Effective impervious area (EIA) is defined as the subset of the total impervious area (TIA) often hydrologically connected to stream networks via stormwater infrastructure. Its importance in runoff modeling and watershed health has been well established in the literature, making it a governing characteristic of urban watersheds. However, there is a critical need to move beyond quantification of the EIA at the watershed outlet toward explicitly identifying locations of connectivity. This paper reviews existing methods to quantify and identify the EIA and proposes a new model framework that builds on these methodologies to offer an automated and objective way to spatially identify the most probable impervious areas comprising the EIA. Impervious runoff is modeled on a volumetric basis with connectivity measured by accounting for attenuation across different surface types that can be calibrated to match observed direct runoff trends. A simplified model representation is presented for three watersheds in Knoxville, Tennessee. The results illustrate the influence of pervious attenuation in urban watersheds, showing that a threefold difference in the EIA is possible in a watershed on the basis of this variable. However, patterns of the EIA and watershed sensitivity to pervious attenuation are variable among watersheds, highlighting how watershed-specific characteristics influence runoff and should be accounted for in management plans. The model results capture the spatial variation in impervious connectivity between watersheds and offer insight into the potential for disconnection using targeted infiltrative enhancements such as green infrastructure. Further research is needed to inform the pervious attenuation variable and allow it to change on the basis of site-scale characteristics such as land cover, soil type and compaction, rooftop connections to stormwater networks, and antecedent moisture conditions. Such explicit quantification of pervious attenuation will allow the application of this method to ungauged watersheds. This work is the first step toward spatially identifying impervious connectivity in watersheds using this spatial modeling framework, providing the potential for more scientifically informed watershed management strategies through targeted green-infrastructure installation.

Although a number of studies have investigated pollutant transport patterns in urban watersheds, these studies have focused primarily on the upland landscape as the point of interest (i.e., prior to stormwater entering an open stream channel). However, it is likely that in-stream processes will influence pollutant transport when the system is viewed at a larger scale. One initial investigation that can be performed to characterize transport dynamics in urban runoff is determining a pollutant’s temporal distribution. By borrowing from urban stormwater literature, the propensity of a pollutant within a system to be more heavily transported in the initial portion of the storm can be quantified (i.e., the “first flush”). Although uncommon for use in stream science, this methodology allows direct comparison of results to previous studies on smaller urban upland catchments. Multiple methods have been proposed to investigate the first flush effect, two of which are applied in this study to two streams in Knoxville, TN, USA. The strength of the first flush was generally corroborated by the two unique methods, a new finding that allows a more robust determination of first flush presence for a given pollutant. Further, an “end flush” was observed and quantified for nutrients and microbes in one stream, a novel outcome that shows how the newer methodology that was employed can provide greater insight into transport processes and pollutant sources. Explanatory variables for changes in each pollutant’s inter-event first flush strength differed, but notable relationships included the influence of flow rate on microbes and influence of rainfall on Cu²⁺. The results appear to support the hypothesis that in-stream processes, such as resuspension, may influence pollutant transport in urban watersheds, pointing toward the need to consider in-stream processes in models developed to predict urban watershed pollutant export.