Water Quality In Distribution Systems Research Articles

Safety of Tap Water in Terms of Changes in Physical, Chemical, and Biological Stability

Monitoring the quality of tap water in the distribution system and the ability to estimate the risk of losing its sanitary safety is an important aspect of managing the collective water supply system. During monitoring, the physical, chemical, and biological stability of water was assessed, which is the main determinant ensuring the appropriate quality of water for consumers. The physicochemical and microbiological quality of water was analyzed for two distribution systems (DSs), including the analysis of heavy metals (Zn, Fe, Mn, Cr, Ni, Cu, Cd, Pb). The tests carried out showed that in both distribution systems, the water supplied to consumers met the guidelines for water intended for human consumption. It can be considered that the risk of uncontrolled changes in water quality in DSs with an average water production of <10,000 m3/d and the length of water pipelines < 150 km is very low. The water introduced into the system differed in the place of water intake and water purification technology, which influenced the final water quality. In DS(II), higher values were recorded for hardness, conductivity, calcium, alkalinity, nitrates, and DOC. It was found that the content of heavy metals during water transport to the consumer increased in the case of DS(I) for Zn, Ni, Cu, Cd, and Pb, and in the case of DS(II) for Fe, Mn, Ni, Cu, Cd, and Pb. The observed differences resulted from the different quality of the intake water as well as from different materials used to build internal installations and their age and technical condition. The analyzed tap water was characterized by physical and chemical stability. However, the water did not meet the guidelines for water biostability due to the increased content of biogenic substances.

Responses of drinking water bulk and biofilm microbiota to elevated water age in bench-scale simulated distribution systems

Reductions in nonresidential water demand during the COVID-19 pandemic highlighted the importance of understanding how water age impacts drinking water quality and microbiota in piped distribution systems. Using benchtop model distribution systems, we aimed to characterize the impacts of elevated water age on microbiota in bulk water and pipe wall biofilms. Five replicate constant-flow reactors were fed with municipal chloraminated tap water for 6 months prior to building closures and 7 months after. After building closures, chloramine levels entering the reactors dropped; in the reactor bulk water and biofilms the mean cell counts and ATP concentrations increased over an order of magnitude while the detection of opportunistic pathogens remained low. Water age, and the corresponding physicochemical changes, strongly influenced microbial abundance and community composition. Differential initial microbial colonization also had a lasting influence on microbial communities in each reactor (i.e., historical contingency).

Machine-learning-assisted prediction and optimized kinetic modelling of residual chlorine decay for enhanced water quality management

The quality of water changes from source to tap, presenting challenges in maintaining consistent water quality across the system. Predicting water quality in distribution systems, including disinfectant residual loss and by-product formation, has been the subject of research since the early 1990s. Although numerous models have been proposed to predict residual chlorine decay, disputes exist among researchers and experts over the superiority of certain models. Accordingly, this study modified the existing process-based bulk decay models by replacing the initial Total Residual Chlorine (TRC) concentration parameter with TRC demand, leading to an improvement in the models' performance. The modification resulted in a 38.03%, 28.02%, 23.11%, and 33.29% average improvement in Mean Squared Error (MSE) values for the First Order Model (FOM), Parallel First Order Model (PFOM), Second Order Model (SOM), and Parallel Second Order Model (PSOM), respectively. The study also introduced an online predictive method based on a Machine Learning (ML) algorithm that predicts the first-order TRC bulk decay rate by using water quality parameters as inputs. A Gaussian Process Regression (GPR) model was used to predict the kinetic parameters in FOM, which accurately predicted the test sets for most of the cases. In addition, a new methodology was proposed in this study for predicting TRC in water distribution systems that incorporates the variability of source natural organic matter, operational actions, and water demands. This method seeks to develop high-fidelity and robust water quality predictions that provide operational decision support for optimized distribution system management. In conclusion, this study emphasizes the importance of understanding water quality changes from source to tap and the challenges of maintaining consistent water quality across the system. The study suggests modifying existing models and introducing a novel methodology for predicting residual chlorine in water distribution systems that can improve water quality management and, ultimately, better public health outcomes.

