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Accelerometric data from the well-studied valley EUROSEISTEST are used to investigate ground motion uncertainty and variability. We define a simple local ground motion prediction equation (GMPE) and investigate changes in standard deviation (σ) and its components, the between-event variability (τ) and within-event variability (φ). Improving seismological metadata significantly reduces τ (30–50%), which in turn reduces the total σ. Improving site information reduces the systematic site-to-site variability, φ S2S (20–30%), in turn reducing φ, and ultimately, σ. Our values of standard deviations are lower than global values from literature, and closer to path-specific than site-specific values. However, our data have insufficient azimuthal coverage for single-path analysis. Certain stations have higher ground-motion variability, possibly due to topography, basin edge or downgoing wave effects. Sensitivity checks show that 3 recordings per event is a sufficient data selection criterion, however, one of the dataset’s advantages is the large number of recordings per station (9–90) that yields good site term estimates. We examine uncertainty components binning our data with magnitude from 0.01 to 2 s; at smaller magnitudes, τ decreases and φ SS increases, possibly due to κ and source-site trade-offs Finally, we investigate the alternative approach of computing φ SS using existing GMPEs instead of creating an ad hoc local GMPE. This is important where data are insufficient to create one, or when site-specific PSHA is performed. We show that global GMPEs may still capture φ SS , provided that: (1) the magnitude scaling errors are accommodated by the event terms; (2) there are no distance scaling errors (use of a regionally applicable model). Site terms (φ S2S ) computed by different global GMPEs (using different site-proxies) vary significantly, especially for hard-rock sites. This indicates that GMPEs may be poorly constrained where they are sometimes most needed, i.e., for hard rock.
The basic seismic load parameters for the upcoming national design regulation for DIN EN 1998-1/NA result from the reassessment of the seismic hazard supported by the German Institution for Civil Engineering (DIBt). This 2016 version of the national seismic hazard assessment for Germany is based on a comprehensive involvement of all accessible uncertainties in models and parameters and includes the provision of a rational framework for integrating ranges of epistemic uncertainties and aleatory variabilities in a comprehensive and transparent way. The developed seismic hazard model incorporates significant improvements over previous versions. It is based on updated and extended databases, it includes robust methods to evolve sets of models representing epistemic uncertainties, and a selection of the latest generation of ground motion prediction equations. The new earthquake model is presented here, which consists of a logic tree with 4040 end branches and essential innovations employed for a realistic approach. The output specifications were designed according to the user oriented needs as suggested by two review teams supervising the entire project. Seismic load parameters, for rock conditions of nu(S30) = 800 m/s, are calculated for three hazard levels (10, 5 and 2% probability of occurrence or exceedance within 50 years) and delivered in the form of uniform hazard spectra, within the spectral period range 0.02-3 s, and seismic hazard maps for peak ground acceleration, spectral response accelerations and for macroseismic intensities. Results are supplied as the mean, the median and the 84th percentile. A broad analysis of resulting uncertainties of calculated seismic load parameters is included. The stability of the hazard maps with respect to previous versions and the cross-border comparison is emphasized.
One paragraph of the manuscript of the paper has been inadvertently omitted in the very final stage of its compilation due to a technical mistake. Since this paragraph discusses the declustering of the used earthquake catalogue and is therefore necessary for the understanding of the seismicity data preprocessing, the authors decided to provide this paragraph in form of a correction. The respective paragraph belongs to chapter 2 of the paper, where it was placed originally, and should be inserted into the published paper before the second to the last paragraph. The omitted text reads as follows:
We study the rupture processes of Iquique earthquake 8.1 (2014/04/01) and its largest aftershock 7.7 (2014/04/03) that ruptured the North Chile subduction zone. High-rate Global Positioning System (GPS) recordings and strong motion data are used to reconstruct the evolution of the slip amplitude, rise time and rupture time of both earthquakes. A two-step inversion scheme is assumed, by first building prior models for both earthquakes from the inversion of the estimated static displacements and then, kinematic inversions in the frequency domain are carried out taken into account this prior information. The preferred model for the mainshock exhibits a seismic moment of 1.73 × 1021 Nm ( 8.1) and maximum slip of ∼9 m, while the aftershock model has a seismic moment of 3.88 × 1020 ( 7.7) and a maximum slip of ∼3 m. For both earthquakes, the final slip distributions show two asperities (a shallow one and a deep one) separated by an area with significant slip deficit. This suggests a segmentation along-dip which might be related to a change of the dipping angle of the subducting slab inferred from gravimetric data. Along-strike, the areas where the seismic ruptures stopped seem to be well correlated with geological features observed from geophysical information (high-resolution bathymetry, gravimetry and coupling maps) that are representative of the long-term segmentation of the subduction margin. Considering the spatially limited portions that were broken by these two earthquakes, our results support the idea that the seismic gap is not filled yet.
