Occurrence, Sources and Virulence Potential of Arcobacter butzleri in Urban Municipal Stormwater Systems.

A. butzleri is an underappreciated emerging global pathogen, despite growing evidence that it is a major contributor of diarrheal illness. Few studies have investigated the occurrence and public health risks that this organism possesses from waterborne exposure routes including through stormwater use. In this study, we assessed the prevalence, virulence potential, and primary sources of stormwater-isolated A. butzleri in fecally contaminated urban stormwater systems. Based on qPCR, A. butzleri was the most common enteric bacterial pathogen [25%] found in stormwater among a panel of pathogens surveyed, including Shiga-toxin producing Escherichia coli (STEC) [6%], Campylobacter spp. [4%], and Salmonella spp. [<1%]. Concentrations of the bacteria, based on qPCR amplification of the single copy gene hsp60, were as high as 6.2 log10 copies/100 mL, suggesting significant loading of this pathogen in some stormwater systems. Importantly, out of 73 unique stormwater culture isolates, 90% were positive for the putative virulence genes cadF, ciaB, tlyA, cjl349, pldA, and mviN, while 50-75% of isolates also possessed the virulence genes irgA, hecA, and hecB. Occurrence of A. butzleri was most often associated with the human fecal pollution marker HF183 in stormwater samples. These results suggest that A. butzleri may be an important bacterial pathogen in stormwater, warranting further study on the risks it represents to public health during stormwater use.

Land use and rainfall influences on bacterial levels and sources in stormwater ponds.

Urban stormwater runoff is a known source of microbial contamination of stormwater ponds. However, less is known about the influences of land use and rainfall on microbial quality over time in these receiving waters. In this study, two fecal indicator bacteria (FIB), namely Escherichia coli and thermotolerant coliforms, were monitored in three stormwater ponds in Calgary, Alberta, Canada. The stormwater ponds were selected due to their potential as water sources for beneficial uses such as irrigation, which requires lower water quality than drinking water, thereby alleviating the pressure on the city's potable water demands. The selected stormwater ponds vary in size and shape, contribution catchment size, and percentages of several primary land use types. Microbial source tracking for human, dog, seagull, Canada goose, ruminant, and muskrat was also conducted to determine sources of bacterial contamination in the stormwater ponds. Sampling was conducted near the pond surface and adjacent to the shoreline, specifically near the outfalls that discharge stormwater runoff into the ponds and the inlets that convey water out of the ponds. Overall, the FIB concentrations in the vicinity of pond outfalls were significantly or relatively higher than those near pond inlets. The contamination in the McCall Lake and the Country Hills stormwater ponds showed higher amounts of human markers (40 to 60%) compared to the Inverness stormwater pond (< 20%), which coincided with their higher FIB concentration medians. The results revealed that stormwater drained from catchments with a higher percentage of commercial land use was more contaminated than those with primary residential land use, while the impacts of residential development on the FIB levels in the Inverness stormwater pond were not obvious. Furthermore, FIB concentrations in the ponds increased in response to both rain events and inter-event dry periods, with human-specific markers being predominant despite the high levels of animal markers during inter-event dry periods. Human-origin sources might be among the main microbial loading contributors in the pond catchments in general. All these findings can inform the development or improvement of measures for mitigating microbial pollution, strategies for reusing stormwater, and maintenance programs.

Sensors for Biomass Monitoring in Vegetated Green Infrastructure: A Review.

Bioretention cells, or rain gardens, can effectively reduce many contaminants in polluted stormwater through phytoremediation and bioremediation. The vegetated soil structure develops bacterial communities both within the soil and around the vegetation roots that play a significant role in the bioremediative process. Prediction of a bioretention cell's performance and efficacy is essential to the design process, operation, and maintenance throughout the design life of the cell. One of the key hurdles to these important issues and, therefore, to appropriate designs, is the lack of effective and inexpensive devices for monitoring and quantitatively assessing this bioremediative process in the field. This research reviews the available technologies for biomass monitoring and assesses their potential for quantifying bioremediative processes in rain gardens. The methods are discussed based on accuracy and calibration requirements, potential for use in situ, in real-time, and for characterizing biofilm formation in media that undergoes large fluctuations in nutrient supply. The methods discussed are microscopical, piezoelectric, fiber-optic, thermometric, and electrochemical. Microscopical methods are precluded from field use but would be essential to the calibration and verification of any field-based sensor. Piezoelectric, fiber-optic, thermometric, and some of the electrochemical-based methods reviewed come with limitations by way of support mechanisms or insufficient detection limits. The impedance-based electrochemical method shows the most promise for applications in rain gardens, and it is supported by microscopical methods for calibration and validation.

