In this study, we calibrated and tested the Soil Conservation Service Curve Number (SCS-CN) based Modified Sahu-Mishra-Eldo (MSME) model for predicting storm event direct runoff (Q(tot)) and its soil saturation coefficient alpha as a threshold antecedent moisture condition for partitioning into overland surface and shallow subsurface runoff components. The model calibration was performed using 36 storm events from 2008 to 2015 on a 160-ha low-gradient forested watershed (WS80) on poorly drained soil. The model was further validated without cali-bration using data from 2011 to 2015 on two sites [115 ha (Conifer) and 210 ha (Eccles Church)] and from 2008 to 2011 on a third site, the 100-ha Upper Debidue Creek (UDC), all similar forested watersheds on the Atlantic Coastal Plain, USA. The calibrated MSME model was able to accurately predict the estimated Q(tot_pred) for the WS80 watershed, with calculated Nash-Sutcliffe efficiency coefficient (NSE), RMSE-standard deviation ratio (RSR), and percent bias (PBIAS) of 0.80, 0.44, and 16.7%, respectively. By applying the same calibrated alpha value of 0.639 from the WS80 to two other similar poorly drained watersheds, the MSME model satisfactorily predicted the estimated Q(tot_pred) for both the Eccles Church (NSE = 0.64; RSR = 0.57; PBIAS = 28.9%) and Conifer (NSE = 0.60; RSR = 0.58; PBIAS = 21.3%) watersheds, respectively. The MSME model, however, yielded un-satisfactory results (NSE =-0.13, RSR = 2.06, PBIAS = 616.3%) on the UDC watershed with coarse-textured soils, indicating the possible association of the alpha coefficient with soil subsurface texture. Based on the analysis of event rainfall and pre-event water table elevation, and linking them with the calibrated alpha coefficient that describes the proportion of saturated depth in a soil profile, it was found that rainfall was the main determining factor for overland runoff generation. These results demonstrate the MSME model's potential to predict direct runoff in poorly drained forested watersheds, which serve as a reference for urbanizing coastal landscapes in a changing climate.

Water quality modeling has been studied extensively to better manage urban runoff impacts on stream health and effectively address stormwater permitting requirements. Recent studies have indicated that previous modeling approaches using buildup and washoff models or regression equations are inadequate because they fail to capture important dimensions in urban runoff and pollutant transport processes. The effective impervious area (EIA) has been identified as one of the greatest determinants of urban stream health in many studies due to connection of these areas via stormwater infrastructure. Thus, accurate measures of EIA should offer additional explanatory power in assessing the variability in urban water quality. Recently refined estimates of EIA were used to assess water quality variability among storms and within storms to provide insight to pollutant dynamics and identify the role of EIA in these trends. Variability among storm events for E. coli, total suspended solids (TSS), copper, and zinc was assessed over multiple storm events on three urban watersheds in Knoxville, Tennessee. Inter-event variability supported findings from other studies but indicated differences among storm events associated with runoff expected to be confined to the EIA, and those with runoff generated by less closely connected impervious areas and pervious sources. Qualitative investigation of pollutant dynamics using hysteresis loops indicated complex patterns that differed by pollutants as well as by the most probable runoff source for the event. Transport trends were well-organized for some events but reflected harder to explain variability for others. The antecedent moisture conditions (AMC) are believed to play a role in this because wet conditions (higher soil moisture) promote runoff connection from areas outside of the EIA. Pollutant delivery along these more disconnected pathways is not well-predicted by typical water quality modeling. These results demonstrate the utility in including both the EIA and AMC in urban water quality modeling moving forward as well as the need for further research in variably sourced runoff effects on water quality loading in urban systems. (C) 2021 American Society of Civil Engineers.

