Horizontal To Vertical Spectral Ratio Curves Research Articles

3D shear wave velocity imaging of the subsurface structure of granite rocks in the arid climate of Pan de Azúcar, Chile, revealed by Bayesian inversion of HVSR curves

Abstract. Seismic methods are emerging as efficient tools for imaging the subsurface to investigate the weathering zone. The structure of the weathering zone can be identified by differing shear wave velocities as various weathering processes will alter the properties of rocks. Currently, 3D subsurface modelling of the weathering zone is gaining increasing importance as results allow the identification of the weathering imprint in the subsurface not only from top to bottom but also in three dimensions. We investigated the 3D weathering structure of monzogranite bedrock near the Pan de Azúcar National Park (Atacama Desert, northern Chile), where the weathering is weak due to the arid climate conditions. We set up an array measurement that records seismic ambient noise, which we used to extract the horizontal-to-vertical spectral ratio (HVSR) curves. The curves were then used to invert for 1D shear wave velocity (Vs) models, which we then used to compile a pseudo-3D model of the subsurface structure in our study area. To invert the 1D Vs model, we applied a transdimensional hierarchical Bayesian inversion scheme, allowing us to invert the HVSR curve with minimal prior information. The resulting 3D model allowed us to image the granite gradient from the surface down to ca. 50 m depth and confirmed the presence of dikes of mafic composition intruding the granite. We identified three main zones of fractured granite, altered granite, and the granite bedrock in addition to the mafic dikes with relatively higher Vs. The fractured granite layer was identified with Vs of 1.4 km s−1 at 30–40 m depth, while the granite bedrock was delineated with Vs of 2.5 km s−1 and a depth range between 10 and 50 m depth. We compared the resulting subsurface structure to other sites in the Chilean coastal cordillera located in various climatic conditions and found that the weathering depth and structure at a given location depend on a complex interaction between surface processes such as precipitation rate, tectonic uplift and fracturing, and erosion. Moreover, these local geological features such as the intrusion of mafic dikes can create significant spatial variations to the weathering structure and therefore emphasize the importance of 3D imaging of the weathering structure. The imaged structure of the subsurface in Pan de Azúcar provides the unique opportunity to image the heterogeneities of a rock preconditioned for weathering but one that has never experienced extensive weathering given the absence of precipitation.

Determination of the VS profile at a “noisy” industrial site via active and passive data: The critical role of Love waves and the opportunities of multicomponent group velocity analysis

To define the procedures necessary to unambiguously define the subsurface model, a comprehensive set of active and passive seismic data was collected in an industrial area characterized by an extremely high level of background microtremors. Passive data are recorded to define three observables: the dispersion curve of the vertical component of Rayleigh waves via miniature array analysis of microtremors, the Love-wave dispersion curve via extended spatial autocorrelation, and the horizontal-to-vertical spectral ratio (HVSR). Active data used for the holistic analysis of surface waves are extracted from data recorded through a hybrid acquisition procedure accomplished with only two 3C geophones used to simultaneously define the HVSR at two points. Defined observables are combined according to three different approaches: the joint analysis of Rayleigh waves and HVSR, the joint analysis of Rayleigh and Love waves together with the HVSR, and the joint analysis of multicomponent group velocities together with the HVSR and Rayleigh-wave particle motion (RPM) curves. In agreement with the theory, data indicate that, in general, surface-wave modeling cannot be performed considering modal dispersion curves: dispersion obtained from passive data needs to be modeled considering the effective curve, whereas group velocity obtained from active data can be analyzed using the full velocity spectrum technique. Results indicate that joint inversion of Rayleigh-wave dispersion and HVSR does not necessarily ensure the correctness of the obtained S-wave velocity ([Formula: see text]) profile and that Love waves represent a key observable to fully constrain an unambiguous inversion procedure. However, the joint analysis of multicomponent group velocity spectra (from active multicomponent single-offset data) together with the HVSR and RPM curves is a further efficient way to obtain robust [Formula: see text] profiles through the active and passive data obtained by a single 3C geophone.

