Multivariate statistical methods for recognition of water quality feature in Meiliang Bay of Taihu Lake(多元统计方法用于太湖梅梁湾水质特征识别)
旨在识别太湖梅梁湾水质特征，为水质保护、规划、管理、利用提供决策参考.研究利用太湖梅梁湾区域9个监测点数据，以主成分分析探讨主要污染来源；以聚类分析划分监测点类别并识别其空间相似性；以比对各类别监测点数据，讨论了污染物类别及浓度变化情况.结果显示梅梁湾水质主要受农业非点源、浮游植物生长、外源输入的有机悬浮物、含氮有机污染物及土壤土质5方面影响；梅梁湾区域9个监测点位划归为4类，即：河流入湖口、入湖口近岸、远离入湖口近岸及湖心点类；梅梁湾水质主要超标污染物为N、P，且各指标浓度变异不大.由此可见，太湖梅梁湾水质具有明确的空间分布与特征....
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | zho |
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Zhejiang University Press
2013-05-01
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| Series: | Zhejiang Daxue xuebao. Lixue ban |
| Subjects: | |
| Online Access: | https://doi.org/10.3785/j.issn.1008-9497.2013.03.014 |
| _version_ | 1797235900712747008 |
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| author | FANLiang-qian(范良千) WUZu-cheng(吴祖成) ZHANGQing-yu(张清宇) LIUQi(刘奇) YUBo(虞波) |
| author_facet | FANLiang-qian(范良千) WUZu-cheng(吴祖成) ZHANGQing-yu(张清宇) LIUQi(刘奇) YUBo(虞波) |
| author_sort | FANLiang-qian(范良千) |
| collection | DOAJ |
| description | 旨在识别太湖梅梁湾水质特征，为水质保护、规划、管理、利用提供决策参考.研究利用太湖梅梁湾区域9个监测点数据，以主成分分析探讨主要污染来源；以聚类分析划分监测点类别并识别其空间相似性；以比对各类别监测点数据，讨论了污染物类别及浓度变化情况.结果显示梅梁湾水质主要受农业非点源、浮游植物生长、外源输入的有机悬浮物、含氮有机污染物及土壤土质5方面影响；梅梁湾区域9个监测点位划归为4类，即：河流入湖口、入湖口近岸、远离入湖口近岸及湖心点类；梅梁湾水质主要超标污染物为N、P，且各指标浓度变异不大.由此可见，太湖梅梁湾水质具有明确的空间分布与特征. |
| first_indexed | 2024-04-24T16:55:19Z |
| format | Article |
| id | doaj.art-395f2c2d631248d19208b8a5c38b55ae |
| institution | Directory Open Access Journal |
| issn | 1008-9497 |
| language | zho |
| last_indexed | 2024-04-24T16:55:19Z |
| publishDate | 2013-05-01 |
| publisher | Zhejiang University Press |
| record_format | Article |
| series | Zhejiang Daxue xuebao. Lixue ban |
| spelling | doaj.art-395f2c2d631248d19208b8a5c38b55ae2024-03-29T01:58:32ZzhoZhejiang University PressZhejiang Daxue xuebao. Lixue ban1008-94972013-05-0140330831310.3785/j.issn.1008-9497.2013.03.014Multivariate statistical methods for recognition of water quality feature in Meiliang Bay of Taihu Lake(多元统计方法用于太湖梅梁湾水质特征识别)FANLiang-qian(范良千)0WUZu-cheng(吴祖成)1ZHANGQing-yu(张清宇)2LIUQi(刘奇)3YUBo(虞波)4 1. Department of Environment Engineering, Zhejiang University, Hangzhou 310058, China( 1.浙江大学 环境工程系，浙江 杭州 310058) 1. Department of Environment Engineering, Zhejiang University, Hangzhou 310058, China( 1.浙江大学 环境工程系，浙江 杭州 310058) 1. Department of Environment Engineering, Zhejiang University, Hangzhou 310058, China( 1.浙江大学 环境工程系，浙江 杭州 310058) 1. Department of Environment Engineering, Zhejiang University, Hangzhou 310058, China( 1.浙江大学 环境工程系，浙江 杭州 310058) 1. Department of Environment Engineering, Zhejiang University, Hangzhou 310058, China( 1.浙江大学 环境工程系，浙江 杭州 310058)旨在识别太湖梅梁湾水质特征，为水质保护、规划、管理、利用提供决策参考.研究利用太湖梅梁湾区域9个监测点数据，以主成分分析探讨主要污染来源；以聚类分析划分监测点类别并识别其空间相似性；以比对各类别监测点数据，讨论了污染物类别及浓度变化情况.结果显示梅梁湾水质主要受农业非点源、浮游植物生长、外源输入的有机悬浮物、含氮有机污染物及土壤土质5方面影响；梅梁湾区域9个监测点位划归为4类，即：河流入湖口、入湖口近岸、远离入湖口近岸及湖心点类；梅梁湾水质主要超标污染物为N、P，且各指标浓度变异不大.由此可见，太湖梅梁湾水质具有明确的空间分布与特征.https://doi.org/10.3785/j.issn.1008-9497.2013.03.014水质多元统计主成分分析聚类分析 |
| spellingShingle | FANLiang-qian(范良千) WUZu-cheng(吴祖成) ZHANGQing-yu(张清宇) LIUQi(刘奇) YUBo(虞波) Multivariate statistical methods for recognition of water quality feature in Meiliang Bay of Taihu Lake(多元统计方法用于太湖梅梁湾水质特征识别) Zhejiang Daxue xuebao. Lixue ban 水质 多元统计 主成分分析 聚类分析 |
| title | Multivariate statistical methods for recognition of water quality feature in Meiliang Bay of Taihu Lake(多元统计方法用于太湖梅梁湾水质特征识别) |
| title_full | Multivariate statistical methods for recognition of water quality feature in Meiliang Bay of Taihu Lake(多元统计方法用于太湖梅梁湾水质特征识别) |
| title_fullStr | Multivariate statistical methods for recognition of water quality feature in Meiliang Bay of Taihu Lake(多元统计方法用于太湖梅梁湾水质特征识别) |
| title_full_unstemmed | Multivariate statistical methods for recognition of water quality feature in Meiliang Bay of Taihu Lake(多元统计方法用于太湖梅梁湾水质特征识别) |
| title_short | Multivariate statistical methods for recognition of water quality feature in Meiliang Bay of Taihu Lake(多元统计方法用于太湖梅梁湾水质特征识别) |
| title_sort | multivariate statistical methods for recognition of water quality feature in meiliang bay of taihu lake 多元统计方法用于太湖梅梁湾水质特征识别 |
| topic | 水质 多元统计 主成分分析 聚类分析 |
| url | https://doi.org/10.3785/j.issn.1008-9497.2013.03.014 |
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