To ensure a safe drinking water supply, it is necessary to protect water quality. To classify the suitability of the Orós Reservoir (Northeast of Brazil) water for human consumption, a Water Quality Index (WQI) was enhanced and refined through a Principal Component Analysis (PCA). Samples were collected bi-monthly at seven points (P1 - P7) from July 2009 to July 2011. Samples were analysed for 29 physico-chemical attributes and 4 macroinvertebrate metrics associated with the macrophytes Pistia stratiotes and Eichhornia crassipes. PCA allowed us to reduce the number of attributes from 33 to 12, and 85.32% of the variance was explained in five dimensions (C1 - C5). Components C1 and C3 were related to water-soluble salts and reflect the weathering process, while C2 was related to surface runoff. C4 was associated with macroinvertebrate diversity, represented by ten pollution-resistant families. C5 was related to the nutrient phosphorus, an indicator of the degree of eutrophication. The mean values for the WQIs ranged from 49 to 65 (rated as fair), indicating that water can be used for human consumption after treatment. The lowest values for the WQI were recorded at the entry points to the reservoir (P3, P1, P5, and P4), while the best WQIs were recorded at the exit points (P6 and P7), highlighting the reservoir's purification ability. The proposed WQI adequately expressed water quality, and can be used for monitoring surface water quality.

Throughout human history, water has undergone changes in quality. This problem is more serious in dry areas, where there is a natural water deficit due to climatic factors. The aims of this study, therefore, were (i) to verify correlations between physical attributes, chemical attributes and biological metrics and (ii) from the biological attributes, to verify the similarity between different points of a body of water in a tropical semi-arid region. Samples were collected every 2 months, from July 2009 to July 2011, at seven points. Four physical attributes, five chemical attributes and four biological metrics were investigated. To identify the correlations between the physicochemical properties and the biological metrics, hierarchical cluster analysis (HCA) and canonical correlation analysis (CCA) were applied. Nine classes of phytoplankton were identified, with the predominance of species of cyanobacteria, and ten families of macroinvertebrates. The use of HCA resulted in the formation of three similar groups, showing that it was possible to reduce the number of sampling points when monitoring water quality with a consequent reduction in cost. Group I was formed from the waters at the high end of the reservoir (points P1, P2 and P3), group II by the waters from the middle third (points P4 and P5), and group III by the waters from the lower part of the reservoir (points P6 and P7). Richness of the phytoplanktons Cyanophyceae, Chorophyceae and Bacillariophyceae was the attribute which determined dissimilarity in water quality. Using CCA, it was possible to identify the spatial variability of the physicochemical attributes (TSS, TKN, nitrate and total phosphorus) that most influence the metrics of the macroinvertebrates and phytoplankton present in the water. Low macroinvertebrate diversity, with a predominance of indicator families for deterioration in water quality, and the composition of phytoplankton showing a predominance of cyanobacteria, suggests greater attention to the management of water resources.

Intensification of the eutrophication process in surface water leads to an increase in the intensity and frequency of cyanobacterial blooms, compromising the availability of drinking water. Therefore, the aim of this study was to investigate the spatio-temporal dynamics of cyanobacteria and identify the most important nutrients for such dynamics in a semiarid artificial lake, the Orós reservoir, in north-eastern Brazil. Seventy-seven water samples were collected in 11 campaigns (six during the dry season and five during the rainy season) from seven points. The attributes under investigation were the Secchi transparency, turbidity, pH, apparent colour, electrical conductivity, total solids, total phosphorus, soluble orthophosphate content, total Kjeldahl nitrogen, ammonia content, nitrate content, and cyanobacteria dynamics, resulting in a total of 924 samples (number of campaigns × number of points × number of attributes). Principal component analysis and cluster analysis were used to investigate the significance and determinant attributes of the spatio-temporal dynamics of cyanobacteria. Of the 17 species of cyanobacteria identified, 10 accounted for 72.47% of the total accumulated variance. During the rainy season, four homogeneous groups of cyanobacteria formed, whereas during the dry season, only three groups formed. The greatest concentrations occurred during the dry season, notably for Aphanocapsa spp., Cylindrospermopsis sp., and Geitlerinema sp., which are potentially toxic and show a greater affinity to the physical attributes of water. Climate seasonality was decisive in the spatio-temporal dynamics of cyanobacteria, and high transparency values limited excessive proliferation of the dominant species.

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