The high land of Ethiopia is characterized as a region of high rates of land degradation and soil erosion, especially the Blue Nile Basin, where the eroded area is due to a significant change of land use/cover. This study aimed to estimate the sediment yield of Angar sub-basin using the Soil and Water Assessment Tool (SWAT) model interface of GIS at the outlet. The land use map of 1990, 2005, and 2018 was identified from TM, ETM+, and OLI_TIRS satellite images, and the accuracy was checked using the error matrix and Kappa statistic. The streamflow and sediment were calibrated and validated to check the model performance. The model performance has been evaluated using statistical parameters of coefficient of determination (R²) 0.75 to 0.94 for calibration & 0.77 to 0.95 for validation and Nash-Sutcliffe efficiency (NSE) 0.60 to 0.93 for calibration & 0.64 to 0.92 for validation. The annual average suspended sediment was 17.64 t/ha/yr. and the simulated annual average sediment yield was 18 t /ha/yr., 19 t/ha/yr. & 22 t/ha/yr. for land use of 1990, 2005, and 2018 respectively. The sediment severity percentage increased from land-use of 1990 to 2018 by 24.32%. due to the expansion of agricultural activities and settlement areas.
| Published in | International Journal of Energy and Power Engineering (Volume 10, Issue 4) |
| DOI | 10.11648/j.ijepe.20211004.11 |
| Page(s) | 62-74 |
| Creative Commons |
This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited. |
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Copyright © The Author(s), 2024. Published by Science Publishing Group |
Angar Sub-basin, Arc SWAT, Land Use/Cover, Sediment Yield
| [1] | Arnold, J. G. (1998). Large Area Hydrological Modeling and Assessment. Part I. Model Development J. America Water Resource ASSOC, 34: 73-89. |
| [2] | Asselman, N. (2000). Fitting and Interpretation of Sediment Curves. Journal of Hydrology, 243: 228-248. |
| [3] | Aster D. Y. and Seleshi B. A. (2009). Characterization and Atlas of the Blue Nile Basin and Its sub-basin. International Water Management Institute. |
| [4] | Bosch, J. J. (1982). Areview of Catchment Experiments to Determine the Effect of Vegetation Changes on Water Yield and Evaporation. |
| [5] | Easton Z. M., F. D. (2010). A multi-basin SWAT Analysis of Runoff and Sedimentation in Blue Nile, Ethiopia. Department of Biological and Environmental Engineering, Cornell University, Ithaca, NY 14853, USA. |
| [6] | FAO. (1998). The Soil and Terrain Database for Northeastern Africa. |
| [7] | Haptamu I. G. (2010). Watershed Sediment Yield Modeling for each Scarcer Area. |
| [8] | Hurni H. (1988). Degradation and Conservation of the Soil Resource in the Ethiopia Highlands. |
| [9] | Leopold, L. B. (1992). Fluvial processes in geomorphology. San Fransisco: W. H. Freeman and Company. |
| [10] | Neitsch, S. A. (2005). Soil and Water Assessment Tool, Theoretical Documentation: Version Temple, TX.. USDA Agricultural Research Service and Texas A & M Blackland Research Center. |
| [11] | Rawat, J. S. (2005). Monitoring Land use/cover Change Using Remote Sensing and GIS Techniques. A case of study of Hawalbagh block, Disrict Almora, Uttarakhand, India, National Authority for Remote Sensing and Space Sciences. The Egyptian Journal of Remote and space sciences, 18, 77-84. |
| [12] | USDA-SCS. (1972). National Engineering Handbook, Section 4. Washington, DC.: Hydrology. U.S. Government Priting Office. |
| [13] | Van Rompaey, A. O. (2001). Modeling Mean Annual Sediment Yield Using A Distributed Approach. Earth Surf. Proc. Landf., 26: 1221-1236. |
| [14] | Walling D. E. (1994). Measuring Sediment Yield from River Basins in Lal, Red., soil Erosion Research Methods. Soil and Water Cnservation Society, Ankeny, IA. |
| [15] | Wermer C. et al. (1986). Soil Conservation Experiments in Anjeni, Gojam Research Unit, Ethiopia. |
| [16] | Williams, J. R. (1975). Sediment yield prediction with Universal Equation using Runoff Energy factor. In present and prespective technology for predicting sediment yield and sources: Preceeding of the sediment yield workshop, USDA-Sedimentation Lab. Oxford, MS, November 28-30. |
APA Style
