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Abstract We present horizontal ground motion predictions at a soft site in the Kumamoto alluvial plain for the Mj 5.9 and Mj 6.5 Kumamoto earthquakes of April 2016, in the framework of an international blind prediction exercise. Such predictions were obtained by leveraging all available information which included: (i) analysis of earthquake ground motions; (ii) processing of ambient vibration data (AMV); and (iii) 1D ground response analysis. Spectral analysis of earthquake ground-motion data were used to obtain empirical estimates of the prediction site amplification function, with evidence of an amplification peak at about 1.2 Hz. Horizontal-to-vertical spectral ratio analysis of AMV confirmed this resonance frequency and pointed out also a low-frequency resonance around 0.3 Hz at the prediction site. AMV were then processed by cross-correlation, modified spatial autocorrelation and high-resolution beamforming methods to retrieve the 1D shear-wave velocity (Vs) structure at the prediction site by joint inversion of surface-wave dispersion and ellipticity curves. The use of low frequency dispersion curve and ellipticity data allowed to retrieve a reference Vs profile down to few thousand meters depth which was then used to perform 1D equivalent-linear simulations of the M 5.9 event, and both equivalent-linear and nonlinear simulations of the M 6.5 event at the target site. Adopting quantitative goodness-of-fit metrics based on time–frequency representation of the signals, we obtained fair-to-good agreement between 1D predictions and observations for the Mj 6.5 earthquake and a poor agreement for the Mj 5.9 earthquake. In terms of acceleration response spectra, while ground-motion overpredictions were obtained for the Mj 5.9 event, simulated ground motions for the Mj 6.5 earthquake severely underestimate the observations, especially those obtained by the nonlinear approach. Graphical Abstract

We present horizontal ground motion predictions at a soft site in the Kumamoto alluvial plain for the Mj 5.9 and Mj 6.5 Kumamoto earthquakes of April 2016, in the framework of an international blind prediction exercise. Such predictions were obtained by leveraging all available information which included: (i) analysis of earthquake ground motions; (ii) processing of ambient vibration data (AMV); and (iii) 1D ground response analysis. Spectral analysis of earthquake ground-motion data were used to obtain empirical estimates of the prediction site amplification function, with evidence of an amplification peak at about 1.2 Hz. Horizontal-to-vertical spectral ratio analysis of AMV confirmed this resonance frequency and pointed out also a low-frequency resonance around 0.3 Hz at the prediction site. AMV were then processed by cross-correlation, modified spatial autocorrelation and high-resolution beamforming methods to retrieve the 1D shear-wave velocity (Vs) structure at the prediction site by joint inversion of surface-wave dispersion and ellipticity curves. The use of low frequency dispersion curve and ellipticity data allowed to retrieve a reference Vs profile down to few thousand meters depth which was then used to perform 1D equivalent-linear simulations of the M 5.9 event, and both equivalent-linear and nonlinear simulations of the M 6.5 event at the target site. Adopting quantitative goodness-of-fit metrics based on time–frequency representation of the signals, we obtained fair-to-good agreement between 1D predictions and observations for the Mj 6.5 earthquake and a poor agreement for the Mj 5.9 earthquake. In terms of acceleration response spectra, while ground-motion overpredictions were obtained for the Mj 5.9 event, simulated ground motions for the Mj 6.5 earthquake severely underestimate the observations, especially those obtained by the nonlinear approach. [ABSTRACT FROM AUTHOR]

The geotechnical industry has widely adopted the refraction microtremor shear-wave velocity measurement technique, which is accepted by building authorities for evaluation of seismic site class around the world. Clark County and the City of Henderson, Nevada, populated their Earthquake Parcel Map with over 10,000 site measurements for building code enforcement, made over a 3-year period. 2D refraction microtremor analysis now allows engineers to image lateral shear-wave velocity variations and do passive subsurface imaging. Along with experience at a basic level, the ability to identify the "no energy area" and the "minimum-velocity envelope" on the slowness-frequency (p-f) image helps practitioners to assess the quality of their ReMi data and analysis. Guides for grading (p-f) image quality, and for estimating depth sensitivity, velocity-depth tradeoffs, and depth and velocity resolution also assist practitioners in deciding whether their refraction microtremor data will meet their investigation objectives. Commercial refraction microtremor surveys use linear arrays, and a new criterion of 2.2% minimum microtremor energy in the array direction allows users to assess the likelihood of correct results. Unfortunately, any useful and popular measurement technique can be abused. Practitioners must follow correct data collection, analysis, interpretation, and measurement procedures, or the results cannot be labeled "refraction microtremor" or "ReMi" results. We present some of the common mistakes and provide solutions with the objective of establishing a "best practices" template for getting consistent, reliable models from refraction microtremor measurements. [ABSTRACT FROM AUTHOR]

