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The spatiotemporal evolution of water quality in the Yangtze River Basin since the impoundment of the Three Gorges Reservoir is critical for formulating comprehensive basin management strategies. Using stepwise multiple linear regression analysis, key water quality indicators influencing the basin from 2003 to 2024 were identified as total phosphorus (TP), permanganate index(CODMn), ammonia nitrogen (NH3-N), lead (Pb), and dissolved oxygen (DO). Evaluations via the single-factor method and the WQImin index demonstrated that the average water quality across the entire Yangtze River Basin has reached an excellent level. However, secondary basins—including the Wu River Basin, Min-Tuo River Basin, and Taihu Lake water system—exhibited relatively severe pollution, with TP and NH3-N being the most prominent contaminants. Significant spatial heterogeneity in water quality was observed. Linear regression and seasonal Kendall tests indicated a statistically significant upward trend in the overall water quality of the Yangtze River Basin. All secondary basins, except the Han River Basin, demonstrated significant improvements. Following the Three Gorges Reservoir impoundment, TP concentrations in the upper reaches of the Yangtze River (specifically the Jialing River Basin, Wu River Basin, and the mainstream section from Yibin to Yichang) initially increased and subsequently declined. Similarly, NH3-N concentrations in the middle reaches (e.g., Dongting Lake and Poyang Lake water systems) and the Wu River Basin located in the upper Yangtze River exhibited comparable trends of initial rise followed by reduction. Conducting research on the spatiotemporal evolution characteristics of water quality across the entire Yangtze River Basin, incorporating secondary tributaries through multi-scale, long-term time series, and multi-indicator analyses, provides critical scientific support for precise pollution mitigation strategies in the region. Such an integrated approach enables a comprehensive understanding of water quality dynamics, identifies pollution hotspots, and informs spatially differentiated management actions, thereby enhancing the efficacy of basin-wide environmental governance.

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揭示三峡水库蓄水以来,长江流域水质时空格局是流域综合治理的基础.基于多元线性逐步回归分析,筛选出2003~2024年间影响长江流域水质的关键指标为TP、CODMn、NH3-N、Pb和DO.单因子评价和WQImin指数评价表明长江全流域平均水质达到优秀水平,乌江流域、岷沱江流域以及太湖水系是长江流域污染较为严重的二级流域,其中TP与NH3-N污染较为突出,水质状况空间异质性显著;使用线性回归分析与季节性Kendall趋势检验,发现长江流域整体水质状况提升趋势显著,具有明显的时间异质性,除汉江外其他二级流域水质状况均有显著上升趋势;三峡水库蓄水以来,上游嘉陵江、乌江流域和宜宾至宜昌干流的TP浓度以及中游洞庭湖、鄱阳湖水系和上游乌江流域NH3-N浓度出现先上升后下降趋势.从长江全流域耦合二级支流,开展多尺度长序列多指标的水质时空演变特征研究,能为长江流域精准治污提供支撑.

, correspAuthors=王永桂, authorNote=null, correspAuthorsNote=
* 责任作者,副教授,
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陈瑞凯(1999-),男,河南开封人,中国地质大学(武汉)硕士研究生,主要从事流域水质变化分析和地表水数值模拟研究..

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陈瑞凯(1999-),男,河南开封人,中国地质大学(武汉)硕士研究生,主要从事流域水质变化分析和地表水数值模拟研究..

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陈瑞凯(1999-),男,河南开封人,中国地质大学(武汉)硕士研究生,主要从事流域水质变化分析和地表水数值模拟研究..

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** : P<0.01

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纵坐标表示斜率,“↗”表示显著上升趋势,“↘”表示显著下降趋势,两者P<0.05

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Normalized values and weights of water quality indices

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水质指标单位权重(Pi)归一化值(Ci)
100806040200
pH值/16~9
CODMnmg/L3≤2≤4≤6≤10≤15≥15
NH3-Nmg/L3≤0.15≤0.5≤1≤1.5≤2≥2
TPmg/L4≤0.02≤0.1≤0.2≤0.3≤0.4≥0.4
BOD5mg/L3≤3≤3≤4≤6≤10≥10
DOmg/L4≥7.5≥6≥5≥3≥2≤2
Asmg/L2≤0.05≤0.05≤0.05≤0.1≤0.1≥0.1
Cr6+mg/L2≤0.01≤0.05≤0.05≤0.05≤0.1≥0.1
Pbmg/L3≤0.01≤0.01≤0.05≤0.05≤0.1≥0.1
挥发酚mg/L3≤0.002≤0.002≤0.005≤0.01≤0.1≥0.1
Cumg/L2≤0.01≤1≤1≤1≤1≥1
氰化物mg/L2≤0.005≤0.05≤0.2≤0.2≤0.2≥0.2
), ArticleFig(id=1241408735441122163, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1241408717791490283, language=CN, label=表1, caption=

