High-Speed Train Elastic Full Waveform Inversion over Viaducts: New Source Implementation and Resulting Near-Surface Multi-Parameter Resolution

High-speed train (HST) signals offer an abundant and eco-friendly seismic source along the railway, but their application to full waveform inversion (FWI) presents unique challenges due to complex source characteristics and field constraints. We develop an HST-based elastic FWI framework that models the train as a distributed pier-force: a chain of time-delayed excitations applied continuously along deeply embedded bridge piers. This source mechanism generates predominantly S- and Rayleigh-wave energy, providing enhanced shallow subsurface illumination. The synthetic anomaly experiment demonstrates that the distributed pier-force enables superior multiparameter reconstruction, particularly achieving higher density accuracy than the explosive and single-force sources. Additional sparse acquisition tests validate the robustness of the method under limited receiver coverage. The field data application successfully reconstructs subsurface layering through simultaneous source and parameter inversion, supporting the physical plausibility of the distributed source model. Overall, this study establishes the distributed pier-force as an effective and computationally efficient HST source for shallow subsurface characterization, while also highlighting limitations under realistic field conditions.