Diatoms are frequently used for water quality assessments; however, identification to species level is difficult, time-consuming and needs in-depth knowledge of the organisms under investigation, as nonhomoplastic species-specific morphological characters are scarce. We here investigate how identification methods based on DNA (metabarcoding using NGS platforms) perform in comparison to morphological diatom identification and propose a workflow to optimize diatom fresh water quality assessments. Diatom diversity at seven different sites along the course of the river system Odra and Lusatian Neisse from the source to the mouth is analysed with DNA and morphological methods, which are compared. The NGS technology almost always leads to a higher number of identified taxa (270 via NGS vs. 103 by light microscopy LM), whose presence could subsequently be verified by LM. The sequence-based approach allows for a much more graduated insight into the taxonomic diversity of the environmental samples. Taxa retrieval varies considerably throughout the river system, depending on species occurrences and the taxonomic depth of the reference databases. Mostly rare taxa from oligotrophic parts of the river systems are less well represented in the reference database used. A workflow for DNA-based NGS diatom identification is presented. 28 000 diatom sequences were evaluated. Our findings provide evidence that metabarcoding of diatoms via NGS sequencing of the V4 region (18S) has a great potential for water quality assessments and could complement and maybe even improve the identification via light microscopy.