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Drinking Water Engineering and Science An interactive open-access journal
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Volume 10, issue 2
Drink. Water Eng. Sci., 10, 53–59, 2017
https://doi.org/10.5194/dwes-10-53-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.

Special issue: Computing and Control for the Water Industry, CCWI 2016

Drink. Water Eng. Sci., 10, 53–59, 2017
https://doi.org/10.5194/dwes-10-53-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.

Technical note 17 Jul 2017

Technical note | 17 Jul 2017

Technical note: Efficient online source identification algorithm for integration within a contamination event management system

Jochen Deuerlein, Lea Meyer-Harries, and Nicolai Guth Jochen Deuerlein et al.
  • 3S Consult GmbH, 76137 Karlsruhe, Germany

Abstract. Drinking water distribution networks are part of critical infrastructures and are exposed to a number of different risks. One of them is the risk of unintended or deliberate contamination of the drinking water within the pipe network. Over the past decade research has focused on the development of new sensors that are able to detect malicious substances in the network and early warning systems for contamination. In addition to the optimal placement of sensors, the automatic identification of the source of a contamination is an important component of an early warning and event management system for security enhancement of water supply networks. Many publications deal with the algorithmic development; however, only little information exists about the integration within a comprehensive real-time event detection and management system. In the following the analytical solution and the software implementation of a real-time source identification module and its integration within a web-based event management system are described. The development was part of the SAFEWATER project, which was funded under FP 7 of the European Commission.

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