Assessing chemical pollution in water environments is crucial to prevent or even reverse its negative effects on ecosystems, including the health of humans and other living beings. Chemical analysis of pollutants needs previous knowledge of the contaminating menaces and does not provide information on their biological effects. Thus, they are not useful for the detection of emerging pollutants or for evaluating the effects of compounds that do not present a monotonic dose-effect relationship. As an alternative, the presence, absence, or changes in the abundance of sentinel organisms (bioindicators) can be used to detect water pollution. Furthermore, biological parameters (biomarkers) evaluated in these organisms at their biochemical, histological, immunological, physiological, or organismic levels are routinely used to detect and assess the negative effect of pollutants. Many of these parameters are related to oxidative stress, as pollutants commonly exert their toxicity and produce pathogenic damages by increasing the levels of reactive oxidative species. However, the number of biomarkers is limited, and their use requires prior knowledge of their mechanism of action, making them inefficient for the evaluation of new or unknown chemicals. Omics allow us to analyse all the biomolecules from a certain sample, what makes them ideal approaches for assessing pollution in an unbiased manner. They can be used to analyse DNA (genomics), mRNA (transcriptomics), proteins (proteomics), or metabolites (metabolomics). Moreover, they can also be utilised to study biomolecules with a spatial perspective (mass spectrometry imaging, MSI) to relate changes with morphological or physiological alterations in multicellular organisms. At the micro-scale, microbes are pivotal for the health of all different types of aquatic ecosystems (i.e. marine, lakes, rivers, wetlands, estuaries, and ponds) and are present even in the most extreme conditions. Analysing microbial alterations using metaomic techniques, mainly based on the taxonomic resolution by rDNA amplicon sequencing, which informs about the composition, structure, and diversity of the microbiome, is to date the most promising method to assess the health status of aquatic environments. Nevertheless, methodological improvements are needed to assure efficient and specific extraction/isolation protocols, and complete reference databases are also imperative for precise bacterial identification. Alterations in the functional capacity of the microbiome in response to pollution can easily be inferred using bioinformatic tools as FAPROTAX or Tax4Fun. This approach has proven to be particularly useful for wastewater-based epidemiology to identify health menaces in aquatic environments. Bacterial community biotic indexes (e.g. microgAMBI) can also be calculated to assess the ecological status of water bodies. In summary, metaomics are proving to be powerful tools for assessing the health of aquatic environments, also providing key information for the effective implementation of corrective bioremediation strategies. Moreover, the increasing development of artificial intelligence tools promises to generate ever more complete databases, faster and more precise identifications, and more accurate biological indexes to evaluate environmental alterations.