The S-wave velocity (SWV) is a crucial parameter in seismic site characterization and seismic microzonation. In Varanasi city, we determined the shear wave velocity through a dual approach, employing joint inversion of microtremor array survey and the Horizontal to Vertical Spectral Ratio (HVSR) method. This combined analysis from two distinct methods enhances the reliability of our S-wave velocity model for the subsurface soil strata. To assess the S-wave velocity profile in shallow subsurface soil layers, we conducted forward and inverse modelling of geophysical data. This evaluation was cross-referenced with geotechnical borehole data to ensure accuracy. Microtremor measurements were conducted at 115 single stations and 12 array stations in the city. Joint modelling of HVSR and Rayleigh wave phase velocity dispersion provided insights into the site characteristics. Utilizing neighbourhood algorithms, we inverted dispersion curves from microtremor array measurements to obtain the S-wave velocity profile. The results were validated using geotechnical borehole data in the study area. The microtremor-derived S-wave velocity disclosed significant impedance contrasts in the topsoil layer, reaching a depth of approximately 12 m, with velocities ranging from 180 to 250 m/s. The second layer, extending to around 40-50 m, exhibited velocities between 300 and 400 m/s, while the bottom layer surpassed 600 m/s. Comparisons with SPT-derived S-wave velocity confirmed a well-correlated S-wave velocity profile for the top layer. The various methods converged to an average S-wave velocity of 360 m/s up to a depth of 50 m.

In recent years, earthquakes have caused several types of damage to residential embankments. To assess the integrity of residential embankments and ascertain necessary countermeasures following ground disasters, it is crucial to accurately define the boundary of cutting and filling. Although surface wave methods nondestructively unveil the S-wave velocity V S across a broad spectrum, there are currently no methods available to predict the boundary of cutting and filling based on V S . In this investigation, surface wave measurements were conducted in an area thought to be an embankment, according to aerial topographic interpretation. The acquired V S data were used to ascertain the soil characteristics of the unaffected residential embankment. Furthermore, the applicability of a method for predicting the boundary of cutting and fillings was examined. When the mode value of V S within the embankment was selected as the threshold for the boundary of cutting and filling, some agreement was confirmed with the outcomes calculated through aerial topographic interpretation. In addition, a straightforward technique for calculating ground subsidence based on V S was considered. It was found that it may be feasible to determine the estimated seismic settlement of residential levees swiftly and nondestructively throughout a sizable region. These results indicate that the use of the surface wave method has the potential to advance residential embankment health assessment systems.

With increasing demand for nuclear power generation, nuclear structures are being planned and constructed worldwide. A grave safety concern is that these structures are sensitive to large-magnitude shaking, e.g., during earthquakes. Seismic response analysis, which requires P- and S-wave velocities, is a key element in nuclear structure design. Accordingly, it is important to determine the P- and S-wave velocities in the Gyeongju and Pohang regions of South Korea, which are home to nuclear power plants and have a history of seismic activity. P- and S-wave velocities can be obtained indirectly through a correlation with physical properties (e.g., N values, Young's modulus, and uniaxial compressive strength), and researchers worldwide have proposed regression equations. However, the Gyeongju and Pohang regions of Korea have not been considered in previous studies. Therefore, a database was constructed for these regions. The database includes physical properties such as N values and P- and S-wave velocities of the soil layer, as well as the uniaxial compressive strength, Young's modulus, and P- and S-wave velocities of the bedrock layer. Using the constructed database, the geological characteristics and distribution of physical properties of the study region were analyzed. Furthermore, models for predicting P- and S-wave velocities were developed for soil and bedrock layers in the Gyeongju and Pohang regions. In particular, the model for predicting the S-wave velocity for the soil layers was compared with models from previous studies, and the results indicated its effectiveness in predicting the S-wave velocity for the soil layers in the Gyeongju and Pohang regions using the N values. The proposed models for predicting P- and S-wave velocities will contribute to predicting the damage caused by earthquakes.