Wastewater contains microorganisms coming from various sources, e.g. feces discharges, soil infiltrations and sewer biofilms and sediments. The primary objective of this work was to determine if end-of-pipe wastewater microbial community structures exhibits short-timescale variation, and assess possible microbial origins. To this end, we measured hourly physicochemical characteristics of wastewater influent for 2 days and analyzed the microbial community at 4-h intervals using 16S rRNA gene amplicon sequencing. Results showed large variations in the microbial community composition at phylum and genus levels, i.e. Proteobacteria ranged from 44 to 63% of the total relative abundance and Arcobacter ranged from 11 to 22%. Diurnal patterns were observed in the alpha-diversity, beta-diversity and the prevalence of several taxa. Wastewater physicochemical characteristics explained 61% of the total microbial community variance by Canonical Correspondence Analysis (CCA), with flow rate being the main explanatory variable exhibiting a clear diurnal profile. Comparison with public databases using closed reference OTUs revealed that only 7.3% of the sequences were shared with human gut microbiota and 21.7% with soil microbiota, the majority being from the sewer biofilms and sediments. The functional trait, weighted average ribosomal RNA operon (rrn) copy number per genome, was found to be relatively high in the wastewater microbiota (average 3.6, soil 2.1, and human gut 2.6) and significantly correlated with flow, inferring active microbial enrichments in the sewer. The prevalence of Methylophilaceae, methanol oxidation genes and denitrification genes were related to high influent methanol and NO3- concentration in the influent wastewater. These functional organisms and genes indicate important carbon and nutrient removal related functions in the sewer. Together, the observed temporal patterns of the microbial community and functional traits suggest that high wastewater flow causes greater transport of active sewer microorganisms which are functionally important.