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Multisource Bayesian Probabilistic Tsunami Hazard Analysis for the Gulf of Naples (Italy)
Author(s) -
Grezio Anita,
Cinti Francesca Romana,
Costa Antonio,
Faenza Licia,
Perfetti Paolo,
Pierdominici Simona,
Pondrelli Silvia,
Sandri Laura,
Tierz Pablo,
Tonini Roberto,
Selva Jacopo
Publication year - 2020
Publication title -
journal of geophysical research: oceans
Language(s) - English
Resource type - Journals
eISSN - 2169-9291
pISSN - 2169-9275
DOI - 10.1029/2019jc015373
Subject(s) - seismology , geology , submarine , bathymetry , probabilistic logic , hazard , hazard analysis , volcano , bayesian probability , seismic hazard , pyroclastic rock , submarine landslide , landslide , oceanography , statistics , engineering , chemistry , mathematics , organic chemistry , aerospace engineering
A methodology for a comprehensive probabilistic tsunami hazard analysis is presented for the major sources of tsunamis (seismic events, landslides, and volcanic activity) and preliminarily applied in the Gulf of Naples (Italy). The methodology uses both a modular procedure to evaluate the tsunami hazard and a Bayesian analysis to include the historical information of the past tsunami events. In the S o u r c e M o d u l e the submarine earthquakes and the submarine mass failures are initially identified in a gridded domain and defined by a set of parameters, producing the sea floor deformations and the corresponding initial tsunami waves. Differently volcanic tsunamis generate sea surface waves caused by pyroclastic density currents from Somma‐Vesuvius. In the P r o p a g a t i o n M o d u l e the tsunami waves are simulated and propagated in the deep sea by a numerical model that solves the shallow water equations. In the I m p a c t M o d u l e the tsunami wave heights are estimated at the coast using the G r e e n 's amplification law. The selected tsunami intensity is the wave height. In the B a y e s i a n M o d u l e the probabilistic tsunami analysis computes the long‐term comprehensive Bayesian probabilistic tsunami hazard analysis. In the prior analysis the probabilities from the scenarios in which the tsunami parameter overcomes the selected threshold levels are combined with the spatial, temporal, and frequency‐size probabilities of occurrence of the tsunamigenic sources. The p r i o r probability density functions are integrated with the l i k e l i h o o d derived from the historical information based on past tsunami data. The p o s t e r i o r probability density functions are evaluated to produce the hazard curves in selected sites of the Gulf of Naples.

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