approximation of the rainfall factor in the Universal Soil Loss Equation. In: De Boodt M, Gabriels D (Eds.), Assessment of Erosion. Wiley, Chichester, UK 127–132.Google Scholar
  5. Belasri A and Lakhouili A (2016) Estimation of soil erosion risk using the Universal Soil Loss Equation (USLE) and Geo-Information Technology in Oued El Makhazine Watershed, Morocco. Journal of Geographic Information System 8: 98–107.  https://doi.org/10.4236/jgis.2016.81010 CrossRefGoogle Scholar
  6. Benhamiche N, Sahi L, Tahar S, et al. (2016) Spatial and temporal variability of groundwater quality of an Algerian aquifer: The case of SoummamWadi. Hydrological Sciences Journal 61: 775–792.  https://doi.org/10.1080/02626667.2014.966723 CrossRefGoogle Scholar
  7. Berghout A, Meddi M (2016) Sediment transport modelling in wadi Chemora during flood flow events. Journal of Water and Land Development 31: 23–31.  https://doi.org/10.1515/jwld-2016-0033 CrossRefGoogle Scholar
  8. De Jong SM, Brouwer LC, Riezebos HT (1998) Erosion hazard assessment in the Peyne catchment, France. Working paper DeMon-2 Project, University of Utrecht.Google Scholar
  9. Efthimiou N, Psomiadis E (2018) The Significance of Land Cover Delineation on Soil Erosion Assessment. Environmental Management 62 (2): 383–402.  https://doi.org/10.1007/s00267-018-1044-3 CrossRefGoogle Scholar
  10. Hermassi T, Cherif MA, Habaieb H (2014) Solid transport study at the Merguellil watershed, central Tunisia: case study of Ettiour and Rajela watersheds. La Houille Blanche 4: 88–96.  https://doi.org/10.1051/lhb/2014043 CrossRefGoogle Scholar
  11. Hudson NW (1981) Soil conservation. Batsford, UK, 2nd edition.Google Scholar
  12. Hyeon SK, Julien PY (2006) Soil erosion modeling using RUSLE and GIS on the IMHA watershed. Water Engineering Research 7 (1): 29–41.Google Scholar
  13. Jah MK, Paudel RC (2010) Erosion predictions by empirical models in a mountainous watershed. Journal of Spatial Hydrology 10: 89–102.Google Scholar
  14. Jiang Z, Huete AR, Chen J, et al. (2006) Analysis of NDVI and scaled difference vegetation index retrievals of vegetation fraction. Remote Sensing of Environment 101: 366–378.  https://doi.org/10.1016/j.rse.2006.01.003 CrossRefGoogle Scholar
  15. Khali Issa L, Ben Hamman Lechhab K, Raissouni A, et al. (2016) Quantitative Mapping of Soil Erosion Risk Using GIS/USLE Approach at the Kalaya Watershed (North Western Morocco). Journal of Materials and Environmental Science 7 (8): 2778–2795. (In French)Google Scholar
  16. Kinnell PIA (2001) Slope length factor for applying the USLE-M to erosion in grid cells. Soil & Tillage Research 58: 11–17.  https://doi.org/10.1016/S0167-1987(00)00179-3 CrossRefGoogle Scholar
  17. Kustas WP, Schmugge TJ, Humes KS, et al. (1993) Relationships between evaporative fraction and remotely sensed vegetation index and microwave brightness temperature for semiarid rangelands. Journal of Applied Meteorology 32: 1781–1790.  https://doi.org/10.1175/1520-0450(1993)032<1781:RBEFAR>2.0.CO;2CrossRefGoogle Scholar
  18. Mazour M, Roose E (2002) Influence de la couverture végétale sur le ruissellement et l’érosion des sols sur parcelles d’érosion dans des bassins versants du Nord-Ouest de l’Algérie. Bulletin Réseau Erosion 21: 320–330. (In French)Google Scholar
