Are the Standard VS-Kappa Host-to-Target Adjustments the Only Way to Get Consistent Hard-Rock Ground Motion Prediction?

Bard, Pierre Yves; Bora, Sanjay Singh; Hollender, Fabrice; Laurendeau, Aurore; Traversa, Paola

doi:10.1007/s00024-019-02173-9

Cited by 23 publications

(12 citation statements)

References 65 publications

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“…Hence, as concluded by Kohrangi et al (2020), this example shows that the traditional approach may lead to biased risk estimates whose amplitude and sign are impossible to predict a priori unless high quality site-specific ground-motion data (Bard et al 2019) allow the development of site-specific non-ergodic GMPEs. Based on these results, the use of the non-ergodic approach is recommended, whenever existing data allow it.…”

Section: Effects Of Partially Non-ergodic Gmpes On Risk Estimatesmentioning

confidence: 83%

Earthquake Catastrophe Risk Modeling, Application to the Insurance Industry: Unknowns and Possible Sources of Bias in Pricing

Kohrangi¹,

Παπαδόπουλος

Kotha

et al. 2021

Springer Tracts in Civil Engineering

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Mathematical risk assessment models based on empirical data and supported by the principles of physics and engineering have been used in the insurance industry for more than three decades to support informed decisions for a wide variety of purposes, including insurance and reinsurance pricing. To supplement scarce data from historical events, these models provide loss estimates caused to portfolios of structures by simulated but realistic scenarios of future events with estimated annual rates of occurrence. The reliability of these estimates has evolved steadily from those based on the rather simplistic and, in many aspects, semi-deterministic approaches adopted in the very early days to those of the more recent models underpinned by a larger wealth of data and fully probabilistic methodologies. Despite the unquestionable progress, several modeling decisions and techniques still routinely adopted in commercial models warrant more careful scrutiny because of their potential to cause biased results. In this chapter we will address two such cases that pertain to the risk assessment for earthquakes. With the help of some illustrative but simple applications we will first motivate our concerns with the current state of practice in modeling earthquake occurrence and building vulnerability for portfolio risk assessment. We will then provide recommendations for moving towards a more comprehensive, and arguably superior, approach to earthquake risk modeling that capitalizes on the progress recently made in risk assessment of single buildings. In addition to these two upgrades, which in our opinion are ready for implementation in commercial models, we will also describe an enhancement in ground motion prediction that will certainly be considered in the models of tomorrow but is not yet ready for primetime. These changes are implemented in example applications that highlight their importance for portfolio risk assessment. Special consideration will be given to the potential bias in the Average Annual Loss estimates, which constitutes the foundation of insurance and reinsurance policies’ pricing, that may result from the application of the traditional approaches.

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Section: Effects Of Partially Non-ergodic Gmpes On Risk Estimatesmentioning

confidence: 83%

Earthquake Catastrophe Risk Modeling, Application to the Insurance Industry: Unknowns and Possible Sources of Bias in Pricing

Kohrangi¹,

Παπαδόπουλος

Kotha

et al. 2021

Springer Tracts in Civil Engineering

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“…In that case, alternative site-response proxies are sought to predict the S2S s , as in Kotha et al (2018);Weatherill et al (2020b). However, even in these studies, while the long period site-response could be partially explained using some geotechnical parameters, short-period site-response is much more variable-even among the so-called reference rock sites (Bard et al 2019;Pilz et al 2020).…”

Section: Towards Non-ergodic Ground-motion Predictionsmentioning

confidence: 99%

A regionally-adaptable ground-motion model for shallow crustal earthquakes in Europe

