Title : Investigating the ability of delay-time method to illustrate accurate uneven horizons on post-sliding sites
Abstract:
Near surface geophysical methods have been extensively used as non-invasive and cost-effective methods to characterize subsurface geological properties over the past two decades. Since these approaches are able to illustrate the temporal and spatial changes of geological conditions, they are applied for the characterization of landslide zones. Landslide events are one of many natural disasters that cause losses of life and property. Landslide mechanisms are affected by topsoil materials, bedrock geometry, and subsurface water content.
Seismic refraction tomography (SRT) has so far been used as the most powerful geophysical methods for landslide investigation. In this research, this technique is used to study spatial and temporal variations of geophysical parameters of sliding site. The landslide incident occurred in Yanshan village placed in Xiaoshan district, Hangzhou City, China. This project focuses on the capability of delay-time method in processing SRT data. This technique employs traveltime curves to determine the time and thickness beneath each receiver. Since the study area is inclined and included undulating surface, the processing technique can provide a better image of the underground features corresponding to inversion models. In this technique, the true velocity can be computed by recording signal from two ends of line (forward and revers shots). It leads to have the actual depth beneath recorders with more details. The values calculated by Matlab have been synthesized in the form of schematic of geological sections of each profile by GEO5 2020 software (slope stability). These models have verified and quantified the geophysical parameters of inversion models mapped by ZondST2D software which incorporates a tomographic inversion method. This processing technique is applied in which a strong horizontal velocity is shown in rugged topography. The good agreement between the inversion models and the synthesized images proves the reliability of the applied processing methods.
