The ever-increasing threats to riverine ecosystems call for novel approaches for highly resolved biodiversity assessments across taxonomic groups and spatio-temporal scales. Recent advances in the joint use of environmental DNA (eDNA) data and eDNA transport models in rivers (e.g., eDITH) allow uncovering the full structure of riverine biodiversity, hence elucidating ecosystem processes and supporting conservation measures. We applied eDITH to a metabarcoding dataset covering three taxonomic groups (fish, invertebrates, bacteria) and three seasons for a catchment sampled for eDNA at 73 sites. We upscaled eDNA-based biodiversity predictions to approximately 1900 reaches, and assessed α- and β-diversity patterns across seasons and taxonomic groups over the whole network. Genus richness predicted by eDITH was generally higher than values from direct eDNA analysis. Both predicted α- and β-diversity varied depending on season and taxonomic group. Predicted fish α-diversity increased downstream in all seasons, while invertebrate and bacteria α-diversity either decreased downstream or were unrelated to network position. Spatial β-diversity mostly decreased downstream, especially for bacteria. The eDITH model yielded a more refined assessment of freshwater biodiversity as compared to raw eDNA data, both in terms of spatial coverage, diversity patterns and effect of covariates, thus providing a more complete picture of freshwater biodiversity.