Kotha

Weatherill

Bindi

et al. 2020

Bull Earthquake Eng

115

233

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To complement the new European Strong-Motion dataset and the ongoing efforts to update the seismic hazard and risk assessment of Europe and Mediterranean regions, we propose a new regionally adaptable ground-motion model (GMM). We present here the GMM capable of predicting the 5% damped RotD50 of PGA, PGV, and SA(T = 0.01 − 8 s) from shallow crustal earthquakes of 3 ≤ M W ≤ 7.4 occurring 0 < R JB ≤ 545 km away from sites with 90 ≤ V s30 ≤ 3000 m s −1 or 0.001 ≤ slope ≤ 1 m m −1. The extended applicability derived from thousands of new recordings, however, comes with an apparent increase in the aleatory variability (σ). Firstly, anticipating contaminations and peculiarities in the dataset, we employed robust mixed-effect regressions to down weigh only, and not eliminate entirely, the influence of outliers on the GMM median and σ. Secondly, we regionalised the attenuating path and localised the earthquake sources using the most recent models, to quantify region-specific anelastic attenuation and locality-specific earthquake characteristics as random-effects, respectively. Thirdly, using the mixed-effect variancecovariance structure, the GMM can be adapted to new regions, localities, and sites with specific datasets. Consequently, the σ is curtailed to a 7% increase at T < 0.3 s, and a substantial 15% decrease at T ≥ 0.3 s, compared to the RESORCE based partially non-ergodic GMM. We provide the 46 attenuating region-, 56 earthquake localities-, and 1829 site-specific adjustments, demonstrate their usage, and present their robustness through a 10-fold cross-validation exercise.

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“…As stated above, the variability of site-response at high frequencies could be from instrument housing type or more physical; such as the influence of deeper soil layers, plasticity of soil column, weathering of bedrock, seasonal changes in shear-wave velocity in shallow layers (Alexis et al 2021;Roumelioti et al 2020), etc. However, in-lieu of resolving such issues, and given the practical importance of high frequency site-response, the most efficient solution yet is to collect more site-specific data (Bard et al 2019).…”

Section: Site-response Variabilitymentioning

confidence: 99%

A Regionally Adaptable Ground-Motion Model for Fourier Amplitude Spectra of Shallow Crustal Earthquakes in Europe

Kotha¹,

Bindi²,

Cotton³

2021

Preprint

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Typical ground-motion models predict the response spectral ordinates (GMM-SA), which are the damped responses of a suite of single-degree-of-freedom oscillators. Response spectra represent the response of an idealized structure to input ground-motion, but not the physics of the actual ground-motion. To complement the regionally adaptable GMM-SA of Kotha et al. (2020), we introduce here a model capable of predicting Fourier amplitudes (GMM-FA); developed from the same Engineering Strong Motion (ESM) dataset for pan-Europe. This GMM-FA reveals the very high variability of high frequency ground-motions, which are completely masked in a GMM-SA. By maintaining the development strategies of GMM-FA identical to that of the GMM-SA, we are able to evaluate the physical meaning of the spatial variability of anelastic attenuation and source characteristics. We find that a fully data-driven geospatial index, Activity Index (AIx), correlates well with the spatial variability of these physical effects. AIx is a fuzzy combination of seismicity and crustal parameters, and can be used to adapt the attenuation and source non-ergodicity of the GMM-FA to regions and tectonic localities sparsely sampled in ESM. While AIx, and a few other parameters we touch upon, may help understand the spatial variability of high frequency attenuation and source effects, the high frequency site-response variability - dominating the overall aleatory variance - is yet unresolvable. With the rapid increase in quantity and quality of ground-motion datasets, we call for an upgrade of regionalization techniques, site-characterisation, and a paradigm shift to Fourier ground-motion models to complement the traditional response spectra prediction models.

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Are the Standard VS-Kappa Host-to-Target Adjustments the Only Way to Get Consistent Hard-Rock Ground Motion Prediction?

Cited by 23 publications

References 65 publications

Earthquake Catastrophe Risk Modeling, Application to the Insurance Industry: Unknowns and Possible Sources of Bias in Pricing

Earthquake Catastrophe Risk Modeling, Application to the Insurance Industry: Unknowns and Possible Sources of Bias in Pricing

A regionally-adaptable ground-motion model for shallow crustal earthquakes in Europe

A Regionally Adaptable Ground-Motion Model for Fourier Amplitude Spectra of Shallow Crustal Earthquakes in Europe

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