Urban development alters hydrology and can degrade water quality, with impacts being pronounced in areas with a high density of impervious surfaces. It is not just the extent of impervious surfaces that affects stream health, but also the connectivity of impervious surfaces to streams. To address this connectivity, we created reproducible workflows using geospatial stormwater system data and high-resolution (1-meter) elevation and land cover data to delineate 1) topo-watersheds, watersheds based predominantly on topography, and 2) storm-watersheds, watersheds that were hydro-enforced We calculated and compared common urban metrics using the boundaries from both the topo-watersheds and storm-watersheds. Urban metrics included percentage of impervious surfaces at high resolution (1-meter), percentage of impervious surfaces at low resolution (30-meter), road density, population density, and housing density. We evaluated differences in correlations between urban metrics and water quality metrics as a function of topo-watershed or storm-watershed delineations. The study area included 25 small watersheds (<75 square kilometers) in the Puget Sound lowlands in King County, Washington, which includes the Seattle metropolitan area. Water quality metrics were based on monthly grab samples for water years 2019 through 2024 for constituents of nitrogen and phosphorus, specific conductance, E. coli, and fecal coliform. Initial correlation results between urban metrics and water quality metrics by topo-watersheds indicated the strongest significant (p<0.05) Spearman rank correlations between road density and median specific conductance (ρ=0.65), low-resolution impervious cover and median ammonia concentration (ρ=0.53), high-resolution impervious and median orthophosphate concentration (ρ=0.61) and median total phosphorus (ρ=0.50), and housing density and median E. coli (ρ=0.72) and fecal coliform counts (ρ=0.69). There were no significant (p<0.05) positive correlations between urban metrics and median nitrate-nitrite concentration or median total nitrogen concentration. Future work will evaluate correlations between urban metrics and water quality metrics based on storm-watershed boundaries. The findings from this study will not only help inform more efficient implementation of best management practices, but the reproducible workflows and analysis frameworks produced from this study can also be used by other researchers and water quality managers to conduct similar studies in other regions.