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首页> 外文期刊>International Journal of Environmental Research and Public Health >Assessment of Water Quality in a Subtropical Alpine Lake Using Multivariate Statistical Techniques and Geostatistical Mapping: A Case Study
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Assessment of Water Quality in a Subtropical Alpine Lake Using Multivariate Statistical Techniques and Geostatistical Mapping: A Case Study

机译：利用多元统计技术和地统计图评估亚热带高山湖泊水质：一个案例研究

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摘要

Concerns about the water quality in Yuan-Yang Lake (YYL), a shallow, subtropical alpine lake located in north-central Taiwan, has been rapidly increasing recently due to the natural and anthropogenic pollution. In order to understand the underlying physical and chemical processes as well as their associated spatial distribution in YYL, this study analyzes fourteen physico-chemical water quality parameters recorded at the eight sampling stations during 2008–2010 by using multivariate statistical techniques and a geostatistical method. Hierarchical clustering analysis (CA) is first applied to distinguish the three general water quality patterns among the stations, followed by the use of principle component analysis (PCA) and factor analysis (FA) to extract and recognize the major underlying factors contributing to the variations among the water quality measures. The spatial distribution of the identified major contributing factors is obtained by using a kriging method. Results show that four principal components i.e., nitrogen nutrients, meteorological factor, turbidity and nitrate factors, account for 65.52% of the total variance among the water quality parameters. The spatial distribution of principal components further confirms that nitrogen sources constitute an important pollutant contribution in the YYL.
机译：位于台湾中北部的浅亚热带高山湖泊元阳湖（YYL）的水质问题由于自然和人为污染而最近迅速增加。为了了解YYL的基本物理和化学过程及其相关的空间分布，本研究使用多元统计技术和地统计方法，分析了2008-2010年在八个采样站记录的十四个理化水质参数。首先应用层次聚类分析（CA）来区分站点之间的三种一般水质模式，然后使用主成分分析（PCA）和因子分析（FA）来提取和识别导致变化的主要潜在因素在水质措施中。通过使用克里金法获得已识别出的主要贡献因素的空间分布。结果表明，氮素养分，气象因子，浊度和硝酸盐因子这四个主要成分占水质参数总变化的65.52％。主要成分的空间分布进一步证实，氮源在YYL中构成重要的污染物贡献。

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