NDLI: A Bayesian vulnerability assessment tool for drinking water mains under extreme events

Content Provider	Springer Nature Link
Author	Paga, Alessandro Giorda, Raffaele Portoghese, Ivan Frati, Umberto Vurro, Michele
Copyright Year	2014
Abstract	Drinking water security is a life safety issue as an adequate supply of safe water is essential for economic, social and sanitary reasons. Damage to any element of a water system, as well as corruption of resource quality, may have significant effects on the population it serves and on all other dependent resources and activities. As well as an analysis of the reliability of water distribution systems in ordinary conditions, it is also crucial to assess system vulnerability in the event of natural disasters and of malicious or accidental anthropogenic acts. The present work summarizes the initial results of research activities that are underway with the intention of developing a vulnerability assessment methodology for drinking water infrastructures subject to hazardous events. The main aim of the work was therefore to provide decision makers with an effective operational tool which could support them mainly to increase risk awareness and preparedness and, possibly, to ease emergency management. The proposed tool is based on Bayesian Belief Networks (BBN), a probabilistic methodology which has demonstrated outstanding potential to integrate a range of sources of knowledge, a great flexibility and the ability to handle in a mathematically sound way uncertainty due to data scarcity and/or limited knowledge of the system to be managed. The tool was implemented to analyze the vulnerability of two of the most important water supply systems in the Apulia region (southern Italy) which have been damaged in the past by natural hazards. As well as being useful for testing and improving the predictive capabilities of the methodology and for possibly modifying its structure and features, the case studies have also helped to underline its strengths and weaknesses. Particularly, the experiences carried out demonstrated how the use of BBN was consistent with the lack of data reliability, quality and accessibility which are typical of complex infrastructures, such as the water distribution networks. The potential applications and future developments of the proposed tool have been also discussed accordingly.
Starting Page	2193
Ending Page	2227
Page Count	35
File Format	PDF
ISSN	0921030X
Journal	Natural Hazards
Volume Number	74
Issue Number	3
e-ISSN	15730840
Language	English
Publisher	Springer Netherlands
Publisher Date	2014-06-28
Publisher Place	Dordrecht
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Bayesian Belief Networks Drinking water supply Vulnerability assessment Decision Support System Physical hazards Natural Hazards Hydrogeology Geophysics/Geodesy Geotechnical Engineering & Applied Earth Sciences Civil Engineering Environmental Management
Content Type	Text
Resource Type	Article
Subject	Atmospheric Science Water Science and Technology

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