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The knowledge of the largest expected earthquake magnitude in a region is one of the key issues in probabilistic seismic hazard calculations and the estimation of worst-case scenarios. Earthquake catalogues are the most informative source of information for the inference of earthquake magnitudes. We analysed the earthquake catalogue for Central Asia with respect to the largest expected magnitudes m(T) in a pre-defined time horizon T-f using a recently developed statistical methodology, extended by the explicit probabilistic consideration of magnitude errors. For this aim, we assumed broad error distributions for historical events, whereas the magnitudes of recently recorded instrumental earthquakes had smaller errors. The results indicate high probabilities for the occurrence of large events (M >= 8), even in short time intervals of a few decades. The expected magnitudes relative to the assumed maximum possible magnitude are generally higher for intermediate-depth earthquakes (51-300 km) than for shallow events (0-50 km). For long future time horizons, for example, a few hundred years, earthquakes with M >= 8.5 have to be taken into account, although, apart from the 1889 Chilik earthquake, it is probable that no such event occurred during the observation period of the catalogue.
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.
A temporary seismic network composed of 11 stations was installed in the city of Potenza (Southern Italy) to record local and regional seismicity within the context of a national project funded by the Italian Department of Civil Protection (DPC). Some stations were moved after a certain time in order to increase the number of measurement points, leading to a total of 14 sites within the city by the end of the experiment. Recordings from 26 local earthquakes (M-l 2.2-3.8 ) were analyzed to compute the site responses at the 14 sites by applying both reference and non-reference site techniques. Furthermore, the Spectral Intensity (SI) for each local earthquake, as well as their ratios with respect to the values obtained at a reference site, were also calculated. In addition, a field survey of 233 single station noise measurements within the city was carried out to increase the information available at localities different from the 14 monitoring sites. By using the results of the correlation analysis between the horizontal-to-vertical spectral ratios computed from noise recordings (NHV) at the 14 selected sites and those derived by the single station noise measurements within the town as a proxy, the spectral intensity correction factors for site amplification obtained from earthquake analysis were extended to the entire city area. This procedure allowed us to provide a microzonation map of the urban area that can be directly used when calculating risk scenarios for civil defence purposes. The amplification factors estimated following this approach show values increasing along the main valley toward east where the detrital and alluvial complexes reach their maximum thickness.
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.
To study the applicability of the passive seismic interferometry technique to near-surface geological studies, seismic noise recordings from a small scale 2-D array of seismic stations were performed in the test site of Nauen (Germany). Rayleigh wave Green's functions were estimated for different frequencies. A tomographic inversion of the traveltimes estimated for each frequency from the Green's functions is then performed, allowing the laterally varying 3-D surfacewave velocity structure below the array to be retrieved at engineering-geotechnical scales. Furthermore, a 2-D S-wave velocity cross-section is obtained by combining 1-D velocity structures derived from the inversion of the dispersion curves extracted at several points along a profile where other geophysical analyses were performed. It is shown that the cross-section from passive seismic interferometry provides a clear image of the local structural heterogeneities that are in excellent agreement with georadar and geoelectrical results. Such findings indicate that the interferometry analysis of seismic noise is potentially of great interest for deriving the shallow 3-D velocity structure in urban areas.
The Engineering Strong-Motion (ESM) flatfile is a parametric table which contains verified and reliable metadata and intensity measures of manually processed waveforms included in the ESM database. The flatfile has been developed within the Seismology Thematic Core Service of EPOS-IP (European Plate Observing System Implementation Phase) and it is disseminated throughout a web portal for research and technical purposes. The adopted criteria for flatfile compilation aim to collect strong motion data and related metadata in a uniform, updated, traceable and quality-checked way to develop Ground Motion Models (GMMs) for Probabilistic Seismic Hazard Assessment (PSHA) and engineering applications. In this paper, we present the characteristics of ESM flatfile in terms of recording, event and station distributions, and we discuss the most relevant features of the Intensity Measures (IMs) of engineering interest included in the table. The dataset for flatfile compilation includes 23,014 recordings from 2179 earthquakes and 2080 stations from Europe and Middle-East. The events are characterized by magnitudes in the range 3.5-8.0 and refer to different tectonics regimes, such as shallow active crustal and subduction zones. Intensity measures include peak and integral parameters and duration of each waveform. The spectral amplitudes of the (5% damping) acceleration and displacement response are provided for 36 periods, in the interval 0.01-10 s, as well as the 103 amplitudes of the Fourier spectrum for the frequency range 0.04-50 Hz. Several statistics are shown with reference to the most significant metadata for GMMs calibrations, such as moment magnitude, focal depth, several distance metrics, style of faulting and parameters for site characterization. Furthermore, we also compare and explain the most relevant differences between the metadata of ESM flatfile with those provided by the previous flatfile derived in RESORCE (Reference Database for Seismic Ground Motion in Europe) project.
