Contamination In Water Distribution Networks Research Articles

Predicting the spread of contamination in water distribution networks laid on sloping terrains

Contamination in domestic and drinking water during the conveyance process is one of the biggest health risks of all time. This is a very common hazard that is expected in the areas where water, sewer, and drainage pipes are laid in trenches near each other. The extent of the contamination spread in the case of intrusion through a pipe leak for water distribution networks (WDNs) laid on sloping terrain is not known. This article deals with the simulation and hydraulic analysis of organic contaminant intrusion in WDNs with significant consideration of the slope of the laid pipes. The source of organic contamination is considered to be the nearby leaking sewer water. The effects of sloping terrain on contaminant spread in the pipe network are studied in detail by injecting contaminant concentrations at eight different critical locations in the network. The results of contamination spread after a particular time at all nodes are compiled, and by using statistical techniques, a relation between the contaminant spread and pipe slope is proposed. The presented model is validated by comparing the actual values of the contaminant in water samples obtained at the site with the calculated ones, and it shows that the values deviate within the range of ±2% only, which is considered a good match. The research proves to be beneficial for the management of water distribution through pipe networks against contaminants to maintaining water quality and public health.

Fungal and bacterial evaluation in drinking water distribution network and their association with physicochemical parameters

Preventing the growth of microorganisms in water distribution network (WDN) is an important public health priority. In this study, 98 water samples were collected from the Gorgan City (Iran) water distribution network (WDN) to assess fungal and bacterial contamination in WDN and their association with physicochemical parameters. All microbiological and physicochemical tests were performed as described in the standard method. The results showed that 15.3 %, 12.2 %, and 2 % of the sample had total coliforms, Clostridium perfringens and fecal coliforms, respectively; however, no Escherichia coli and fecal streptococci were found in samples. The average count of heterotrophic bacteria and fungi was 203.45 CFU/mL and 6.83 CFU/100 mL, respectively. Seven genera of fungi were isolated, of which Candida (19.4 %) and Aspergillus (11.2 %) were the most prevalent, followed by Penicillium (5.1 %), Rhodotorula (3.1 %), Cladosporium (2 %), Acremonium (2 %) and Alternaria (1 %). The mean and Standard deviation of free residual chlorine (FRC), pH, turbidity, temperature, total organic carbon and electrical conductivity were 0.22 ± 0.27 mg/l, 7.28 ± 0.22, 0.61 ± 0.68 NTU, 19.27 ± 2.83 °C, 0.45 ± 0.17 mg/l, and 953.49 ± 207.54 (µs/cm), respectively. The presence of pathogens fungus is a major public health concern for people with lowered immunity. The present study indicated that using microorganisms with different features provides a more reliable evaluation to assess the microbial growth in WDN. Amongst physicochemical parameters, FRC above 0.8 mg/l prevented the fungal and bacterial pathogens growth in WDN. However, further research is required to measure the risks of trihalomethane formation.

Optimal Water Quality Sensor Placement by Accounting for Possible Contamination Events in Water Distribution Networks

Contamination in water distribution networks (WDNs) can occur at any time and location. One protection measure in WDNs is the placement of water quality sensors (WQSs) to detect contamination and provide information for locating the potential contamination source. The placement of WQSs in WDNs must be optimally planned. Therefore, a robust sensor-placement strategy (SPS) is vital. The SPS should have clear objectives regarding what needs to be achieved by the sensor configuration. Here, the objectives of the SPS were set to cover the contamination event stages of detection, consumption, and source localization. As contamination events occur in any form of intrusion, at any location and time, the objectives had to be tested against many possible scenarios, and they needed to reach a fair value considering all scenarios. In this study, the particle swarm optimization (PSO) algorithm was selected as the optimizer. The SPS was further reinforced using a databasing method to improve its computational efficiency. The performance of the proposed method was examined by comparing it with a benchmark SPS example and applying it to DMA-sized, real WDNs. The proposed optimization approach improved the overall fitness of the configuration by 23.1% and showed a stable placement behavior with the increase in sensors.

