Matches in UGent Biblio for { ?s ?p Soil survey interpretation and soil information systems help to predict potentials, limitations, problems and management needs for soils. However, high expert input, difficulty of producing a large-scale soil map and financial constraints, especially in developing countries like Ethiopia, are major problems to undertake detailed surveys and have available data for different applications. As a result, developing a soil-landscape relationship model for an area helps surveyors to extrapolate results to other areas with similar soil forming factors. The study area, Ruba Feleg catchment in Tigray, Ethiopia at 2747 - 3065 m a.s.l. comprises Precambrian meta-sediments with small patches of Meta volcanic Precambrian rock, and Ordovician Enticho Sandstone, overlaying the Precambrian rock. A geopedologic map was produced with the help of topographic maps, aerial photograph interpretation and field data. The soil data were obtained from a grid auger survey and standard profile pits. A conceptual discrete model of spatial variation was developed, which was then validated in the nearby Kuret catchment, which has similar soil forming conditions. The study showed that the different soil types within the landscape result not only from the difference in position along the catena but also from differences in lithology and land cover. In areas having Precambrian rock or Enticho Sandstone, the occurrence of different soils such as Lithic Leptosols, Leptic Cambisols and Leptic Regosols is mainly due to topographic conditions (steepness and curvature). In the area where thin colluvium of Enticho Sandstone covers the soils developed from Precambrian, complexes of Haplic Cambisols, Haplic Regosols and Skeletic Regosols are observed. In addition to this, the land cover also contributed to the formation of different soils. The verified results furthermore indicated that the soil landscape relationship modelling should strongly consider the slight variations in lithology (facies) and degree of land degradation to extrapolate the model successfully to other areas.. }
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- aggregation abstract "Soil survey interpretation and soil information systems help to predict potentials, limitations, problems and management needs for soils. However, high expert input, difficulty of producing a large-scale soil map and financial constraints, especially in developing countries like Ethiopia, are major problems to undertake detailed surveys and have available data for different applications. As a result, developing a soil-landscape relationship model for an area helps surveyors to extrapolate results to other areas with similar soil forming factors. The study area, Ruba Feleg catchment in Tigray, Ethiopia at 2747 - 3065 m a.s.l. comprises Precambrian meta-sediments with small patches of Meta volcanic Precambrian rock, and Ordovician Enticho Sandstone, overlaying the Precambrian rock. A geopedologic map was produced with the help of topographic maps, aerial photograph interpretation and field data. The soil data were obtained from a grid auger survey and standard profile pits. A conceptual discrete model of spatial variation was developed, which was then validated in the nearby Kuret catchment, which has similar soil forming conditions. The study showed that the different soil types within the landscape result not only from the difference in position along the catena but also from differences in lithology and land cover. In areas having Precambrian rock or Enticho Sandstone, the occurrence of different soils such as Lithic Leptosols, Leptic Cambisols and Leptic Regosols is mainly due to topographic conditions (steepness and curvature). In the area where thin colluvium of Enticho Sandstone covers the soils developed from Precambrian, complexes of Haplic Cambisols, Haplic Regosols and Skeletic Regosols are observed. In addition to this, the land cover also contributed to the formation of different soils. The verified results furthermore indicated that the soil landscape relationship modelling should strongly consider the slight variations in lithology (facies) and degree of land degradation to extrapolate the model successfully to other areas.".