Region‐Specific Assessment, Adjustment, and Weighting of Ground‐Motion Prediction Models: Application to the 2015 Swiss Seismic‐Hazard Maps

2016 ◽  
Vol 106 (4) ◽  
pp. 1840-1857 ◽  
Author(s):  
Benjamin Edwards ◽  
Carlo Cauzzi ◽  
Laurentiu Danciu ◽  
Donat Fäh
Keyword(s):  
Seismic Hazard ◽  
Ground Motion ◽  
Prediction Models ◽  
Motion Prediction ◽  
Hazard Maps ◽  
Ground Motion Prediction ◽  
Seismic Hazard Maps ◽  
Specific Assessment

On the Forecasting of Ground-Motion Parameters for Probabilistic Seismic Hazard Analysis

2011 ◽  
Vol 27 (1) ◽  
pp. 1-21 ◽  
Author(s):  
Danny Arroyo ◽  
Mario Ordaz
Keyword(s):  
Seismic Hazard ◽  
Ground Motion ◽  
Prediction Models ◽  
Hazard Analysis ◽  
Probabilistic Seismic Hazard Analysis ◽  
Seismic Hazard Analysis ◽  
Motion Prediction ◽  
Probabilistic Seismic Hazard ◽  
Ground Motion Prediction ◽  
Data Set

It is well understood that the range of application for an empirical ground-motion prediction model is constrained by the range of predictor variables covered in the data used in the analysis. However, in probabilistic seismic hazard analysis (PSHA), the limits in the application of ground-motion prediction models (GMPMs) are often ignored, and the empirical relationships are extrapolated. In this paper, we show that this extrapolation leads to a quantifiable increment in the uncertainty of a GMPM when it is used to forecast a future value of a given intensity parameter. This increment, which is clearly of epistemic nature, depends on the adopted functional form, on the covariance matrix of the regression coefficients, on the used regression technique, and on the quality of the data set. In addition, through some examples using the database of the Next Generation of Ground-Motion Attenuation Models project and some currently favored functional forms we study the increment in the seismic hazard produced by the extrapolation of GMPMs.

scholarly journals Site Specific Probabilistic Seismic Hazard Model for Isfahan, Iran: Estimates and Uncertainties

2021 ◽  
Author(s):  
Mohsen Kohrangi ◽  
Homayon Safaei ◽  
Laurentiu Danciu ◽  
Hossein Tajmir-Riahi ◽  
Rassoul Ajalloeian ◽  
...  
Keyword(s):  
Seismic Hazard ◽  
Ground Motion ◽  
Prediction Models ◽  
Seismic Source ◽  
Motion Prediction ◽  
Probabilistic Seismic Hazard ◽  
Maximum Magnitude ◽  
Ground Motion Prediction ◽  
Study Region ◽  
Site Specific

Abstract We present a seismic source characterization model for the probabilistic seismic hazard assessment (PSHA) of the Isfahan urban area, Iran. We compiled the required datasets including the earthquake catalogue and the geological and seismotectonic structure and faults systems within the study region to delineate and characterize seismic source models. We identified seven relatively large zones that bound each region with similar seismotectonic characteristics and catalogue completeness periods. These regions were used for calculating the b-value of the Gutenberg-Richter magnitude recurrence relationship and for estimating the maximum magnitude value within each region. The recurrence parameters were then used to build a spatially varying distributed seismic source model using a smoothed kernel. Additionally, based on a fault database developed in this study and on a local expert’s opinion about their slip velocity, an active faults based model is also created. We further performed sets of sensitivity analyses to find stable estimates of the ground motion intensity and to define alternative branches for both the seismogenic source and ground motion prediction models. Site amplification is considered based on a Vs30 map for Isfahan compiled within this study. The alternative source and ground motion prediction models considered in the logic tree of this study are then implemented in the software Open Quake to generate hazard maps and uniform hazard spectra for return periods of interest. Finally, we provide a detailed comparison of the PSHA outcomes of the current study both with those presented in the 2014 Earthquake Model of Middle East (EMME14) and with the national seismic design spectrum to further discuss the discrepancies between hazard estimates from site-specific and regional PSHA studies.

Probabilistic seismic hazard maps for California do not perform better relative to historical shaking data when site-specific VS30 is considered

2021 ◽  
Author(s):  
Molly Gallahue ◽  
Leah Salditch ◽  
Madeleine Lucas ◽  
James Neely ◽  
Susan Hough ◽  
...  
Keyword(s):  
Seismic Hazard ◽  
Ground Motion ◽  
Tall Buildings ◽  
Historical Period ◽  
Probabilistic Seismic Hazard ◽  
Hazard Maps ◽  
Site Specific ◽  
Seismic Hazard Maps ◽  
Intensity Mapping ◽  
Aleatory Variability

<div> <p>Probabilistic seismic hazard assessments forecast levels of earthquake shaking that should be exceeded with only a certain probability over a given period of time are important for earthquake hazard mitigation. These rely on assumptions about when and where earthquakes will occur, their size, and the resulting shaking as a function of distance as described by ground-motion models (GMMs) that cover broad geologic regions. Seismic hazard maps are used to develop building codes.</p> </div><div> <p>To explore the robustness of maps’ shaking forecasts, we consider how maps hindcast past shaking. We have compiled the California Historical Intensity Mapping Project (CHIMP) dataset of the maximum observed seismic intensity of shaking from the largest Californian earthquakes over the past 162 years. Previous comparisons between the maps for a constant V<sub>S30</sub> (shear-wave velcoity in the top 30 m of soil) of 760 m/s and CHIMP based on several metrics suggested that current maps overpredict shaking.</p> <p>The differences between the V<sub>S30</sub> at the CHIMP sites and the reference value of 760 m/s could amplify or deamplify the ground motions relative to the mapped values. We evaluate whether the V<sub>S30 </sub>at the CHIMP sites could cause a possible bias in the models. By comparison with the intensity data in CHIMP, we find that using site-specific V<sub>S30</sub> does not improve map performance, because the site corrections cause only minor differences from the original 2018 USGS hazard maps at the short periods (high frequencies) relevant to peak ground acceleration and hence MMI. The minimal differences reflect the fact that the nonlinear deamplification due to increased soil damping largely offsets the linear amplification due to low V<sub>S30</sub>. The net effects will be larger for longer periods relevant to tall buildings, where net amplification occurs. </p> <div> <p>Possible reasons for this discrepancy include limitations of the dataset, a bias in the hazard models, an over-estimation of the aleatory variability of the ground motion or that seismicity throughout the historical period has been lower than the long-term average, perhaps by chance due to the variability of earthquake recurrence. Resolving this discrepancy, which is also observed in Italy and Japan, could improve the performance of seismic hazard maps and thus earthquake safety for California and, by extension, worldwide. We also explore whether new nonergodic GMMs, with reduced aleatory variability, perform better than presently used ergodic GMMs compared to historical data.</p> </div> </div>

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