Abstract

Multivariate techniques, like cluster analysis (CA) and principal component analysis (PCA), were used to evaluate the spatial and temporal variability of surface water quality in a large neotropical hydroelectric reservoir (Nova Ponte Reservoir). The dataset, obtained during the period of 1995–2011 from the Energy Company of Minas Gerais State (CEMIG), contains 14 parameters surveyed quarterly in 14 sites, at different depths. The CA grouped the 14 sites in three main groups: lotic sites, half of the photic zone sites and bottom sites. Statistical tests showed that only three parameters (total dissolved solids, nitrate and chemical oxygen demand) have no significant difference between cluster groups. The PCA results showed temporal changes of the water quality in all groups, illustrating modifications to the importance of the parameters over time. PCA also revealed the major causes of water deterioration from 1995 to 2005 were related to agricultural and livestock activities. Currently, the water quality parameters related to organic pollution are also highlighted. Generally, this study shows that possible optimization of the monitoring network should consider temporal variation of water quality parameters.

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