  19. McCool DK, Brown LC, Foster GR, et al. (1987) Revised slope steepness factor for the Universal Soil Loss Equation. Transactions of the American Society of Agricultural Engineers 30: 1387–1396.  https://doi.org/10.13031/2013.30576 CrossRefGoogle Scholar
  20. McCool DK, Foster GR, Mutchler CK, et al. (1989) Revised slope length factor for the universal soil loss equation. Transactions of the American Society of Agricultural Engineers 32(5): 1571–1576.  https://doi.org/10.13031/2013.31192 CrossRefGoogle Scholar
  21. Meddi M and Toumi S (2017) Spatial variability and cartography of maximum annual daily rainfall under different return periods in the North of Algeria. International Journal of Hydrology Science and Technology 7 (1): 77–102.  https://doi.org/10.1007/s11629-014-3084-3 CrossRefGoogle Scholar
  22. Milward AA, Mersy JE (1999) Adapting RULSE to model soil erosion potential in a mountainous tropical watershed. Catena (38): 109–129.  https://doi.org/10.1016/S0341-8162(99)00067-3
  23. Mokhtari EH (2017) Impact de l’érosion hydrique sur l’envasement du barrage Ghrib. Thèse de doctorat en sciences, Université Hassiba Ben Bouali, Chlef, Algérie. (In French)Google Scholar
  24. Prasannakumar V, Vijith H, Abinod S, et al. (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. Geoscience Frontiers 3 (2): 209–215.  https://doi.org/10.1016/j.gsf.2011.11.003 CrossRefGoogle Scholar
  25. Panagos P, Meusburger K, Alewell C, et al. (2012) Soil erodibility estimation using LUCAS point survey data of Europe. Environmental Modelling & Software 30: 143–145.  https://doi.org/10.1016/j.envsoft.2011.11.002 CrossRefGoogle Scholar
  26. Panagos P, Ballabio C, Borrelli P, et al. (2015a) Rainfall erosivity in Europe. Science of the Total Environment 511: 801–814.  https://doi.org/10.1016/j.scitotenv.2015.01.008 CrossRefGoogle Scholar
  27. Panagos P, Borrelli P, Meusburger K (2015b) A new European slope length and steepness factor (LS-factor) for modeling soil erosion by water. Geosciences 5: 117–126.  https://doi.org/10.3390/geosciences5020117 CrossRefGoogle Scholar
  28. Panagos P, Borrelli P, Meusburger K, et al. (2015c) Modelling the effect of support practices (P-factor) on the reduction of soil erosion by water at European scale. Environmental Science & Policy 51: 23–24.  https://doi.org/10.1016/j.envsci.2015.03.012 CrossRefGoogle Scholar
  29. Panagos P, Borrelli P, Meusburger C, et al. (2015d) Estimating the soil erosion cover-management factor at European scale. Land Use Policy 48(C): 38–50.  https://doi.org/10.1016/j.landusepol.2015.05.021 CrossRefGoogle Scholar
  30. Probst JL, and Suchet AP (1992) Fluvial suspended sediment transport and mechanical erosion in the Maghreb (North Africa). Hydrological Sciences Journal 37: 621–637.  https://doi.org/10.1080/02626669209492628 CrossRefGoogle Scholar
  31. Renard KG, Foster GR, Weesies GA, et al. (1991) RUSLE: Revised Universal Soil Loss Equation. Journal of Soil and Water Conservation 46(1): 30–33.Google Scholar
  32. Renard KG, Foster GR, Weesies GA, et al. (1997) Predicting rainfall erosion by water: A guide to conservation planning with the revised universal soil loss equation (RUSLE). Agricultural handbook, USDA. 703.Google Scholar
  33. Rouse JW, Haas RH, Schell JA, et al. (1973) Monitoring vegetation systems in the Great Plains with ERTS. In: 3rd ERTS symposium, Washington, DC. NASA SP-351.Google Scholar
