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Spatiotemporal Patterns in River Water Quality and Pollution Source Apportionment in the Arid Beichuan River Basin of Northwestern China Using Positive Matrix Factorization Receptor Modeling Techniques

Author

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  • Lele Xiao

    (College of Geology and Environment, Xi’an University of Science and Technology, Xi’an 710054, China)

  • Qianqian Zhang

    (Hebei and China Geological Survey Key Laboratory of Groundwater Remediation, Institute of Hydrogeology and Environmental Geology, Chinese Academy of Geological Sciences, Shijiazhuang 050061, China)

  • Chao Niu

    (College of Geology and Environment, Xi’an University of Science and Technology, Xi’an 710054, China)

  • Huiwei Wang

    (Hebei and China Geological Survey Key Laboratory of Groundwater Remediation, Institute of Hydrogeology and Environmental Geology, Chinese Academy of Geological Sciences, Shijiazhuang 050061, China)

Abstract

Deteriorating surface water quality has become an important environmental problem in China. In this study, river water quality was monitored in July (wet season) and October (dry season) 2019 at 26 sites, and a water quality index (WQI) and positive matrix factorization (PMF) model were used to assess surface water quality and identify pollution sources in the Beichuan River basin, Qinghai Province, China. The results showed that 53.85% and 76.92% of TN, 11.54% and 34.62% of TP, 65.38% and 76.92% of Fe, and 11.54% and 15.38% of Mn samples in the dry and wet seasons, respectively, exceeded the Chinese Government’s Grade III standards for surface water quality. The spatial variation in water quality showed that it gradually deteriorated from upstream to downstream as a result of human activity. The temporal variation showed that water quality was poorer in the wet season than in the dry season because of the rainfall runoff effect. The PMF model outputs showed that the primary sources of pollution in the wet season were mineral weathering and organic pollution sources, domestic and industrial sewage, and agricultural and urban non-point pollution sources. However, in the dry season, the primary sources were mineral weathering and organic pollution sources, industrial sewage, and domestic sewage. Our results suggest that the point pollution sources (domestic and industrial sewage) should be more strictly controlled, as a priority, in order to prevent the continued deterioration in water quality.

Suggested Citation

  • Lele Xiao & Qianqian Zhang & Chao Niu & Huiwei Wang, 2020. "Spatiotemporal Patterns in River Water Quality and Pollution Source Apportionment in the Arid Beichuan River Basin of Northwestern China Using Positive Matrix Factorization Receptor Modeling Technique," IJERPH, MDPI, vol. 17(14), pages 1-15, July.
    • Handle: RePEc:gam:jijerp:v:17:y:2020:i:14:p:5015-:d:383648
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    References listed on IDEAS

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    1. Rabia Koklu & Bulent Sengorur & Bayram Topal, 2010. "Water Quality Assessment Using Multivariate Statistical Methods—A Case Study: Melen River System (Turkey)," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 24(5), pages 959-978, March.
    2. Qianqian Zhang & Long Wang & Huiwei Wang & Xi Zhu & Lijun Wang, 2020. "Spatio-Temporal Variation of Groundwater Quality and Source Apportionment Using Multivariate Statistical Techniques for the Hutuo River Alluvial-Pluvial Fan, China," IJERPH, MDPI, vol. 17(3), pages 1-14, February.
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    Cited by:

    1. Bing Zhou & Huiwei Wang & Qianqian Zhang, 2021. "Assessment of the Evolution of Groundwater Chemistry and Its Controlling Factors in the Huangshui River Basin of Northwestern China, Using Hydrochemistry and Multivariate Statistical Techniques," IJERPH, MDPI, vol. 18(14), pages 1-16, July.
    2. Lele Xiao & Fan Li & Chao Niu & Gelian Dai & Qian Qiao & Chengsen Lin, 2022. "Evaluation of Water Inrush Hazard in Coal Seam Roof Based on the AHP-CRITIC Composite Weighted Method," Energies, MDPI, vol. 16(1), pages 1-20, December.

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