TDG prediction model improvement by analysis and validation of experiments on a dam model.

The combination of aerated flows and a high-pressure environment in a stilling basin can result in the supersaturation of total dissolved gas (TDG) downstream of hydraulic projects, posing an ecological risk to aquatic populations by inducing gas bubble disease (GBD) or other negative effects. There is limited literature reporting TDG mass transfer experiments on a complete physical dam model; most existing research is based on measurements in prototype tailwaters. In this study, TDG mass transfer experiments were conducted on a physical model of an under-constructed dam, with TDG-supersaturated water as the inflow, and TDG concentrations were meticulously monitored within the stilling basin. The measurements indicate that the TDG saturation at the outlet of the stilling basin decreased by 13.7% and 10.6% compared to the inlet for the two cases, respectively. Subsequently, an improved TDG prediction model was developed by incorporating a sub-grid air entrainment model and a phase-constrained scalar model. The numerical simulation results were compared with experimental data, indicating a maximum error in TDG saturation at all measured points of less than ± 3%. Moreover, the TDG saturation showed an error of only ± 0.3% at the outlet of the stilling basin. This model has broad applicability to various flow types for obtaining TDG mass transfer results and evaluating mitigation measures of TDG supersaturation to reduce the harmful effects on aquatic ecosystems.

Quantification and cultivation of Helicobacter pylori (H. pylori) from various urban water environments: A comprehensive analysis of precondition methods and sample characteristics.

Substantial evidence suggests that all types of water, such as drinking water, wastewater, surface water, and groundwater, can be potential sources of Helicobacter pylori (H. pylori) infection. Thus, it is critical to thoroughly investigate all possible preconditioning methods to enhance the recovery of H. pylori, improve the reproducibility of subsequent detection, and optimize the suitability for various water types and different detection purposes. In this study, we proposed and evaluated five distinct preconditioning methods for treating water samples collected from multiple urban water environments, aiming to maximize the quantitative qPCR readouts and achieve effective selective cultivation. According to the experimental results, when using the qPCR technique to examine WWTP influent, effluent, septic tank, and wetland water samples, the significance of having a preliminary cleaning step becomes more evident as it can profoundly influence qPCR detection results. In contrast, the simple, straightforward membrane filtration method could perform best when isolating and culturing H. pylori from all water samples. Upon examining the cultivation and qPCR results obtained from groundwater samples, the presence of infectious H. pylori (potentially other pathogens) in aquifers must represent a pressing environmental emergency demanding immediate attention. Furthermore, we believe groundwater can be used as a medium to reflect the H. pylori prevalence in a highly populated community due to its straightforward analytical matrix, consistent detection performance, and minimal interferences from human activities, temperature, precipitation, and other environmental fluctuations.

Assessment of rainfall-derived inflow and infiltration in sewer systems with machine learning approaches.

Rainfall-derived inflow/infiltration (RDII) modelling during heavy rainfall events is essential for sewer flow management. In this study, two machine learning algorithms, random forest (RF) and long short-term memory (LSTM), were developed for sewer flow prediction and RDII estimation based on field monitoring data. The study implemented feature engineering for extracting physically significant features in sewer flow modelling and investigated the importance of the relevant features. The results from two case studies indicated the superior capability of machine learning models in RDII estimation in the combined and separated sewer systems, and LSTM model outperformed the two models. Compared to traditional methods, machine learning models were capable of simulating the temporal variation in RDII processes and improved prediction accuracy for peak flows and RDII volumes in storm events.

TDG generation in a ski-jump spillway with a fully or partial-flip bucket.

