Water quality is mainly assessed using traditional water quality assessment methods that measure chemical parameters against established standards. The water quality index is used worldwide for water quality assessment. The main parameters evaluated include the total dissolved solids, electrical conductivity, nitrite, and nitrate. In this study, the WQI combined with microbiological analyses was used to assess the water quality of two rivers, Munim and Iguará. Data obtained in this study were then correlated using multivariate statistical analysis. Principal component analysis grouped the monitored sampling points into three clusters and identified temperature, Escherichia coli, and turbidity, as features correlated to the rainy season, while phosphorus, total dissolved solids, and biochemical oxygen demand are associated with the dry season. Four principal components explained 81.20% of the data variance during the studied seasons. The evaluated correlations indicated that in the rainy season, E. coli (~443.63 CFU/100 mL) and turbidity (~36.51 NTU) levels were the highest. However, in the dry season, the levels of phosphorus (~4.25 mg·L−1), total dissolved solids (145.46 mg·L−1), and dissolved oxygen (~9.89 mg·L−1) were the highest.