Preliminary Result: Analysis of Dominant Frequency in Western Part of Java, Indonesia using Hilbert-Huang Transform-HVSR Method

The western part of Java is situated near various geological formations stemming from the collision between the Indo-Australian and Eurasian tectonic plates. These formations include the Java Trench, Sunda Strait, and several active onshore faults, rendering the area susceptible to seismic activity. The dynamic response of the soil to seismic shaking in this region warrants thorough investigation, particularly due to the prevalence of alluvium deposits in certain areas, which have the potential to amplify ground motion. In this research endeavor, seismic data recorded by 81 temporary seismic stations in West Java were utilized. The analysis employed the Hilbert-Huang Transform technique in conjunction with the Horizontal to Vertical Spectral Ratio (HVSR) method to derive the Horizontal-to-Vertical (H/V) spectral response curve for each measurement point. The implementation of the Hilbert-Huang Transform served the purpose of mitigating non-stationary transient noise commonly encountered in urban measurements, thereby enhancing the accuracy of the HVSR curve in portraying the dominant frequency characteristics of the measurement area. The findings of this study reveal that within the western part of Java, the dominant frequency values fall within the range of 0.9 to 7 Hz. Areas exhibiting lower dominant frequencies are indicative of a greater sediment thickness, predominantly observed in the northern region of the western part of Java, the Bandung Basin, some areas surrounding active volcanoes as well as various locales within the province of Banten.

Uncertainty of site period on the variability of the site period-based ground motion prediction equations

Site period has been widely acknowledged to be a reasonable site parameter for ground-motion modeling and site effect modeling. Its value could be analytically calculated using the shear-wave velocity (VS) profile by assuming that soil layers overlie a rigid bedrock, or empirically estimated from the horizontal-to-vertical spectral ratio (HVSR). In this study, we tested the uncertainty of site period on the variability of the site period-based ground-motion prediction equations (GMPEs). The ground-motion records and site data in Japan were used. We first used different VS values as engineering bedrock to derive a set of analytical site periods, and tested the uncertainty because of the bedrock VS selection on the GMPE variability. The results show that adding information about the stiff-soil or soft-rock layer beneath the surface soft-soil layers would significantly improve site effect prediction accuracy. An engineering bedrock with VS equal to about 800 m/s is recommended. We then tested the uncertainty of site period because of the choice between the analytical one and the empirical one on the GMPE variability. The empirical site period is better than the analytical site period at spectral periods from 0.06s to 0.4s. At spectral periods longer than 0.4s, the empirical site period produces larger variability than the analytical one using VS ≥ 800 m/s bedrock and has a better performance than that using VS < 600 m/s bedrock. The larger variability is partly contributed by the uncertainty in identifying site period value from the HVSR curve. Using the site period from the first peak of the HVSR curve generally produces a smaller variability than that from the highest peak. For sites with more than one comparable peak in the HVSR curve, the site period from the first peak is recommended. For the regions out of Japan, cautions may be paid for these recommendations because of the potential region dependence of site response.

Shear-wave velocity imaging of weathered granite in La Campana (Chile) from Bayesian inversion of micro-tremor H/V spectral ratios

Subsurface imaging of the regolith layer is an important tool for weathering zone characterization. For example, the extent of bedrock modification by weathering processes can be modelled by means of differing seismic velocities. We acquired a 360 m-long seismic profile in central Chile to characterise weathering at a semi-arid site. We used 87 3-component geophones, which continuously recorded ambient seismic noise for three days. The seismic line was centered at an 88 m deep borehole, providing core and downhole logging data for calibration. We extract Horizontal-to-Vertical Spectral Ratio (HVSR) curves along the seismic line to image the subsurface. Temporal analysis of the HVSR curves shows that the ambient noise vibrations recorded during the nighttime provide more stable HVSR curves. The trans-dimensional Bayesian Markov chain Monte Carlo (McMC) approach was used to invert the micro-tremor HVSR curves at each station to reconstruct 1D shear-wave velocity (Vs) models. The resulting individual 1D Vs models were merged to create a 2D Vs model along the linear seismic array in La Campana. The resulting Vs model shows an increase from 0.85 km/s at the surface to ca. 2.5 km/s at 100 m depth. We use the interface probability as a by-product of the Bayesian inversion to apply a more data-driven approach in identifying the different weathering layers. This method identified the boundary between saprolite and fractured bedrock at 42 m depth at the borehole, as evidenced by the interpretation of downhole logging data such as magnetic susceptibility. The resulting 2D Vs model of this site in Mediterranean climate shows a strong correlation between the interpreted weathering front at around 90-m depth and a higher precipitation rate in the study site compared to arid sites. The horizontal alignment of the weathering front indicates a correlation between the weathering front depth with topography and fractures in the bedrock.

