Evolving complex mixtures of pharmaceuticals and transformation products in effluent-dominated streams pose potential impacts to aquatic species; thus, understanding the attenuation dynamics in the field and characterizing the prominent attenuation mechanisms of pharmaceuticals and their transformation products (TPs) is critical for hazard assessments. Herein, we determined the attenuation dynamics and the associated prominent mechanisms of pharmaceuticals and their corresponding TPs via a combined long-term field study and controlled laboratory experiments. For the field study, we quantified spatiotemporal exposure concentrations of five pharmaceuticals and six associated TPs in a small, temperate-region effluent-dominated stream during baseflow conditions where the wastewater plant was the main source of pharmaceuticals. We selected four sites (upstream, at, and two progressively downstream from effluent discharge) and collected water samples at 16 time points (64 samples in total, approximately twice monthly, depending on flows) for 1 year. Concurrently, we conducted photolysis, sorption, and biodegradation batch tests under controlled conditions to determine the major attenuation mechanisms. We observed 10-fold greater attenuation rates in the field compared to batch tests, demonstrating that connecting laboratory batch tests with field measurements to enhance predictive power is a critical need. Batch systems alone, often used for assessment, are useful for determining fate processes but poorly approximate in-stream attenuation kinetics. Sorption was the dominant attenuation process (t_1/2<7.7 d) for 5 of 11 compounds in the batch tests, while the other compounds (n = 6) persisted in the batch tests and along the 5.1 km stream reach. In-stream parent-to-product transformation was minimal. Differential attenuation contributed to the evolving pharmaceutical mixture and created changing exposure conditions with concomitant implications for aquatic and terrestrial biota. Tandem field and laboratory characterization can better inform modeling efforts for transport and risk assessments.