On December 18, 2023, an Ms6.2 earthquake struck Jishishan County, Gansu Province, in western China. The China Earthquake Early Warning Network (CEEWN) captured extensive near-field ground motion data using high-density microelectromechanical system (MEMS) sensors and force-balanced accelerographs (FBAs). Through noise level and usable frequency range assessments of MEMS/FBA recordings, we compiled a strong- motion dataset encompassing the Ms6.2 mainshock and 13 aftershocks (Ms >= 3.0). Analysis of this dataset revealed distinct source characteristics and site effects through spatial distributions and attenuation patterns of peak ground acceleration (PGA, up to 1.1 g at station N002B), peak ground velocity (PGV), and spectral accelerations (SAs) across various periods. The mainshock's near-fault motions exhibited pronounced short-period energy, with 0.2 s SAs exceeding 1.0 gin intensity zones VII-VIII due to hanging wall effects, soil amplification, and topographic influences. Site-to-reference ratio (SSR) analysis identified site nonlinearity above 1 Hz and amplification between 1 and 10 Hz. Observed PGAs and short-period SAs surpassed ground motion model (GMM) predictions with faster attenuation rates, while long-period SAs (>1.0 s) remained below predictions. Residual analysis of intensity measures (IMs) and horizontal-to-vertical spectral ratios (HVSRs) demonstrated progressive site nonlinearity, showing HVSR frequency reductions and amplitude declines at PGAs >500 cm/s(2). This dataset advances regional ground motion model (GMM) development, while our findings on strong ground motion characteristics offer critical insights for earthquake damage assessment and post-disaster reconstruction.

Seismic waves exhibit distinct attenuation characteristics that are contingent upon the medium they traverse. The attenuation characteristics can be employed to monitor engineering activities, such as detecting gas pipeline leaks and third-party intrusions, by the utilization of Distributed Acoustic Sensing (DAS) technology. This study aims to explore the feasibility of identifying the seismic wave attenuation characteristics of different soils using DAS. A circular experimental pit with a diameter of 1 m was designed to measure the responses of various soils. Seismic waves were recorded while propagating through sand and clay under different overlying pressure conditions, encompassing both dry and wet states. The waveform data, collected at various distance from the point of excitation, were analyzed using Power Spectral Density (PSD), Continuous Wavelet Transform (CWT), and quality factor analysis. The energy attenuation amplitude of seismic waves shows an opposite pattern in sand and clay as water content increased. By utilizing the seismic wave attenuation characteristics, it is possible to issue timely warnings for identifying third-party intrusions around urban underground tunnels and pipelines to mitigate potential damage to underground infrastructure.