Benthic macroinvertebrates are widely used as bioindicators to assess the ecological status of freshwater ecosystems. Current biomonitoring programmes based on macroinvertebrates rely on morphological identification at genus or family level. However, this approach can be time-consuming and requires a high level of expertise, especially if identification is performed directly in the field. Moreover, the taxonomy of these organisms is constantly evolving and this can lead to uncertainties and mis-determinations. DNA metabarcoding is a genetic technique that provides faunistic lists from composite samples and holds the promise to replace morphological identification for biomonitoring purposes in the near future. Comparing the performance of both these methods is thus key to evaluate their strengths and weaknesses, in order to inform future biomonitoring programmes. We compared morphological and DNA metabarcoding identification on 17 streams belonging to 4 different hydroecoregions in NW Italy. Macroinvertebrates were collected with a proportional multihabitat method and organisms were identified in the field according to the Italian national legislation. On the same samples, DNA metabarcoding was performed to obtain macroinvertebrate community composition, using the BF2/BR2 primer set targeting a 421-bp fragment of the Cytochrome c oxidase I. STAR_ICMi index and its sub-metrics were then calculated from the results of both methods. Morphological identification detected more families than metabarcoding and the STAR_ICMi indices correlated just moderately between the two methods. However, metabarcoding provided species-level identification for most organisms, including alien species in multiple taxonomic groups. Although metabarcoding provides novel perspectives, reveals hidden biodiversity, and enhances ecological understanding, it cannot yet fully replace traditional biomonitoring methods, as it misses some invertebrate taxa detected through morphological identification. Our study shows the importance of maximising the amount of available information in a global climate change scenario, with the perspective of preserving fragile river ecosystems from invasive species and biodiversity loss.