水质指标的归一化值和权重

, figureFileSmall=null, figureFileBig=null, tableContent=
水质指标单位权重(Pi)归一化值(Ci)
100806040200
pH值/16~9
CODMnmg/L3≤2≤4≤6≤10≤15≥15
NH3-Nmg/L3≤0.15≤0.5≤1≤1.5≤2≥2
TPmg/L4≤0.02≤0.1≤0.2≤0.3≤0.4≥0.4
BOD5mg/L3≤3≤3≤4≤6≤10≥10
DOmg/L4≥7.5≥6≥5≥3≥2≤2
Asmg/L2≤0.05≤0.05≤0.05≤0.1≤0.1≥0.1
Cr6+mg/L2≤0.01≤0.05≤0.05≤0.05≤0.1≥0.1
Pbmg/L3≤0.01≤0.01≤0.05≤0.05≤0.1≥0.1
挥发酚mg/L3≤0.002≤0.002≤0.005≤0.01≤0.1≥0.1
Cumg/L2≤0.01≤1≤1≤1≤1≥1
氰化物mg/L2≤0.005≤0.05≤0.2≤0.2≤0.2≥0.2
), ArticleFig(id=1241408735671808896, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1241408717791490283, language=EN, label=Table 2, caption=

Multiple linear stepwise regression analysis of WQI and water quality index

, figureFileSmall=null, figureFileBig=null, tableContent=
模型线性方程R2F P
12.100***-0.217***lg(CODMn+1)0.51287.9<0.001
22.081***-0.213***lg(CODMn+1)-0.153***lg(NH3-N+1)0.73376.3<0.001
32.132***-0.151***lg(CODMn+1)-0.178***lg(NH3-N+1)-0.073***lg(Pb+1)0.80360.3<0.001
42.046***-0.122***lg(CODMn+1)-0.189***lg(NH3-N+1)-0.074***lg(Pb+1)+0.076***lg(DO+1)0.81299.0<0.001
52.029***-0.094***lg(CODMn+1)-0.191***lg(NH3-N+1)-0.071***lg(Pb+1)+0.090***lg(DO+1)-0.306***lg(TP+1)0.83267.2<0.001
62.037***-0.073***lg(CODMn+1)-0.135***lg(NH3-N+1)-0.077***lg(Pb+1)+0.098***lg(DO+1)-0.342***lg(TP+1)-0.063***lg(BOD5+1)0.85242.4<0.001
), ArticleFig(id=1241408735957021584, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1241408717791490283, language=CN, label=表2, caption=

WQI与水质指标的多元线性逐步回归分析

, figureFileSmall=null, figureFileBig=null, tableContent=
模型线性方程R2F P
12.100***-0.217***lg(CODMn+1)0.51287.9<0.001
22.081***-0.213***lg(CODMn+1)-0.153***lg(NH3-N+1)0.73376.3<0.001
32.132***-0.151***lg(CODMn+1)-0.178***lg(NH3-N+1)-0.073***lg(Pb+1)0.80360.3<0.001
42.046***-0.122***lg(CODMn+1)-0.189***lg(NH3-N+1)-0.074***lg(Pb+1)+0.076***lg(DO+1)0.81299.0<0.001
52.029***-0.094***lg(CODMn+1)-0.191***lg(NH3-N+1)-0.071***lg(Pb+1)+0.090***lg(DO+1)-0.306***lg(TP+1)0.83267.2<0.001
62.037***-0.073***lg(CODMn+1)-0.135***lg(NH3-N+1)-0.077***lg(Pb+1)+0.098***lg(DO+1)-0.342***lg(TP+1)-0.063***lg(BOD5+1)0.85242.4<0.001
), ArticleFig(id=1241408736078656412, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1241408717791490283, language=EN, label=Table 3, caption=

Comparison of the average WQImin values in the Yangtze River Basin from 2003 to 2024

, figureFileSmall=null, figureFileBig=null, tableContent=
流域水系WQIminWQI-CODMnWQI-NH3-NWQI-TPWQI-DOWQI-Pb
2003~2024年均值距平
上游流域金沙江92.011.395.696.887.196.1 84.5
岷沱江69.1-11.681.355.551.589.0 68.4
嘉陵江85.85.182.489.479.294.9 82.9
乌江48.7-3256.412.923.057.7 93.5
宜宾至宜昌干流86.96.291.998.369.994.3 80.0
中游流域洞庭湖水系88.88.195.883.679.293.3 92.3
汉江90.09.389.596.479.997.1 86.9
鄱阳湖水系85.64.982.681.674.991.0 98.1
宜昌至湖口干流86.05.385.491.968.094.9 89.7
下游流域湖口以下干流83.12.486.284.568.592.5 83.9
太湖水系70.6-10.161.657.358.975.9 99.5
长江全流域80.7/82.877.367.489.0 87.1
), ArticleFig(id=1241408736233845675, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1241408717791490283, language=CN, label=表3, caption=

