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Key Takeaways: Biennial data from 2017 to 2023 show that water and sewer prices increased substantially, from an average combined monthly price of $79.39 in 2017 to $95.02 in 2023 at 6,200 gallons per month for single‐family residential customers. Water rate structures became more regressive during that time, with utilities collecting an increasing share of revenue through fixed charges and less revenue through volumetric charges. Average low‐income affordability in the United States has worsened over the past six years, mainly driven by extreme unaffordability in a small minority of utilities. [ABSTRACT FROM AUTHOR]

Risk analysis (including resilience analysis) of infrastructure requires models that describe the connection of components and subsequent flow dynamics. However, the detailed information needed to define these models may not be available, especially for small‐scale infrastructure that connect to every building. In this paper, we generate location‐specific small‐scale networks using detailed data that should always be available. We propose a general framework where we generate the network topology, we estimate the resource demand at each building, and we design the network components to meet the demands. This general framework is applicable to all types of infrastructure, but many procedures are specific to the type of network being generated. This paper develops the necessary procedures to generate sewer networks and illustrates the usage for an example network in a small study area in Seaside, Oregon. The proposed sewer network generator produces realistic sewer networks as compared to the real network of Seaside. [ABSTRACT FROM AUTHOR]

Flooding in urban areas is expected to increase its magnitude and frequency in the future. Therefore, there is a strong need to better model sewer–surface flow interactions. Existing numerical methods are commonly based on simplified representations of sewer/surface mass exchange, and mainly validated in steady flow conditions. Current methodologies describing the propagation of transient conditions/waves through interaction nodes are simplified, rely on empirical coefficients and/or lack detailed validation. In this paper, an integrated numerical approach for modelling the propagation of water waves through interaction nodes (e.g., manholes) is presented. In this solution, the shallow water equations are used to simulate the free‐surface propagation inside the sewer network, and an ordinary differential equation is employed for modelling flow regimes through pipes and manholes. The model proposed is validated against the well‐known STAR‐CD modelling software for a number of test cases. Finally, further validation is performed against experimental data describing the evolution of water depth around a manhole in unsteady surcharging conditions. [ABSTRACT FROM AUTHOR]

Increasingly, collective actors in Europe, such as in the Netherlands and Italy, turn to litigation as the preferred strategy to attain their goals. Both at the national level and at the European level, civil society organisations (CSOs) are active in high‐profile cases, for example, in the field of asylum law. These CSOs operate in a different national political and legal system but do have similar European‐level opportunities. However, the extent to which European Union (EU) law is mobilised differs per CSO. This begs the following key question: Why do some CSOs mobilise EU law more frequently than others? Using empirical data, this article attempts to uncover what factors are relevant for four CSOs from Italy and the Netherlands whether to mobilise EU law or not. Most importantly, the article concludes that the framing of EU legal opportunities by the CSOs is considered to be relevant in (non‐)mobilisation of EU law. [ABSTRACT FROM AUTHOR]

South Carolina's Beaufort‐Jasper Water and Sewer Authority optimized its wastewater systems using Partnership for Clean Water goals. [ABSTRACT FROM AUTHOR]

The inactivation kinetics of total coliforms to increase the pathogenic removal efficiency in a full‐scale ozonation contactor in a wastewater treatment plant in Algeria is investigated. An enhanced ozone contactor design is proposed and 3D multiphase computational fluid dynamics simulations were conducted to optimize the operating parameters, including flow rates, ozone concentrations considering the treatment performance, and total operating cost. The existing design has several limitations, including poor mass‐transfer efficiency and uneven distribution of dissolved ozone. To address these issues, the optimized design includes new injection‐point settings and an increased number of diffusers. The optimized design achieved a significant improvement in mass transfer efficiency. The ozone treatment effectively reduced the total coliform counts in the wastewater samples compared to the existing design. The Chick‐Watson model predicted inactivation kinetics, with a reduction of up to 99.997 %. The practical implications of this research can significantly improve the inactivation kinetics of ozone treatments. [ABSTRACT FROM AUTHOR]

This paper proposes a method for reducing the environmental impact of sewer network (SN) overflows. The main objective of the paper is to minimize the wastewater quantity and the pollutant loads that overflow from the SN. The proposed algorithm to achieve this goal is Model Predictive Control using Particle Swarm Optimization as optimization method. It was tested in simulation using a simplified model of the network based on Benchmark Simulation Modelsewer as prediction model, and a forecasted influent. Three cases have been considered: (a) the fitness function is defined as the global yearly overflow volume calculated using equal weights for each tank; (b) the fitness function uses different weights for each tank depending on the medium loads and (c) integrating a penalty term related to the system state at the end of the prediction horizon in the previous fitness function. The simplified model determined a significant reduction of the integration time minimizing the optimization time. Key Points: Model Predictive Control is used to reduce pollution caused by sewer network (SN) overflowsSimplified SN flow model decreases the optimization time of the control algorithmPollutant loads are assessed by the control algorithm by weighting overflow volumes with values calculated based on offline measurements [ABSTRACT FROM AUTHOR]

Overflow is usually used to keep fluid continuously flowing to avoid the fluid from changing flow direction and subsequently inducing large stresses. To explore the mechanism of flow‐induced stress evolution, a flow model was established in terms of compressible, non‐isothermal, and viscoelastic flow. Based on the Leonov model and the mid‐plane approach, a pseudo‐Poisson type equation for pressure was derived to decouple the interdependence between velocity and pressure. To improve computational efficiency, a numerical approach involving double iterations was proposed to solve the flow problem. Two kinds of mold cavities, with and without overflow, were designed and manufactured. Molding experiments were conducted, and corresponding simulations based on the proposed model and algorithm were performed. The results show that the simulated contours of flow‐induced stress are in good agreement with the photoelastic streaks. The use of overflow can significantly reduce flow‐induced stresses. If the slot thickness is set to a proper value, the flow‐induced stress can be reduced by more than 80%. On the other hand, a slot that is too thick does not have significant reducing effects. Therefore, using overflow to reduce flow‐induced stresses during transparent part production is a promising approach if the material cost is worthy of the quality. Highlights: A double iteration method is proposed for viscoelastic flow problem.Overflow can reduce the stress as much as 80% if the dimension is properly set.The simulated stress streaks are in good agreement with photoelasticities. [ABSTRACT FROM AUTHOR]

