The single-station microtremor horizontal-to-vertical spectral ratio (MHVSR) method was initially proposed to retrieve the site amplification function and its resonance frequencies produced by unconsolidated sediments overlying high-velocity bedrock. Presently, MHVSR measurements are predominantly conducted to obtain an estimate of the fundamental site frequency at sites where a strong subsurface impedance contrast exists. Of the earthquake site characterization methods presented in this special issue, the MHVSR method is the furthest behind in terms of consensus towards standardized guidelines and commercial use. The greatest challenges to an international standardization of MHVSR acquisition and analysis are (1) thewhat— the underlying composition of the microtremor wavefield is site-dependent, and thus, the appropriate theoretical (forward) model for inversion is still debated; and (2) thehow— many factors and options are involved in the data acquisition, processing, and interpretation stages. This paper reviews briefly a historical development of the MHVSR technique and the physical basis of an MHVSR (thewhat). We then summarize recommendations for MHVSR acquisition and analysis (thehow). Specific sections address MHVSR interpretation and uncertainty assessment.

We have been discussing the validity of using the horizontal-to-vertical spectral ratios (HVRs) as a substitute for S-wave amplifications after Nakamura first proposed the idea in 1989. So far a formula for HVRs had not been derived that fully utilized their physical characteristics until a recent proposal based on the diffuse field concept. There is another source of confusion that comes from the mixed use of HVRs from earthquake and microtremors, although their wave fields are hardly the same. In this study, we compared HVRs from observed microtremors (MHVR) and those from observed earthquake motions (EHVR) at one hundred K-NET and KiK-net stations. We found that MHVR and EHVR share similarities, especially until their first peak frequency, but have significant differences in the higher frequency range. This is because microtremors mainly consist of surface waves so that peaks associated with higher modes would not be prominent, while seismic motions mainly consist of upwardly propagating plain body waves so that higher mode resonances can be seen in high frequency. We defined here the spectral amplitude ratio between them as EMR and calculated their average. We categorize all the sites into five bins by their fundamental peak frequencies in MHVR. Once we obtained EMRs for five categories, we back-calculated EHVRs from MHVRs, which we call pseudo-EHVRs (pEHVR). We found that pEHVR is much closer to EHVR than MHVR. Then we use our inversion code to invert the one-dimensional S-wave velocity structures from EHVRs based on the diffuse field concept. We also applied the same code to pEHVRs and MHVRs for comparison. We found that pEHVRs yield velocity structures much closer to those by EHVRs than those by MHVRs. This is natural since what we have done up to here is circular except for the average operation in EMRs. Finally, we showed independent examples of data not used in the EMR calculation, where better ground structures were successfully identified from pEHVRs again. Thus we proposed here a simple empirical method to estimate S-wave velocity structures using single-station microtremor records, which is the most cost-effective method to characterize the site effects.

Generalized inversion techniques (GITs) have become popular for determining seismological parameters (e.g., source, attenuation, and site response), particularly in low-to-moderate seismicity regions. Indeed, GITs can potentially provide reliable site-response estimates when a minimum number of recordings is available, as well as valuable information about source parameters and regional attenuation characteristics. Significant advances have been made on GITs in which different approaches and hypotheses were investigated, such as the application of “nonparametric” and “parametric” inversion schemes. In this context, several scientific questions have arisen that depend on the final scope of the GITs: What is the optimal inversion strategy for a given dataset configuration? What is the impact of the different choices, assumptions, and implementations on the reliability of the results? Is it possible to quantify the associated epistemic uncertainties? Here, we have considered and compared the different approaches of GITs to improve the understanding of each for use in different applications. A methodological benchmark that includes different GIT methods and dataset configurations is set up to fulfill the objective, using a simple synthetic dataset, a French regional sparse dataset, and an Italian national dense dataset. The benchmark is developed in two phases: (1) phase I: a free phase with no common constraints; and (2) phase II: a constrained phase with unified reference conditions. Despite unifying the reference conditions in the different inversions, the variability was not reduced. Discrepancies are observed between different terms of GITs. Site responses appear to be the most robust estimates, compared to source and attenuation terms. The way that stress drops of earthquakes and quality factors for crustal attenuation are parameterized appears to lead to significant variability between different approaches. Finally, uncertainties are addressed by quantification of the inter-method variability for the different terms and parameters.

