Open Access
Issue
E3S Web Conf.
Volume 150, 2020
The Seventh International Congress “Water, Waste and Environment” (EDE7-2019)
Article Number 03014
Number of page(s) 15
Section Geosciences and Environmental Culture
DOI https://doi.org/10.1051/e3sconf/202015003014
Published online 12 February 2020
  1. ABHS, Study to update the management master plan integrates water resources in the Sebou watershed. Sebou-mission review, Kingdom of Morocco Sebou Hydraulic Basin Agency, (2005) [Google Scholar]
  2. Boufala M. El Hmaidi A. Chadli K. et al, Hydrological modeling of water and soil resources in the basin upstream of the Allal El Fassi dam (Upper Sebou watershed, Morocco). Model. Earth Syst. Environ,(2019). https://doi.org/10.1007/s40808-019-00621-yhttps://doi.org/10.1007/s40808-019-00621-yhttps://doi.org/10.1007/s40808-019-00621-yhttps://doi.org/10.1007/s40808-019-00621-y [Google Scholar]
  3. FAO, Global soil status, processes and trends. Status of the World’s Soil Resources (SWSR) Main Report of the Food and Agriculture Organization, New York, United Nations, (2015) [Google Scholar]
  4. Toumi S, Application des techniques nucléaires et de la télédétection a l’étude de l’érosion hydrique dans le bassin versant de l’Oued Mina. Thèse de Doctorat Es-Sciences, L’école nationale supérieure d’hydraulique, Algérie, 175 p,(2013) [Google Scholar]
  5. Knapp B. van Dommelen P, The Mediterranean. In Archaeology Vol II. Encyclopedia of Life Support Systems, (2005) [Google Scholar]
  6. Abbaspour KC, User manual for SWAT- CUP, SWAT calibration and uncertainty analysus programs. Swiss Federal Institute of Aquatic Science and Technology, Eawag, Duebendorf, Switzerland. 103 pp, (2011) [Google Scholar]
  7. Gitas I. Z, Douros K., Minakou C., Silleos G.N. and Karydas C.G., Multi-temporal soil erosion risk assessment in N. Chalkidiki using a modified USLE raster model. EARSel eProceedings8, (2009) [Google Scholar]
  8. Panagopoulos Y. Makropoulos C. and Mimikou M, Decision Support for Agricultural Water Management. Global Nest Journal, Special Issue on Water Resources, Hydrology and Hydraulics, Vol. 14(3), pp. 255-263, (2012) [Google Scholar]
  9. Hazan R. et Lazarevic D, Hydrologie en zone karstique au Maroc: Sebou - Beth. Pub. Annuaires Hydrol. Maroc 1962-1963 et Actes Coll. hydrol. roches fissurées. Dubrovnik 1965. publi. 1967. Ass. Int. Hydrol. Sci, UNESCO Paris 1967, pp 275-292, (1965) [Google Scholar]
  10. Neitsch SL. Arnold JG. Kiniry JR. Williams JR. and King K.W, Soil and Water Assessment Tool –Theoretical Documentation – Version 2009.Grassland, Soil and Water Research Laboratory, Agricultural Research Service and Blackland Research Center, Texas Agricultural Experiment Station, Temple, Texas, (2011) [Google Scholar]
  11. Arnold JG. Kiniry JR. Srinivasan R. Williams JR. Haney EB and Neitsch SL, Soil and Water Assessment Tool, Input/Output File Documentation,Version 2012. Texas Water Research Institute. Technical Report 439, College Station, Texas, (2012) [Google Scholar]
  12. Di Luzio M. Srinivasan R. Arnold JG. Neitsch SL, Soil and Water Assessment Tool. ArcView GIS Interface Manual: Version 2000. GSWRL Report 02-03, BRC Report 02-07. Published by Texas Water Resources Institute TR-193, College Station, TX. 346p, (2002) [Google Scholar]
