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<p>Climate change and human activities have redefined seasonal river water quality patterns, yet their respective impacts remain unclear. Here, we propose a novel trend-based metric, the T-NM index, to isolate asymmetric human amplification and suppression effects across 195 natural and 1540 managed watersheds in China (2006–2020). Consistent trends in 52–89% of watersheds suggest climatic dominance, while anthropogenic drivers intensified or attenuated trends by 22–158% and 14–56%, especially in summer. Four independent multivariable models simulated seasonal COD and DO concentrations. Attribution analysis showed that seasonal factors explained 47.08% of the variation, while rainfall (25.37%) and slope (17.40%) accounted for COD and DO changes in natural watersheds; in contrast, Shannon Diversity Index (11.58%) and Largest Patch Index (10.66%) dominated in managed watersheds. This study establishes a generalizable framework for distinguishing natural and anthropogenic influences, offering key insights for adaptive water quality management under future climatic and socio-economic transitions.</p>

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Natural and anthropogenic imprints on seasonal river water quality trends across China

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年6月2日

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  • Haoran Zhang,
  • Huihang Sun,
  • Jiarong Li,
  • Yuelei Li,
  • Luyu Zhang,
  • Ruikun Zhao,
  • Xiangang Hu,
  • Nanqi Ren,
  • Yu Tian

摘要

Climate change and human activities have redefined seasonal river water quality patterns, yet their respective impacts remain unclear. Here, we propose a novel trend-based metric, the T-NM index, to isolate asymmetric human amplification and suppression effects across 195 natural and 1540 managed watersheds in China (2006–2020). Consistent trends in 52–89% of watersheds suggest climatic dominance, while anthropogenic drivers intensified or attenuated trends by 22–158% and 14–56%, especially in summer. Four independent multivariable models simulated seasonal COD and DO concentrations. Attribution analysis showed that seasonal factors explained 47.08% of the variation, while rainfall (25.37%) and slope (17.40%) accounted for COD and DO changes in natural watersheds; in contrast, Shannon Diversity Index (11.58%) and Largest Patch Index (10.66%) dominated in managed watersheds. This study establishes a generalizable framework for distinguishing natural and anthropogenic influences, offering key insights for adaptive water quality management under future climatic and socio-economic transitions.