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Daily weather conditions for an entire city are usually represented by a single weather station, often located at a nearby airport. This resolution of atmospheric data fails to recognize the microscale climatic variability associated with land use decisions across and within urban neighborhoods. This study uses heat index, a measure of the combined effects of temperature and humidity, to assess the variability of heat exposure from ten weather stations across four urban neighborhoods and two control locations (downtown and in a nearby nature center) in Knoxville, Tennessee, USA. Results suggest that trees may negate a portion of excess urban heat, but are also associated with greater humidity. As a result, the heat index of locations with more trees is significantly higher than downtown and areas with fewer trees. Trees may also reduce heat stress by shading individuals from incoming radiation, though this is not considered in this study. Greater amounts of impervious surfaces correspond with reduced evapotranspiration and greater runoff, in terms of overall mass balance, leading to a higher temperature, but lower relative humidity. Heat index and relative humidity were found to significantly vary between locations with different tree cover and neighborhood characteristics for the full study time period as well as for the top 10% of heat index days. This work demonstrates the need for high-resolution climate data and the use of additional measures beyond temperature to understand urban neighborhood exposure to extreme heat, and expresses the importance of considering vulnerability differences among residents when analyzing neighborhood-scale impacts.

Sustainable long-term performance of water quality swales, a common stormwater control measure (SCM), requires a futuristic view that considers the impact of socio-economic conditions. The impact of five socio-economic scenarios on a water quality swale in Knightdale, North Carolina, USA, was assessed using WinSLAMM, a stormwater quality model. Scenarios included changing annual average daily traffic (AADT) and maintenance regimes mimicking environmental protection and degradation. Statistical performance evaluation criteria (e.g., RMSE, R2) were used to assess model suitability and calibration for runoff volume and sediment. Results indicated that sediment delivery to the swale increased with AADT, and reduced maintenance negatively impacted swale performance. While the reduced AADT during the COVID-19 pandemic provided short-term water quality benefits, a lack of maintenance impacted treatment through the swale. SCM inspection and maintenance is critical for accommodating increased AADT and enhancing swale life-cycle. This exploratory impact assessment focused on the socio-economic axis of climate change scenario framework and underscored the importance of sound environmental policies for sustainable swale performance. Future studies are needed in other areas to influence local environmental policies.

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.

An urban watershed in Raleigh, NC, was evaluated for Escherichia coli ( E. coli ), fecal coliform, enterococci, and total suspended solids (TSS) over 20 storm events. Sampling procedures allowed collection of multiple discrete samples per event, resulting in a relatively detailed description of microbe and TSS export for each storm. Data were evaluated to determine if a first flush effect was present for indicator bacteria and TSS in stormwater runoff. Analyses suggested there was a significant first flush effect for fecal coliform and TSS, although the first flush effect for fecal coliform was relatively weak. For E. coli and enterococci, no significant first flush effect was noted. Overall, the first flush effect was not always present for indicator bacteria and, if present, tended to be weak. The first flush effect for TSS was substantially stronger than that of any indicator bacteria. Further analysis showed poor correlation between first flush strength and antecedent climate variables, storm characteristics, and flow characteristics. However, seasonal differences for first flush strength were noted. Specifically, winter storms showed a stronger first flush effect for all indicator bacteria. The results of this study indicate that stormwater runoff presents a potential public health hazard due to elevated indicator bacteria levels for all portions of the storm event. Further, stormwater management practices cannot be expected to treat proportionally more indicator bacteria when sized for the water quality event. Instead, removal will simply be a function of a management practice’s volume capture and microbe sequestration efficiency.

The increase of impermeable areas in a catchment is known to elevate flood risk. To adequately understand and plan for these risks, changes in the basin water cycle must be quantified as imperviousness increases, requiring the use of hydrological modeling to obtain design runoff volumes and peak flow rates. A key stage of modeling is adopting the structure of the model and estimating its parameters. Due to the fact that most impervious basins are uncontrolled, hydrological models that do not require parameter calibration are advantageous. At the same time, it should be remembered that these models are sensitive to the values of assumed parameters. The purpose of this work is to determine the effect of catchment impermeability on the flow variability in the Sudół Dominikański stream in Cracow, Poland, and assess the influence of the frequency of rainfall on values of time of concentration (here it is meant as critical storm duration). The major finding in this work is that the critical storm duration for all different scenarios of catchment imperviousness depends on the rainfall exceedance probability. In the case of rainfall probability lower than 5.0%, the critical storm duration was equal to 2 h, for higher probabilities (p ≥ 50%) it was equal to 24 h. Simulations showed that the increase of impermeable areas caused peak time abbreviation. In the case of rainfall with exceedance probability p = 1.0% and critical storm duration Dkr = 2 h, the peak time decreased about 12.5% and for impermeable areas increased from 22.01 to 44.95%.

