An approach for estimating the largest probable tsunami from far-field subduction zone earthquakes

Kalligeris, Nikos; Montoya, Luis; Ayça, Aykut; Lynett, Patrick

doi:10.1007/s11069-017-2961-9

Cited by 7 publications

(5 citation statements)

References 49 publications

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“…This is significant because PTHAs often employ FAUS-like uniform-slip scenarios with magnitude-dependent length and width based on a scaling relation (e.g. Løvholt et al 2014;Roshan et al 2016;Davies et al 2017;Kalligeris et al 2017). In our study some historical tsunamis were poorly represented with the FAUS approach, and it predicted significantly lower tsunami hazard in Australia than the other approaches.…”

Section: Discussionmentioning

confidence: 83%

“…In practice the rigidity of subduction zones is not very well constrained (Bilek and Lay 1999;Geist and Bilek 2001), but tsunami hazard studies often assume constant l ' 3 À 6 Â 10 10 Pa (e.g. Butler et al 2017;Fukutani et al 2018;Kalligeris et al 2017). Despite this common practice, the use of depth-varying l (with low near-trench values) appears necessary to simulate the large tsunamis observed historically following shallow 'tsunami-earthquake' events (e.g.…”

Section: Introductionmentioning

confidence: 99%

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Sensitivity of Probabilistic Tsunami Hazard Assessment to Far-Field Earthquake Slip Complexity and Rigidity Depth-Dependence: Case Study of Australia

Davies

Griffin

2019

Pure Appl. Geophys.

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Probabilistic Tsunami Hazard Assessment (PTHA) often proceeds by constructing a suite of hypothetical earthquake scenarios, and modelling their tsunamis and occurrence-rates. Both tsunami and occurrence-rate models are affected by the representation of earthquake slip and rigidity, but the overall importance of these factors for far-field PTHA is unclear. We study the sensitivity of an Australia-wide PTHA to six different far-field earthquake scenario representations, including two rigidity models (constant and depth-varying) combined with three slip models: fixed-areauniform-slip (with rupture area deterministically related to magnitude); variable-area-uniform-slip; and spatially heterogeneousslip. Earthquake-tsunami scenarios are tested by comparison with DART-buoy tsunami observations, demonstrating biases in some slip models. Scenario occurrence-rates are modelled using Bayesian techniques to account for uncertainties in seismic coupling, maximum-magnitudes and Gutenberg-Richter b-values. The approach maintains reasonable consistency with the historical earthquake record and spatially variable plate convergence rates for all slip/rigidity model combinations, and facilitates partial correction of model-specific biases (identified via DART-buoy testing). The modelled magnitude exceedance-rates are tested by comparison with rates derived from long-term historical and paleoseismic data and alternative moment-conservation techniques, demonstrating the robustness of our approach. The tsunami hazard offshore of Australia is found to be insensitive to the choice of rigidity model, but significantly affected by the choice of slip model. The fixed-area-uniform-slip model produces lower hazard than the other slip models. Bias adjustment of the variable-areauniform-slip model produces a strong preference for 'compact' scenarios, which compensates for a lack of slip heterogeneity. Thus, both heterogeneous-slip and variable-area-uniform-slip models induce similar far-field tsunami hazard.

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Section: Discussionmentioning

confidence: 83%

Section: Introductionmentioning

confidence: 99%

Sensitivity of Probabilistic Tsunami Hazard Assessment to Far-Field Earthquake Slip Complexity and Rigidity Depth-Dependence: Case Study of Australia

Davies

Griffin

2019

Pure Appl. Geophys.

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“…However the earthquake history is far too short to preclude the possibility of earthquakes much larger than historically observed (McCaffrey, 2008;Zöller, 2013;Rong et al, 2014;Zöller, 2017). Such events have been suggested on the basis of paleotsunami evidence (Power et al, 2012;Goff et al, 2020) and seem plausible given the fault geometry (McCaffrey, 2008;Kalligeris et al, 2017;Davies et al, 2017;Plescia & Hayes, 2020). As a result there is much uncertainty as to the potential for large earthquakes on the Kermadec-Tonga trench (Berryman et al, 2015;UNESCO/IOC, 2020).…”