Two ground motion prediction equation models for subduction zones have been tested using a public ground motion database of the KiK-net records obtained by automated processing protocols (Dawood et al., 2016, https://doi.org/10.1193/071214EQS106). The database contains records of more than 700 interface earthquakes that occurred on the Japan subduction between 1998 and 2012. The Zhao et al. (2006, https://doi.org/10.1785/0120050122) ground motion prediction equation was shown to be the best suited model for the region. It was then used as backbone to analyze the variability of ground motion records. The residuals between observed and predicted ground motions have been analyzed to study the spatial variation of the earthquakes' ground motion frequency content on the Japan megathrust. This analysis revealed a depth dependency of generated ground motions consistent with the downdip segmentation proposed for subduction interfaces (Lay et al., 2012, https://doi.org/10.1029/2011JB009133), a regional ground motion dependency that may be related with lateral variations of the mechanical properties of the subduction interface and a high-frequency radiations drop in the earthquake sequence that preceded the Tohoku-Oki earthquake Mw 9.0. The regional ground motion dependency suggests the existence of different domains along trench of the Japan subduction megathrust that control the ground motions and the wave radiation patterns of interface earthquakes. The location of their boundaries is consistent with the extension of the rupture of the 2011 Tohoku-Oki earthquake, with pre-Tohoku interseismic coupling, and with the free air gravity anomalies.
We study the rupture processes of Iquique earthquake M-w 8.1 (2014/04/01) and its largest aftershock M-w 7.7 (2014/04/03) that ruptured the North Chile subduction zone. High-rate Global Positioning System (GPS) recordings and strong motion data are used to reconstruct the evolution of the slip amplitude, rise time and rupture time of both earthquakes. A two-step inversion scheme is assumed, by first building prior models for both earthquakes from the inversion of the estimated static displacements and then, kinematic inversions in the frequency domain are carried out taken into account this prior information. The preferred model for the mainshock exhibits a seismic moment of 1.73 x 10(21) Nm (M-w 8.1) and maximum slip of similar to 9 m, while the aftershock model has a seismic moment of 3.88 x 10(20) (M-w 7.7) and a maximum slip of similar to 3 m. For both earthquakes, the final slip distributions show two asperities (a shallow one and a deep one) separated by an area with significant slip deficit. This suggests a segmentation along-dip which might be related to a change of the dipping angle of the subducting slab inferred from gravimetric data. Along-strike, the areas where the seismic ruptures stopped seem to be well correlated with geological features observed from geophysical information (high-resolution bathymetry, gravimetry and coupling maps) that are representative of the long-term segmentation of the subduction margin. Considering the spatially limited portions that were broken by these two earthquakes, our results support the idea that the seismic gap is not filled yet. (C) 2018 Elsevier B.V. All rights reserved.
