Urban flood modeling with a novel coupling method of surface and sewer hydrodynamic processes.

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.

Optimal sensor placement for the routine monitoring of urban drainage systems: A re-clustering method.

The construction of an efficient monitoring network is critical for the effective and safe management of urban drainage systems. This study developed a re-clustering methodology that incorporates additional perspectives beyond node similarity to improve the traditional clustering process for optimal sensor placement. Instead of targeting event-specific water quality or hydraulic monitoring, the method integrates the water hydraulic and quality characteristics of nodes in response to the demand for routine monitoring. The implementation of this method first applies model simulation to generate the attribute datasets required for clustering analysis, and then re-clusters the initial clustering result according to the constructed re-clustering potential indices. And the information theory-based evaluation metrics were introduced to quantitatively assess the sensor deployment scheme obtained by amalgamating the two clustering results. Two networks with different drainage systems and sizes were chosen as case studies to illustrate the application of the framework. The results demonstrate that the clustering process enables to expand the information contained in the monitoring network, and that the re-clustering strategy can generate more comprehensive and practical solutions upon this basis.

GIS-based fuzzy comprehensive evaluation of urban flooding risk with socioeconomic index system development.

Due to the climate change-induced extreme rainfall, urban flooding risk is one of the major concerning risks in the near future with accelerating occurrence frequency and intensity. To systematically evaluate the socioeconomic impacts induced by urban flooding, this paper proposed a GIS-based spatial fuzzy comprehensive evaluation (FCE) framework for local government to efficiently take contingency measures especially under urgent rescue conditions. The risk-assessing procedure could be investigated in 4 aspects: 1) application of the hydrodynamic model to simulate the depth and extent of inundation; 2) quantification of the impact of flooding with 6 methodically picked evaluation indexes concerning the transportation attenuation, residential security, and tangible and intangible monetary losses according to depth-damage functions; 3) implementing FCE method: comprehensive evaluation of urban flooding risk with the diverse socioeconomic indexes by fuzzy theory; and 4) presenting the risk maps of single and multiple impact factors intuitively in ArcGIS platform. The detailed case study in SA city validates the effectiveness of the adopted multiple index evaluation framework, which could help detect higher risk areas with low transport efficiency, high economic loss, high social impact, and high intangible damage. The results of single-factor analysis can also provide feasible suggestions for decision-makers and other stakeholders. Theoretically, the proposed method tends to improve the evaluation accuracy as the inundation distribution can be simulated by hydrodynamic model rather than subjective prediction with hazard factors, while the impact quantification with flood-loss models can also directly reflect the vulnerability of involved factors instead of empirical weight analysis of traditional methods. Besides, the results illustrate that the areas with higher risk levels reasonably coincide with severe inundation situations and dense hazard-bearing bodies. This systematic evaluation framework can support applicable references for further extension to other similar cities.

A novel design of in-line static mixer for permanganate/bisulfite process: Numerical simulations and pilot-scale testing.

An increasing number of chemical technologies to wipe out contaminants within an incredibly short period of time have been developed recently, while their application was always hindered by the inefficient or improper mixing of reactants. To address this issue, the present work proposed a new static mixer named Tai-Chi which consists of blade, fin, and spoiler elements. Tai-Chi mixer can slice and divert the solutions inside and generate high shear flow to promote mixing process. Numerical simulations helped to determine the optimal operating conditions for Tai-Chi mixer, including laying its components anterior to the injection nozzles and keeping the velocity rate ratio of main pipe to branch pipe within the range of 0.5 to 1. Numerical simulations further proved that Tai-Chi mixer could strike a great balance between mixing performance (coefficient of variation [CoV] reaches 0.1 within 5 to 7 pipe diameters downstream) and head loss (nearly a half of other high shear static mixer in the market). Data of pilot-scale testing by Tai-Chi mixer confirm that 80% sulfamethoxazole could be eliminated in permanganate/bisulfite process within 8 pipe diameters, as well as showed the superiority of Tai-Chi's mixing performance in early stage compared with other static mixers in the market. PRACTITIONER POINTS: A Tai-Chi static mixer with blade, fin, and spoiler elements is devised. The optimal condition of flow rate and installment of Tai-Chi mixer is determined. Ultra-fast mixing is achieved by Tai-Chi (CoV < 0.1 within 5-7 pipe diameters). Pilot-scale test verifies the mixing efficiency of Tai-Chi mixer.