A data quality assessment framework for drinking water distribution system water quality time series datasets

Abstract The derivation of information from monitoring drinking water quality at high spatiotemporal resolution as it passes through complex, ageing distribution systems is limited by the variable data quality from the sensitive scientific instruments necessary. A framework is developed to overcome this. Application to three extensive real-world datasets, consisting of 92 multi-parameter water quality time series of data taken from different hardware configurations, shows how the algorithms can provide quality-assured data and actionable insight. Focussing on turbidity and chlorine, the framework consists of three steps to bridge the gap between data and information; firstly, an automated rule-based data quality assessment is developed and applied to each water quality sensor, then, cross-correlation is used to determine spatiotemporal relationships and finally, spatiotemporal information enables multi-sensor data quality validation. The framework provides a method to achieve automated data quality assurance, applicable to both historic and online datasets, such that insight and actionable insight can be gained to help ensure the supply of safe, clean drinking water to protect public health.

Analysis of the evolution of ultra-filtered water quality in a drinking water distribution system by particle size distribution: Influence of pre-ozonation.

An experimental drinking water distribution system (DWDS) was used to evaluate the evolution of particle size distribution (PSD) and basic quality parameters of ultrafiltered water with or without pre-ozonation. An ultrafiltration (UF) module was set up, associated with a pre-ozonation system (3.7g O3 /m3 ). The permeate was circulated in the DWDS (300 m; 0.9m/s) with 0.4mg/L of chlorine, and the analysis of the PSD was performed using a β-variable mathematical model. A better control of membrane fouling was obtained with pre-ozonation, and PSD was necessary to observe water quality differences between permeates and in the DWDS. A decrease in particle concentration of 1.8 logarithms was obtained with the application of UF membranes, while a decrease of only 1.2 logarithms was obtained with pre-ozonation. The system without pre-ozonation showed a higher efficiency at removing smaller particles (around 2μm), with the absence of particles larger than 23 μm during both stages. The PSD revealed a worsening of water quality in the DWDS with an increase of particles smaller than 5μm during the application of UF membranes, while with pre-ozonation, all particle sizes analyzed increased their concentration. PRACTITIONER POINTS: Pre-ozonation led to a better control of membrane fouling, but a worsening of permeate quality according to particle size distribution. Pre-ozonation does not improve the turbidity, dissolved organic carbon or UV254 removal capacity of ultrafiltration during drinking water treatment. Particles size distribution reveals the deterioration of water quality in a drinking water distribution system better than turbidity or DOC. Ozone prior to ultrafiltration membranes led to a worsening of permeate quality, more significant in the drinking water distribution system.

Uncertainty analysis of water quality in water distribution system

Abstract Water quality simulation is affected by uncertain parameters such as pipe roughness coefficients, chlorine bulk decay coefficients, and chlorine wall decay coefficients, which are usually considered to be fuzzy variables. The minimum and maximum nodal chlorine concentrations and water ages at each α-cut level were obtained by the genetic algorithm (GA) based on EPANET hydraulic and water quality simulation toolkit. The fuzziness of nodal chlorine concentrations and water ages were measured using the fuzziness measure (FM) proposed in this paper. The method was applied to four networks to analyze the fuzziness of nodal chlorine concentrations and water ages. The results indicated that the distribution of nodal chlorine concentrations does not follow typical trapezoid distribution, while the distribution of nodal water ages follows typical trapezoid distribution. In addition, the chlorine concentration and water ages of nodes farther from the source are affected by uncertain parameters to a greater extent. The greater demands of nodes lead to less effects of uncertain parameters on chlorine concentration, and greater effects of uncertain parameters on water ages. This study would help in analyzing the fuzziness of hydraulic and water quality simulation results in WDS under uncertain conditions.

What Keeps Distribution System Water Quality Professionals Up at Night?

