scholarly journals Separation of Aleatory and Epistemic Uncertainty from Inter-Event Residuals in Ground Motion Prediction Equations

2013 ◽  
Vol 13 (1) ◽  
pp. 37-51
Author(s):  
Yasuo UCHIYAMA ◽  
Saburoh Midorikawa
Keyword(s):  
Ground Motion ◽  
Epistemic Uncertainty ◽  
Motion Prediction ◽  
Ground Motion Prediction Equations ◽  
Prediction Equations ◽  
Ground Motion Prediction ◽  
Aleatory And Epistemic Uncertainty

Improvement of the Quantification of Epistemic Uncertainty Using Single‐Station Ground‐Motion Prediction Equations

2019 ◽  
Vol 109 (4) ◽  
pp. 1358-1377
Author(s):  
Chih‐Hsuan Sung ◽  
Chyi‐Tyi Lee
Keyword(s):  
Ground Motion ◽  
Epistemic Uncertainty ◽  
Hazard Analysis ◽  
Strong Motion ◽  
Motion Prediction ◽  
Ground Motion Prediction Equations ◽  
Prediction Equations ◽  
Ground Motion Prediction ◽  
Ground Acceleration ◽  
Single Station

Abstract The results of probabilistic seismic hazard analysis (PSHA) are sensitive to the standard deviation of the residuals of the ground‐motion prediction equations (GMPEs), especially for long‐return periods. Recent studies have proven that the epistemic uncertainty should be incorporated into PSHA using a logic‐tree method instead of mixing it with the aleatory variability. In this study, we propose using single‐station GMPEs with a novel approach (an epistemic‐residual diagram) to improve the quantification of epistemic uncertainty per station. The single‐station attenuation model is established from the observational recordings of a single station, hence, site‐to‐site variability (σS) can be ignored. We use 20,006 records of 497 crustal earthquakes with moment magnitudes (Mw) greater than 4.0, obtained from the Taiwan Strong Motion Instrumentation Program network, to build the single‐station GMPEs for 570 stations showing the peak ground acceleration (PGA) and spectral accelerations. A comparison is made between the total sigma of the regional GMPE (σT), the single‐station sigma of the regional GMPE as estimated by the variance decomposition method (σSS), and the sigma of single‐station GMPEs (σSS,S), for different periods. For most stations (70%), the σSS,S is about 20%–50% smaller than the σT. Furthermore, we adopt the epistemic‐residual diagram to separate the σSS,S into the epistemic uncertainty (σEP,S) and the remaining unexplained variability (σSP,S) for each station. The results show that in most areas, the σSP,S for the PGA is about 50%–80% smaller than the σT. Finally, the variations in the various sigma and model coefficients are mapped with the geographical locations of the stations for analysis of different regional characteristics.

A suite of ground motion prediction equations for cumulative absolute velocity in shallow crustal earthquakes including epistemic uncertainty

2020 ◽  
pp. 875529302095734
Author(s):  
Zach Bullock ◽  
Abbie B Liel ◽  
Shideh Dashti ◽  
Keith A. Porter
Keyword(s):  
Ground Motion ◽  
Epistemic Uncertainty ◽  
Absolute Velocity ◽  
Motion Prediction ◽  
Ground Motion Prediction Equations ◽  
Prediction Equations ◽  
Ground Motion Prediction ◽  
Crustal Earthquakes ◽  
Cumulative Absolute Velocity ◽  
Earthquake Characteristics

Recent research has highlighted the usefulness of cumulative absolute velocity [Formula: see text] in several contexts, including using the [Formula: see text] at the ground surface for earthquake early warning and using the [Formula: see text] at rock reference conditions for evaluation of the liquefaction risk facing structures. However, there are relatively few ground motion prediction equations for CAV, they are based on relatively small data sets, and they give relatively similar results. This study develops nine ground motion prediction equations for [Formula: see text] based on a global database of ground motion records from shallow crustal earthquakes. Its provision of nine models enables characterization of epistemic uncertainty for ranges of earthquake characteristics that are sparsely populated in the regression database. The functional forms provide different perspectives on extrapolation to important ranges of earthquake characteristics, particularly large magnitude events and short distances. The variability and epistemic uncertainty in the models are characterized. Spatial autocorrelation of the models’ errors is investigated. The models’ predictions agree with existing broadly applicable models at small to moderate magnitudes and moderate to long distances. These models can be used to improve hazard analysis of [Formula: see text] that incorporates the influence of epistemic uncertainty.

