Complex Water Distribution Systems Research Articles

Risk Assessment and Detection of Legionella species in the Water System of A Luxury Hotel in Dhaka city, Bangladesh

Legionella cause Legionnaires’ disease and Pontiac fever, and, more rarely, extrapulmonary infections, collectively referred to as legionellosis. Legionella pneumophila causes serious pneumonic infections, and water and Air Conditioning systems are a common source. We performed this study focusing on identifying and assessing the potential sources of Legionella spp. in a luxury hotel water system in Dhaka, Bangladesh. As hotels often have complex water distribution systems that can harbor and facilitate the growth of these bacteria, understanding the risks and implementing effective control measures is crucial for public health. This study determines the presence of Legionella spp. and potential factors contributing to their proliferation within the hotel water systems. In total 42 water samples and six swabs from 7 different points were collected multiple times between March 2018 and April 2019 and were analyzed. Legionella spp. was detected in all samples (100%) tested. The highest colony counts were observed in water samples from the hot water tank and cooling system. The findings highlight the importance of regular monitoring, maintenance, disinfection, and flushing protocols to mitigate the risk of Legionella spp., contamination, and subsequent health issues among hotel guests and staff.
 Bangladesh J Microbiol, Volume 40, Number 1, June 2023, pp 33-39

Water consumption assessment and classification in industrial buildings - The case study of Continental Advanced Antenna, Vila Real, Portugal

Water abstraction for the industrial, domestic, and agricultural sectors increased from 0.67 trillion m3/year in the 1900s to 3.79 trillion m3/year in 2000, and it is expected to increase by 55 % in 2050 when the majority of the world's population will live in urban areas. Concerning the industrial sector, despite the efforts to a more sustainable use, water is still an essential and irreplaceable resource, and this situation tends to increase due to modern industrial installations that require large-scale and complex water distribution systems. Usually, industries consume a large volume of water, however due to more and severer regulations, it is necessary to propose strategies for the aid of water conservation.This article presents a methodology to analyse, classify and optimize water consumption in industrial installations, using a real case study located in Vila Real, Portugal. The daily water consumption per worker, the daily record of use of each type of device and the hourly usage pattern were analysed and a classification was achieved according to the ANQIP (National Association for Quality in Building Installations) calculator. The case study revealed a great opportunity of improvement in what concerns to water efficient use. Some measures to improve the efficiency of water use in the building were pointed out, such as the use of rainwater harvesting systems, the use of aerators and replacements of taps and faucets when possible.The methodology is expeditious and user-friendly, and easy to replicate in similar cases, however it reveals some difficulties (especially in the data collection process that is made by inquiry, once it is always dependent on the respondent sensibility and willingness).

Development of Smoothed Particle Hydrodynamics based water hammer model for water distribution systems

ABSTRACTSmoothed 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.

Proper Pricing Approach to the Water Supply Cost Sharing: A Case Study of the Eastern Route of the South to North Water Diversion Project in China

Conflict in cost sharing is normal in complex water distribution system projects, such as the inter-basin water diversion project (IWDP). China’s South to North Water Diversion Project (SNWDP) is the largest IWDP in the world, with a complex relationship between upstream and downstream users of the water supply. Therefore, it is necessary to propose an applicable and unsophisticated cost-sharing method to deal with the complex relationship between upstream and downstream users. This paper proposes an improved cost-sharing method based on the continuity equation of water quantity and the balance equation of the project cost between upstream and downstream users. The fairness of sharing the joint cost between parties involved in the eastern route of SNWDP (ER-SNWDP) obtained using the proposed improved cost-sharing method is investigated by comparing its results with the existing cost-sharing method. The results demonstrate that the proposed method can overcome the non-convergence issue of the existing sharing formula and reduce the differences between upstream and downstream users’ sharing costs. The improved method provides a cost-sharing strategy that is more easily accepted by both the upstream and downstream users than the existing estimation approach. Therefore, the proposed pricing approach can provide technical guidance for decision makers in the effective operation of large-scale IWDPs in areas with quasi water markets.

Identifying Major Hydrologic Change Drivers in a Highly Managed Transboundary Endorheic Basin: Integrating Hydro‐Ecological Models and Time Series Data Mining Techniques

AbstractThe fragile balance of endorheic lakes in highly managed semiarid basins with transboundary water issues has been altered by the intertwined effects of global warming and long‐term water mismanagement to support agricultural and industrial demand. The alarming rate of global endorheic lakes' depletion in recent decades necessitates formulating mitigation strategies for ecosystem restoration. However, detecting and quantifying the relative contribution of causal factors (climate variability and anthropogenic stressors) is challenging. This study developed a diagnostic multivariate framework to identify major hydrologic drivers of lake depletion in a highly managed endorheic basin with a complex water distribution system. The framework integrates the Soil and Water Assessment Tool (SWAT) simulations with time series decomposition and clustering methods to identify the major drivers of change. This diagnostic framework was applied to the Salton Sea Transboundary Basin (SSTB), the host of the world's most impaired inland lake. The results showed signs of depletion across the SSTB since late 1998 with no significant changes in climate conditions. The time series data mining of the SSTB water balance components indicated that decreases in lake tributary inflows (−16.4 Mm3 yr−2) in response to decline in Colorado River inflows, associated with state water transfer agreements, are causing the Salton Sea to shrink, not changes in the irrigation operation as commonly believed. The developed multivariate detection and attribution framework is useful for identifying major drivers of change in coupled natural human systems.

