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GIS based soil loss assessment using RUSLE model: A case of Horo district, western Ethiopia
Land degradation in the form of soil erosion is a worldwide challenge and make environmental problem that affects crop yields, makes livelihoods difficult, and creates crises. The main objective of this study was to measure soil loss using the Revised Universal Soil Loss Equation (RUSLE) Model in Ho...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9932455/ https://www.ncbi.nlm.nih.gov/pubmed/36816241 http://dx.doi.org/10.1016/j.heliyon.2023.e13313 |
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author | Olika, Gamtesa Fikadu, Gelana Gedefa, Basha |
author_facet | Olika, Gamtesa Fikadu, Gelana Gedefa, Basha |
author_sort | Olika, Gamtesa |
collection | PubMed |
description | Land degradation in the form of soil erosion is a worldwide challenge and make environmental problem that affects crop yields, makes livelihoods difficult, and creates crises. The main objective of this study was to measure soil loss using the Revised Universal Soil Loss Equation (RUSLE) Model in Horo district, Western Ethiopia. RUSLE with a Geographical Information System (GIS) was used to quantify soil loss using rainfall, soil, a digital elevation model (DEM), and satellite image datasets as factor value inputs. Those factors are erosivity (R), erodibility (K), topography (LS), cover management (C), and conservation support practice (P) layer values that can be interactively used using weighted overlay in ArcGIS 10.8. The result shows that the maximum and minimum potential annual soil loss of the study area ranged from nil (0.01 t/ha/yr) on plain surfaces to 216.01 t/ha/yr. The average annual soil loss rate in the study area was 13.27 t ha/yr. The highest mean annual soil loss of 216.01 t/ha/yr were observed from farmland and it was the largest portion of the study area, which covered about 64243.02 ha and represented about 73.75% of the total. As a result, forest land (16383.23 ha) was the second-largest, accounting for 18.81% of the total area. Consequently, the study revealed that the farmland was more vulnerable to erosion than other land uses and land cover types. Hence, information on average annual soil loss is important for selecting appropriate conservation measures to reduce on-site soil loss and its off-site effects. Therefore, farmers and other expected bodies should have focused on soil conservation and management practices at the highest soil loss severity classes, which must get priority for conservation by stakeholders, agents, and the government. |
format | Online Article Text |
id | pubmed-9932455 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-99324552023-02-17 GIS based soil loss assessment using RUSLE model: A case of Horo district, western Ethiopia Olika, Gamtesa Fikadu, Gelana Gedefa, Basha Heliyon Research Article Land degradation in the form of soil erosion is a worldwide challenge and make environmental problem that affects crop yields, makes livelihoods difficult, and creates crises. The main objective of this study was to measure soil loss using the Revised Universal Soil Loss Equation (RUSLE) Model in Horo district, Western Ethiopia. RUSLE with a Geographical Information System (GIS) was used to quantify soil loss using rainfall, soil, a digital elevation model (DEM), and satellite image datasets as factor value inputs. Those factors are erosivity (R), erodibility (K), topography (LS), cover management (C), and conservation support practice (P) layer values that can be interactively used using weighted overlay in ArcGIS 10.8. The result shows that the maximum and minimum potential annual soil loss of the study area ranged from nil (0.01 t/ha/yr) on plain surfaces to 216.01 t/ha/yr. The average annual soil loss rate in the study area was 13.27 t ha/yr. The highest mean annual soil loss of 216.01 t/ha/yr were observed from farmland and it was the largest portion of the study area, which covered about 64243.02 ha and represented about 73.75% of the total. As a result, forest land (16383.23 ha) was the second-largest, accounting for 18.81% of the total area. Consequently, the study revealed that the farmland was more vulnerable to erosion than other land uses and land cover types. Hence, information on average annual soil loss is important for selecting appropriate conservation measures to reduce on-site soil loss and its off-site effects. Therefore, farmers and other expected bodies should have focused on soil conservation and management practices at the highest soil loss severity classes, which must get priority for conservation by stakeholders, agents, and the government. Elsevier 2023-01-31 /pmc/articles/PMC9932455/ /pubmed/36816241 http://dx.doi.org/10.1016/j.heliyon.2023.e13313 Text en © 2023 The Authors https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). |
spellingShingle | Research Article Olika, Gamtesa Fikadu, Gelana Gedefa, Basha GIS based soil loss assessment using RUSLE model: A case of Horo district, western Ethiopia |
title | GIS based soil loss assessment using RUSLE model: A case of Horo district, western Ethiopia |
title_full | GIS based soil loss assessment using RUSLE model: A case of Horo district, western Ethiopia |
title_fullStr | GIS based soil loss assessment using RUSLE model: A case of Horo district, western Ethiopia |
title_full_unstemmed | GIS based soil loss assessment using RUSLE model: A case of Horo district, western Ethiopia |
title_short | GIS based soil loss assessment using RUSLE model: A case of Horo district, western Ethiopia |
title_sort | gis based soil loss assessment using rusle model: a case of horo district, western ethiopia |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9932455/ https://www.ncbi.nlm.nih.gov/pubmed/36816241 http://dx.doi.org/10.1016/j.heliyon.2023.e13313 |
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