Use of Continuous Recording Water-Quality Monitoring Equipment for Conducting Water-Distribution System Tracer Tests: The Good, the Bad and the Ugly

2005 ◽  
Author(s):  
M. L. Maslia ◽  
J. B. Sautner ◽  
C. Valenzuela ◽  
W. M. Grayman ◽  
M. M. Aral ◽  
...  
Keyword(s):  
Water Quality ◽  
Distribution System ◽  
Water Distribution ◽  
Water Distribution System ◽  
Tracer Tests ◽  
Water Quality Monitoring ◽  
Quality Monitoring ◽  
Continuous Recording ◽  
Monitoring Equipment

scholarly journals Water Quality Monitoring Sensors Optimum Location in a Metropolitan Supply Network

2020 ◽  
Vol 71 (1) ◽  
pp. 327-334
Author(s):  
Albert Titus Constantin ◽  
Gheorghe I. Lazar ◽  
Serban-Vlad Nicoara
Keyword(s):  
Water Quality ◽  
Distribution System ◽  
Water Distribution ◽  
Water Distribution System ◽  
Water Quality Monitoring ◽  
Quality Monitoring ◽  
Supply Network ◽  
Optimum Location ◽  
Software Toolkit ◽  
Water Quality Sensors

The discrete numerical model developed by the help of TEVA-SPOT specialized software toolkit serves to a subsequent analysis that looks to estimate the water distribution system vulnerability in case of a contaminant agent release. The optimum location of the water quality sensors attached to a number of joints in the Timisoara (Romania) metropolitan water supply network can be reached in order to warn the company management and competent authorities and so to reduce the contamination effects upon the consumers.

scholarly journals Analyzing multi-variate water quality signals for water quality monitoring station placement in water distribution systems

2018 ◽  
Vol 20 (6) ◽  
pp. 1323-1342 ◽  
Author(s):  
Nathan Sankary ◽  
Avi Ostfeld
Keyword(s):  
Water Quality ◽  
Distribution System ◽  
False Positive ◽  
Water Distribution ◽  
Water Distribution System ◽  
Water Quality Monitoring ◽  
Quality Monitoring ◽  
Quality Signals ◽  
Risk Of Exposure ◽  
Monitoring Stations

Abstract Placing fixed water quality monitoring stations in a water distribution system can greatly improve the security of the system via prompt detection of poor water quality. In the event that a harmful substance is injected into a water distribution system, large populations can be put at risk of exposure to the contaminant. Promptly detecting the presence of a contaminant will reduce the number of people put at risk of exposure. However, to protect against a wide variety of possible contaminants, a water quality monitoring station will need to identify contamination via recognition of anomalous changes in a suite of surrogate water quality indicators (chlorine, pH, etc.). This work attempts to place water quality monitoring stations within the water distribution at locations that best detect contamination events via surrogate water quality signals. Networks of water quality monitoring stations are designed to minimize the population affected prior to contamination event detection, and simultaneously minimize the expected number of false positive detections, under uncertain water quality conditions. Solutions generated in this study are compared to solutions designed via classical detection methods. Results show the sensor networks designed without consideration to detection via surrogate water quality parameters have higher false positive detection rates.

Identifying water quality monitoring stations in a water supply system

2014 ◽  
Vol 14 (6) ◽  
pp. 1076-1086 ◽  
Author(s):  
M. Al-Zahrani ◽  
K. Moied
Keyword(s):  
Water Quality ◽  
Water Supply ◽  
Distribution System ◽  
Water Distribution ◽  
Water Quality Monitoring ◽  
Quality Monitoring ◽  
Multiple Sources ◽  
Water Age ◽  
Average Water ◽  
Monitoring Stations

Despite good quality assurance and conformance to the standards at the treatment plants, water quality could vary considerably within the distribution network. As water flows through the pipe network, its quality undergoes various transformations due to many factors such as the properties of the finished water, pipe materials, water temperature, water age and low level of disinfectant residuals. Sampling and monitoring of water quality is, therefore, important to ensure that clean and safe water is transported to the consumers. In this paper, a model based on genetic algorithms and fuzzy logic was developed to identify locations of water quality monitoring stations in a water distribution system. While identifying the monitoring locations, multiple sources of water supply, water age and constituent concentration were considered. The developed model was applied on a hypothetical network and results indicate that monitoring stations are proposed at locations with maximum coverage of water supply within the network and maximum violation for average water age and constituent concentrations.

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