Hard as a rock? Looking for typical and atypical reference sites in the Greek network

Author(s):  
Olga-Joan Ktenidou ◽  
Faidra Gkika ◽  
Erion-Vasilis Pikoulis ◽  
Christos Evangelidis

<p>Although it is nowadays desirable and even typical to characterise site conditions in detail at modern recording stations, this is not yet a general rule in Greece, due to the large number and geographical dispersion of stations. Indeed, most of them are still characterised merely through geological descriptions or proxy-based parameters, rather than through in-situ measurements. Considering: 1. the progress made in recent years with sophisticated ground motion models and the need to define region-specific rock conditions based on data, 2. the move towards large open-access strong-motion databases that require detailed site metadata, and 3. that Greek-provenance recordings represent a significant portion of European seismic data, there are many reasons to improve our understanding of site response at these stations. Moreover, it has been shown recently in several regions that even sites considered as rock can exhibit amplification and ground motion variability, which has given rise to more scientific research into the definition of reference sites. For Greece, in-situ-characterisation campaigns for the entire network would impose unattainable time/budget constraints; so, instead, we implement alternative empirical approaches using the recordings themselves, such as the horizontal-to-vertical spectral ratio technique and its variability. We present examples of 'well-behaved', typical rock sites, and others whose response diverges from what is assumed for their class.</p><p> </p>

2021 ◽  
Author(s):  
Claudia Mascandola ◽  
Giovanni Lanzano ◽  
Francesca Pacor

<p>The rapid increase of seismic waveforms, due to the increment of seismic stations and continuous real-time streaming to data centres, leads to the need for automatic procedures aimed at supporting data processing and data quality control. In this study, we propose a semi-automatic procedure for the consistency check of large strong-motion datasets, classifying the anomalies observed on the residuals analysis and identifying the possible causes.</p><p>The data collected in the strong-motion databases are usually arranged as parametric tables (called flatfiles), used to disseminate the Intensity Measures (IMs) and the associated metadata of the processed waveforms. This is the current practice for the ITalian ACcelerometric Archive (ITACA, D’Amico et al., 2020) and Engineering Strong Motion (ESM; Lanzano et al. 2019a) databases. The adopted criteria for flatfile compilation are designed to collect IMs and related metadata in a uniform, updated, and traceable way, with the aim of providing datasets useful to develop Ground Motion Models (GMMs) for Probabilistic Seismic Hazard Assessment (PSHA) and engineering applications. Therefore, the consistency check of the flatfiles is a crucial task to improve the quality of the products provided by the waveform services.</p><p>The proposed procedure is based on the residual distributions obtained from ad-hoc ground motion prediction equations for the ordinates of the 5% damped acceleration response spectra. In this study, we focus on the active shallow crust events in ITACA, considering the ITA18 ground motion model (Lanzano et al., 2019b) as a reference for Italy. The total residuals, computed as logarithm difference between observations and predictions, are decomposed in between-event, between-station and event-and-station corrected residuals by applying a mixed-effect regression (Bates et al., 2015). This is the common practice for the (partial) removal of the ergodic assumption in empirical GMMs (e.g., Stafford 2014), where the contribution of the systematic corrective effects of event and station on aleatory variability are identified and shifted to the epistemic uncertainty. Afterward, the proposed procedure is applied to raise a warning in case of anomalous residual values. Warnings are provided when the normalized residuals exceed a certain threshold, in three ranges of periods (i.e., 0.01-0.15 s, 0.15-1 s, 1-5 s). The causes of warnings may be several and may concern the event, the site, the waveform, or a combination of them. Among the possible sources of anomalous trends, the more common are: preliminary or inaccurate event localization or magnitude, wrong soil category assigned based on proxies, misleading tectonic regime assigned to the earthquake, and fault directivity that may cause strong-ground motion amplification in certain directions. Warnings may also raise for peculiarities in the site-response (e.g., large amplifications/de-amplifications at certain frequency-bands) and to the occurrence of near-source effects in the waveforms (see Pacor et al., 2018). Based on the raised warnings, a decision tree classifier is developed to identify the common anomaly sources and to support the consistency check of the semi-automatic procedure.</p><p>This study may help to enhance the waveform services and related products, besides reducing the variability of ground motion models and guiding decisions for site characterization studies and network maintenance.</p>