Forecasting of wastewater treatment plant inflow dynamics constitutes an enabler technology for wastewater treatment process optimization using model predictive control. However, accurate inflow prediction is still challenging, especially for strong rainfall events, where complex system dynamics and missing information on future rainfall represent limiting factors. We propose a seasonal probabilistic time series model for modeling the short‐term wastewater inflow accurately while providing quantification of forecast uncertainty. To ensure suitability for practical implementation, the unconstrained parameters of the predictive distribution are modeled as linear functions of the input variables in the framework of Generalized Additive Models for Location Scale and Shape. Non‐linear effects are approximated by Rectified Linear Units, accounting for buffering within the sewer network and flow‐dependent catchment response time. In addition to water level measurements from within the sewer network and rain rate measurements, rain forecasts are incorporated as exogenous regressors, where historical rain forecasts are used for model calibration. The model performance is evaluated on historical data from a German wastewater treatment plant using deterministic and probabilistic scoring rules. We benchmark against an autoregressive time series model and a long short‐term memory artificial neural network. Our results show that the proposed model unites the benefits of high prediction accuracy of the neural network and enhanced intelligibility of the autoregressive model, but accurate real‐time rain forecasts are mandatory for successful real‐world implementation. Plain Language Summary: The wastewater treatment process accounts for a large proportion of a wastewater treatment plant's energy consumption. Here, an accurate prediction of future wastewater inflow is an important tool for the optimization of energy efficiency. The potential for optimization is particularly large for rain events. However, especially in such situations, inflow prediction is most challenging. We developed a specialized computer algorithm for inflow prediction that utilizes weather forecasts in order to produce reliable inflow predictions in such situations. The developed algorithm is a machine learning model that learns the knowledge needed to perform accurate predictions from historical data. Although capable machine learning models are generally complex, we aimed to design the algorithm in such a way that it is understandable and hence trustworthy for practitioners so that it can easily be used in real‐world application. We tested the algorithm and our results show that it is possible to generate precise wastewater inflow predictions, but very accurate and quickly available weather forecasts are mandatory, which is an interesting objective for further research. Key Points: We propose a model for probabilistic wastewater treatment plant inflow prediction utilizing rain forecast data to handle rain eventsNon‐linear dynamics within the sewer system are approximated in a linear framework using rectified linear unitsOur results indicate similar performance to less intelligible non‐linear models, but rain forecast accuracy constitutes a limitation [ABSTRACT FROM AUTHOR]

Sanitary sewer systems are major infrastructures in every modern city, which are essential in protecting water pollution and preventing urban waterlogging. Since the conditions of sewer systems continuously deteriorate over time due to various defects and extrinsic factors, early intervention in the defects is necessary to prolong the service life of the pipelines. However, prior works for defect inspection are limited by accuracy, efficiency, and economic cost. In addition, the current loss functions in object detection approaches are unable to handle the imbalanced data well. To address the above drawbacks, this paper proposes an automatic defect detection framework that accurately identifies and localizes eight types of defects in closed‐circuit television videos based on a deep neural network. First, an effective attention module is introduced and used in the backbone of the detector for better feature extraction. Then, a novel feature fusion mechanism is presented in the neck to alleviate the problem of feature dilution. After that, an efficient loss function that can reasonably adjust the weight of training samples is proposed to tackle the imbalanced data problem. Also, a publicly available dataset is provided for defect detection tasks. The proposed detection framework is robust against the imbalanced data and achieves a state‐of‐the‐art mean average precision of 73.4%, which is potentially applied in realistic sewer defect inspections. [ABSTRACT FROM AUTHOR]

Morphometric properties of channel networks are useful tools to classify catchments and calculate their hydrological response. Scaling laws have been established for Optimal Channel Networks (OCNs), which are defined based on a generative geomorphological mechanism of minimizing the total energy dissipation. However, sewer networks obey engineering efficiency rules and are conceived based on local optimizations, both in time and space, for minimal costs. Not all the scaling laws have been verified for artificial sewer networks found in urban areas. This raises questions regarding the applicability of OCN scaling laws to sewer networks and their potential impact on the shape of the Geomorphological Instantaneous Unit Hydrograph (GIUH). Hence, this work aims to study the morphometric properties of the Greater Paris combined sewer system through a case study on twelve nested subcatchments. A two‐step methodology is used. First, the morphometric properties are analysed using the reference Horton‐Strahler, Rodríguez‐Iturbe and Moussa‐Bocquillon scaling laws. The results show that Horton‐Strahler's laws of bifurcation are verified while the length and area laws are not always verified. Rodriguez‐Iturbe and Moussa‐Bocquillon laws are verified with slightly different values of the descriptors in comparison to OCNs. Second, these morphometric properties are used to calculate four GIUHs: the reference Width Function (GWF), the Nash unit hydrograph (GN) using Horton‐Strahler ratios, the Nash Unit Hydrograph equivalent (GNe) using Moussa‐Bocquillon descriptors, and the Hayami function (GH) solution of the diffusive wave equation. We identified four catchments for which the scaling laws are verified and therefore all GIUHs are similar while for four other catchments the scaling laws are not verified and strongly impact the GIUHs. These morphometric descriptors and the GIUHs can be considered as 'hydrological signatures' of Combined Sewer Systems (CSSs) and are useful for the comparison and classification of hydrological responses. [ABSTRACT FROM AUTHOR]

Urban areas are constantly developing and thereby affect the local water cycle. Real‐time control (RTC) strategies are used to operate urban drainage systems optimally during these transitions. This paper aims to develop a methodology to study the impacts of common gradual changes occurring in the urban environment (densification of the urban area and implementation of blue‐green infrastructure), forming cumulative transitions, on the functioning of real‐time optimization procedures. A new generic methodology, relying on a comprehensive evaluation strategy based on three indicators assessing the continued optimal performance of RTC was proposed. This methodology was applied to two urban drainage catchments in Eindhoven and Rotterdam using both probabilistic and projected transitional paths. Based on the results obtained it can be noted that the performances of the RTC procedures were not strongly affected by the modeled transitions although the relative performance compared to the maximum performance potential decreases significantly with the large‐scale implementation of blue‐green infrastructure, indicating that the revision of RTC procedures could improve the sewer system functioning further. The relative performance loss associated with the modeled transitions was higher for model predictive control compared to heuristic RTC procedures for one case study and vice versa for the other. Continuous re‐evaluation of the RTC strategy is, therefore, an important but overlooked part of the implementation of RTC procedures. Key Points: Urban transitions are modeled to assess the effect on optimal control (RTC) efficacyStrong divergence from optimality was associated with SUDS implementationLong‐term implementation of RTC should include a regular re‐evaluation of the strategy [ABSTRACT FROM AUTHOR]

Sewer systems are an essential part of sanitation infrastructure for protecting human and ecosystem health. Initially, they were used to solely convey stormwater, but over time municipal sewage was discharged to these conduits and transformed them into combined sewer systems (CSS). Due to climate change and rapid urbanization, these systems are no longer sufficient and overflow in wet weather conditions. Mechanistic and data‐driven models have been frequently used in research on combined sewer overflow (CSO) management integrating low‐impact development and gray‐green infrastructures. Recent advances in measurement, communication, and computation technologies have simplified data collection methods. As a result, technologies such as artificial intelligence (AI), geographic information system, and remote sensing can be integrated into CSO and stormwater management as a part of the smart city and digital twin concepts to build climate‐resilient infrastructures and services. Therefore, smart management of CSS is now both technically and economically feasible to tackle the challenges ahead. This review article explores CSO characteristics and associated impact on receiving waterbodies, evaluates suitable models for CSO management, and presents studies including above‐mentioned technologies in the context of smart CSO and stormwater management. Although integration of all these technologies has a big potential, further research is required to achieve AI‐controlled CSS for robust and agile CSO mitigation. This article is categorized under:Engineering Water > Sustainable Engineering of WaterScience of Water > Water and Environmental Change [ABSTRACT FROM AUTHOR]