Journal AWWAVolume 114, Issue 8 p. 66-69 Water Quality Matters What Keeps Distribution System Water Quality Professionals Up at Night? Rebecca Slabaugh, Corresponding Author Rebecca Slabaugh rebecca.slabaugh@arcadis.com Search for more papers by this author Rebecca Slabaugh, Corresponding Author Rebecca Slabaugh rebecca.slabaugh@arcadis.com Search for more papers by this author First published: 04 October 2022 https://doi.org/10.1002/awwa.1981Read the full textAboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onFacebookTwitterLinked InRedditWechat Volume114, Issue8October 2022Pages 66-69 RelatedInformation

Water quality analysis and corrosion potential of the distribution network of Patna, Bihar, India

Drinking water distribution system water quality can be affected by chemical and microbial processes. A change in the chemical concentration of water is a result of pipe scaling and corrosion. It causes insignificant deterioration of water quality. This study determined the corrosion and scaling potential of the drinking water in the distribution networks of the water supply in Patna City, Bihar, India. For the determination of the physico-chemical parameters, 92 water samples were collected from 46 points of the distribution network. Four parameters were analysed in situ – namely, temperature, electrical conductivity, pH and total dissolved solids – and the remaining parameters – alkalinity, total hardness, calcium, magnesium, chloride, sulfate, nitrate and iron – were measured in the laboratory. Various widely used indices – namely, Langelier saturation index (LSI), Ryznar stability index (RSI), Puckorius scaling index (PSI), Larson–Skold index (LS) and aggressive index (AI) – were used to calculate corrosion and scaling potential of water samples. A result of the LSI and RSI, show that 86.96% of water samples are corrosive and only 13.04% are scaling tendency. PSI shows 30.43% of water samples are corrosive. LS shows all water samples are mildly corrosive. AI shows 71.74% of the water samples are moderately corrosive and only 28.26% of the water samples are scaling tendency.

Staged energy and water quality optimization for large water distribution systems.

Simultaneous optimization of energy and water quality in real-time large-sized water distribution systems is a daunting task for water suppliers. The complexity of energy optimization increases with a large number of pipes, scheduling of several pumps, and adjustments of tanks' water levels. Most of the simultaneous energy and water quality optimization approaches evaluate small (or hypothetical) networks or compromise water quality. In the proposed staged approach, Stage 1 uses a risk-based approach to optimally locate the chlorine boosters in a large distribution system based on residual chlorine failures and the associated consequences in different land uses of the service area. Integrating EPANET and CPLEX software, Stage 2 uses mixed integer goal programming for optimizing the day-ahead pump scheduling. The objective function minimizes the pumping energy cost as well as the undesirable deviations from goal constraints, such as expected water demand. Stage 3 evaluates the combined hydraulics and water quality performances at the network level. The implementation of the proposed approach on a real-time large-sized network of Al-Khobar City in Saudi Arabia, with 44 groundwater wells, 12 reservoirs, 2 storage tanks, 191 mains, 141 junctions, and 17 pumps, illustrated the practicality of the framework. Simulating the network with an optimal pumping schedule and chlorine boosters' locations shows a 40% improvement in water quality performance, desired hydraulics performance with optimal pump scheduling, and an average 20% energy cost reduction compared to the normal (unoptimized) base case scenario.

Optimization of booster chlorination for water distribution system under dual uncertainties

ABSTRACT Chlorine is generally used as disinfectant to sustain water quality in water distribution system (WDS). To prevent the occurrence of disinfectant by-product as well as control the growth of microorganism, the residual chlorine concentration in WDS should be kept between acceptable intervals. However, the chlorine concentration was uncertain due to chlorine decay, imprecise measure, hydraulic and topological conditions. In addition, nodal response coefficients to unit disinfectant mass in the left-hand-side of the constraints were also uncertain, which is affected by uncertain pipe diameter, roughness coefficients, nodal demand, bulk decay coefficient, and wall decay coefficient, etc. Therefore, in this paper a fuzzy chance-constrained optimization model under dual uncertainties was proposed and applied to optimize the chlorine injection mass to maintain chlorine in WDS distributed uniformly with consideration of randomness of chlorine concentration limits as well as uncertainty in response coefficient. The total injection mass decreases with the uncertainty level under possibility of dominance and necessity of dominance indices, while increases with the uncertainty level under possibility of strict dominance and necessity of strict dominance indices, which is effective in chlorine injection management.

