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<p>Accurate assessment of river water quality and its spatiotemporal dynamics is essential for effective water environment management. In this study, daily monitoring data for pH, dissolved oxygen (DO), permanganate index (CODMn), ammonia nitrogen (NH₃-N), total phosphorus (TP), and total nitrogen (TN) from nine national monitoring sections along the Chongqing reach of the Yangtze River Basin (2021–2023) were analyzed. To address the limitations of traditional single-factor and classical Water Quality Index (WQI) approaches, an improved comprehensive water quality identification index (IWQI) was developed, integrating the Entropy Weight Coefficient Method (EWM) and Principal Component Analysis (PCA) to optimize indicator weights and enhance evaluation accuracy. The results show that, temporally, water quality in the Chongqing reach improved markedly from 2021 to 2023, with 2021 identified as the turning point for substantial improvement. During the subsequent study period, all monitored sections met the secondary water quality standards required for water functional zones. Flood season water quality was generally poorer than during the non-flood season, with CODMn, TP, and TN consistently identified as the dominant pollutants throughout both periods. Spatially, the upstream sections maintained Class II status, while the middle and lower reaches experienced higher pollution loads, although most sections showed significant improvement by the end of the study period. The IWQI evaluation closely matched the actual management objectives for water function zones, and PCA confirmed CODMn, TP, and TN as the principal contributors to water quality degradation. The findings provide a robust scientific basis for the formulation of targeted water pollution prevention and control strategies in the Yangtze River Basin and demonstrate the utility of improved index-based evaluation methods in large river systems.</p>

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Spatiotemporal Variation Analysis of Yangtze River Basin Water Quality in Chong Qing, China During 2021–2023 Based on Improved Water Quality Assessment

  • 期刊论文

  • 发表日期：

    2025年11月15日

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  • Libo Ran,
  • Xing Wei,
  • Yulin Zhou,
  • Qingmei Zhang,
  • Yanan Fu,
  • Zikan Deng

摘要

Accurate assessment of river water quality and its spatiotemporal dynamics is essential for effective water environment management. In this study, daily monitoring data for pH, dissolved oxygen (DO), permanganate index (CODMn), ammonia nitrogen (NH₃-N), total phosphorus (TP), and total nitrogen (TN) from nine national monitoring sections along the Chongqing reach of the Yangtze River Basin (2021–2023) were analyzed. To address the limitations of traditional single-factor and classical Water Quality Index (WQI) approaches, an improved comprehensive water quality identification index (IWQI) was developed, integrating the Entropy Weight Coefficient Method (EWM) and Principal Component Analysis (PCA) to optimize indicator weights and enhance evaluation accuracy. The results show that, temporally, water quality in the Chongqing reach improved markedly from 2021 to 2023, with 2021 identified as the turning point for substantial improvement. During the subsequent study period, all monitored sections met the secondary water quality standards required for water functional zones. Flood season water quality was generally poorer than during the non-flood season, with CODMn, TP, and TN consistently identified as the dominant pollutants throughout both periods. Spatially, the upstream sections maintained Class II status, while the middle and lower reaches experienced higher pollution loads, although most sections showed significant improvement by the end of the study period. The IWQI evaluation closely matched the actual management objectives for water function zones, and PCA confirmed CODMn, TP, and TN as the principal contributors to water quality degradation. The findings provide a robust scientific basis for the formulation of targeted water pollution prevention and control strategies in the Yangtze River Basin and demonstrate the utility of improved index-based evaluation methods in large river systems.