Qualidade da água do reservatório Poção da Ribeira : uma avaliação com base em técnicas estatísticas multivariadas e nos processos geoquímicos de salinização - Santos, Carlos Eduardo Oliveira (2016)
This study aimed to analyze the temporal and spatial variation of the parameters of the water quality of the Poção da Ribeira reservoir, located in Sergipe State, with storage capacity of 16.5 hm³ and how primary purpose the irrigation. The monitoring was conducted in two phases, the first of them during the years 2013 and 2014, with sampling during the dry and rainy seasons of those years, at a single point (P0), while for the second phase of monitoring occurred during the year 2015, was sought to evaluate the existence of spatial variation of parameters for this were chosen three points (P1, P2 and P3) distributed in the reservoir and checked for stratification of the water column, being held this year three sampling campaigns (May, August and November). In situ were performed measures the temperature of the water depth. For water samples sent to the laboratory the following parameters were analyzed: Turbidity, pH, alkalinity, hardness, dissolved oxygen (DO), dissolved organic carbon (DOC), fecal coliforms, total phosphorus (Ptotal), phosphate (PO4 3-) ammonia (NH3), nitrate (NO3 -), nitrite (NO2 -), electrical conductivity (EC), total dissolved solids (TDS), sodium (Na+), potassium (K+), calcium (Ca2+), magnesium (Mg2+), bicarbonates (HCO3 -), sulfate (SO4 2-) and chloride (Cl-). There was a significant seasonal variation for water quality parameters, as the spatial variation was no evidence of horizontal compartmentalization of the reservoir water in against departure, there was strong stratification of temperature during the dry season, increasing the electrical conductivity from 8 m depth during the rainy season and strong lowering of the pH in the first collection in 2015. The multivariate statistical cluster analysis showed the existence of three statistically significant groups, being revealed by principal component analysis (PCA) that 99.0% of the variance of the data matrix was due to three main components (PC), the first component (PC1), with greater weight associated with the EC, accounting for 94.0% of the variability of water quality. It has been shown by geochemical study, the prevalence of type sodic/chlorinated waters, which are classified as to their use in irrigation, as C2S1.