Miressa Bayisa, Dereje Adeba. (2021). Land Use Land Cover Dynamics on Sediment Yield Modeling of Angar Sub-Basin, Blue Nile Basin, Ethiopia. International Journal of Energy and Power Engineering, 10(4), 62-74. https://doi.org/10.11648/j.ijepe.20211004.11
ACS Style
Miressa Bayisa; Dereje Adeba. Land Use Land Cover Dynamics on Sediment Yield Modeling of Angar Sub-Basin, Blue Nile Basin, Ethiopia. Int. J. Energy Power Eng. 2021, 10(4), 62-74. doi: 10.11648/j.ijepe.20211004.11
AMA Style
Miressa Bayisa, Dereje Adeba. Land Use Land Cover Dynamics on Sediment Yield Modeling of Angar Sub-Basin, Blue Nile Basin, Ethiopia. Int J Energy Power Eng. 2021;10(4):62-74. doi: 10.11648/j.ijepe.20211004.11
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Download@article{10.11648/j.ijepe.20211004.11,
author = {Miressa Bayisa and Dereje Adeba},
title = {Land Use Land Cover Dynamics on Sediment Yield Modeling of Angar Sub-Basin, Blue Nile Basin, Ethiopia},
journal = {International Journal of Energy and Power Engineering},
volume = {10},
number = {4},
pages = {62-74},
doi = {10.11648/j.ijepe.20211004.11},
url = {https://doi.org/10.11648/j.ijepe.20211004.11},
eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ijepe.20211004.11},
abstract = {The high land of Ethiopia is characterized as a region of high rates of land degradation and soil erosion, especially the Blue Nile Basin, where the eroded area is due to a significant change of land use/cover. This study aimed to estimate the sediment yield of Angar sub-basin using the Soil and Water Assessment Tool (SWAT) model interface of GIS at the outlet. The land use map of 1990, 2005, and 2018 was identified from TM, ETM+, and OLI_TIRS satellite images, and the accuracy was checked using the error matrix and Kappa statistic. The streamflow and sediment were calibrated and validated to check the model performance. The model performance has been evaluated using statistical parameters of coefficient of determination (R²) 0.75 to 0.94 for calibration & 0.77 to 0.95 for validation and Nash-Sutcliffe efficiency (NSE) 0.60 to 0.93 for calibration & 0.64 to 0.92 for validation. The annual average suspended sediment was 17.64 t/ha/yr. and the simulated annual average sediment yield was 18 t /ha/yr., 19 t/ha/yr. & 22 t/ha/yr. for land use of 1990, 2005, and 2018 respectively. The sediment severity percentage increased from land-use of 1990 to 2018 by 24.32%. due to the expansion of agricultural activities and settlement areas.},
year = {2021}
}
TY - JOUR T1 - Land Use Land Cover Dynamics on Sediment Yield Modeling of Angar Sub-Basin, Blue Nile Basin, Ethiopia AU - Miressa Bayisa AU - Dereje Adeba Y1 - 2021/08/26 PY - 2021 N1 - https://doi.org/10.11648/j.ijepe.20211004.11 DO - 10.11648/j.ijepe.20211004.11 T2 - International Journal of Energy and Power Engineering JF - International Journal of Energy and Power Engineering JO - International Journal of Energy and Power Engineering SP - 62 EP - 74 PB - Science Publishing Group SN - 2326-960X UR - https://doi.org/10.11648/j.ijepe.20211004.11 AB - The high land of Ethiopia is characterized as a region of high rates of land degradation and soil erosion, especially the Blue Nile Basin, where the eroded area is due to a significant change of land use/cover. This study aimed to estimate the sediment yield of Angar sub-basin using the Soil and Water Assessment Tool (SWAT) model interface of GIS at the outlet. The land use map of 1990, 2005, and 2018 was identified from TM, ETM+, and OLI_TIRS satellite images, and the accuracy was checked using the error matrix and Kappa statistic. The streamflow and sediment were calibrated and validated to check the model performance. The model performance has been evaluated using statistical parameters of coefficient of determination (R²) 0.75 to 0.94 for calibration & 0.77 to 0.95 for validation and Nash-Sutcliffe efficiency (NSE) 0.60 to 0.93 for calibration & 0.64 to 0.92 for validation. The annual average suspended sediment was 17.64 t/ha/yr. and the simulated annual average sediment yield was 18 t /ha/yr., 19 t/ha/yr. & 22 t/ha/yr. for land use of 1990, 2005, and 2018 respectively. The sediment severity percentage increased from land-use of 1990 to 2018 by 24.32%. due to the expansion of agricultural activities and settlement areas. VL - 10 IS - 4 ER -
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