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Advances in Materials Science and Engineering - Volume 2016 2016, Article ID 9585962, 8 pages -

Research Article

Department of Hydrology and Water Resources Management, Faculty of Meteorology, Environment and Arid Land Agriculture, King Abdulaziz University, Jeddah 21589, Saudi Arabia

Biological Sciences Department, Faculty of Science, King Abdulaziz University, Jeddah 21589, Saudi Arabia

Botany Department, Faculty of Science, Assiut University, Assiut 71515, Egypt

Department of Botany and Microbiology, Faculty of Science, Cairo University, Giza 12613, Egypt

Received 11 October 2015; Revised 5 February 2016; Accepted 16 February 2016

Academic Editor: Jianxi Zhu

Copyright © 2016 Jarbou A. Bahrawi et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


Soil erosion is one of the major environmental problems in terms of soil degradation in Saudi Arabia. Soil erosion leads to significant on- and off-site impacts such as significant decrease in the productive capacity of the land and sedimentation. The key aspects influencing the quantity of soil erosion mainly rely on the vegetation cover, topography, soil type, and climate. This research studies the quantification of soil erosion under different levels of data availability in Wadi Yalamlam. Remote Sensing RS and Geographic Information Systems GIS techniques have been implemented for the assessment of the data, applying the Revised Universal Soil Loss Equation RUSLE for the calculation of the risk of erosion. Thirty-four soil samples were randomly selected for the calculation of the erodibility factor, based on calculating the -factor values derived from soil property surfaces after interpolating soil sampling points. Soil erosion risk map was reclassified into five erosion risk classes and 19.3% of the Wadi Yalamlam is under very severe risk 37,740 ha. GIS and RS proved to be powerful instruments for mapping soil erosion risk, providing sufficient tools for the analytical part of this research. The mapping results certified the role of RUSLE as a decision support tool.

Author: Jarbou A. Bahrawi, Mohamed Elhag, Amal Y. Aldhebiani, Hanaa K. Galal, Ahmad K. Hegazy, and Ebtisam Alghailani



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