The aim of this paper is to investigate the ability of various site-condition proxies (SCPs) to reduce ground-motion aleatory variability and evaluate how SCPs capture nonlinearity site effects. The SCPs used here are time-averaged shear-wave velocity in the top 30 m (V-S30), the topographical slope (slope), the fundamental resonance frequency (f(0)) and the depth beyond which V-s exceeds 800 m/s (H800). We considered first the performance of each SCP taken alone and then the combined performance of the 6 SCP pairs [V-S30-f(0)], [V-S30-H-800], [f(0)-slope], [H-800-slope], [V-S30-slope] and [f(0)-H-800]. This analysis is performed using a neural network approach including a random effect applied on a KiK-net subset for derivation of ground-motion prediction equations setting the relationship between various ground-motion parameters such as peak ground acceleration, peak ground velocity and pseudo-spectral acceleration PSA (T), and Mw, RJB, focal depth and SCPs. While the choice of SCP is found to have almost no impact on the median groundmotion prediction, it does impact the level of aleatory uncertainty. VS30 is found to perform the best of single proxies at short periods (T < 0.6 s), while f(0) and H-800 perform better at longer periods; considering SCP pairs leads to significant improvements, with particular emphasis on [V-S30-H-800] and [f(0)-slope] pairs. The results also indicate significant nonlinearity on the site terms for soft sites and that the most relevant loading parameter for characterising nonlinear site response is the "stiff" spectral ordinate at the considered period.
We have analyzed the recently developed pan-European strong motion database, RESORCE-2012: spectral parameters, such as stress drop (stress parameter, Delta sigma), anelastic attenuation (Q), near surface attenuation (kappa(0)) and site amplification have been estimated from observed strong motion recordings. The selected dataset exhibits a bilinear distance-dependent Q model with average kappa(0) value 0.0308 s. Strong regional variations in inelastic attenuation were also observed: frequency-independent Q(0) of 1462 and 601 were estimated for Turkish and Italian data respectively. Due to the strong coupling between Q and kappa(0), the regional variations in Q have strong impact on the estimation of near surface attenuation kappa(0). kappa(0) was estimated as 0.0457 and 0.0261 s for Turkey and Italy respectively. Furthermore, a detailed analysis of the variability in estimated kappa(0) revealed significant within-station variability. The linear site amplification factors were constrained from residual analysis at each station and site-class type. Using the regional Q(0) model and a site-class specific kappa(0), seismic moments (M-0) and source corner frequencies f (c) were estimated from the site corrected empirical Fourier spectra. Delta sigma did not exhibit magnitude dependence. The median Delta sigma value was obtained as 5.75 and 5.65 MPa from inverted and database magnitudes respectively. A comparison of response spectra from the stochastic model (derived herein) with that from (regional) ground motion prediction equations (GMPEs) suggests that the presented seismological parameters can be used to represent the corresponding seismological attributes of the regional GMPEs in a host-to-target adjustment framework. The analysis presented herein can be considered as an update of that undertaken for the previous Euro-Mediterranean strong motion database presented by Edwards and Fah (Geophys J Int 194(2):1190-1202, 2013a).
The task of downloading comprehensive datasets of event-based seismic waveforms has been made easier through the development of standardized webservices but is still highly nontrivial because the likelihood of temporary network failures or subtle data errors naturally increases when the amount of requested data is in the order of millions of relatively short segments. This is even more challenging because the typical workflow is not restricted to a single massive download but consists of fetching all possible available input data (e.g., with several repeated download executions) for a processing stage producing any desired user-defined output. Here, we present stream2segment, a highly customizable Python 2+3 package helping the user in the entire workflow of downloading, inspecting, and processing event-based seismic data by means of a relational database management system as archiving storage, which has clear performance and usability advantages, and an integrated processing subroutine requiring a configuration file and a single Python function to produce user-defined output. Stream2segment can also produce diagnostic maps or user-defined plots, which, unlike existing tools, do not require external software dependencies and are not static images but instead are interactive browser-based applications ideally suited for data inspection or annotation tasks and subsequent training of classifiers in foreseen supervised machine-learning applications. Stream2segment has already been used as a data quality tool for datasets within the European Integrated Data Archive and to create a weak-motion database (in the form of a so-called flat file) for the stable continental region of Europe in the context of the European Ground Shaking Intensity Model service, in turn an important building block for seismic hazard studies.
