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| 基金项目：江苏省地质勘查专项资金项目“高邮湖周边山水林田湖草综合地质调查评价”(苏财资环〔2019〕14号);江苏省科技厅自然科学基金项目“南京‘城市表面’径流碳汇效应研究”（BK20201507） |
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| 摘要： |
| 为查明江苏境内高邮湖及其周边出入湖河流水质分布特征，采用SPSS软件对湖区及周边25个水质样品监测数据（2020年8月）进行主成分分析，并采用水质标识指数法进行定性和定量评价。主成分分析将7个水质指标综合为3个主成分进行解释，解释率为75.62%，控制指标为总磷、氨氮、总氮和F-。单因子水质标识指数法将水质划分为Ⅳ类、Ⅴ类，综合指数评价水质均未超Ⅲ类，指数大小排序较为一致。分析结果表明：超标严重的指标（总磷、总氮）易掩盖其他水质指标信息，对水质类别判定影响较大；主成分分析法与水质标识指数法对主要污染指标的评价结论基本吻合，点位污染指数次序一致性较好；水质污染程度整体表现为入湖河流水系＞出湖河流水系＞高邮湖湖体，说明高邮湖入湖水系是湖区水质污染的重要因素。两种评价方法相结合，既能筛选出水质污染指标，又能在水质优劣排序基础上填补水质类别信息，使评价结果更加详实、可信。 |
| 关键词：主成分分析法 水质标识指数法 水质评价 相关性分析 高邮湖 |
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| Abstract: |
| In order to find out the water quality distribution characteristics of Gaoyou Lake and its surrounding rivers, the SPSS software was used to conduct principal component analysis on the monitoring data of 25 water quality samples (August 2020) in the lake and its surrounding areas, and the water quality identification index method was used for qualitative and quantitative evaluation. In principal component analysis, 7 water quality indexes were integrated into 3 principal components for interpretation, the interpretation rate was 75.62%, and the control indexes were total phosphorus, ammonia nitrogen, total nitrogen and F-. The single factor water quality labeling index method divides the water quality into class Ⅳ and Ⅴ, and the comprehensive index evaluation finds that the water quality in the study area is not higher than class Ⅲ, and the index size ranking is consistent. The results show that the indexes with serious exceedance (total phosphorus and total nitrogen) are easy to cover up the information of other water quality indexes, and have a great influence on the classification of water quality. The results of principal component analysis (PCA) and water quality identification index (WPI) are basically consistent, and the order of point pollution index is in good agreement. The degree of water pollution is as follows: river system entering the lake > river system exiting the lake > Gaoyou Lake body, indicating that the water system entering the lake is an important factor of water pollution in the lake. The combination of the two evaluation methods can not only screen out the water pollution index, but also fill in the water quality classification information on the basis of the quality ranking, so that the evaluation results are more detailed and reliable. |
| Keywords:principal component analysis water quality identification index water quality evaluation correlation analysis Gaoyou Lake |
| 金鹏，张斌，夏同法，等.基于主成分分析及水质标识指数法的高邮湖水质评价[J].地质学刊,2024,48(2):194-201 |
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