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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.

Contamination source identification (CSI) is significant for water quality security and social stability when a contamination intrusion event occurs in water distribution systems (WDSs). However, in research, this is an extremely challenging task for many reasons, such as limited number of water quality sensors and their limitations in detecting contaminants. Hence, some researchers have introduced consumers’ complaint information as an alternative of sensors for CSI. But the problem with this approach is that the uncertainty of complaint delay time has a great impact on the identification accuracy. To address this issue, this study constructed complaint matrices to present the spatiotemporal characteristics of consumer complaints in an intrusion event and proposed a new methodology employing convolution neural network (CNN)—a deep learning algorithm—for the purpose of pattern recognition. CNN aimed to explore the inherent characteristics of complaint patterns corresponding to different contaminant intrusion nodes and to improve the performance of identifying the contamination source based on consumer complaint information. Two case studies illustrated methodology effectiveness in WDSs of various scales, even with the high uncertainties of complaint delay time. The comparison between CNN and a back-propagation artificial neural network algorithm demonstrates that the former framework possesses stronger robustness and higher accuracy for CSI.

In this study, we propose an optimized long short-term memory (LSTM)-based approach which is applied to early warning and forecasting of ponding in the urban drainage system. This approach can quickly identify and locate ponding with relatively high accuracy. Based on the approach, a model is developed, which is constructed by two tandem processes and utilizes a multi-task learning mechanism. The superiority of the developed model was demonstrated by comparing with two widely used neural networks (LSTM and convolutional neural networks). Then, the model was further revised with the available monitoring data in the study area to achieve higher accuracy. We also discussed how the number of selected monitoring points influenced the performance of the corrected model. In this study, over 15 000 designed rainfall events were used for model training, covering various extreme weather conditions.

The water quality performance of permeable pavement is influenced by many factors. The knowledge of the combined effect of multifactor on the performance of permeable pavement is vital to its design and construction. However, few quantitative relations are available in literature. Regression orthogonal composite design was adopted to develop models to predict the combined effects of multifactor on the performance of surface pavement layer and gravel layer of permeable pavement. The most commonly concerned factors, including rainfall intensity, inflow concentration of total suspended sediment (TSS), gradation of gravels, and thickness of the gravel layer, were selected. The interactions of these factors were also considered. The viability of the models was tested using analysis of variance (ANOVA), and the results showed the models for TSS removal rate of the surface pavement layer and gravel layer, Cd, Cu, Zn, TP, NH4-N, and NOx-N removal rate of the gravel layer were reliable and can be used for prediction purpose. More importantly, an integrated model was developed to predict the overall performance of permeable pavement, and a good performance was achieved (− 2.43% to approximately 1.85%) through comparison with the measured values, illustrating its promising application. Then, the integrated model was compiled as modeling tools based on EPA SWMM (modified SWMM) and applied to a campus renovation scenario (three scenarios) assessment. Scenario 1 with higher pollutant removal rates is better than others. The results obtained demonstrated that the modified SWMM can respond to the changes of influencing parameters and will be beneficial for both practitioners and decision makers in permeable pavement design and construction.HighlightsRegression orthogonal composite design was employed to predict pollutant removals.The relative importance and the most influential input variables were pointed.An integrated model was developed to predict performance of permeable pavement.The viability of model was tested and promising results were obtained.The model was incorporated into SWMM and the application proved its effectiveness.

Smoothed Particle Hydrodynamics (SPH) method is used to solve water hammer equations for pipeline systems due to its potential advantages of easily capturing column separation and slug impact. Currently, the SPH-based water hammer model has been only developed to simulate single pipe flow with simple boundary conditions. It is still a challenge to apply the SPH-based water hammer model to practical water distribution systems (WDSs). To address this issue, this study develops a complete SPH-based Water Hammer model for Water Distribution System (SPH-WHWDS). Within the proposed method, the complex internal and external boundary condition treatment models of the multi-pipe joint junction and different hydraulic components are developed. Buffer and mirror particles are designed for boundary treatment coupling with the method of characteristics (MOC). Two benchmark test cases, including an unsteady pipe flow experiment and a complex WDS, are used to validate the proposed model, with the data from the experimental test in the literature and the simulation results by the classical MOC. The results show the proposed SPH-WHWDS model is capable to simulate transient flows with accurate and robust results for pipeline systems, which may provide further insights and an alternative tool to study water hammer phenomena in complex WDSs.

Transient (highly unsteady) air-water two-phase flows and spring-like geysers have been one of the critical concerns in drainage pipeline systems, which may cause or exacerbate drainage flooding problems and associated damage consequences. In this paper, the flow dynamics and energy evolution mechanism of the induced spring-like geysers are innovatively investigated through a two-phase full-2D numerical model developed in this study. After full validation by laboratory experimental tests conducted in this study, the proposed 2D model is systematically applied to simulate transient air-water flows in drainage pipelines. The results have shown acceptable accuracy of this full-2D model to capture the complex flow interactions between the air and water phases, and indicated that the velocity and pressure distribution patterns are highly relevant to the air-water interface deformation and energy exchange. The in-depth energy analysis demonstrates that the intermittent eruption of geysers could be attributed to the conservation and release of different energy forms during the transient air-water two-phase flow process. Besides, the numerical applications for the systems with different boundaries and initial conditions indicate that the different ventilation conditions and initially entrapped air volume may significantly affect the velocity distribution of the air phase, thereby playing an essential role to provide effective measures to mitigate unexpected geyser events and pressure oscillations in the system. The results and findings of this paper could provide insights to improve the theory and practice of transient air-water two-phase flows in drainage pipeline systems.