A Velocity Meter for Quantifying Advection Velocity Vectors in Large Water Bodies.

A velocity meter was designed and built in order to meet market needs for an affordable instrument that measures the range of velocity magnitudes and direction experienced in medium- to large-sized water bodies. The velocity meter consists of a graduated plate with an injector protruding from the center and a camera held downward above the plate. Once the Dye Injection Velocity (DIV) meter is in the flow, dye is injected and the camera records the dye fluid transport. The recorded video is analyzed to determine the local flow velocity and direction. The DIV was calibrated for a range of velocities between 0.0094 m/s and 0.1566 m/s using particle image velocimetry (PIV) in a flow visualization flume. The accuracy of the instrument was found to be +6.3% and -9.8% of full scale. The coefficient of determination of the calibration curve was equal to 98%. Once calibrated, the DIV was deployed to the Inverness Stormwater pond in Calgary, Canada, for validation tests against an Acoustic Doppler Velocity (ADV) meter. During the validation tests, both flow velocity magnitude and direction were measured at several spatial points. The velocity magnitude results showed good agreement and the Mann-Whitney test showed no statistically significant difference (p-value > 0.05). At two spatial points, the differences between direction data were significant, which could be caused by the random errors involved in the validation test. However, the averaged data showed good agreement.

The impact of media, plants and their interactions on bioretention performance: A review.

Bioretention systems have gained considerable popularity as a more natural approach to stormwater management in urban environments. The choice of bioretention media is frequently cited as one of the critical design parameters with the ultimate impact on the performance of the system. The goal of this review is to highlight data that challenge the importance of media as being the dominant design parameter and argue that the long-term performance is shaped by the interactions between media and the living components of a bioretention system, especially vegetation. Some of the key interactions are related to the impact of plant roots on media pore structure, which has implications on infiltration, storage capacity, and treatment. Another relevant interaction pertains to evapotranspiration and the associated impacts on the water balance and the water quality performance of bioretention systems. The impacts of vegetation on the media are highlighted and actual, as well as potential, impacts of plant-media interactions on bioretention performance are presented.

Phosphorus and nitrogen storage, partitioning, and export in a large gravel bed river.

Nutrient dynamics in a 25 km long treated wastewater effluent impacted reach of a large, gravel-bed river were evaluated in five river compartments: surficial sediment, surface water, hyporheic zone water, and aquatic biomass (including epilithic algae and macrophytes). Nutrient storage within, and export from, the river reach, was quantified to assess the impact of WWTP effluent on nutrient dynamics. More than 98% of N and P storage was found in the surficial river bed sediment, where it is available to support epilithic algal and macrophyte growth. Nutrient export from the river reach by sediment, hyporheic water, and biomass were small compared to water column transport. The N:P ratios for the five different compartments suggested that the water column was severely P limited, whereas sediment, hyporheic water, and aquatic biomass tended towards co-limitation and N limitation. Within the river reach, the majority of P was stored immediately downstream of the WWTP effluent outfall, whereas N was retained at a higher rate relative to P in the remainder of the reach. Correlation analysis of nutrient exchange between different compartments suggested that multiple nutrient compartments should be considered when establishing nutrient loading criteria. Nutrient analysis in multiple compartments in the river can add valuable insight into nutrient dynamics and nutrient limitation.

Response of green roof performance to multiple hydrologic and design variables: a laboratory investigation.

