Multivariate statistical analysis as a tool for monitoring drinking water sources in an Atlantic Rainforest Conservation Unit

Water quality monitoring is paramount in identifying and mitigating pollution sources, protecting aquatic ecosystems, and ensuring safe water for human and wildlife consumption. This study is aimed at evaluating the quality of drinking water sources in three communities located in a Sustainable Use Conservation Unit in the municipality of Mangaratiba, Rio de Janeiro, Brazil, employing a multivariate statistical analysis. A total of 161 water samples were collected from January to December 2022, encompassing 32 surface water and 129 tap water samples. Physicochemical parameters were determined in situ employing a Horiba U50 multiparameter probe. The samples were stored and transported at 4 degrees C to the laboratory for microbiological analyses concerning total coliforms and Escherichia coli using a commercial enzymatic test. All samples contained coliforms, while E. coli were detected in 87% of the samples. The multivariate analysis indicated that the microbiological water quality in sampling region R2 was influenced by rainy periods and that, in general, the water quality within R3 was the most affected by the transport of solids to the water sources. The statistical methods applied herein aided in characterizing the study areas and detecting points of attention regarding physicochemical and microbiological parameters that significantly influence the water quality of each sampling point. Representative points for each study region were identified and may be employed for future monitoring and prevention actions.