An experimental study for chlorine residual and trihalomethane formation with rechlorination

2007 ◽  
Vol 55 (1-2) ◽  
pp. 307-313 ◽  
Author(s):  
J. Lee ◽  
D. Lee ◽  
J. Sohn

Maintenance of adequate chlorine residuals and control of disinfection byproducts (DBPs) throughout water distribution systems is currently an important issue. In particular, rechlorination can be a powerful tool in controlling adequate chlorine residual in a large distribution system. The patterns of chlorine decay and formation of DBPs due to rechlorination are different from those of chlorination; chlorine decay is slower and trihalomethane (THM) formation is lower with rechlorination. The present study evaluates whether existing predictive models for chlorine residual and THM formation are applicable in the case of rechlorination. A parallel first-order decay model represents the best simulation results for chlorine decay, and an empirical power function model (modified Amy model) with an introduced correction coefficient (ϕ1, ϕ2) is more suitable to THM formation.

2003 ◽  
Vol 3 (1-2) ◽  
pp. 239-246 ◽  
Author(s):  
G. Kastl ◽  
I. Fisher ◽  
V. Jegatheesan ◽  
J. Chandy ◽  
K. Clarkson

Nearly all drinking water distribution systems experience a “natural” reduction of disinfection residuals. The most frequently used disinfectant is chlorine, which can decay due to reactions with organic and inorganic compounds in the water and by liquid/solids reaction with the biofilm, pipe walls and sediments. Usually levels of 0.2-0.5 mg/L of free chlorine are required at the point of consumption to maintain bacteriological safety. Higher concentrations are not desirable as they present the problems of taste and odour and increase formation of disinfection by-products. It is usually a considerable concern for the operators of drinking water distribution systems to manage chlorine residuals at the “optimum level”, considering all these issues. This paper describes how the chlorine profile in a drinking water distribution system can be modelled and optimised on the basis of readily and inexpensively available laboratory data. Methods are presented for deriving the laboratory data, fitting a chlorine decay model of bulk water to the data and applying the model, in conjunction with a simplified hydraulic model, to obtain the chlorine profile in a distribution system at steady flow conditions. Two case studies are used to demonstrate the utility of the technique. Melbourne’s Greenvale-Sydenham distribution system is unfiltered and uses chlorination as its only treatment. The chlorine model developed from laboratory data was applied to the whole system and the chlorine profile was shown to be accurately simulated. Biofilm was not found to critically affect chlorine decay. In the other case study, Sydney Water’s Nepean system was modelled from limited hydraulic data. Chlorine decay and trihalomethane (THM) formation in raw and treated water were measured in a laboratory, and a chlorine decay and THM model was derived on the basis of these data. Simulated chlorine and THM profiles agree well with the measured values available. Various applications of this modelling approach are also briefly discussed.


Water SA ◽  
2019 ◽  
Vol 45 (2 April) ◽  
Author(s):  
Denis Nono ◽  
Phillimon T Odirile ◽  
Innocent Basupi ◽  
Bhagabat P Parida

Assessment of probable causes of chlorine decay in water distribution systems of Gaborone city, Botswana Gaborone city water distribution system (GCWDS) is rapidly expanding and has been faced with the major problems of high water losses due to leakage, water shortages due to drought and inadequate chlorine residuals at remote areas of the network. This study investigated the probable causes of chlorine decay, due to pipe wall conditions and distribution system water quality in the GCWDS. An experimental approach, which applied a pipe-loop network model to estimate biofilm growth and chlorine reaction rate constants, was used to analyse pipe wall chlorine decay. Also, effects of key water quality parameters on chlorine decay were analysed. The water quality parameters considered were: natural organic matter (measured by total organic carbon, TOC; dissolved organic carbon, DOC; and ultraviolet absorbance at wavelength 254, UVA-254, as surrogates), inorganic compounds (iron and manganese) and heterotrophic plate count (HPC). Samples were collected from selected locations in the GCWDS for analysis of water quality parameters. The results of biofilm growth and chlorine reaction rate constants revealed that chlorine decay was higher in pipe walls than in the bulk of water in the GCWDS. The analysis of key water quality parameters revealed the presence of TOC, DOC and significant levels of organics (measured by UVA-254), which suggests that organic compounds contributed to chlorine decay in the GCWDS. However, low amounts of iron and manganese (< 0.3 mg/L) indicated that inorganic compounds may have had insignificant contributions to chlorine decay. The knowledge gained on chlorine decay would be useful for improving water treatment and network operating conditions so that appropriate chlorine residuals are maintained to protect the network from the risks of poor water quality that may occur due to the aforementioned problems.


