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Water Distribution Networks (WDNs) are critical infrastructures that are exposed to deliberate or accidental chemical, biological or radioactive contamination which need to be detected in due time. However, until now, no monitoring system is capable of protecting a WDN in real time. Powerful online sensor systems are currently developed and the prototypes are able to detect a small change in water quality. In the immediate future, water service utilities will install their networks with water quantity and water quality sensors. For taking appropriate decisions and countermeasures, WDN operators will need to dispose of: 1) a fast and reliable detection of abnormal events in the WDNs; 2) reliable online models both for the hydraulics and water quality predictions; 3) methods for contaminant source identification backtracking from the data history. Actually, in general none of these issues (1) – (3) are available at the water suppliers. Consequently, the main objective of the project SMaRT-OnlineWDN is the development of an online security management toolkit for WDNs that is based on sensor measurements of water quality as well as water quantity. Its main innovations are the detection of abnormal events with a binary classifier of high accuracy and the generation of real-time, reliable (i) flow and pressure predictions, (ii) water quality indicator predictions of the whole water network. Detailed information regarding contamination sources (localization and intensity) will be explored by means of the online running model, which is automatically calibrated to the measured sensor data. Its field of application ranges from the detection of deliberate contamination including source identification and decision support for effective countermeasures to improved operation and control of a WDN under normal and abnormal conditions (dual benefit).In this project, the technical research work is completed with a sociological, economical and management analysis.


Session S1-05, Special Sympoisum: Real-time Modeling Projects and Case Studies



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