The main objective of this study is to develop physics‐based constraints on the spatiotemporal variation of the slip‐rate function using a simplified dynamic rupture model. First, we performed dynamic rupture modeling of the 2019 $Mw$ 7.1 Ridgecrest, California, earthquake, to analyze the effects of depth‐dependent stress and material friction on slip rate. Then, we used our modeling results to guide refinements to the slip‐rate function that were implemented in the Graves–Pitarka kinematic rupture generation technique. The dynamic ruptures were computed on a surface‐rupturing, planar strike‐slip fault that includes a weak (negative to low‐stress‐drop) zone in the upper 4 km of the crust. Below the weak zone, we placed high‐stress‐drop patches designed to mirror the large‐slip areas seen in various rupture model inversions of the event. The locations of the high‐stress‐drop patches and the hypocenter were varied in multiple realizations to investigate how changing the dynamic conditions affected the resulting rupture kinematics, in particular, the slip rate. From these simulations, we observed a systematic change in the shape of the slip‐rate function from Kostrov type below the weak zone to a predominantly symmetric shape within the weak zone, along with a depth‐dependent reduction of peak slip rate. We generalized these shallow rupture features into a depth‐dependent parametric variation of the slip‐rate function and implemented it in the Graves–Pitarka kinematic rupture model generator. The performance of the updated kinematic approach was then verified in 0–4 Hz simulations of the $Mw$ 7.1 Ridgecrest earthquake, which showed that incorporating the depth‐dependent variation in the shape of the slip‐rate function improves the fit to the observed near‐fault ground motions in the 0.5–3 s period range.

Tsunami evacuation simulations are often used to determine necessary countermeasures that will reduce human loss effectively after earthquakes and subsequent tsunamis. However, so far there has been no simulation for the estimated building damage using up-to-date knowledge of seismic engineering. In this study, in order to clarify the effect of building damage on a tsunami evacuation, we first predicted building damage based on the nonlinear response analysis for a realistic strong ground motion and then simulated a tsunami evacuation considering road blockage due to the collapsed buildings. We used one district in Tanabe City in Wakayama Prefecture in Japan where we expect to have a 12 m of tsunami height after an earthquake along the Nankai Trough plate boundary. We found that the prepared capacity of evacuation sites is not enough to let everyone evacuate and that the number of survivors increases by 3–4% if all of the buildings and houses are seismically reinforced. Considering this, plus 1% of expected casualties inside the collapsed houses, it appears to be not as efficient to reinforce buildings and houses to prevent human loss in comparison with increasing the capacity of tsunami evacuation sites in the target district. However, the damage to building and houses will cause a lot of side effects which are not considered here, but will prolong the evacuation time. Thus, we concluded that we need to reinforce the buildings and houses as well as consider the appropriate placement, number, and capacity of the evacuation sites.

To understand the cause of heavy structural damage during the mainshock (on April 16, 2016) of the 2016 Kumamoto earthquake sequence, we carried out a field survey from April 29 through May 1, 2016, in Mashiki where heavy damage concentration was observed. The heavy damage concentration in downtown Mashiki could be understood based on the observed strong motions with the Japan Meteorological Agency instrumental seismic intensity of VII and information collected by the field investigation. First, the fundamental features of the structural damage in downtown Mashiki were summarized. Then, a distribution map of peak frequencies was derived from horizontal-to-vertical spectral ratios of microtremors. We could not see any systematic correlation between the peak frequencies and spatial distribution of damage ratios. We also analyzed observed strong motion data at two sites to obtain fling-step-like motions in the displacement time histories through the double integration of unfiltered accelerograms. It turned out that at both strong motion observation sites in Mashiki, only the east–west (EW) components had very strong velocity pulses westward before the emergence of the fling-step-like motion eastward, which would be the primary cause of heavy structural damage in downtown Mashiki, not site effects nor the fling-step-like motion itself.