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Teleconnection Patterns of River Water Quality Dynamics Based on Complex Network Analysis
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  • jiping jiang,
  • Sijie Tang,
  • Bellie Sivakumar,
  • Tianrui Pang,
  • Na Wu,
  • Yi Zheng
jiping jiang
Southern University of Science and Technology

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Sijie Tang
Southern University of Science and Technology
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Bellie Sivakumar
Indian Institute of Technology Bombay
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Tianrui Pang
Harbin Institute of Technology
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Na Wu
Tongji University
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Yi Zheng
Southern University of Science and Technology
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Water quality in rivers is influenced by natural factors and human activities that interact in complex and nonlinear ways, which make water quality modelling a challenging task. The concepts of complex networks (CN), a recent development in network theory, seem to provide new avenues to unravel the connections and dynamics of water quality phenomenon, including clandestine teleconnections. This study aims to explore the spatial patterns of water quality using the CN concepts, at both catchment scale and larger national scale. Three major water quality parameters, i.e. dissolved oxygen (DO), permanganate index (COD Mn), and ammonia nitrogen (NH 3-N) are considered for analysis. Weekly data over a period of 12 years (since 2006) from 91 monitoring stations across China are analysed. Degree centrality and clustering coefficient methods are employed. The results show that the degree centrality and clustering coefficients values for water quality indicators is DO > NH 3-N > COD Mn at both basin scale and national scale. Since COD Mn is more sensitive to the upstream point source pollution, as it depends upon the locality and human activities, it leads to a higher heterogeneity of CN indexes even among spatially closer stations. NH 3-N comes next due to the identical pollution level and degradation process in a certain spatial extension. Meanwhile, DO shows good regional connectivity in line with the strong diffusivity. However, the CN characteristic is relatively inconspicuous in large basins and nationwide scale, which indicates the regional impact on water quality fluctuation and CN analysis. These original findings boost a comprehensive understanding of water quality dynamics and enlighten novel methods for environment system analysis and watershed management.
21 Feb 2024Published in Advanced Hydroinformatics on pages 357-372. 10.1002/9781119639268.ch13