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.
Shear-waves are the most energetic body-waves radiated from an earthquake, and are responsible for the destruction of engineered structures. In both short-term emergency response and long-term risk forecasting of disaster-resilient built environment, it is critical to predict spatially accurate distribution of shear-wave amplitudes. Although decades’ old theory proposes a deterministic, highly anisotropic, four-lobed shear-wave radiation pattern, from lack of convincing evidence, most empirical ground-shaking prediction models settled for an oversimplified stochastic radiation pattern that is isotropic on average. Today, using the large datasets of uniformly processed seismograms from several strike, normal, reverse, and oblique-slip earthquakes across the globe, compiled specifically for engineering applications, we could reveal, quantify, and calibrate the frequency-, distance-, and style-of-faulting dependent transition of shear-wave radiation between a stochastic-isotropic and a deterministic-anisotropic phenomenon. Consequent recalibration of empirical ground-shaking models dramatically improved their predictions: with isodistant anisotropic variations of ±40%, and 8% reduction in uncertainty. The outcomes presented here can potentially trigger a reappraisal of several practical issues in engineering seismology, particularly in seismic ground-shaking studies and seismic hazard and risk assessment.
Site-Corrected Magnitude- and Region-Dependent Correlations of Horizontal Peak Spectral Amplitudes
(2017)
Empirical correlations of horizontal peak spectral amplitudes (PSA) are modeled using the total-residuals obtained in a ground motion prediction equation (GMPE) regression. Recent GMPEs moved toward partially non-ergodic region-and site-specific predictions, while the residual correlation models remained largely ergodic. Using mixed-effects regression, we decompose the total-residuals of a pan-European GMPE into between-event, between-site, and event-and-site corrected residuals to investigate the ergodicity in empirical PSA correlations. We first observed that the between-event correlations are magnitude-dependent, partially due to the differences in source spectra, and influence of stress-drop parameter on small and large events. Next, removing the between-site residuals from within-event residuals yields the event-and-site corrected residuals which are found to be region-dependent, possibly due to the regional differences in distance-decay of short period PSAs. Using our site-corrected magnitude- and region-dependent correlations, and the between-site residuals as empirical site-specific ground motion adjustments, we compute partially non-ergodic conditional mean spectra at four well-recorded sites in Europe and Middle Eastern regions.
The increasing numbers of recordings at individual sites allows quantification of empirical linear site-response adjustment factors (delta S2S(s)) from the ground motion prediction equation (GMPE) residuals. The delta S2S(s) are then used to linearly scale the ergodic GMPE predictions to obtain site-specific ground motion predictions in a partially non-ergodic Probabilistic Seismic Hazard Assessment (PSHA). To address key statistical and conceptual issues in the current practice, we introduce a novel empirical region-and site-specific PSHA methodology wherein, (1) site-to-site variability (phi(S2S)) is first estimated as a random-variance in a mixed-effects GMPE regression, (2) delta S2S(s) at new sites with strong motion are estimated using the a priori phi(S2S), and (3) the GMPE site-specific single-site aleatory variability sigma(ss,s) is replaced with a generic site-corrected aleatory variability sigma(0). Comparison of region- and site-specific hazard curves from our method against the traditional ergodic estimates at 225 sites in Europe and Middle East shows an approximate 50% difference in predicted ground motions over a range of hazard levels-a strong motivation to increase seismological monitoring of critical facilities and enrich regional ground motion data sets.