Investigating the spatiotemporal dynamics of contaminants in surface water is crucial to better understand how introduced chemicals are interacting with and potentially influencing aquatic organisms and environments. Within the Chesapeake Bay Watershed, USA, there are concerns about the potential role of contaminant exposure on fish health. Evidence suggests that exposure to contaminants in surface water is causing immunosuppression and intersex in freshwater fish species. Despite these concerns, there is a paucity of information regarding the complex dynamics of contaminant occurrence and co-occurrence in surface water across both space and time. To address these concerns, we applied a Bayesian hierarchical joint-contaminant model to describe the occurrence and co-occurrence patterns of 28 contaminants and total estrogenicity across six river sites and over three years. We found that seasonal occurrence patterns varied by contaminant, with the highest occurrence probabilities during the spring and summer months. Additionally, we found that the proportion of agricultural landcover in the immediate catchment, as well as stream discharge, did not have a significant effect on the occurrence probabilities of most compounds. Four pesticides (atrazine, metolachlor, fipronil and simazine) co-occurred across sites after accounting for environmental covariates. These results provide baseline information on the contaminant occurrence patterns of several classes of compounds within the Chesapeake Bay Watershed. Understanding the spatiotemporal dynamics of contaminants in surface water is the first step in investigating the effects of contaminant exposure on fisheries and aquatic environments.