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

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Listed:
  • Weili Duan
  • Bin He
  • Yaning Chen
  • Shan Zou
  • Yi Wang
  • Daniel Nover
  • Wen Chen
  • Guishan Yang

Abstract

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 NH4-N and CODMn 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 CODMn, and NH4-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 CODMn. 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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  • Weili Duan & Bin He & Yaning Chen & Shan Zou & Yi Wang & Daniel Nover & Wen Chen & Guishan Yang, 2018. "Identification of long-term trends and seasonality in high-frequency water quality data from the Yangtze River basin, China," PLOS ONE, Public Library of Science, vol. 13(2), pages 1-18, February.
  • Handle: RePEc:plo:pone00:0188889
    DOI: 10.1371/journal.pone.0188889
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    References listed on IDEAS

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    Cited by:

    1. Wei Sun & Yi Wang & Wen Chen & Bin He & Chong-Gang Liu, 2020. "Basin Water Sensitivity and Its Impact on Spatial Expansion: A Case Study of the Taihu Basin, China," Sustainability, MDPI, vol. 12(24), pages 1-18, December.
    2. Yuangang Li & Maohua Sun & Guanghui Yuan & Yujing Liu, 2019. "Evaluation Methods of Water Environment Safety and Their Application to the Three Northeast Provinces of China," Sustainability, MDPI, vol. 11(18), pages 1-16, September.
    3. Xu Yang & Guangxing Ji & Chong Wang & Jingping Zuo & Haiqing Yang & Jianhua Xu & Ruishan Chen, 2019. "Modeling nitrogen and phosphorus export with InVEST model in Bosten Lake basin of Northwest China," PLOS ONE, Public Library of Science, vol. 14(7), pages 1-17, July.

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