长江流域WQImin2003~2024年均值对比

, figureFileSmall=null, figureFileBig=null, tableContent=
流域水系WQIminWQI-CODMnWQI-NH3-NWQI-TPWQI-DOWQI-Pb
2003~2024年均值距平
上游流域金沙江92.011.395.696.887.196.1 84.5
岷沱江69.1-11.681.355.551.589.0 68.4
嘉陵江85.85.182.489.479.294.9 82.9
乌江48.7-3256.412.923.057.7 93.5
宜宾至宜昌干流86.96.291.998.369.994.3 80.0
中游流域洞庭湖水系88.88.195.883.679.293.3 92.3
汉江90.09.389.596.479.997.1 86.9
鄱阳湖水系85.64.982.681.674.991.0 98.1
宜昌至湖口干流86.05.385.491.968.094.9 89.7
下游流域湖口以下干流83.12.486.284.568.592.5 83.9
太湖水系70.6-10.161.657.358.975.9 99.5
长江全流域80.7/82.877.367.489.0 87.1
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2003~2024年长江流域水质时空演变特征
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陈瑞凯 1 , 康瑾 2 , 赵琰鑫 3 , 郭琰琪 1 , 徐晓林 1 , 王永桂 1, *
中国环境科学 | 环境生态 2025,45(4): 2171-2182
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中国环境科学 | 环境生态 2025, 45(4): 2171-2182
2003~2024年长江流域水质时空演变特征
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陈瑞凯1 , 康瑾2, 赵琰鑫3, 郭琰琪1, 徐晓林1, 王永桂1, *
作者信息
  • 1.中国地质大学(武汉)地理与信息工程学院,区域生态过程与环境演变湖北省重点实验室,湖北 武汉 430074
  • 2.湖北省生态环境科学研究院,湖北 武汉 430072
  • 3.生态环境部环境规划院,北京 100012
  • 陈瑞凯(1999-),男,河南开封人,中国地质大学(武汉)硕士研究生,主要从事流域水质变化分析和地表水数值模拟研究..

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* 责任作者,副教授,
Spatial and temporal evolution of water quality in the Yangtze River Basin from 2003 to 2024
Rui-kai CHEN1 , Jin KANG2, Yan-xin ZHAO3, Yan-qi GUO1, Xiao-lin XU1, Yong-gui WANG1, *
Affiliations
  • 1.Hubei Key Laboratory of Regional Ecology and Environmental Change, School of Geography and Information Engineering, China University of Geosciences, Wuhan 430074, China
  • 2.Hubei Academy of Eco-Environmental Sciences, Wuhan 430072, China
  • 3.Chinese Academy of Environmental Planning, Beijing 100012, China
出版时间: 2025-04-20
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揭示三峡水库蓄水以来,长江流域水质时空格局是流域综合治理的基础.基于多元线性逐步回归分析,筛选出2003~2024年间影响长江流域水质的关键指标为TP、CODMn、NH3-N、Pb和DO.单因子评价和WQImin指数评价表明长江全流域平均水质达到优秀水平,乌江流域、岷沱江流域以及太湖水系是长江流域污染较为严重的二级流域,其中TP与NH3-N污染较为突出,水质状况空间异质性显著;使用线性回归分析与季节性Kendall趋势检验,发现长江流域整体水质状况提升趋势显著,具有明显的时间异质性,除汉江外其他二级流域水质状况均有显著上升趋势;三峡水库蓄水以来,上游嘉陵江、乌江流域和宜宾至宜昌干流的TP浓度以及中游洞庭湖、鄱阳湖水系和上游乌江流域NH3-N浓度出现先上升后下降趋势.从长江全流域耦合二级支流,开展多尺度长序列多指标的水质时空演变特征研究,能为长江流域精准治污提供支撑.

三峡水库  /  长江流域  /  水质评价  /  时空演变  /  异质性

The spatiotemporal evolution of water quality in the Yangtze River Basin since the impoundment of the Three Gorges Reservoir is critical for formulating comprehensive basin management strategies. Using stepwise multiple linear regression analysis, key water quality indicators influencing the basin from 2003 to 2024 were identified as total phosphorus (TP), permanganate index(CODMn), ammonia nitrogen (NH3-N), lead (Pb), and dissolved oxygen (DO). Evaluations via the single-factor method and the WQImin index demonstrated that the average water quality across the entire Yangtze River Basin has reached an excellent level. However, secondary basins—including the Wu River Basin, Min-Tuo River Basin, and Taihu Lake water system—exhibited relatively severe pollution, with TP and NH3-N being the most prominent contaminants. Significant spatial heterogeneity in water quality was observed. Linear regression and seasonal Kendall tests indicated a statistically significant upward trend in the overall water quality of the Yangtze River Basin. All secondary basins, except the Han River Basin, demonstrated significant improvements. Following the Three Gorges Reservoir impoundment, TP concentrations in the upper reaches of the Yangtze River (specifically the Jialing River Basin, Wu River Basin, and the mainstream section from Yibin to Yichang) initially increased and subsequently declined. Similarly, NH3-N concentrations in the middle reaches (e.g., Dongting Lake and Poyang Lake water systems) and the Wu River Basin located in the upper Yangtze River exhibited comparable trends of initial rise followed by reduction. Conducting research on the spatiotemporal evolution characteristics of water quality across the entire Yangtze River Basin, incorporating secondary tributaries through multi-scale, long-term time series, and multi-indicator analyses, provides critical scientific support for precise pollution mitigation strategies in the region. Such an integrated approach enables a comprehensive understanding of water quality dynamics, identifies pollution hotspots, and informs spatially differentiated management actions, thereby enhancing the efficacy of basin-wide environmental governance.