Detections of pP and sP phase arrivals (the so-called depth phases) at teleseismic distance provide one of the best ways to estimate earthquake focal depth, as the P-pP and the P-sP delays are strongly dependent on the depth. Based on a new processing workflow and using a single seismic array at teleseismic distance, we can estimate the depth of clusters of small events down to magnitude M-b 3.5. Our method provides a direct view of the relative variations of the seismicity depth from an active area. This study focuses on the application of this new methodology to study the lateral variations of the Guerrero subduction zone (Mexico) using the Eielson seismic array in Alaska (USA). After denoising the signals, 1232 M-b 3.5 + events were detected, with clear P, pP, sP and PcP arrivals. A high-resolution view of the lateral variations of the depth of the seismicity of the Guerero-Oaxaca area is thus obtained. The seismicity is shown to be mainly clustered along the interface, coherently following the geometry of the plate as constrained by the receiver-function analysis along the Meso America Subduction Experiment profile. From this study, the hypothesis of tears on the western part of Guerrero and the eastern part of Oaxaca are strongly confirmed by dramatic lateral changes in the depth of the earthquake clusters. The presence of these two tears might explain the observed lateral variations in seismicity, which is correlated with the boundaries of the slow slip events.
A transparent and data-driven global tectonic regionalization model for seismic hazard assessment
(2018)
A key concept that is common to many assumptions inherent within seismic hazard assessment is that of tectonic similarity. This recognizes that certain regions of the globe may display similar geophysical characteristics, such as in the attenuation of seismic waves, the magnitude scaling properties of seismogenic sources or the seismic coupling of the lithosphere. Previous attempts at tectonic regionalization, particularly within a seismic hazard assessment context, have often been based on expert judgements; in most of these cases, the process for delineating tectonic regions is neither reproducible nor consistent from location to location. In this work, the regionalization process is implemented in a scheme that is reproducible, comprehensible from a geophysical rationale, and revisable when new relevant data are published. A spatial classification-scheme is developed based on fuzzy logic, enabling the quantification of concepts that are approximate rather than precise. Using the proposed methodology, we obtain a transparent and data-driven global tectonic regionalization model for seismic hazard applications as well as the subjective probabilities (e.g. degree of being active/degree of being cratonic) that indicate the degree to which a site belongs in a tectonic category.
Python is at the forefront of scientific computation for seismologists and therefore should be introduced to students interested in becoming seismologists. On its own, Python is open source and well designed with extensive libraries. However, Python code can also be executed, visualized, and communicated to others with "Jupyter Notebooks". Thus, Jupyter Notebooks are ideal for teaching students Python and scientific computation. In this article, we designed an openly available Python library and collection of Jupyter Notebooks based on defined scientific computation learning goals for seismology students. The Notebooks cover topics from an introduction to Python to organizing data, earthquake catalog statistics, linear regression, and making maps. Our Python library and collection of Jupyter Notebooks are meant to be used as course materials for an upper-division data analysis course in an Earth Science Department, and the materials were tested in a Probabilistic Seismic Hazard course. However, seismologists or anyone else who is interested in Python for data analysis and map making can use these materials.
To evaluate the spatiotemporal variations of ground motions in northern Chile, we built a high-quality rock seismic acceleration database and an interface earthquakes catalog. Two ground-motion prediction equation (GMPE) models for subduction zones have been tested and validated for the area. They were then used as backbone models to describe the time-space variations of earthquake frequency content (Fourier and response spectra). Consistent with previous studies of large subduction earthquakes, moderate interface earthquakes in northern Chile show an increase of the high-frequency energy released with depth. A regional variability of earthquake frequency content is also observed, which may be related to a lateral segmentation of the mechanical properties of the subduction interface. Finally, interface earthquakes show a temporal evolution of their frequency content in the earthquake sequence associated with the 2014 Iquique M-w 8.1 megathrust earthquake. Surprisingly, the change does not occur with the mainshock but is associated with an 8 month slow slip preceding the megathrust. Electronic Supplement: Strong-motion database.
