Abstract
Accidental contamination and malicious attacks can degrade the water quality in water distribution networks and threat the human health. Therefore, a rapid detection of water contamination is required to prevent waterborne diseases. The use of water quality sensors allows a real-time monitoring of several physical and chemical parameters. The aim of this paper is to combine the smart monitoring with the risk assessment approach to ensure early detection of water contamination. Within the European Project “SmartWater4Europe,” S::CAN sensor was implemented, on the water supply system of the Campus of Lille University, France, since 2016. The campus is a representative field study with 15 km of water distribution network. In this paper, Turbidity and Chlorine, recorded online by S::CAN, were analyzed continuously to define the risk assessment parameters (the severity of consequences and the likelihood of an event). The application of the proposed approach indicates that the magnitude of deviation from thresholds limits and the duration of events are the two essential parameters to be considered in risk assessment approach. The paper shows that this new approach provides promising perspective for the early detection of the water contamination. It allows to identify the risk level and the priority required in real time, without resorting laboratory analyses.
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Saab, C., Shahrour, I. & Hage Chehade, F. Risk Assessment of Water Accidental Contamination Using Smart Water Quality Monitoring. Expo Health 12, 281–293 (2020). https://doi.org/10.1007/s12403-019-00311-1
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DOI: https://doi.org/10.1007/s12403-019-00311-1