Climate stationarity is a traditional assumption in the design of the urban drainage network, including green infrastructure practices such as bioretention cells. Predicted deviations from historic climate trends associated with global climate change introduce uncertainty in the ability of these systems to maintain service levels in the future. Climate change projections are made using output from coarse-scale general circulation models (GCMs), which can then be downscaled using regional climate models (RCMs) to provide predictions at a finer spatial resolution. However, all models contain sources of error and uncertainty, and predicted changes in future climate can be contradictory between models, requiring an approach that considers multiple projections. The performance of bioretention cells were modeled using USEPA's Storm Water Management Model (SWMM) to determine how design modifications could add resilience to these systems under future climate conditions projected for Knoxville, Tennessee, USA. Ten downscaled climate projections were acquired from the North American Coordinated Regional Downscaling Experiment program, and model bias was corrected using Kernel Density Distribution Mapping (KDDM). Bias-corrected climate projections were used to assess bioretention hydrologic function in future climate conditions. Several scenarios were evaluated using a probabilistic approach to determine the confidence with which design modifications could be implemented to maintain historic performance for both new and existing (retrofitted) bioretention cells. The largest deviations from current design (i.e., concurrently increasing ponding depths, thickness of media layer, media conductivity rates, and bioretention surface areas by 307%, 200%, 200%, and 300%, respectively, beyond current standards) resulted in the greatest improvements on historic performance with respect to annual volumes of infiltration and surface overflow, with all ten future climate scenarios across various soil types yielding increased infiltration and decreased surface overflow compared to historic conditions. However, lower performance was observed for more conservative design modifications; on average, between 13-82% and 77-100% of models fell below historic annual volumes of infiltration and surface overflow, respectively, when ponding zone depth, media layer thickness, and media conductivity were increased alone. Findings demonstrate that increasing bioretention surface area relative to the contributing catchment provides the greatest overall return on historic performance under future climate conditions and should be prioritized in locations with low in situ soil drainage rates. This study highlights the importance of considering local site conditions and management objectives when incorporating resiliency to climate change uncertainty into bioretention designs.

Permeable pavements are implemented to provide at-source treatment of urban stormwater runoff while supporting vehicular and pedestrian use. Studies on these systems have mainly focused on those treating only direct rainfall and installed atop well-drained soils which typically provide substantial hydrologic mitigation through exfiltration that may not be representative of more hydrologically taxing conditions. A single lane parking area retrofitted with permeable interlocking concrete pavement in Vermilion, OH, USA was monitored over a 15-month period to quantify its hydrologic performance under such conditions. The 470 m(2) permeable pavement was underlain by silt loam soils and a shallow bedrock layer and treated run-on from the adjacent 324 m(2) asphalt drive lane. Observed data were compared to a calibrated SWMM model developed to simulate the pre-retrofit conditions of the site (i.e., a completely impervious parking lot). Cumulative runoff volumes were reduced by 43% across all events in the monitoring period compared to a fully impervious parking lot. While median peak flows were reduced by 75%, substantial mitigation was limited to smaller, lower intensity events with longer antecedent dry periods (i.e., non-flood producing events). The permeable pavement significantly delayed the occurrence of peak flows from the site following peak rainfall intensity by a median 29 min. Results from this study demonstrate that permeable pavements which receive run-on from adjacent imperious cover and are installed atop poorly drained soils can significantly reduce runoff volumes and peak flow rates and delay the occurrence of peak discharge. The modelling approach implemented can provide a better estimation of diffuse inflows to green infrastructure stormwater controls and aid in refining design features which enhance the hydrologic performance in systems underlain by poorly drained soils.

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.

There is a need for enhanced guidance in siting distributed, infiltrative green infrastructure (GI) practices, especially in densely developed urban watersheds where retrofits come at a high cost. To maximize the hydrologic benefit of GI practices on urban streams, the disconnection of effective impervious areas (EIA), or those impervious areas hydraulically connected to the stormwater network, has been identified as a strategic management approach that is expected to have the greatest impact. The overall effect of full disconnection of spatially-identified EIA on watershed hydrology is uncertain because this type of full disconnection is rarely brought to full-scale implementation. In this study, spatial EIA identification is used to parametrize an urban runoff model using the United States Environmental Protection Agency's Storm Water Management Model (SWMM). The calibrated model is used to assess runoff reductions resulting from GI practices distributed through the watershed via different placement strategies, both spatially-informed and not. Full treatment of the spatially identified EIA using bioretention cells was compared to two scenarios treating the same area of impervious surfaces, but with random placement either among all impervious areas or placement focused in areas of higher imperviousness. Model results indicate that substantially higher runoff reduction could be realized by targeting EIA, with a median runoff reduction of nearly 30% more than other treatment scenarios across storm events ranging from 1.27 to 20.7 mm using this strategic siting. Further improvements in optimizing distributed infiltrative GI practice placement are needed and targeting of spatially-identified EIA appears to be a viable method for increasing the hydrologic improvements realized through watershed scale implementations.

