Predicting runoff and sediment yields using soil and water assessment tool (SWAT) model in the Jemma Subbasin of Upper Blue Nile, Central Ethiopia

The Jemma Subbasin (JS) has a major soil erosion problem emanating from deforestation, overgrazing, and agricultural expansion, including farming of unproductive fringed lands and steep slope terrains. This study was conducted to assess runoff and estimate the subsequent sediment yields in the JS us...

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Main Authors: Negash Tamiru Zewde, Mekuria Argaw Denboba, Solomon Ayele Tadesse, Yitea Seneshaw Getahun
Format: Article
Language:English
Published: Elsevier 2024-01-01
Series:Environmental Challenges
Subjects:
Online Access:http://www.sciencedirect.com/science/article/pii/S2667010023001294
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author Negash Tamiru Zewde
Mekuria Argaw Denboba
Solomon Ayele Tadesse
Yitea Seneshaw Getahun
author_facet Negash Tamiru Zewde
Mekuria Argaw Denboba
Solomon Ayele Tadesse
Yitea Seneshaw Getahun
author_sort Negash Tamiru Zewde
collection DOAJ
description The Jemma Subbasin (JS) has a major soil erosion problem emanating from deforestation, overgrazing, and agricultural expansion, including farming of unproductive fringed lands and steep slope terrains. This study was conducted to assess runoff and estimate the subsequent sediment yields in the JS using the Soil and Water Assessment Tool (SWAT) model. The overall efficiency of the SWAT model to accurately estimate the sediment yields in the JS was evaluated by the values of its calibration (R2 = 0.66) and validation (R2 = 0.63), respectively. The findings of the SWAT model revealed that barren land was not only the most susceptible land use type to soil erosion, but also had the highest sediment loads followed by agricultural and grazing lands. In particular, the highest soil erosion coupled with significant sediment yields is attributed to the crop-growing period particularly in the months of July and August in which the cultivated lands were extremely vulnerable to soil erosion resulting from heavy rainfall. Consequently, sediment yields were all significantly greater in the agricultural fields of the lower, middle, and upper parts of the subbasin. This is because those agricultural lands were mainly composed of undulated and moderately steep slope terrains so that they had the highest soil erosion values. However, due to the dense vegetation cover and the associated root density, forestlands were the least erosion vulnerable land use type which in turn resulted in minimal soil loss. Furthermore, the SWAT model showed that the maximum upland sediment yield was estimated to be 3,685.14 tons/ha whereas the average upland annual sediment yield was predicted to be 78.1 tons/ha; however, the sediment yield can be doubled due to climate projection scenario. As a result of the effective implementation of cover (c) and conservation practice (p), the SWAT model predicted that the sediment yields can be reduced by 44.28 % and 35.92 % for RCP8.5 and RCP4.5, respectively. Effective designing and executing of proper soil and water management measures are crucial in the study subbasin so as to minimize the serious soil erosion challenges that can be accelerated by climate and land use land cover (LULC) changes for the long-term sustainability of the degraded landscape of the JS which is categorized by subsistence farming.