In sewer pipes, haze caused by the humid environment seriously impairs the quality of closed‐circuit television (CCTV) images, which leads to poor performance of subsequent pipe defects detection. Meanwhile, the complexity of sewer images, such as steep depth change and extensive textureless regions, brings great challenges to the performance or application of general dehazing algorithms. Therefore, this study estimates sewer depth maps first with the help of the water–pipewall borderlines to produce the paired dehazing dataset. Then a structure‐aware nonlocal network (SANL‐Net) is proposed with the detected borderlines and the dehazing result as two supervisory signals. SANL‐Net shows its superiority over other state‐of‐the‐art approaches with 147 in mean square error (MSE), 27.28 in peak signal to noise ratio (PSNR), 0.8963 in structural similarity index measure (SSIM), and 15.47M in parameters. Also, the outstanding performance in real image dehazing implies the accuracy of depth estimation. Experimental results indicate that SANL‐Net significantly improves the performance of defects detection tasks, such as an increase of 23.16% in mean intersection over union (mIoU) for semantic segmentation. [ABSTRACT FROM AUTHOR]

This article aims to present structural and geotechnical design challenges of the flood relief project "Segundo Emisario del Arroyo Vega", part of Buenos Aires city hydraulic master plan. Works comprised the execution of an 8.4 km‐long tunnel for relief of the existing sewer network. Tunnel alignment develops in a highly populated area, with important interferences such as two metro lines, three railway lines and a main potable water tunnel. All tunnel sections extend mostly within firm, silty soils. Overburden varies between 15 and 25 m. The downstream section was executed with a 6.1 m‐diameter Earth pressure Balance Tunnel Boring Machine (EPB TBM) launched from a 35 m‐diameter shaft with water table pressures up to 200 kPa. Break‐in was performed across a watertight, plastic diaphragm wall cell, which allowed safe shaft wall manual demolition, resulting in a very safe TBM launch. The tunnel upstream section, 2.85 m in diameter, was executed using pipe jacking technology, with the peculiarity of using bidirectional launch shafts along its alignment. To allow water entrance from existing system – through flow diversion chambers – into the new relief tunnel, openings were made in the TBM tunnel, with connection areas of 4 to 7 m2. Its design was particularly challenging, given that unbolted segmental lining was used. [ABSTRACT FROM AUTHOR]

Digital construction on building sites – application settings and improvement potential Digital construction, also known as Building Information Modeling (BIM), has the potential to revolutionize the way we plan, construct, and operate buildings and infrastructure. By using digital methods and tools, we can optimize processes and work more efficiently and cost‐effectively. This is not just limited to the planning and approval stages but can also be applied during the construction phase. At STRABAG, they have already begun to implement these techniques on their construction sites, resulting in improved processes and higher‐quality structures. In this article, the author will explore the practical applications of digital tools and methods in infrastructure construction. She will discuss the impact it has on the construction process and the preconditions needed for its successful implementation. One specific area to be delve into is the use of digital component tracking in sewer construction. The process of ordering, producing, delivering, and installing pipes and manholes is time‐consuming and requires a great deal of logistical planning. Digital component tracking simplifies these steps, making sewer construction more efficient and cost‐effective. [ABSTRACT FROM AUTHOR]

Basement backups and sewer overflows from rainfall‐derived inflow and infiltration (RDII) are a significant threat to human and environmental health; however, reducing inflow and infiltration is a challenge for municipalities due to the difficulty and resources required to accurately identify source areas. This case study seeks to address this challenge by evaluating the influence that sewershed characteristics have on inflow and infiltration into sanitary sewer systems. To do so, we used 4.5 years of monitoring data from 19 sanitary sewer locations in Milwaukee, Wisconsin to explore the relationships between RDII defined using the RTK unit hydrograph method and sewershed physical, land cover, and pipe characteristics. Results demonstrate that inflow, or fast direct flows into the system, is positively correlated to pipe length per acre, number of parcels, and medium intensity land use. Infiltration, or slow inputs from groundwater sources, is negatively correlated with imperviousness, pipe length per acre, low intensity, and medium intensity land use. Multivariable linear regression using these parameters explained between 55% and 72% of the variance in normalized inflow and infiltration. These findings demonstrate a way in which collection system managers may be able to narrow the search areas for RDII sources within their sanitary sewer systems by evaluating sewershed characteristics. [ABSTRACT FROM AUTHOR]

Modelling urban inundation and its associated health implications is numerous in its many applications. Flood modelling research contains a broad wealth of material, and microbial risk assessment has gained more popularity over the last decade. However, there is still a relative lack of understanding of how the microbial risk can be quantified from urban sewer flooding. This article intends to review the literature encompassing contemporary urban flood modelling approaches. Hydrodynamic and microbial models that can be applied for quantitative microbial risk assessment will be discussed. Consequently, urban sewer flooding will be the focus. This review found that the literature contains a variety of different hazards posed by urban flooding. Yet, far fewer examples encompass microbial risk from sewer system exceedance. To date, there is no evidence of a perfect model or technique, to carry out a quantitative microbial risk assessment from hydrodynamic simulations. The literature details many different methods. We intend to detail the advantages and limitations of each method. Along similar lines, hydraulic data constitutes a large part of the uncertainty which is inherent to this research field. Many studies in the literature detail data paucity and uncertainty in input data. As such, any advancement in this discipline will very likely aid future research. [ABSTRACT FROM AUTHOR]

When the manufacturers produce capacitor voltage transformers (CVT), the function of harmonic measurement is not considered. Therefore, this paper explores methods to solve the problems of harmonic measurement from the perspective of manufacturers. Using the amplitude‐frequency characteristic curve of CVT under no‐load condition and standard environment as the benchmark, the estimation method of stray capacitance parameters in CVT based on CSO algorithm is proposed. Besides, in order to improve the accuracy of harmonic correction of CVT in different operating environments, this paper deeply studies the influence of oil temperature and industrial frequency on internal parameters and harmonic transfer characteristics of CVT. On this basis, this paper proposes a correction method of CVT harmonic transfer characteristic curves under different operating environments based on BP neural network algorithm. Finally, under the actual operating environment, calculating the amplitude‐frequency characteristic curve of CVT by utilizing the actual harmonic voltages at the secondary side of the TYP3‐0.02HF CVT and RCVT, and comparing it with the amplitude‐frequency characteristic curve of CVT predicted by the BP neural network. The results show that the proposed methods are effective and feasible. [ABSTRACT FROM AUTHOR]