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. (C) 2018 American Society of Civil Engineers.

The urban heat island (UHI) is a well-documented effect of urbanization on local climate, identified by higher temperatures compared to surrounding areas, especially at night and during the warm season. The details of a UHI are city-specific, and microclimates may even exist within a given city. Thus, investigating the spatiotemporal variability of a city’s UHI is an ongoing and critical research need. We deploy ten weather stations across Knoxville, Tennessee, to analyze the city’s UHI and its differential impacts across urban neighborhoods: two each in four neighborhoods, one in more dense tree cover and one in less dense tree cover, and one each in downtown Knoxville and Ijams Nature Center that serve as control locations. Three months of temperature data (beginning 2 July 2014) are analyzed using paired-sample t tests and a three-way analysis of variance. Major findings include the following: (1) Within a given neighborhood, tree cover helps negate daytime heat (resulting in up to 1.19 ∘C lower maximum temperature), but does not have as large of an influence on minimum temperature; (2) largest temperature differences between neighborhoods occur during the day (0.38–1.16 ∘C difference), but larger differences between neighborhoods and the downtown control occur at night (1.04–1.88 ∘C difference); (3) presiding weather (i.e., air mass type) has a significant, consistent impact on the temperature in a given city, and lacks the differential impacts found at a larger-scale in previous studies; (4) distance from city center does not impact temperature as much as land use factors. This is a preliminary step towards informing local planning with a scientific understanding of how mitigation strategies may help minimize the UHI and reduce the effects of extreme weather on public health and well-being.

Epps, Thomas H., Daniel R. Hitchcock, Anand D. Jayakaran, Drake R. Loflin, Thomas M. Williams, and Devendra M. Amatya, 2012. Characterization of Storm Flow Dynamics of Headwater Streams in the South Carolina Lower Coastal Plain. Journal of the American Water Resources Association (JAWRA) 1‐14. DOI: 10.1111/jawr.12000Abstract: Hydrologic monitoring was conducted in two first‐order lower coastal plain watersheds in South Carolina, United States, a region with increasing growth and land use change. Storm events over a three‐year period were analyzed for direct runoff coefficients (ROC) and the total storm response (TSR) as percent rainfall. ROC calculations utilized an empirical hydrograph separation method that partitioned total streamflow into sustained base flow and direct runoff components. ROC ratios ranged from 0 to 0.32 on the Upper Debidue Creek (UDC) watershed and 0 to 0.57 on Watershed 80 (WS80); TSR results ranged from 0 to 0.93 at UDC and 0.01 to 0.74 at WS80. Variability in event runoff generation was attributed to seasonal trends in water table elevation fluctuation as regulated by evapotranspiration. Groundwater elevation breakpoints for each watershed were identified based on antecedent water table elevation, streamflow, ROCs, and TSRs. These thresholds represent the groundwater elevation above which event runoff generation increased sharply in response to rainfall. For effective coastal land use decision making, baseline watershed hydrology must be understood to serve as a benchmark for management goals, based on both seasonal and event‐based surface and groundwater interactions.

The objective of this study was to assess curve number (CN) values derived for two forested headwater catchments in the Lower Coastal Plain (LCP) of South Carolina using a three‐year period of storm event rainfall and runoff data in comparison with results obtained from CN method calculations. Derived CNs from rainfall/runoff pairs ranged from 46 to 90 for the Upper Debidue Creek (UDC) watershed and from 42 to 89 for the Watershed 80 (WS80). However, runoff generation from storm events was strongly related to water table elevation, where seasonally variable evapotranspirative wet and dry moisture conditions persist. Seasonal water table fluctuation is independent of, but can be compounded by, wet conditions that occur as a result of prior storm events, further complicating flow prediction. Runoff predictions for LCP first‐order watersheds do not compare closely to measured flow under the average moisture condition normally associated with the CN method. In this study, however, results show improvement in flow predictions using CNs adjusted for antecedent runoff conditions and based on water table position. These results indicate that adaptations of CN model parameters are required for reliable flow predictions for these LCP catchments with shallow water tables. Low gradient topography and shallow water table characteristics of LCP watersheds allow for unique hydrologic conditions that must be assessed and managed differently than higher gradient watersheds.