Mixing of arsenic-rich groundwater and surface water in drinking water distribution systems: Implications for contaminants, disinfection byproducts and organic components

The utilization of groundwaters containing high levels of arsenic (As) for drinking water purposes presents major health and economic challenges for water utilities. One low-cost approach is to mix arsenic-rich groundwater (GW) with arsenic-free surface waters (SW) to achieve acceptable As levels. In this study we investigated the effect of different mixing ratios on water quality in an eastern Croatian water distribution system (WDS). To investigate the effects of mixing on drinking water quality, we measured the organic matter (OM) composition, disinfection byproduct (DBP) and metal concentrations in differently mixed ratios of GW and SW within the WDS. Fluorescence analysis revealed that the GW and SW had similar OM composition, with an almost equal ratio of humic- and protein-like OM throughout the WDS despite fluorescence indices revealing slightly different OM sources between the two water types. The tyrosine-like OM component was more variable, increasing during warmer months and towards the end of the WDS, most likely due to enhanced biofilm formation. Arsenic concentrations decreased to below 10 μg/L in the second half of the sampling campaign. Acceptable water quality was achieved after a period of destabilization and solubilization of loose deposits within the WDS resulting in their mobilization caused by water quality changes. Principal component and classification analysis, regression models and Spearman correlation coefficients revealed an association between As, OM and DBP concentrations with these correlations suggestive of their role in As mobilization in the WDS. Changing source waters, with different OM content and characteristics, corresponded to variable As release within the WDS.

AWWA Water Science Author Spotlight

<i>AWWA Water Science</i> Author Spotlight

Water quality deterioration of reclaimed water produced by reverse osmosis process in large pilot-scale distribution systems of different pipe materials

Abstract This work reports the effects of five pipe materials on reverse osmosis (RO)-reclaimed water quality in a large pilot-scale distribution system. These materials includes cast iron (CI), cast iron with cement-mortar lining (CML), stainless steel (SS), PVC, and PE. Long-term running tests for 96 hours are conducted with water quality parameters monitored online and analyzed offline. The results showed that red water appeared in CI pipe due to iron corrosion. The pH and TDS increased during the long-term test. Alkali–silica reaction in CML pipe led to a high increase of pH from 6.3 to 11.4, and TDS from 51 to 230 mg/L. Water quality deterioration was not observed in SS, PVC, and PE pipes. Residual chlorine decay occurred in all the five material pipes with the decay rate order of CI ≫ CML &amp;gt; SS ≈ PVC ≈ PE. Ion concentration variation was also followed during the tests. Fe and Mn ions were detected in CI pipe and Ca, Si, Al, and S were detected in CML pipe. No detectable ion release was found in SS, PVC, and PE pipes. A kinetic model was postulated for the detected ion release with the mechanisms discussed in-depth.

Fate of ammonia and implications for distribution system water quality at four ion exchange softening plants with elevated source water ammonia

