Arc SWAT Model Integrated with Arc GIS - Based Evaluation of Land Use /Land Cover Change on the Hydrological Response of Muga Watershed, Abbay Basin, Ethiopia

Natnael Yasab Assefa


The study has shown the integration of Arc SWAT with Arc GIS and remote sensing tool are helpful analyze and evaluate both spatial and temporal land use/cover dynamics. It has also shown that Arc SWAT is an effective tool in analyzing the impacts of land use/cover changes on stream flow in areas with limited readily available data. This study is mainly focusing on the investigation of the impacts of land use / land cover changes on the stream flow of Muga watershed which is located in the East Choke Mountains watersheds, Upper Abbay Basin, East Gojjam Zone, Amhara Regional state, Ethiopia. Soil and Water Assessment Tool (SWAT) model were used it investigate the impact of land cover change on the stream flow. For this study SWAT Simulation is used in identifying the most vulnerable sub basins to the stream flow and sediment load changes of Muga watershed. The model was calibrated and validated using historic Stream flow data. The model was calibrated using stream flow data from 1993 to1998, validated from 1999 to2002. The R2 and NSE values were used to examine model performance and the result indicates 0.81 and 0.87 to R2 and 0.80 and 0.86 to NSE during calibration and validation respectively. The result of this analysis indicated that the mean monthly stream flow for wet months had increased by 17.75m3/s while the dry season decreased by 12.76m3/s during the 1995-2013 period due to the land use and land cover change. The highest annual surface runoff was attributed by sub basin 5 whereas sub basin 6 contributes the highest ground water respectively for 1995, 2003 and 2013 land cover maps. In terms of sediment yield, sub basin 1 contributes a maximum load for the study periods.

Keywords: Arc SWAT, Arc GIS, Land Use /land cover change, Muga Watershed

DOI: 10.7176/CER/13-2-01

Publication date: April 30th 2021

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ISSN (Paper)2224-5790 ISSN (Online)2225-0514

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