Ski-jump spillways are frequently used as discharge structures for high dams during floods with high energy heads. The selection of bucket types at the end of spillways has a pronounced effect on the hydraulics of jet characteristics, such as trajectories and entrained air features. However, there is no literature reporting how changes in the bucket types influence TDG generation. This study compares the hydraulic characteristics and TDG mass transfer properties of a hydraulic project under construction using both the traditional fully-flip bucket and the partial-flip bucket configurations. The results indicate that, the use of the partial-flip bucket at the end of the spillway significantly disperses the water flow and yields better energy dissipation effects. At low flow rates (lower than 400 m3/s for the dam in this study), there is little difference in the downstream TDG saturation between the traditional fully-flip bucket and the partial-flip bucket, the average difference is 1.6 % in three cases with a low flow rate. However, at high flow rates (higher than 400 m3/s), the partial-flip bucket generates more TDG compared to the traditional fully-flip bucket, reaching up to 6.2 % at the maximum flow rate. This phenomenon stems from significant changes in the hydrodynamics of the stilling basin at high flow rates due to variations in the flip bucket type. When strict control of TDG generation is necessary downstream of dams, the use of the partial-flip bucket should be carefully considered. This is because, at high flow rates, the partial-flip bucket might result in higher TDG saturation than the fully-flip bucket.

Numerical study on hydraulic characteristics of rotating stepped dropshafts in deep urban tunnels.

As an important component of the deep tunnel drainage system for dealing with urban waterlogging, the rotating stepped dropshaft has been proposed due to its small air entrainment. However, the hydraulic characteristics inside the shaft still need to be fully studied. In this study, the flow patterns, water velocity, and pressure in the rotating stepped dropshaft under different flow rates and geometric parameters were studied using a three-dimensional numerical model. The results show that increasing the central angle of the step and reducing the step height can both reduce the terminal velocity. A theoretical formula for predicting the terminal velocity was established and well validated. The connection between the shaft and the outlet pipe poses a severe threat to the structural safety due to alternating positive and negative pressures. Wall-attached swirling flow generates a circular high-pressure zone at the bottom of the dropshaft and the larger the flow rate, the greater the pressure gradient at the center of the bottom. By using the momentum theorem and considering the impact pressure range of the swirling flow, the shaft bottom pressure can be predicted reasonably well.

Inflow and infiltration assessment of a prototype sanitary sewer network in a coastal city in China.

A 16-month monitoring program was conducted on a prototype sanitary system in a coastal city in China. The groundwater infiltration (GWI) on dry weather days and the rain-derived inflow and infiltration (RDII) on wet weather days were quantified and analyzed. The proportion of monthly averaged GWI to total flow can be as high as 70% during the observation period mainly due to the high groundwater level. The results also show that the ratio of RDII volume to total rainfall volume (defined as R-value) reaches a limited value of approximately 10% for the studied system when the total rainfall depth increases. A reference indicator Rlim for the limited R-value was proposed for assessing the conditions of sewer systems in terms of RDII. The Rlim value depends on local sewer conditions and in general, a lower Rlim value represents a better performance on RDII and vice versa. This study enriches the case studies on the performance of a specific sanitary sewer system on inflow and infiltration in a typical coastal city with exceptionally high groundwater levels, excess rainfall events in the monitoring season and possible typhoon events, which addresses the unique locational and hydrological properties of a representative coastal city.

Flow field and sediment removal in a stormwater sump utilizing internal structures.

This study investigated the hydraulic characteristics of stormwater sumps and their design optimization for sediment retention using physical experiments. Particle image velocimetry was utilized to measure the flow field, and the use of internal structures was investigated for improving solids retention. Results indicate that these internal structures can significantly improve the sediment removal efficiency of suspended solids with an average size of 125 µm, resulting in an efficiency improvement of 20-30%. Additionally, a modified Péclet number was proposed to more accurately evaluate the sediment removal efficiency of stormwater sumps, and recommendations were provided for further improving and optimizing sump design. This study provides insights into the hydraulic characteristics of stormwater sumps and has important implications for optimizing and designing particle removal systems for various industrial and environmental applications.

Evaluation of pollutant removal efficiency of urban stormwater wet ponds and the application of machine learning algorithms.

