Monitoring water quality of the Sergipe River basin: an evaluation using multivariate data analysis

被引：15

作者：

Hora Alves, Jose do Patrocinio ^{[1
]}

Fonseca, Lucas Cruz ^{[2
]}

Alves Chielle, Raisa de Siqueira ^{[3
]}

Barreto Macedo, Lucia Calumby ^{[2
]}

机构：

[1] Univ Fed Sergipe, Sao Cristovao, SE, Brazil

[2] Inst Tecnol & Pesquisas Estado Sergipe, Aracaju, SE, Brazil

[3] Univ Fed Ceara, Fortaleza, CE, Brazil

来源：

RBRH-REVISTA BRASILEIRA DE RECURSOS HIDRICOS | 2018年 / 23卷

关键词：

Monitoring; Water quality; Principal component analysis; Cluster analysis; Sergipe River;

D O I：

10.1590/2318-0331.231820170124

中图分类号：

TV21 [水资源调查与水利规划];

学科分类号：

081501 ;

摘要：

This study evaluated the efficiency of the water quality monitoring network of the Sergipe river basin, using multivariate data analysis, such as principal component analysis (PCA) and hierarchical cluster analysis (HCA). The PCA was applied to a data matrix consisting of 12 sampling stations and mean concentrations of 23 water quality parameters, obtained in four sampling campaigns from June/2013 to November/2015. All 12 sampling stations were considered as main (weight> 0.7) and therefore should remain in the monitoring program. The PCA pointed out that of the 23 measured parameters, only 16 are essential for water quality assessment, in the dry period and 17 in the rainy season. The HCA separated the stations of the monitoring network in 4 groups according to the water quality characteristics, considering the natural and anthropogenic impacts. The main impacts were originated from natural sources (mineral constituents) and the anthropogenic contributions were associated with urban input, sewage, industrial dumps and surface runoff from agricultural areas.

引用

页数：12