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Assessing Current and Projected Land Use Land Cover Change Impacts on Soil erosion Using Revised Universal Soil Loss Equation (RUSLE) with remote sensing and GIS Technique: A case of Gojeb River Catchment, Omo Gibe Basin, Ethiopia

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dc.contributor.author Ahimed, Hamid
dc.contributor.author Temam, Dawd
dc.contributor.author Mustefa, Mahmud
dc.date.accessioned 2023-03-31T12:54:24Z
dc.date.available 2023-03-31T12:54:24Z
dc.date.issued 2023-02-23
dc.identifier.uri https://repository.ju.edu.et//handle/123456789/8091
dc.description.abstract Soil erosion is one of the major environmental and economic crisis of the glob, due to its impacts on agricultural productivity, food security and reservoir sedimentations. Now a day, Land Use Land Cover (LULC) changes are considered as one of the major factors responsible for the soil erosion propagation. Assessment of LULC change impacts on soil erosion is vital for stakeholders to plan sustainable water resource management in the future. The aim of this study is to assess LULC change impact on soil erosion condition of Gojeb River catchment using Revised Universal Soil Loss Equation (RUSLE) and Arc GIS tool. For this assessment, data such as Digital Elevation Model (DEM), soil type, rainfall and LULC data were used. To quantify annual average soil erosion of the study area six RUSLE model parameters: rainfall erosivity (R-factor), soil erodibility (K-factor), slope steepness and slope length (LS-factor), cover management (C-factor), support and conservation practice (P-factor) were used. Evaluation of LULC change impacts on soil erosion is conducted after classification of satellite image for the years 2000, 2010 and 2020 downloaded from United State Geological Survey (USGS) produced by Landsat 4-5, Thematic mapper (TM), Landsat 7, Enhanced Thematic Mapper (ETM+) imagery and Landsat 8, Operational Land Imagery Thermal Infrared Sensor (OLI-TIRS) respectively. In this study, the LULC classification of the year 2020 was checked for its classification accuracy and found to be acceptable (84.1%). The future LULC for the year 2030 was predicted using QGIS, MOLUSCE Plugin and the change of LULC between the years 2020 and 2030 and the corresponding soil erosion condition was evaluated. Based on the result, the current average annual soil loss in year 2020 is 25.3 t ha-1 yr-1 with 16.8 million tons of soil erosion. Whereas, the predicted average annual soil loss in year 2030 is 27.45 t ha-1 yr-1 which is 18.3 million tons of soil erosion for the entire study area. The result showed that the area of cultivated land is significantly increased from 26.34% in 2020 to 30.29% in 2030, dense forest was decreased from 27.69% in years 2020 to 25.04% in 2030 and open forest was decreased from 26.19% in years 2020 to 24.93% in 2030. LULC changes between the years 2020 and 2030 that is; increase in cultivated land, decrease in forestland in general it is directly related with agricultural land expansion and forest cover decline. This study result highlights the need of appropriate land use land cover management practice from stakeholders in the watershed en_US
dc.language.iso en_US en_US
dc.subject Arc GIS en_US
dc.subject LULC change en_US
dc.subject RUSLE Model en_US
dc.subject Soil erosion en_US
dc.subject QGIS MOLUSCE plugin en_US
dc.title Assessing Current and Projected Land Use Land Cover Change Impacts on Soil erosion Using Revised Universal Soil Loss Equation (RUSLE) with remote sensing and GIS Technique: A case of Gojeb River Catchment, Omo Gibe Basin, Ethiopia en_US
dc.type Thesis en_US


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