Maintaining the long-term accuracy of water distribution models with data assimilation methods: A comparative study.

The upgrading of water supply services is calling for more accurate and adaptive numerical models to give insight into actual water distribution systems (WDSs), which underlines the importance of carefully calibrating model parameters. Due to unavoidable uncertainties in the calibration process such as measurement errors, errors in model parameters assumed to be known, and local-optimum of calibration algorithms, calibrated parameters could still contain non-negligible latent errors, and the calibrated model may not able to maintain its long-term accuracy when operating conditions change. To solve this problem, there is growing interest in adopting data assimilation (DA) methods to utilize more comprehensive information in long-term measurements to reduce the impact of uncertainties and maintain the accuracy and stability of calibrated models. In this study, two traditional calibration methods and four DA methods were tested and compared in two WDSs with different structures, which aims to form a general understanding of the behavior and applicability of different methods. The calibration results show that DA methods perform better than traditional methods and are more robust to different types of uncertainties, which provide an effective way to maintain the long-term accuracy of WDS models to enable better management of WDSs. Ensemble-based DA methods such as Particle Filter (PF) and Inferential-Measurement Kalman Filter (IMKF) performed well in the real-life system. They avoid linear approximation and can better estimate the impact of uncertainties to assimilate accurate correction information of the parameters. Gradient-based DA methods such as Extended Kalman Filter (EKF) and Variational Bayesian Adaptive Kalman Filter (VBAKF) have lower computational demand, but they are found to be less robust when dealing with large system uncertainties and nonlinearities.

Contamination source identification in water distribution networks using convolutional neural network.

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.

Iron stability on the inner wall of prepared polyethylene drinking pipe: Effects of multi-water quality factors.

Iron is currently one of the main contaminants of drinking water. The inner walls of drinking pipes can cause iron to release in water chemistry, which alters the water quality, including its chloride, sulfate, bicarbonate, pH, and humic acid (HA) levels. Hence, the goal of this research was to improve our understanding of the multi-water quality factors affecting iron release in polyethylene pipes. An array of bench-scale experiments were conducted exposing model water with different concentrations of chloride, sulfate, bicarbonate, HA, and different pH levels to prepared polyethylene pipes following the response surface methodology. The single role of HA during iron release is also evaluated by changing its concentration. A comprehensive study revealed that regression models could be used to describe the relationship between the five water quality parameters and iron release. The coefficients of determination were 0.890 and 0.870 for the fitting equations of total and soluble iron concentrations in water, respectively. In the presence of HA, the concentration of iron in water increased more rapidly than that for the other four factors (chloride, sulfate, bicarbonate, and pH). In addition, the Visual MINTEQ results suggest that a lower HA concentration tended to increase the degree of saturation of iron solids. In turn, this limits iron release and considerably increases the iron concentration in water.

A practical multi-objective optimization sectorization method for water distribution network.

In recent years, water leakage problems in water distribution networks (WDN) have been attracting more attention, with an emphasis on energy and water resources. As one of the measures used for flow monitoring and leakage control, water network sectorization is a research hotspot in China. This paper, which begins with an introduction of present sectorization methods, proposes a multi-objective optimization sectorization method based on a comprehensive consideration of the hydraulics, water quality and economy. This method is based on the non-dominated sorting genetic algorithm (NSGA-II) which is a heuristic algorithm for multi-objective optimization to obtain the optimal schemes. In addition, human experience is also considered in the optimization process. In a case study, this method proves to be efficient in producing good results with little impact on the hydraulics and water quality of the WDN, and the results obtained are acceptable for multiple objectives. Therefore, this method provides references for the transformation of future water distribution network sectorization.

A novel anammox granules-circulating expanded granular sludge bed reactor for the efficient circulation and retention of floating anammox granules.

