Using multivariate techniques as a strategy to guide optimization projects for the surface water quality network monitoring in the Velhas river basin, Brazil

被引:20
|
作者
Calazans, Giovanna Moura [1 ]
Pinto, Carolina Cristiane [1 ]
da Costa, Elizangela Pinheiro [1 ]
Perini, Anna Flavia [1 ]
Oliveira, Silvia Correa [1 ]
机构
[1] Univ Fed Minas Gerais, Escola Engn, Campus Pampulha,Av Antonio Carlos 6627,Bloco 1, BR-3127090 Belo Horizonte, MG, Brazil
关键词
Cluster analysis; Principal component analysis; Factorial analysis; Network monitoring assessment; Brazilian watershed; STATISTICAL TECHNIQUES; DESIGN; INDIA;
D O I
10.1007/s10661-018-7099-z
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Surface water quality monitoring networks are usually deployed and rarely re-evaluated with regard to their effectiveness. In this sense, this work sought to evaluate and to guide optimization projects for the water quality monitoring network of the Velhas river basin, using multivariate statistical methods. The cluster, principal components, and factorial analyses, associated with non-parametric tests and the analysis of violation to the standards set recommended by legislation, identified the most relevant water quality parameters and monitoring sites, and evaluated the sampling frequency. Thermotolerant coliforms, total arsenic, and total phosphorus were considered the most relevant parameters for characterization of water quality in the river basin. The monitoring sites BV156, BV141, BV142, BV150, BV137, and BV153 were considered priorities for maintenance of the network. The multivariate statistical analysis showed the importance of a monthly sampling frequency, specifically the parameters considered most important.
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收藏
页数:15
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