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A ground motion logic tree for seismic hazard analysis in the stable cratonic region of Europe
(2020)
Regions of low seismicity present a particular challenge for probabilistic seismic hazard analysis when identifying suitable ground motion models (GMMs) and quantifying their epistemic uncertainty. The 2020 European Seismic Hazard Model adopts a scaled backbone approach to characterise this uncertainty for shallow seismicity in Europe, incorporating region-to-region source and attenuation variability based on European strong motion data. This approach, however, may not be suited to stable cratonic region of northeastern Europe (encompassing Finland, Sweden and the Baltic countries), where exploration of various global geophysical datasets reveals that its crustal properties are distinctly different from the rest of Europe, and are instead more closely represented by those of the Central and Eastern United States. Building upon the suite of models developed by the recent NGA East project, we construct a new scaled backbone ground motion model and calibrate its corresponding epistemic uncertainties. The resulting logic tree is shown to provide comparable hazard outcomes to the epistemic uncertainty modelling strategy adopted for the Eastern United States, despite the different approaches taken. Comparison with previous GMM selections for northeastern Europe, however, highlights key differences in short period accelerations resulting from new assumptions regarding the characteristics of the reference rock and its influence on site amplification.
The steady increase of ground-motion data not only allows new possibilities but also comes with new challenges in the development of ground-motion models (GMMs). Data classification techniques (e.g., cluster analysis) do not only produce deterministic classifications but also probabilistic classifications (e.g., probabilities for each datum to belong to a given class or cluster). One challenge is the integration of such continuous classification in regressions for GMM development such as the widely used mixed-effects model. We address this issue by introducing an extension of the mixed-effects model to incorporate data weighting. The parameter estimation of the mixed-effects model, that is, fixed-effects coefficients of the GMMs and the random-effects variances, are based on the weighted likelihood function, which also provides analytic uncertainty estimates. The data weighting permits for earthquake classification beyond the classical, expert-driven, binary classification based, for example, on event depth, distance to trench, style of faulting, and fault dip angle. We apply Angular Classification with Expectation-maximization, an algorithm to identify clusters of nodal planes from focal mechanisms to differentiate between, for example, interface- and intraslab-type events. Classification is continuous, that is, no event belongs completely to one class, which is taken into account in the ground-motion modeling. The theoretical framework described in this article allows for a fully automatic calibration of ground-motion models using large databases with automated classification and processing of earthquake and ground-motion data. As an example, we developed a GMM on the basis of the GMM by Montalva et al. (2017) with data from the strong-motion flat file of Bastias and Montalva (2016) with similar to 2400 records from 319 events in the Chilean subduction zone. Our GMM with the data-driven classification is comparable to the expert-classification-based model. Furthermore, the model shows temporal variations of the between-event residuals before and after large earthquakes in the region.
With increasing amount of strong motion data, Ground Motion Prediction Equation (GMPE) developers are able to quantify empirical site amplification functions (delta S2S(s)) from GMPE residuals, for use in site-specific Probabilistic Seismic Hazard Assessment. In this study, we first derive a GMPE for 5% damped Pseudo Spectral Acceleration (g) of Active Shallow Crustal earthquakes in Japan with 3.4 <= M-w <= 7.3 and 0 <= R-JB <= 600km. Using k-mean spectral clustering technique, we then classify our estimated delta S2S(s)(T = 0.01 - 2s) of 588 wellcharacterized sites, into 8 site clusters with distinct mean site amplification functions, and within-cluster site-tosite variability similar to 50% smaller than the overall dataset variability (phi(S2S)). Following an evaluation of existing schemes, we propose a revised data-driven site classification characterized by kernel density distributions of V-s30, V-s10, H-800, and predominant period (T-G) of the site clusters.
