raybet体育在线 院报 ›› 2025, Vol. 42 ›› Issue (7): 69-76.DOI: 10.11988/ckyyb.20240503

• 水环境与水生态 • 上一篇    下一篇

长江安徽段水质时空变化特征及影响因素

冯家成1(), 曹学康2, 陶理3(), 华飞3, 吴康3   

  1. 1 安徽省芜湖生态环境监测中心,安徽 芜湖 241000
    2 同济大学 环境科学与工程学院,上海 200092
    3 芜湖职业技术学院 材料工程学院,安徽 芜湖 241003
  • 收稿日期:2024-05-03 修回日期:2024-07-30 出版日期:2025-07-01 发布日期:2025-07-01
  • 通信作者:
    陶理(1997-),女,安徽芜湖人,助教,硕士,研究方向为河湖水生态环境治理。E-mail:
  • 作者简介:

    冯家成(1997-),男,安徽芜湖人,助理工程师,硕士,研究方向为河湖水环境模型。E-mail:

  • 基金资助:
    2024年度高校科学研究项目(2024AH040254)

Spatiotemporal Variation Characteristics and Influencing Factors of Water Quality in the Anhui Section of Yangtze River

FENG Jia-cheng1(), CAO Xue-kang2, TAO Li3(), HUA Fei3, WU Kang3   

  1. 1 Anhui Wuhu Ecological Environment Monitoring Center,Wuhu 241000,China
    2 College of Environmental Science and Engineering, Tongji University, Shanghai 200092, China
    3 School of Materials Engineering, Wuhu Institute of Technology, Wuhu 241003, China
  • Received:2024-05-03 Revised:2024-07-30 Published:2025-07-01 Online:2025-07-01

摘要:

长江安徽段作为长江下游的初始河段,其水质变化状况一直备受关注。基于2021—2023年长江安徽29个国考断面逐日水质监测数据,采用综合水质指数法结合主成分分析、相关性分析等多种方法探究水质时空变化特征及其影响因素。结果表明:①长江安徽段水质指数整体平均值为71.65,水质状况较好。其中,CODMn、NH3-N和TN为影响地区河流水环境质量的主要指标。②从空间上看,上游流域断面(除XK断面外)水质较下游流域更优,造成这一现象可能是由于上下游湖泊水系连通程度、矿产资源利用开发程度以及农业种植规模等有所差异。③从时间上看,受温度以及降水等气象因素影响,水质指数在4个季度上呈现先下降后上升的变化趋势,冬春季节水质优于夏秋季节。

关键词: 水质指数, 综合水质评价法, 主成分分析, 时空变化, 长江安徽段

Abstract:

[Objective] As the uppermost section of the lower Yangtze River, the water quality changes in the Anhui section have attracted significant attention. Investigating the spatiotemporal variation characteristics of water quality and the underlying influencing factors in this region over recent years can provide clearer guidance for future water environment management in the lower Yangtze River. [Methods] Based on daily water quality data from 29 national assessment sections in the Anhui section of the Yangtze River from 2021 to 2023, this study adopted the comprehensive water quality index method to evaluate water quality, and integrated principal component analysis, correlation analysis, and other methods to explore the spatiotemporal variation and influencing factors of water quality. [Results] (1) The daily data values of different water quality indicators at various monitoring sections in the Anhui section from 2021 to 2023 exhibited varying degrees of fluctuation. Additionally, the WQI showed a significant positive correlation with pH and dissolved oxygen (DO) (P<0.01), while it exhibited a significant negative correlation with permanganate index (CODMn), ammonia nitrogen (NH3-N), total nitrogen (TN), and total phosphorus (TP) (P<0.01). (2) Overall, the water environment quality in the upstream basin in the Anhui section was superior to that of the downstream basin, with several downstream sections having WQI values above 80. The overall water quality in the Anhui section deteriorated progressively from the upstream to the downstream (flowing from the southwest to the northeast). (3) From 2021 to 2023, the overall water quality showed an upward trend, with annual average WQI values of 70.49, 72.24, and 72.49, respectively. Additionally, the quarterly trend within each year was characterized by an initial decline followed by an increase, with average WQI values for the first, second, third, and fourth quarters being 72.21, 71.74, 69.18, and 73.55, respectively. [Conclusion] (1) The overall average WQI value in the Anhui section of the Yangtze River is 71.65, indicating good water quality. CODMn, NH3-N, and TN are identified as the primary indicators influencing the water environment quality of the region. (2) Spatially, the water quality of the upstream basin sections (except for XK section) is better than that of the downstream basin, which may be attributed to differences in the connectivity of upstream and downstream lake systems, the degree of mineral resource exploitation and development, and the scale of agriculture. (3) Temporally, influenced by meteorological factors such as temperature and precipitation, water quality exhibits a trend of first decreasing and then increasing across the four quarters, with better water quality in winter and spring compared to summer and autumn.

Key words: water quality index(WQI), comprehensive water quality assessment method, principal component analysis, spatiotemporal variation, Anhui section of Yangtze River

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