Nowadays, sensitive harmonic loads (SHLs) are being increasingly used in the industrial sector. SHLs generate harmonics and may become disconnected from the network when voltage sags occur at the point of common coupling (PCC). Here, a new approach is proposed to reduce harmonics distortion and establish a more reliable annual operation of SHLs by reducing the area of pollution (AOP) with harmonic and the area of vulnerability (AOV) to voltage sag, respectively. The proposed approach includes an innovative optimization problem for planning passive harmonic filters which is solved by the Non‐dominant Sorting Genetic Algorithm (NSGA‐II) on the basis of historical data of the industrial power grid. By doing so, a solution is obtained in which the costs of passive harmonic filters and financial costs due to grid losses and voltage sags are minimized. In order to assess the new proposed approach, an Iranian large copper mine electrical network equipped with SHLs is used. Results of using the new approach show that total harmonic distortion and grid losses decrease by nearly 80% and 15%, respectively and also, the voltage value at the PCC is improved which can assure the secure operation of SHLs. Moreover, decreased financial losses is obtained since voltage sags are reduced by 65%. [ABSTRACT FROM AUTHOR]

COVID‐19 wastewater‐based epidemiology has been performed in catchments of various sizes and sewer types with many short‐term studies available and multi‐seasonal studies emerging. The objective of this study was to compare weekly observations of SARS‐CoV‐2 genes in municipal wastewater across multiple seasons for different systems as a factor of sewer type (combined, separate sanitary) and system size. Sampling occurred following the first wave of SARS‐CoV‐2 cases in the study region (June 2020) and continued through the third wave (May 2021), the period during which clinical testing was widely available and different variants dominated clinical cases. The strongest correlations were observed between wastewater N1 concentrations and the cumulative clinical cases reported in the 2 weeks prior to wastewater sampling, followed by the week prior, new cases, and the week after wastewater sampling. Sewer type and size did not necessarily explain the strength of the correlations, indicating that other non‐sewer factors may be impacting the observations. In‐system sampling results for the largest system sampled are presented for 1 month. Removing wet weather days from the data sets improved even the flow‐normalized correlations for the systems, potentially indicating that interpreting results during wet weather events may be more complicated than simply accounting for dilution. Practitioner Points: SARS‐CoV‐2 in wastewater correlated best with total clinical cases reported in 2 weeks before wastewater sampling at the utility level.Study performed when clinical testing was widespread during the year after the first COVID‐19 wave in the region.Sewer type and size did not necessarily explain correlation strength between clinical cases and wastewater‐based epidemiology results.Removing wet weather days improved correlations for 3/4 utilities studied, including both separate sanitary and combined sewers. [ABSTRACT FROM AUTHOR]

Real‐time control (RTC) of urban drainage systems (UDS) has been proved an efficient tool in combined sewer overflow (CSO) and flooding mitigation. Recently, new RTC approaches based on reinforcement learning (RL) were developed for flooding mitigation in stormwater systems. While these studies have made contributions to enable an improved urban water management, they are insufficient to allow for deeply understanding of the effectiveness of different RLs in UDS. Meanwhile, the risk of handing over the control process to a RL agent is still unavoidable because of the fluctuations of RLs' output and the unknown consequences of implementing RLs control strategy. This study conducted four tasks to address these problems. First, five RTC systems based on five individual RLs were designed to distinguish different RLs' performance in the context of UDS. Then, an independent security system based on SWMM was provided to forecast and evaluate the consequence of RL control strategy. After that, an innovative hybrid RTC system, called Voting, was developed by coupling multiple RLs and the independent security system through a model predictive control framework to avoid the fluctuations of RLs' output. Finally, the robustness of the RL agents was validated using uncertainty analysis. All the RLs were evaluated through simulation based on a Storm Water Management Model of a UDS located in Eastern China. According to the results, (a) different RLs show promise in CSO and flooding mitigation; (b) Voting selects a relatively reliable and optimal control trajectory compared with any single RL agents; (c) the performances of RL agents have certain robustness when facing different rainfall events and imperfect input. Key Points: Different reinforcement learnings (RLs) show promise in CSO and flooding mitigationVoting selects a relatively more reliable and more optimal control trajectory compared with any single RL agentsRLs' performance is influenced by rainfall events and imperfect input, but they still have certain robustness [ABSTRACT FROM AUTHOR]

Storm sewerages are crucial infrastructures in water management. In this paper, a system was developed to detect the blockage of the sewerage and the presence of illegal spills in Storm sewerages. Different nodes with sensors measuring the water level, turbidity, conductivity, and oil presence are scattered in the sewerage. These nodes are connected to a master node for processing the information with a rain sensor. The rain and water level sensors are used to determine one of the four possibilities regarding the presence of water in the sewerage and whether it is raining. According to the combinations, it can be determined whether it is a normal situation or there are spills or blockages. It is shown that there are differences between sewerage with and without blockage via the water level. This can be used to determine the presence of a blockage. The identification of an illegal spill is performed with the use of conductivity, turbidity, and oil sensors. The authors determined that yellow and infrared light can determine the oil concentration in the oil sensor in a range of 0–2.2 mL oil/L water with yellow light and 0.4–20 mL oil/L water with infrared light. Finally, the conductivity sensor can determine water conductivity from 0.526 to 58.4 mS/cm. [ABSTRACT FROM AUTHOR]

Many urban flood models employ coarse grids to reduce the computational cost of real‐time forecasting. Such a coarse grid, however, may result in poor predictions of the discharge rate of surface water because of difficulties in representing the detailed features of drainage facilities. In the present study, an urban flood model that consists of a one‐dimensional (1D) river flow model, a two‐dimensional (2D) ground surface flow model, and a 1D sewer network model was developed. A coarse grid is used for the 2D ground surface flow model, and the tail networks of the sewer systems are neglected to reduce computational cost. A novel approach is proposed for determining the integrated water discharge from the ground surface to the trunk sewer network to retain the accuracy of a simplified coarse‐grid system. Numerical experiments were performed to evaluate the performance of the proposed method. Measured water levels at manholes were employed to examine the accuracy of the model. The results show that this approach significantly improves the accuracy of the simulated water level in a sewer network with enhanced computational efficiency. [ABSTRACT FROM AUTHOR]

Human norovirus (NoV) is the leading cause of foodborne illness in the United States and Canada. Bivalve molluscan shellfish is one commodity commonly identified as being a vector of NoV. Bivalve molluscan shellfish are grown in waters that may be affected by contamination events, tend to bioaccumulate viruses, and are frequently eaten raw. In an effort to better assess the elements that contribute to potential risk of NoV infection and illness from consumption of bivalve molluscan shellfish, the U.S. Department of Health and Human Services/Food and Drug Administration (FDA), Health Canada (HC), the Canadian Food Inspection Agency (CFIA), and Environment and Climate Change Canada (ECCC) collaborated to conduct a quantitative risk assessment for NoV in bivalve molluscan shellfish, notably oysters. This study describes the model and scenarios developed and results obtained to assess the risk of NoV infection and illness from consumption of raw oysters harvested from a quasi‐steady‐state situation. Among the many factors that influence the risk of NoV illness for raw oyster consumers, the concentrations of NoV in the influent (raw, untreated) and effluent (treated) of wastewater treatment plants (WWTP) were identified to be the most important. Thus, mitigation and control strategies that limit the influence from human waste (WWTP outfalls) in oyster growing areas have a major influence on the risk of illness from consumption of those oysters. [ABSTRACT FROM AUTHOR]

