Scientific African (Sep 2023)

Optimization of land management measures for soil erosion risk using GIS in agricultural landscape of western Hararghe highlands, Ethiopia

  • Sultan Mohammed Heyder,
  • Solomon Asfaw Beza,
  • Solomon Tekalign Demissie

Journal volume & issue
Vol. 21
p. e01853

Abstract

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Soil loss through water is one of the major environmental problems leading to land degradation worldwide. Though soil erosion is an inevitable natural phenomenon, it is possible to reverse and minimize the rate at a local level. This requires spatially unambiguous evidence on rate of soil loss so as to implement site specific land management decisions. The aim of this study was to estimate the mean annual soil loss and optimize land management measures in the Midhagdu watershed of western Hararghe highlands, Ethiopia. The study used five soil loss factors as input variables to estimate the soil loss. A thematic layer map was generated for each factor with spatial resolution of 30 m using Geographical Information System (GIS), and combined them with revised universal soil loss equation (RUSLE) model to estimate soil loss and identify erosion risky area in the watershed. According to the results, the distribution of annual soil loss varied between 0 and 179 t ha−1 yr−1, with a mean annual loss rate of 44.24 t ha−1 yr−1. The total annual soil loss in the entire watershed was 240,250 tons. Of this, 93.48% (224,593 tons) of the loss occurred in 49% (2,674 ha) of the catchment area,which was above the maximum tolerable soil loss limits. Most of the soil erosion affected areas are spatially situated in the upper and hillsides of the watershed. This is due to factors attributed to the steepness of the slope, dominance of Leptosols with shallow soil depth, coupled with absence of supporting practice in these parts of the watershed. Thus, slope length and slope steepness (LS) factor was the primary RUSLE parameters that controlled the soil loss in the studied watershed followed by soil erodibility (K) and support practice (P) factor. Hence, this study optimized land management options for future intervention based on the inherent limitation of the biophysical environment, socioeconomic and cultural conditions of the watershed community.

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