Section: Study Site and Offshore Pthamentioning

confidence: 99%

From offshore to onshore probabilistic tsunami hazard assessment via efficient Monte-Carlo sampling

Davies¹,

Weber²,

Wilson³

et al. 2022

Preprint

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Offshore Probabilistic Tsunami Hazard Assessments (offshore PTHAs) provide large-scale analyses of earthquake-tsunami frequencies and uncertainties in the deep ocean, but do not provide high-resolution onshore tsunami hazard information as required for many risk-management applications. To understand the implications of an offshore PTHA for the onshore hazard at any site, in principle the tsunami inundation should be simulated locally for every scenario in the offshore PTHA. In practice this is rarely feasible due to the computational expense of inundation models, and the large number of scenarios in offshore PTHAs. Monte-Carlo methods offer a practical and rigorous alternative for approximating the onshore hazard, using a random subset of scenarios. The resulting Monte-Carlo errors can be quantified and controlled, enabling high-resolution onshore PTHAs to be implemented at a fraction of the computational cost. This study develops novel Monte-Carlo sampling approaches for offshore-to-onshore PTHA. Modelled offshore PTHA wave heights are used to preferentially sample scenarios that have large offshore waves near an onshore site of interest. By appropriately weighting the scenarios, the Monte-Carlo errors are reduced without introducing any bias. The techniques are applied to a high-resolution onshore PTHA for the island of Tongatapu in Tonga. In this region, the new approaches lead to efficiency improvements equivalent to using 4-18 times more random scenarios, as compared with stratified-sampling by magnitude, which is commonly used for onshore PTHA. The greatest efficiency improvements are for rare, large tsunamis, and for calculations that represent epistemic uncertainties in the tsunami hazard. To facilitate the control of Monte-Carlo errors in practical applications, this study also provides analytical techniques for estimating the errors both before and after inundation simulations are conducted. Before inundation simulation, this enables a proposed Monte-Carlo sampling scheme to be checked, and potentially improved, at minimal computational cost. After inundation simulation, it enables the remaining Monte-Carlo errors to be quantified at onshore sites, without additional inundation simulations. In combination these techniques enable offshore PTHAs to be rigorously transformed into onshore PTHAs, with full characterisation of epistemic uncertainties, while controlling Monte-Carlo errors.

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“…Davies and Griffin (2020) used two rigidity models (constant and depth‐varying models) combined with three slip models to investigate the impact of rigidity on the PTHA and concluded that the tsunami hazard off the shore of Australia was insensitive to the chosen rigidity model. Based on their results, we set the rigidity to be constant, as other tsunami hazard studies often assume a constant value (e.g., Butler et al., 2017; Kalligeris et al., 2017). The Japan Society of Civil Engineers (2016) estimated that the rigidity of the plate boundaries surrounding the islands of Japan is 3.5 × 10 10 Pa when the fault depth is shallower than 20 km, 6.5 × 10 10 Pa when the fault depth is deeper than 20 km, and 5.0 × 10 10 Pa when the fault depth reaches 20 km.…”

Section: Application To the Sagami Trough Earthquake In Japanmentioning

confidence: 99%

Time‐Dependent Probabilistic Tsunami Inundation Assessment Using Mode Decomposition to Assess Uncertainty for an Earthquake Scenario

et al. 2021

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 The singular value decomposition method is used to evaluate the eigenmodes of the tsunami inundation depth distribution and reduce the computational cost.  The variations in three variables are considered earthquake fault uncertainties: the fault depth, slip amount, and slip distribution.  A time-dependent probabilistic tsunami inundation assessment is performed with the BPT distribution to account for seismic imminence.

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An approach for estimating the largest probable tsunami from far-field subduction zone earthquakes

Cited by 7 publications

References 49 publications

Sensitivity of Probabilistic Tsunami Hazard Assessment to Far-Field Earthquake Slip Complexity and Rigidity Depth-Dependence: Case Study of Australia

Sensitivity of Probabilistic Tsunami Hazard Assessment to Far-Field Earthquake Slip Complexity and Rigidity Depth-Dependence: Case Study of Australia

From offshore to onshore probabilistic tsunami hazard assessment via efficient Monte-Carlo sampling

Time‐Dependent Probabilistic Tsunami Inundation Assessment Using Mode Decomposition to Assess Uncertainty for an Earthquake Scenario

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