Spatial and Seasonal Assessment of Water Quality in the Lobo Stream River Basin, Brazil Using Multivariate Statistical Techniques

被引:3
|
作者
Neves, Gabriela L. [1 ]
Guimaraes, Taina T. [2 ]
Anjinho, Phelipe S. [1 ]
Barbosa, Mariana A. G. A. [1 ]
Dos Santos, Allita R. [1 ]
Virgens Filho, Jorim S. [3 ]
Mauad, Frederico F. [1 ]
机构
[1] Univ Sao Paulo, Ctr Recursos Hidr & Estudos Ambientais, Ave Domingos Innocentini,Km 13, Itirapina, SP, Brazil
[2] Univ Vale Rio dos Sinos Unisinos, Ctr Ciencias Exatas & Tecnol, Ave Unisinos 950, BR-93022750 Sao Leopoldo, RS, Brazil
[3] Univ Estadual Ponta Grossa, Dept Matemat & Estat, Ave Carlos Cavalcanti 4748, BR-84030900 Ponta Grossa, PR, Brazil
关键词
anthropic activities; cluster analysis; correlation matrix; hydrological variables; principal component analysis; water pollution; ECOSYSTEM SERVICES; REGION; AREA;
D O I
10.1590/0001-3765202120210072
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
In view of the complexity of the processes associated to water quality, this study objective is to identify the main factors related to spatial and seasonal variability in water courses of the Lobo Stream River Basin. To this, multivariate statistical techniques were used. Data collection for water quality and streamflow variables were carried out monthly, from May 2018 to April 2019, at 10 monitoring points along basin's tributaries. The results show that, during the dry season, the main causes for water quality decrease are related to erosion process on the river margins, which is intensified by inadequate handling in livestock activities in some monitoring points. In the rainy season, the main causes are related to soil leaching in agricultural areas that increases the nitrogen compounds concentration and reduces water quality. However, in addition to this, it was noted that regardless the environmental conditions, the most impactful factor is the point pollution from the effluent discharge of Itirapina City sewage treatment plant, responsible for nutrient concentration increase, organic contamination, OD reduction, and, consequently, water quality deterioration. With this, the study shows how multivariate statistical analysis enables more relevant evaluation of water quality data variability and supports further studies in the basin.
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页数:20
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