不同水质评价方法在通江湖泊中的适用性

殷雪妍; 严广寒; 汪星; 黄代中; 李利强

doi:10.12153/j.issn.1674-991X.20220397

不同水质评价方法在通江湖泊中的适用性—以洞庭湖为例

doi: 10.12153/j.issn.1674-991X.20220397

殷雪妍^{1, 2, 3,},
严广寒^{1, 2, 3},
汪星^{1, 2, 3, ,},
黄代中⁴,
李利强⁴

1.
湖泊水污染治理与生态修复技术国家工程实验室, 中国环境科学研究院
2.
国家环境保护饮用水水源地保护重点实验室, 中国环境科学研究院
3.
国家环境保护洞庭湖科学观测研究站, 中国环境科学研究院
4.
湖南省洞庭湖生态环境监测中心

基金项目: 社会公益类科研机构改革专项项目（2020-JY-009）；洞庭湖江湖生态监测重点站项目（JJ2021）

详细信息

作者简介:
殷雪妍（1994—），女，工程师，研究方向为湖库生态保护与修复，yinxy@craes.org.cn

通讯作者:
汪星（1983—），男，副研究员，研究方向为湖库富营养化控制与治理，wangxing@craes.org.cn

中图分类号: X524
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- 被引次数: 0
出版历程
- 收稿日期: 2022-04-26

Applicability of different water quality evaluation methods in river-connected lakes: a case study of Dongting Lake

YIN Xueyan^{1, 2, 3
,},
YAN Guanghan^{1, 2, 3},
WANG Xing^{1, 2, 3
, ,},
HUANG Daizhong⁴,
LI Liqiang⁴

1.
National Engineering Laboratory for Lake Pollution Control and Ecological Restoration, Chinese Research Academy of Environmental Sciences
2.
State Environmental Protection Key Laboratory of Drinking Water Source Protection, Chinese Research Academy of Environmental Sciences
3.
State Environmental Protection Scientific Observation and Research Station for Lake Dongting, Chinese Research Academy of Environmental Sciences
4.
Ecological and Environmental Monitoring Center of Dongting Lake, Hunan Province

摘要

摘要:
三峡工程运行使得通江湖泊与长江原有的江湖关系发生明显变化，进而影响通江湖泊水环境，如何有效评价长江流域最大的通江湖泊洞庭湖的水质显得尤为重要。在洞庭湖湖区设置15个采样点，选取9项水质参数，运用单因子指数法、主成分分析（PCA）法、内梅罗污染指数法及Shannon-Weaver多样性指数法对2019年1—12月洞庭湖水质进行综合评价。结果显示，单因子指数法可快速准确评价水质类别，内梅罗污染指数法计算简单并在水质评价中得到广泛应用，但这2种方法均无法准确给出不同采样点间受污染程度的差异，而Shannon-Weaver多样性指数评价结果与部分采样点实际情况不符。综合考虑不同评价方法的适用性和准确性，推荐使用PCA法开展洞庭湖水质评价，该方法既能反映各主要污染指标及其贡献率，也能对不同区域水体受污染程度进行排序，且评价结果客观实际，更适用于洞庭湖区域的水质评价工作。但是在水质评价管理工作中，建议结合单因子指数法对水质类别进行判定，以保证管理的实效性。
- 洞庭湖 /
- 水质评价 /
- 单因子指数法 /
- 内梅罗污染指数法 /
- 主成分分析(PCA)法
Abstract:
The operation of the Three Gorges Project has significantly changed the relationship between the river-connected lakes and the Yangtze River, thus affecting the water environment of the river-connected lakes. It was particularly important to effectively evaluate the water quality of Dongting Lake, the largest river-connected Lake in the Yangtze River basin. In 2019, monthly monitoring data were collected at 15 sampling sites in Dongting Lake, including nine water quality factors. The single factor index method, principal components analysis (PCA) method, Nemero pollution index method and Shannon-Weaver biodiversity index method were used to evaluate the water quality of Dongting Lake. The single factor index method could quickly and accurately evaluate water quality categories, and the Nemerow pollution index method was simple to calculate and widely used in water quality evaluation. However, the two methods could not accurately give the difference of pollution degree between different sampling points, and the Shannon-Weaver diversity index evaluation results were not consistent with the actual situation of some sampling points. To comprehensively consider the applicability and accuracy of different evaluation methods, it was recommended to use the PCA method to carry out Dongting Lake water quality evaluation. PCA method could not only reflect the main pollution index and its contribution rate, but also rank the pollution degree of different regional water bodies, and the evaluation results were objective and practical, so it was more suitable for the water quality evaluation of Dongting Lake region. However, in the daily work of water quality evaluation management, it was suggested that the single factor index method should be combined to determine the water quality categories, so as to ensure the effectiveness of management.
- Dongting Lake /
- water quality evaluation /
- single factor index method /
- Nemero pollution index method /
- principal components analysis (PCA) method

HTML全文

图 1 洞庭湖采样点分布

Figure 1. Distribution of sampling sites in Dongting Lake

下载: 全尺寸图片幻灯片

图 2 2019年洞庭湖各采样点I变化

Figure 2. Nemerow pollution index of Dongting Lake sampling sites in 2019

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图 3 2019年不同水期各采样点主成分得分分布

Figure 3. Principal component score distribution of each sampling section in different periods in 2019

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图 4 2019年洞庭湖各采样点的主成分得分分布

Figure 4. Spatial distribution of principal component scores in sampling sections of Dongting Lake in 2019

下载: 全尺寸图片幻灯片

图 5 2019年洞庭湖PCA评价结果

Figure 5. Evaluation results of Dongting Lake by PCA in 2019

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图 6 2019年不同水期洞庭湖各采样点H'变化

Figure 6. Changes of H' at different water quality monitoring sections of Dongting Lake in different periods in 2019

