Illicit discharges into sewer systems are a widespread concern within China\'s urban drainage management. They can result in unforeseen environmental contamination and deterioration in the performance of wastewater treatment plants. Consequently, pinpointing the origin of unauthorized discharges in the sewer network is crucial. This study aims to evaluate an integrative method that employs numerical modeling and statistical analysis to determine the locations and characteristics of illicit discharges. The Storm Water Management Model (SWMM) was employed to track water quality variations within the sewer network and examine the concentration profiles of exogenous pollutants under a range of scenarios. The identification technique employed Bayesian inference fused with the Markov chain Monte Carlo sampling method, enabling the estimation of probability distributions for the position of the suspected source, the discharge magnitude, and the commencement of the event. Specifically, the cases involving continuous release and multiple sources were examined. For single-point source identification, where all three parameters are unknown, concentration profiles from two monitoring sites in the path of pollutant transport and dispersion are necessary and sufficient to characterize the pollution source. For the identification of multiple sources, the proposed SWMM-Bayesian strategy with improved sampling is applied, which significantly improves the accuracy.

Even though it has been established that a hyetograph\'s shape affects the results of hydrological simulations, common engineering practice does not always account for this fact. Instead, a single design storm is often considered sufficient for designing a urban drainage system. This study examines the impact that this design paradigm, combined with the uncertainty introduced by subjective choices made during the design process, has on the robustness of a designed system. To do so, we evaluated a set of individual designs created by engineering students using the same Chicago hyetograph as a design storm. We then created ensembles of hyetographs with the same precipitation volume and duration as the Chicago hyetograph and evaluated the designs\' hydrological responses. The results showed that designs, which performed equally well for the initial design storm, triggered varying responses for the storms in the ensembles and, consequently, showed different levels of robustness, hinting at a need to adapt the current design approach.

Numerous countries and regions have embraced implementing a separate sewer system, segregating sanitary and storm sewers into distinct systems. However, the functionality of these systems often needs to improve due to irregular interconnections, resulting in a mixed and malfunctioning system. Sewage collection is crucial for residential sanitation, but untreated collection significantly contributes to environmental degradation. Analyzing the simultaneous operation of both systems becomes vital for effective management. Using mathematical tools for precise and unified diagnosis and prognosis becomes imperative. However, municipal professionals and companies need more tools specifically designed to evaluate these systems in a unified way, mapping all the hydraulic connections observed in practice. This study proposes a unified simulation method for stormwater and sanitary sewer urban systems, addressing real-world scenarios and potential interferences. The primary goal is to develop a simulation method for both systems, considering system interconnections and urban layouts, involving hydrodynamic and water quality simulations. The practical application of this method, the Multilayer Hydrodynamic Simulation Method (MODCEL-MHUS), successfully identifies issues in urban water networks and suggests solutions, making it a valuable tool for urban water management and environmental engineering professionals.

With the increasing frequency of extreme weather events and a deepening understanding of disasters, resilience has received widespread attention in urban drainage systems. The studies on the resilience assessment of urban drainage systems are mostly indirect assessments that did not simulate human behavior affected by rainfall or semi-quantitative assessments that did not build simulation models, but few research characterizes the processes between people and infrastructure to assess resilience directly. Our study developed a dynamic model that integrates urban mobility, flood inundation, and sewer hydrodynamics processes. The model can simulate the impact of rainfall on people\'s mobility behavior and the full process including runoff generation, runoff entering pipes, node overflow, flood migration, urban mobility, and residential water usage. Then, we assessed the resilience of the urban drainage system under rainfall events from the perspectives of property loss and urban mobility. The study found that the average percentage increase in commuting time under different return periods of rainfall ranged from 6.4 to 203.9%. Calculating the annual expectation of property loss and traffic obstruction, the study found that the annual expectation loss in urban mobility is 9.1% of the annual expectation of property loss if the rainfall is near the morning commuting peak.

In the management of urban drainage networks, great interest has been generated in the removal of sediments from sewer systems. The unsteady three-dimensional (3D) flow and turbulent coherent structures surrounding sediment reduction plates in a sewer system are investigated by means of the detached-eddy simulation (DES). Particular emphasis is given to detailing the instantaneous velocity and vorticity fields within the grooves, along with an examination of the three-dimensional, long-term, average flow structure at a Reynolds number of approximately 105. Velocity vectors demonstrate continuous flapping of the flow on the groove wall, periodically interacting with ejections of positive and negative vorticity originating from the grooves. The interaction between the three-dimensional groove flow and the shear flow leads to the downstream transport of patches of positive and negative vorticity, which significantly influence sediment transport. The high-velocity shear flows and strong vortices generated in undulating topography, as identified by the Q-criteria, are the key factors contributing to the efficient sediment reduction capabilities of the sediment reduction plates. The sediment reduction plates with partially enclosed structures exhibit low sedimentation rates in grooves on the plate, a broader acceleration region, and a lesser impact on the flow capacity. The results improve the understanding of the hydrodynamics and turbulent coherent structures surrounding the sediment reduction plates while elucidating the driving factors behind the enhancement of sediment scouring and suspension capacities. These results indicate that the redesign of the plates as partially enclosed structures contributes to further improving their sediment reduction performance.