  34. Sadiki A, Bouhlassa S, Auajjar J, et al. (2004) Use of GIS for the Evaluation and Mapping of Erosion Risk by the Universal Soil Loss Equation in the Eastern Rif (Morocco): case study of Boussouab watershed. Bulletin de l’Institut Scientifique, Rabat, section Sciences de la Terre 26: 69–79. (In French)Google Scholar
  35. Sepuru TK, Dube T (2018) An appraisal on the progress of remote sensing applications in soil erosion mapping and monitoring. Remote Sensing Applications: Society and Environment 9: 1–9.  https://doi.org/10.1016/j.rsase.2017.10.005 CrossRefGoogle Scholar
  36. Simonneaux V, Cheggour A, Deschamps C, et al. (2015) Land use and climate change effects on soil erosion in a semi-arid mountainous watershed (High Atlas, Morocco). Journal of Arid Environments 122: 64–75.  https://doi.org/10.1016/j.jaridenv.2015.06.002 CrossRefGoogle Scholar
  37. Stone RP, Hilborn D (2000) Equation universelle des pertes en terre (USLE). Soil Erosion. Water Resources Management 16: 447–467. (In French)Google Scholar
  38. Touaibia B (2010) Problematic of erosion and transport of solids in Northern Algeria. Sécheresse 1: 1–6. (In french)Google Scholar
  39. Toumi S, Meddi M, Mahé G, et al. (2013) Cartographie de l’érosion dans le bassin versant de l’Oued Mina en Algérie par télédétection et SIG. Hydrological Sciences Journal 58(7): 1542–1558. (In French)  https://doi.org/10.1080/02626667.2013.824088 CrossRefGoogle Scholar
  40. Turki I, Laignel B, Benhamiche N, et al. (2016) Hydrological variability of the Soummam watershed (Northeastern Algeria) and the possible links to climate fluctuations. Arabian Journal of Geosciences 9: 477.  https://doi.org/10.1007/s12517-016-2448-0 CrossRefGoogle Scholar
  41. Wischmeier WH, Smith DD (1978) Predicting rainfall erosion losses — a guide to conservation planning. Agriculture handbook, USDA. 537.Google Scholar
  42. Wynants M, Solomon H, Ndakidemi P, et al. (2018) Pinpointing areas of increased soil erosion risk following land cover change in the Lake Manyara catchment, Tanzania. International Journal of Applied Earth Observation and Geoinformation 71: 1–8.  https://doi.org/10.1016/j.jag.2018.05.008 CrossRefGoogle Scholar
  43. Xu YQ, Shao XM, Kong XB, et al. (2008) Adapting the RUSLE and GIS to model soil erosion risk in a mountains karst watershed, Guizhou Province, China. Environmental Monitoring Assessement 141: 275–286.  https://doi.org/10.1007/s10661-007-9894-9 CrossRefGoogle Scholar
  44. Zhang H, Yang Q, Li R, et al. (2013) Extension of a GIS procedure for calculating the RUSLE equation LS factor. Computers & Geosciences 52: 177–188.  https://doi.org/10.1016/j.cageo.2012.09.027 CrossRefGoogle Scholar

Copyright information

© Science Press, Institute of Mountain Hazards and Environment, CAS and Springer-Verlag GmbH Germany, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Laboratory of Biomathematics, Biophysics, Biochemistry, and Scientometry (L3BS), Faculty of TechnologyUniversity of BejaiaBejaiaAlgeria
  2. 2.Department of Hydraulics, Faculty of TechnologyUniversity of M’silaM’silaAlgeria
  3. 3.UMR CNRS 6143 Continental and Coastal Morphodynamics Laboratory (M2C)University of RouenCedex, Mont-Saint-AignanFrance
  4. 4.CNRS, SIGMA Clermont, Pascal InstituteUniversity Clermont AuvergneClermont-FerrandFrance

Personalised recommendations