Comparison of topological, empirical and optimization-based approaches for locating quality detection points in water distribution networks

The positioning of quality detection points as well as the frequency of sampling is a crucial aspect for the implementation of Water Safety Plans (WSPs), which have been proposed worldwide to ensure water quality and to minimize the risk from contamination in water distribution networks (WDNs). In this regard, some international legislations and best practices about quality of drinking water suggest very fine sampling frequencies, but they do not specify where the detection points should be located in a WDN. In this paper, three different approaches, based on empiricism, optimization and topology, respectively, were applied to locate detection quality points in a WDN. The comparison highlighted that empirical approach commonly adopted by water utility practitioners is unsatisfactory. The optimization-based approach, although performing significantly better, is difficult to apply, since it requires a calibrated hydraulic model. The topological approach, based on the use of the betweenness centrality and not requiring any hydraulic information and simulation, proves to be effective, and it can be easily adopted by water utilities to identify the location for quality detection points, due to its simplicity compared with the optimization-based approach.

Control of Lead Contamination in Water Distribution Networks: A Dynamic Optimization Framework

This study investigates the optimization of free chlorine-based disinfectant dosage for controlling the dissolution of lead (Pb) while limiting disinfection by-products (DBPs) formation in water distribution networks. A dynamic optimization framework is developed in this study to account for the impact of spatial and temporal variations of network hydraulics and water chemistry on dissolved lead concentrations. Accordingly, a dynamic schedule of disinfectant dosage is proposed to minimize water lead levels and two-point chlorine residual violations in the network. The results suggest that optimization of water chemistry parameters such as pH and orthophosphate dosage provide an additional degree of freedom to be explored in the problem of optimizing disinfectant dosage for compliance with conflicting mandates regulating lead levels and DBPs concentration in drinking water.

Impact of diffusion and dispersion of contaminants in water distribution networks modelling and monitoring

Abstract In recent years, there has been a need to seek adequate preventive measures to deal with contamination in water distribution networks that may be related to the accidental contamination and the deliberate injection of toxic agents. Therefore, it is very important to create a sensor system that detects contamination events in real time, maintains the reliability and efficiency of measurements, and limits the cost of the instrumentation. To this aim, two problems have to be faced: practical difficulties connected to the experimental verification of the optimal sensor configuration efficiency on real operating systems and challenges related to the reliability of the network modelling approaches, which usually neglect the dispersion and diffusion phenomena. The present study applies a numerical optimization approach using the NSGA-II genetic algorithm that was coupled with a new diffusive-dispersive hydraulic simulator. The results are compared with those of an experimental campaign on a laboratory network (Enna, Italy) equipped with a real-time water quality monitoring system and those of a full-scale real distribution network (Zandvoort, Netherlands). The results showed the importance of diffusive processes when flow velocity in the network is low. Neglecting diffusion can negatively influence the water quality sensor positioning, leading to inefficient monitoring networks.

Reducing Impacts of Contamination in Water Distribution Networks: A Combined Strategy Based on Network Partitioning and Installation of Water Quality Sensors

This paper proposes a combined management strategy for monitoring water distribution networks (WDNs). This strategy is based on the application of water network partitioning (WNP) for the creation of district metered areas (DMAs) and on the installation of sensors for water quality monitoring. The proposed methodology was tested on a real WDN, showing that boundary pipes, at which flowmeters are installed to monitor flow, are good candidate locations for sensor installation, when considered along with few other nodes detected through topological criteria on the partitioned WDN. The option of considering only these potential locations, instead of all WDN nodes, inside a multi-objective optimization process, helps in reducing the search space of possible solutions and, ultimately, the computational burden. The solutions obtained with the optimization are effective in reducing affected population and detection time in contamination scenarios, and in increasing detection likelihood and redundancy of the monitoring system. Last but most importantly, these solutions offer benefits in terms of management and costs. In fact, installing a sensor alongside the flowmeter present between two adjacent DMAs yields managerial advantages associated with the closeness of the two devices. Furthermore, economic benefits due to the possibility of sharing some electronical components for data acquisition, saving, and transmission are derived.

Towards Development of an Optimization Model to Identify Contamination Source in a Water Distribution Network