Across the globe, water quality standards have been implemented to protect receiving waters from stormwater pollution, motivating regulators (and consequently designers) to develop tools to predict the performance of stormwater control measures such as constructed stormwater wetlands (CSWs). The goal of this study was to determine how well the relaxed tanks-in-series (P-k-C*) model described the performance of CSWs in North Carolina. Storm events monitored at 10 CSWs in North Carolina were used for calibrating the model, and statistical evaluations concluded the model could adequately predict the performance for all pollutants except organic nitrogen. Nash–Sutcliff calibration/validation values were determined to be 0.72/0.78, 0.78/0.74, 0.91/0.87, 0.72/0.62, 0.88/0.73, and 0.91/0.63 for total nitrogen, total ammoniacal nitrogen, oxidized nitrogen, organic nitrogen, total phosphorus, and total suspended solids, respectively. Sensitivity analysis revealed only one calibration parameter with strong sensitivity, the Arrhenius coefficient (temperature dependent model coefficient). With this model, CSWs can be optimized to treat watershed-specific influent concentrations to meet effluent targets. In general, the current design technique used in North Carolina and many other locations (a first flush volume detention method) oversizes CSWs for water quality vis-à-vis the method herein, suggesting improved designs for water quality may be possible through scientifically-informed methods.

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.

Across the United States, the impacts of stormwater runoff are being managed through the National Pollutant Discharge Elimination System (NPDES) in an effort to restore and/or maintain the quality of surface waters. State transportation authorities fall within this regulatory framework, being tasked with managing runoff leaving their impervious surfaces. Opportunely, the highway environment also has substantial amounts of green space that may be leveraged for this purpose. However, there are questions as to how much runoff reduction is provided by these spaces, a question that may have a dramatic impact on stormwater management strategies across the country. A highway median swale, located on Asheville Highway, Knoxville, Tennessee, was monitored for hydrology over an 11-month period. The total catchment was 0.64 ha, with 0.26 ha of roadway draining to 0.38 ha of a vegetated median. The results of this study indicated that 87.2% of runoff volume was sequestered by the swale. The Source Loading and Management Model for Windows (WinSLAMM) was used to model the swale runoff reduction performance to determine how well this model may perform in such an application. To calibrate the model, adjustments were made to measured on-site infiltration rates, which was identified as a sensitive parameter in the model that also had substantial measurement uncertainty in the field. The calibrated model performed reasonably with a Nash Sutcliffe Efficiency of 0.46. WinSLAMM proved to be a beneficial resource to assess green space performance; however, the sensitivity of the infiltration parameter suggests that field measurements of this characteristic may be needed to achieve accurate results.

New technologies can sense urban environmental conditions at finer scales than previously possible. This has paved the way for monitoring microclimates between and within neighborhoods. Equally vital, though much less studied, is stakeholder engagement in understanding and using such data. This study examines interests and preferences for accessing neighborhood-scale microclimate data among residents of Knoxville, Tennessee, USA. Data are from randomly sampled phone surveys (N = 200) and purposively sampled focus group participants (N = 25). Survey participants expressed high interest in neighborhood air quality, temperature, and rainfall. Focus groups revealed four themes for designing smartphone applications or websites for neighborhood-scale data: easy access to integrated data, clear and intuitive design, information for everyday living and healthy behavior, and tools for civic engagement. Results support the value of creating meaningful, usable science interfaces with which the public can readily engage.

Urbanisation has been associated with a reduction in the long-term correlation within a streamflow series, quantified by the Hurst exponent (H). This presents an opportunity to use the H exponent as an index for the classification of catchments on a scale from natural to urbanised conditions. However, before using the H exponent as a general index, the relationship between this exponent and level of urbanisation needs to be further examined and verified on catchments with different levels of imperviousness and from different climatic regions. In this study, the H exponent is estimated for 38 (deseasonalised) mean daily runoff time series, 22 from the USA and 16 from Australia, using the traditional rescaled-range statistic (R∕S) and the more advanced multifractal detrended fluctuation analysis (MF-DFA). Relationships between H and catchment imperviousness, catchment size, annual rainfall and specific mean discharge were investigated. No clear relationship with catchment area was found, and a weak negative relationship with annual rainfall and specific mean streamflow was found only when the R∕S method was used. Conversely, both methods showed decreasing values of H as catchment imperviousness increased. The H exponent decreased from around 1.0 for catchments in natural conditions to around 0.6 for highly urbanised catchments. Three significantly different ranges of H exponents were identified, allowing catchments to be parsed into groups with imperviousness lower than 5 % (natural), catchments with imperviousness between 5 and 15 % (peri-urban) and catchments with imperviousness larger than 15 % (urban). The H exponent thus represents a useful metric to quantitatively assess the impact of catchment imperviousness on streamflow regime.