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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...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2018
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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 |
Sumario: | 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. |
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