Abstract
In the western High Atlas of Morocco (WHAM), most of the mountainous regions experience important soil loss triggered by both natural and anthropogenic factors. It forms a major geohazard that impacts negatively upon agricultural production due to decreased water availability and reductions in soil fertility, which in the absence of measured datasets, the situation of soil loss will be getting worse. Hence, the relevance of using modeling techniques such as RUSLE (Revised Universal Soil Loss Equation), in quantifying and identifying areas subject to erosion. Not only this study aims at assessing soil loss in WHAM, but also it intends to study the controlling factors in different three areas throughout the WHAM, in an attempt to find the key factor(s) that controls the most soil loss in this region. The combination of the controlling factors maps with the resulting soil loss map in a GIS environment using Pearson’s correlation method, allows us to provide a matrix that computes the influence of these factors on the erosion process. Findings show that the WHAM is subject to significant amounts of erosion, this is mainly due to the topographic factor (LS), which is considered to be extremely rugged, followed by the soil conservation practices factor (P) and the vegetation cover factor (C). This study provides mandatory information for stakeholders hel** in implementing proper management planning in drylands.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
References
Arnoldus HMJ (1980) “Methodology Used to Determine the Maximum Potential Average Annual Soil Loss Due to Sheet and Rill Erosion in Morocco.” FAO Soils Bulletins (FAO).
Beasley DB, Huggins LF, Monke EJ (1980) ANSWERS: a model for watershed planning. Transactions of the ASAE 23(4):938–44
Bou-imajjane L, Belfoul MA, Elkadiri R, StokesBou-imajjane M, Latifa MA, Belfoul RE, Stokes M (2020a) Soil erosion assessment in a semi-arid environment: a case study from the Argana Corridor, Morocco. Environ Earth Sci 79(18):1–14
Bou-imajjane L, Belfoul MA (2020b) Soil loss assessment in Western High Atlas of Morocco: Beni Mohand Watershed study case. Appl Environ Soil Sci 2020:6384176. https://doi.org/10.1155/2020/6384176
Bou-imajjane L et al (2022) Adaptation of the revised universal soil loss equation (RUSLE) to soil loss modeling in a semi-arid watershed: a case study from western high Atlas, Morocco. Model Earth Syst Environ. https://doi.org/10.1007/s40808-022-01476-6
Cohen J (1988) Statistical Power Analysis for the Behavioral Sciences-Second Edition 12 Lawrence Erlbaum Associates Inc. Hillsdale, New Jersey, p 13
Dissanayake DMSLB, Morimoto T, Manjula RanagalageDissanayake DMSLB, Morimoto T, Ranagalage M (2019) Accessing the soil erosion rate based on RUSLE model for sustainable land use management: a case study of the Kotmale Watershed, Sri Lanka. Modeling Earth Syst Enviro 5(1):291–306
Elaloui A et al (2017) USLE-based assessment of soil erosion by water in the watershed upstream tessaoute (Central High Atlas, Morocco). Model Earth Syst Environ 3(3):873–85
Erencin Z, Shresta DP, BGCM IR ( 2000) “C-Factor Map** Using Remote Sensing and GIS.” Case study Lom SakLom Kao Thail Geogr Inst Justus-Liebig-Univ Giess Intern Inst Aerosp Surv Earth SciITC Enschede Netherland. https://core.ac.uk/display/56347214?utm_source=pdfutm_medium=bannerutm_campaign=pdf-decoration-v1
FAO-PNUMA-UNESCO (1980) Metodología provisional para la evaluación de la degradación de los suelos. Organización de las Naciones Unidas para el Desarrollo de la Agricultura y la Alimentación (FAO), Programa de las Naciones Unidas para el Medio Ambiente (PNUMA), Organización de las Naciones para el Medio Ambiente (UNESCO). Roma, FAO
Gayen A, Saha S, PourghasemiGayen HR, Amiya SS, Pourghasemi HR (2020) Soil erosion assessment using RUSLE model and its validation by fr probability model. Geocarto Int 35(15):1750–1768
Gayen A, Saha S (2017) Application of weights-of-evidence (WoE) and evidential belief function (EBF) Models for the delineation of soil erosion vulnerable zones: a study on pathro river Basin, Jharkhand, India. Model Earth Syst Environ 3(3):1123–39
Gayen A et al (2019) Gully erosion susceptibility assessment and management of hazard-prone areas in india using different machine learning algorithms. Sci Total Environ 668:124–38
Gourfi A, Daoudi L (2019) Effects of land use changes on soil erosion and sedimentation of dams in semi-arid regions: example of N’fis watershed in western High Atlas, Morocco. J Earth Sci Clim Change 10(513):2
Issa LK, Raissouni A, Moussadek R, El ArrimIssa A, Khali L, Raissouni A, Moussadek R, El Arrim A (2014) Map** and assessment of water erosion in the khmiss watershed (North Western Rif, Morocco). Curr Adv Environ Sci 2(4):119–130
Ketema A, Dwarakish GS (2021) Water erosion assessment methods: a review. ISH J Hydraul Eng 27(4):434–441