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spelling doaj.art-08d43a84f82f46968bb01b51d389422d2024-02-28T05:14:20ZengElsevierEnvironmental Challenges2667-01002024-01-0114100806Predicting runoff and sediment yields using soil and water assessment tool (SWAT) model in the Jemma Subbasin of Upper Blue Nile, Central EthiopiaNegash Tamiru Zewde0Mekuria Argaw Denboba1Solomon Ayele Tadesse2Yitea Seneshaw Getahun3Department of Plant Science, College of Agriculture and Natural Resource Sciences, Debre Berhan University, P. O. Box 445, Debre Berhan, EthiopiaDepartment of Environmental Science, College of Natural and Computational Sciences, Addis Ababa University, P. O. Box 1176, Addis Ababa, EthiopiaDepartment of Natural Resources Management, College of Agriculture and Natural Resource Sciences, Debre Berhan University, P. O. Box 445, Debre Berhan, Ethiopia; Corresponding author.Department of Natural Resources Management, College of Agriculture and Natural Resource Sciences, Debre Berhan University, P. O. Box 445, Debre Berhan, EthiopiaThe Jemma Subbasin (JS) has a major soil erosion problem emanating from deforestation, overgrazing, and agricultural expansion, including farming of unproductive fringed lands and steep slope terrains. This study was conducted to assess runoff and estimate the subsequent sediment yields in the JS using the Soil and Water Assessment Tool (SWAT) model. The overall efficiency of the SWAT model to accurately estimate the sediment yields in the JS was evaluated by the values of its calibration (R2 = 0.66) and validation (R2 = 0.63), respectively. The findings of the SWAT model revealed that barren land was not only the most susceptible land use type to soil erosion, but also had the highest sediment loads followed by agricultural and grazing lands. In particular, the highest soil erosion coupled with significant sediment yields is attributed to the crop-growing period particularly in the months of July and August in which the cultivated lands were extremely vulnerable to soil erosion resulting from heavy rainfall. Consequently, sediment yields were all significantly greater in the agricultural fields of the lower, middle, and upper parts of the subbasin. This is because those agricultural lands were mainly composed of undulated and moderately steep slope terrains so that they had the highest soil erosion values. However, due to the dense vegetation cover and the associated root density, forestlands were the least erosion vulnerable land use type which in turn resulted in minimal soil loss. Furthermore, the SWAT model showed that the maximum upland sediment yield was estimated to be 3,685.14 tons/ha whereas the average upland annual sediment yield was predicted to be 78.1 tons/ha; however, the sediment yield can be doubled due to climate projection scenario. As a result of the effective implementation of cover (c) and conservation practice (p), the SWAT model predicted that the sediment yields can be reduced by 44.28 % and 35.92 % for RCP8.5 and RCP4.5, respectively. Effective designing and executing of proper soil and water management measures are crucial in the study subbasin so as to minimize the serious soil erosion challenges that can be accelerated by climate and land use land cover (LULC) changes for the long-term sustainability of the degraded landscape of the JS which is categorized by subsistence farming.http://www.sciencedirect.com/science/article/pii/S2667010023001294Conservation practiceRunoffSediment yieldsSWATSubbasin management
spellingShingle Negash Tamiru Zewde
Mekuria Argaw Denboba
Solomon Ayele Tadesse
Yitea Seneshaw Getahun
Predicting runoff and sediment yields using soil and water assessment tool (SWAT) model in the Jemma Subbasin of Upper Blue Nile, Central Ethiopia
Environmental Challenges
Conservation practice
Runoff
Sediment yields
SWAT
Subbasin management
title Predicting runoff and sediment yields using soil and water assessment tool (SWAT) model in the Jemma Subbasin of Upper Blue Nile, Central Ethiopia
title_full Predicting runoff and sediment yields using soil and water assessment tool (SWAT) model in the Jemma Subbasin of Upper Blue Nile, Central Ethiopia
title_fullStr Predicting runoff and sediment yields using soil and water assessment tool (SWAT) model in the Jemma Subbasin of Upper Blue Nile, Central Ethiopia
title_full_unstemmed Predicting runoff and sediment yields using soil and water assessment tool (SWAT) model in the Jemma Subbasin of Upper Blue Nile, Central Ethiopia
title_short Predicting runoff and sediment yields using soil and water assessment tool (SWAT) model in the Jemma Subbasin of Upper Blue Nile, Central Ethiopia
title_sort predicting runoff and sediment yields using soil and water assessment tool swat model in the jemma subbasin of upper blue nile central ethiopia
topic Conservation practice
Runoff
Sediment yields
SWAT
Subbasin management
url http://www.sciencedirect.com/science/article/pii/S2667010023001294
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