Estimation of Runoff and Sediment Yield Using SWAT Model: The Case of Katar Watershed, Rift Valley Lake Basin of Ethiopia

Husen, Dulo; Abate, Brook

doi:10.11648/j.ijmea.20200806.11

Cited by 5 publications

(5 citation statements)

References 12 publications

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“…This result is consistent with the finding that the degree of erosion increases with increasing slope gradient [24]. Acceptable soil loss to maintain economic viability and high levels of production [25] is 5 to 11 t/ha/year. However, soil loss from the watershed exceeds this range, making the area susceptible to soil loss.…”

Section: A Runoff and Sediment Loss Prediction With Swat And Wepp Modelsupporting

confidence: 91%

“…The main reasons for the high runoff and sediment volumes can be attributed to land degradation, poor land cover, improper land management, and cultivation of undulating slopes without conservation. The acceptable soil loss to sustain the economy and high levels of production [25] is 5-11 t/ha/yr. However, sediment losses from these sub watersheds exceed this range; the region is susceptible to soil loss.…”

Section: B Spatial Distribution Map Of Sediment Yieldmentioning

confidence: 99%

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Comparison of SWAT and WEPP for Modeling Annual Runoff and Sediment Yield in Agewu - Mariyam Watershed, Northern Ethiopia

Worku,

Moges,

Kendie

2024

IJ-FANRES

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The Soil and Water Assessment Tool (SWAT) and the Geographic Water Erosion Prediction Project (Geo-WEPP) were applied to compare modeling of annual runoff and sediment yield in the Agewmariam watershed, eastern Amhara Region, Ethiopia. Spatial and temporal data distributions were required as inputs to run both models. Soil texture and other soil properties were measured in the field and in the laboratory, and soil maps were generated from global digital soil maps. Land use maps were created by manually digitizing Google Earth images. Watersheds were defined using watershed DEMs and gradient maps were created for each runoff event. Runoff samples were collected and analyzed for sediment concentrations in the laboratory; average annual runoff and sediment volumes were estimated using the WEPP and SWAT models. The results were satisfactory compared to the observed values, with R2 values of 0.86 and 0.91 for the SWAT and WEPP models, respectively, and NSE values of 0.54 and 0.71 for the monthly runoff. The estimated annual mean runoff and sediment yield at the watershed outlets were 65.54 mm, 146.14 mm, 43t/ha/yr and 41.7t/ha/yr for the WEPP and SWAT models, respectively. Several sub watersheds were determined to be susceptible to soil erosion and were prioritized, so more attention was given to this area to reduce runoff and soil erosion. Therefore, the SWAT and WEPP models were suitable for estimating annual runoff and sediment volumes. Sediment yields simulated from both models were high and alarming and far exceeded the allowable rate of soil loss.

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Section: A Runoff and Sediment Loss Prediction With Swat And Wepp Modelsupporting

confidence: 91%

Section: B Spatial Distribution Map Of Sediment Yieldmentioning

confidence: 99%

Comparison of SWAT and WEPP for Modeling Annual Runoff and Sediment Yield in Agewu - Mariyam Watershed, Northern Ethiopia

Worku,

Moges,

Kendie

2024

IJ-FANRES

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“…Scenario III: A Grassed Waterway. By increasing sediment trapping and lowering flow velocity, grassed waterways reduce sediment yield at the channel outlet [23]. For this study, the setup of the grassed waterway was adjusted and simulated with an average width of 3 m and an average depth of 0.141 m, which was (3/64) * GWATW and a 25% channel slope reduction (0.75 * HRU-slope).…”

Section: Scenario Ii: Filter Stripsmentioning

confidence: 99%

“…ey also used the model to estimate runoff and sediment yield in the Katar watershed, with a catchment area of 3327 km 2 , in the Rift Valley Lake basin of Ethiopia, and this resulted in successful calibration and validation [23]. is study has been initiated to estimate the sediment yields, identify the critical source area of soil erosion, and map its spatial variability using the SWAT model.…”

Section: Introductionmentioning

confidence: 99%

Prioritization of Susceptible Watershed to Sediment Yield and Evaluation of Best Management Practice: A Case Study of Awata River, Southern Ethiopia