Existing, high‐fidelity models for sewer network modeling are accurate but too slow and inflexible for modern applications such as optimization or scenario analysis. Reduced complexity surrogate modeling has been applied in response to this, however, current approaches are expensive to set up and still require high‐fidelity simulations to derive parameters. In this study, we compare and develop graph partitioning algorithms to automatically group sections of sewer networks into semi‐distributed compartments. These compartments can then be simulated using sewer network information only in the integrated modeling framework, CityWat‐SemiDistributed (CWSD), which has been developed for application to sewer network modeling in this study. We find that combining graph partitioning with CWSD can produce accurate simulations 100–1,000× faster than existing high‐fidelity modeling. Because we anticipate that many CWSD users will not have high‐fidelity models available, we demonstrate that the approach provides reasonable simulations even under significant parametric uncertainty through a sensitivity analysis. We compare multiple graph partitioning techniques enabling users to specify the spatial aggregation of the partitioned network, also enabling them to preserve key locations for simulation. We test the impact of temporal resolution, finding that accurate simulations can be produced with timesteps up to one hour. Our experiments show a log‐log relationship between temporal/spatial resolution and simulation time, enabling users to pre‐specify the efficiency and accuracy needed for their applications. We expect that the efficiency and flexibility of our approach may facilitate novel applications of sewer network models ranging from continuous simulations for long‐term planning to spatially optimizing the placement of network sensors. Plain Language Summary: Existing sewer models are too slow and inflexible to be applied to a range of modern demands that are placed on sewer modeling. For example, climate analyses require simulations of long and continuous timeseries spanning decades over a range of potential futures. The solution to this is to reduce the complexity of sewer models, aiming to provide good enough simulations that are computationally fast and flexible to adapt to the variety of planning situations faced by modern sewer model users. Existing approaches to reduced complexity sewer modeling require time consuming activities such as calibrating to detailed simulations (which are often not available) and inflexible methods to reduce complexity (typically aggregating the network spatially). In this paper, we provide a physically based reduced complexity model that can be applied without calibration. We combine it with graph partitioning, which is a flexible and automated way to reduce a sewer network's complexity in space. Our simulation experiments find the proposed approach to be successful in producing accurate simulations and highlight the utility of reduced complexity modeling by investigating how spatial and temporal resolution interact and impact the accuracy of simulation results. Key Points: Automatic graph partitioning can flexibly reduce the complexity of sewer networks to enable surrogate modelingCityWat‐SemiDistributed can model these reduced networks without needing parameter derivation from high‐fidelity simulationsThe combined approach provides computationally cheap simulations and performs accurately even when no high‐fidelity model is available [ABSTRACT FROM AUTHOR]

In this work, a revised formulation of chance‐constrained (CC) model predictive control (MPC) is presented. The focus of this work is on the mathematical formulation of the revised CC‐MPC, and the reason behind the need for its revision. The revised formulation is given in the context of sewer systems, and their weir overflow structures. A linear sewer model of the Astlingen benchmark sewer model is utilized to illustrate the application of the formulation, both mathematically and performance‐wise through simulations. Based on the simulations, a comparison of performance is done between the revised CC‐MPC and a comparable deterministic MPC, with a focus on overflow avoidance, computation time, and operational behavior. The simulations show similar performance for overflow avoidance for both types of MPC, while the computation time increases slightly for the CC‐MPC, together with operational behaviors getting limited. [ABSTRACT FROM AUTHOR]

In this work, we present a framework for ensemble‐based (E) chance‐constrained (CC) model predictive control (MPC) in sewer systems. The framework considers the availability of ensemble forecasts and the difficulties with propagation of distributions; through distribution estimation. Utilizing a case study of the sewer network of the city of Aarhus in Denmark, the performance of the ECC‐MPC framework is evaluated through simulations. The evaluations were based on linear models of the case study and compare the ECC‐MPC performance with the performance of CC‐MPC. Based on the simulations, it was found that the ECC‐MPC performed comparable to the performance of the CC‐MPC, not only in the context of overflow and outflow but also with respect to behavior in response to changes in different aspects of forecast uncertainties. Regarding the aspects, it was found that expectation offset biases in the forecast were affecting the performance of the CC‐ and ECC‐MPC the most. While other aspects only had a reduced effect on the performances, within the ranges tested. With the comparable performances, it was found that ECC‐MPC would work as an alternative approach to CC‐MPC. [ABSTRACT FROM AUTHOR]

The design of wastewater system pipe size is traditionally based on the maximum wastewater flow that is a function of multiple factors. Understanding the appropriate peaking factors (PF) by using daily flow variations through wastewater collection systems (WWCS) is essential for cost‐effective design. This paper describes the maximum and minimum PFs by using wastewater flow data of four separate residential areas such as Lara, Belek‐1, Kemer, and Hurma in Antalya, which is the tourism capital of Turkey. The study involves the analysis of wastewater data recorded at daily interval for two different time periods (2006–2009 and 2016–2019) in Antalya. There is a comprehensive investigation regarding PFs that involves sustained peaking flow and percentiles. Therefore, a new empirical equation was proposed by using wastewater flowrate for the estimation of the maximum daily peaking factor. When the daily PFs are determined in the range of 1.31–1.52, 1.60–2.58, 2.26–3.29, and 1.93–2.29 for Lara, Belek‐1, Kemer, and Hurma wastewater treatment plants (WWTPs) for 2016–2019 time period, they are in the range of 2.19–2.93 and 1.95–3.31 for Lara and Hurma WWTPs for the time period of 2006–2009, respectively. In brief, this study presents a comprehensive calculation of PFs with a determination of their sustained flow analysis with different durations and percentiles. Practitioner Points: This study presents the findings regarding peaking factors and its statistical analysis for different time periods.Statistical analysis included sustained flow, and the percentile of peaking factors was applied to waste water flow data for touristic city of Antalya.The new formula of PFmax,dry=39.18⋅(Qav,d)−0.32 was determined by using more touristic areas of Antalya within the scope of estimation of the daily peaking factor for dry weather flow by using average daily wastewater flowrate data with the determination coefficient of 0.95. [ABSTRACT FROM AUTHOR]

Technical alternatives offering high water efficiency are being developed to complement existing centralized water and wastewater conveyance and treatment systems. Understanding of the negative effects wide‐spread implementation of such alternative systems may have on existing systems is still limited, despite the importance of this inevitable transition. In this study, we present a novel approach to systematically identify these negative impacts. A comprehensive model integrating transport and transformation processes in sewer pipes was set up and simulated for various transition scenarios. A significant finding of this research is that reduced flows and increased chemical oxygen demand (COD) concentrations result in the accumulation of sediments and sulphides in sewer pipes. For the examined sewer system, when reducing the total daily flow by 50%, 30% of the pipes were found to accumulate sediments, and 30% of the pipes experienced effects due to the presence of sulphides in different states depending on the wastewater temperature. It was found that an optimal spatial distribution of these water‐efficient solutions will most likely require compromises between sediment and sulphide accumulation. The product of two design parameters, diameter and bed slope, was found to be a suitable predictor of the potential of a pipe to accumulate sediments. This research provides novel approaches to assessing the feasibility of transition to solutions offering higher water efficiency. The results indicate where the most affected points in the systems are expected to occur and might help in preparing an experimental approach to assess such negative effects, increasing urban water management efficiency. Key Points: A systematic approach for evaluating effects of transition to water‐efficient solutions on sewers is presentedTransition to water‐efficient solutions affects sulphide and sediment accumulation in pipesReduced flows and increased chemical oxygen demand and temperatures affect these accumulations [ABSTRACT FROM AUTHOR]

