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In this work, we analyse continuous measurements of microseisms to assess the reliability of the fundamental resonance frequency estimated by means of the horizontal-to-vertical (H/V) spectral ratio within the 0.1-1 Hz frequency range, using short-period sensors (natural period of 1 s). We apply the H/V technique to recordings of stations installed in two alluvial basins with different sedimentary cover thicknesses-the Lower Rhine Embayment (Germany) and the Gubbio Plain (Central Italy). The spectral ratios are estimated over the time-frequency domain, and we discuss the reliability of the results considering both the variability of the microseism activity and the amplitude of the instrumental noise. We show that microseisms measured by short period sensors allow the retrieval of fundamental resonance frequencies greater than about 0.1-0.2 Hz, with this lower frequency bound depending on the relative amplitude of the microseism signal and the self-noise of the instruments. In particular, we show an example where the considered short-period sensor is connected to instruments characterized by an instrumental noise level which allows detecting only fundamental frequencies greater than about 0.4 Hz. Since the frequency at which the peak of the H/V spectral ratio is biased depends upon the seismic signal-to-instrument noise ratio, the power spectral amplitude of instrumental self- noise should be always considered when interpreting the frequency of the peak as the fundamental resonance frequency of the investigated site.
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.
P>Computing the magnitude of an earthquake requires correcting for the propagation effects from the source to the receivers. This is often accomplished by performing numerical simulations using a suitable Earth model. In this work, the energy magnitude M(e) is considered and its determination is performed using theoretical spectral amplitude decay functions over teleseismic distances based on the global Earth model AK135Q. Since the high frequency part (above the corner frequency) of the source spectrum has to be considered in computing M(e), the influence of propagation and site effects may not be negligible and they could bias the single station M(e) estimations. Therefore, in this study we assess the inter- and intrastation distributions of errors by considering the M(e) residuals computed for a large data set of earthquakes recorded at teleseismic distances by seismic stations deployed worldwide. To separate the inter- and intrastation contribution of errors, we apply a maximum likelihood approach to the M(e) residuals. We show that the interstation errors (describing a sort of site effect for a station) are within +/- 0.2 magnitude units for most stations and their spatial distribution reflects the expected lateral variation affecting the velocity and attenuation of the Earth's structure in the uppermost layers, not accounted for by the 1-D AK135Q model. The variance of the intrastation error distribution (describing the record-to-record component of variability) is larger than the interstation one (0.240 against 0.159), and the spatial distribution of the errors is not random but shows specific patterns depending on the source-to-station paths. The set of coefficients empirically determined may be used in the future to account for the heterogeneities of the real Earth not considered in the theoretical calculations of the spectral amplitude decay functions used to correct the recorded data for propagation effects.
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.
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.
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 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.
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.
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.
In this study, we analyzed 10 yrs of seismicity in central Italy from 2008 to 2017, a period witnessing more than 1400 earthquakes in the magnitude range 2.5≤Mw≤6.5. The data set includes the main sequences that have occurred in the area, including those associated with the 2009 Mw 6.3 L'Aquila earthquake and the 2016–2017 sequence (Mw 6.2 Amatrice, Mw 6.1 Visso, and Mw 6.5 Norcia earthquakes). We calibrated a local magnitude scale, investigating the impact of changing the reference distance at which the nonparametric attenuation is tied to the zero‐magnitude attenuation function for southern California. We also developed an attenuation model to compute the radiated seismic energy (Es) from the time integral of the squared ground‐motion velocity. Seismic moment (M0) and stress drop (Δσ) were estimated for each earthquake by fitting a ω‐square model to the source spectra obtained by applying a nonparametric spectral inversion. The Δσ‐values vary over three orders of magnitude from about 0.1 to 10 MPa, the larger values associated with the mainshocks. The Δσ‐values describe a lognormal distribution with mean and standard deviation equal to log(Δσ)=(−0.25±0.45) (i.e., the mean Δσ is 0.57 MPa, with a 95% confidence interval from 0.08 to 4.79 MPa). The Δσ variability introduces a spread in the distribution of seismic energy versus moment, with differences in energy up two orders of magnitudes for earthquakes with the same moment. The variability in the high‐frequency spectral levels is captured by the local magnitude (ML), which scales with radiated energy as ML=(−1.59+0.52logEs) for logEs≤10.26 and ML=(−1.38+0.50logEs) otherwise. As the peak ground velocity increases with increasing Δσ, local and energy magnitudes perform better than moment magnitude as predictors for the shaking potential. The availability of different magnitude scales and source parameters for a large earthquake population will help characterize the between‐event ground‐motion variability in central Italy.