Three Gorges Reservoir  /  Yangtze River Basin  /  water quality assessment  /  space-time evolution  /  heterogeneity
陈瑞凯, 康瑾, 赵琰鑫, 郭琰琪, 徐晓林, 王永桂. 2003~2024年长江流域水质时空演变特征. 中国环境科学, 2025 , 45 (4) : 2171 -2182 .
Rui-kai CHEN, Jin KANG, Yan-xin ZHAO, Yan-qi GUO, Xiao-lin XU, Yong-gui WANG. Spatial and temporal evolution of water quality in the Yangtze River Basin from 2003 to 2024[J]. China Environmental Science, 2025 , 45 (4) : 2171 -2182 .
自2003年三峡水库蓄水以来,长江流域经济社会发展迅速,城镇化水平大幅跃升,GDP占全国比重不断上升[1].经济社会的持续发展对水环境造成的压力不断加大,加剧了水质的恶化[2-4].蓄水所引起的水文条件变化和社会经济发展对水质时空格局的叠加影响是长江流域综合治理关注的重点问题.
近来有众多学者开展了相关研究.在全流域尺度:学者们通过单因子评价法和修正水质指数(WQI-DET)等方法,发现自2008年以来,长江流域溶解氧(DO)浓度不断上升,氨氮(NH3-N)浓度不断下降,流域水体耗氧污染明显减轻,河流水体富营养化有所缓解;长江流域中河流级别越低水质相对越差,总磷(TP)已经成为长江流域主要超标指标[5-8].在子流域尺度:学者们发现上游沱江、乌江流域的NH3-N与TP已成为当地的主要污染物[9-10];中游洞庭湖流域的主要污染物为总氮(TN)与TP[11],三峡水库蓄水以来洞庭湖TN呈显著增加、TP呈显著下降趋势[12];下游太湖流域水质评价为“中等”[13],流域水质改善明显,TN浓度显著下降,TP变化不明显[14].从研究方法上看:水质评价的主流方法是单因子评价法[6-7,9,15]与水质指数法(WQI)[5,13,16-17],其中单因子评价法简单方便,是我国《地表水环境质量标准》(GB3838-2002)[18]所使用的方法,WQI方法评价结果准确、直观,能够反映水质整体状况.水质的时空异质性演变,主要为线性回归分析[19]、图表及描述性分析等方法[20],水质序列数据通常具有非正态性、周期性、较多异常值和缺失值等特点,而非参数统计方法(如Spearman秩相关分析、Mann-Kendall检验、季节性Kendall检验)等不要求样本遵循正态分布、且受异常值影响较小,适用面广泛、结论客观准确,因此被广泛应用于水质时间序列趋势的分析[21-23].随着《长江经济带发展规划纲要》、《长江保护法》、《“十四五”重点流域水环境综合治理规划》、《长江保护修复攻坚战行动计划》等规划、法律以及重要指示相继提出,“共抓大保护、不搞大开发”,要求我们认识长江流域的整体情况,并能识别出重点管控子流域,以支撑在有限的经费与精力条件下,让长江流域水环境保护与综合治理能够更快见到成效.这就要求同时以长江流域为整体,并兼顾子流域开展研究.虽然关于长江流域水质评价已取得丰富成果,但现有研究或以长江流域为一个整体开展研究[5-8],或选择部分支流进行分析[9-14],二者兼顾的研究还需要进一步开展.
基于以上背景,本文利用单因子评价法和WQImin方法对2003年三峡水库蓄水以来长江流域进行多年水质评价,并通过线性回归分析、季节性Kendall趋势检验探究长江流域及其二级流域的水质时空异质性演变特征,以便更好地认识长江流域的水质状况,为长江流域综合治理提供科学支撑.
长江发源于唐古拉山脉各拉丹冬峰,干流全长6300余km,是中国第一长河,流域面积约180万km2,占我国陆地总面积的18.8%.长江流域划分为金沙江石鼓以上(占流域总面积的12.15%)、金沙江石鼓以下(14.41%)、岷沱江(9.13%)、嘉陵江(9.05%)、乌江(2.59%)、宜宾至宜昌(8.01%)、洞庭湖水系(14.71%)、汉江(8.62%)、鄱阳湖水系(9.10%)、宜昌至湖口(5.34%)、湖口以下干流(4.84%)、太湖水系(2.05%)12个水资源二级区.本研究将金沙江石鼓以上、石鼓以下合并为一个二级流域——金沙江流域,研究对象为11个二级流域(图1).
(1)水质数据
数据来源于国家地表水水质手工月度监测数据.从所获得的数据中筛选出2003~2024年监测站点位置未发生较大变化、且监测方式与指标均未发生改变的58个国控站点(图1).选取监测持续时间长、数据质量好、具有代表性的pH值、CODMn、NH3-N、TP、BOD5、DO、As、Cr6+、Pb、挥发酚、Cu、氰化物12项水质指标.