The study of the effects of mixing potable water with wastewater is a complex and difficult research area. This difficulty is because water and sewage networks are subject to various physical, environmental, and operational factors. The main objective of the study was to propose a new comprehensive framework for analyzing and assessing water quality based on Bayesian networks. An intervention plan was proposed to reduce the consequences of water quality and networks failure. The proposed framework was applied to water distribution network of Mdaourouch city (Souk Ahras, Algeria) to demonstrate its effectiveness. The results indicated that the water contamination rate has reached 33.9 %, which caused severe consequences. The effectiveness of the proposed plan has been verified theoretically using simulations, and the results have proven to be very satisfactory. The proposed model is a decision support tool, which is expected to assist decision‐makers and engineers in reviewing their plans and making the right decision. Practitioner Points: This paper proposes a novel comprehensive framework for analyzing and assessing water quality and failure consequences based on Bayesian networks.This paper revisits the failure consequences.An intervention plan is proposed to reduce failure consequences.Results demonstrate that the proposed plan leads to fewer consequences probabilities.The proposed method can give the probability of failure of water and sewer network. [ABSTRACT FROM AUTHOR]

Wastewater treatment is one of the most effective solutions to manage the problem of water scarcity. Falling film evaporators are excellent technology in wastewater treatment plants. These wastewater evaporators provide high heat transfer, short residence time in the heating zone, and high‐purity distilled water. In the present study, the mechanism of turbulent falling film evaporation in a vertical tube has been investigated. A model has been developed for symmetrical two‐dimensional pure and saline water flow in a vertical tube under constant wall heat flux. The numerical simulation has been carried out by a commercial computational fluid dynamics code. The evaporation of saturated liquid film is simulated utilizing a two‐phase volume of fluid method and Tanasawa phase‐change model. The main objective of this study is to evaluate the effects of water salinity, liquid Reynolds number, wall heat flux, and liquid film thickness on the two‐ phase heat transfer coefficient and vapor volume fraction. The numerical heat transfer coefficients are compared with the obtained results by Chen's empirical correlation. With a MAPE ≤ 11%, this study proves that the numerical method is highly effective at predicting the heat transfer coefficient. Moreover, the empirical coefficient of the Tanasawa model and the minimum thickness of the falling film are determined. [ABSTRACT FROM AUTHOR]

Hazardous waste site investigations have shown that volatile organic compounds (VOCs) can be transported via sewer pipes and migrate into indoor spaces. Despite field data confirming the presence of this exposure pathway, there is lack of context‐based numerical models that provide guidance to characterize and predict VOCs concentration in sewer gas at vapor intrusion sites. Particularly, this poses a challenge when assessing and mitigating risks associated with these exposure pathways. Therefore, a numerical model has been developed to simulate the concentration of VOCs in sewer gas in different stages throughout the sewer lines. The developed model considers various input parameters, including temperature, sewer liquid depth, groundwater depth, and sewer construction characteristics to incorporate local and operational conditions. The model's output is verified using field data from a sewer system constructed near a Superfund site. Moreover, a sensitivity analysis was conducted to evaluate the model's response to variation of the external input parameters. To the best of our knowledge, this study is the first attempt to model VOCs concentration in sewer gas, particularly to address vapor intrusion. The developed model can be used as a numerical tool to support the development of sewer assessment guidelines, risk assessment studies, and mitigation strategies. [ABSTRACT FROM AUTHOR]

Persistent dry and wet spells can arise from stationary weather situations or recurrent flow patterns and result in significant socio‐economic impacts. Here, we study the effects of recurrent synoptic‐scale transient Rossby wave packets (RRWPs) on the persistence of dry and wet spells using the ERA‐Interim reanalysis data. RRWPs significantly alter (decrease and increase) dry and wet spell persistence across the globe. Spatial patterns of statistically significant links between RRWPs and spell durations arise from the superposition of a zonally symmetric component and a wave‐like component that is modulated by local factors such as orography and the position relative to major moisture sources. The zonally symmetric component is apparent during the Northern Hemisphere winter and dominates the Southern Hemisphere signal in winter and summer. The wave‐like component appears primarily in the Northern Hemisphere, changes its wavenumber with the season and is thus, conceivably related to stationary wave dynamics. Plain Language Summary: Unchanged weather conditions over a prolonged period (persistent weather) can lead to adverse conditions for example, in agriculture. Traditionally, such weather conditions are understood to arise from slow‐moving (i.e., "stationary") weather systems. In this study, we illustrate an alternative, "non‐stationary" atmospheric flow configuration, which can cause such persistent weather by the repeated formation (recurrence) of troughs and ridges in the same areas. The upper‐level atmospheric waves, which influence our daily weather, govern this process. We show two example cases, where recurrence leads to persistent dry or wet conditions. By analyzing over 35 years of data, we find such wave recurrence to be statistically relevant for persistent dry and wet conditions. For many land areas of both the Northern and the Southern Hemisphere, increased or reduced persistence of dry and wet conditions are related to the recurrent upper‐level waves. Key Points: Recurrent Rossby wave packets significantly alter (lengthen or shorten) the persistence of both wet and dry spells in the extratropicsThey lengthen or shorten dry (wet) spells through the recurrent formation of ridges (troughs) in the same areaRecurrence of transient Rossby waves should be considered as a key dynamical mechanism for fostering persistent surface weather [ABSTRACT FROM AUTHOR]

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This paper presents an unprecedented set of data in a challenging underground environment: the visitable sewers of Barcelona. To the best of our knowledge, this is the first data set involving ground and aerial robots in such scenario: the sewer inspection autonomous robot (SIAR) ground robot and the autonomous robot for sewer inspection aerial platform. These platforms captured data from a great variety of sensors, including sequences of red green blue‐depth (RGB‐D) images with their onboard cameras. The set consists of 14 logs of experiments that were obtained in more than 10 different days and in four different locations. The complete length of the experiments in the data set exceeds 5 km. In addition, we provide the users with a partial ground‐truth and baselines of the localization of the platforms, which can be used for testing their localization and simultaneous localization and mapping (SLAM) algorithms. We also provide details on the setup and execution of each mission and a partial labeling of the elements found in the sewers. All the data were recorded by using the rosbag tool from robot operating system framework. Our goal is to make the data available to the scientific community as a benchmark to test localization, SLAM and classification algorithms in underground environments. The data set are available at https://robotics.upo.es/datasets/echord. [ABSTRACT FROM AUTHOR]