Reliability analysis of complex water distribution systems: the role of the network connectivity and tanks

Abstract A reliable water distribution network (WDN) can provide an adequate supply service to customers under both normal and abnormal working conditions. The WDN reliability analysis, therefore, is a keystone to improve the supply service efficiency. Strategies for reliability analysis are usually proved on small WDNs, which do not compare with large real complex systems in terms of number of water tanks, pressure reduction valves, variable speed pumps, controlled devices and possible alternative water supply schemes. The topological changes due to pipeline interruptions impact on emptying–filling of water tanks and network pressure status. This work proposes a two-level procedure for mechanical reliability assessment, suited for large real WDNs. It leverages a path/connectivity-based approach to set up reliability indicators for global-level analysis and local screening of the most critical scenarios. The employed advanced hydraulic model includes the automatic detection of topological changes and the robust modelling of water level in tanks using the generalized global gradient algorithm. The extended period simulation enables the reliability assessment of alternative water supply schemes and the sensitivity of tanks and controlled devices to single failure events. The procedure is demonstrated on a real complex network, being consistent with the ongoing digital transition in the WDN management sector.

Modular interdependency analysis for water distribution systems

Complexity in water distribution systems (WDSs) poses a challenge for analysis and management of the systems. To reduce the complexity, the recent development of complex network science provides a system decomposition technique that converts a complex WDS with a large number of components into a simple system with a set of interconnected modules. Each module is a subsystem with stronger internal connections than external connections. Thus far, the topological features of the modular structure in WDS have been extensively studied but not the behavioural features, e.g. the hydraulic interdependencies among modules. Therefore, this paper aims to quantitatively measure and graphically visualize the module interdependency in WDSs, which helps understanding the behavioural complexity of WDSs and thus various WDS analyses, such as pipe maintenance, model calibration, rehabilitation, and District Metered Areas planning. Specifically, this study first identifies the WDS's modular structure then measures how changes in the state of one module (i.e. any single pipe failure or perturbed demand within each module) affect the state of another module. Modular interdependencies are summarized in an interdependency matrix and visualized by the digraph. Four real-world systems are analysed, and three of them shows low interdependencies among most of the modules and there are only a few critical modules whose status changes will substantially affect a number of other modules. Hence, highly interconnected topologies may not result in strong and complex module interdependency, which is a fact that simplifies several WDS analysis for practical applications as discussed in this paper.

Coupling compositional data analysis (CoDA) with hierarchical cluster analysis (HCA) for preliminary understanding of the dynamics of a complex water distribution system: the Naples (South Italy) case study

Providing safe tap water has been a global concern.

Multiphase DMA Design Methodology Based on Graph Theory and Many-Objective Optimization

Partitioning a water distribution system (WDS) into district metered areas (DMAs) is a difficult task due to the complex WDS structure and simultaneous consideration of multiple constraints. Further, alternative metrics can define DMA goals, and expressing and quantifying those objectives in an efficient algorithm is also challenging. To address the multifaceted set of objectives, a multiphase DMA design method is developed. DMA feed pipes are identified as the primary flow paths in a branched network. In the methodology presented here, the feed pipe network is first laid out by determining node clusters and boundary pipes that maximize the dissimilarity of pressures and modularities between clusters and minimize the number of cuts between clusters while defining the number of DMAs closest to the desired number. In the methodology’s second phase, secondary DMA feed pipes are identified by minimizing the number of secondary feed pipes and maximizing the nodal excess energy while maintaining desired pressure. Finally, a postoptimization analysis compares the performance of the Pareto solutions based on their availability, water quality, and daily leakage. System availability is calculated based on the minimum cut-set method combined with a new pressure-driven analysis method. To accelerate the optimization algorithm, two strategies are applied: step-by-step optimization and reducing the decision variable searching space by considering desirable DMA characteristics. The effectiveness of the methods is examined by applying it to the C-Town and real B-Town water distribution networks. Results demonstrate that the search space reduction method effectively decomposes the full network into DMAs in the face of multiple hydraulic and water quality metrics.

