Identifying investment priority areas for soil conservation in the Winike watershed, upper Omo Gibe Basin of Ethiopia

Abreham Berta Aneseyee , Eyasu Elias , Teshome Sorromessa
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Abstract

Sustainable land management is necessary for soil erosion control, vegetation recovery, and land restoration. This study was conducted to identify the soil erosion susceptibility areas in the Winike watershed, upper Omo Gibe Basin of Ethiopia. Analytic Hierarchy Process (AHP) and InVEST modeling combined with GIS were used to generate primary data on soil erosion severity. Land use types, slope, elevation, NDVI, rainfall, drainage density, and soil types were important variables analyzed for soil erosion rate determination. The result shows a significant variation in soil erosion vulnerability among sub-watersheds ranging from low to very high vulnerability. The watershed’s very highly vulnerable eastern part accounts for 108.23 km2 (9.91 %) due to lacks vegetation cover, while the less vulnerable to the western part covers 179.66 km2 (16.46 %). Analysis of the Geo-environmental parameters shows that rainfall (26 %) is the most significant influencing factor, followed by vegetation cover (i.e., land use types), explaining about 23 % of the erosion severity. Comparing soil erosion vulnerability using the AHP and InVEST SDR models was 14.01 % and 16 %, respectively, suggesting insignificant variation between the erosion vulnerability analysis models. The study emphasizes the usefulness of erosion vulnerability modeling for identifying investment priority areas based on soil erosion status for soil conservation intervention, offering a range of decision-making options for land management.
确定埃塞俄比亚上奥莫吉贝盆地Winike流域土壤保持投资优先领域
可持续的土地管理是控制水土流失、植被恢复和土地恢复的必要条件。对埃塞俄比亚Omo Gibe盆地上游Winike流域土壤侵蚀易感区进行了研究。利用层次分析法(AHP)和InVEST模型与GIS相结合,生成土壤侵蚀严重程度的原始数据。土地利用类型、坡度、高程、NDVI、降雨量、排水密度和土壤类型是确定土壤侵蚀速率的重要变量。结果表明,各流域土壤侵蚀脆弱性存在着从低到高的显著差异。流域东部由于缺乏植被覆盖,高度脆弱区面积为108.23 km2(9.91%),而西部相对脆弱区面积为179.66 km2(16.46%)。地质环境参数分析表明,降雨(26%)是最重要的影响因素,其次是植被覆盖(即土地利用类型),解释了约23%的侵蚀严重程度。AHP模型和InVEST SDR模型对土壤侵蚀脆弱性的比较分别为14.01%和16%,表明侵蚀脆弱性分析模型之间差异不显著。该研究强调了侵蚀脆弱性模型在确定土壤保持干预的投资重点区域方面的作用,为土地管理提供了一系列决策选择。
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