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A Probabilistic Assessment of Soil Erosion Susceptibility in a Head Catchment of the Jemma Basin, Ethiopian Highlands

机译:埃塞俄比亚高地Jemma盆地头部流域土壤侵蚀易感性的概率评价

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Soil erosion represents one of the most important global issues with serious effects on agriculture and water quality, especially in developing countries, such as Ethiopia, where rapid population growth and climatic changes affect widely mountainous areas. The Meskay catchment is a head catchment of the Jemma Basin draining into the Blue Nile (Central Ethiopia) and is characterized by high relief energy. Thus, it is exposed to high degradation dynamics, especially in the lower parts of the catchment. In this study, we aim at the geomorphological assessment of soil erosion susceptibilities. First, a geomorphological map was generated based on remote sensing observations. In particular, we mapped three categories of landforms related to (i) sheet erosion, (ii) gully erosion, and (iii) badlands using a high-resolution digital elevation model (DEM). The map was validated by a detailed field survey. Subsequently, we used the three categories as dependent variables in a probabilistic modelling approach to derive the spatial distribution of the specific process susceptibilities. In this study we applied the maximum entropy model (MaxEnt). The independent variables were derived from a set of spatial attributes describing the lithology, terrain, and land cover based on remote sensing data and DEMs. As a result, we produced three separate susceptibility maps for sheet and gully erosion as well as badlands. The resulting susceptibility maps showed good to excellent prediction performance. Moreover, to explore the mutual overlap of the three susceptibility maps, we generated a combined map as a color composite where each color represents one component of water erosion. The latter map yields useful information for land-use managers and planning purposes.
机译:土壤侵蚀代表了对农业和水质的严重影响最重要的全球问题之一,特别是在埃塞俄比亚如埃塞俄比亚等发展中国家,其中人口迅速增长和气候变化影响广泛的山区。 Meskay集水区是jemma盆地排放到蓝尼罗河(中部埃塞俄比亚)的头部集水区,其特点是高浮雕能量。因此,它暴露于高降解动态,尤其是在集水器的下部。在这项研究中,我们旨在对土壤侵蚀敏感性的地貌评估。首先,基于遥感观察生成地貌图。特别是,我们使用高分辨率数字高度模型(DEM)映射了与(i)张侵蚀,(ii)沟壑侵蚀,(iii)荒漠化的三类地形。该地图通过详细的现场调查验证。随后,我们使用三类作为概率建模方法中的依赖变量来导出特定过程敏感性的空间分布。在这项研究中,我们应用了最大熵模型(MaxEnt)。独立变量源自描述基于遥感数据和DEM的岩性,地形和陆地覆盖的一组空间属性。因此,我们为薄片和沟壑侵蚀以及荒地制作了三张单独的易感性图。由此产生的易感性图显示出良好的预测性能。此外,为了探讨三个易感性图的相互重叠,我们产生了组合地图作为颜色复合材料,其中每种颜色代表水腐蚀的一个分量。后一张地图会产生用于土地使用经理和规划目的的有用信息。

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