Stormwater wetlands are an important environmental feature intended to capture and retain contaminants from stormwater, which would otherwise negatively affect the health of aquatic ecosystems downstream. Given their design, the chemical profile of stormwater wetlands are largely representative of the surrounding catchment area. Environmental DNA is expanding the field of aquatic monitoring, introducing the ability to assess biological profiles quickly and reliably, and allowing for the assessment of chemical contamination on sedimentary microbial dynamics. Sediment samples collected from the inlet and outlet of nine urban stormwater wetlands and one rural wetland were analysed for chemical contaminants through ICP-AES and microbial community structure through 16S rRNA amplicon sequencing. Multivariate analyses used to determine the interrelation between the chemical and biological data included alpha diversity analysis, non-metric multidimensional scaling (nMDS), analysis of similarities (ANOSIM), SIMPER, distance-based redundancy analysis (dbRDA), and BEST analysis. We found significant variation in the chemical and microbial profiles between the rural wetland and stormwater wetlands, as well as significant variation between over half of the inlets and outlets within each stormwater wetland. The bacterial phyla Cyanobacteria and Proteobacteria were mostly driving this variation, along with Planctomycetota and Bacteriodota. Zinc and barium were also identified as key chemical drivers of this variation, the latter of which has not previously been associated with microbial dynamics in freshwater environments. This study validates the ability of eDNA metabarcoding to reliably evaluate sedimentary microbial profiles in stormwater wetlands and highlights its value in the assessment and prediction of contamination in these environments.