scholarly journals Ground Motion Prediction Equations for Malaysia Due to Subduction Zone Earthquakes in Sumatran Region

IEEE Access ◽  
2017 ◽  
Vol 5 ◽  
pp. 23920-23937
Author(s):  
M. S. Liew ◽  
Kamaluddeen Usman Danyaro ◽  
Mazlina Mohamad ◽  
Lim Eu Shawn ◽  
Aziz Aulov
Keyword(s):  
Subduction Zone ◽  
Ground Motion ◽  
Motion Prediction ◽  
Ground Motion Prediction Equations ◽  
Prediction Equations ◽  
Ground Motion Prediction ◽  
Subduction Zone Earthquakes

scholarly journals Ground motions in urban Los Angeles from the 2019 Ridgecrest earthquake sequence

2021 ◽  
pp. 875529302110039
Author(s):  
Filippos Filippitzis ◽  
Monica D Kohler ◽  
Thomas H Heaton ◽  
Robert W Graves ◽  
Robert W Clayton ◽  
...  
Keyword(s):  
Los Angeles ◽  
Ground Motion ◽  
Ground Motions ◽  
Earthquake Sequence ◽  
Motion Prediction ◽  
Ground Motion Prediction Equations ◽  
Prediction Equations ◽  
Ground Motion Prediction ◽  
Velocity Models ◽  
Spectral Accelerations

We study ground-motion response in urban Los Angeles during the two largest events (M7.1 and M6.4) of the 2019 Ridgecrest earthquake sequence using recordings from multiple regional seismic networks as well as a subset of 350 stations from the much denser Community Seismic Network. In the first part of our study, we examine the observed response spectral (pseudo) accelerations for a selection of periods of engineering significance (1, 3, 6, and 8 s). Significant ground-motion amplification is present and reproducible between the two events. For the longer periods, coherent spectral acceleration patterns are visible throughout the Los Angeles Basin, while for the shorter periods, the motions are less spatially coherent. However, coherence is still observable at smaller length scales due to the high spatial density of the measurements. Examining possible correlations of the computed response spectral accelerations with basement depth and Vs30, we find the correlations to be stronger for the longer periods. In the second part of the study, we test the performance of two state-of-the-art methods for estimating ground motions for the largest event of the Ridgecrest earthquake sequence, namely three-dimensional (3D) finite-difference simulations and ground motion prediction equations. For the simulations, we are interested in the performance of the two Southern California Earthquake Center 3D community velocity models (CVM-S and CVM-H). For the ground motion prediction equations, we consider four of the 2014 Next Generation Attenuation-West2 Project equations. For some cases, the methods match the observations reasonably well; however, neither approach is able to reproduce the specific locations of the maximum response spectral accelerations or match the details of the observed amplification patterns.

scholarly journals Selection of Ground Motion Prediction Equations for the Global Earthquake Model

2015 ◽  
Vol 31 (1) ◽  
pp. 19-45 ◽  
Author(s):  
Jonathan P. Stewart ◽  
John Douglas ◽  
Mohammad Javanbarg ◽  
Yousef Bozorgnia ◽  
Norman A. Abrahamson ◽  
...  
Keyword(s):  
Ground Motion ◽  
Selection Process ◽  
Selection Procedure ◽  
Empirical Models ◽  
Motion Prediction ◽  
Ground Motion Prediction Equations ◽  
Prediction Equations ◽  
Ground Motion Prediction ◽  
Intensity Measures ◽  
Earthquake Model

Ground motion prediction equations (GMPEs) relate ground motion intensity measures to variables describing earthquake source, path, and site effects. From many available GMPEs, we select those models recommended for use in seismic hazard assessments in the Global Earthquake Model. We present a GMPE selection procedure that evaluates multidimensional ground motion trends (e.g., with respect to magnitude, distance, and structural period), examines functional forms, and evaluates published quantitative tests of GMPE performance against independent data. Our recommendations include: four models, based principally on simulations, for stable continental regions; three empirical models for interface and in-slab subduction zone events; and three empirical models for active shallow crustal regions. To approximately incorporate epistemic uncertainties, the selection process accounts for alternate representations of key GMPE attributes, such as the rate of distance attenuation, which are defensible from available data. Recommended models for each domain will change over time as additional GMPEs are developed.

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