Assessment of water quality based on statistical analysis of physical-chemical, biomonitoring and land use data: Manso River supply reservoir.

Preserving the quality of surface water has become increasingly difficult due to the intensification of human activities in watersheds. This study assessed the water quality of the Manso River reservoir, which supplies water to Brazil's third largest metropolitan region. The integration of >10,000 secondary data, comprising physico-chemical parameters, metals and microbiological indicators, together with biomonitoring and land use and occupation data, were analyzed by using statistical tools, the Water Quality Index (WQI) and the Trophic State Index (TSI). The results showed higher concentrations for solids and metals (Fe and Mn) characteristic of local geochemistry and also related to the mining activity in the region. Parameters associated with organic pollution, such as total phosphorus and Escherichia coli, were also elevated, probably due to contamination by untreated or insufficiently treated domestic sewage. The water at the tributary watercourses presented worse quality, predominantly medium WQI, compared with the stations inside the reservoir (predominantly good WQI). The TSI indicated a predominance of ultra-oligotrophic conditions for stations located in the lotic environment and mesotrophic conditions for those located in the lentic environment. In general, the same pattern was observed for the occurrence of the phytoplankton and zooplankton classes, indicating the relationship between the degree of trophy and the composition of these groups. In quantitative terms, for phytoplankton, the Euchlorophyceae and Cyanophyceae classes stood out, mainly in the rainy period (summer), whereas for zooplankton, the Crustacea and Monogonta classes were dominant. Regarding land use and occupation in the reservoir sub-basin, the positive impact of the surrounding forest cover was observed. It was also identified the effect of seasonality on the quality of aquatic environments. The integrated evaluation of the results proved to be efficient in assessing the environmental conditions of the reservoir and the tributaries, providing information for better management of these water resources.

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.

The nonparametric test of Kruskal-Wallis and relative risk were used to evaluate surface water quality allowed to an identification of the most degraded water bodies in Piracicaba River and Paraopeba River basins, two important hydrographic basins in Brazil. Total manganese, dissolved iron, and fecal contamination indicator were considered the most relevant parameters for the characterization of water quality in the basins. The Peixe River, in Nova Era, and Pedras Creek, in Betim, were considered the most impacted water bodies in the Piracicaba River and Paraopeba River basins, respectively. The analysis of violations and the relative risk confirmed that both basins are subject to impacts resulting from economic activities. On comparing the relative risks, the Paraopeba River basin showed a higher risk of violation for 5-day biological oxygen demand (BOD5), total manganese, total phosphorus, total suspended solids, and turbidity, while the Piracicaba River basin showed a higher risk of violation for fecal contamination indicator. The release of domestic sewage and industrial effluents, mining activities, and diffuse pollution from agriculture and pasture areas were responsible for the surface water quality deterioration in these basins. The results show the need for investment in basic sanitation, improved treatment efficiency for industrial effluents, adequate soil management, riparian vegetation preservation, and environmental education actions.

Adequacy analysis of drinking water treatment technologies in regard to the parameter turbidity, considering the quality of natural waters treated by large-scale WTPs in Brazil.

This paper seeks to present a performance evaluation of large-scale water treatment plants and verify the adjustment of the treatment to the parameter turbidity of natural waters. Nonparametric and multivariate statistical tools were used to analyze raw water and treated water turbidity of a large on-line monitoring databank for the period from 2013 to 2015, from six large-scale treatment plants utilizing different technologies. Cluster analysis was able to differentiate adequately groups of treatment plants with similar raw and treated water quality. Considering the effluent turbidity as a marker parameter, the results indicated that selection of the technology to be applied must be well studied to always seek the best solution, and that other factors than only the raw water characteristics should be evaluated. It was also demonstrated that utilization of the same treatment technology does not always result in the same effluent quality, since there are many factors related to operation, maintenance, raw water variability, climatic interferences, and others.

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

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.

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

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.

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

Unfortunately, the original version of this article was published online with error. The Tables 3 and 4 data was mixed up. The corrected Tables 3 and 4 are shown in the next page. The original article has been corrected.

