Selection of earthquake ground motion models using the deviance information criterion

2019 ◽  
Vol 117 ◽  
pp. 288-299 ◽  
Author(s):  
Milad Kowsari ◽  
Benedikt Halldorsson ◽  
Birgir Hrafnkelsson ◽  
Sigurjón Jónsson
Author(s):  
Jaleena Sunny ◽  
Marco De Angelis ◽  
Benjamin Edwards

Abstract We introduce the cumulative-distribution-based area metric (AM)—also known as stochastic AM—as a scoring metric for earthquake ground-motion models (GMMs). The AM quantitatively informs the user of the degree to which observed or test data fit with a given model, providing a rankable absolute measure of misfit. The AM considers underlying data distributions and model uncertainties without any assumption of form. We apply this metric, along with existing testing methods, to four GMMs in order to test their performance using earthquake ground-motion data from the Preston New Road (United Kingdom) induced seismicity sequences in 2018 and 2019. An advantage of the proposed approach is its applicability to sparse datasets. We, therefore, focus on the ranking of models for discrete ranges of magnitude and distance, some of which have few data points. The variable performance of models in different ranges of the data reveals the importance of considering alternative models. We extend the ranking of GMMs through analysis of intermodel variations of the candidate models over different ranges of magnitude and distance using the AM. We find the intermodel AM can be a useful tool for selection of models for the logic-tree framework in seismic-hazard analysis. Overall, the AM is shown to be efficient and robust in the process of selection and ranking of GMMs for various applications, particularly for sparse and small-sized datasets.


2016 ◽  
Vol 15 (4) ◽  
pp. 1319-1343 ◽  
Author(s):  
Radmila Salic ◽  
M. Abdullah Sandikkaya ◽  
Zoran Milutinovic ◽  
Zeynep Gulerce ◽  
Llambro Duni ◽  
...  

2021 ◽  
pp. 875529302110348
Author(s):  
Grace A Parker ◽  
Jonathan P Stewart ◽  
David M Boore ◽  
Gail M Atkinson ◽  
Behzad Hassani

We develop semi-empirical ground motion models (GMMs) for peak ground acceleration, peak ground velocity, and 5%-damped pseudo-spectral accelerations for periods from 0.01 to 10 s, for the median orientation-independent horizontal component of subduction earthquake ground motion. The GMMs are applicable to interface and intraslab subduction earthquakes in Japan, Taiwan, Mexico, Central America, South America, Alaska, the Aleutian Islands, and Cascadia. The GMMs are developed using a combination of data inspection, data regression with respect to physics-informed functions, ground-motion simulations, and geometrical constraints for certain model components. The GMMs capture observed differences in source and path effects for interface and intraslab events, conditioned on moment magnitude, rupture distance, and hypocentral depth. Site effect and aleatory variability models are shared between event types. Regionalized GMM components include the model constant (that controls ground motion amplitude), anelastic attenuation, magnitude-scaling break point, linear site response, and sediment depth terms. We develop models for the aleatory between-event variability [Formula: see text], within-event variability [Formula: see text], single-station within-event variability [Formula: see text], and site-to-site variability [Formula: see text]. Ergodic analyses should use the median GMM and aleatory variability computed using the between-event and within-event variability models. An analysis incorporating non-ergodic site response should use the median GMM at the reference shear-wave velocity condition, a site-specific site response model, and aleatory variability computed using the between-event and single-station within-event variability models. Epistemic uncertainty in the median model is represented by standard deviations on the regional model constants, which facilitates scaled-backbone representations of model uncertainty in hazard analyses.


2021 ◽  
Author(s):  
Roberto Paolucci ◽  
Angela Chiecchio ◽  
Manuela Vanini

Abstract This paper aims at providing a quantitative evaluation of the performance of a set of empirical ground motion models (GMMs), by testing them in a magnitude and distance range (Mw = 5.5 ÷ 7.0 and Joyner-Boore source-to-site distance Rjb ≤ 20 km) which dominates hazard in the highest seismicity areas of Italy for the return periods of upmost interest for seismic design. To this end, we made use of the very recent release of the NESS2.0 dataset (Sgobba et al., 2021), that collects worldwide near-source strong motion records with detailed metadata. After selection of an ample set of GMMs, based on either their application in past seismic hazard assessment (SHA) studies or for their recent introduction, a quantification of between- and within-event residuals of predictions with respect to records was performed, with the final aim of shedding light on the performance of existing GMMs in the near-source of moderate-to-large earthquakes, in view of a proper selection and weighting of GMMs for SHA.


Author(s):  
Soumya Kanti Maiti ◽  
Gony Yagoda-Biran ◽  
Ronnie Kamai

ABSTRACT Models for estimating earthquake ground motions are a key component in seismic hazard analysis. In data-rich regions, these models are mostly empirical, relying on the ever-increasing ground-motion databases. However, in areas in which strong-motion data are scarce, other approaches for ground-motion estimates are sought, including, but not limited to, the use of simulations to replace empirical data. In Israel, despite a clear seismic hazard posed by the active plate boundary on its eastern border, the instrumental record is sparse and poor, leading to the use of global models for hazard estimation in the building code and all other engineering applications. In this study, we develop a suite of alternative ground-motion models for Israel, based on an empirical database from Israel as well as on four data-calibrated synthetic databases. Two host models are used to constrain model behavior, such that the epistemic uncertainty is captured and characterized. Despite the lack of empirical data at large magnitudes and short distances, constraints based on the host models or on the physical grounds provided by simulations ensure these models are appropriate for engineering applications. The models presented herein are cast in terms of the Fourier amplitude spectra, which is a linear, physical representation of ground motions. The models are suitable for shallow crustal earthquakes; they include an estimate of the median and the aleatory variability, and are applicable in the magnitude range of 3–8 and distance range of 1–300 km.


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