Gleeson, K. orcid.org/0000-0002-3767-3001, Husband, S. orcid.org/0000-0002-2771-1166, Gaffney, J. et al. (1 more author) (2024) Algorithms to mimic human interpretation of turbidity events from drinking water distribution systems. Journal of Hydroinformatics, 26 (1). pp. 143-161. ISSN 1464-7141
Abstract
Deriving insight from the increasing volume of water quality time series data from drinking water distribution systems is complex and is usually situation- and individual-specific. This research used crowd-sourcing exercises involving groups of domain experts to identify features of interest within turbidity time series data from operational systems. The resulting labels provide insight and a novel benchmark against which algorithmic approaches to mimic the human interpretation could be evaluated. Reflection of the results of the labelling exercises resulted in the proposal of a turbidity event scale consisting of advisory <2 NTU, alert 2 < NTU < 4, and alarm >4 NTU levels to inform utility response. Automation, for scale up, was designed to enable event detection within these categories, with the <2NTU category being the most challenging. A time-based averaging approach, based on data at the same time of day, was found to be most effective for identifying these advisory events. The automation of event detection and categorisation presented here provides the opportunity to gain actionable insight to safeguard drinking water quality from ageing infrastructure.
Metadata
Item Type: | Article |
---|---|
Authors/Creators: |
|
Copyright, Publisher and Additional Information: | © 2023 The Authors. This is an Open Access article distributed under the terms of the Creative Commons Attribution Licence (CC BY 4.0), which permits copying, adaptation and redistribution, provided the original work is properly cited (http://creativecommons.org/licenses/by/4.0/). |
Keywords: | discolouration; drinking water distribution systems; drinking water quality; event detection; turbidity; water quality time series |
Dates: |
|
Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Civil and Structural Engineering (Sheffield) |
Funding Information: | Funder Grant number Engineering and Physical Sciences Research Council EP/S023666/1 |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 15 Jan 2024 12:20 |
Last Modified: | 01 Nov 2024 14:18 |
Status: | Published |
Publisher: | IWA Publishing |
Refereed: | Yes |
Identification Number: | 10.2166/hydro.2023.159 |
Related URLs: | |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:207541 |