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Watershed prioritization of Kailali district through morphometric parameters and landuse/landcover datasets using GIS
Watershed prioritization is considered an important tool for soil and watershed management. This study focuses on the watershed prioritization of the Kailali district in terms of soil erosion, considering morphometric parameters and land use/landcover (LULC) datasets using GIS. ALOS DEM of 30 m reso...
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/PMC10238735/ https://www.ncbi.nlm.nih.gov/pubmed/37274710 http://dx.doi.org/10.1016/j.heliyon.2023.e16489 |
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author | Ojha, Susil Puri, Lila Bist, Suraj Prasad Bastola, Arjun Prasad Acharya, Bishwabandhu |
author_facet | Ojha, Susil Puri, Lila Bist, Suraj Prasad Bastola, Arjun Prasad Acharya, Bishwabandhu |
author_sort | Ojha, Susil |
collection | PubMed |
description | Watershed prioritization is considered an important tool for soil and watershed management. This study focuses on the watershed prioritization of the Kailali district in terms of soil erosion, considering morphometric parameters and land use/landcover (LULC) datasets using GIS. ALOS DEM of 30 m resolution was used to delineate sub-watersheds and calculate linear, areal, and relief morphometric parameters. Similarly, Esri LULC 2021 (Sentinel-2 imagery at 10 m resolution) was used to calculate LULC parameters. An integrated approach of Principal Component Analysis (PCA) and Weighted Sum Analysis (WSA) was used for prioritization. PCA was used to reduce selected parameters, calculate the correlation matrix, and define the significant parameters. WSA was used to define weightage value, and Compound Value (CV) was calculated for the ranking of sub-watersheds. 22 sub-watersheds with at least 3rd order stream and 15 parameters were selected for prioritization. PCA integrated with WSA was found to be effective for prioritization. The findings showed that about 61.58% of the watershed area is in the high-priority category, suggesting those areas are at a higher risk of erosion. Therefore, different land rehabilitation programs and bioengineering techniques should be focused on the sub-watershed of high-priority categories followed by medium and low-priority categories to control further soil erosion. The adopted methodology of prioritization can also be performed for multi-hazard mapping. |
format | Online Article Text |
id | pubmed-10238735 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-102387352023-06-04 Watershed prioritization of Kailali district through morphometric parameters and landuse/landcover datasets using GIS Ojha, Susil Puri, Lila Bist, Suraj Prasad Bastola, Arjun Prasad Acharya, Bishwabandhu Heliyon Research Article Watershed prioritization is considered an important tool for soil and watershed management. This study focuses on the watershed prioritization of the Kailali district in terms of soil erosion, considering morphometric parameters and land use/landcover (LULC) datasets using GIS. ALOS DEM of 30 m resolution was used to delineate sub-watersheds and calculate linear, areal, and relief morphometric parameters. Similarly, Esri LULC 2021 (Sentinel-2 imagery at 10 m resolution) was used to calculate LULC parameters. An integrated approach of Principal Component Analysis (PCA) and Weighted Sum Analysis (WSA) was used for prioritization. PCA was used to reduce selected parameters, calculate the correlation matrix, and define the significant parameters. WSA was used to define weightage value, and Compound Value (CV) was calculated for the ranking of sub-watersheds. 22 sub-watersheds with at least 3rd order stream and 15 parameters were selected for prioritization. PCA integrated with WSA was found to be effective for prioritization. The findings showed that about 61.58% of the watershed area is in the high-priority category, suggesting those areas are at a higher risk of erosion. Therefore, different land rehabilitation programs and bioengineering techniques should be focused on the sub-watershed of high-priority categories followed by medium and low-priority categories to control further soil erosion. The adopted methodology of prioritization can also be performed for multi-hazard mapping. Elsevier 2023-05-23 /pmc/articles/PMC10238735/ /pubmed/37274710 http://dx.doi.org/10.1016/j.heliyon.2023.e16489 Text en © 2023 The Authors https://creativecommons.org/licenses/by/4.0/This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Research Article Ojha, Susil Puri, Lila Bist, Suraj Prasad Bastola, Arjun Prasad Acharya, Bishwabandhu Watershed prioritization of Kailali district through morphometric parameters and landuse/landcover datasets using GIS |
title | Watershed prioritization of Kailali district through morphometric parameters and landuse/landcover datasets using GIS |
title_full | Watershed prioritization of Kailali district through morphometric parameters and landuse/landcover datasets using GIS |
title_fullStr | Watershed prioritization of Kailali district through morphometric parameters and landuse/landcover datasets using GIS |
title_full_unstemmed | Watershed prioritization of Kailali district through morphometric parameters and landuse/landcover datasets using GIS |
title_short | Watershed prioritization of Kailali district through morphometric parameters and landuse/landcover datasets using GIS |
title_sort | watershed prioritization of kailali district through morphometric parameters and landuse/landcover datasets using gis |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10238735/ https://www.ncbi.nlm.nih.gov/pubmed/37274710 http://dx.doi.org/10.1016/j.heliyon.2023.e16489 |
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