Monitoring performance of slopes via ambient seismic noise recordings: Case study in a colluvium deposit

Long-term monitoring of slopes is of significance for engineering geology research and geo-disaster prevention. There is a growing need to develop fast, nondestructive and affordable techniques that can detect gradual and cyclic changes inside slopes. For this purpose, we propose a fast and low-cost computational framework based on processing the single-point ambient seismic noise recordings by the horizontal-to-vertical spectral ratio (HVSR) method. To test the efficiency of the proposed framework, we conduct a demonstration study in a road-cut slope in colluvium deposits in Southwest China. First, we carry out short-term ambient seismic noise surveys on the slope, delineate the shear wave velocity (Vs) structure of the slope, verify and establish this structure as the reference Vs model for the slope. Then we conduct the long-term monitoring of the ambient seismic noise on two profiles of the slope, calculate the HVSR curves and observe the time-dependent variations of the predominant peaks that reflect temporal changes of subsurface interfaces. Finally, we perform the Vs inversion to investigate changes in the Vs structure with rainfall. Through the monitoring, we identify the rainfall-induced slope failure and discover that both predominant frequency and shallow subsurface Vs of slope are negatively correlated with rainfall. The HVSR calculation, the predominant peak identification and the Vs inversion can all be implemented in minutes, which is much faster than the array-based surface wave method. The theoretical analysis and the demonstration application show that the framework we proposed in this study has great potential for monitoring changes in performance of slopes.

AutoHVSR: A machine-learning-supported algorithm for the fully-automated processing of horizontal-to-vertical spectral ratio measurements

The horizontal-to-vertical spectral ratio (HVSR) has seen widespread use as a tool for measuring a site’s resonant behavior. However, the processing of HVSR with traditional methods can be tedious and time-consuming when the HVSR is complex and exhibits multiple resonances. This work proposes the AutoHVSR algorithm that allows for fully-automated processing of HVSR measurements, including those with zero, one, or multiple clear resonances. The AutoHVSR algorithm accepts microtremor or earthquake recordings and user-defined HVSR processing parameters as input and returns the computed HVSR from each time window or earthquake record, the mean/median HVSR curve, and statistics on each automatically identified HVSR resonance in terms of frequency and amplitude. The AutoHVSR algorithm integrates robust signal processing and computational methods with state-of-the-art machine-learning models trained using a diverse dataset of 1108 HVSR measurements. The AutoHVSR algorithm demonstrates excellent performance by correctly determining the number of HVSR resonances for 1098 of the 1108 HVSR measurements (>99%) and predicting the mean resonant frequency of the correctly identified resonances with a root mean square error (RMSE) of 0.05 Hz. Furthermore, the AutoHVSR algorithm was able to produce these predictions in 13 min (including HVSR processing time) compared to the 30 h required for traditional processing (a speed up of 138). The AutoHVSR algorithm is further demonstrated on a challenging dataset from Canterbury, New Zealand that included many HVSR curves with multiple and/or ambiguous resonances. Despite the challenging nature of the Canterbury dataset, the AutoHVSR algorithm was capable of correctly determining the number of HVSR resonances for 113 of the 129 HVSR measurements (>87%) and predicting the mean resonant frequency of the correctly identified resonances with a RMSE of 0.10 Hz. The AutoHVSR algorithm produced these predictions under 2 min (including HVSR processing time) compared to the 4 h required for traditional processing (a speed up of 120). Finally, while the AutoHVSR algorithm was developed using microtremor measurements where the horizontal components were combined using the geometric mean, it is shown to extend without modification to microtremor HVSR measurements where the two horizontal components are rotated azimuthally and to HVSR measurements from earthquake recordings. The AutoHVSR algorithm has been made publicly available in v0.3.0 of HVSRweb, it can be accessed at https://hvsrweb.designsafe-ci.org/.