A new view of Ecuador's complex geodynamics has been developed in the course of modeling seismic source zones for probabilistic seismic hazard analysis. This study focuses on two aspects of the plates' interaction at a continental scale: (a) age-related differences in rheology between Farallon and Nazca plates—marked by the Grijalva rifted margin and its inland projection—as they subduct underneath central Ecuador, and (b) the rapidly changing convergence obliquity resulting from the convex shape of the South American northwestern continental margin. Both conditions satisfactorily explain several characteristics of the observed seismicity and of the interseismic coupling. Intermediate-depth seismicity reveals a severe flexure in the Farallon slab as it dips and contorts at depth, originating the El Puyo seismic cluster. The two slabs position and geometry below continental Ecuador also correlate with surface expressions observable in the local and regional geology and tectonics. The interseismic coupling is weak and shallow south of the Grijalva rifted margin and increases northward, with a heterogeneous pattern locally associated to the Carnegie ridge subduction. High convergence obliquity is responsible for the North Andean Block northeastward movement along localized fault systems. The Cosanga and Pallatanga fault segments of the North Andean Block-South American boundary concentrate most of the seismic moment release in continental Ecuador. Other inner block faults located along the western border of the inter-Andean Depression also show a high rate of moderate-size earthquake production. Finally, a total of 19 seismic source zones were modeled in accordance with the proposed geodynamic and neotectonic scheme.
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.
The Seismic Hazard Inferred from Tectonics based on the Global Strain Rate Map (SHIFT_GSRM) earthquake forecast was designed to provide high-resolution estimates of global shallow seismicity to be used in seismic hazard assessment. This model combines geodetic strain rates with global earthquake parameters to characterize long-term rates of seismic moment and earthquake activity. Although SHIFT_GSRM properly computes seismicity rates in seismically active continental regions, it underestimates earthquake rates in subduction zones by an average factor of approximately 3. We present a complementary method to SHIFT_GSRM to more accurately forecast earthquake rates in 37 subduction segments, based on the conservation of moment principle and the use of regional interface seismicity parameters, such as subduction dip angles, corner magnitudes, and coupled seismogenic thicknesses. In seven progressive steps, we find that SHIFT_GSRM earthquake-rate underpredictions are mainly due to the utilization of a global probability function of seismic moment release that poorly captures the great variability among subduction megathrust interfaces. Retrospective test results show that the forecast is consistent with the observations during the 1 January 1977 to 31 December 2014 period. Moreover, successful pseudoprospective evaluations for the 1 January 2015 to 31 December 2018 period demonstrate the power of the regionalized earthquake model to properly estimate subduction-zone seismicity.
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.
We analyze the spatiotemporal evolution of seismicity during a sequence of moderate (an M-w 4.7 foreshock and M-w 5.8 mainshock) earthquakes occurring in September 2019 at the transition between a creeping and a locked segment of the North Anatolian fault in the central Sea of Marmara, northwest Turkey. To investigate in detail the seismicity evolution, we apply a matched-filter technique to continuous waveforms, thus reducing the magnitude threshold for detection. Sequences of foreshocks preceding the two largest events are clearly seen, exhibiting two different behaviors: a long-term activation of the seismicity along the entire fault segment and a short-term concentration around the epicenters of the large events. We suggest a two-scale preparation phase, with aseismic slip preparing the mainshock final rupture a few days before, and a cascade mechanism leading to the nucleation of the mainshock. Thus, our study shows a combination of seismic and aseismic slip during the foreshock sequence changing the strength of the fault, bringing it closer to failure.
The mechanisms leading to large earthquakes are poorly understood and documented. Here we characterize the long-term precursory phase of the 1 April 2014 M(w)8.1 North Chile megathrust. We show that a group of coastal GPS stations accelerated westward 8months before the main shock, corresponding to a M(w)6.5 slow slip event on the subduction interface, 80% of which was aseismic. Concurrent interface foreshocks underwent a diminution of their radiation at high frequency, as shown by the temporal evolution of Fourier spectra and residuals with respect to ground motions predicted by recent subduction models. Such ground motions change suggests that in response to the slow sliding of the subduction interface, seismic ruptures are progressively becoming smoother and/or slower. The gradual propagation of seismic ruptures beyond seismic asperities into surrounding metastable areas could explain these observations and might be the precursory mechanism eventually leading to the main shock.