(2)基础地理信息数据
长江流域1:25万流域分级矢量数据,由国家地球系统科学数据中心-湖泊-流域分中心(http://lake.geodata.cn)提供.
本文按照我国《地表水环境质量标准》(GB3838-2002)[18]和《地表水环境质量评价办法(试行)》(环办〔2011〕22号)规定的水质标准对长江流域水质进行单因子评价.当流域水质指标浓度超过Ⅲ类标准时,计算其污染物的超标倍数.超标倍数公式如下:
式中:B为某评价指标超标倍数;ρ为某评价指标的质量浓度,单位为mg/L;ρIII为该指标Ⅲ类水质标准限值,单位为mg/L.溶解氧不计算超标倍数.
采用由Pesce和Wunderlin于2000年提出WQI计算公式[24],如下:
式中:n为参与计算的水质指标个数;Ci为第i个水质指标的归一化值;Pi为第i个水质指标的权重,Pi由该水质指标对水质的影响程度确定,影响最大的指标权重设为4,最小为1,相关数值见表1[24-26].
WQI是一个代表整体水质状况的无量纲数,范围为[0,100],分值越高代表水质状况越好.为更好地将WQI评价结果和单因子评价法进行匹配,参考《地表水环境质量标准》(GB3838-2002)[18]以及其他学者研究成果[26-29],对Ci的阈值进行划分,并将WQI值分成五个区间,分别对应五个水质等级:优秀(80~100)、良好(60~80)、中等(40~60)、差(20~40)、极差(0~20).
为增加模型的精确度,同时构建权重模型WQImin-a和非权重模型WQImin-b,并比较两种模型与WQI的相关性.权重模型WQImin-a采用与WQI相同的计算公式(2),非权重模型WQImin-b根据公式(3)来计算.
首先将2003~2024年长江干流(宜宾至宜昌、宜昌至湖口、湖口以下)的水质数据进行对数转换(lg(x+1)),以满足正态性[30];然后进行多元线性逐步回归分析,提取关键指标.
通过回归分析筛选出的6个关键参数及其线性方程如表2所示.结果显示,CODMn能解释WQI变异的51%;CODMn、NH3-N共同解释73%;CODMn、NH3-N、Pb三者解释度为80%.根据陈善荣[31]、娄保锋[32]等人的研究,TP是长江流域近年来的主要污染物,因此将TP作为WQImin的一项关键计算参数,将以上4个参数建立权重模型WQImin-a1与非权重模型WQImin-b1,然后考虑DO、BOD5二者各自以及共同作用对WQImin的影响,将其依次提取,建立权重模型WQImin-a2-WQImin-a4与非权重模型WQImin-b2-WQImin-b4八个模型,解释度分别上升至81%、83%、85%.基于决定系数(R2)和百分比误差(PE)来评估WQImin模型的性能:R2越接近于1,拟合度越好;PE越接近0,表示模型损失信息越少,PE计算公式如下:
评估结果显示,WQImin-a4相较于其他模型具有最高的相关性(R2=0.95),WQImin-b4相较于其他模型具有最低的PE值(4.98%).WQImin-b2具有与WQImin-a4接近的相关性(R2=0.93),且有较低的PE值(8.09%),从指标精简角度看,WQImin-b2使用了较少的指标却依旧保持与WQImin-a4相当的相关性,以及与WQImin-b4相当的PE值,表现更为突出.综合考量下选择WQImin-b2作为最终的WQImin模型,即以TP、CODMn、NH3-N、Pb、DO五项水质指标作为WQImin计算参数.
(1)线性回归分析.利用线性回归分析进行长江流域时空异质性研究.根据最小二乘原理,将三峡水库蓄水以来2003~2024年的水质数据与时间进行一元线性回归分析.
其中自变量x为时间,因变量y为水质数据,a与b由最小二乘法计算得出.a为斜率,即水质要素的线性趋势,当a为正时,表明水质数据随时间有增加趋势;当a为负时,表明水质数据随时间有减小趋势;当a为0时,表明水质数据随时间无明显变化趋势;|a|越大,表明变化越剧烈.
(2)季节性Kendall趋势检验.季节性Kendall趋势检验是对非参数时间序列趋势检验方法——Mann-Kendall检验的一种推广,由Hirsch等[33]于1982年提出,并经过了Smith等[34]的改进.在该检验中,首先把历年相同月份或季节的水质数据进行比较,若后面的值(按时间序列)高于前面的值,则计为“+”号;若低于,计为“-”号;若相等,则计为“0”.如果“+”号与“-”号数量一致,则该数据序列不存在趋势;如果“+”号个数多于“-”号,则可能为上升趋势;反之则为下降趋势.季节性Kendall检验将历年相同月份间的水质资料进行比较,从而避免了因流量的周期性变化导致水质浓度季节性变化的影响.同时,由于数据比较只考虑相对排列而不考虑其大小,故能避免水质资料中常见的漏测值问题[35].
