The paper presents an example of using multivariate techniques to interpret a large data set obtained during a 4-year water quality monitoring program in the Gdansk Municipality region, on the southern coast of the Baltic Sea. From 2004 to 2007, 11 physicochemical water parameters were analyzed monthly at 15 sites within eight watercourses. Principal-components analysis and cluster analysis were used to explore the data. Spatio-temporal trends in water quality were evaluated, the variables that determined the data set’s structure and the factors that affected the water’s physicochemical composition identified, with the goal of helping to optimize future monitoring. To reduce the number of analyzed variables, relationships between the analyzed parameters were also identified. The results revealed that the differences in physicochemical water properties among stations were generally smaller than those between the warmer and cooler seasons. It was determined that seasonal intrusions of brackish water from the Gulf of Gdansk can modify the water properties of some watercourses in the study area, but that dissolved oxygen, chemical oxygen demand, and total phosphorus were the main parameters responsible for the overall variation in the observed data. These parameters are related to pollution of anthropogenic origin.