Gleeson, K. orcid.org/0000-0002-3767-3001, Husband, S. orcid.org/0000-0002-2771-1166, Gaffney, J. et al. (1 more author) (2023) Determining the spatio-temporal relationship between water quality monitors in drinking water distribution systems. In: IOP Conference Series: Earth and Environmental Science. 14th International Conference on Hydroinformatics, 04-08 Jul 2022, Bucharest, Romania. IOP Publishing , 012046.
Abstract
A novel method to both assess the strength of connectivity and determine hydraulic transit times between water quality monitors from time series data is reported. It was developed using a network of over 50 mobile multi-parameter sensors deployed for 18 months across a UK drinking water distribution system, and then validated using a network of 18 sensors from a different UK utility. Correlation coefficients are calculated at different time shifts for each possible sensor pair, with strength of connectivity represented by the highest correlation coefficient, and with the temporal lag of this highest correlation also designates the transit time. The results demonstrate the potential to derive valuable spatio-temporal information, with potential to increase understanding of system performance and connectivity. This information can be used to assist with further analytics such as tracking water quality events and improving hydraulic and disinfection residual decay modelling.
Metadata
Item Type: | Proceedings Paper |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2023 Published under licence by IOP Publishing Ltd. Content from this work may be used under the terms of the Creative Commons Attribution 3.0 licence (http://creativecommons.org/licenses/by/3.0). Any further distribution of this work must maintain attribution to the author(s) and the title of the work, journal citation and DOI. |
Dates: |
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Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Civil and Structural Engineering (Sheffield) |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 25 Jan 2023 16:37 |
Last Modified: | 25 Jan 2023 16:40 |
Status: | Published |
Publisher: | IOP Publishing |
Refereed: | Yes |
Identification Number: | 10.1088/1755-1315/1136/1/012046 |
Related URLs: | |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:195583 |
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