Abstract
AbstractHeavy metals in urban stormwater runoff can adversely impact aquatic ecosystems. Successful management of such systems requires the accurate prediction of contaminant concentrations. This has created the need for simplistic statistical models. In this study, models were constructed to predict three of the most prevalent heavy metal constituents in urban stormwater: copper (Cu), lead (Pb) and zinc (Zn). Data from the United States, obtained during the Nationwide Urban Runoff Program (NURP), were used to calibrate and verify the models. A comparison of the models revealed that regression models were more accurate than the landuse‐based or metropolitan area averages of event mean concentration (EMC). The regression models also provided insight into important stormwater processes. It was found that pollutant accumulation on the catchment surface was essentially supply limited, and that significant portions of heavy metals originate from highly impervious areas.
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