Estimating Site Characteristic Parameters of the Gobi Desert Region Using Seismic Noise

In the Gobi desert region, the predominant frequency of the horizontal-to-vertical spectral ratio (HVSR) curve of seismic noise ( f H / V ) is typically above 3 Hz. However, most of the existing formulas for estimating cover thickness (H) based on f H / V are only applicable for f H / V values below 5 Hz. Therefore, new formulas that can accurately calculate H in this region are crucially needed. To this end, a case study was conducted where noise measurements were carried out in the Gobi region in China, as well as in the east and northeast regions of China. The HVSR curves and f H / V were calculated, and a formula that correlates f H / V with H was derived. In addition, formulas that correlate with Vs20 (average shear-wave velocities to depth 20 m) and Vs30 (average shear-wave velocities to depth 30 m) f H / V were fitted. The relationship between the site fundamental period ( T s ) and T H / V ( 1 / f H / V ) was also investigated. Finally, by using all of the noise measurements and applying the derived relationships, a method for rapidly measuring the site type was proposed. The results showed that the equation for calculating H in this paper is highly reliable, with relative errors less than 30% compared to other researchers. The correlation between f H / V and Vs30 was higher than that between f H / V and Vs20. The accuracy rate of the proposed method for fast identification of ground types was greater than 80%.

Seismic signatures and site characterization of an intermittent stream in dry and flood conditions: an implication for soil losses and landslide triggering

Identifying ambient noise-based (ANb) signatures together with the erosion-prone site conditions retrieved from georadar attribute analysis of streams can help in the estimation of their erosive potential (EP) that promotes reverie landslides and soil losses in the fluvial valleys. This is particularly imperative on flooding or rainy days, leading to stronger erosion-prone conditions (colluvium and boulders) of the valley beds. Developing such research direction can benefit the local communities, as is the case with the Cerrado region of Brazil, where these phenomena have high destructive potential with social, economic, and climatic implications. For the present study, a seasonal stream in the Federal District of Brazil was investigated by ANb monitoring supported by ground penetration radar (GPR) for site characterization. The ANb monitoring was conducted (at a safe distance) with a seismometer over several durations of dry and rainy conditions. The power spectral density (PSDs) as a function of several weather conditions (rainfall, wind speed, and pressure), time–frequency spectrograms, and ambient noise displacement root mean square (dRMS) were computed. This analysis also considered the single station horizontal-to-vertical spectral ratio (HVSR), where rain, wind, pressure, river flow and anthropogenic signatures were evident (at selective frequency ranges). Multi-peaks that emerged on the HVSR curve were further analyzed to identify amplitude and frequency changes, with the three peaks shifting on average to a lower position during the rainy period. The GPR amplitude and waveform variation features were attributed to the stratigraphy of the floodplain and regions susceptible to erosion, such as erosion-prone lithological spots, which provide the basis for non-destructive monitoring tools that enable the detection of “seismic signatures” and weak spots of the fluvial channels for improving environmental management.

Combination of passive and active methods towards site characterization of accelerometer stations in Greece

AbstractThe strong correlation between earthquake damage and the local geological conditions in an area has long been established, and site characterization studies are common practice for realistic estimation of seismic hazard and mitigation of the respective seismic risk. Estimation of the time‐averaged S‐waves velocity of the topmost 30 m (VS30) is recognized as a basic proxy for site characterization and has been incorporated in several building codes. In our work, we examine the inversion of single‐station ambient noise horizontal to vertical spectral ratio (HVSR) curves to estimate the local one‐dimensional (1D) VS(Z) structure. The inversion is performed based on the diffuse field assumption, which allows for the inversion of HVSR, including the contributions of both body and surface waves. Although ambient noise data acquisition is immensely cost‐effective, HVSR curve inversion is subject to the solution non‐uniqueness issue, offering ambiguous results. To provide a possible solution for this matter, additional near‐surface geophysical methods such as the multichannel analysis of surface waves and the electrical resistivity tomography (ERT) were applied to derive information on the shallow subsurface structure. The acquired 1D seismic velocity profile was implemented as initial model in the HVSR inversion to constrain the velocities of the upper meters. Additionally, the inferred stratigraphy from the ERT electrical profile was utilized to constrain the thicknesses of the layers. Tests were conducted with and without a priori information from complementary techniques to explore how the HVSR inversion procedure is facilitated. The proposed methodology was applied at the locations of six accelerometers in the city of Thessaloniki, northern Greece, under different geological conditions. The reliability of the inverted VS(Z) models was checked by performing 1D numerical simulations of ambient noise waveforms generated by distributed sources and by direct comparison between synthetic ambient noise HVSR and single‐station earthquake HVSR curves.