The estimation of minimum-misfit stochastic models from empirical ground-motion prediction equations
(2006)
In areas of moderate to low seismic activity there is commonly a lack of recorded strong ground motion. As a consequence, the prediction of ground motion expected for hypothetical future earthquakes is often performed by employing empirical models from other regions. In this context, Campbell's hybrid empirical approach (Campbell, 2003, 2004) provides a methodological framework to adapt ground-motion prediction equations to arbitrary target regions by using response spectral host-to-target-region-conversion filters. For this purpose, the empirical ground-motion prediction equation has to be quantified in terms of a stochastic model. The problem we address here is how to do this in a systematic way and how to assess the corresponding uncertainties. For the determination of the model parameters we use a genetic algorithm search. The stochastic model spectra were calculated by using a speed-optimized version of SMSIM (Boore, 2000). For most of the empirical ground-motion models, we obtain sets of stochastic models that match the empirical models within the full magnitude and distance ranges of their generating data sets fairly well. The overall quality of fit and the resulting model parameter sets strongly depend on the particular choice of the distance metric used for the stochastic model. We suggest the use of the hypocentral distance metric for the stochastic Simulation of strong ground motion because it provides the lowest-misfit stochastic models for most empirical equations. This is in agreement with the results of two recent studies of hypocenter locations in finite-source models which indicate that hypocenters are often located close to regions of large slip (Mai et al., 2005; Manighetti et al., 2005). Because essentially all empirical ground-motion prediction equations contain data from different geographical regions, the model parameters corresponding to the lowest-misfit stochastic models cannot necessarily be expected to represent single, physically realizable host regions but to model the generating data sets in an average way. In addition, the differences between the lowest-misfit stochastic models and the empirical ground-motion prediction equation are strongly distance, magnitude, and frequency dependent, which, according to the laws of uncertainty propagation, will increase the variance of the corresponding hybrid empirical model predictions (Scherbaum et al., 2005). As a consequence, the selection of empirical ground-motion models for host-to-target-region conversions requires considerable judgment of the ground-motion analyst
The PEGASOS project was a major international seismic hazard study, one of the largest ever conducted anywhere in the world, to assess seismic hazard at four nuclear power plant sites in Switzerland. Before the report of this project has become publicly available, a paper attacking both methodology and results has appeared. Since the general scientific readership may have difficulty in assessing this attack in the absence of the report being attacked, we supply a response in the present paper. The bulk of the attack, besides some misconceived arguments about the role of uncertainties in seismic hazard analysis, is carried by some exercises that purport to be validation exercises. In practice, they are no such thing; they are merely independent sets of hazard calculations based on varying assumptions and procedures, often rather questionable, which come up with various different answers which have no particular significance. (C) 2005 Elsevier B.V. All rights reserved
Composite ground-motion models and logic trees: Methodology, sensitivities, and uncertainties
(2005)
Logic trees have become a popular tool in seismic hazard studies. Commonly, the models corresponding to the end branches of the complete logic tree in a probabalistic seismic hazard analysis (PSHA) are treated separately until the final calculation of the set of hazard curves. This comes at the price that information regarding sensitivities and uncertainties in the ground-motion sections of the logic tree are only obtainable after disaggregation. Furthermore, from this end-branch model perspective even the designers of the logic tree cannot directly tell what ground-motion scenarios most likely would result from their logic trees for a given earthquake at a particular distance, nor how uncertain these scenarios might be or how they would be affected by the choices of the hazard analyst. On the other hand, all this information is already implicitly present in the logic tree. Therefore, with the ground-motion perspective that we propose in the present article, we treat the ground-motion sections of a complete logic tree for seismic hazard as a single composite model representing the complete state-of-knowledge-and-belief of a particular analyst on ground motion in a particular target region. We implement this view by resampling the ground-motion models represented in the ground-motion sections of the logic tree by Monte Carlo simulation (separately for the median values and the sigma values) and then recombining the sets of simulated values in proportion to their logic-tree branch weights. The quantiles of this resampled composite model provide the hazard analyst and the decision maker with a simple, clear, and quantitative representation of the overall physical meaning of the ground-motion section of a logic tree and the accompanying epistemic uncertainty. Quantiles of the composite model also provide an easy way to analyze the sensitivities and uncertainties related to a given logic-tree model. We illustrate this for a composite ground- motion model for central Europe. Further potential fields of applications are seen wherever individual best estimates of ground motion have to be derived from a set of candidate models, for example, for hazard rnaps, sensitivity studies, or for modeling scenario earthquakes