Wet ponds have been extensively used for controlling stormwater pollutants, such as sediment and nutrients, in urban watersheds. The removal of pollutants relies on a combination of physical, chemical, and biological processes. It is crucial to assess the performance of wet ponds in terms of removal efficiency and develop an effective modeling scheme for removal efficiency prediction to optimize water quality management. To achieve this, a two-year field program was conducted at two wet ponds in Calgary, Alberta, Canada to evaluate the wet ponds' performance. Additionally, machine learning (ML) algorithms have been shown to provide promising predictions in datasets with intricate interactions between variables. In this study, the generalized linear model (GLM), partial least squares (PLS) regression, support vector machine (SVM), random forest (RF), and K-nearest neighbors (KNN) were applied to predict the outflow concentrations of three key pollutants: total suspended solids (TSS), total nitrogen (TN), and total phosphorus (TP). Generally, the concentrations of inflow pollutants in the two study ponds are highly variable, and a wide range of removal efficiencies are observed. The results indicate that the concentrations of TSS, TN, and TP decrease significantly from the inlet to outlet of the ponds. Meanwhile, inflow concentration, rainfall characteristics, and wind are important indicators of pond removal efficiency. In addition, ML algorithms can be an effective approach for predicting outflow water quality: PLS, GLM, and SVM have shown strong potential to capture the dynamic interactions in wet ponds and predict the outflow concentration. This study highlights the complexity of pollutant removal dynamics in wet ponds and demonstrates the potential of data-driven outflow water quality prediction.

Numerical study of effects of flushing gate height and sediment bed properties on cleaning efficiency in a simplified self-cleaning device.

Sediment accumulation in combined sewers can induce blockage and odor problems. Among various cleaning methods, using self-cleaning device-generated flushing waves has been thought to be an effective solution. In this study, a series of numerical tests were conducted using CFD software to investigate the cleaning efficiency of deposited sediment particles based on a simplified self-cleaning device. The CFD model was validated by the experimental and numerical results in the literature. The effects of several parameters including the flushing gate height, sediment bed thickness, sediment bed length, and sediment bed position on cleaning efficiency were discussed. A relative accumulative transport rate was defined to analyze the cleaning efficiency. Results showed that the lowest height of the flushing gate had the best effects on sediment removal. The flushing waves generated from the sudden opening of the flushing gate were capable of cleaning sediment deposits in the given initial sediment bed thickness, length, and position. The required time duration for cleaning the sediment deposit completely increased about 6, 3, and 3 times when the sediment bed thickness, sediment bed length, and distance between the flushing gate and sediment bed increased 10, 4, and 7 times, respectively.

Long-range hydrophobic force enhanced interfacial photocatalysis for the submerged surface anti-biofouling.

Developing anti-biofouling and anti-biofilm techniques is of great importance for protecting water-contact surfaces. In this study, we developed a novel double-layer system consisting of a bottom immobilized TiO2 nanoflower arrays (TNFs) unit and an upper superhydrophobic (SHB) coating along with the assistance of nanobubbles (NBs), which can significantly elevate the interfacial oxygen level by establishing the long-range hydrophobic force between NBs and SHB and effectively maximize the photocatalytic reaction brought by the bottom TNFs. The developed NBs-SHB/TNFs system demonstrated the highest bulk chemical oxygen demand (COD) reduction efficiency at approximately 80% and achieved significant E. coli and Chlorella sp. inhibition efficiencies of 5.38 and 1.99 logs. Meanwhile, the system showed a sevenfold higher resistance to biofilm formation when testing in a wastewater matrix using a wildly collected biofilm seeding solution. These findings provide insights for implementing nanobubble-integrated techniques for submerged surface protection.

Experimental study on pollution release and sediment scouring of sewage sediment in a drainage pipe considering incubation time.

The pollution release and the antiscourability characteristics of pipe sewage sediments can directly determine the blockage status of pipelines and the treatment burden at the outflow (sewage treatment plant). In this study, sewer environments with different burial depths were designed to explore the impact of incubation time on microbial activity, and the impacts of microbial activity on the physicochemical characteristics, pollution release effect and antiscouring ability of the silted sediment in the drainage pipe were further explored. The results showed that the incubation time, sediment matrix, temperature and dissolved oxygen affected microbial activity, but temperature had a greater influence. These factors affected microbial activity and loosened the superstructure in the sediment. In addition, by measuring the indices of nitrogen and phosphorus in the overlying water, it was found that sediment incubated for a certain time released pollutants into the overlying water, and the release amount was obviously affected by high temperature (e.g. 35 ℃). After a certain time (e.g. 30 days), biofilms appeared on the sediment surface, and the antiscourability of sediment was significantly improved, which was reflected in the increase in the median particle size of sediment left in the pipe.