The regular inspection of sewer systems is essential to assess the level of degradation and to plan maintenance work. Currently, human inspectors must walk through sewers and use their sense of touch to inspect the roughness of the floor and check for cracks. The sense of touch is used since the floor is often covered by (waste) water and biofilm, which renders visual inspection very challenging. In this paper, we demonstrate a robotic inspection system which evaluates concrete deterioration using tactile interaction. We deployed the quadruped robot ANYmal in the sewers of Zurich and commanded it using shared autonomy for several such missions. The inspection itself is realized via a well‐defined scratching motion using one of the limbs on the sewer floor. Inertial and force/torque sensors embedded within specially designed feet captured the resulting vibrations. A pretrained support vector machine (SVM) is evaluated to assess the state of the concrete. The results of the classification are then displayed in a three‐dimensional map recorded by the robot for easy visualization and assessment. To train the SVM we recorded 625 samples with ground truth labels provided by professional sewer inspectors. We make this data set publicly available. We achieved deterioration level estimates within three classes of more than 92% accuracy. During the four deployment missions, we covered a total distance of 300 m and acquired 130 inspection samples. [ABSTRACT FROM AUTHOR]

Stable isotope analysis of preserved natural‐history specimens from long‐term storage can provide useful data about energy flow and trophic structure in ecosystems of the past. Nitrogen isotope values from primary producers are used as critical food web baselines, while both nitrogen and carbon isotopes expose the presence of sewage contamination and nutrient runoff. Seaweed specimens being prepared for long‐term storage are often fixed in formalin prior to being dried or transferred into a storage liquid, but the effects of this fixative on nitrogen and carbon stable isotope values of marine primary producers have not been investigated. We evaluated the effects of formalin on macroalgal and cyanobacterial stable isotope values. For this purpose, we analyzed δ15N and δ13C values of 41 pairs of formalin‐preserved vs. dried seaweed specimens stored for up to 5 yr. While neither isotope was consistently altered by formalin when all seaweeds were pooled, δ15N values were overall less variable than δ13C values. However, formalin preservation lowered δ13C values in Ochrophyta by 0.2% on average. Neither isotope was affected by duration of formalin preservation. Because formalin‐exposed samples show similar δ15N and δ13C values to dried samples, formalin‐exposed specimens can be used to accurately assess nutrient dynamics and food webs of historic marine ecosystems provided that one has sufficient sample sizes of seaweeds. [ABSTRACT FROM AUTHOR]

The deterioration and cost‐effective maintenance of infrastructure has for many years been an area of social and financial importance. The deterioration of the wastewater infrastructure is particularly important because of its key role in the maintenance of public health for urban conglomerations. This paper describes two case studies that are taken from an ongoing study of the sewerage network in the Municipality of Rennes, France. Both studies concern spun concrete pipes laid approximately 55 years ago. The first case is that of a sewer in good order because of its location within the network and its design. The second case describes a sewer that has been oversized and the conditions within the reach of the sewer have led to sulphide attack. It is concluded that two important considerations that must be taken into account is the design detailing and appropriate selection of materials. [ABSTRACT FROM AUTHOR]

Urbanisation and climate change worsen the ever‐increasing gap between demand and the supply of water. Closing the gap between water demand and supply remains a global challenge that influences the growing uptake of water‐saving schemes (WSSs) to reduce the threat to water security. This study proposes a method for simultaneous design of sanitary sewers (SSs) and the selection of WSSs. An integrated design approach (or problem) that matches SSs with WSSs was formulated and solved as a multi‐objective optimisation problem. The two objectives considered are: (1) minimisation of the total cost and (2) maximisation of the cost benefits of interventions. The main constraints considered include the sanitary sewer technical and hydraulic performances. The problem was solved using the well‐known NSGA2 optimisation technique. The proposed method was demonstrated using a subsystem of the Tsholofelo Extension sanitary sewer in Gaborone. The results obtained from the integrated approach suggest that WSSs influence designs of the sanitary sewer (SS) and the other way round. [ABSTRACT FROM AUTHOR]

Key Takeaways: In 2019, US utilities on average charged the equivalent of 10.1 hours' labor at minimum wage for basic monthly water and sewer service for a four‐person household. Basic water and sewer service cost an average of 12.4% of disposable income for a four‐person household at the 20th percentile income. US water and sewer service on average became less affordable over the past two years, varying by region and utility ownership, driven by increasing water and nonwater prices. [ABSTRACT FROM AUTHOR]

The aim of this study is to evaluate the use of Spirogyra sp. green algae for wastewater treatment process in sewer. The effects of light and carbon sources were investigated on growth of the algae Spirogyra sp, removal of nitrate, nitrite, phosphate, chemical oxygen demand (COD) and pH changes. Samples 1 & 4 were grown in autotroph form, while samples 2 & 5 and 3 & 6 were grown in media containing 100 and 200 mg/L of glucose, respectively. Samples 1 up to 3 were grown in cycling light but samples 4 up to 6 were grown in continuous light. Results indicated that algal growth, levels of nitrites and pH and removal of nitrate and phosphate were increased in continuous illumination and carbon sources availability (100 and 200 mg/L of glucose). It can be recommended to apply Spirogyra sp. for wastewater treatment process in sewer collection system. [ABSTRACT FROM AUTHOR]

The characterization of sludge settling is important in determining the operating performance of the secondary clarifier and also evaluating the purification efficiency of wastewater treatment plants. Many models have been proposed to explain the activities of settling velocity and illustrating the relationship between settleability characteristics. The aim of this research was to present a model for the settling velocity as a function of the stirred specific volume index at 3.5 g/L (SSVI3.5), based on the Vesilind function, the solids flux theory, and the experimental data. Using this model gives an important performance improvement after calibration of the different settleability parameters. Practitioner points: Batch settling tests are some of the most interesting source of information to determine the sedimentation velocities and their characteristics.The modeling as an optimum operation of wastewater treatment plants is widely used for design, optimization, and management of installations.The characterization of sludge settling is important in determining the operating performance of the secondary clarifier.The characterization of sludge settling is necessary to evaluate the purification efficiency of wastewater treatment plants. [ABSTRACT FROM AUTHOR]

The disposal of unflushable products via the toilet is an enduring problem and increasing contributor to environmental and infrastructural challenges such as fatbergs, water quality and plastic pollution. Rising scientific and public interest in "throw‐away" cultures, and renewed government pressure for water and sewerage companies to act as custodians of water resources, raises questions about how and why impactful disposal practices occur and what might be done to change them. To date there has been little systematic research on unflushable products, and little is known about the routines and practices through which unflushable products find their way into wastewater systems. This paper reviews social science research including historical, sociological, and anthropological studies of cleanliness and hygiene, as well as sociotechnical approaches to the study of household practices and infrastructures to understand the challenges of unflushables. Based on this research, the paper offers a new conceptualization of the unflushables challenge. We argue that unflushables are a distributed problem, one that is not the direct consequence of either individual behavior, product design or infrastructural decline, but the outcome of myriad social, cultural and material developments in society. These include diversity in "flushing" cultures, gendered expectations in cleanliness practices; the evolution of conventions around cleanliness and hygiene; infrastructural imaginaries and expectations; and political dimensions of infrastructural development and maintenance. We demonstrate how social science research is essential in defining a new global research agenda on unflushables that further aids the design of new intervention and policy pathways. This article is categorized under:Engineering Water > Sustainable Engineering of WaterScience of Water > Water Quality [ABSTRACT FROM AUTHOR]