2017 ◽  
Vol 7 (2) ◽  
pp. 1528-1534 ◽  
Author(s):  
A. Gupta ◽  
N. Bokde ◽  
D. Marathe ◽  
K. Kulat

Reduction of leakages in a water distribution system (WDS) is one of the major concerns of water industries. Leakages depend on pressure, hence installing pressure reducing valves (PRVs) in the water network is a successful techniques for reducing leakages. Determining the number of valves, their locations, and optimal control setting are the challenges faced. This paper presents a new algorithm-based rule for determining the location of valves in a WDS having a variable demand pattern, which results in more favorable optimization of PRV localization than that caused by previous techniques. A multiobjective genetic algorithm (NSGA-II) was used to determine the optimized control value of PRVs and to minimize the leakage rate in the WDS. Minimum required pressure was maintained at all nodes to avoid pressure deficiency at any node. Proposed methodology is applied in a benchmark WDS and after using PRVs, the average leakage rate was reduced by 6.05 l/s (20.64%), which is more favorable than the rate obtained with the existing techniques used for leakage control in the WDS. Compared with earlier studies, a lower number of PRVs was required for optimization, thus the proposed algorithm tends to provide a more cost-effective solution. In conclusion, the proposed algorithm leads to more favorable optimized localization and control of PRV with improved leakage reduction rate.


2009 ◽  
Vol 9 (4) ◽  
pp. 349-355 ◽  
Author(s):  
Y. Wang ◽  
X. J. Zhang ◽  
Z. B. Niu ◽  
C. Chen ◽  
P. P. Lu ◽  
...  

Iron release from scale brought about serious problems such as noticeable increases in turbidity and colour of the water in distribution system and taps. Field study and bench scale experiment on iron release from corrosion scale were carried out. In old cast iron pipe, higher iron release occurred with lower chlorine residual concentration, while lower iron release occurred with higher chlorine residual concentration. The reason lay in the structure of scale and the electro-chemical reactions occurring on the scale and in the bulk. The passivated-out-layer of scale was formed by ferric oxide. It could be broken down by reductive reaction in an atmosphere of low chlorine residual concentration. In contrast, the situation was quite different with new cast iron pipe, the age of which was only half a year. Iron release was considered as the product of the iron matrix and chlorine since the passivated-out-layer of scale had not formed yet. This iron release was consistent with chlorine residual concentration. It is suggested that maintaining a high chlorine residual concentration in a drinking water distribution system is beneficial to controlling both microorganism' regrowth and iron release.


2018 ◽  
Vol 17 (1) ◽  
pp. 1-24 ◽  
Author(s):  
Shakhawat Chowdhury

Abstract Desalinated seawater is the major source of drinking water in many countries. During desalination, several activities including pretreatment, desalination, stabilization, mixing, storage and distribution are performed. Few disinfectants are used during these activities to control the biofouling agents and microbiological regrowth. The reactions between the disinfectants and natural organic matter (NOM), bromide and iodide form disinfection by-products (DBPs) in product water. The product water is stabilized and mixed with treated freshwater (e.g., groundwater) to meet the domestic water demands. The DBPs in desalinated and blend water are an issue due to their possible cancer and non-cancer risks to humans. In this paper, formation and distribution of DBPs in different steps of desalination and water distribution systems prior to reaching the consumer tap were reviewed. The variability of DBPs among different sources and desalination processes was explained. The toxicities of DBPs were compared and the strategies to control DBPs in desalinated water were proposed. Several research directions were identified to achieve comprehensive control on DBPs in desalinated water, which are likely to protect humans from the adverse consequences of DBPs.


2010 ◽  
Vol 13 (3) ◽  
pp. 419-428 ◽  
Author(s):  
Qiang Xu ◽  
Qiuwen Chen ◽  
Weifeng Li

The water loss from a water distribution system is a serious problem for many cities, which incurs enormous economic and social loss. However, the economic and human resource costs to exactly locate the leakage are extraordinarily high. Thus, reliable and robust pipe failure models are demanded to assess a pipe's propensity to fail. Beijing City was selected as the case study area and the pipe failure data for 19 years (1987–2005) were analyzed. Three different kinds of methods were applied to build pipe failure models. First, a statistical model was built, which discovered that the ages of leakage pipes followed the Weibull distribution. Then, two other models were developed using genetic programming (GP) with different data pre-processing strategies. The three models were compared thereafter and the best model was applied to assess the criticality of all the pipe segments of the entire water supply network in Beijing City based on GIS data.