Evolution process and failure mechanism of a large expressway roadside landslide.

Site investigation, deformation monitoring, laboratory test, and theoretical calculations were used to analyze the evolution details of a large expressway roadside landslide during the start-up sliding process. The monitoring results show that the initial deformation and failure occurred on the protective wall at the slope toe, then gradually developed to the upper part of the slope, and finally led to tensile cracks at the slope trailing edge. Accelerated deformation of the slope support structures, such as the protective wall at the slope toe, the anti-slide pile, and the anchor cable, were observed during the continuous extreme rainfall. The infiltrated rainwater can change the weight, the osmotic pressure, the anti-sliding force, the sliding force of the sliding mass, and further soften the fully weathered tuff soil and reduce its strength, resulting in the landslide occurrence. Block the slope surface runoff is an effective measure to reduce the landslide risk. The current analysis will be helpful to the prevention, control, and emergency disposal of similar landslides.

Indigenous microbial community governs the survival of Escherichia coli O157:H7 in constructed wetlands.

The survival pattern of Escherichia coli O157:H7 (E. coli O157:H7) and its regulatory factors in natural environments have been widely studied. However, there is little information about the survival of E. coli O157:H7 in artificial environments, especially in wastewater treatment facilities. In this study, a contamination experiment was performed to explore the survival pattern of E. coli O157:H7 and its central control factors in two constructed wetlands (CWs) under different hydraulic loading rates (HLRs). The results showed that the survival time of E. coli O157:H7 was longer in the CW under the higher HLR. Substrate ammonium nitrogen and available phosphorus were the main factors that influenced the survival of E. coli O157:H7 in CWs. Despite the minimal effect of microbial α-diversity, some keystone taxa, such as Aeromonas, Selenomonas, and Paramecium, governed the survival of E. coli O157:H7. In addition, the prokaryotic community had a more significant impact on the survival of E. coli O157:H7 than the eukaryotic community. The biotic properties had a more substantial direct power on the survival of E. coli O157:H7 than the abiotic factors in CWs. Collectively, this study comprehensively disclosed the survival pattern of E. coli O157:H7 in CWs, which is an essential addition to the environmental behavior of E. coli O157:H7, providing a theoretical basis for the prevention and control of biological contamination in wastewater treatment processes.

Stratification and its consequences in two constructed urban stormwater wetlands.

Stratification in constructed urban stormwater wetlands is one of the fundamental physical processes that affect hydrodynamics, transport and fate of stormwater pollutants. Adverse effects of stratification include decreasing pollutant retention capacity, causing the water at lower depths to become anoxic, degrading water quality and increasing stress on the downstream aquatic communities. The current study reports on a comprehensive field monitoring program of stratification and hydrodynamics in two ice-free seasons (May - October) in two constructed urban stormwater wetlands in Calgary, Canada, with different inlet, outlet, morphometric and vegetation designs. Despite their small sizes of 0.5 and 1.2 ha and shallow water depths of 0.8 m, stratification was strong and persistent in the wetlands. The response of stratification and mixing to atmospheric forcings (e.g., air temperature, atmospheric instability, rainfall depth, wind speed) and the impact of design characteristics (inlet/outlet design, water depth, surface area and aquatic vegetation) were examined and discussed. Thermal stratification, defined as a vertical temperature gradient >1 °C/m, was found to be significantly higher (up to ten times) near the inlets and last longer (up to twice) than in the main cells and the outlet basins due to the relatively cold summer inflows. The wetland with twice the permanent water volume and surface area and half the length-to-width ratio had denser submerged aquatic vegetation, higher (by up to 2 °C) water temperature and more severe (up to eight times) thermal stratification. Strong densimetric stratification and low wind stress on the water surface caused hypoxic conditions near the bed, potentially adversely affecting water quality and downstream aquatic communities.