In application of anammox process, the operation of the conventional expanded granular sludge bed reactor (EGSBconv.) is severely limited by the blocking and decay of floating anammox granules.To address this emerging issue, a novel three-phase separator configuration was designed and an anammox granules circulating EGSB (EGSBGC) was proposed in this study. In the EGSBGC, an influent scour on floating granules, whose effect was confirmed by simulation with a three-dimensional flow model, was obtained by integrating the external three-phase separator with the influent and the external cycle. After 166-d operation, the nitrogen removal efficiency of the EGSBGC reached 75.6%, being 1.28-times that of the EGSBconv. (58.9%). The sludge concentration in the main body of the EGSBGC reached 3112 ±â€¯65 mg/L, compared with 2613 ±â€¯42 mg/L in the EGSBconv. (p < 0.05). Moreover, the severe granules blockage and decay problem that is frequently encountered in the EGSBconv. no longer occurred in the EGSBGC. The relative abundance of anammox bacteria in granules from the three-phase separator of the EGSBGC was 29.7%, significantly higher than that from the EGSBconv. (16.1%, p < 0.05). The blockage and decay of granules in the three-phase separator of the EGSBconv. led to an obvious proliferation of heterotrophic bacteria, with their relative abundance increased by 9.4% compared with the seed sludge (38.6% vs. 29.2%). This study proposed a practical three-phase separator configuration to sustain efficient and stable operation of anammox processes toward the promotion of granules circulation, retention and reaction.

Laboratory analysis on the surface runoff pollution reduction performance of permeable pavements.

Permeable pavements are used to address the water quality impacts of urbanization. However, few quantitative relations are available on their pollutant removal performance with respect to varying conditions, especially for different components of a permeable pavement. Individually, the water quality performance of the surface pavement layer and gravel layer of a permeable pavement under various conditions was determined in laboratory-scale pavement cells. Our aim was to reveal the manner in which different factors influence the ability of these two layers to remove total suspended solids (TSS), nutrients, including nitrate (NOx-N), ammonia (NH4-N) and phosphorous (TP), chemical oxygen demand (COD), and heavy metals (copper (Cu), lead (Pb), cadmium (Cd), and zinc (Zn)), and to provide quantitative understanding of these influences. The removal efficiencies of most stormwater runoff pollutants showed a significant variation with changing rainfall intensity. NH4-N, NOx-N, TP, and TSS removal exhibited statistically negative linear relationship with rainfall intensity. TSS removal was negatively correlated with TSS concentration for the gravel layer, whereas no obvious trend was observed for the surface pavement layer. The statistical results obtained demonstrate that TSS, NH4-N, NOx-N, TP, and COD were removed mainly by the surface pavement layer. A smaller gravel gradation was more effective for removing most pollutants, except for NOx-N and COD. Positive linear relationships were observed between the gravel layer thickness and pollutant (TSS, TP, NH4-N, Cu, and Cd) removal. More importantly, a simple mathematical model was developed to predict the overall performance of the permeable pavement system. By comparing with the overall measured performance, a good performance was achieved, illustrating its promising application in the design of permeable pavements.

A simple but robust convergence trajectory controlled method for pressure driven analysis in water distribution system.

This paper presents a novel convergence trajectory controlled method to perform pressure driven analysis (PDA) in water distribution systems (WDSs). The proposed method makes forcibly the convergence error decrease continuously, which is fundamentally different from the traditional uncontrolled convergence process, thereby ensuring a robust convergence behavior for hydraulic analysis with PDA in WDS. In addition, two Relaxation Factor section strategies are developed to control the convergence trajectory towards the desired downtrends. The novel methodology is implemented based on EPANET3.0 by modifying the source code which is available in GitHub (https://github.com/OpenWaterAnalytics/epanet-dev). Firstly, the improved code was validated extensively with a benchmark WDS under rigorous boundary conditions. Subsequently, four challenging different size WDSs are also tested in terms of the effectiveness and efficiency. The results illustrate that the proposed method is able to enable the convergence of PDA to be more stable and more robust, even under some extreme abnormal boundary conditions.

Effects of Sulfate, Chloride, and Bicarbonate on Iron Stability in a PVC-U Drinking Pipe.

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.

Computational fluid dynamics modelling of flow and particulate contaminants sedimentation in an urban stormwater detention and settling basin.

Sedimentation is a common but complex phenomenon in the urban drainage system. The settling mechanisms involved in detention basins are still not well understood. The lack of knowledge on sediment transport and settling processes in actual detention basins is still an obstacle to the optimization of the design and the management of the stormwater detention basins. In order to well understand the sedimentation processes, in this paper, a new boundary condition as an attempt to represent the sedimentation processes based on particle tracking approach is presented. The proposed boundary condition is based on the assumption that the flow turbulent kinetic energy near the bottom plays an important role on the sedimentation processes. The simulated results show that the proposed boundary condition appears as a potential capability to identify the preferential sediment zones and to predict the trapping efficiency of the basin during storm events.