We present three case studies from recent site investigations that have utilised geophysical data to supplement traditional geotechnical investigations. The refraction microtremor (ReMi) method, which measures the shear-wave velocity of the subsurface soil profile, is used to enhance our overall understanding of geotechnical site conditions. Interpolation of the closely spaced one-dimensional velocity-depth profiles along linear arrays allows two- or three-dimensional velocity-versus-depth representations to be produced, thereby mapping lateral variations and extending subsurface characterisations between more expensive spot borehole measurements. The ReMi technique provides a non-invasive and cost-effective way of estimating vertical soil/rock shear-wave versus depth profiles and therefore is an effective reconnaissance tool for targeting key areas for further, more expensive intrusive investigation method. This paper examines the contribution ReMi shear-wave velocity assessments can make towards enhancing subsurface geological and geotechnical models to mitigate risk from unforeseen ground conditions. Case studies demonstrate the benefits of incorporating the shear-wave velocity estimates from ReMi into the geotechnical investigations. These include identifying the thickness of basalt flows, identifying the location of buried stream channels, characterising palaeo-topographical features, identifying areas of low velocity which may be prone to liquefaction, and assessing the thickness and velocity variations within geological units between borehole and test pit locations. The objective is not to replace traditional geotechnical investigations but allow more meaningful ground models to be developed. [ABSTRACT FROM AUTHOR]

The Eastern United States (EUS) has a complex geological history and hosts several seismic active regions. We investigate the subsurface structure beneath the broader EUS. To produce reliable images of the subsurface, we simultaneously invert smoothed P‐wave receiver functions, Rayleigh‐wave phase and group velocity measurements, and Bouguer gravity observations for the 3D shear‐wave speed. Using surface‐wave observations (3–250 s) and spatially smoothed receiver functions, our velocity models are robust, reliable, and rich in detail. The shear‐wave velocity models fit all three types of observations well. The resulting velocity model for the eastern U.S. shows thinner crust beneath New England, the east coast, and the Mississippi Embayment (ME). A relatively thicker crust was found beneath the stable North America craton. A relatively slower upper mantle was imaged beneath New England, the east coast, and western ME. A comparison of crust thickness derived from our model against four recent published models shows first‐order consistency. A relatively small upper mantle low‐speed region correlates with a published P‐wave analysis that has associated the anomaly with a 75 Ma kimberlite volcanic site in Kentucky. We also explored the relationship between the subsurface structure and seismicity in the eastern U.S. We found that earthquakes often locate near regions with seismic velocity variations, but not universally. Not all regions of significant subsurface wave speed changes are loci of seismicity. A weak correlation between upper mantle shear velocity and earthquake focal mechanism has been observed. Plain Language Summary: The Eastern United States (EUS) experienced a complex series of geological activities. Earthquakes in the EUS have been recorded at several localized regions. A detailed subsurface structure can help us recover the geological history and studying earthquakes. We use multiple types of geophysical observations to reliably image the subsurface. Our images of the subsurface confirmed many findings from previous studies. The crust is thinner beneath New England, the east coast, and the southcentral United States. The interior of North America has a thicker crust. The upper mantle seismic speed is shower beneath New England, the east coast, and the western portion of the southcentral United States. A smaller region of slower upper mantle speed in Kentucky agrees with a published study, which linked the slower speed with a 75 Ma volcanic site. We compared images of subsurface against earthquake locations. Earthquakes often locate near regions with lateral subsurface structure changes. Lateral subsurface structure changes do not always collocate with earthquakes. The type (faulting) of earthquakes weakly correlates with the upper mantle seismic speed. Key Points: Inverting smoothed receiver functions, surface‐wave dispersion, and gravity for a 3D shear‐wave velocity model for the eastern USOur velocity model is broadly consistent with published results for the regionEarthquakes often but not universally locate near areas with seismic speed variation, but not all velocity changes are loci of seismicity [ABSTRACT FROM AUTHOR]

Abstract The Eastern United States (EUS) has a complex geological history and hosts several seismic active regions. We investigate the subsurface structure beneath the broader EUS. To produce reliable images of the subsurface, we simultaneously invert smoothed P‐wave receiver functions, Rayleigh‐wave phase and group velocity measurements, and Bouguer gravity observations for the 3D shear‐wave speed. Using surface‐wave observations (3–250 s) and spatially smoothed receiver functions, our velocity models are robust, reliable, and rich in detail. The shear‐wave velocity models fit all three types of observations well. The resulting velocity model for the eastern U.S. shows thinner crust beneath New England, the east coast, and the Mississippi Embayment (ME). A relatively thicker crust was found beneath the stable North America craton. A relatively slower upper mantle was imaged beneath New England, the east coast, and western ME. A comparison of crust thickness derived from our model against four recent published models shows first‐order consistency. A relatively small upper mantle low‐speed region correlates with a published P‐wave analysis that has associated the anomaly with a 75 Ma kimberlite volcanic site in Kentucky. We also explored the relationship between the subsurface structure and seismicity in the eastern U.S. We found that earthquakes often locate near regions with seismic velocity variations, but not universally. Not all regions of significant subsurface wave speed changes are loci of seismicity. A weak correlation between upper mantle shear velocity and earthquake focal mechanism has been observed.