Constructed wetlands as hotspots of antibiotic resistance genes and pathogens: Evidence from metagenomic analysis in Chinese rural areas.

In rural China, many constructed wetlands (CWs) have been developed to treat rural wastewater sustainably. However, due to the scarce information on those rural CWs, it is difficult to analyze the biological contaminants within those systems, such as antibiotic resistance genes (ARGs) and pathogens. Based on the data collected from two pilot-scale, one-year-observed CWs, for the first time, this study explored the accumulation of ARGs and pathogens using the metagenomic sequencing approach and SourceTracker analysis under different hydraulic loading rates. The Shannon index of ARGs in the effluent surpassed the level found in the influent. The DESeq2 analysis showed that up to 21.49% of the total pathogen species had increased relative abundance in the effluent compared with the influent. By combining the contribution of substrate and rhizosphere, the CW became a more influencing factor for ARGs and pathogens contamination than the influent. The network analysis revealed a critical but latent fact that the development of antibiotic-resistant pathogens is highly likely to be triggered by the co-occurrence of ARGs and pathogens. Collectively, from the aspect of biological risk, our study showed that CWs alone might not be an ideal solution for improving wastewater treatment in rural China.

Simultaneous use of nitrate and calcium peroxide to control sulfide and greenhouse gas emission in sewers.

The sewer system is a significant source of hydrogen sulfide (H2S) and greenhouse gases which has attracted extensive interest from researchers. In this study, a novel combined dosing strategy using nitrate and calcium peroxide (CaO2) was proposed to simultaneously control sulfide and greenhouse gases, and its performance was evaluated in laboratory-scale reactors. Results suggested that the addition of nitrate and CaO2 improved the effectiveness of sulfide control. And the combination index method further proved that nitrate and CaO2 were synergistic in controlling sulfide. Meanwhile, the combination of nitrate and CaO2 substantially reduced greenhouse gas emissions, especially the carbon dioxide (CO2) and methane (CH4). The microbial analysis revealed that the combined addition greatly stimulated the accumulation of nitrate reducing-sulfide oxidizing bacteria (NR-SOB) that participate in anoxic nitrate-dependent sulfide oxidation, while the abundance of heterotrophic denitrification bacteria (hNRB) was reduced significantly. Moreover, the presence of oxygen and alkaline chemicals generated by CaO2 facilitated the inhibition of sulfate-reducing bacteria (SRB) activities. Therefore, the nitrate dosage was diminished significantly. On the other hand, the generated alkaline chemicals promoted CO2 elimination and inhibited the activities of methanogens, leading to a decrease of CO2 and CH4 fluxes, which facilitated elimination of greenhouse effects. The intermittent dosing test showed that the nitrate and CaO2 could be applied intermittently for sulfide removal. And the chemical cost of intermittent dosing strategy was reduced by 85 % compared to the continuous dosing nitrate strategy. Therefore, intermittent dosing nitrate combined with CaO2 is probably an effective and economical approach to control sulfide and greenhouse gases in sewer systems.

Impact of rainfall characteristics on urban stormwater quality using data mining framework.

Understanding the impact of rainfall characteristics on urban stormwater quality is important for stormwater management. Even though significant attempts have been undertaken to study the relationship between rainfall and urban stormwater quality, the knowledge developed may be difficult to apply in commercial stormwater management models. A data mining framework was proposed to study the impacts of rainfall characteristics on stormwater quality. A rainfall type-based calibration approach was developed to improve water quality model performance. Specifically, the relationship between rainfall characteristics and stormwater quality was studied using principal component analysis and correlation analysis. Rainfall events were classified using a K-means clustering method based on the selected rainfall characteristics. A rainfall type-based (RTB) model was independently calibrated for each rainfall type to obtain optimal parameter sets of stormwater quality models. The results revealed that antecedent dry days, average rainfall intensity, and rainfall duration were the most critical rainfall characteristics affecting the event mean concentrations (EMCs) of total suspended solids, total nitrogen, and total phosphorus, while total rainfall was found to be of negligible importance. The K-means method effectively clustered the rainfall events into four types that could represent the rainfall characteristics in the study areas. The rainfall type-based calibration approach can considerably improve water quality model accuracy. Compared to the traditional continuous simulation model, the relative error of the RTB model was reduced by 11.4 % to 16.4 % over the calibration period. The calibrated stormwater quality parameters can be transferred to adjacent catchments with similar characteristics.