Knisel WG (1980) CREAMS: a field scale model for chemicals, runoff, and erosion from agricultural management systems (No. 26). Dep Agric, Sci Educ Adm
Lal R (2001) Soil degradation by erosion. Land Degrad Dev 12(6):519–39
Moreau J-D (2020) A new ichnofauna from the permian of the zat valley in the marrakech High Atlas of Morocco. J African Earth Sci 172:103973
Morgan RPC et al (1998) The European soil erosion model (EUROSEM): a dynamic approach for predicting sediment transport from fields and small catchments. Earth Surf Proc Land 23(6):527–544
Mujtar Verónica El et al (2019) Role and management of soil biodiversity for food security and nutrition; where do we stand? Global Food Secur 20:132–44
Nearing MA, Foster GR, Lane LJ, FinknerNearing SC, Mark A, Foster GR, Lane LJ, Finkner SC (1989) A Process-based soil erosion model for USDA-water erosion prediction project technology. Trans ASAE 32(5):1587–1593
Nearing MA, **e Y, Liu B, YeNearing Yu, Mark A, **e Y, Liu B, Ye Yu (2017) Natural and anthropogenic rates of soil erosion. Int Soil Water Conserv Rese 5(2):77–84
Parysow P, Wang G, Gertner G, AndersonParysow AB, Pablo GW, Gertner G, Anderson AB (2003) Spatial uncertainty analysis for map** soil erodibility based on joint sequential simulation. CATENA 53(1):65–78
Pearson K (1896) “VII. Mathematical contributions to the theory of evolution.—III. Regression, heredity, and Panmixia.” Philos Trans Royal Soc London Series, Contain Papers Math Phys cCharact 187:253–318
Pérez-Rodríguez R, Marques MJ, BienesPérez-Rodríguez R, Raquel MJ (2007) Spatial variability of the soil erodibility parameters and their relation with the soil map at subgroup level. Sci Total Environ 378(1–2):166–173
Pradeep GS, Krishnan MV, Vijith H (2015) Identification of critical soil erosion prone areas and annual average soil loss in an upland agricultural watershed of Western Ghats, using analytical hierarchy process (AHP) and RUSLE techniques. Arab J Geosci 8(6):3697–3711
Roose E (1994) Introduction à La Gestion Conservatoire de l’eau, de La Biomasse et de La Fertilité Des Sols (GCES). Organisation des Nations Unies pour l'alimentation et l'agriculture 70
Sharpley AN, WilliamsSharpley JR (1990) EPIC-Erosion/Productivity impact calculator. I: Model documentation. II: User manual. Tech Bull-US Dept Agricu 1768
Shin GJ (1999) The analysis of soil erosion analysis in watershed using GIS
Somasiri IS, Hewawasam T, Rambukkange MP (2022) Adaptation of the revised universal soil loss equation to map spatial distribution of soil erosion in tropical watersheds: A GIS/RS-based study of the upper Mahaweli River Catchment of Sri Lanka. Model Earth Syst Environ 8(2):2627–2645
Teshome As et al (2021) Soil erosion modelling using gis and revised universal soil loss equation approach: a case study of guna-tana landscape, Northern Ethiopia. Model Earth Syst Environ 7(1):125–34
Tessema YM, Tessema YM, et al. et al (2020) Soil loss estimation for conservation planning in the welmel watershed of the Genale Dawa Basin, Ethiopia. Agronomy 10(6):777
Wang G et al (2002) Spatial and Temporal prediction and uncertainty of soil loss using the revised universal soil loss equation: a case study of the rainfall-runoff erosivity r factor. Ecol Model 153(1–2):143–55
Wikipediawikipedia (2022) High Atlas. wikipedia. https://en.wikipedia.org/wiki/High_Atlas
WischmeierWH, Smith DD(1978) Predicting rainfall erosion losses: a guide to conservation planning. Dep Agric, Sci Educ Adm.
Zakerinejad R, Maerker M (2015) An integrated assessment of soil erosion dynamics with special emphasis on gully erosion in the Mazayjan Basin, Southwestern Iran. Nat Hazards 79(1):25–50
Acknowledgements
The authors acknowledge Pr. Racha Elkadiri (Assistant professor at Middle Tennessee State University, USA), for providing technical help during the research.
Funding
This work was supported by AUF “Agence Universitaire de la francophonie” as a post-doctoral mobility scholarship in Romania [grant numbers 11, 2021]. This work was supported by the National Center for Scientific and Technical Research (CNRST) Rabat, Morocco [grant numbers L 006/006, 2016].
Author information
Authors and Affiliations
Corresponding author
Ethics declarations
Conflict of interest
The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
Additional information
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
Springer Nature or its licensor holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
About this article
Cite this article
Bou-imajjane, L., Belfoul, M.A., Niacsu, L. et al. Key factor(s) triggering erosion in a semi-arid environment (Western High Atlas of Morocco). Model. Earth Syst. Environ. 9, 735–747 (2023). https://doi.org/10.1007/s40808-022-01525-0
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s40808-022-01525-0