当Kendall检验统计量τ>0,则说明数据序列具有上升趋势,当τ<0,则说明具有下降趋势,当τ=0时无趋势.给定趋势检验显著性水平α为0.05,当P≤0.05时,说明序列趋势具有显著性.
本文使用Hipel[36]提出的方法,借助python语言完成,计算水质序列的变化趋势、斜率、显著性.
图2(a)所示,在三峡水库蓄水影响较大的几个流域中,嘉陵江流域以及宜宾至宜昌干流NH3-N年平均浓度呈现波动下降趋势,而乌江流域、洞庭湖水系、鄱阳湖水系、宜昌至湖口以及湖口以下干流前期呈波动上升趋势,后期呈波动下降趋势.如图2(b)所示,嘉陵江流域、乌江流域、宜宾至宜昌干流TP年平均浓度前期呈波动上升趋势,后期呈波动下降趋势.宜昌至湖口干流TP年平均浓度2014年之前略有上升,但绝大部分年份低于宜宾至宜昌干流的总磷年平均浓度,之后呈现下降趋势.洞庭湖、鄱阳湖水系以及湖口以下干流TP年平均浓度自2003年以来均呈现波动下降趋势.
三峡水库蓄水改变了库区的下垫面性质,影响库区及周围的降雨,有研究表明,三峡大正式蓄水以来,库区极端降雨数量呈现上升的趋势[37],库区TP污染来源多以面源为主[10,38-39],强降雨导致TP入河量增加,是三峡水库蓄水前期上游嘉陵江流域、乌江流域、宜宾至宜昌干流TP浓度不断上升的重要原因之一.乌江流域NH3-N主要来源于易受降水影响的生活污水以及农业面源污染[10],极端降雨数量增多导致乌江流域NH3-N入河量增加.三峡大坝建成后,作为磷载体的泥沙被大量拦截,对下游的宜昌至湖口、湖口以下干流的总磷输送通量减少.大量清水下泄使得三峡大坝以下的河床被不断冲刷下切,长江入洞庭湖水量减少[40],使得洞庭湖水环境容量减少,在2003~2011年间NH3-N浓度出现波动上升现象.因三峡水库蓄水的影响,鄱阳湖丰水期缩短、枯水期延长[41],使得鄱阳湖水体自净能力减弱,在2003~2019年NH3-N年平均浓度呈现明显上升趋势,与他学者研究结果一致[42].
基于筛选出的NH3-N、TP、CODMn、DO、Pb五项影响长江流域水质的关键指标,对长江流域水质进行单因子评价.三峡水库蓄水以来长江全流域2003~2024年平均CODMn、NH3-N、TP、DO、Pb浓度分别达到了Ⅱ类、Ⅲ类、Ⅲ类、Ⅰ类、Ⅲ类标准.2003~2024年长江流域主要水质指标均值单因子评价空间分布如图3所示.长江各二级流域2003~2024年CODMn浓度平均值,除乌江与太湖为Ⅲ类外,其余均达到或优于Ⅱ类水质标准. 2003~2024年长江各二级流域NH3-N、TP平均浓度仅乌江未达到Ⅲ类水质标准,均为劣Ⅴ类,超标倍数为4.12倍与1.5倍.长江各二级支流2003~2024年DO与Pb平均浓度值均未超过Ⅲ类水质标准.方差分析结果显示,5个水质指标的空间差异性显著(P<0.001).
根据《地表水环境质量标准》(GB3838-2002)[18],对长江流域2003年6月-2024年6月水质监测数据作单因子评价.超标频次从高至低分别为NH3-N、TP、CODMn、DO,Pb无超标.NH3-N超标409月次,岷沱江、乌江、鄱阳湖水系、宜昌至湖口、太湖水系这五个子流域有超标现象,平均超标倍数为2.97;TP超标360月次,除汉江、宜昌至湖口、湖口以下干流外,其余子流域均有超标,主要集中在上游流域,平均超标倍数为1.28;CODMn超标115月次,岷沱江、嘉陵江、乌江、宜宾至宜昌、以及太湖水系这五个子流域超标,平均超标倍数为0.45;DO超标140月次,分别为岷沱江流域超标1月次,乌江流域超标106月次,太湖水系超标33月次.
图4所示,乌江流域、岷沱江流域、太湖水系均为NH3-N和TP超标排名前三的流域,乌江流域NH3-N、TP污染严重,两者浓度常年为劣Ⅴ类,超标倍数分别达4.80、2.10;岷沱江流域NH3-N、TP浓度以Ⅲ类为主,超标倍数分别为0.90、0.41;太湖水系NH3-N浓度在Ⅱ-Ⅳ类占比大致相当,TP浓度以Ⅲ类为主,超标倍数分别为0.65、0.25.DO和CODMn分别有140、115月次未达标,主要出现在乌江流域和太湖水系.总体来看,NH3-N和TP是长江流域近年来主要污染物,乌江、岷沱江、太湖水系是污染较严重的三个子流域.
