The within-site variability in site response is the randomness in site response at a given site from different earthquakes and is treated as aleatory variability in current seismic hazard/risk analyses. In this study, we investigate the single-station variability in linear site response at K-NET and KiK-net stations in Japan using a large number of earthquake recordings. We found that the standard deviation of the horizontal-to-vertical Fourier spectral ratio at individual sites, that is single-station horizontal-to-vertical spectral ratio (HVSR) sigma σ_HV,s, approximates the within-site variability in site response quantified using surface-to-borehole spectral ratios (for oscillator frequencies higher than the site fundamental frequency) or empirical ground-motion models. Based on this finding, we then utilize the single-station HVSR sigma as a convenient tool to study the site-response variability at 697 KiK-net and 1169 K-NET sites. Our results show that at certain frequencies, stiff, rough and shallow sites, as well as small and local events tend to have a higher σ_HV,s. However, when being averaged over different sites, the single-station HVSR sigma, that is σ_HV, increases gradually with decreasing frequency. In the frequency range of 0.25–25 Hz, σ_HV is centred at 0.23–0.43 in ln scales (a linear scale factor of 1.26–1.54) with one standard deviation of less than 0.1. σ_HV is quite stable across different tectonic regions, and we present a constant, as well as earthquake magnitude- and distance-dependent σ_HV models.

The effects of variations in annual, seasonal, and extreme precipitation in the Han River Basin (HRB) were explored using innovative trend analysis, Spearmen’s rho test, and Mann-Kendall test. Extreme-value precipitation was analyzed using various precipitation categories (light, low, moderate, high, and extreme). Stations in the north and northeast parts of the basin were more sensitive to precipitation inconsistencies. Hydrologically extreme events such as flood and drought were associated with extreme (> 90th percentile) and light (< 10th percentile) precipitation categories. Significant variability was detected in summer precipitation, whereas annual and extreme precipitation trends were more sensitive in the northeastern parts of the basin, signifying possible flooding aggregation. However, a decrease in flooding in the southern HRB indicated a shift in the precipitation regime from south to north. Overall results suggest that the eastern and northwestern regions were more likely to experience extreme floods during the summer and severe droughts during the fall and winter. An increase in precipitation was observed over time from the south to the north. A warming and wetting trend was observed in the north, while a warming-drying trend was evident in the south. Mitigating hydro-meteorological disasters such as flood and drought in the HRB will require more research attention to these trends.

This study describes the methodology employed to construct a seismic fragility function based on a pre-existing numerical model tailored for underground stations. Employing a dynamic numerical model, a comprehensive analysis encompassing 110 distinct cases was conducted, each varying in soil depth and classification. Seismic waves, conforming to the standard design spectrum, were utilized within these numerical analyses. The formulation of the fragility function within the constructed model follows a structured approach, segmented by damage indices and severity levels. This systematic breakdown serves to outline the fundamental framework for establishing the fragility function, providing insights into its development process. Subsequently, the derived fragility function underwent a rigorous comparative analysis against established seismic fragility functions from prior studies. This comparative assessment serves as a critical evaluation tool, allowing for an appraisal of the suitability and robustness of the newly developed fragility function in relation to existing benchmarks.

This study suggests a linearly combined ground motion model (GMM) optimized for the within-rock conditions of South Korea. Ground motions recorded by accelerometers positioned in within-rock layers are used as target intensity measures (IMs), and five local GMMs and four global GMMs are used as candidates for combination. Optimization, which seeks to find a weight vector minimizing the uncertainty of the combined model, is performed using the quadratic programming (QP) technique, which provides very fast and solid results for the linear combination problem. This study illustrates how to use the QP technique for the linear combination problems. Also, we suggest optimized weight vectors for GMM combinations for two conditions: 1) the IM prediction of a scenario event without observations and 2) the IM prediction of a past event with observations. Among the local and global GMMs considered, JB03, Eea15, JH21, and BSSA14 are selected as the best four GMMs for the first condition, and Jea02, JB03, JH21, and CB14 are selected as the best four GMMs for the second condition. The combined model reduces the standard deviation of residuals in natural logarithms by 10% and 8% for the first and second conditions, respectively, compared to the best individual GMM at each period. Among the GMMs considered, the prediction by Eea15 is only applicable for magnitudes less than 5. Hence, for large magnitude (Mw > 5) prediction, CB14 is recommended instead of Eea15 for the best four models for the first condition.

This paper describes the relationship between bedrock depth (D) and site fundamental frequency (f₀) in the Nakdonggang delta region in the southeastern part of the Korean peninsula. We collected borehole logs to confirm the thickness of the sediments and estimated the f₀ at over 200 locations across the delta using the horizontal-to-vertical spectral ratio (HVSR) method. We developed an f₀ map of the study area by spatially interpolating the f₀ values using the Ordinary Kriging method. The bedrock depth in the main delta showed a power-law dependence on the f₀. The derived f₀–D model predicted much shallower bedrock depths compared with similar studies from other parts of the world. This was attributed to the fact that the Nakdonggang delta region is composed of relatively low V_s Holocene sediments. With an f₀ map, the derived model could enable a quick estimation of the bedrock depth, which could help to determine the site class in the Nakdonggang delta region according to the Korean Seismic Design Standard (KDS 17 10 00).

The Korea Meteorological Administration (KMA), SK Telecom, and Kyungpook National University collaborated to develop the low-cost IoT seismometer (LCIS) that embeds a micro-electro-mechanical systems accelerometer and LTE communication sensor. Currently, approximately 7,000 stations (the average density is 0.07/km ² ) with LCIS devices are operating in real-time on the Korean Peninsula, which is about 25 times higher density than the national seismic network with high performance seismometers operated by KMA. The majority of LCISs are installed inside buildings so that adjustment is applied to convert to the free-surface equivalent vibration. Researchers derived seismic intensity maps using only LCIS network data, which showed very similar distributions to the maps from the high-performance network. This validates the usefulness of the LCIS network for Modified Mercalli intensity (MMI) map generation and earthquake early warning system.