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

This study sought to evaluate and propose adjustments to the water quality monitoring network of surface freshwaters in the Paraopeba river basin (Minas Gerais, Brazil), using multivariate statistical methods. A total of 13,560 valid data were analyzed for 19 water quality parameters at 30 monitoring sites, over a period of 5 years (2008-2013). The cluster analysis grouped the monitoring sites in eight groups based on similarities of water quality characteristics. This analysis made it possible to detect the most relevant monitoring stations in the river basin. The principal components analysis associated with non-parametric tests and the analysis of violation of the standards prescribed by law, allowed for identifying the most relevant parameters which must be maintained in the network (thermotolerant coliforms, total manganese, and total phosphorus). The discharge of domestic sewage and industrial wastewater, that from mining activities and diffuse pollution from agriculture and pasture areas are the main sources of pollution responsible for the surface water quality deterioration in this basin. The BP073 monitoring site presents the most degraded water quality in the Paropeba river basin. The monitoring sites BP094 and BP092 are located geographically close and they measure similar water quality, so a possible assessment of the need to maintain only one of the two in the monitoring network is suggested. Therefore, multivariate analyses were efficient to assess the adequacy of the water quality monitoring network of the Paraopeba river basin, and it can be used in other watersheds.

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

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.

Qualidade das águas superficiais do Médio São Francisco após a implantação dos perímetros irrigados de Gorutuba/Lagoa Grande e Jaíba / Surface water quality of the Middle San Francisco river basin after the implementation of irrigated perimeters of Gorutuba/Lagoa Grande and Jaíba

RESUMO Os perímetros irrigados de Gorutuba/Lagoa Grande e Jaíba localizam-se na porção mineira do Médio São Francisco, totalizando cerca de 31.493 ha. Essa região possui potencial de contaminar os recursos hídricos em decorrência da urbanização, do desmatamento e da utilização de fertilizantes e de agrotóxicos nas atividades agrícolas. O objetivo desta pesquisa foi investigar o impacto da irrigação na qualidade das águas superficiais da região, utilizando fontes de dados secundários de monitoramento. Foram selecionadas nove estações de monitoramento da qualidade da água superficial na região, que representavam diferentes usos e ocupação do solo. A análise de cluster e o teste não paramétrico de Kruskal-Wallis, seguido do teste de comparações múltiplas, foram utilizados para avaliar comparativamente as estações de amostragem, bem como identificar os parâmetros que apresentaram comportamentos diferenciados entre essas estações. Apesar de não ter sido possível observar um padrão de contaminação em função da localização das estações, detectou-se que as estações localizadas ao longo do Rio São Francisco não apresentaram diferenças significativas entre si, ainda que o uso e ocupação do solo fossem diferentes. A tendência temporal dos constituintes foi verificada através da aplicação do teste de hipótese de estacionariedade de Spearman, o qual detectou que a maioria dos dados analisados foram não estacionários, apresentando tendência de elevação ou redução ao longo do período analisado. Após a aplicação desses testes estatísticos, concluiu-se que, de maneira geral, a implantação de perímetros irrigados causou baixo impacto na qualidade das águas na região, no período estudado, considerando os parâmetros analisados neste trabalho.

ABSTRACT The irrigation perimeters of Jaíba and Gorutuba/Lagoa Grande are located in the Minas Gerais portion of the Middle São Francisco river basin, Brazil, occupying an area of approximately 31,493 ha. This region has the potential to contaminate water resources as a result of urbanization, deforestation and the application of fertilizers and pesticides in agricultural activities. The aim of this research was to investigate the impact of irrigation on surface water quality in the region, using secondary monitoring. Nine monitoring stations were selected in the region, which represent the diferente uses and occupation of land. The cluster analysis and the nonparametric Kruskal-Wallis test, followed by multiple comparisons, were used to comparatively evaluate the sampling stations and to identify which parameters showed different behavior among these stations. Although it was not possible to observe a pattern of contamination due to the location of the stations, it was found that the stations located along the São Francisco river showed no significant differences, although the use and occupation of land were different. The temporal trend of the constituents was verified by applying the test of the hypothesis of stationarity Spearmant, which found that most of the data analyzed were not stationary, with a tendency of increase or decrease over the analysis period. After the application of these statistical tests, it was concluded that, in general, the implementation of irrigated perimeters caused low impact in water quality in the region, in the period studied, considering the parameters analyzed in this study.