  13. Baker TJ. Miller SN, Using the soil and water assessment tool (SWAT) to assess land use impact on water resources in an East African watershed. J Hydrol 486:100–111, (2013) [CrossRef] [Google Scholar]
  14. Setegn GS. Srinivasan R. Dargahi B, Hydrological modelling in the Lake Tana Basin, Ethiopia using SWAT model. Open Hydrol J 2(1), (2008) [Google Scholar]
  15. Borah DK. Bera M, Watershed-scale hydrologic and nonpoint source pollution models: Review of mathematical bases. Trans ASAE 46(6):1553, (2003) [Google Scholar]
  16. Kiros et al, Performance Evaluation of SWAT Model for Land Use and Land Cover Changes in Semi-Arid Climatic Conditions: A Review. Hydrol Current Res, 6:3 DOI: 10.4172/2157-7587.1000216, (2015) [Google Scholar]
  17. Williams JR, Chapter 25. The EPIC Model. In: Computer models of watershed hydrology. Water Resources Publications. Highlands Ranch. pp 909–1000,(1995) [Google Scholar]
  18. Abbaspour K. Yang J. Maximov I. Siber R. Bogner K. Mieleitner J. Zobrist J. Srinivasan R, Modeling hydrology and water quality in the pre-alpine/alpine Thur watershed using SWAT. J Hydrol 333:413–430, (2007) [CrossRef] [Google Scholar]
  19. Hirt C. Filmer MS. Featherstone WE, Comparison and validation of recent freely available ASTER-GDEM ver1, STRM ver4.1 and GEODATA DEM-9S ver3 digital elevation models over Australia, Australian Journal of Earth Sciences 57 (3), pp. 337-347, (2010) [CrossRef] [Google Scholar]
  20. Dile YT. Srinivasan R, Evaluation of CFSR climate data for hydrologic prediction in data-scarce watersheds: an application in the Blue Nile River Basin. J Am Water Resour Assoc 50(5):1226–1241, (2014) [Google Scholar]
  21. Fuka DR. Walter MT. MacAlister C. Degaetano AT. Steenhuis TS. Easton ZM, Using the climate forecast system reanalysis as weather input data for watershed models. Hydrol Process 28(22):5613–5623, (2013) [Google Scholar]
  22. Wischmeier WH. Smith DD, Predicting rainfall erosion losses—a guide for conservation planning. U.S. Department of Agriculture, Agriculture. Handbook 537, (1978) [Google Scholar]
  23. Renard KG. Foster GR. Weesies GA. McCool DK. Yoder DC, Predicting soil erosion by water—a guide toconservation planning with the Revised Universal Soil Loss Equation (RUSLE). United States Department of Agriculture, Agricultural Research Service (USDA-ARS) Handbook No. 703. United States Government Printing Office, Washington, DC, (1997) [Google Scholar]
  24. Benchettouh A, Spatial estimation of soil erosion risk using RUSLE/GIS techniques and practices conservation suggested for reducing soil erosion in Wadi Mina watershed (northwest, Algeria) Arab J Geosci (2017) 10:79 - DOI 10.1007/s12517-017-2875-6, (2012) [Google Scholar]
  25. Chadli K, Estimation of soil loss using RUSLE model for Sebou watershed (Morocco) Model. Earth Syst. Environ. (2016) 2:51 DOI 10.1007/s40808-016-0105-y, (2016) [Google Scholar]
  26. Corte´s THG, Caracterizacion de la erosividad de la lluvia en México utilizando meétodos multivariados. Tesis M. C. Colegio de postgraduados, Montecillos, México, (1991) [Google Scholar]
  27. Fu BJ. Zhao WW. Chen LD. Zhang QJ. Lu YH. Gulinck H. Poesen J, Assessment of soil erosion at large watershed scale using RUSLE and GIS: a case study in the loess plateau of China. Land Degrad Dev 16:73–85, (2005) [Google Scholar]
  28. Stone RP. Hilborn D, Universal soil loss equation (USLE) factsheet. Ministry of Agriculture, Food and Rural Affairs, Ontario, (2012) [Google Scholar]