Kefay

Abdisa

Tumsa

2022

Applied and Environmental Soil Science

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Soil erosion is currently a global problem that causes land degradation and long-lasting challenges in Ethiopia. Sediment yield is influenced by the watershed characteristics such as land cover, soil class, and slope, which are considered the drivers of soil erosion in the basin. The middle Awata watershed is highly susceptible to soil erosion due to its topographical features. This study is therefore aimed at estimating sediment yield, examining its spatial distribution, and evaluating the selected Best Management Practices (BMPs) to reduce soil erosion-prone areas at downstream. The model simulation was done by dividing the total watershed area of 1912 km2 into 37 subbasins and 294 hydrologic response units (HRUs) for 31 years (1988–2018). The model’s uncertainty evaluation was carried out on monthly basis using the Sequential Uncertainty Fitting (SUFI-2) algorithm. The performance of the model was evaluated by statistical parameters that gave R2 = 0.76, NSE = 0.75, RSR = 0.51, and PBIAS = 5.6% for calibration and R2 = 0.75, NSE = 0.74, RSR = 0.51, and PBIAS = 2.7% for validation of streamflow. Meanwhile, sediment yield in the watershed was also simulated with R2 = 0.69, NES = 0.66, RSR = 0.58, and PBIAS = 3.7% for calibration and R2 = 0.67, NES = 0.65, RSR = 0.61, and PBIAS = 5.6% for validation of sediment distribution. The simulated annual average sediment yield was 34.543 × 103 ton/year at the outlet of the middle Awata watershed. The developed spatial distribution of sediment yield identified the first twelve upstream subwatersheds as being soil erosion-prone areas. Following an evaluation of the four selected BMPs, it was determined that parallel terracing is the most recommended method for soil erosion reduction option in all critical subbasins found in the watershed.

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“…Parameters were included in the sensitivity analysis depending upon the previous study that was conducted in the Omo‐Gibe basin, near Deme (Estifanos, 2014; Feyissa, 2016; Husen & Abate, 2020), and another method to include parameters in the sensitivity analysis was to select uncertainty in parameter values definition, during the parameterization step and based on the author's observations during the calibration process. Depending upon these, 21 parameters were selected and ranked by global sensitivity analysis based on their p value and t stat in SWAT‐ CUP.…”

Section: Study Methodologymentioning

confidence: 99%

Sediment yield assessment and suggesting mitigation measures—A case study of Deme watershed, Omo‐Gibe Basin, Ethiopia

Mekuria,

Derib,

Melesse

2024

World Water Policy

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Soil erosion is a big challenge of natural resource development in Ethiopia due to the high expansion of agricultural activity and poor land‐use management. Deme watershed is one of the watersheds found in the Omo‐Gibe Basin, Ethiopia with soil erosion problems. It covers 1284.4 km2. The Soil and Water Assessment Tool (SWAT) integrated with ArcGIS was used to assess the sediment yield of the Deme watershed and develop mitigation measures for soil erosion. The purpose of this study was to assess the sediment yield and provide mitigation measures for the Deme watershed. Ground Control Point (GCP) data collection and field observation were conducted for land‐use land cover classification. The performance of the model was evaluated by coefficient of determination (R2), Nash Sutcliffe simulation efficiency (NSE), and percent bias (PBIAS). SWAT adequately reproduced the observed daily flows and sediment loads temporal evolution with R2 and NSE ≥ .7 and PBIAS < 15% both for the calibration and validation periods. The sediment‐rating curve measured an annual average suspended sediment yield of 12.79 tons per hectare per year, whereas the SWAT model predicted an annual average sediment yield of 14.35 tons per hectare per year. The spatial distribution map of sediment showed that 9 out of 17 sub‐watersheds generate a higher amount of sediment yield (15.1–45 tons/h/year) and are found to be erosion‐prone areas. For proper management of watershed terracing, filter strips, contouring, and reforestation scenarios were developed. Each scenario reduces the sediment yield by 74.29%, 58.34%, 47.78%, and 69.76%, respectively. The proper combination of these scenarios resulted in a 90% reduction in sediment yield. Policymakers and land‐use planners of different organization will benefit from this research by implementing soil and water conservation mechanisms and practices that strengthen and mitigate the natural systems of Deme watershed.

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Estimation of Runoff and Sediment Yield Using SWAT Model: The Case of Katar Watershed, Rift Valley Lake Basin of Ethiopia

Cited by 5 publications

References 12 publications

Comparison of SWAT and WEPP for Modeling Annual Runoff and Sediment Yield in Agewu - Mariyam Watershed, Northern Ethiopia

Comparison of SWAT and WEPP for Modeling Annual Runoff and Sediment Yield in Agewu - Mariyam Watershed, Northern Ethiopia

Prioritization of Susceptible Watershed to Sediment Yield and Evaluation of Best Management Practice: A Case Study of Awata River, Southern Ethiopia

Sediment yield assessment and suggesting mitigation measures—A case study of Deme watershed, Omo‐Gibe Basin, Ethiopia

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