Rivers around the world are under pressure from chemical pollution originating from agriculture, industry and settlements. This pollution, among others, by trace contaminants -- including potentially toxic elements (PTE) and persistent ''forever chemicals'' -- threatens ecosystems and human water use. Effectively managing this pollution requires a river basin perspective, as rivers naturally integrate all upstream contaminant inputs. By understanding contaminant emission quantities and their pathways across entire catchments, managers can prioritise efforts for contamination monitoring and target emission mitigation measures where they are most needed. This thesis develops and applies innovative methods to quantify trace contaminant emissions via different pathways at the river basin scale, providing scientific tools for effective pollution control in three complementary studies: Study 1 investigated the transport dynamics of PTEs during high-flow events in a lowland river catchment to improve monitoring strategies and emission modelling. Field sampling was conducted at three sites during multiple flow events, analysing water samples for total and dissolved concentrations of 29 elements. Concentration of PTE in suspended particulate matter (SPM) were derived by calculation and compared to riverbed sediment and land-use stratified soil samples. The study found that while the quantity of transported SPM was the primary driver of PTE transport during events, significant changes in SPM composition also occurred. Notably, concentrations of Sb and Cu in SPM decreased as events progressed, suggesting a ''first flush'' contribution from sources like road dust containing brake wear particles. Furthermore, PTEs and a few other elements showed systematic enrichment in SPM compared to catchment soils, particularly for Ag, Bi, Zn, Cu, P, Sb, Ni and Li, indicating anthropogenic sources. However, sediment fingerprinting to identify specific SPM sources in the catchment was deemed unfeasible due to low variability of concentrations in potential source materials. Study 2 addressed the critical need for accessible and harmonised data to support pathway-oriented emission inventories for trace contaminants in the Danube River Basin (DRB). It established a relational database integrating fragmented concentration measurements and essential metadata from various environmental compartments (surface water, groundwater, wastewater, soil, atmospheric deposition, stormwater runoff) across multiple countries. The database was published online in a research data repository under a Creative Commons license, applying FAIR principles (Findable, Accessible, Interoperable, Reusable) to facilitate widespread reuse. Analysis revealed severe imbalances: surface water and groundwater data dominated while atmospheric deposition, stormwater runoff, and soils were under-represented; spatially, coverage was extensive in Austria, Germany, and Hungary but limited elsewhere in the DRB primarily to compartments monitored under EU legislation. The database identified critical gaps caused by inconsistent metadata and suboptimal data storage, enabling prioritisation of future monitoring efforts and informing recommendations for a harmonised transnational monitoring programme covering tributaries and under-represented pathways. Study 3 applied a pathway-oriented approach using the MoRE model to quantify emissions and river concentrations of two prevalent ''forever chemicals'' -- perfluorooctanesulfonic acid (PFOS) and perfluorooctanoic acid (PFOA) -- across Austria, supported by tailor-made monitoring. The analysis revealed different pathway contributions: PFOS emissions were predominantly driven by wastewater treatment plants (WWTPs), whereas PFOA exhibited greater contributions from diffuse pathways like surface runoff and groundwater. Regional patterns showed elevated concentrations for both substances in eastern Austria, where the dilution capacity of rivers is limited, alongside a major PFOA hotspot near the legacy industrial PFOA production site in Gendorf, Germany. The model demonstrated markedly better performance than previous model studies using generalised inputs (e.g., population-based emissions). This enabled a reliable identification of priority areas and evaluation of scenarios on mitigation measures, such as advanced wastewater treatment, demonstrating its value for strategic management of persistent pollutants. This thesis establishes a comprehensive framework for quantifying trace contaminant emissions in river basins, integrating process understanding, data management, and pathway-oriented modelling. By advancing methodologies for emission validation, transnational data infrastructure, and spatially resolved pathway analysis, it provides scientifically robust tools to identify pollution hotspots and prioritise mitigation efforts. The consistent application of open-source tools (R, PostgreSQL, MoRE) and advanced statistical methods ensures transparency and reproducibility, supporting evidence-based river basin management. Collectively, this work demonstrates how pathway-focused emission quantification can help to direct pollution control resources where they yield the greatest environmental benefit.
