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Assessment of spatial variations in the surface water quality of the Velhas River Basin, Brazil, using multivariate statistical analysis and nonparametric statistics

  • Carolina Cristiane Pinto
  • Giovanna Moura Calazans
  • Sílvia Corrêa OliveiraEmail author
Article

Abstract

The Velhas River sub-basin, which is located in the third-largest river basin in Brazil (São Francisco), is in an advanced state of degradation. In this work, the surface water quality of the Velhas River Basin was studied at 65 monitoring sites; 16 water quality parameters were sampled quarterly for 11 years (2008 to 2013). Cluster analysis (CA) and a nonparametric Kruskal–Wallis test were associated with the analysis of violations to water quality standards to interpret the water quality data set from the Velhas River Basin and assess its spatial variations. The CA grouped the 65 monitoring sites into four groups. The Kruskal–Wallis test identified significant differences (p < 0.05) between the groups formed by CA. The results show that watercourses located in the upper region of the Velhas River Basin are more affected by the release of industrial effluent and domestic sewage, and the lower region is more affected by diffuse pollution and erosion. This association between multivariate statistical techniques and nonparametric tests was effective for the classification and processing of large water quality datasets and the identification of major differences between water pollution sources in the basin. Therefore, these results provide an understanding of the factors affecting water quality in the Velhas River Basin. The results can aid in decision-making by water managers and these methods can be applied to other river basins.

Keywords

Water quality assessment Multivariate techniques Monitoring network Velhas River Basin 

Notes

Acknowledgements

We would like to thank the Institute of Water Management ofMinas Gerais (Igam) and its technical team for providing the monitoring data and for the constant support and service.

Funding information

This study received financial supports from the National Counsel of Technological and Scientific Development (CNPq), the Coordination for the Improvement of Higher Education Personnel (CAPES), and the Foundation of Support Research of the State of Minas Gerais (FAPEMIG).

Supplementary material

10661_2019_7281_MOESM1_ESM.pdf (291 kb)
ESM 1 (PDF 291 kb)

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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Carolina Cristiane Pinto
    • 1
  • Giovanna Moura Calazans
    • 1
  • Sílvia Corrêa Oliveira
    • 1
    Email author
  1. 1.Escola de EngenhariaUniversidade Federal de Minas GeraisBelo HorizonteBrazil

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