Water Supply (May 2022)

Spatiotemporal water quality variations in the urbanizing Chongqing reach of Jialing River, China

  • Xunjian Long,
  • Yi Zhang,
  • Yan Ye,
  • Yong Ye,
  • Tingbing Xu,
  • Tianyang Li

DOI
https://doi.org/10.2166/ws.2022.145
Journal volume & issue
Vol. 22, no. 5
pp. 5603 – 5617

Abstract

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Water quality in rivers usually exhibits markedly spatiotemporal variations as affected by urbanization, while the magnitude of these effects remain unclear. This study aimed to investigate the spatiotemporal water quality variations in the urbanizing Chongqing reach of Jialing River and its tributary using a 6-yr multisite dataset (January 2010–December 2015). Water quality variables including pH, dissolved oxygen (DO), permanganate index (CODMn), ammonia nitrogen (NH3-N) and total phosphorus (TP) were deciphered. Results showed that the trunk river displayed respectively 1.2 and 39.8% higher pH and DO concentration but 66.9, 94.7 and 85.2% lower CODMn, NH3-N and TP concentrations relative to the tributary (P < 0.05), due largely to the dilution effects occurring in the trunk river. The dry season presented respectively 1.3, 18.2, 102.8 and 32.5% higher pH, DO, NH3-N and TP concentrations than those in the wet season (P < 0.05). DO concentration showed significant inter-annual variations (P < 0.05), and CODMn, NH3-N and TP concentrations all presented markedly declining trends from 2010 to 2015 (P < 0.05). Significant relationships among the study variables were found in different spatiotemporal scales (P < 0.05). Our results are valuable to optimize strategies for sustainable water quality management in rivers experiencing urbanization worldwide. HIGHLIGHTS Spatiotemporal water quality variations in the lower Jialing River are examined.; Trunk Jialing River shows better water quality condition than its tributary river.; Lower river pollutant concentrations are found in the wet season rather than the dry season.; Pollutant concentrations decline in the lower Jialing River from 2010 to 2015.; Water quality variables display marked links across various spatiotemporal scales.;

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