四川省境内的岷沱江流域以及贵州省境内的乌江流域是我国磷矿主产区,磷化工产业所产生的含磷废水,是长江上游总磷污染的重要原因[8].随着点源污染被有效管控,农业面源污染已逐渐成为长江流域地表水体氮、磷污染的最主要来源[39].乌江流域NH3-N污染严重的主要原因是生活污水直接排放和农业生产过程中氮肥流失造成的面源污染以及工厂污水排放[10].岷沱江流域农业发达,城镇化发展较快,农业面源污染、畜禽养殖以及生活污水是其NH3-N超标的重要原因[43-45].太湖流域作为我国主要的综合性工业基地之一,流域内化工、印染、造纸等污水排放大的企业众多,并且太湖流域自古就有“鱼米之乡”的美誉,流域种植发达,生活污水、工业废水的大量排放以及农业化肥的过量使用都是NH3-N超标的重要原因[46].
通过构建的WQImin对流域水质进行综合评价,2003~2024年长江全流域及各二级分区的WQImin均值见表3,空间分布见图5.长江流域整体水质达优秀水平,WQImin=80.7.就二级分区来看,太湖水系、岷沱江、乌江是水质最差的三个子流域,WQImin分别为70.3,69.1,48.7,这也是仅有的三个低于全流域WQImin均值的子流域.从空间分布上看,上游流域WQImin为76.5,中游流域为87.4,下游流域为76.9,中游流域水质最好.上游和下游流域相对较差,主要是因为上游的乌江流域和岷沱江流域污染较重,下游流域的太湖水系水质较差,影响了流域整体表现.
就WQI分项指数来说,WQIDO、WQIPb、WQICODMn、WQINH3-N、WQITP五项指标依次降低.DO、Pb、CODMn三者的整体水质达到了优秀(WQI>80),说明长江流域整体的耗氧污染物污染和重金属污染较轻;WQINH3-N、WQITP值较低,TP指标最差,印证了单因子评价的结果.众多研究也表明TP与NH3-N为长江流域主要污染因子[7-8,15,47],说明TP与NH3-N是近年来需重点关注的水污染因子.
乌江是重污染流域,其中WQITP为差,WQINH3-N为极差水平,WQICODMn和WQIDO的也是全流域最低.岷沱江与太湖水系的WQINH3-N和WQITP均为中等水平,以上流域的污染突出指标应成为当地水污染治理的重点方向.
自三峡水库蓄水以来,长江流域WQImin及主要水质指标浓度变化如图6所示.长江流域WQImin值从2003年的75.7逐步升至2024年的88.9,提升幅度达17.40%.线性回归分析结果显示,R2为0.93,斜率为0.7,表明长江流域WQImin值呈显出明显的线性增长趋势,近年来长江流域水质转好态势显著.其中,在2006年长江流域WQImin相比上一年出现明显下滑,主要原因是自2006年开始,将污染较为严重的太湖流域数据纳入计算.根据季节性Kendall趋势检验结果显示(图7),长江流域WQImin、DO有显著上升趋势,CODMn、NH3-N、TP、Pb有显著下降趋势,表明长江流域水质改善趋势明显.
在主要水质水质指标中,CODMn、DO、Pb三项在线性回归分析中,R2均大于0.7,拟合效果好,变化趋势明显.长江流域CODMn浓度自2003年的3.30mg/L下降至2024年的2.12mg/L,下降幅度接近35.76%.DO浓度从2003年的7.45mg/L升至2024年的8.81mg/L,上升幅度接近18.26%.TP浓度自2003年的0.15mg/L下降至2024年的0.07mg/L,下降幅度接近53.33%,整体呈明显波动下降趋势.而长江流域NH3-N、TP浓度线性回归分析结果显示,其R2均小于0.7,表明长江流域NH3-N、TP浓度波动变化较大.NH3-N浓度自2003年的0.94mg/L下降至2024年的0.19mg/L,下降幅度接近79.79%,虽然下降幅度较大,但其浓度随时间变化出现大幅的涨落,在2006年、2011年、以及2013年出现三个明显的峰值.TP浓度自2003年的0.15mg/L下降至2024年的0.07mg/L,下降幅度接近53.33%,与NH3-N类似,TP浓度在2003~2024年间出现明显的涨落,在2004年、2006年、以及2013年出现三个明显的峰值.以上变化趋势表明长江流域NH3-N、TP污染反复,治理难度大.综上,长江流域CODMn、DO、Pb三项水质指标自三峡水库蓄水以来改善效果显著,呈逐年向好趋势;而NH3-N、TP两项水质指标自三峡水库蓄水以来波动较大,污染反复,需持续治理.