Stochastic finite fault modeling of Mw 6.4 earthquake along Indo-Burmese arc and site classification of its seismic recording station

This study simulates the strong ground motion of an earthquake having magnitude 6.4 occurred on 4 February 2011 in Indo-Burmese Arc (IBA). This earthquake recorded on seven seismic recording stations namely Jowai, Jorhat, Sibsagar, Nagaon, Guwahati, Cooch Bihar and Kokhrajhar. Also, estimation of site class performed to observe the site effects of recording stations in this study. The simulation performed on the basis of revised stochastic finite fault model with dynamic corner frequency and site class for the seismic recording station where the earthquake recorded has been estimated by using Horizontal to Vertical Spectral Ratio (HVSR) technique because modeling and simulation of ground motion majorly depend upon the recorded ground motion as well as site effects, where earthquake has been recorded. The revised well known finite source simulation program (EXSIM) used in this study becomes efficient in providing the results for small magnitude earthquake occurred at large distance. The average HVSR curves plotted for all the recording stations, providing peak frequency for all 7 sites. It is observed from the present work that simulated time histories as far as primary attributes, for example, Fourier spectra, Peak ground acceleration (PGA), Response spectra, Predominant frequency are in close concurrence with the recorded ones. The predominant frequency (fpeak) obtained from HVSR technique has been validated from existing literature for the estimation of site class for seismic recording stations. The fpeak determines the average shear wave velocity (Vs30) at depth of 30 ​m of overburden thickness which varies from 200 ​m/s to 1600 ​m/s according to Program for Excellence in Strong Motion Studies (PESMOS). Whereas, National Earthquake Hazard Reduction Program (NEHRP) provision consider the site class for Vs30 below 180 ​m/s. Due its wide range of site characterization, it has been adopted globally. Therefore, in this study, the site class obtained has been compared with the site classification scheme recommended by PESMOS, NEHRP provisions and previous literature. However, the ground motion parameters and the soil classification of the earthquake recording stations for the IBA region has not been explored yet even after seeing its severity in the past decades. Productive representation of present earthquake gives the confidence to understand and evaluate seismic danger at various parts of Indo- Burmese region from tremors of various sizes. In this study it is proposed that PESMOS site classification data should be revised because it covers wide range of soil types just into three (A, B and C type) class.

Site classification using deep‐learning‐based image recognition techniques

AbstractClassification of local soil conditions is important for the interpretation of structural seismic damage, which also plays a vital role in site‐specific seismic hazard analyses. In this study, we propose to classify sites as an image recognition task using a deep convolutional neural network (DCNN)‐based technique. We design the input image as a combination of the topographic slope and the mean horizontal‐to‐vertical spectral ratio (HVSR) of earthquake recordings. A DCNN model with five convolutional layers is trained using 1649 sites in Japan. The recall rates for site classes C, D, and E using our DCNN classifier for Japanese sites are 82%, 70%, and 60%, respectively. When compared with existing site classification schemes relying on predefined standard HVSR curves, our proposed method achieves the highest total accuracy rate (between 73% and 75%). The generality and applicability of our trained classifier are further validated using sites in Europe with a total accuracy between 64% and 66%. The proposed data‐driven approach could be extended to other types of site amplification functions in the future.