Applying conservation of energy to estimate earthquake frequencies from strain rates and stresses
(2020)
Estimating earthquake occurrence rates from the accumulation rate of seismic moment is an established tool of seismic hazard analysis. We propose an alternative, fault-agnostic approach based on the conservation of energy: the Energy-Conserving Seismicity Framework (ENCOS). Working in energy space has the advantage that the radiated energy is a better predictor of the damage potential of earthquake waves than the seismic moment release. In a region, ENCOS balances the stationary power available to cause earthquakes with the long-term seismic energy release represented by the energy-frequency distribution's first moment. Accumulation and release are connected through the average seismic efficiency, by which we mean the fraction of released energy that is converted into seismic waves. Besides measuring earthquakes in energy, ENCOS differs from moment balance essentially in that the energy accumulation rate depends on the total stress in addition to the strain rate tensor. To validate ENCOS, we exemplarily model the energy-frequency distribution around Southern California. We estimate the energy accumulation rate due to tectonic loading assuming poroelasticity and hydrostasis. Using data from the World Stress Map and assuming the frictional limit to estimate the stress tensor, we obtain a power of 0.8 GW. The uncertainty range, 0.3-2.0GW, originates mainly from the thickness of the seismogenic crust, the friction coefficient on preexisting faults, and models of Global Positioning System (GPS) derived strain rates. Based on a Gutenberg-Richter magnitude-frequency distribution, this power can be distributed over a range of energies consistent with historical earthquake rates and reasonable bounds on the seismic efficiency.
A proper assessment of seismic reference site conditions has important applications as they represent the basis on which ground motions and amplifications are generally computed. Besides accounting for the average S-wave velocity over the uppermost 30 m (V-S30), the parameterization of high-frequency ground motions beyond source-corner frequency received significant attention. kappa, an empirical parameter introduced by Anderson and Hough (1984), is often used to represent the spectral decay of the acceleration spectrum at high frequencies. The lack of hard-rock records and the poor understanding of the physics of kappa introduced significant epistemic uncertainty in the final seismic hazard of recent projects. Thus, determining precise and accurate regional hard-rock kappa(0) values is critical. We propose an alternative procedure for capturing the reference kappa(0) on regional scales by linking thewell-known high-frequency attenuation parameter kappa and the properties of multiple-scattered coda waves. Using geological and geophysical data around more than 1300 stations for separating reference and soft soil sites and based on more than 10,000 crustal earthquake recordings, we observe that kappa(0) from multiple-scattered coda waves seems to be independent of the soil type but correlated with the hard-rock kappa(0), showing significant regional variations across Europe. The values range between 0.004 s for northern Europe and 0.020 s for the southern and southeastern parts. On the other hand, measuring kappa (and correspondingly kappa(0)) on the S-wave window (as classically proposed), the results are strongly affected by transmitted (reflected, refracted, and scattered) waves included in the analyzed window biasing the proper assessment of kappa(0). This effect is more pronounced for soft soil sites. In this way, kappa(coda)(0) can serve as a proxy for the regional hard-rock kappa(0) at the reference sites.
We propose an alternative procedure for the capture of the hard‐rock regional kappa (κ0ref). In our approach, we make use of a potential link between the well‐known κ parameter and the properties of coda waves. In our analysis, we consider near‐distance records of four crustal earthquakes of local magnitude 3.7–4.9 that occurred in four regions of France in different geological contexts: the crystalline axial chain of Pyrenees to the southwest, the large sedimentary basin to the southeast, the Alpine range to the east, and the extensional Rhine graben to the northeast. Each earthquake has been recorded at a pair of nearby soft‐ and hard‐rock station sites. The high‐frequency (16–32 Hz) spectral amplitudes of the coda window (carefully selected on the time series of the accelerograms) confirm an exponential decrease, which we quantify by κAHcoda and call “kappa of coda.” It is found that κAHcoda is independent of the soil type but shows significant regional variations. κ measurements (Anderson and Hough, 1984) over the coda window (κAHcoda) and full time series (κAH) show strong correlation at hard‐rock sites. This suggests that κAHcoda can provide a new proxy to estimate the regional hard rock κ0ref (Ktenidou et al., 2015). Theoretical analysis is also presented to relate the regional κAHcoda and coda quality factor Qc, which quantifies the average attenuation properties of the crust (both scattering and absorption). It allows interpreting κAHcoda as the time spent by the waves in the medium, weighted by its attenuation properties. This theoretical analysis also shows that the classical κ measurement should be frequency dependent; this was confirmed by the spectra of the observed records.
