Cargando…

Identification of long-term trends and seasonality in high-frequency water quality data from the Yangtze River basin, China

Comprehensive understanding of the long-term trends and seasonality of water quality is important for controlling water pollution. This study focuses on spatio-temporal distributions, long-term trends, and seasonality of water quality in the Yangtze River basin using a combination of the seasonal Ma...

Descripción completa

Detalles Bibliográficos
Autores principales: Duan, Weili, He, Bin, Chen, Yaning, Zou, Shan, Wang, Yi, Nover, Daniel, Chen, Wen, Yang, Guishan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5821306/
https://www.ncbi.nlm.nih.gov/pubmed/29466354
http://dx.doi.org/10.1371/journal.pone.0188889
_version_ 1783301491900022784
author Duan, Weili
He, Bin
Chen, Yaning
Zou, Shan
Wang, Yi
Nover, Daniel
Chen, Wen
Yang, Guishan
author_facet Duan, Weili
He, Bin
Chen, Yaning
Zou, Shan
Wang, Yi
Nover, Daniel
Chen, Wen
Yang, Guishan
author_sort Duan, Weili
collection PubMed
description Comprehensive understanding of the long-term trends and seasonality of water quality is important for controlling water pollution. This study focuses on spatio-temporal distributions, long-term trends, and seasonality of water quality in the Yangtze River basin using a combination of the seasonal Mann-Kendall test and time-series decomposition. The used weekly water quality data were from 17 environmental stations for the period January 2004 to December 2015. Results show gradual improvement in water quality during this period in the Yangtze River basin and greater improvement in the Uppermost Yangtze River basin. The larger cities, with high GDP and population density, experienced relatively higher pollution levels due to discharge of industrial and household wastewater. There are higher pollution levels in Xiang and Gan River basins, as indicated by higher NH(4)-N and COD(Mn) concentrations measured at the stations within these basins. Significant trends in water quality were identified for the 2004–2015 period. Operations of the three Gorges Reservoir (TGR) enhanced pH fluctuations and possibly attenuated COD(Mn), and NH(4)-N transportation. Finally, seasonal cycles of varying strength were detected for time-series of pollutants in river discharge. Seasonal patterns in pH indicate that maxima appear in winter, and minima in summer, with the opposite true for COD(Mn). Accurate understanding of long-term trends and seasonality are necessary goals of water quality monitoring system efforts and the analysis methods described here provide essential information for effectively controlling water pollution.
format Online
Article
Text
id pubmed-5821306
institution National Center for Biotechnology Information
language English
publishDate 2018
publisher Public Library of Science
record_format MEDLINE/PubMed
spelling pubmed-58213062018-03-02 Identification of long-term trends and seasonality in high-frequency water quality data from the Yangtze River basin, China Duan, Weili He, Bin Chen, Yaning Zou, Shan Wang, Yi Nover, Daniel Chen, Wen Yang, Guishan PLoS One Research Article Comprehensive understanding of the long-term trends and seasonality of water quality is important for controlling water pollution. This study focuses on spatio-temporal distributions, long-term trends, and seasonality of water quality in the Yangtze River basin using a combination of the seasonal Mann-Kendall test and time-series decomposition. The used weekly water quality data were from 17 environmental stations for the period January 2004 to December 2015. Results show gradual improvement in water quality during this period in the Yangtze River basin and greater improvement in the Uppermost Yangtze River basin. The larger cities, with high GDP and population density, experienced relatively higher pollution levels due to discharge of industrial and household wastewater. There are higher pollution levels in Xiang and Gan River basins, as indicated by higher NH(4)-N and COD(Mn) concentrations measured at the stations within these basins. Significant trends in water quality were identified for the 2004–2015 period. Operations of the three Gorges Reservoir (TGR) enhanced pH fluctuations and possibly attenuated COD(Mn), and NH(4)-N transportation. Finally, seasonal cycles of varying strength were detected for time-series of pollutants in river discharge. Seasonal patterns in pH indicate that maxima appear in winter, and minima in summer, with the opposite true for COD(Mn). Accurate understanding of long-term trends and seasonality are necessary goals of water quality monitoring system efforts and the analysis methods described here provide essential information for effectively controlling water pollution. Public Library of Science 2018-02-21 /pmc/articles/PMC5821306/ /pubmed/29466354 http://dx.doi.org/10.1371/journal.pone.0188889 Text en © 2018 Duan et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Duan, Weili
He, Bin
Chen, Yaning
Zou, Shan
Wang, Yi
Nover, Daniel
Chen, Wen
Yang, Guishan
Identification of long-term trends and seasonality in high-frequency water quality data from the Yangtze River basin, China
title Identification of long-term trends and seasonality in high-frequency water quality data from the Yangtze River basin, China
title_full Identification of long-term trends and seasonality in high-frequency water quality data from the Yangtze River basin, China
title_fullStr Identification of long-term trends and seasonality in high-frequency water quality data from the Yangtze River basin, China
title_full_unstemmed Identification of long-term trends and seasonality in high-frequency water quality data from the Yangtze River basin, China
title_short Identification of long-term trends and seasonality in high-frequency water quality data from the Yangtze River basin, China
title_sort identification of long-term trends and seasonality in high-frequency water quality data from the yangtze river basin, china
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5821306/
https://www.ncbi.nlm.nih.gov/pubmed/29466354
http://dx.doi.org/10.1371/journal.pone.0188889
work_keys_str_mv AT duanweili identificationoflongtermtrendsandseasonalityinhighfrequencywaterqualitydatafromtheyangtzeriverbasinchina
AT hebin identificationoflongtermtrendsandseasonalityinhighfrequencywaterqualitydatafromtheyangtzeriverbasinchina
AT chenyaning identificationoflongtermtrendsandseasonalityinhighfrequencywaterqualitydatafromtheyangtzeriverbasinchina
AT zoushan identificationoflongtermtrendsandseasonalityinhighfrequencywaterqualitydatafromtheyangtzeriverbasinchina
AT wangyi identificationoflongtermtrendsandseasonalityinhighfrequencywaterqualitydatafromtheyangtzeriverbasinchina
AT noverdaniel identificationoflongtermtrendsandseasonalityinhighfrequencywaterqualitydatafromtheyangtzeriverbasinchina
AT chenwen identificationoflongtermtrendsandseasonalityinhighfrequencywaterqualitydatafromtheyangtzeriverbasinchina
AT yangguishan identificationoflongtermtrendsandseasonalityinhighfrequencywaterqualitydatafromtheyangtzeriverbasinchina