Increase in anthropogenic antibiotic resistance markers in water supplied by overhead tank based-water distribution system

Author(s):  
Deepika Bhaskar ◽  
Gargi Singh

Overhead tank (OHT)-based gravity-fed water distribution systems are popular in many low and middle-income countries; yet, are poorly characterized despite being notorious for water quality deterioration. We investigated potential for...

2015 ◽  
Vol 42 (4) ◽  
pp. 250-258 ◽  
Author(s):  
Megan J. Liu ◽  
Stephen Craik ◽  
David Z. Zhu

Predicting disinfectant concentrations in water distribution systems using water quality models requires the input of the wall decay coefficient of the disinfectant. In this study, field water sampling data was integrated with network hydraulic and water quality model simulations of a section of the municipal water distribution system in the City of Edmonton, composed of predominantly cast iron piping, to determine a wall decay coefficient for combined chlorine (chloramine). Unique combined chlorine wall decay coefficients that provided the best fit of model-predicted chlorine concentrations to the field data were determined at two temperatures. Using the determined wall decay coefficients, the water quality model can be used to predict combined chlorine concentrations.


Water ◽  
2019 ◽  
Vol 11 (3) ◽  
pp. 567 ◽  
Author(s):  
Kegong Diao ◽  
Robert Sitzenfrei ◽  
Wolfgang Rauch

Resilient water distribution systems (WDSs) need to minimize the level of service failure in terms of magnitude and duration over its design life when subject to exceptional conditions. This requires WDS design to consider scenarios as close as possible to real conditions of the WDS to avoid any unexpected level of service failure in future operation (e.g., insufficient pressure, much higher operational cost, water quality issues, etc.). Thus, this research aims at exploring the impacts of design flow scenarios (i.e., spatial-variant demand patterns) on water distribution system design and operation. WDSs are traditionally designed by using a uniform demand pattern for the whole system. Nevertheless, in reality, the patterns are highly related to the number of consumers, service areas, and the duration of peak flows. Thus, water distribution systems are comprised of distribution blocks (communities) organized in a hierarchical structure. As each community may be significantly different from the others in scale and water use, the WDSs have spatially variable demand patterns. Hence, there might be considerable variability of real flow patterns for different parts of the system. Consequently, the system operation might not reach the expected performance determined during the design stage, since all corresponding facilities are commonly tailor-made to serve the design flow scenario instead of the real situation. To quantify the impacts, WDSs’ performances under both uniform and spatial distributed patterns are compared based on case studies. The corresponding impacts on system performances are then quantified based on three major metrics; i.e., capital cost, energy cost, and water quality. This study exemplifies that designing a WDS using spatial distributed demand patterns might result in decreased life-cycle cost (i.e., lower capital cost and nearly the same pump operating cost) and longer water ages. The outcomes of this study provide valuable information regarding design and operation of water supply infrastructures; e.g., assisting the optimal design.


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.


2004 ◽  
Vol 2 (3) ◽  
pp. 137-156 ◽  
Author(s):  
M. M. Aral ◽  
J. Guan ◽  
M. L. Maslia ◽  
J. B. Sautner ◽  
R. E. Gillig ◽  
...  

In a recently completed case-control epidemiological study, the New Jersey Department of Health and Senior Services (NJDHSS) with support from the Agency for Toxic Substances and Disease Registry (ATSDR) documented an association between prenatal exposure to a specific contaminated community water source and leukaemia in female children. An important and necessary step in the epidemiological study was the reconstruction of the historical water supply strategy of the water distribution system serving the Dover Township area, New Jersey. The sensitivity of solutions to: (1) pressure and pattern factor constraints, (2) allowable operational extremes of water levels in the storage tanks, and (3) the non-uniqueness of the water supply solution are analysed in detail. The computational results show that the proposed approach yields satisfactory results for the complete set of monthly simulations and sensitivity analyses, providing a consistent approach for identifying the historical water supply strategy of the water distribution system. Sensitivity analyses indicated that the alternative strategy obtained from the revised objective function and the variation of constraints did not yield significantly different water supply characteristics. The overall analysis demonstrates that the progressive optimality genetic algorithm (POGA) developed to solve the optimization problem is an effective and efficient algorithm for the reconstruction of water supply strategies in water distribution systems.


2012 ◽  
Vol 12 (5) ◽  
pp. 580-587 ◽  
Author(s):  
Stephen Mounce ◽  
John Machell ◽  
Joby Boxall

Safe, clean drinking water is a foundation of society and water quality monitoring can contribute to ensuring this. A case study application of the CANARY software to historic data from a UK drinking water distribution system is described. Sensitivity studies explored appropriate choice of algorithmic parameter settings for a baseline site, performance was evaluated with artificial events and the system then transferred to all sites. Results are presented for analysis of nine water quality sensors measuring six parameters and deployed in three connected district meter areas (DMAs), fed from a single water source (service reservoir), for a 1 year period and evaluated using comprehensive water utility records with 86% of event clusters successfully correlated to causes (spatially limited to DMA level). False negatives, defined by temporal clusters of water quality complaints in the pilot area not corresponding to detections, were only approximately 25%. It was demonstrated that the software could be configured and applied retrospectively (with potential for future near real time application) to detect various water quality event types (with a wider remit than contamination alone) for further interpretation.


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