Literature DB >> 29086029

Evaluation of violations in water quality standards in the monitoring network of São Francisco River basin, the third largest in Brazil.

Elizângela Pinheiro da Costa1, Carolina Cristiane Pinto2, Ana Luiza Cunha Soares1, Livia Duarte Ventura Melo1, Sílvia Maria Alves Corrêa Oliveira3.   

Abstract

The São Francisco River is the largest river located entirely within Brazil, and water scarcity problems have been a major concern of Brazilian society and government. Water quality issues are also a concern and have worsened with the recent intensification of urbanization and industrialization. In this study, violations to water quality standards established by local legislation were calculated as a percentage for 26 selected parameters over a monitoring period of 14 years. The violation percentages were analyzed spatially using the Kruskal-Wallis test, followed by multiple comparison analysis. Temporal analysis was performed using the Mann-Kendall test and Spearman correlation. Some parameters could be identified as cause for concern due to high violation levels, such as the fecal coliform indicator (FCI) and phosphorus-both related to domestic and effluent disposal without treatment or with insufficient treatment-and color, turbidity, manganese, and total suspended solids-which can be affected by erosive processes of natural and anthropogenic causes. The study found that these violations are concentrated in the most urbanized and industrialized areas of the basin. Some metallic parameters, such as iron and arsenic violations, may be related to mining activities in the rich soil of the Iron Quadrangle area located within the Minas Gerais State. Trend analysis results indicated that most monitoring stations did not have significant modification (elevation or reduction) trends over time, which, together with the high violation percentages, might indicate the maintenance of a scenario of constant pressure upon water resources, in particular in those more urbanized areas.

Entities:  

Keywords:  Brazil; Mann-Kendall; Monitoring network; São Francisco River basin; Trend analysis; Water quality standards

Mesh:

Substances:

Year:  2017        PMID: 29086029     DOI: 10.1007/s10661-017-6266-y

Source DB:  PubMed          Journal:  Environ Monit Assess        ISSN: 0167-6369            Impact factor:   2.513


  10 in total

1.  Long-term variations of water quality parameters in the Maroon River, Iran.

Authors:  Hossein Tabari; Safar Marofi; Mohammad Ahmadi
Journal:  Environ Monit Assess       Date:  2010-08-11       Impact factor: 2.513

2.  Temporal trend and source apportionment of water pollution in different functional zones of Qiantang River, China.

Authors:  Shiliang Su; Dan Li; Qi Zhang; Rui Xiao; Fang Huang; Jiaping Wu
Journal:  Water Res       Date:  2010-11-30       Impact factor: 11.236

3.  Multi-scale analysis of oxygen demand trends in an urbanizing Oregon watershed, USA.

Authors:  Mike Boeder; Heejun Chang
Journal:  J Environ Manage       Date:  2008-01-16       Impact factor: 6.789

Review 4.  Statistical approaches used to assess and redesign surface water-quality-monitoring networks.

Authors:  B Khalil; T B M J Ouarda
Journal:  J Environ Monit       Date:  2009-10-05

5.  Geochemistry and spatial variability of metal(loid) concentrations in soils of the state of Minas Gerais, Brazil.

Authors:  José João Lelis Leal de Souza; Walter Antônio Pereira Abrahão; Jaime Wilson Vargas de Mello; Juscimar da Silva; Liovando Marciano da Costa; Teógenes Senna de Oliveira
Journal:  Sci Total Environ       Date:  2014-10-18       Impact factor: 7.963

Review 6.  Phosphorus in rivers--ecology and management.

Authors:  Chris P Mainston; William Parr
Journal:  Sci Total Environ       Date:  2002-01-23       Impact factor: 7.963

7.  Spatial analysis of water quality trends in the Han River basin, South Korea.

Authors:  Heejun Chang
Journal:  Water Res       Date:  2008-04-15       Impact factor: 11.236

8.  Investigation of temporal trends in hydrochemical quality of surface water in Western Turkey.

Authors:  Hülya Boyacioglu; Hayal Boyacioglu
Journal:  Bull Environ Contam Toxicol       Date:  2008-05-18       Impact factor: 2.151

9.  Water quality variation in the highly disturbed Huai River Basin, China from 1994 to 2005 by multi-statistical analyses.

Authors:  Xiaoyan Zhai; Jun Xia; Yongyong Zhang
Journal:  Sci Total Environ       Date:  2014-08-08       Impact factor: 7.963

10.  Hydrological influences on the water quality trends in Tamiraparani Basin, South India.

Authors:  S Ravichandran
Journal:  Environ Monit Assess       Date:  2003-09       Impact factor: 2.513

  10 in total
  4 in total

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

Authors:  Giovanna Moura Calazans; Carolina Cristiane Pinto; Elizângela Pinheiro da Costa; Anna Flávia Perini; Sílvia Corrêa Oliveira
Journal:  Environ Monit Assess       Date:  2018-11-15       Impact factor: 2.513

2.  The use of multivariate statistical methods for optimization of the surface water quality network monitoring in the Paraopeba river basin, Brazil.

Authors:  Giovanna Moura Calazans; Carolina Cristiane Pinto; Elizângela Pinheiro da Costa; Anna Flávia Perini; Sílvia Corrêa Oliveira
Journal:  Environ Monit Assess       Date:  2018-07-28       Impact factor: 2.513

3.  Impacts of anthropogenic activities and calculation of the relative risk of violating surface water quality standards established by environmental legislation: a case study from the Piracicaba and Paraopeba river basins, Brazil.

Authors:  Ana Luiza Cunha Soares; Carolina Cristiane Pinto; Sílvia Corrêa Oliveira
Journal:  Environ Sci Pollut Res Int       Date:  2020-02-10       Impact factor: 4.223

4.  Methodological proposal for the allocation of water quality monitoring stations using strategic decision analysis.

Authors:  Micael de Souza Fraga; Demetrius David da Silva; Abrahão Alexandre Alden Elesbon; Hugo Alexandre Soares Guedes
Journal:  Environ Monit Assess       Date:  2019-11-28       Impact factor: 2.513

  4 in total

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