Identification of Contamination Potential Source (ICPS): A Topological Approach for the Optimal Recognition of Sensitive Nodes in a Water Distribution Network

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Abstract

The correct management of urban water networks have to be supported by monitoring and estimating water quality. The infrastructure maintenance status and the possibility of a prevention plan availability influence the potential risk of contamination. In this context, the Contamination Source Identification (CSI) models aim to identify the contamination source starting from the concentration values referring to the nodes. This paper proposes a methodology based on Dynamics of Network Pollution (DNP). The DNP approach, linked to the pollution matrix and the incidence matrix, allows a topological analysis on the network structure in order to identify the nodes and paths most sensitive to contamination, namely those that favor a more critical diffusion of the introduced contaminant. The procedure is proposed with the aim of optimally identifying the potential contamination points. By simulating the contamination of a synthetic network, using a bottom-up approach, an optimized procedure is defined to trace back to the chosen node as the most probable contamination source.

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Capano, G., Bonora, M. A., Carini, M., & Maiolo, M. (2020). Identification of Contamination Potential Source (ICPS): A Topological Approach for the Optimal Recognition of Sensitive Nodes in a Water Distribution Network. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 11973 LNCS, pp. 525–536). Springer. https://doi.org/10.1007/978-3-030-39081-5_45

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