Evaluation of significant sources influencing the variation of water quality of Kandla creek, Gulf of Katchchh, using PCA

被引：30

作者：

Dalal, S. G. ^{[1
]}

Shirodkar, P. V. ^{[1
]}

Jagtap, T. G. ^{[1
]}

Naik, B. G. ^{[1
]}

Rao, G. S. ^{[2
]}

机构：

[1] Natl Inst Oceanog, Panaji 403004, Goa, India

[2] Kandla Port Trust, Gandhidham, Gujarat, India

来源：

ENVIRONMENTAL MONITORING AND ASSESSMENT | 2010年 / 163卷 / 1-4期

关键词：

Water quality; PCA; Significant sources; Kandla creek; PRINCIPAL COMPONENT ANALYSIS; RIVER WATER;

D O I：

10.1007/s10661-009-0815-y

中图分类号：

X [环境科学、安全科学];

学科分类号：

08 ; 0830 ;

摘要：

To evaluate the significant sources contributing to water quality parameters, we used principal component analysis (PCA) for the interpretation of a large complex data matrix obtained from the Kandla creek environmental monitoring program. The data set consists of analytical results of a seasonal sampling survey conducted over 2 years at four stations. PCA indicates five principal components to be responsible for the data structure and explains 76% of the total variance of the data set. The study stresses the need to include new parameters in the analysis in order to make the interpretation of principal components more meaningful. The PCA could be applied as a useful tool to eliminate multi-collinearity problems and to remove the indirect effect of parameters.

引用

页码：49 / 56

页数：8

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