Soil Erosion Estimation Using Revised Universal Soil Loss Equation Integrated with Geographic Information System by Different Resolution Digital Elevation Model Data in Weyto Sub-Basin, Southern Ethiopia

Shimeles Damene, P. Satyal
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Abstract

Soil erosion is a global environmental challenge for developing countries including Ethiopia that require regular monitoring to take corrective measures. In this context, this study was focused on estimating soil erosion using the Revised Universal Soil Loss Equation (rusle) integrated with Geographical Information System (gis) technique for which it applied 30 m and 200 m resolution Digital Elevation Model (dem) data to generate slope gradient and length. Rainfall erosivity, soil erodibility, land cover/use and management factors data were obtained from existing studies and field-based assessments where the data were used to estimate the soil erosion using rusle model in ArcMap under two different dem resolution scenario. The model estimated an average of 1.38 and 1.86 million tons of annual soil loss by water using 200 and 30 meters resolution dem data, respectively, while keeping other factors constant. The erosion estimated using higher (30 m) resolution dem data was more realistic than low (200 m) resolution data , as the higher resolution dem data allowed less generalization. In high resolution dem data, the slopes generated were also more in line with ground reality. Based on the case study of Weyto sub-basin in Southern Ethiopia, we thus conclude that the gis technique and remote sensing data can be used in rusle based erosion risk prediction for large areas even at basin, sub-basin and macro watershed level. We suggest that the accuracy of the prediction can be improved by using high resolution (large scale) input data disaggregated by micro- and sub-watersheds.
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埃塞俄比亚南部Weyto子流域不同分辨率数字高程模型数据与地理信息系统集成的修正通用水土流失方程土壤侵蚀估算
土壤侵蚀是包括埃塞俄比亚在内的发展中国家面临的全球性环境挑战,需要定期监测以采取纠正措施。在此背景下,本研究的重点是利用经修订的通用土壤流失方程(rusle)和地理信息系统(gis)技术来估算土壤侵蚀,其中应用了30米和200米分辨率的数字高程模型(dem)数据来生成坡度和长度。降雨侵蚀力、土壤可蚀性、土地覆盖/利用和管理因子数据来源于已有研究和实地评估,并利用ArcMap中的rusle模型估算了两种不同dem分辨率情景下的土壤侵蚀。在保持其他因素不变的情况下,该模型分别使用200米和30米分辨率的dem数据估算年均水土流失量分别为138万吨和186万吨。使用高分辨率(30米)dem数据估算的侵蚀比低分辨率(200米)数据更真实,因为高分辨率dem数据的泛化程度较低。在高分辨率dem数据中,生成的坡度也更符合地面实际。以埃塞俄比亚南部Weyto子流域为例,分析了gis技术和遥感数据在流域、子流域和宏观流域层面上的应用前景。我们建议使用高分辨率(大尺度)的输入数据来分解微流域和次流域,可以提高预测的准确性。
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