Local Site Effects Investigation in Durres City (Albania) Using Ambient Noise, after the 26 November 2019 (M6.4) Destructive Earthquake

Site characterization of metropolitan areas, especially after an earthquake, is of paramount importance for interpretation of spatial damage distribution and taking measures that assure realistic design actions to strengthen existing constructions and create new ones. Such a case is the city of Durres, Albania, that was hit by the disastrous earthquake of 26 November 2019 (M6.4). Significant differences in structural damage were observed throughout the city, despite its uniform epicentral distance (approximately 15 km); this could be either due to varying vulnerability of the affected constructions and/or to spatial variation of strong ground motion in the city, resulting from local site effects; the latter factor was investigated in this study. This was achieved by taking single station ambient noise measurements throughout the city, at approximately 80 sites. Ambient noise measurements are favorable, as acquiring ambient noise data is an easy and effective noninvasive approach within urban environments. Measurements were processed using the widely applied Horizontal-to-Vertical Spectral Ratio (HVSR) method, following the SESAME project (2004) guidelines. Their fundamental and dominant frequencies, fo and fd, respectively, were calculated and related to the iso-depth contours of the investigated area, as well as their corresponding amplitudes, Ao, and Ad. These experimental parameters and the HVSR curves were used to group all examined sites into classes with similar properties. This clustering provided a zonation map with four categories consisting of similar shapes and amplitudes, applicable to the city of Durres. This map can be utilized as a first level zonation of local site effects for the city. In addition, dynamic properties of soil profiles in selected sites were investigated and tested using 1D synthetic ambient noise data, based on the Hisada (1994, 1995) simulation method, and compared to experimental HVSRs in proximity to the selected sites. A comparison of the proposed four categories zonation map to the observed damage of the 26 November 2019, mainshock is attempted and evaluated. The four categories zonation map with similar expected local site effects proposed in this study can be used as a first level seismic microzonation of Durres. Undoubtedly, corrections for 2D/3D effects on ground shaking must be applied to sites lying in the edges of the Durres basin.

Metamorphic bedrock geometry of Santorini using HVSR information and geophysical modeling of ambient noise and active-source surface-wave data

Santorini is the most active volcano of the Southern Aegean Volcanic Arc, with volcanic material that has accumulated during the last 600+ Kyrs on top of the pre-volcanic Santorini island. The geometry of the pre-volcanic basement not only provides constraints on the volcanic history, but is also fundamental for seismic hazard assessment, as it partly controls site-effects on strong ground motions. We investigate the geometry of the metamorphic (Cycladic) basement of Santorini using information from both passive (noise) and active source data. We performed a large number (∼280) of single-station ambient noise measurements and collected additional data from 42 previous studies to compute the Horizontal-to-Vertical Spectral Ratio (HVSR) curves. The majority of the recovered HVSR curves show prominent spectral ratio peaks (locally larger than 7–8) indicating a large impedance contrast between pyroclastic volcanic strata and bedrock metamorphic formations. We also performed active (MASW) and passive (Noise Array) surface wave measurements at 4 selected sites to determine local dispersion curves. To find the 1D Vs structure from the surface down to the metamorphic bedrock we performed a joint Monte Carlo inversion of the dispersion curves and the fundamental frequency (f0HVSR) values from the HVSR curves. These models, as well as deep borehole information and HVSR data along the caldera cliff, where the thickness and stratigraphy of the volcanic formations above the bedrock can be directly observed, allowed us to determine a linear relationship between the thickness of the pyroclastic formations and their fundamental resonance period for central-southern Santorini. The resulting geometry of pre-volcanic island shows deep basins around the pre-Alpine bedrock outcrop (Profitis Ilias) and generally agrees with recent results from larger-scale tomographic and gravity data but with some significant local differences. The basins are 200+ meters thick in the Kamari and Perissa area (southeastern Santorini) and >400 m thick in the central (Fira-Imerovigli) area, while there is a thick (∼70-130 m) pyroclastic layer on top of a metamorphic basement “plateau” in the Megalochori area.

Peculiarities of the HVSR Method Application to Seismic Records Obtained by Ocean-Bottom Seismographs in the Arctic