2021 ◽  
Author(s):  
Jaleena Sunny ◽  
Marco De Angelis ◽  
Ben Edwards

<p>The selection and ranking of  Ground Motion Models (GMMs) for scenario earthquakes is a crucial element in seismic hazard analysis. Typically model testing and ranking do not appropriately account for uncertainties, thus leading to improper ranking. We introduce the stochastic area metric (AM) as a scoring metric for GMMs, which not only informs the analyst of the degree to which observed or test data fit the model but also considers the uncertainties without the assumption of how data are distributed. The AM can be used as a scoring metric or cost function, whose minimum value identifies the model that best fits a given dataset. We apply this metric along with existing testing methods to recent and commonly used European ground motion prediction equations: Bindi et al. (2014, B014), Akkar et al. (2014, A014) and Cauzzi et al. (2015, C015). The GMMs are ranked and their performance analysed against the European Engineering Strong Motion (ESM) dataset. We focus on the ranking of models for ranges of magnitude and distance with sparse data, which pose a specific problem with other statistical testing methods. The performance of models over different ranges of magnitude and distance were analysed using AM, revealing the importance of considering different models for specific applications (e.g., tectonic, induced). We find the A014 model displays good performance with complete dataset while B014 appears to be best for small magnitudes and distances. In addition, we calibrated GMMs derived from a compendium of data and generated a suite of models for the given region through an optimisation technique utilising the concept of AM and ground motion variability. This novel framework for ranking and calibration guides the informed selection of models and helps develop regionally adjusted and application-specific GMMs for better prediction. </p><p> </p>


2019 ◽  
Vol 35 (2) ◽  
pp. 883-905 ◽  
Author(s):  
Marco Pilz ◽  
Fabrice Cotton

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.


2021 ◽  
pp. 875529302098802
Author(s):  
Chuanbin Zhu ◽  
Graeme Weatherill ◽  
Fabrice Cotton ◽  
Marco Pilz ◽  
Dong Youp Kwak ◽  
...  

This article describes an open-source site database for a total number of 1742 earthquake recording sites in the K-NET (Kyoshin network) and KiK-net (Kiban Kyoshin network) networks in Japan. This database contains site characterization parameters directly derived from available velocity profiles, including average wave velocities, bedrock depths, and velocity contrast. Meanwhile, it also consists of earthquake horizontal-to-vertical spectral ratio (HVSR) and peak parameters, for example, peak frequency, amplitude, width, and prominence. In addition, the site database also comprises topographic and geological proxies inferred from regional models or maps. Each parameter is derived in a consistent manner for all sites. This site database can benefit the application of machine learning techniques in studies on site amplification. Besides, it can facilitate, for instances, the search of the optimal site parameter(s) for the prediction of site amplification, the development and testing of ground-motion models or methodologies, as well as investigations on spatial or regional variability in site response. All resources (the site database, earthquake HVSR data at all sites, and the MATLAB script for peak identification) can be freely accessed via: https://doi.org/10.5880/GFZ.2.1.2020.006


2021 ◽  
Author(s):  
Sreeram Reddy Kotha ◽  
Dino Bindi ◽  
Fabrice Cotton

Abstract Typical ground-motion models predict the response spectral ordinates (GMM-SA), which are the damped responses of a suite of single-degree-of-freedom oscillators. Response spectra represent the response of an idealized structure to input ground-motion, but not the physics of the actual ground-motion. To complement the regionally adaptable GMM-SA of Kotha et al. (2020), we introduce here a model capable of predicting Fourier amplitudes (GMM-FA); developed from the same Engineering Strong Motion (ESM) dataset for pan-Europe. This GMM-FA reveals the very high variability of high frequency ground-motions, which are completely masked in a GMM-SA. By maintaining the development strategies of GMM-FA identical to that of the GMM-SA, we are able to evaluate the physical meaning of the spatial variability of anelastic attenuation and source characteristics. We find that a fully data-driven geospatial index, Activity Index (AIx), correlates well with the spatial variability of these physical effects. AIx is a fuzzy combination of seismicity and crustal parameters, and can be used to adapt the attenuation and source non-ergodicity of the GMM-FA to regions and tectonic localities sparsely sampled in ESM. While AIx, and a few other parameters we touch upon, may help understand the spatial variability of high frequency attenuation and source effects, the high frequency site-response variability - dominating the overall aleatory variance - is yet unresolvable. With the rapid increase in quantity and quality of ground-motion datasets, we call for an upgrade of regionalization techniques, site-characterisation, and a paradigm shift to Fourier ground-motion models to complement the traditional response spectra prediction models.


