Skip to main content

Advertisement

Log in

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

  • Published:
Journal of Mountain Science Aims and scope Submit manuscript

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.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

Explore related subjects

Discover the latest articles and news from researchers in related subjects, suggested using machine learning.

References

  • 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

    Google Scholar 

  • 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

    Google Scholar 

  • 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

    Google Scholar 

  • 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 

  • 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

    Google Scholar 

  • 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

    Google Scholar 

  • 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

    Google Scholar 

  • 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 

  • 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

    Google Scholar 

  • 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

    Google Scholar 

  • Hudson NW (1981) Soil conservation. Batsford, UK, 2nd edition.

  • 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 

  • Jah MK, Paudel RC (2010) Erosion predictions by empirical models in a mountainous watershed. Journal of Spatial Hydrology 10: 89–102.

    Google Scholar 

  • 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

    Article  Google Scholar 

  • 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 

  • 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

    Article  Google Scholar 

  • 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;2

    Article  Google Scholar 

  • 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 

  • 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

    Article  Google Scholar 

  • 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

    Google Scholar 

  • 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

    Google Scholar 

  • 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

  • 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 

  • 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

    Google Scholar 

  • 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

    Google Scholar 

  • 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

    Google Scholar 

  • 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

    Google Scholar 

  • 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

    Google Scholar 

  • 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

    Google Scholar 

  • 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

    Google Scholar 

  • 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 

  • 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.

  • 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.

  • 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 

  • 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

    Article  Google Scholar 

  • 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

    Article  Google Scholar 

  • Stone RP, Hilborn D (2000) Equation universelle des pertes en terre (USLE). Soil Erosion. Water Resources Management 16: 447–467. (In French)

    Google Scholar 

  • Touaibia B (2010) Problematic of erosion and transport of solids in Northern Algeria. Sécheresse 1: 1–6. (In french)

    Google Scholar 

  • 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

    Article  Google Scholar 

  • 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

    Google Scholar 

  • Wischmeier WH, Smith DD (1978) Predicting rainfall erosion losses — a guide to conservation planning. Agriculture handbook, USDA. 537.

  • 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

    Google Scholar 

  • 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

    Google Scholar 

  • 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

    Google Scholar 

Download references

Acknowledgement

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

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Belkacem Merzouk.

Electronic Supplementary Material

11629_2018_5325_MOESM1_ESM.pdf

Mapping of surface water erosion potential using the Revised Universal Soil Loss Equation in the Soummam watershed, Northeast Algeria

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Sahli, Y., Mokhtari, E., Merzouk, B. et al. Mapping surface water erosion potential in the Soummam watershed in Northeast Algeria with RUSLE model. J. Mt. Sci. 16, 1606–1615 (2019). https://doi.org/10.1007/s11629-018-5325-3

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11629-018-5325-3

Keywords

Profiles

  1. Elhadj Mokhtari