  29. Wang G. Wente S. Gertner GZ. Anderson A, Improvement in mapping vegetation cover factor for the universal soil loss equation by geostatistical methods with Landsat thematic mapper images. Int J Remote Sens 23(18):3649–3667, (2002) [Google Scholar]
  30. Sinha K.C. Labi S, Transportation Decision Making: Principles of Project Evaluation and Programming, In: Chapter 13, Impacts on water resources Wiley Publications, (2007) [Google Scholar]
  31. Jones DS. Kowalski DG and Shaw R.B, Calculating Revised Universal Soil Loss Equation (RUSLE) Estimates on Department of Defense Lands: A Review of RUSLE Factors and U.S. Army Land Condition-Trend Analysis (LCTA) Data Gaps. Center for Ecological Management of Military Lands, Department of Forest Science, Colorado State University, USA, (1996) [Google Scholar]
  32. Sadiki A. Bouhlassa S. Auajjar J. Faleh A. Macaire JJ, Utilisation d’un SIG pour l’évaluation et la cartographie des risques d’érosion par l’Equation universelle des pertes en sol dans le Rif oriental (Maroc): cas du bassin versant de l’oued Boussouab. Bulletin de l’Institut Scientifique, Rabat, section Sciences de la Terre, 2004, n°26, p. 69-79, (2004) [Google Scholar]
  33. Andrade MA and al, Méthode basée sur l’homologie pour l’identification de répétitions de protéines en utilisant des estimations de signification statistique. J Mol Biol 298 (3): 521-37, (2000) [Google Scholar]
  34. Moriasi DN. Arnold JG. Van Liew MW. Bingner RL. Harmel RD. Veith TL, Model evaluation guidelines for systematic quantification of accuracy in watershed simulations, Trans. ASABE, 50(3),885-900, (2007) [CrossRef] [Google Scholar]
  35. EZ-ZAHAOUANI B, Apports du modèle MUSLE et des techniques radiométriques à l’évaluation de l’impact du projet d’aménagement du bassin versant de l’Oued Sebou sur l’envasement du barrage Allal El Fassi, Projet de Fin d’Etudes présenté pour l’obtention du diplôme d’Ingénieur en Agronomie, Institut Agronomique et Vétérinaire HASSAN II, (2015) [Google Scholar]
  36. Georgia Soil Water and Conservation Commission, Manuel for Erosion and Sediment Control in Georgia, (2000) [Google Scholar]
  37. El Garouani A. Chen H. Lewis L. Tribak A et Abahrour M, Apport de la télédétection et du SIG pour le suivi spatio-temporel de l’occupation du sol et de l’érosion nette dans le bassin versant de l’Oued Tlata (Maroc). Actes de JSIRAUF, Hanoi, 1-9, (2007) [Google Scholar]
  38. Ibrahimi S, Application du 210Pbexe comme une alternative à l’utilisation du 137Cs pour l’étude de la redistribution du sol sur des transects cultivés et non cultivés. Bassin versants El Hachef et Raouz, nord du Maroc, Thèse présentée pour l’obtention du doctorat en Sciences, Université Abdelmalek Essaadi, Tanger, Maroc, (2005) [Google Scholar]
  39. Aït Brahim L. Sossey Alaoui F. Siteril H et Tahiri M, Quantification des pertes en sols dans le bassin versant Nakhla (Rif septentrional) ». Sciences et changements planétaires/séchresse.Volume 14, Numéro 2, 101-6, Note de recherche, (2003) [Google Scholar]
  40. Karrat L. Elouadeihe K. Brehert JG. Hessane MA, Erosion et matières transportées en suspension dans le bassin versant de l’Oued Sebou en amont du barrage Allal Fassi (Moyen Atlas, Maroc), Revue Marocaine de Géomorphologie, Numéro 1, pp 47-61, (2016). [Google Scholar]

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