Geosciences ◽  
2021 ◽  
Vol 11 (5) ◽  
pp. 186
Author(s):  
Alessandro Todrani ◽  
Giovanna Cultrera

On 24 August 2016, a Mw 6.0 earthquake started a damaging seismic sequence in central Italy. The historical center of Amatrice village reached the XI degree (MCS scale) but the high vulnerability alone could not explain the heavy damage. Unfortunately, at the time of the earthquake only AMT station, 200 m away from the downtown, recorded the mainshock, whereas tens of temporary stations were installed afterwards. We propose a method to simulate the ground motion affecting Amatrice, using the FFT amplitude recorded at AMT, which has been modified by the standard spectral ratio (SSR) computed at 14 seismic stations in downtown. We tested the procedure by comparing simulations and recordings of two later mainshocks (Mw 5.9 and Mw 6.5), underlining advantages and limits of the technique. The strong motion variability of simulations was related to the proximity of the seismic source, accounted for by the ground motion at AMT, and to the peculiar site effects, described by the transfer function at the sites. The largest amplification characterized the stations close to the NE hill edge and produced simulated values of intensity measures clearly above one standard deviation of the GMM expected for Italy, up to 1.6 g for PGA.


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.


2015 ◽  
Vol 31 (3) ◽  
pp. 1629-1645 ◽  
Author(s):  
Ronnie Kamai ◽  
Norman Abrahamson

We evaluate how much of the fling effect is removed from the NGA database and accompanying GMPEs due to standard strong motion processing. The analysis uses a large set of finite-fault simulations, processed with four different high-pass filter corners, representing the distribution within the PEER ground motion database. The effects of processing on the average horizontal component, the vertical component, and peak ground motion values are evaluated by taking the ratio between unprocessed and processed values. The results show that PGA, PGV, and other spectral values are not significantly affected by processing, partly thanks to the maximum period constraint used when developing the NGA GMPEs, but that the bias in peak ground displacement should not be ignored.


Author(s):  
Paul Somerville

This paper reviews concepts and trends in seismic hazard characterization that have emerged in the past decade, and identifies trends and concepts that are anticipated during the coming decade. New methods have been developed for characterizing potential earthquake sources that use geological and geodetic data in conjunction with historical seismicity data. Scaling relationships among earthquake source parameters have been developed to provide a more detailed representation of the earthquake source for ground motion prediction. Improved empirical ground motion models have been derived from a strong motion data set that has grown markedly over the past decade. However, these empirical models have a large degree of uncertainty because the magnitude - distance - soil category parameterization of these models often oversimplifies reality. This reflects the fact that other conditions that are known to have an important influence on strong ground motions, such as near- fault rupture directivity effects, crustal waveguide effects, and basin response effects, are not treated as parameters of these simple models. Numerical ground motion models based on seismological theory that include these additional effects have been developed and extensively validated against recorded ground motions, and used to estimate the ground motions of past earthquakes and predict the ground motions of future scenario earthquakes. The probabilistic approach to characterizing the ground motion that a given site will experience in the future is very compatible with current trends in earthquake engineering and the development of building codes. Performance based design requires a more comprehensive representation of ground motions than has conventionally been used. Ground motions estimates are needed at multiple annual probability levels, and may need to be specified not only by response spectra but also by suites of strong motion time histories for input into time-domain non-linear analyses of structures.


1991 ◽  
Vol 7 (4) ◽  
pp. 551-561 ◽  
Author(s):  
Antonio Rovelli ◽  
Shri K. Singh ◽  
Luca Malagnini ◽  
Alessandro Amato ◽  
Massimo Cocco

We explore the feasibility of the use of microtremors in estimating the amplification of seismic waves at soft sites in Italy. Microtremors were measured at three soft sites and nearby hard sites at night when the cultural noise was minimum. These soft sites were selected as those showing the largest amplifications of ground motion during earthquakes as compared to the records on the hard sites or with respect to the predicted spectra. We compare the soft-to-hard site microtremor spectral ratios with the corresponding acceleration spectral ratios. A rough estimate of the shape and level of spectral amplification is obtained from the microtremor data in all three cases. However, the details of the soft-to-hard site spectral ratio are not reproduced and some differences appear in (a) the frequency at which the maximum amplification occurs, and (b) the bandwidth of the significant amplification. More testing of the method is needed before its wider use for microzonation in Italy can be recommended.


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