Protection of the water system is paramount due to the negative consequences of contaminated water on the public health. Water resources are one of the critical infrastructures that must be preserved from deliberate and accidental attacks. Water qualities are examined at the treatment plant. However, its quality can substantially be contaminated during transportation from the plant to the consumers’ taps. Contamination in water distribution networks (WDNs) is a danger that can have severe consequences on public health as well as an economic and social instability. Water distribution networks are immensely susceptible to deliberate or accidental attacks due to the complex nature of the system. Hence, contamination source identification (CSI) is a topical issue in water distribution systems that require immediate attention of researchers in order to protect mankind from the adverse effect of consuming contaminated water. Usually, a contaminant event can be detected by the water quality monitoring sensors or the contaminant warning system (CWS) installed on the network. Nevertheless, how to derive the source of the contamination from the collected information is a difficult task that must be tackled in order to evaluate the spread of the contamination and for immediate remedial strategies. In the past two decades, considerable efforts and advancement have been made by researchers applying various techniques in order to locate the source of the contamination in WDNs. Each of the techniques has certain limitations and applicability as reported in the literature. This paper presents a comprehensive review of the existing techniques with emphasis on their importance and technical challenges. Despite a series of investigations in this domain, the field is yet to be unified. Hence, open research areas are still available to explore. Consequently, improvement on the existing techniques is necessary and hereby suggested. More importantly, practical application of these techniques offer a major research gap that must be addressed.

Water Quality Event Detection in Drinking Water Network

Drinking water network is vulnerable to toxic chemicals. Anomaly detection-based event detection can provide reliable indication of contamination by analyzing the real-time water quality data, collected by online-distributed sensors in water network. This article reviews the water quality event detection methodologies based on the correlation of water quality parameters and contaminants. Further, we review how to reduce the impact of contamination in water distribution network, including sensor placement optimization and contamination source determination.

Identification of sources of pollution and contamination in water distribution networks based on pattern recognition

An intrusion of contaminants into the water distribution network (WDN) can occur through storage tanks (via animals, dust-carrying bacteria, and infiltration) and pipes. A sensor network could yield useful observations that help identify the location of the source, the strength, the time of occurrence, and the duration of contamination. This paper proposes a methodology for identifying the contamination sources in a water distribution system, which identifies the key characteristics of contamination, such as location, starting time, and injection rates at different time intervals. Based on simplified hypotheses and associated with a high computational efficiency, the methodology is designed to be a simple and easy-to-use tool for water companies to ensure rapid identification of the contamination sources, The proposed methodology identifies the characteristics of pollution sources by matching the dynamic patterns of the simulated and measured concentrations. The application of this methodology to a literature network and a real WDN are illustrated with the aid of an example. The results showed that if contaminants are transported from the sources to the sensors at intervals, then this method can identify the most possible ones from candidate pollution sources. However, if the contamination data is minimal, a greater number of redundant contamination source nodes will be present. Consequently, more data from different sensors obtained through network monitoring are required to effectively use this method for locating multi-sources of contamination in the WDN.

Monitoring Residual Chlorine Decay and Coliform Contamination in Water Distribution Network of Kampala, Uganda

The study was undertaken to examine water quality in the distribution network of Kampala City by assessing five storage reservoirs and four consumer taps. The aim was to evaluate residual chlorine decay andrelate it to the risk of recontamination. Physicochemical quality of water in the distribution network was temperature 25.6(24.23-28.66) pH 6.6 (6.5-7.1); turbidity 1.9 (0.5-4.5) NTU; colour 17.2 (2.0-54) PtCo, ammonia0.02 (0.0-0.05) mgl-1, and Fe2+ 0.005 (0-0.0.08) mgl-1. Residual chlorine decay was significant between the Water Treatment Plant (WTP) and the storage tanks (Total Chlorine, F=35.67, P< 0.05; Free Chlorine, F=37.97, P

Discussion of “Pollution Source Identification of Accidental Contamination in Water Distribution Networks” by Cristiana Di Cristo and Angelo Leopardi

Discussion of “Pollution Source Identification of Accidental Contamination in Water Distribution Networks” by Cristiana Di Cristo and Angelo Leopardi

Closure to “Pollution Source Identification of Accidental Contamination in Water Distribution Networks” by Cristiana Di Cristo and Angelo Leopardi

Closure to “Pollution Source Identification of Accidental Contamination in Water Distribution Networks” by Cristiana Di Cristo and Angelo Leopardi

Pollution Source Identification of Accidental Contamination in Water Distribution Networks

In the present technical note, a simple methodology for identifying the source location of an accidental contamination in a water distribution network is formulated. Starting from measured solute concentration data and using the pollution matrix concept, the methodology first selects a group of candidate nodes, which are possible intrusion points. Among all candidate nodes, the source location is then identified, minimizing the differences between simulated and measured concentrations. The source location procedure, which incorporates a hydraulic network simulation model, is formulated as an optimization problem, linearized using the water fraction matrix concept. An example illustrates methodology effectiveness. An uncertainty analysis is performed in order to demonstrate the methodology robustness with respect to uncertainties in some input data, like concentration measurements and water demands.