Estimating Soil Loss Using the Revised Universal Soil Loss Equation (RUSLE): Wadi Zarqa Ma’in Watershed as a Case Study
DOI:
https://doi.org/10.35516/hum.v51i2.1484Keywords:
Erosion, Jordan, sediment yield, soil loss, soil loss equationAbstract
Objectives: The present study examines soil loss in Wadi Zarqa Ma’in watershed, which drains the Madaba Plateau in Jordan.
Methods: The study employs the Revised Universal Soil Loss Equation (RUSLE) to map potential soil loss. Remote sensing data were obtained from the USGS website, while rainfall and soil data were obtained from the Ministry of Water and Irrigation and the Ministry of Agriculture in Jordan.
Results: The results of the study reveal that potential soil loss in the upper parts of the watershed was minimal because of the relatively flat terrains, the vegetation cover, and the widespread urban landscapes. However, significant soil loss was observed along watercourses draining the watershed due to the very steep topography and the lack of vegetation cover. According to the classification scheme of soil erosion archived by the FAO, the potential soil loss prevalent in the study area is very limited. The study reveals that the average soil loss over the entire watershed is 14.4 ton/ha per year.
Conclusion: If 40% of this soil loss is transported by waterways, there will be 120-130 thousand tons of sediment, giving a sediment volume of 80-100 ×103 m3 each year. The current study could supply valuable quantitative guidelines to identify areas where terracing is needed to control soil erosion in watersheds. Furthermore, it could serve as a valuable decision support tool for land management aimed at protecting natural resources and conserving ecosystems.
Downloads
References
Abdo, H., Salloum, J. (2017). Mapping the soil loss in Marqya basin: Syria using RUSLE model in GIS and RS techniques. Environ Earth Sci, 76, 114. https://doi.org/10.1007/s12665-017-6424-0
Alka. Sahu, Triambak. Baghel, Manish. Kumar Sinha. (2017), Erosion Modeling using Rusle and GIS on Dudhawa Catchment. International Journal of Applied Environmental Sciences, 12, (6), 1147-1158.
Bensekhria, A.; Bouhata, R. (2022). Assessment and Mapping Soil Water Erosion Using RUSLE Approach and GIS Tools: Case of Oued el-Hai Watershed, Aurès West, Northeastern of Algeria. ISPRS Int. J. Geo-Inf. 2022, 11, 84. https://doi.org/10.3390/ijgi 11020084
Dickinson A, Collins R. (1998). Predicting erosion and sediment yield at the catchment scale. In: Penning de Vries FWT, Agus F, and Kerr J (Eds) Soil erosion at multiple scales, principles and methods for assessing causes and impact. CABI Publishing, Wallingford, UK in association with the International Board for Soil Research and Management, 317–342.
El-Swaify S. A., (1997). Factors Affecting Soil Erosion Hazards and Conservation Needs for Tropical Steep Lands, Soil Technology, 11(1). 3-16.
FAO (1984). Ethiopian Highland reclamation study. (EHRS). Final Report, vol 1-2 Roma.
FAO & ITPS, (2015). Status of the World’s Soil Resources (SWSR) – Technical Summary. Food and Agriculture Organization of the United Nations.
Farhan, Y., Zregat, D., Farhan, I. (2013). Spatial Estimation of Soil Erosion Risk Using RUSLE Approach, RS, and GIS Techniques: A Case Study of Kufranja Watershed, Northern Jordan. Journal of Water Resource and Protection, 5, 1247-1261.
Goudie, A. (1981). Geomorphological Techniques, George Allen &Unwin Ltd, London, 395.
Li, X. Y (2000). Soil and Water Conservation in Arid and Semi-arid Areas: The Chinese Experience Annals of Arid Zone, 39(4), 377-393.
Igwe, P.U.; Onuigbo, A.A.; Chinedu, O.C.; Ezeaku, I.I.; Muoneke, M.M (2017). Soil Erosion: A Review of Models and Applications, Int. J. Adv. Eng. Res. Sci., 4(12), 2349-2456, doi: 10.22161/ijaers.4.12.22
George, J., Suresh Kumar, S. (2017). Modelling soil erosion risk in a mountainous watershed of Mid-Himalaya by integrating RUSLE model with GIS. Eurasian Journal of Soil Science, 6 (2), 92-105.