Hard water and elevated ammonia are problems for many United States groundwater drinking water utilities, and some utilities, particularly those in the Midwest, face both challenges. Ion (cation) exchange (IX) is a common treatment technique for hardness reduction (i.e., softening) and may be used to remove ammonia as well, but these constituents may compete in IX and impact overall treatment performance. Few data have been reported on the impact on ammonia concentrations when using IX for softening in full-scale systems. This study investigated four full-scale groundwater treatment plants in Illinois that practice IX for softening (raw water hardness > 220 mg/L as CaCO3) and have elevated groundwater ammonia concentrations (> 2 mg N/L). Sampling throughout the year revealed consistent finished water hardness levels but variable ammonia concentrations. Ammonia removal varied and depended on how much water had been treated since the last regeneration. High ammonia removal (sometimes > 90%) occurred in the first half of the IX service cycle, while effluent ammonia concentrations increased compared to the influent (sometimes > 200%) towards the end of the IX cycle (total length 50,000-92,000 gallons [190-350 m3]). Ammonia removal efficiency varied among the plants, but the overall trends were similar. Because variable ammonia concentrations may make it difficult to produce a consistent total chlorine residual, they can negatively impact disinfection and water quality in the distribution system. Ammonia concentrations should be considered when designing softening systems to determine regeneration frequency, develop blending strategies, or include an alternative ammonia treatment process before IX softening to produce a more stable and consistent finished water.

Intermittent Water Supply Impacts on Distribution System Biofilms and Water Quality

Intermittent water supplies (IWS) are routinely experienced by drinking water distribution systems around the world, either due to ongoing operational practices or due to one off interruptions. During IWS events changing conditions may impact the endemic biofilms leading to hydraulic mobilisation of organic and inorganic materials attached to pipes walls with a resulting degradation in water quality. To study the impact of IWS on the microbiological and physico-chemical characteristics of drinking water, an experimental full-scale chlorinated pipe facility was operated over 60 days under realistic hydraulic conditions to allow for biofilm growth and to investigate flow resumption behaviour post-IWS events of 6, 48 and 144 hours.Turbidity and metal concentrations showed significant responses to flow restarting, indicating biofilm changes, with events greater than 6 hours generating more turbidity responses and hence discolouration risk. The increase in pressure when the system was restarted showed a substantial increase in total cell counts, while the subsequent increases in flow led to elevated turbidity and metals concentrations. SUVA254 monitoring indicated that shorter times of non-water supply increased the risk of aromatic organic compounds and hence risk of disinfection-by-products formation. DNA sequencing indicated that increasing IWS times resulted in increased relative abundance of potential pathogenic microorganisms, such as Mycobacterium, Sphingomonas, and the fungi Penicillium and Cladosporium.Overall findings indicate that shorter IWS result in a higher proportion of aromatic organic compounds, which can potentially react with chlorine and increase risk of disinfection-by-products formation. However, by minimising IWS times, biofilm-associated impacts can be reduced, yet these are complex ecosystems and much remains to be understood about how microbial interactions can be managed to best ensure continued water safe supply.

Using complex network analysis for water quality assessment in large water distribution systems

Assessing and modelling the water quality in a water distribution system (WDS) are highly important to ensure a reliable supply with sufficient water quality. Owing to the high computational burden of such an analysis, frequently, simplifications are required or surrogate models are used (e.g., reducing the level of detail of the network model), neglecting significant aspects. For large (currently all-pipe) models and/or recurrent simulations (e.g., integrated studies, sensitivity analysis, deep uncertainty analysis, design, and optimization), the computational burden further increases. In this study, a novel complex network analysis-based approach for high-computational efficiency water quality assessment in a WDS is developed and comprehensively tested (R² values in comparison with state-of-the-art nodal water qualities in median of 0.95 are achieved). The proposed model is successfully utilized in a design study to identify the design solutions exceeding water quality thresholds with a correct identification rate between 96% and 100%. The computational efficiency is determined to be a factor 4.2e-06 less than that of state-of-the-art models. Therefore, the proposed model significantly improves the water quality assessment for such tasks in large WDSs.

Inexact [Formula: see text] fuzzy chance-constrained programming of booster chlorination for water distribution system under uncertainty.