The stress tensor is an important property for upper crustal studies such as those that involve pore fluids and earthquake hazards. At tectonic plate scale, plate boundary forces and mantle convection are the primary drivers of the stress field. In many local settings (10–100 s of km and <10 km depth) in tectonic plate interiors, we can simplify by assuming a constant background stress field that is perturbed by local heterogeneity in density and elasticity. Local stress orientation and sometimes magnitude can be estimated from earthquake and borehole‐based observations when available. Modeling of the local stress field often involves interpolating sparse observations. We present a new method to estimate the 3D stress field in the upper crust and demonstrate it for Oklahoma. We created a 3D material model by inverting multiple types of geophysical observations simultaneously. Integrating surface‐wave dispersion, local travel times and gravity observations produces a model of P‐wave velocity, S‐wave velocity, and density. The stress field can then be modeled using finite element simulations. The simulations are performed using our simplified view of the local stress field as the sum of a constant background stress field that is perturbed by local density and elasticity heterogeneity and gravitational body forces. An orientation of N82°E, for the maximum compressive tectonic force, best agrees with previously observed stress orientations and faulting types in Oklahoma. The gravitational contribution of the horizontal stress field has a magnitude comparable to the tectonic contribution for the upper 5 km of the subsurface. Key Points: We compute the stress field using finite element modeling by considering contributions from both gravitational and far‐field tectonic forcesWe obtain the orientation and magnitude of the tectonic force by finding the stress field that best‐fits the observed stress observationsGravitational contribution to the horizontal stress field has a comparable magnitude regarding tectonic contribution for the upper 5 km [ABSTRACT FROM AUTHOR]

Surface-wave phase-velocity maps for the full footprint of the USArray Transportable Array (TA) across the conterminous United States are developed and tested. Three-component, long-period continuous seismograms recorded on more than 1800 seismometers, most of which were deployed for 18 months or longer, are processed using a noise cross-correlation technique to derive inter-station Love and Rayleigh dispersion curves at periods between 5 and 40 s. The phase-velocity measurements are quality controlled using an automated algorithm and then used in inversions for Love and Rayleigh phase-velocity models at discrete periods on a 0.25°-by-0.25° pixel grid. The robustness of the results is examined using comparisons of maps derived from subsets of the data. A winter–summer division of the cross-correlation data results in small model differences, indicating relatively minor sensitivity of the results to seasonal variations in the distribution of noise sources. Division of the dispersion data based on inter-station azimuth does not result in geographically coherent model differences, suggesting that azimuthal anisotropy at the regional scale is weak compared with variations in isotropic velocities and does not substantially influence the results for isotropic velocities. The phase-velocity maps and dispersion measurements are documented and made available as data products of the 10-year-long USArray TA deployment. [ABSTRACT FROM AUTHOR]

We have computed group velocities of the fundamental mode of Rayleigh waves along two paths using broadband seismograms of fourteen subduction-zone earthquakes in Mexico. One path crosses the Guerrero terrane while the other traverses the Oaxaca terrane. The dispersion curves have been inverted for crustal structure using genetic and simulated annealing algorithms. Our results show significant differences in crustal structure beneath the Guerrero and the Oaxaca terranes, especially in velocity of the superficial layer and Moho depth. The genetic algorithm (GA) is considerably faster than the simulated annealing algorithm (SA). On the other hand, the SA requires a small computer memory. Another significant advantage of SA is that it reaches a smaller misfit value than GA.

Continuous data recorded on more than 1600 USArray seismic stations operating in the western and central US between 2006 and 2012 are used to map phase velocities of Love and Rayleigh waves at short periods (5-40 s) using a noise-correlation technique. Vertical and transverse records for all station pairs separated by less than 600 km are cross correlated in 4-h-long segments, and the resulting spectra are stacked for the time period of station operation. Dispersion curves are determined from the locations of zeros in the real component of the correlation spectra using a method based on that of Aki (1957). Phase-velocity maps expanded on a 0.25°-by-0.25° pixel grid are estimated by inversion of the phase-velocity measurements. Comparison with predicted phase-velocity maps based on the crustal model CRUST2.0 combined with the mantle model ND08 shows good agreement at the longer periods. Strong slow anomalies (>25%>25%) in the short-period maps are geographically correlated with basins and regions of thick sedimentary cover. The strength of these anomalies is not well predicted by existing crustal-velocity models. [ABSTRACT FROM AUTHOR]

Abstract: Recently it has been found that the performance of surface-wave (SW) sustained microwave discharges can be enhanced by corrugating the dielectric–plasma interface guiding the SW. The present contribution explains this behavior in terms of the SW dispersion as modified by the presence of corrugations. The latter are treated as an anisotropic dielectric medium with effective permittivity tensor governed by the corrugation depth, pitch and dielectric loading ratio 0&#60; γ &#60;1. Closed form SW dispersion equations are introduced. We demonstrate that the corrugations significantly lower the threshold electron density above which SW propagation is possible. Moreover they can reduce the SW group velocity and thus improve the wave–plasma interaction. Additional advantage is that one can custom-tune the SW dispersion and the wave–plasma interaction by controlling the dielectric loading ratio γ. [Copyright &y& Elsevier]