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利用多元统计技术和地质统计学制图评估亚热带高山湖泊水质:案例研究。

Assessment of water quality in a subtropical alpine lake using multivariate statistical techniques and geostatistical mapping: a case study.

机构信息

Department of Civil Disaster Prevention Engineering, National United University, Miao-Li 36003, Taiwan.

出版信息

Int J Environ Res Public Health. 2011 Apr;8(4):1126-40. doi: 10.3390/ijerph8041126. Epub 2011 Apr 15.

Abstract

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.

摘要

由于自然和人为污染,位于台湾中北部的浅水亚热带高山湖泊——鸳鸯湖的水质问题近来受到了广泛关注。为了了解湖泊底层的物理化学过程及其在鸳鸯湖的相关空间分布,本研究采用多元统计技术和地质统计方法,分析了 2008 年至 2010 年在 8 个采样点记录的 14 个理化水质参数。首先应用层次聚类分析(CA)区分了站点之间的三种一般水质模式,然后应用主成分分析(PCA)和因子分析(FA)提取并识别对水质变化有较大影响的主要因素。利用克立格法获得了所识别的主要贡献因素的空间分布。结果表明,氮营养物、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方差的 65.52%。主要成分的空间分布进一步证实了氮源是鸳鸯湖的重要污染物来源之一。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/eba0/3118881/23f1a820f827/ijerph-08-01126f1.jpg

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