Assessment of ecological status for the European Water Framework Directive (WFD) is based on “Biological Quality Elements” (BQEs), namely phytoplankton, benthic flora, benthic invertebrates and fish. Morphological identification of these organisms is a time-consuming and expensive procedure. Here, we assess the options for complementing and, perhaps, replacing morphological identification with identification using eDNA, metabarcoding or similar approaches. We rate the suitability of DNA-based identification for the individual BQEs and water categories (rivers, lakes, transitional and coastal waters) against twelve criteria encompassing representativeness (e.g. suitability of current sampling methods for DNA-based identification, errors from DNA-based species detection), sensitivity (e.g. capability to detect sensitive taxa, unassigned reads), precision of DNA-based identification (knowledge about uncertainty), comparability with conventional approaches (e.g. sensitivity of metrics to differences in DNA-based identification), cost effectiveness and animal well-being. Overall, suitability of DNA-based identification is particularly high for fish, as eDNA is a well-suited sampling approach, which can replace expensive and harmful methods such as electrofishing, gill-netting or trailing, and there are options to replace absolute by relative abundance in metric calculations. For invertebrates and phytobenthos, the main remaining challenges include the modification of indices and completing barcode libraries. For phytoplankton, the latter problem is even more severe, due to the high taxonomic diversity in plankton samples. DNA-based identification is currently least appropriate for macrophytes (rivers, lakes) and angiosperms / macroalgae (transitional and coastal waters), which are surveyed rather than sampled. We discuss general implications of implementing DNA-based identification into standard ecological assessment, in particular considering any adaptations to the WFD that may be required facilitate the transition to molecular data.