Water ◽  
2021 ◽  
Vol 13 (9) ◽  
pp. 1163
Author(s):  
Mengning Qiu ◽  
Avi Ostfeld

Steady-state demand-driven water distribution system (WDS) solution is the bedrock for much research conducted in the field related to WDSs. WDSs are modeled using the Darcy–Weisbach equation with the Swamee–Jain equation. However, the Swamee–Jain equation approximates the Colebrook–White equation, errors of which are within 1% for ϵ/D∈[10−6,10−2] and Re∈[5000,108]. A formulation is presented for the solution of WDSs using the Colebrook–White equation. The correctness and efficacy of the head formulation have been demonstrated by applying it to six WDSs with the number of pipes ranges from 454 to 157,044 and the number of nodes ranges from 443 to 150,630. The addition of a physically and fundamentally more accurate WDS solution method can improve the quality of the results achieved in both academic research and industrial application, such as contamination source identification, water hammer analysis, WDS network calibration, sensor placement, and least-cost design and operation of WDSs.


Water ◽  
2021 ◽  
Vol 13 (9) ◽  
pp. 1247
Author(s):  
Lydia Tsiami ◽  
Christos Makropoulos

Prompt detection of cyber–physical attacks (CPAs) on a water distribution system (WDS) is critical to avoid irreversible damage to the network infrastructure and disruption of water services. However, the complex interdependencies of the water network’s components make CPA detection challenging. To better capture the spatiotemporal dimensions of these interdependencies, we represented the WDS as a mathematical graph and approached the problem by utilizing graph neural networks. We presented an online, one-stage, prediction-based algorithm that implements the temporal graph convolutional network and makes use of the Mahalanobis distance. The algorithm exhibited strong detection performance and was capable of localizing the targeted network components for several benchmark attacks. We suggested that an important property of the proposed algorithm was its explainability, which allowed the extraction of useful information about how the model works and as such it is a step towards the creation of trustworthy AI algorithms for water applications. Additional insights into metrics commonly used to rank algorithm performance were also presented and discussed.


Water ◽  
2020 ◽  
Vol 12 (3) ◽  
pp. 695 ◽  
Author(s):  
Weiwei Bi ◽  
Yihui Xu ◽  
Hongyu Wang

Over the past few decades, various evolutionary algorithms (EAs) have been applied to the optimization design of water distribution systems (WDSs). An important research area is to compare the performance of these EAs, thereby offering guidance for the selection of the appropriate EAs for practical implementations. Such comparisons are mainly based on the final solution statistics and, hence, are unable to provide knowledge on how different EAs reach the final optimal solutions and why different EAs performed differently in identifying optimal solutions. To this end, this paper aims to compare the real-time searching behaviour of three widely used EAs, which are genetic algorithms (GAs), the differential evolution (DE) algorithm and the ant colony optimization (ACO). These three EAs are applied to five WDS benchmarking case studies with different scales and complexities, and a set of five metrics are used to measure their run-time searching quality and convergence properties. Results show that the run-time metrics can effectively reveal the underlying searching mechanisms associated with each EA, which significantly goes beyond the knowledge from the traditional end-of-run solution statistics. It is observed that the DE is able to identify better solutions if moderate and large computational budgets are allowed due to its great ability in maintaining the balance between the exploration and exploitation. However, if the computational resources are rather limited or the decision has to be made in a very short time (e.g., real-time WDS operation), the GA can be a good choice as it can always identify better solutions than the DE and ACO at the early searching stages. Based on the results, the ACO performs the worst for the five case study considered. The outcome of this study is the offer of guidance for the algorithm selection based on the available computation resources, as well as knowledge into the EA’s underlying searching behaviours.


1997 ◽  
Vol 36 (5) ◽  
pp. 317-324 ◽  
Author(s):  
M.J. Rodriguez ◽  
J.R. West ◽  
J. Powell ◽  
J.B. Sérodes

Increasingly, those who work in the field of drinking water have demonstrated an interest in developing models for evolution of water quality from the treatment plant to the consumer's tap. To date, most of the modelling efforts have been focused on residual chlorine as a key parameter of quality within distribution systems. This paper presents the application of a conventional approach, the first order model, and the application of an emergent modelling approach, an artificial neural network (ANN) model, to simulate residual chlorine in a Severn Trent Water Ltd (U.K.) distribution system. The application of the first order model depends on the adequate estimation of the chlorine decay coefficient and the travel time within the system. The success of an ANN model depends on the use of representative data about factors which affect chlorine evolution in the system. Results demonstrate that ANN has a promising capacity for learning the dynamics of chlorine decay. The development of an ANN appears to be justifiable for disinfection control purposes, in cases when parameter estimation within the first order model is imprecise or difficult to obtain.


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