The application of the horizontal-to-vertical spectral ratio (HVSR) modeling and inversion techniques is becoming more and more widespread for assessing the seismic response and velocity model of soil deposits due to their effectiveness, environmental friendliness, relative simplicity and low cost. Nevertheless, a number of issues related to the use of these techniques in difficult natural conditions, such as in the shelf areas of the Arctic seas, where the critical structures are also designed, remain poorly understood. In this paper, we describe the features of applying the HVSR modeling and inversion techniques to seismic records obtained by ocean-bottom seismographs (OBS) on the outer shelf of the Laptev Sea. This region is characterized by high seismotectonic activity, as well as sparse submarine permafrost distribution and the massive release of bubble methane from bottom sediments. The seismic stations were installed for one year and their period of operation included periods of time when the sea was covered with ice and when the sea was ice-free. The results of processing of the recorded ambient seismic noise, as well as the wave recorder data and ERA5 and EUMETSAT reanalysis data, showed a strong dependence of seafloor seismic noise on the presence of sea ice cover, as well as weather conditions, wind speed in particular. Wind-generated gravity waves, as well as infragravity waves, are responsible for the increase in the level of ambient seismic noise. The high-frequency range of 5 Hz and above is strongly affected by the coupling effect, which in turn also depends on wind-generated gravity waves and infragravity waves. The described seafloor seismic noise features must be taken into account during HVSR modeling and interpretation. The obtained HVSR curves plotted from the records of one of the OBSs revealed a resonant peak corresponding to 3 Hz, while the curves plotted from the records of another OBS did not show clear resonance peaks in the representative frequency range. Since both OBSs were located in the area of sparse distribution of submarine permafrost, the presence of a resonance peak may be an indicator of the presence of a contrasting boundary of the upper permafrost surface under the location of the OBS. The absence of a clear resonant peak in the HVSR curve may indicate that the permafrost boundary is either absent at this site or its depth is beyond the values corresponding to representative seismic sensor frequency band. Thus, HVSR modeling and inversion techniques can be effective for studying the position of submarine permafrost.

Site characterization study with microtremor data: A case study at the West Borneo NPP potential site

ABSTRACTA site characterization using a microtremor measurement study was conducted at the West Borneo nuclear power plant (NPP) potential site as a preliminary feasibility study. This study measured the natural resonant frequency of soil and estimated the subsurface VS as prior information for the design planning of an NPP building foundation. The single station microtremor data were processed using the horizontal‐to‐vertical spectral ratio (HVSR) method to obtain the f0 and A0 values, and the array data were processed using the spatial autocorrelation (SPAC) method. The study area was classified based on the f0 and A0 values. Due to the unavailability of borehole data and limited array data, the HVSR curve was used to estimate the VS profile. The HVSR curve VS estimation was calculated using Rayleigh wave ellipticity inversion. The inversion results were constrained by VS profiles from SPAC and regional geology data to ensure that the inverted model was rational. It was demonstrated that the constrained inversion process could generate a rational subsurface model for Pantai Gosong's coastline. Based on the result, the feasible bedrock for the NPP building foundation was found at a depth of 40 m in the coastline area.

Characteristics of Horizontal to Vertical Spectral Ratio of InSight Seismic Data From Mars

AbstractSince February 2019, the InSight mission has returned seismic and meteorological data from Mars. We conducted horizontal to vertical spectral ratio (HVSR) analysis to the InSight seismic data recorded both on the lander and on the ground. Horizontal to vertical spectral ratio curves of ground data show multi‐peak characteristics at frequencies between 1 and 30 Hz with the highest peak appearing at around 11.7 Hz. The HVSR results of the Very Broad Band (VBB) and Short Period (SP) data differ greatly for frequencies over 10 Hz due to the difference in vertical component. The onboard SP data have the same highest H/V peak as the ground SP data. We conducted numerical modeling of HVSR and confirmed that the wind‐induced lander vibrations are the major sources to the InSight seismic ground motion in high frequencies. The HVSR curves of the continuous ground SEIS data show diurnal variation and are highly correlated with local meteorological conditions. The particle motions are investigated through the polarization analysis and the random decrement method. Generally, the ground motions above the self‐noise level are linearly polarized in the horizontal plane around the highest H/V peak. The damping analysis demonstrated the mechanical origins of the highest HVSR peak, while the 2.4 Hz mode is the most likely one having natural origin. Finally, most marsquake signals analyzed in this study generally highlight the 2.4 Hz trough but cause no significant change on the shape of the H/V curves. Our study explores the possible existence of natural sources in relatively high frequencies of Mars' background noise.

