Modelling of sediment yield using the soil and water assessment tool (SWAT) model: A case study of the Chanchaga Watersheds, Nigeria

Kuti, Ibrahim Abayomi; Ewemoje, Temitayo Abayomi

doi:10.1016/j.sciaf.2021.e00936

Cited by 14 publications

(8 citation statements)

References 34 publications

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“…ese sediments result in a reduction of soil productivity and reservoir capacity. e system of sediment modelling is the simulation of a watershed's response in terms of sediment yield to those influencing factors [14].…”

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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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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“…We evaluated SWAT model performance by comparing observed and simulated outputs using Nash-Sutcliffe modeling efficiency (NSE), coefficient of determination (R 2 ), and percent bias (PBIAS) [ [54] , [55] , [56] , [57] , [58] ]. The NSE ( Table 3 ) is calculated as a ratio of simulated to observed variances, ranging from − ∞ to +1.…”

Section: Methodsmentioning

confidence: 99%

Evaluation of best management practices to reduce sediment yield in the upper Gilo watershed, Baro akobo basin, Ethiopia using SWAT

Zantet oybitet,

Sambeto Bibi,

Abdulkerim Adem

2023

Heliyon

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“…The collected daily discharge data for Bilate watershed at Bilate Tena gauging station was analyzed but collected suspended sediment concentration record was few in number. Thus, the continuous time step sediment data prepared using sediment rating curve (Figure 2) and arranged as per requirement of soil and water assessment tool (SWAT) model calibration and Validation (Kuti and Ewemoje, 2021).…”

Section: Hydro-meteorological Data Collection and Analysismentioning

confidence: 99%

Simulating sediment yield by SWAT and optimizing the parameters using SUFI-2 in Bilate river of Lake Abaya in Ethiopia

Ayele

Lohani

Mirani

et al. 2022

WJE

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Purpose Prediction of sediment yield for a particular river is essential to study the river morphology, agricultural land management and the lake/reservoir sedimentation investigation. The purpose of this research was to predict sediment yield by simulating and optimizing using model analysis from Bilate River. Design/methodology/approach Continuous daily sediment produced was estimated using sediment rating curve analysis. Sediment yield was simulated with soil and water assessment tool (SWAT) and the parameters were optimized by using Sequential Uncertainty Fitting algorithm. A total of 15 years of monthly flow and sediment yield data was calibrated and validated during the course of time. Findings Results evaluated through SWAT showed that the model performance was very good. From the model output prediction, the total measured and simulated sediment yield were 5.425 million ton/year and 5.538 million ton/year, respectively. The result indicates that there were high amount of soil loss resulting into sediment yield produced from the watershed per year which needs appropriate soil and water conservation techniques. Thus, the finding of this research work can provide an effective watershed/river basin management and environmental restoration. Originality/value This paper is an original research work and all the referred sources are cited properly wherever deemed fit.

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Modelling of sediment yield using the soil and water assessment tool (SWAT) model: A case study of the Chanchaga Watersheds, Nigeria

Cited by 14 publications

References 34 publications

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

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

Evaluation of best management practices to reduce sediment yield in the upper Gilo watershed, Baro akobo basin, Ethiopia using SWAT

Simulating sediment yield by SWAT and optimizing the parameters using SUFI-2 in Bilate river of Lake Abaya in Ethiopia

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