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Identification of Spatial Patterns of Soil Erosion Based on the Combination of RUSLE and MCDA in the Ahferom District, Northern Ethiopia

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  • Gebreslassie Welu Hailemariam

    (School of Geological Engineering and Geomatics, Chang’an University, Xi’an 710054, China
    Department of Natural Resource Management, Wolaita Sodo University, Wolaita Sodo P.O. Box 138, Ethiopia)

  • Jianlin Zhao

    (School of Geological Engineering and Geomatics, Chang’an University, Xi’an 710054, China)

  • Awdenegest Moges

    (Institute of Technology, Agricultural Engineering, Hawassa University, Hawassa P.O. Box 05, Ethiopia)

Abstract

Soil erosion is a widespread concern that is indeed considered to be a significant environmental issue, and it has particularly severe consequences in less developed countries like Ethiopia. An effective watershed management procedure for establishing priority is supported by the identification of erosion-susceptible areas. Therefore, the main objective of the study was to assess soil erosion dynamics and its spatial pattern using a novel methodological framework combining the RUSLE and MCDA. The study used data on land use and cover, topography, soil, and climatic data. The analytical hierarchy process (AHP) were used to identify soil erosion-susceptible areas and the factors were weighted using a pairwise comparison matrix, and weights were combined using weighted overlay in GIS. Our results indicated that the mean annual soil loss rate was 27.10 t ha −1 yr −1 , while the total soil loss from the entire study area was 3.11 Mt. The highest soil loss was observed in bare land (30.54 t ha −1 yr −1 ) and farmland (23.65 t ha −1 yr −1 ), which were considered as the most susceptible land types to erosion. Likewise, 10.3% of the study area is very highly susceptible; 20.2% is highly susceptible, 24.2% of the area is moderately susceptible, 27.1% is low, and 18.2% has very low susceptibility. The district’s most significant erosion-susceptible areas are characterized by steep slopes that are composed of farmland and bare land. This suggests the majority of the area is susceptible to erosion, requiring interventions to reverse the alarming degradation level. The presented framework has a board application to estimate regional soil erosion and to identify spatial patterns of soil erosion.

Suggested Citation

  • Gebreslassie Welu Hailemariam & Jianlin Zhao & Awdenegest Moges, 2024. "Identification of Spatial Patterns of Soil Erosion Based on the Combination of RUSLE and MCDA in the Ahferom District, Northern Ethiopia," Land, MDPI, vol. 13(10), pages 1-19, October.
    • Handle: RePEc:gam:jlands:v:13:y:2024:i:10:p:1684-:d:1499492
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    References listed on IDEAS

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    1. Saaty, Thomas L., 1990. "How to make a decision: The analytic hierarchy process," European Journal of Operational Research, Elsevier, vol. 48(1), pages 9-26, September.
    2. Gezahegn Weldu Woldemariam & Arus Edo Harka, 2020. "Effect of Land Use and Land Cover Change on Soil Erosion in Erer Sub-Basin, Northeast Wabi Shebelle Basin, Ethiopia," Land, MDPI, vol. 9(4), pages 1-25, April.
    3. Brijesh Yadav & Lal Chand Malav & Raimundo Jiménez-Ballesta & Chiranjeev Kumawat & Abhik Patra & Abhishek Patel & Abhishek Jangir & Mahaveer Nogiya & Roshan Lal Meena & Pravash Chandra Moharana & Nirm, 2022. "Modeling and Assessment of Land Degradation Vulnerability in Arid Ecosystem of Rajasthan Using Analytical Hierarchy Process and Geospatial Techniques," Land, MDPI, vol. 12(1), pages 1-20, December.
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