The pollution of aquatic ecosystems with complex and largely unknown mixtures of organic micropollutants is not sufficiently addressed with current monitoring strategies based on target screening methods. In this study, we implemented an open-source workflow based on non-target screening to unravel longitudinal pollution patterns of organic micropollutants along a river course. The 47 km long Holtemme River, a tributary of the Bode River (both Saxony-Anhalt, Germany), was used as a case study. Sixteen grab samples were taken along the river and analyzed by liquid chromatography coupled to high-resolution mass spectrometry. We applied a cluster analysis specifically designed for longitudinal data sets to identify spatial pollutant patterns and prioritize peaks for compound identification. Three main pollution patterns were identified representing pollutants entering a) from wastewater treatment plants, b) at the confluence with the Bode River and c) from diffuse and random inputs via small point sources and groundwater input. By further sub-clustering of the main patterns, source-related fingerprints were revealed. The main patterns were characterized by specific isotopologue signatures and the abundance of peaks in homologue series representing the major (pollution) sources. Furthermore, we identified 25 out of 38 representative compounds for the patterns by structure elucidation. The workflow represents an important contribution to the ongoing attempts to understand, monitor, prioritize and manage complex environmental mixtures and may be applied to other settings.