Multiple factors affect green roof performance and their effects might vary at different stages of operation. This paper aimed to link green roof performance to hydrologic variables (antecedent moisture condition (AMC) and rainfall intensity) and design variables (growing medium (GM) type and depth) under multiple dimensions at the early stage of operation using laboratory experiment data. The results showed that the AMC is the most influential factor of hydrologic performance, whereas the GM type appeared to primarily affect the nutrient levels of the outflow. The significant main effects of other variables and interaction effects between two variables point to challenges in green roof design.

River flood prediction using fuzzy neural networks: an investigation on automated network architecture.

Urban floods are one of the most devastating natural disasters globally and improved flood prediction is essential for better flood management. Today, high-resolution real-time datasets for flood-related variables are widely available. These data can be used to create data-driven models for improved real-time flood prediction. However, data-driven models have uncertainty stemming from a number of issues: the selection of input data, the optimisation of model architecture, estimation of model parameters, and model output. Addressing these sources of uncertainty will improve flood prediction. In this research, a fuzzy neural network is proposed to predict peak flow in an urban river. The network uses fuzzy numbers to account for the uncertainty in the output and model parameters. An algorithm that uses possibility theory is used to train the network. An adaptation of the automated neural pathway strength feature selection (ANPSFS) method is used to select the input features. A search and optimisation algorithm is used to select the network architecture. Data for the Bow River in Calgary, Canada are used to train and test the network.

Relative importance of P and N in macrophyte and epilithic algae biomass in a wastewater-impacted oligotrophic river.

The role of nutrient loading on biomass growth in wastewater-impacted rivers is important in order to effectively optimize wastewater treatment to avoid excessive biomass growth in the receiving water body. This paper directly relates wastewater treatment plant (WWTP) effluent nutrients (including ammonia (NH3-N), nitrate (NO3-N) and total phosphorus (TP)) to the temporal and spatial distribution of epilithic algae and macrophyte biomass in an oligotrophic river. Annual macrophyte biomass, epilithic algae data and WWTP effluent nutrient data from 1980 to 2012 were statistically analysed. Because discharge can affect aquatic biomass growth, locally weighted scatterplot smoothing (LOWESS) was used to remove the influence of river discharge from the aquatic biomass (macrophytes and algae) data before further analysis was conducted. The results from LOWESS indicated that aquatic biomass did not increase beyond site-specific threshold discharge values in the river. The LOWESS-estimated biomass residuals showed a variable response to different nutrients. Macrophyte biomass residuals showed a decreasing trend concurrent with enhanced nutrient removal at the WWTP and decreased effluent P loading, whereas epilithic algae biomass residuals showed greater response to enhanced N removal. Correlation analysis between effluent nutrient concentrations and the biomass residuals (both epilithic algae and macrophytes) suggested that aquatic biomass is nitrogen limited, especially by NH3-N, at most sampling sites. The response of aquatic biomass residuals to effluent nutrient concentrations did not change with increasing distance to the WWTP but was different for P and N, allowing for additional conclusions about nutrient limitation in specific river reaches. The data further showed that the mixing process between the effluent and the river has an influence on the spatial distribution of biomass growth.

Characteristics of suspended solids, microorganisms, and chemical water quality in event-based stormwater runoff from an urban residential area.

Temporal evolution of microbiological, physical, and chemical quality of stormwater runoff from a stormwater drain in an urban residential area in Calgary, Canada, was investigated from May to September, 2006 and 2007. Investigating event mean concentrations and their correlations with rainfall characteristics revealed that intensive rainfall events produced highly polluted stormwater runoff when pollutant source limitation did not occur. Inconsistent event-based correlations between total suspended solids (TSS) concentrations and water quality parameters were observed. During storms, the loading of TSS exhibited a flow-dependent nature, whereas microorganism discharge appeared to be governed by a flow-independent mechanism. No strong first-flush effect was observed in either TSS or microorganisms, on average. No correlations of first-flush loads of TSS with rainfall characteristics were identified. Moderate negative correlations between first-flush loads of microorganisms and rainfall depth and intensity indicated that first flush of microorganisms tended to occur in small storms.