Pollution of surface water by polar pesticides is a major environmental risk, particularly in river catchments where potable water supplies are abstracted. In these cases, there is a need to understand pesticide sources, occurrence and fate. Hence, we developed a novel strategy to improve water quality management at the catchment scale using passive sampling coupled to suspect screening and multivariate analysis. Chemcatcher® passive sampling devices were deployed (14 days) over a 12 month period at eight sites (including a water supply works abstraction site) in the Western Rother, a river catchment in South East England. Sample extracts (n = 197) were analysed using high-resolution liquid chromatography-quadrupole-time-of-flight mass spectrometry and compounds identified against a commercially available database. A total of 128 pesticides from different classes were found. Statistical analysis of the qualitative screening data was used to identify clusters of pesticides with similar spatiotemporal pollution patterns. This enabled pesticide sources and fate to be identified. At the water supply works abstraction site, spot sampling and passive sampling were found to be complementary, however, the passive sampling method in conjunction with suspect screening detected 50 pesticides missed by spot sampling combined with targeted analysis. Geospatial data describing pesticide application rates was found to be poorly correlated to their detection frequency using the Chemcatcher®. Our analysis prioritised 61 pesticides for inclusion in a future water quality risk assessment at the abstraction site. It was also possible to design a seasonal monitoring programme to effectively characterise the spatiotemporal pesticide profiles within the catchment. A work flow of how to incorporate passive sampling coupled to suspect screening into existing regulatory monitoring is proposed. Our novel approach will enable water quality managers to target the mitigation (non-engineered actions) of pesticide pollution within the catchment and hence, to better inform drinking water treatment processes and save on operational costs.