长江流域季节性Kendall趋势检验结果如图7所示.长江流域WQImin整体呈显著上升趋势,各二级流域除汉江流域变化趋势不显著外,其余子流域均呈显著上升趋势,WQImin年平均变化率前三位分别为乌江(+1.54)、太湖水系(+1.52)以及岷沱江(+1.23).CODMn浓度全流域呈显著下降趋势,但下降幅度较小,其中乌江流域CODMn浓度呈显著下降趋势且下降幅度最大,而鄱阳湖水系CODMn浓度呈显著上升趋势,但上升幅度较小.鄱阳湖及其支流周边工农业聚集,人口稠密,工农业生产所产生的污水对流域水环境影响巨大[42],污水中含有的大量有机污染物使得鄱阳湖流域有机污染程度加深[48].加之三峡水库等大型水利枢纽工程蓄水运行后,对鄱阳湖水文情况造成影响,枯水期提前并且延长[49],水体中污染物浓度升高导致水质变差.NH3-N浓度全流域呈显著下降趋势,但下降幅度较小,其中乌江流域NH3-N浓度呈显著下降趋势且相较于其他二级流域下降幅度最大,太湖水系与岷沱江流域NH3-N浓度年全年平均变化率略高于除乌江流域以外的其他水系.长江流域整体TP浓度呈显著下降趋势,但年均变化率较小,各二级流域中只有乌江流域年均变化率超过0.01(mg/(L⋅a)),表明长江流域近二十余年来TP污染治理难度大,各子流域治理效果差异明显.长江流域整体DO浓度有显著上升趋势,除宜昌至湖口以及湖口以下干流外,其它二级流域同样表现出显著上升趋势,其中乌江流域DO浓度年全年平均变化率最高(+0.1).长江流域Pb浓度整体呈显著下降趋势,除乌江、汉江、洞庭湖与鄱阳湖水系外,其他二级流域均呈显著下降趋势,长江流域整体Pb浓度年平均变化率较高(-0.25),子流域中太湖水系(-0.41)变化最为突出.综上,除鄱阳湖水系CODMn浓度呈显著上升趋势外,长江各二级流域的主要水质指标时间变化趋势整体向好;乌江、岷沱江以及太湖水系NH3-N浓度下降幅度较大;而在TP指标的时间变化趋势上各二级流域年均变化率较小.现有研究表明长江TP污染多为面源污染[38,50],治理难度大.
图8所示,长江流域水质时空异质性显著.三峡水库蓄水以来,随时间推移,各二级流域水质不断好转.处在上游的岷沱江、乌江与处在下游的太湖水系污染突出,与其余二级流域形成明显对比.尤其是乌江流域,污染最为严重,2003年乌江流域WQImin年均值仅为37.7,2024年上升至64.上游金沙江流域水质状况整体趋势优于其他二级流域.长江上游的金沙江流域地势险峻、人口及工业数量较少,所造成的污染较轻.汉江流域水质一直保持良好水平,呈现出先上升再下降再上升的趋势.除去汉江流域外的长江其他二级流域,WQImin年均值都表现出显著增长趋势.
3.1 长江流域2003~2024年水质状况整体呈现良好状态,TP和NH3-N是长江流域近年来主要的水体污染物.各水质指标浓度分布空间差异显著.乌江、岷沱江、太湖水系是污染较严重的三个流域.
3.2 三峡水库蓄水以来,嘉陵江流域、宜宾至宜昌干流的TP浓度、乌江流域的TP和NH3-N浓度、以及洞庭湖与鄱阳湖水系的NH3-N浓度出现先升高后下降的趋势.
3.3 长江流域水质线性回归分析与季节性Kendall趋势检验结果显示,长江流域整体水质状况明显好转.线性回归分析表明NH3-N、TP两项水质指标波动较大,需持续治理.季节性Kendall趋势检验表明鄱阳湖水系CODMn浓度呈显著上升趋势,但上升幅度较小;乌江、岷沱江以及太湖水系NH3-N浓度降幅度较大,治理效果显著;长江流域整体各水质指标均有显著改善,但TP变化幅度较小,表明TP污染仍是未来长江流域污染治理的重点.
3.4 针对长江流域存在的TP和NH3-N污染问题,应从源头治理,整治磷化工污染,提高磷石膏资源利用率;改进工业污水处理工艺,提高污水处理能力;加大养殖行业污水处理监管力度;合理降低化肥施用量.
  • 湖北省自然科学基金三峡创新发展联合基金(2024AFD371)
  • 国家重点研发计划(2022YFC3203502)
  • 湖北省科技重大专项(2023BCA003)
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2025年第45卷第4期
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  • 接收时间:2024-09-30
  • 首发时间:2026-03-19
  • 出版时间:2025-04-20
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  • 收稿日期:2024-09-30
基金
湖北省自然科学基金三峡创新发展联合基金(2024AFD371)
国家重点研发计划(2022YFC3203502)
湖北省科技重大专项(2023BCA003)
作者信息
    1.中国地质大学(武汉)地理与信息工程学院,区域生态过程与环境演变湖北省重点实验室,湖北 武汉 430074
    2.湖北省生态环境科学研究院,湖北 武汉 430072
    3.生态环境部环境规划院,北京 100012

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鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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