To sustain water quality in water distribution system (WDS), disinfectant generally chlorine is boosted to water distribution system. However, the concentration of chlorine should be limited to acceptable scope. The upper bound of the scope is set for preventing the occurrence of disinfectant byproduct, which is harmful to human health. The lower bound of the scope is set for controlling the growth of microorganism as well as reducing the cost. As such, the optimization model was applied to solve the water quality issue in WDS. However, in WDS, chlorine decays and varies with time and space, affected by pipe material, temperature, pH value, and chlorine injection. Therefore, in this paper, an inexact [Formula: see text] fuzzy chance-constrained programming (IMFCCP) model was proposed to optimize the chlorine injection to maintain chlorine in WDS at an acceptable level with consideration of uncertainty in water quality simulation. The results indicated that the upper bounds, the lower bounds, and intervals of the injection mass increased with preference parameter λ, which means that the results are more unreliable with higher preference parameter λ. However, the effect of reliability level ζ on the injection mass is determined by the relationship between the preference parameter λ and reliability level ζ. In case of [Formula: see text], the effect is not more significant than the case of [Formula: see text]. The results can help managers determine the injection strategy under uncertainty.

WITHDRAWN: Prediction of water quality in municipal distribution system

In this study Feed Forward Back propagation (FFBP) and Cascade Feed Forward Back propagation (CFBP) algorithms have been compared for prediction of water quality in the distribution systems, so as make it tomeet the standards of sustainability. These algorithms have been used for forecasting Water Quality Index (WQI) in various zones of municipal distribution system by using pH, alkalinity, hardness, dissolved oxygen (DO), total solids (TS) and MPN as the input variables. Different ANN models were developed using training data set and tested in order to determine optimum number of neurons in the hidden layer, best fitting transfer function, optimum length of training dataset and best suited ANN algorithm. Further the developed ANN models were compared with multiple linear regression (MLR) technique, which is a commonly used statistical technique for modelling water quality variables. The study revealed that ANN model outperforms multiple regression technique for prediction of water quality in the distribution system and it is a robust tool for understanding the poorly defined relations between water quality variables and WQI in municipal distribution system.

Impact of Water Demand Pattern Variation on Hydraulic Behavior and Water Quality in Water Distribution Systems

Water is the most valuable source for human life. Egypt is one of the driest countries facing an enormous shortage of potable water especially with the population increase and limited water resources. It is becoming aware of the need to preserve water and sustainable water management. Potable water supply pipes are important for delivering water to consumers and serving as the last process between the treatment plant and the consumer. Water demand can vary periodically over the course of the day and for the same average daily demand, the peak value of the demand pattern can vary. These variations in peak demand can have significant effect on the hydraulic behavior of pipes network, water quality, and energy consumption through it. A significant amount of cost is spent on energy consumption in the water supply pipes network. In this research, the effect of water demand pattern variation on hydraulic behavior, water quality and energy consumption in water supply pipes network is studied. EPANET2 software was used to perform the hydraulic analysis through extended period simulation through a hypothetical water supply pipes network. Five patterns of demand variation were adopted in this analysis called pattern demand for big city, village, rural area, industrial zone and hotels. It was found that the type of demand pattern has a significant effect on velocity through the different pipes and pressure head of the different nodes and chlorine decay through the network.

Modeling Residual Free Chlorine in Drinking Water Distribution Systems.(Dept.C)

Water is at its peak quality when it leaves the treatment plant. With time, the disinfectant residual decreases, possibly with increase in microbial activity. Changes in quality may be caused by biological or chemical transformations, by mixing of waters from different sources, or by a loss of system safety. Until recently, no much research has been made to the problem of changes in water quality in distribution system especially in Egypt. This paper app lies WaterCAD simulation model for modeling water quality in the distribution systems at El-Delta Co. for Fertilizer and Chemical Industries and compares the results to field data. This software implements the Eulerian Discrete Volume-Element Method (DVEM) to solve the numerical constituent transport problem for the system being analyzed. A model is used to predict the residence time and the propagation of chlorine residual in several points in the distribution system. Good correspondence with observed chlorine residuals is obtained at locations where the hydraulics is well characterized. It was found that using a wall decay constant in the range of 0.2 - 2.0 for pipes in a network might be suitable for all distribution systems. Field quality data is important in developing and understanding predictive models.