Kaushik. Ghosal, Santasmita. Das Bhattacharya, (2020). A Review of RUSLE Model. Indian Society of Remote Sensing, 48(4), 689–707. https://doi.org/10.1007/s12524-019-01097-0.
López D. T., Aide M. T., Scatena F.N. (1998). The effect of land use on soil erosion in the Guadiana watershed in Puerto Rico. Caribbean Journal of Science, 34, 298–307.
McCool DK, Brown LC, Foster GR (1987) Revised slope steepness factor for the universal soil loss equation. Trans Am Soc Agric Eng, 30, 1387–1396.
Moore, I., Burch, G. (1986), “Basis of the Length-Slope Factor in the Universal Soil Loss Equation. Soil”. Science Society of America Journal, 50, 1294-1298.
Nguyen, K., Chen, W. (2018). Estimating sediment delivery ratio by stream slope and relief ratio, MATEC Web of Conferences 192(HY12): doi: 10.1051/matecconf/201819202040 ICEAST
Ontario Center for Soil Resource Evaluation (1993), (http://www.omafra.gov. on. ca/ english/ landuse/facts/soil_survey.htm).
Oroud, I. M (2015). Water budget assessment within a typical semiarid watershed in the Eastern Mediterranean, Environmental Process 06/2015; 3(2),1-15. DOI: 10.1007/s40710-015-0072-8.
Oroud, I. M. (2018). Global warming and its implications on meteorological and hydrological drought in the southeastern Mediterranean: Environmental Processes, DOI:10.1007/s4071-018-0301-z
Oroud, I. M. (2022). Integration of GIS and remote sensing to derive spatially continuous thermal comfort and degree days across the populated areas in Jordan. International Journal of Biometeorology, DOI: 10.1007/s00484-022-02355-6
Renard, K. G., Foster, G. R., Weesies, G. A., McCool, D., and Yoder, D., (1997). Predicting Soil Erosion by Water: A Guide to Conservation Planning with the Revised Universal Soil Loss Equation (RUSLE). Agriculture Handbook (Washington)(703).
Samanta, S., Koloa, C., Kumar K., Palsamanta, B. (2016). Estimation of potential soil erosion rate using RUSLE and E30 model. Modeling Earth Systems and Environment volume 2, Article number: 149.
Shamshad, C.S. Leow, A. Ramlah, W.M.A. Wan Hussin, S.A. Mohd. Sanusi (2008). Applications of AnnAGNPS model for soil loss estimation and nutrient loading for Malaysian conditions, International Journal of Applied Earth Observation and Geoinformation, 10 (2008) 239–252
Soil Conservation Service (SCS) (1972) National Engineering Handbook, Section 4: Hydrology. Department of Agriculture, Washington DC, 762.
Soto, M. J., Domínguez-Ferreras, A., Pérez-Mendoza, D., Sanjuán, J., and Olivares, J. (2009). Mutualism versus pathogenesis: the give-and-take in plant–bacteria interactions. Cell. Microbiol. 11, 381–388. doi: 10.1111/j.1462-5822.2009.01282.x
Wang Q, Liu J and Zhu H (2018). Genetic and Molecular Mechanisms Underlying Symbiotic Specificity in Legume-Rhizobium Interactions. Front. Plant Sci. 9, 313. doi: 10.3389/fpls.2018.0031
Wischmeier, W., Smith, D. (1965), Predicting rainfall-erosion losses from cropland east of the Rocky Mountains: Guide for selection of practices for soil and water conservation. U.S. Department of Agriculture, Agricultural Research Service, Issue 282 of Agriculture Handbook. Washington DC, USA. 47.
Wischmeier. W., Smith, D.,)1978(, Predicting rainfall erosion losses—A guide to conservation planning. Agriculture Hand-book No. 537, 3–4.
Walling, D. E. (1983). The sediment delivery problem, J. Hydrology, 65, 209-237.
Young, R. A., Onstad, C. A., Bosch, D. D. and Anderson, W. P. (1995). AGNPS: A Nonpoint Source Pollution Model. In: Computer Models of Watershed Hydrology, Chapter 26:1011-1020. Water Resources Publications, Colorado, USA.
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2024 Dirasat: Human and Social Sciences

This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
Accepted 2023-04-12
Published 2024-03-30


