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  • Hindawi Limited  (2)
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  • Hindawi Limited  (2)
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  • 1
    Online Resource
    Online Resource
    Hindawi Limited ; 2016
    In:  Advances in Materials Science and Engineering Vol. 2016 ( 2016), p. 1-8
    In: Advances in Materials Science and Engineering, Hindawi Limited, Vol. 2016 ( 2016), p. 1-8
    Abstract: 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 K -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.
    Type of Medium: Online Resource
    ISSN: 1687-8434 , 1687-8442
    Language: English
    Publisher: Hindawi Limited
    Publication Date: 2016
    detail.hit.zdb_id: 2501025-6
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  • 2
    Online Resource
    Online Resource
    Hindawi Limited ; 2014
    In:  The Scientific World Journal Vol. 2014 ( 2014), p. 1-8
    In: The Scientific World Journal, Hindawi Limited, Vol. 2014 ( 2014), p. 1-8
    Abstract: The amount of water on earth is the same and only the distribution and the reallocation of water forms are altered in both time and space. To improve the rainwater harvesting a better understanding of the hydrological cycle is mandatory. Clouds are major component of the hydrological cycle; therefore, clouds distribution is the keystone of better rainwater harvesting. Remote sensing technology has shown robust capabilities in resolving challenges of water resource management in arid environments. Soil moisture content and cloud average distribution are essential remote sensing applications in extracting information of geophysical, geomorphological, and meteorological interest from satellite images. Current research study aimed to map the soil moisture content using recent Landsat 8 images and to map cloud average distribution of the corresponding area using 59 MERIS satellite imageries collected from January 2006 to October 2011. Cloud average distribution map shows specific location in the study area where it is always cloudy all the year and the site corresponding soil moisture content map came in agreement with cloud distribution. The overlay of the two previously mentioned maps over the geological map of the study area shows potential locations for better rainwater harvesting.
    Type of Medium: Online Resource
    ISSN: 2356-6140 , 1537-744X
    Language: English
    Publisher: Hindawi Limited
    Publication Date: 2014
    detail.hit.zdb_id: 2075968-X
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