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GIS based annual soil loss estimation with revised universal soil loss equation (RUSLE) in the upper Meki sub-catchment, rift valley sub-basin, Ethiopia

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  • معلومة اضافية
    • بيانات النشر:
      Taylor & Francis Group, 2024.
    • الموضوع:
      2024
    • Collection:
      LCC:Agriculture
      LCC:Food processing and manufacture
    • نبذة مختصرة :
      AbstractSoil erosion is the most challenging and major environmental problems in the Upper Meki Sub catchment. Therefore, this work aims to determine the relative influences of erosion governing factors and to estimate the annual soil loss in the sub catchment area using RUSLE model. The model variables including rainfall erosivity (R), soil erodibility (K), topography (LS), cover and management (C), and support practices (P) were implemented into the GIS environment and a layer of each of these factors was prepared. The estimated value of R, K, LS, C, and P for the sub catchment area ranges from 512 to 604 MJ mm ha-1 h-1 yr-1, 0.137 to 0.169 tons/ha, 0 to 59, 0.001 to 0.4 and 0.10 – 1.00 respectively. The raster values of all these factors were multiplied by using GIS calculator. Based on the results from GIS raster calculation and RUSLE model, the total annual potential soil loss from the sub catchment area is about 2,756,540 tons per year with a mean estimated soil loss rate of 28.12 + 34.77 t/ha/yr and the total actual annual soil loss is 492929 tons with an estimated erosion rate of 37.05 + 46.7 t/ha/yr. Rainfall is identified as the most sensitive factor of soil erosion in the sub catchment area. Our estimation of soil erosion provides notional basses that the area needs immediate action to sustain the soil. Nevertheless, further research on severity analysis and area prioritization, and sediment loss estimation in this watershed is highly recommended to develop practical way of conserving practices.
    • File Description:
      electronic resource
    • ISSN:
      23311932
      2331-1932
    • Relation:
      https://doaj.org/toc/2331-1932
    • الرقم المعرف:
      10.1080/23311932.2024.2311802
    • الرقم المعرف:
      edsdoj.00b8a7538d034845bb12841b39cfa935