Improving the Resilience of Postdisaster Water Distribution Systems Using Dynamic Optimization Framework

Improving the resilience of water distribution systems (WDSs) to handle natural disasters (e.g., earthquakes) is a critical step toward sustainable urban water management. This requires the water utility to be able to respond quickly to such disaster events, and in an organized manner, to prioritize the use of available resources to restore service rapidly while minimizing the negative impacts. Many methods have been developed to evaluate the WDS resilience, but few efforts are made so far to improve the resilience of a postdisaster WDS through identifying optimal sequencing of recovery actions. To address this gap, the authors propose a new dynamic optimization framework in this study in which the resilience of a postdisaster WDS is evaluated using six different metrics. A tailored genetic algorithm is developed to solve the complex optimization problem driven by these metrics. The proposed framework is demonstrated using a real-world WDS with 6,064 pipes. Results obtained show that the proposed framework successfully identifies near-optimal sequencing of recovery actions for this complex WDS. The gained insights, conditional on the specific attributes of the case study, include the following: (1) the near-optimal sequencing of a recovery strategy heavily depends on the damage properties of the WDS; (2) replacements of damaged elements tend to be scheduled at the intermediate-late stages of the recovery process due to their long operation time; and (3) interventions to damaged pipe elements near critical facilities (e.g., hospitals) should not be necessarily the first priority to recover due to complex hydraulic interactions within the WDS.

Save Energy With Anti‐Stagnation Valves

The city of Hamilton's water distribution system is one of Canada's oldest and most complex water distribution systems. Situated at the west end of Lake Ontario, the city has an elevation of 298 ft (91 m) above sea level and is defined by unique geographical features, including the Niagara Escarpment and the Hamilton Harbor.

Leakage detection of HVAC pipeline network based on pressure signal diagnosis

In order to further improve the accuracy and application range of pipeline network leakage detection, this paper simulates the complex water distribution system to set up an experimental platform. On this basis, a leakage detection method using improved wavelet denoising and short time Fourier transform is proposed, which can be used to monitor the leakage of the pipeline network in real time. This method is compared with the six methods of Empirical Mode Decomposition (EMD), wavelet decomposition, Gauss model, recurrence plot, Wigner-Ville distribution (WVD) and Wigner-Hough transformation (WHT). The results show that this method can accurately diagnose the leakage of the pipeline network. This method is verified by the field measured pressure signals of other literature. It is concluded that this method is effectual for the leakage detection of the actual complex pipeline network. In order to test the universality of this method, it is also used to analyze the pressure signal of the heating pipeline network and the gas pipeline network. The results show that the method proposed in this paper is also applicable to other complex pipeline networks.

Optimal Design for Shock Damper with Genetic Algorithm to Control Water Hammer Effects in Complex Water Distribution Systems

In this paper, the optimal design of a shock damper and its parameters along with the layout for controlling water hammer effects in water distribution systems (WDS) will be investigated. The shock damper and its governing equations are introduced, and then complex network (networks with loop and branching) analysis is performed during the occurrence of a water hammer. Because of the multiple design parameters for the shock damper and the complexity of WDS transient analysis, a standard optimization problem is defined with maximum safety as the objective function. The problem constraints are the network analysis equations in the event of a water hammer. Also, other constraints consist of the maximum and minimum range of the allowable head and values of the design parameters for the shock damper. To solve the problem, a genetic algorithm is used, and a flow chart of the problem-solving design with the genetic algorithm is also provided. To investigate the efficiency and the effect of the optimal design of the shock damper, two real water distribution networks are considered, which include a gravity network and a pumping network. To create a water hammer occurrence in the first network, the amount of discharge in one of the nodes is suddenly increased, while in the second network, one of the control valves is closed suddenly. These events lead to the occurrence of a significant water hammer in each system, resulting in both positive and negative waves and water column separation phenomena. The results show the high effectiveness of the optimal shock damper design in controlling the effects of transient flows in real water distribution systems, thereby increasing those systems’ effectiveness.

A Bayesian model updating approach for detection-related problems in water distribution networks

A Bayesian system identification technique is proposed for detection-related problems in the context of water distribution networks. The identification process is combined with a hydraulic simulation model for performing steady and unsteady analyses. In particular, leakage detection in water pipe networks is examined. A number of hydraulic model classes are defined as potential leakage events. Based on information from flow rates in the pipes, the implemented simulation-based Bayesian model updating technique provides estimates of the most probable leakage scenarios. Such scenarios correspond to the model classes that maximize their posterior probabilities. The effectiveness of the proposed framework is illustrated by applying the leakage detection approach to a complex water distribution system. Issues such as the effect of model and measurement errors, number of flow tests at each monitoring location, and sensor number and location on the performance of the detection methodology are addressed.

