• Title of article

    Estimation of soil erosion using SLEMSA model and OWA approach in Lorestan Province (Iran)

  • Author/Authors

    Heydarnejad, S. Department of Desert Science - Faculty of Natural Resources and Earth Sciences - University of Kashan, Iran , Ranjbar Fordoei, A. Department of Desert Science - Faculty of Natural Resources and Earth Sciences - University of Kashan, Iran , Mousavi, S.H. Department of Geography and Ecotourism - Faculty of Natural Resources and Earth Sciences - University of Kashan, Iran , Mirzaei, R. Department of Environmental Science - Faculty of Natural Resources and Earth Sciences - University of Kashan, Iran

  • Pages
    14
  • From page
    11
  • To page
    24
  • Abstract
    Identifying suitable models for estimating soil erosion is one of the most important issues facing decision makers and managers in comprehensive planning and management of soil and water. In this research, with the purpose of estimating soil erosion in Lorestan Province, the conventional SLEMSA method was jointly used with OWA (ordered weighted averaging) multi-criteria evaluation method. The results showed that in the SLEMSA model, erosion classes with very low and very high erosion rates with an area of 16334 and 167 km2, covered the largest (58.7%) and the smallest areas of the region (0.6%), respectively. In the OWA method, on average, 63.67% of the area covering 18007 km2 was located in a very low erosion class, while the very high erosion class with an area of 956.5 km2, comprised 5.85% of the study area. The results of this research showed that besides using the SLEMSA model, the OWA method introducing a decision environment with risk and uncertainties can be used to estimate erosion, and its output can lead to a relatively precise assessment of the soil erosion in a short time and at a low cost for a vast area like Lorestan Province.
  • Keywords
    Soil erosion , Erodibility , Topography , Vegetation , Ordered weight
  • Journal title
    Environmental Resources Research
  • Serial Year
    2020
  • Record number

    2524200