Antimicrobial resistance (AMR) is a global public health threat, and the environment has been identified as an important reservoir for resistant microorganisms and genes. Storm overflows (SOs) discharge wastewater and stormwater, and are found throughout many wastewater networks. While there are no data currently showing the impact of SOs on the environment with respect to AMR in the UK, there is a small but growing body of evidence globally highlighting the potential role of SOs on environmental AMR. This review aims to provide an overview of the current state of SOs, describe global data investigating the impact of SOs on environmental AMR, and discuss the implications of SOs regarding AMR and human health. In addition, the complexities of studying the effects of SOs are discussed and a set of priority research questions and policy interventions to tackle a potentially emerging threat to public health are presented.

Real-time and model-predictive control promises to make urban drainage systems (UDS) adaptive, coordinated, and dynamically optimal. Though early implementations are promising, existing control algorithms have drawbacks in computational expense, trust, system-level coordination, and labor cost. Linear feedback control has distinct advantages in computational expense, interpretation, and coordination. However, current methods for building linear feedback controllers require calibrated software models. Here we present an automated method for generating tunable linear feedback controllers that require only system response data. The controller design consists of three main steps: (1) estimating the network connectivity using tools for causal inference, (2) identifying a linear, time-invariant (LTI) dynamical system which approximates the network, and (3) designing and tuning a feedback controller based on the LTI urban drainage system approximation. The flooding safety, erosion prevention, and water treatment performance of the method are evaluated across 190 design storms on a separated sewer model. Strong results suggest that the system knowledge required for generating effective, safe, and tunable controllers for UDS is surprisingly basic. This method allows near-turnkey synthesis of controllers solely from sensor data or reduction of process-based models.

Drainage modeling that accurately captures urban storm inundation serves as the foundation for flood warning and drainage scheduling. In this paper, we proposed a novel coupling ideology that, by integrating 2D-1D and 1D-2D unidirectional processes, overcomes the drawback of the conventional unidirectional coupling approach that fails to properly represent the rainfall surface catchment dynamics, and provides more coherent hydrological implications compared to the bidirectional coupling concept. This paper first referred to a laboratory experimental case from the literature, applied and analyzed the coupling scheme proposed in this paper and the bidirectional coupling scheme that has been widely studied in recent years, compared the two coupling solutions in terms of the resulting accuracy and applicability, and discussed their respective strengths and weaknesses to validate the reliability of the proposed method. The verified proposed coupling scheme was then applied to the modeling of a real drainage system in a region of Nanjing, China, and the results proved that the coupling mechanism proposed in this study is of practical application value.

Increasingly frequent urban floods strain the traditional grey infrastructure, overwhelming the capacity of drainage networks and causing challenges in managing stormwater. The heavy precipitation leads to flooding and damage to drainage systems. Consequently, efficient mitigation strategies for flooding have been researched deeply. Green infrastructure (GI) has proved to be effective in responding the increasing risk of flood and alleviate pressure on drainage systems. However, as the primary infrastructure of stormwater management, there is still a lack of attention to the dynamic operation feature of urban sewer systems during precipitation events. To fill this gap, we proposed a novel approach that integrates hydraulic characteristics and the topological structure of a sewer network system. This approach aims to identify influential nodes, which contribute to the connectivity of the sewer network amidst dynamic changes in inflow during precipitation events. Furthermore, we adopted rain barrels to serve as exemplars of GI, and 14 GI layout schemes are produced based on the different ranks of influential nodes. Implementing GI measures on both poorly performing and well-performing nodes can yield distinct benefits in mitigating node flooding. This approach provides a new perspective for stormwater management, establishing effective synergy between GI and the drainage system.

With climate change and urbanization, existing urban drainage systems are being stressed beyond their design capacity in many parts of the world. Real-time control (RTC) can improve the performance of these systems and reduce the need for system upgrades. However, developing optimal control policies for RTC is a challenging research area due to computational demands, high uncertainties and system dynamics. This study presents a new RTC method using neuro-evolution for controlling combined sewer overflow (CSO) in urban drainage systems. Neuro-evolution is an approach to neural network research by evolutionary algorithms. Neuro-evolution realizes RTC by training the control policy in advance, thus avoiding the online optimization process in the application period. The simulation results of the benchmark Astlingen network indicate that the trained control policy outperforms the equal filling degree strategy in terms of CSO volume reduction and robustness in the face of tank level uncertainty. The performance analysis of the typical CSO events shows that the control policy mainly makes positive contributions during \'small\' CSO events rather than \'large\' ones. In particular, the effectiveness of the control policy in \'small\' CSO events is more prominent in the initial phase of the events compared with the final phase. This work stands to support a foundation for future studies in the control of urban water systems based on neuro-evolution.