A New Set of Automated Methodologies for Estimating Site Fundamental Frequency and Its Uncertainty Using Horizontal-to-Vertical Spectral Ratio Curves

AbstractThis study proposes a new set of methodologies to estimate the site fundamental frequency using the horizontal-to-vertical spectral ratio (HVSR) of recorded surface ground motions. Because of the lack of consensus in HVSR calculation among researchers, a wide range of methods are practiced in this area, yielding different site fundamental frequencies at a given site due to analyst subjectivity. In this study, current practices for combining horizontal components—geometric mean and RotD50—are examined first, and results show that both methods provide comparable HVSR curves. However, RotD50 has the advantage of being orientation independent. Second, the application of Fourier amplitude spectrum (FAS) and 5% damped pseudospectral acceleration (PSA) in computing HVSR is studied, and results are presented for one case study in which PSA-based HVSR seems to suffer from scenario dependency, whereas the FAS-based results appear stable. Different values for Konno–Ohmachi smoothing parameter b were evaluated, and its effect on estimating the site fundamental frequency was considered; using b = 40 is our preference. In previous studies, average HVSR curves were used to estimate a single number representing the site fundamental frequency without incorporating uncertainty. This study proposes four methodologies that use events’ individual HVSR curves to estimate the site fundamental frequency and its associated uncertainty in a completely automated manner. Methods 1–3 use individual HVSR curves to find the maximum-likelihood estimate of the site fundamental frequency (fml), whereas method 4 uses both individual and average HVSR curves to estimate the first resonance frequency (f0). To evaluate the automated methods, a subset of the Next Generation Attenuation-West2 dataset is used to study 50 stations, and the results are compared with an independent study demonstrating good consistency. The proposed methods are further illustrated using data from the Garner Valley Downhole Array (GVDA), which highlights the pros and cons of the presented methods.

Development of a seismic site-response zonation map for the Netherlands

Abstract. Earthquake site response is an essential part of seismic hazard assessment, especially in densely populated areas. The shallow geology of the Netherlands consists of a very heterogeneous soft sediment cover, which has a strong effect on the amplitude of ground shaking. Even though the Netherlands is a low- to moderate-seismicity area, the seismic risk cannot be neglected, in particular, because shallow induced earthquakes occur. The aim of this study is to establish a nationwide site-response zonation by combining 3D lithostratigraphic models and earthquake and ambient vibration recordings. As a first step, we constrain the parameters (velocity contrast and shear-wave velocity) that are indicative of ground motion amplification in the Groningen area. For this, we compare ambient vibration and earthquake recordings using the horizontal-to-vertical spectral ratio (HVSR) method, borehole empirical transfer functions (ETFs), and amplification factors (AFs). This enables us to define an empirical relationship between the amplification measured from earthquakes by using the ETF and AF and the amplification estimated from ambient vibrations by using the HVSR. With this, we show that the HVSR can be used as a first proxy for site response. Subsequently, HVSR curves throughout the Netherlands are estimated. The HVSR amplitude characteristics largely coincide with the in situ lithostratigraphic sequences and the presence of a strong velocity contrast in the near surface. Next, sediment profiles representing the Dutch shallow subsurface are categorised into five classes, where each class represents a level of expected amplification. The mean amplification for each class, and its variability, is quantified using 66 sites with measured earthquake amplification (ETF and AF) and 115 sites with HVSR curves. The site-response (amplification) zonation map for the Netherlands is designed by transforming geological 3D grid cell models into the five classes, and an AF is assigned to most of the classes. This site-response assessment, presented on a nationwide scale, is important for a first identification of regions with increased seismic hazard potential, for example at locations with mining or geothermal energy activities.

Shear wave velocity estimation based on the particle swarm optimization method of HVSR curve inversion in Bakauheni district, Indonesia

The Nakamura method, known as horizontal to vertical spectral ratio (HVSR), has been used to analyze site effect assessment. Over the past decade, various HVSR curve inversion methods for near-surface geophysical surveys have been developed. Particle swarm optimization (PSO) inversion method has been applied to solve the HVSR inversion curve to estimate the shear wave velocity (Vs) value towards the depth. In this study, the HVSR curve inversion experiment has been applied with two synthetic data: noise-free data and the other is contaminated by 10% random noise. This research aims to find out how the PSO algorithm performs to find the best solution. The result indicated that the PSO algorithm is relatively stable fast in converging and producing the solution closely with the actual model. Finally, we obtained a fit model on actual data inversion that shows the Vs value towards depth from PSO inversion and is able to describe the fault model and sediment layer in Way Baka fault.