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Quantification of Soil Losses along the Coastal Protected Areas in Kenya

Author

Listed:
  • Yves Hategekimana

    (Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100101, China
    University of Chinese Academy of Sciences, Beijing 100049, China)

  • Mona Allam

    (Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100101, China
    Environment & Climate Change Research Institute, National Water Research Center, Cairo 12613, Egypt)

  • Qingyan Meng

    (Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100101, China)

  • Yueping Nie

    (Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100101, China)

  • Elhag Mohamed

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

Abstract

Monitoring of improper soil erosion empowered by water is constantly adding more risk to the natural resource mitigation scenarios, especially in developing countries. The demographical pattern and the rate of growth, in addition to the impairments of the rainfall pattern, are consequently disposed to adverse environmental disturbances. The current research goal is to evaluate soil erosion triggered by water in the coastal area of Kenya on the district level, and also in protected areas. The Revised Universal Soil Loss Equation (RUSLE) model was exercised to estimate the soil loss in the designated study area. RUSLE input parameters were functionally realized in terms of rainfall and runoff erosivity factor (R), soil erodibility factor (K), slope length and gradient factor (LS), land cover management factor (C) and slope factor (P). The realization of RUSLE input parameters was carried out using different dataset sources, including meteorological data, soil/geology maps, the Digital Elevation Model (DEM) and processing of satellite imagery. Out of 26 districts in coastal area, eight districts were projected to have mean annual soil loss rates of >10 t·ha −1 ·y −1 : Kololenli (19.709 t·ha −1 ·y −1 ), Kubo (14.36 t·ha −1 ·y −1 ), Matuga (19.32 t·ha −1 ·y −1 ), Changamwe (26.7 t·ha −1 ·y −1 ), Kisauni (16.23 t·ha −1 ·y −1 ), Likoni (27.9 t·ha −1 ·y −1 ), Mwatate (15.9 t·ha −1 ·y −1 ) and Wundanyi (26.51 t·ha −1 ·y −1 ). Out of 34 protected areas at the coastal areas, only four were projected to have high soil loss estimation rates >10 t·ha −1 ·y −1 : Taita Hills (11.12 t·ha −1 ·y −1 ), Gonja (18.52 t·ha −1 ·y −1 ), Mailuganji (13.75.74 t·ha −1 ·y −1 ), and Shimba Hills (15.06 t·ha −1 ·y −1 ). In order to mitigate soil erosion in Kenya’s coastal areas, it is crucial to regulate the anthropogenic disturbances embedded mainly in deforestation of the timberlands, in addition to the natural deforestation process caused by the wildfires.

Suggested Citation

  • Yves Hategekimana & Mona Allam & Qingyan Meng & Yueping Nie & Elhag Mohamed, 2020. "Quantification of Soil Losses along the Coastal Protected Areas in Kenya," Land, MDPI, vol. 9(5), pages 1-16, May.
    • Handle: RePEc:gam:jlands:v:9:y:2020:i:5:p:137-:d:353169
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    References listed on IDEAS

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    Cited by:

    1. George Watene & Lijun Yu & Yueping Nie & Jianfeng Zhu & Thomas Ngigi & Jean de Dieu Nambajimana & Benson Kenduiywo, 2021. "Water Erosion Risk Assessment in the Kenya Great Rift Valley Region," Sustainability, MDPI, vol. 13(2), pages 1-31, January.
    2. Benjamin Kipkemboi Kogo & Lalit Kumar & Richard Koech, 2020. "Impact of Land Use/Cover Changes on Soil Erosion in Western Kenya," Sustainability, MDPI, vol. 12(22), pages 1-17, November.
    3. Susanta Das & Proloy Deb & Pradip Kumar Bora & Prafull Katre, 2020. "Comparison of RUSLE and MMF Soil Loss Models and Evaluation of Catchment Scale Best Management Practices for a Mountainous Watershed in India," Sustainability, MDPI, vol. 13(1), pages 1-22, December.
    4. Kamal Elbadaoui & Soukaina Mansour & Mustapha Ikirri & Kamal Abdelrahman & Tamer Abu-Alam & Mohamed Abioui, 2023. "Integrating Erosion Potential Model (EPM) and PAP/RAC Guidelines for Water Erosion Mapping and Detection of Vulnerable Areas in the Toudgha River Watershed of the Central High Atlas, Morocco," Land, MDPI, vol. 12(4), pages 1-24, April.

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