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标题：Probabilistic characterisation of coastal storm-induced risks using Bayesian networks
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作者：Sanuy, Marc ; Jiménez, Jose A.
期刊名称：Natural Hazards and Earth System Sciences
电子版ISSN：2195-9269
出版年度：2021
卷号：21
期号：1
页码：219-238
DOI：10.5194/nhess-21-219-2021
语种：English
出版社：Copernicus Publications
摘要：A probabilistic estimation of hazards based on theresponse approach requires assessing large amounts of sourcecharacteristics, representing an entire storm climate. In addition, thecoast is a dynamic environment, and factors such as existing backgrounderosion trends require performing risk analyses under different scenarios.This work applies Bayesian networks (BNs) following thesource–pathway–receptor–consequence scheme aiming to perform aprobabilistic risk characterisation at the Tordera delta (NE Spain). One ofthe main differences of the developed BN framework is that it includes theentire storm climate (all recorded storm events, 179 in the study case) toretrieve the integrated and conditioned risk-oriented results atindividually identified receptors (about 4000 in the study case). Obtainedresults highlight the storm characteristics with higher probabilities toinduce given risk levels for inundation and erosion, as well as how these areexpected to change under given scenarios of shoreline retreat due tobackground erosion. As an example, storms with smaller waves and fromsecondary incoming direction will increase erosion and inundation risks atthe study area. The BNs also output probabilistic distributions of thedifferent risk levels conditioned to given distances to the beach innerlimit, allowing for the definition of probabilistic setbacks. Under currentconditions, high and moderate inundation risks, as well as direct exposure toerosion can be reduced with a small coastal setback (∼10 m),which needs to be increased up to 20–55 m to be efficient under futurescenarios (+20 years).