Secondary settling tanks (SSTs) are a crucial process that determines the performance of the activated sludge process. However, their performance is often far from satisfactory. In the last 30 years, computational fluid dynamics (CFD) has become a robust and cost‐efficient tool for designing new SSTs, modifying the geometries of existing SSTs and improved control techniques in wastewater treatment plants. The first part of this review paper discusses the different approaches to model the motion of particles in SSTs. The applications of different multiphase approaches and the widely applied single‐phase approach in different SST studies are reviewed. The second part reviews current CFD research and engineering practice, focusing on the formation and the effect of density currents, effects of different design variables, parameter uncertainties in modeling structures, and atmospheric conditions. Finally, challenges and future improvements of sub‐models (sludge settling, rheology, turbulence, and flocculation) in the SST model framework are identified. Practitioner points: The first journal review for the CFD applications in SSTs over the last decade.The controversy over the relationship between SOR and SST performance can be largely explained by the prediction of the CFD model.Density decoupling in the turbulence model is possible for well‐baffled SSTs.The relative importance of three modeling parameters is summarized.Recommendations for future data collection are provided. [ABSTRACT FROM AUTHOR]

Mixing efficiency is an important turbulent flow property in fluid dynamics, whose variability potentially affects the large‐scale ocean circulation. However, there are several confusing definitions. Here we compare and contrast patch‐wise versus bulk estimates of mixing efficiency in the abyss by revisiting data from previous extensive field surveys in the Brazil Basin. Observed patch‐wise efficiency is highly variable over a wide range of turbulence intensity. Bulk efficiency is dominated by rare extreme turbulence events. In the case where enhanced near‐bottom turbulence is thought to be driven by breaking of small‐scale internal tides, the estimated bulk efficiency is 20%, close to the conventional value of 17%. On the other hand, where enhanced near‐bottom turbulence appears to be convectively driven by hydraulic overflows, bulk efficiency is suggested to be as large as 45%, which has implications for a further significant role of overflow mixing on deep‐water mass transformation. Plain Language Summary: Ocean turbulence can vertically mix the stratified water column to raise the background gravitational potential energy, maintaining the ocean stratification. "Mixing efficiency" is a parameter representing the fraction of the available turbulent mechanical energy that is irreversibly converted to the background gravitational potential energy during a mixing event. Efficiency has traditionally been treated as a global constant of 17%, but there is growing evidence for its highly variable nature during individual turbulence events. It remains unknown how variable bulk mixing efficiency is (defined as the average over multiple turbulence events, including rare extreme cases). Here we show that bulk efficiency can be significantly different from the corresponding space‐time average of local‐instantaneous patch‐wise efficiency estimates at deep depths with weak stratification. This warns against the application of variable mixing efficiency revealed in individual turbulence events to large‐ocean circulation models. The use of the conventional efficiency in such models is supported in a tidal mixing hotspot over rough bathymetry. On the other hand, significantly higher mixing efficiency, up to 45%, is suggested in a localized mixing hotspot over a fracture zone sill, implying a more significant role of overflow mixing on deep‐water mass transformation than previously thought. Key Points: Bulk efficiency, which is dominated by rare extreme turbulence events, differs from the corresponding average of patch‐wise efficiencyThe widely used efficiency of 17% is supported over a rough bottom where breaking of small‐scale internal tides causes enhanced turbulenceEstimated efficiency is as large as 45% over a sill where enhanced turbulence is thought to be convectively driven by hydraulic overflows [ABSTRACT FROM AUTHOR]

Concrete repair of the Starzenbach duct in Feldafingen with carbon concrete Repairing concrete structures with carbon reinforced textile concrete under wet conditions or even underwater is not yet taken in to account according to the German abZ. Nonetheless, it can be assumed that there is a high potential for application in outdoor areas /facilities like channels or sewers which are fully exposed to weathering or even partially flooded with water. Recent research already shows that there are possibilities of applying textile reinforced carbon concrete under such conditions, which finally led to the entitled pilot project that has already successfully been completed. This project was a highly damaged duct liable to collapse in the centre of Feldafingen. The repair must be performed as quickly as possible while traffic and thus access to the adjacent properties must be granted. To meet these requirements, it was necessary to combine the standardised shotcrete method with still developing carbon concrete technology and perform extensive underwater tests prior to the project itself. It was possible to restore the duct with an additional layer of only 70 mm thickness. Furthermore, the flow speed of the water was improved by the seamless and smooth surface of the carbon concrete. [ABSTRACT FROM AUTHOR]

This study uses contemporary metrics and data from an original, representative sample of water and sewer utilities in the United States to calculate the affordability of basic single-family residential water and sewer services for lowincome households in 2019. Results show that affordability conditions have worsened on average since the last such study in 2017: low-income households must spend an average of 12.4% of their disposable income (up from 10.9%) and/or work 10.1 h at minimum wage (up from 9.9 h) to pay for basic monthly water and sewer services. Analysis suggests that rising prices combine with underlying economic trends to exacerbate affordability. [ABSTRACT FROM AUTHOR]

The Metropolitan Water Reclamation District of Greater Chicago adopted the Tunnel and Reservoir Plan (TARP) to reduce combined sewer overflow (CSO) events in the Chicago region. The Thornton Composite Reservoir (TCR) became operational in 2015 providing an additional 30 million m3 of CSO‐impacted stormwater capacity. In the United States, no other mega reservoirs are in operation to provide as a reference to study the long‐term impacts of biosolids operations in water resource recovery facilities. The mean daily volume pumped from the Calumet TARP system to the Calumet Plant increased 144–238 m3 from 2012–2014 to 273–360 m3 from 2016–2018. Overall annual digester feed solids for the 2016–2018 post‐TCR period were 28,182 Mg, which was 11 percent less than the mean for the 2012–2014 period of 31,745 Mg. Annual digester draw solids for the 2016–2018 post‐TCR period were 19,422 Mg, which were 4 percent less than the 2012–2014 pre‐TCR period mean of 20,190 Mg. This paper demonstrated a decrease in digester feed loading to the Calumet Plant and, ultimately, a decrease in digester draw solids with an overall increase in plant and TARP flow in the years following operation of the TCR for the capture and treatment of CSO‐impacted stormwater. Practitioner points: Reservoirs capturing combined sewer overflow‐impacted stormwater improve water quality of local waterways.Mega reservoirs may impact solids loading to water resource recovery facilities.Hydraulic loading to water resource recovery facilities may be substantial with mega reservoirs. [ABSTRACT FROM AUTHOR]