Toward an intensive understanding of sewer sediment prokaryotic community assembly and function.

Prokaryotic communities play important roles in sewer sediment ecosystems, but the community composition, functional potential, and assembly mechanisms of sewer sediment prokaryotic communities are still poorly understood. Here, we studied the sediment prokaryotic communities in different urban functional areas (multifunctional, commercial, and residential areas) through 16S rRNA gene amplicon sequencing. Our results suggested that the compositions of prokaryotic communities varied significantly among functional areas. Desulfomicrobium, Desulfovibrio, and Desulfobacter involved in the sulfur cycle and some hydrolytic fermentation bacteria were enriched in multifunctional area, while Methanospirillum and Methanoregulaceae, which were related to methane metabolism were significantly discriminant taxa in the commercial area. Physicochemical properties were closely related to overall community changes (p < 0.001), especially the nutrient levels of sediments (i.e., total nitrogen and total phosphorus) and sediment pH. Network analysis revealed that the prokaryotic community network of the residential area sediment was more complex than the other functional areas, suggesting higher stability of the prokaryotic community in the residential area. Stochastic processes dominated the construction of the prokaryotic community. These results expand our understanding of the characteristics of prokaryotic communities in sewer sediment, providing a new perspective for studying sewer sediment prokaryotic community structure.

Experimental study of sediment washout from stormwater sumps.

Sumps are commonly used in urban stormwater systems, which can be considered as a simple pretreatment device for stormwater quality control. However, they may function as pollution sources due to sediment washout under high flow conditions. An experimental study was conducted to investigate the scour process of predeposited sediments from a sump and its influencing parameters. Under conditions with large inflows or high sediment deposit, the sediment particles could be resuspended, entrained and flushed out. The washout mass decreased exponentially with time if the sediment bed surface depth was larger than a threshold value; otherwise, the amount of washout would be much smaller. The same scour pattern was observed for all the testing cases, of which the largest scour depth always occurred below the outlet. The deposit below the inlet might increase under conditions with high flow rates and low levels of sediment bed. Dimension analysis was performed and principal non-dimensional parameters were found, including the Péclet number, the pipe Froude number, and the dimensionless particle diameter, which can be used to determine whether the washout would occur and its intensity in a stormwater sump under given conditions.

Field observations of stratification in stormwater wet ponds.

Stratification is one of the fundamental physical processes that may have a significant impact on water quality in stormwater wet ponds. However, the role of thermal and chemical stratifications in governing water quality processes is not fully understood. This is in part due to the lack of detailed field measurements of sufficient governing parameters over time periods that span a wide range of environmental conditions. To fill this gap, a comprehensive 2-year field program was undertaken in two stormwater wet ponds in Calgary, Alberta, Canada, during the ice-free season from May to November in 2018 and 2019. At different locations in each pond, thermal and chemical stratifications were observed, thermocline depth and strength were determined, and continuous water velocity profiles were measured. In addition, the effect of local weather conditions on stratification, thermocline, and hydrodynamics was investigated. The results showed that the ponds had vertical water temperature differences >1 °C for 99% of the time, May to August. In addition, salt-laden inflows from road deicing salts led to strong chemical stratification up to five times stronger in the sediment forebays than in the main cells in spring. Wind-induced surface currents were insignificant, scaling at 0.3% of the wind speed with negligible impact on vertical mixing in the ponds. Our results demonstrate that the ponds' strong and prolonged stratification decreased pollutant retention capacity and caused the water at depth to become anoxic, degrading the quality of the water discharged downstream. Hence, additional consideration of stratification is required when designing new stormwater ponds.