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Water quality attribution and simulation of non-point source pollution load flux in the Hulan River basin
Surface water is the main source of irrigation and drinking water for rural communities by the Hulan River basin, an important grain-producing region in northeastern China. Understanding the spatial and temporal distribution of water quality and its driving forces is critical for sustainable develop...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7033256/ https://www.ncbi.nlm.nih.gov/pubmed/32080276 http://dx.doi.org/10.1038/s41598-020-59980-7 |
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author | Liu, Yan Li, Hongyan Cui, Geng Cao, Yuqing |
author_facet | Liu, Yan Li, Hongyan Cui, Geng Cao, Yuqing |
author_sort | Liu, Yan |
collection | PubMed |
description | Surface water is the main source of irrigation and drinking water for rural communities by the Hulan River basin, an important grain-producing region in northeastern China. Understanding the spatial and temporal distribution of water quality and its driving forces is critical for sustainable development and the protection of water resources in the basin. Following sample collection and testing, the spatial distribution and driving forces of water quality were investigated using cluster analysis, hydrochemical feature partitioning, and Gibbs diagrams. The results demonstrated that the surface waters of the Hulan River Basin tend to be medium–weakly alkaline with a low degree of mineralization and water-rock interaction. Changes in topography and land use, confluence, application of pesticides and fertilizers, and the development of tourism were found to be important driving forces affecting the water quality of the basin. Non-point source pollution load fluxes of nitrogen (N) and phosphorus (P) were simulated using the Soil Water and Assessment Tool. The simulation demonstrated that the non-point source pollution loading is low upstream and increases downstream. The distributions of N and P loading varied throughout the basin. The findings of this study provide information regarding the spatial distribution of water quality in the region and present a scientific basis for future pollution control. |
format | Online Article Text |
id | pubmed-7033256 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-70332562020-02-28 Water quality attribution and simulation of non-point source pollution load flux in the Hulan River basin Liu, Yan Li, Hongyan Cui, Geng Cao, Yuqing Sci Rep Article Surface water is the main source of irrigation and drinking water for rural communities by the Hulan River basin, an important grain-producing region in northeastern China. Understanding the spatial and temporal distribution of water quality and its driving forces is critical for sustainable development and the protection of water resources in the basin. Following sample collection and testing, the spatial distribution and driving forces of water quality were investigated using cluster analysis, hydrochemical feature partitioning, and Gibbs diagrams. The results demonstrated that the surface waters of the Hulan River Basin tend to be medium–weakly alkaline with a low degree of mineralization and water-rock interaction. Changes in topography and land use, confluence, application of pesticides and fertilizers, and the development of tourism were found to be important driving forces affecting the water quality of the basin. Non-point source pollution load fluxes of nitrogen (N) and phosphorus (P) were simulated using the Soil Water and Assessment Tool. The simulation demonstrated that the non-point source pollution loading is low upstream and increases downstream. The distributions of N and P loading varied throughout the basin. The findings of this study provide information regarding the spatial distribution of water quality in the region and present a scientific basis for future pollution control. Nature Publishing Group UK 2020-02-20 /pmc/articles/PMC7033256/ /pubmed/32080276 http://dx.doi.org/10.1038/s41598-020-59980-7 Text en © The Author(s) 2020 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Article Liu, Yan Li, Hongyan Cui, Geng Cao, Yuqing Water quality attribution and simulation of non-point source pollution load flux in the Hulan River basin |
title | Water quality attribution and simulation of non-point source pollution load flux in the Hulan River basin |
title_full | Water quality attribution and simulation of non-point source pollution load flux in the Hulan River basin |
title_fullStr | Water quality attribution and simulation of non-point source pollution load flux in the Hulan River basin |
title_full_unstemmed | Water quality attribution and simulation of non-point source pollution load flux in the Hulan River basin |
title_short | Water quality attribution and simulation of non-point source pollution load flux in the Hulan River basin |
title_sort | water quality attribution and simulation of non-point source pollution load flux in the hulan river basin |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7033256/ https://www.ncbi.nlm.nih.gov/pubmed/32080276 http://dx.doi.org/10.1038/s41598-020-59980-7 |
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