Logic trees are widely used in probabilistic seismic hazard analysis as a tool to capture the epistemic uncertainty associated with the seismogenic sources and the ground-motion prediction models used in estimating the hazard. Combining two or more ground-motion relations within a logic tree will generally require several conversions to be made, because there are several definitions available for both the predicted ground-motion parameters and the explanatory parameters within the predictive ground-motion relations. Procedures for making conversions for each of these factors are presented, using a suite of predictive equations in current use for illustration. The sensitivity of the resulting ground-motion models to these conversions is shown to be pronounced for some of the parameters, especially the measure of source-to-site distance, highlighting the need to take into account any incompatibilities among the selected equations. Procedures are also presented for assigning weights to the branches in the ground-motion section of the logic tree in a transparent fashion, considering both intrinsic merits of the individual equations and their degree of applicability to the particular application
One of the major challenges in engineering seismology is the reliable prediction of site-specific ground motion for particular earthquakes, observed at specific distances. For larger events, a special problem arises, at short distances, with the source-to-site distance measure, because distance metrics based on a point-source model are no longer appropriate. As a consequence, different attenuation relations differ in the distance metric that they use. In addition to being a source of confusion, this causes problems to quantitatively compare or combine different ground- motion models; for example, in the context of Probabilistic Seismic Hazard Assessment, in cases where ground-motion models with different distance metrics occupy neighboring branches of a logic tree. In such a situation, very crude assumptions about source sizes and orientations often have to be used to be able to derive an estimate of the particular metric required. Even if this solves the problem of providing a number to put into the attenuation relation, a serious problem remains. When converting distance measures, the corresponding uncertainties map onto the estimated ground motions according to the laws of error propagation. To make matters worse, conversion of distance metrics can cause the uncertainties of the adapted ground-motion model to become magnitude and distance dependent, even if they are not in the original relation. To be able to treat this problem quantitatively, the variability increase caused by the distance metric conversion has to be quantified. For this purpose, we have used well established scaling laws to determine explicit distance conversion relations using regression analysis on simulated data. We demonstrate that, for all practical purposes, most popular distance metrics can be related to the Joyner-Boore distance using models based on gamma distributions to express the shape of some "residual function." The functional forms are magnitude and distance dependent and are expressed as polynomials. We compare the performance of these relations with manually derived individual distance estimates for the Landers, the Imperial Valley, and the Chi-Chi earthquakes
The use of ground-motion-prediction equations to estimate ground shaking has become a very popular approach for seismic-hazard assessment, especially in the framework of a logic-tree approach. Owing to the large number of existing published ground-motion models, however, the selection and ranking of appropriate models for a particular target area often pose serious practical problems. Here we show how observed around-motion records can help to guide this process in a systematic and comprehensible way. A key element in this context is a new, likelihood based, goodness-of-fit measure that has the property not only to quantify the model fit but also to measure in some degree how well the underlying statistical model assumptions are met. By design, this measure naturally scales between 0 and 1, with a value of 0.5 for a situation in which the model perfectly matches the sample distribution both in terms of mean and standard deviation. We have used it in combination with other goodness-of-fit measures to derive a simple classification scheme to quantify how well a candidate ground-rnotion-prediction equation models a particular set of observed-response spectra. This scheme is demonstrated to perform well in recognizing a number of popular ground-motion models from their rock-site- recording, subsets. This indicates its potential for aiding the assignment of logic-tree weights in a consistent and reproducible way. We have applied our scheme to the border region of France, Germany, and Switzerland where the M-w 4.8 St. Die earthquake of 22 February 2003 in eastern France recently provided a small set of observed-response spectra. These records are best modeled by the ground-motion-prediction equation of Berge-Thierry et al. (2003), which is based on the analysis of predominantly European data. The fact that the Swiss model of Bay et al. (2003) is not able to model the observed records in an acceptable way may indicate general problems arising from the use of weak-motion data for strong-motion prediction