This article presents comparisons among the five ground-motion models described in other articles within this special issue, in terms of data selection criteria, characteristics of the models and predicted peak ground and response spectral accelerations. Comparisons are also made with predictions from the Next Generation Attenuation (NGA) models to which the models presented here have similarities (e.g. a common master database has been used) but also differences (e.g. some models in this issue are nonparametric). As a result of the differing data selection criteria and derivation techniques the predicted median ground motions show considerable differences (up to a factor of two for certain scenarios), particularly for magnitudes and distances close to or beyond the range of the available observations. The predicted influence of style-of-faulting shows much variation among models whereas site amplification factors are more similar, with peak amplification at around 1s. These differences are greater than those among predictions from the NGA models. The models for aleatory variability (sigma), however, are similar and suggest that ground-motion variability from this region is slightly higher than that predicted by the NGA models, based primarily on data from California and Taiwan.
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
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.
Seismic-hazard assessment is of great importance within the field of engineering seismology. Nowadays, it is common practice to define future seismic demands using probabilistic seismic-hazard analysis (PSHA). Often it is neither obvious nor transparent how PSHA responds to changes in its inputs. In addition, PSHA relies on many uncertain inputs. Sensitivity analysis (SA) is concerned with the assessment and quantification of how changes in the model inputs affect the model response and how input uncertainties influence the distribution of the model response. Sensitivity studies are challenging primarily for computational reasons; hence, the development of efficient methods is of major importance. Powerful local (deterministic) methods widely used in other fields can make SA feasible, even for complex models with a large number of inputs; for example, automatic/algorithmic differentiation (AD)-based adjoint methods. Recently developed derivative-based global sensitivity measures can combine the advantages of such local SA methods with efficient sampling strategies facilitating quantitative global sensitivity analysis (GSA) for complex models. In our study, we propose and implement exactly this combination. It allows an upper bounding of the sensitivities involved in PSHA globally and, therefore, an identification of the noninfluential and the most important uncertain inputs. To the best of our knowledge, it is the first time that derivative-based GSA measures are combined with AD in practice. In addition, we show that first-order uncertainty propagation using the delta method can give satisfactory approximations of global sensitivity measures and allow a rough characterization of the model output distribution in the case of PSHA. An illustrative example is shown for the suggested derivative-based GSA of a PSHA that uses stochastic ground-motion simulations.
In this investigation, we examine the uncertainties using the horizontal-to-vertical spectral ratio (HVSR) technique on earthquake recordings to detect site resonant frequencies at 207 KiK-net sites. Our results show that the scenario dependence of response (pseudospectral acceleration) spectral ratio could bias the estimates of resonant frequencies for sites having multiple significant peaks with comparable amplitudes. Thus, the Fourier amplitude spectrum (FAS) should be preferred in computing HVSR. For more than 80% of the investigated sites, the first peak (in the frequency domain) on the average HVSR curve over multiple sites coincides with the highest peak. However, for sites with multiple peaks, the highest peak frequency (f(p)) is less susceptible to the selection criteria of significant peaks and the extent of smoothing to spectrum than the first peak frequency (f(0)). Meanwhile, in comparison to the surface-to-borehole spectral ratio, f(0) tends to underestimate the predominant frequency (at which the largest amplification occurs) more than f(p). In addition, in terms of characterizing linear site response, f(p) shows a better overall performance than f(0). Based on these findings, we thus recommend that seismic network operators provide f(p) on the average HVSRFAS curve as a priority, ideally together with the average HVSRFAS curve in site characterization.
The one-dimensional (1-D) approach is still the dominant method to incorporate site effects in engineering applications. To bridge the 1-D to multidimensional site response analysis, we develop quantitative criteria and a reproducible method to identify KiK-net sites with significant deviations from 1-D behavior. We found that 158 out of 354 show two-dimensional (2-D) and three-dimensional (3-D) effects, extending the resonance toward shorter periods at which 2-D or 3-D site effects exceed those of the classic 1-D configurations and imposing an additional amplification to that caused by the impedance contrast alone. Such 2-D and 3-D effects go along with a large within-station ground motion variability. Remarkably, these effects are found to be more pronounced for small impedance contrasts. While it is hardly possible to identify common features in ground motion behavior for stations with similar topography typologies, it is not over-conservative to apply a safety factor to account for 2-D and 3-D site effects in ground motion modeling.