Water Leakage Detection for Complex Pipe Systems Using Hybrid Learning Algorithm Based on ANFIS Method

In most city water distribution systems, a considerable amount of water is lost because of leaks occurring in pipes. Moreover, an unobservable fluid leakage fault that may occur in a hazardous industrial system, such as nuclear power plant cooling process or chemical waste disposal, can cause both environmental and economical disasters. This situation generates crucial interest for industry and academia due to the financial cost related with public health risks, environmental responsibility, and energy efficiency. In this paper, to find a reliable and economic solution for this problem, adaptive neuro fuzzy inference system (ANFIS) method which consists of backpropagation and least-squares learning algorithms is proposed for estimating leakage locations in a complex water distribution system. The hybrid algorithm is trained with acceleration, pressure, and flow rate data measured through the sensors located on some specific points of the complex water distribution system. The effectiveness of the proposed method is discussed comparing the results with the current methods popularly used in this area.

Clustering for Analysis of Water Distribution Systems

AbstractSimplification methodologies for complex water distribution systems (WDS) are essential for better understanding water distribution system behavior. Such methodologies have substantially im...

Delta Smelt and Water Politics in California

The Delta Smelt Hypomesus transpacificus is a small translucent fish that lives in the heart of California's water distribution system. It is an endemic species that is on verge of extinction, largely because it is in direct competition with people for water. This article discusses the controversy surrounding this fish by describing (1) the biology of Delta Smelt; (2) California's complex water storage and distribution system; (3) the history of Delta Smelt, including conservation efforts; (4) the present controversies surrounding it; and (5) the future of Delta Smelt. The decline of Delta Smelt is a strong indicator that the ecosystem of the Sacramento–San Joaquin Delta has undergone large‐scale changes that make it an unfavorable environment for native fishes. Reversing the trajectory of the Delta Smelt toward extinction will require major shifts in California water policy and water use as well as active management of the smelt's habitat and life history.

Impact of Urban Development on Energy Use in a Distribution System

This research examined the effect of urban development patterns on the energy use of a complex water distribution system in the United States. The energy inputs and outputs to each pressure zone were quantified under historical expansion and urban intensification scenarios. Results showed that the lift energy increased in zones farthest from the river source. Frictional energy loss was highest in the zone nearest the source because system pipes conveyed flows to meet demands in all zones. While the zone nearest the source had a higher connectivity, the frictional energy loss in this zone was comparable to that in zones near the edge of the system with a lower level of connectivity. In the intensification scenario, the reallocation of demand from the edge to the urban core of the system decreased energy use by 50%, reduced frictional losses from 22 to 16%, and increased the energy supplied to users.

Efficacy of copper-silver ionisation in controlling Legionella in complex water distribution systems and a cooling tower: Over 5 years of practical experience

Control of Legionella bacteria in water distribution systems and cooling towers is an increasing priority for health authorities world wide. Treatment of Legionella contaminated water is essential, and a well-recognized method to control Legionella is copper-silver ionisation. In this study the efficacy of copper-silver ionisation in 4 complex drinking water distribution systems (1 juvenile institution, 2 hotels and 1 penitentiary) and 1 cooling tower was studied over a period of at least 5 years. Dosing of 400±200μg/l copper and 40±20μg/l silver proved to be effective to control, abate and eradicate Legionella bacteria at all 5 treated locations. Legionella reoccurred only incidentally and temporarily (in 3.8% of the measurements; 27 out of 718), most likely due to insufficient flushing of the water distribution systems; in the case of the cooling tower technical malfunction of the tower itself and non-optimal positioning of the copper-silver ionisation system in the cooling tower. There was no evidence that pH (7.8–8.6) and hardness (1.4–2.3mmol/l) of treated drinking and cooling water influenced the efficacy of copper-silver ionisation.

Utility-Based Maintenance Optimization for Complex Water-Distribution Systems Using Bayesian Networks

Water supply systems (WSS), as well as other real-world systems, are characterized by complex configurations. For these systems, it is essential to ensure appropriate utility through optimal maintenance planning. The difficulties in decision-making are much increased by lack of information regarding the operation and failure conditions. When maintenance optimization is considered for systems configured as networks, comprising a large number of components, the main challenge is to model the reliability characteristics, such as availability, taking account of the interactions and dependencies between different components. The aim of this paper is to provide an optimal Preventive Maintenance (PM) plan with a view to maximizing the utility of a complex repairable system using Bayesian Networks (BNs). For each node of the BN, the optimal PM periodicity is obtained, in accordance with the policy of periodic imperfect PM with minimal repair at failure. The system availability is then computed, by Bayesian inference, for various combinations of nodes, or subsystems, periodicities and partial renewals before the complete renewal of the whole system. A utility function is then introduced to provide the maintenance plan for the system, leading to the implementation of the best policy. The methodology is illustrated by numerical application on WSS.