Contamination event diagnosis in drinking water networks: A review

Ηλιάδης, Δημήτριος Γ.; Vrachimis, Stelios G.; Moghaddam, Alireza; Tzortzis, Ioannis; Polycarpou, Marios M.

doi:10.1016/j.arcontrol.2023.03.011

Cited by 13 publications

(1 citation statement)

References 236 publications

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“…Water quality within a water supply network is influenced by a range of factors, each capable of causing alterations and potential risks. These factors are pivotal to comprehend and manage in order to ensure a dependable and safe water supply [19][20][21][22][23][24][25]. The susceptibility to corrosion of the selected pipe material can significantly affect water quality.…”

Section: Introductionmentioning

confidence: 99%

The Failure Risk Analysis of the Water Supply Network

Tchórzewska-Cieślak,

Pietrucha-Urbanik,

Piegdoń

2023

Water

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The primary objective of this work is to introduce a novel approach that modifies the method for analyzing and assessing the risk of water supply network failure. The approach aligns with recommendations from the World Health Organization and the European Union regarding the reliability and safety of water supply to consumers. The presented method for assessing the risk in the water distribution subsystem was based on the vulnerability identifying method (VIM) and involves the determination of the vulnerability index (VI). The VIM vulnerability factors considered encompass the failure rate, chemical stability of water, and issues related to water corrosion properties in water distribution subsystems. The obtained risk assessment includes parameters such as the probability of hazard occurrence, the consequences of these hazards, and vulnerability to them. This concept was evaluated using real operational data from the water distribution subsystem. The estimated risk level, under the given operating conditions, indicates its acceptability.

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Section: Introductionmentioning

confidence: 99%

The Failure Risk Analysis of the Water Supply Network

Tchórzewska-Cieślak,

Pietrucha-Urbanik,

Piegdoń

2023

Water

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Challenges, Methods, Data–A Survey of Machine Learning in Water Distribution Networks

Vaquet,

Hinder,

Artelt

et al. 2024

Lecture Notes in Computer Science

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Research on methods for planning and controlling water distribution networks gains increasing relevance as the availability of drinking water will decrease as a consequence of climate change. So far, the majority of approaches is based on hydraulics and engineering expertise. However, with the increasing availability of sensors, machine learning techniques constitute a promising tool. This work presents the main tasks in water distribution networks, discusses how they relate to machine learning and analyses how the particularities of the domain pose challenges to and can be leveraged by machine learning approaches. Besides, it provides a technical toolkit by presenting evaluation benchmarks and a structured survey of the exemplary task of leakage detection and localization.

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