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Spatial Multiobjective Optimization of Agricultural Conservation Practices using a SWAT Model and an Evolutionary Algorithm
Published on: December 9, 2012
SWAT-based soil erosion and sediment yield modeling in the upper Gilgel Abay catchment, Blue Nile Basin, Ethiopia
Endalamaw Dessie Alebachew1, Kebede Wolka2, Mikias Biazen Molla2
1Hawassa University, Wondo Genet College of Forestry and Natural Resources, Hawassa, Ethiopia. endex2345@gmail.com.
Abstract:
Soil erosion is a critical global issue, threatening the sustainability of natural resources and agricultural productivity. Accurate information on sediment yield and soil erosion risk within watersheds is essential for developing effective management strategies. This study aimed to estimate soil loss in the Upper Gilgel Abay catchment using the Soil and Water Assessment Tool (SWAT). The observed daily sediment data were utilized for the calibration and validation of the model outputs. Calibration and validation were performed for the periods 2002-2015 and 2016-2021, respectively. Sensitivity analysis identified the most influential parameters affecting soil loss estimates. The model performance was quite satisfactory. The coefficient of determination (R2) was 0.69 for the calibration and 0.67 for the validation of sediment yield. Over the past 18 years, the Gilgel Abay catchment experienced approximately 1.5 billion tons of soil loss, with spatial analysis revealing soil loss rates of up to 53.88 t/ha/year, particularly in the upper catchment. The maximum and minimum annual sediment yields at the outlet of the catchment were 318, 233 tons, and 61,575 tons per year, respectively. On average 184,695 tons of soil leave the catchment annually. While the model provided an acceptable level of the average basin-wide soil loss, certain areas exhibited severe erosion. These findings underscore the urgent need for targeted soil conservation practices, such as terracing, reforestation, and sustainable land management, to mitigate soil degradation and enhance catchment sustainability.
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