Urban water distribution networks (WDNs) are facing serious leakage problems. As cities expand, the leakage localization burden on large WDNs gradually increases. Although methods have been widely researched, there is a lack of studies and successful applications for large-scale WDNs. To deal with this, a stepwise fast leakage localization Method, SFLLM, utilizing the `dynamic area narrowing down (DAND)' strategy and coupled leakage features (CLF) is proposed. The SFLLM includes a fast-and-dynamic stage using the DAND strategy to reduce the potential leakage area and an accurate localization stage. Only partial representative candidate locations are required to simulate leakages by DAND, and meantime CLF is used to analyze the leakage similarities so that the localization accuracy and efficiency can be improved. SFLLM was tested on a benchmark WDN, saving more than 88% of simulation by DAND strategy and achieving localization in 11 seconds. The results also proved the enhanced performance of CLF in ensuring the stability of the accuracy against various types of uncertainties that may occur in real WDNs. Moreover, three real burst leaks in an actual large-scale WDN were localized within 205 m in about 22 minutes by SFLLM, showing the method's reliable applicability in guiding field leak exploration.

BackgroundChanging water quality was prevalent in the current water supply. The fluctuation of iron stability due to changing water quality followed four characteristics: objectivity, relativity, predictability, and controllability. Therefore, it was necessary to study the stability of iron in the pipe network by integrating different water quality factors.ResultsThe iron stability risk evaluation system was established according to the different water quality factors in the drinking water distribution systems (DWDSs). Meanwhile, an improved fuzzy comprehensive evaluation method was established to evaluate the risk of iron. Chloride, sulfate, dissolved organic matter (DOM) and pH were selected as the risk assessment index. The divisions of different evaluation levels were carried out through the values of water quality factor. On the basis of expert scoring, the weight and membership degree of water quality factors were analyzed by structural entropy method. In addition, risk analysis was established by using the optimized risk assessment system. According to the results of the comprehensive evaluation, DOM and pH were identified as two of the most important factors in the evaluation of the iron stability. In addition, compared with the traditional fuzzy comprehensive evaluation method, the optimized method had a higher degree of fit which could more clearly prove the relationship between the risk value and the iron concentration.ConclusionThe uncertainty between the factors was eliminated by establishment of the fuzzy evaluation method combined with the different effects of water factors on iron stability. The method could be used as a comprehensive evaluation and be beneficial to the analysis of iron risk in water supply network.

In order to describe iron stability in plastic pipes and to ensure the drinking water security, the influence factors and rules for iron adsorption and release were studied, dependent on the Unplasticized poly (vinyl chloride) (PVC-U) drinking pipes employed in this research. In this paper, sulfate, chloride, and bicarbonate, as well as synthesized models, were chosen to investigate the iron stability on the inner wall of PVC-U drinking pipes. The existence of the three kinds of anions could significantly affect the process of iron adsorption, and a positive association was found between the level of anion concentration and the adsorption rate. However, the scaling formed on the inner surface of the pipes would be released into the water under certain conditions. The Larson Index (LI), used for a synthetic consideration of anion effects on iron stability, was selected to investigate the iron release under multi-factor conditions. Moreover, a well fitted linear model was established to gain a better understanding of iron release under multi-factor conditions. The simulation results demonstrated that the linear model was better fitted than the LI model for the prediction of iron release.

Long-term corrosion, construction irregularities, road pressure and other reasons lead to various defects in urban sewer pipelines. Closed-circuit television (CCTV) and quick view (QV) are currently the most commonly used techniques to detect the internal state of the pipeline, but CCTV requires a large amount of capital investment and manpower costs, while QV is faced with the use of limitations and inaccurate positioning. The inspection of urban sewerage networks has long been a challenge for the relevant management authorities to overcome. To this end, in this study, an device was assembled using a six-axis MEMS gyroscope sensor as the core component to inspect and locate the breakage point of the pipe. Specifically, a six-axis MEMS gyroscope sensor is used as the core component along with a small lithium battery and a remote control switch assembled in a highly waterproof round box, and dropped into a laboratory to simulate a sewage pipe that has external water infiltration. Then the device is recovered and the SD card on which the data is stored is removed, the data is loaded to perform the coordinate conversion process and restore the trajectory and attitude of the device along its travel. The three axis axial acceleration of the device before and after passing through the infiltration point is analyzed for anomalies, as well as changes in the roll and pitch angle fluctuations of the device. Multiple experiments demonstrated that the six-axis MEMS gyro sensor response is very sensitive, generating data and storing it through the DATALOG module. With the reading and analysis of the data, when the pipeline is broken by external water intrusion, the axial acceleration value, pitch angle and roll angle of the device will change abruptly after flowing through the infiltration point, based on the analysis of these indicators the preliminary judgment of the extent of external water infiltration and locate the location of the infiltration point, potential applications of MEMS gyroscopic sensors in the field of sewerage are believed to be vast.