A Methodology for a Comprehensive Probabilistic Tsunami Hazard Assessment: Multiple Sources and Short-Term Interactions

Grezio, Anita; Tonini, Roberto; Sandri, Laura; Pierdominici, S.; Selva, Jacopo

doi:10.3390/jmse3010023

Cited by 17 publications

(12 citation statements)

References 78 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Also, given a set Y of the observed data the corresponding probability density distribution is indicated by [Y ]. The Ba es' theorem updates P in light of the observed data (Gelman et al, 2013;Grezio et al, 2015;Marzocchi et al, 2008):…”

Section: Bayesian Pthamentioning

confidence: 99%

Multisource Bayesian Probabilistic Tsunami Hazard Analysis for the Gulf of Naples (Italy)

et al. 2020

Self Cite

View full text Add to dashboard Cite

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 SourceModule 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 PropagationModule the tsunami waves are simulated and propagated in the deep sea by a numerical model that solves the shallow water equations. In the ImpactModule the tsunami wave heights are estimated at the coast using the Green's amplification law. The selected tsunami intensity is the wave height. In the BayesianModule 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 prior probability density functions are integrated with the likelihood derived from the historical information based on past tsunami data. The posterior probability density functions are evaluated to produce the hazard curves in selected sites of the Gulf of Naples.

show abstract

Section: Bayesian Pthamentioning

confidence: 99%

Multisource Bayesian Probabilistic Tsunami Hazard Analysis for the Gulf of Naples (Italy)

et al. 2020

Self Cite

View full text Add to dashboard Cite

show abstract

“…Determining rates of occurrence tends to be more problematic for nonearthquake sources compared with earthquake sources because they often lack any clear time dependence, and source mechanisms can be strongly nonlinear. Probabilistic hazard assessments of tsunamis from submarine mass failures, some including the potential for earthquake triggering, have been undertaken for the U.S. Atlantic (Geist & Parsons, 2010;Grilli et al, 2009;Lynett & Martinez, 2012;Maretzki et al, 2007;ten Brink et al, 2009ten Brink et al, , 2014 and Pacific margins (Watts, 2004), the Canadian coast (Leonard et al, 2014), New Zealand coasts (Lane, Mountjoy, Power, & Mueller, 2016), and the Tyrrhenian Sea (e.g., Grezio et al, 2012Grezio et al, , 2015. Probabilistic analysis of meteotsunamis were introduced by and Šepić, Medugorac, et al (2016) for the northeast U.S. coastlines and the Balearic Islands, Spain, respectively.…”

Section: Introductionmentioning

confidence: 99%

Probabilistic Tsunami Hazard Analysis: Multiple Sources and Global Applications

Grezio

Babeyko²,

Baptista

et al. 2017

Reviews of Geophysics

Self Cite

211

165

View full text Add to dashboard Cite

Applying probabilistic methods to infrequent but devastating natural events is intrinsically challenging. For tsunami analyses, a suite of geophysical assessments should be in principle evaluated because of the different causes generating tsunamis (earthquakes, landslides, volcanic activity, meteorological events, and asteroid impacts) with varying mean recurrence rates. Probabilistic Tsunami Hazard Analyses (PTHAs) are conducted in different areas of the world at global, regional, and local scales with the aim of understanding tsunami hazard to inform tsunami risk reduction activities. PTHAs enhance knowledge of the potential tsunamigenic threat by estimating the probability of exceeding specific levels of tsunami intensity metrics (e.g., run‐up or maximum inundation heights) within a certain period of time (exposure time) at given locations (target sites); these estimates can be summarized in hazard maps or hazard curves. This discussion presents a broad overview of PTHA, including (i) sources and mechanisms of tsunami generation, emphasizing the variety and complexity of the tsunami sources and their generation mechanisms, (ii) developments in modeling the propagation and impact of tsunami waves, and (iii) statistical procedures for tsunami hazard estimates that include the associated epistemic and aleatoric uncertainties. Key elements in understanding the potential tsunami hazard are discussed, in light of the rapid development of PTHA methods during the last decade and the globally distributed applications, including the importance of considering multiple sources, their relative intensities, probabilities of occurrence, and uncertainties in an integrated and consistent probabilistic framework.

show abstract

“…In this area, the hazard due to crustal seismicity represents an important component of the total S-PTHA (Sørensen et al 2012;Selva et al 2016). One should eventually consider also hazard from non-seismic sources (e.g., Tonini et al 2011;Grezio et al 2012Grezio et al , 2015Urlaub et al 2018;Paris et al 2019). As a further simplification in comparison to the TSUMAPS-NEAM model, we consider a narrower range of alternative models to describe the epistemic uncertainty, both as far as the seismicity rates and the inundation models are concerned.…”

Section: Introductionmentioning

confidence: 99%

Effect of Shallow Slip Amplification Uncertainty on Probabilistic Tsunami Hazard Analysis in Subduction Zones: Use of Long-Term Balanced Stochastic Slip Models

Scala

Lorito

Romano

et al. 2019

Pure Appl. Geophys.

View full text Add to dashboard Cite

The complexity of coseismic slip distributions influences the tsunami hazard posed by local and, to a certain extent, distant tsunami sources. Large slip concentrated in shallow patches was observed in recent tsunamigenic earthquakes, possibly due to dynamic amplification near the free surface, variable frictional conditions or other factors. We propose a method for incorporating enhanced shallow slip for subduction earthquakes while preventing systematic slip excess at shallow depths over one or more seismic cycles. The method uses the classic k-2 stochastic slip distributions, augmented by shallow slip amplification. It is necessary for deep events with lower slip to occur more often than shallow ones with amplified slip to balance the long-term cumulative slip. We evaluate the impact of this approach on tsunami hazard in the central and eastern Mediterranean Sea adopting a realistic 3D geometry for three subduction zones, by using it to model * 150,000 earthquakes with M w from 6.0 to 9.0. We combine earthquake rates, depth-dependent slip distributions, tsunami modeling, and epistemic uncertainty through an ensemble modeling technique. We found that the mean hazard curves obtained with our method show enhanced probabilities for larger inundation heights as compared to the curves derived from depthindependent slip distributions. Our approach is completely general and can be applied to any subduction zone in the world.

show abstract

A Methodology for a Comprehensive Probabilistic Tsunami Hazard Assessment: Multiple Sources and Short-Term Interactions

Cited by 17 publications

References 78 publications

Multisource Bayesian Probabilistic Tsunami Hazard Analysis for the Gulf of Naples (Italy)

Multisource Bayesian Probabilistic Tsunami Hazard Analysis for the Gulf of Naples (Italy)

Probabilistic Tsunami Hazard Analysis: Multiple Sources and Global Applications

Effect of Shallow Slip Amplification Uncertainty on Probabilistic Tsunami Hazard Analysis in Subduction Zones: Use of Long-Term Balanced Stochastic Slip Models

Contact Info

Product

Resources

About