Abstract
Designing a state-of-the-art online water quality monitoring system requires a comprehensive procedure for the selection of pertinent water quality parameters and available cost-effective and reliable sensors. Proper selection of pertinent contaminants/indicators for online monitoring ensures that the overall quality of the distributed water is not compromised and all regulations/guidelines are complied with fully. On the other hand, the selection of monitoring devices and sensors suitable for a typical online water quality monitoring system involves consideration of various factors including reliability, cost, response time, etc. In this paper, we illustrate the use of a multi-criteria decision analysis methodology based on an analytic hierarchy process to optimize the selection of indicator/contaminant sets and related water quality sensors as applied to drinking water distribution networks. A similar methodology could be used for most online monitoring applications in other areas. For the water distribution network application, we shortlisted 18 water quality indicators (WQI) from an initial list of 94 parameters. Similarly, from a comprehensive list of 71 potential water quality monitoring devices, nine were shortlisted for further analysis. Three of these nine monitoring devices were found to be suitable for monitoring 14 of the 18 shortlisted WQI. These three monitoring devices were found to be the best sensors because they demonstrated the ability to monitor 14 selected WQI simultaneously.
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Acknowledgments
The authors would like to take this opportunity to express their sincere gratitude and thanks to all the manufacturers and distributors who provided us with much needed information regarding their sensors and water quality monitors. The financial support from NSERC Strategic Project Grant is highly appreciated.
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Lee, A., Francisque, A., Najjaran, H. et al. Online monitoring of drinking water quality in a distribution network: a selection procedure for suitable water quality parameters and sensor devices. Int J Syst Assur Eng Manag 3, 323–337 (2012). https://doi.org/10.1007/s13198-012-0133-6
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DOI: https://doi.org/10.1007/s13198-012-0133-6