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图 7 内梅罗污染指数法与PCA法评价结果线性相关性

Figure 7. Linear correlation between evaluation results of Nemero pollution index method and PCA method

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表 1 2019年洞庭湖各采样点水质单因子指数评价结果（TN不参与评价）

Table 1. Single factor evaluation results of water quality at different sampling points in Dongting Lake in 2019 (TN was not involved in the evaluation)

湖区	采样点	枯水期		平水期		丰水期		年均值
湖区	采样点	水质类别	主要污染物	水质类别	主要污染物	水质类别	主要污染物	水质类别	主要污染物
入湖河流	S1	Ⅱ		Ⅱ		Ⅱ		Ⅱ
	S2	Ⅱ		Ⅱ		Ⅱ		Ⅱ
	S3	Ⅱ		Ⅱ		Ⅱ		Ⅱ
	S4	Ⅱ		Ⅱ		Ⅱ		Ⅱ
西洞庭湖	S5	Ⅳ	TP	Ⅳ	TP	Ⅳ	TP	Ⅳ	TP
	S6	Ⅲ	TP	Ⅳ	TP	Ⅳ	TP	Ⅳ	TP
	S7	Ⅳ	TP	Ⅳ	TP	Ⅳ	TP	Ⅳ	TP
	S8	Ⅲ	TP	Ⅳ	TP	Ⅳ	TP	Ⅳ	TP
南洞庭湖	S9	Ⅳ	TP	Ⅳ	TP	Ⅳ	TP	Ⅳ	TP
南洞庭湖	S10	Ⅳ	TP	Ⅳ	TP	Ⅳ	TP	Ⅳ	TP
东洞庭湖	S11	Ⅳ	TP	Ⅳ	TP	Ⅳ	TP	Ⅳ	TP
	S12	Ⅳ	TP	Ⅳ	TP	Ⅳ	TP	Ⅳ	TP
	S13	Ⅳ	TP	Ⅳ	TP	Ⅳ	TP	Ⅳ	TP
	S14	Ⅳ	TP、COD_Cr	Ⅴ	TP、 COD_Cr、 COD_Mn	Ⅴ	TP、COD_Cr、COD_Mn	Ⅳ	TP、COD_Cr
出湖口	S15	Ⅳ	TP	Ⅳ	TP	Ⅳ	TP	Ⅳ	TP

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表 2 2019年洞庭湖各采样点TN和TP评价结果

Table 2. TN and TP evaluation results of sampling sites in Dongting Lake in 2019

水期	主要污染物	不同水质类别对应的采样点
水期	主要污染物	Ⅲ类	Ⅳ类	Ⅴ类	劣Ⅴ类
年均值	TN		S4、S7	S1、S5、S6、S8~S15	S2
年均值	TP		S5~S15
枯水期	TN		S7	S3~S5、S8、S9、S11~S15	S1、S2、S10
枯水期	TP	S6、S8	S5、S7、S9~S15
平水期	TN		S3、S5~S9、S13	S1、S4、S10、S11、S14、S15	S2
平水期	TP		S5~S7、S9~S13、S15	S8、S14
丰水期	TN		S1、S4、S7、S13、S15	S2、S3、S5、S6、S8~S12、S14
丰水期	TP		S5~S13、S15	S14

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表 3 不同水期旋转后的因子载荷量

Table 3. Rotated component matrix in different water periods

因子	丰水期			平水期			枯水期
因子	PC1	PC2	PC3	PC1	PC2	PC3	PC1	PC2	PC3
水温	−0.86	−0.16	−0.30	−0.83	0.05	0.44	−0.11	0.59	0.72
pH	0.24	0.73	0.52	0.17	−0.83	0.45	−0.40	0.46	0.33
DO浓度	0.79	−0.22	−0.33	0.82	−0.21	0.43	−0.61	0.55	−0.17
COD_Mn	0.95	−0.18	−0.10	0.94	0.23	0.09	0.79	0.57	−0.12
COD_Cr	0.94	−0.18	−0.12	0.95	0.15	0.11	0.71	0.68	−0.03
BOD₅	0.89	0.21	0.18	0.88	−0.26	0.04	0.49	0.60	−0.53
NH₃-N浓度	−0.11	−0.45	0.72	0.89	0.23	0.12	0.77	−0.13	0.44
TP浓度	0.94	−0.05	0.02	0.74	0.19	−0.38	0.54	−0.47	−0.37
TN浓度	0.22	0.70	−0.37	−0.18	0.69	0.66	0.68	−0.41	0.50
特征值	4.88	1.41	1.18	5.31	1.45	1.19	3.25	2.41	1.53
方差百分比/%	54.27	15.68	13.12	59.04	16.12	13.23	36.13	26.73	16.99
累计方差百分比/%	54.27	69.95	83.07	59.04	75.16	88.39	36.13	62.86	79.85
注：黑体数字为环境因子在不同主成分中的载荷超过0.70的值。

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表 4 年均值旋转后的因子载荷量

Table 4. Rotated component load matrix of annual mean

项目	PC1	PC2
水温	−0.86	0.21
pH	0.25	−0.74
DO浓度	0.77	−0.23
COD_Mn	0.96	0.17
COD_Cr	0.98	0.14
BOD₅	0.92	−0.23
NH₃-N浓度	0.61	0.59
TN浓度	−0.06	0.82
TP浓度	0.82	0.17
特征值	5.15	1.79
方差百分比/%	57.27	19.94
累计方差百分比/%	57.27	77.21
注：同表3。

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