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Article

The Management of Na-Tech Risk Using Bayesian Network

Department of Engineering, University of Messina, Contrada di Dio, 98166 Messina, Italy
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Author to whom correspondence should be addressed.
Academic Editor: George Arhonditsis
Water 2021, 13(14), 1966; https://doi.org/10.3390/w13141966
Received: 18 June 2021 / Revised: 14 July 2021 / Accepted: 15 July 2021 / Published: 17 July 2021
(This article belongs to the Section Hydrology)
In the last decades, the frequency and severity of Natural-Technological events (i.e., industrial accidents triggered by natural phenomena or Na-Techs) increased. These could be more severe than simple technological accidents because the natural phenomenon could cause the prevention/mitigation/emergency systems fail. The dynamic assessment of the risk associated with these events is essential for a more effective prevention and mitigation of the consequences and emergency preparation. The main goal of this study is the development of a fast and dynamic tool for the risk manager. An approach supporting the management of the consequence is presented. It is based on the definition of a risk-related index, presented in the form of a discrete variable that combines frequency and magnitude of the events and other factors contributing to the worsening of Na-Tech. A properly designed Geographical Information System (GIS) allows the collection and processing of territorial information with the aim to create new data contributing to the quantification of the Na-Tech risk index. A Bayesian network has been built which efficiently lends in including within the model multiple elements with a direct or indirect impact on the distribution of risk levels. By means of this approach, a dynamic updating of the risk index is made. The proposed approach has been applied to an Italian case-study. View Full-Text
Keywords: natural-technological events; hazardous material; chemical industry; dynamic risk assessment; risk management; flood natural-technological events; hazardous material; chemical industry; dynamic risk assessment; risk management; flood
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MDPI and ACS Style

Ancione, G.; Milazzo, M.F. The Management of Na-Tech Risk Using Bayesian Network. Water 2021, 13, 1966. https://doi.org/10.3390/w13141966

AMA Style

Ancione G, Milazzo MF. The Management of Na-Tech Risk Using Bayesian Network. Water. 2021; 13(14):1966. https://doi.org/10.3390/w13141966

Chicago/Turabian Style

Ancione, Giuseppa, and Maria F. Milazzo 2021. "The Management of Na-Tech Risk Using Bayesian Network" Water 13, no. 14: 1966. https://doi.org/10.3390/w13141966

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