Probabilistic estimation of shear-wave velocity profiles and site classes from surface wave surveys for accelerometer stations in the southern Korean Peninsula

In this study, we present a probabilistic framework for deriving shear-wave velocity (VS) profiles at 21 permanent accelerometer stations in the southeastern Korean Peninsula. Surface wave dispersion (SWD) data from multichannel analysis of surface waves (MASW) and microtremor array measurement (MAM) were jointly inverted using an ensemble-based stochastic approach that accounts for measurement errors, frequency gaps, and inversion parameterization. The resulting VS profiles extend from the surface to depths of up to 1,000 m, providing a thorough characterization of subsurface structures. Validation was performed against borehole direct measurements and fundamental resonance frequencies derived from one-dimensional transfer functions (1DTF) and horizontal-to-vertical spectral ratios (HVSR). In most cases, the derived profiles closely match borehole data, although minor discrepancies at greater depths suggest lateral heterogeneity or measurement uncertainties. The 1DTF peaks at most stations also show strong agreement with HVSR resonance frequencies, confirming that the inverted VS profiles accurately capture the soil–bedrock interface and its impedance contrast. From these profiles, we estimate site parameters, VS30, Hrock, and VSsoil, and employ them for probabilistic site classification, spanning from soft soil (Class D) to rock (Class B). Notably, the relationships between site parameters reveal a strong positive correlation between VS30 and HVSR resonance frequency, while Hrock exhibits an inverse exponential trend. By quantifying uncertainty through ensemble modeling, this approach offers distinct advantages over conventional deterministic methods, ultimately benefiting seismic hazard assessment, ground motion prediction, and site response analyses.