Quasi-distributed fiber optic monitoring of thermo-hydro behavior of frozen loess for frost heave prediction

We developed a quasi-distributed fiber optic monitoring technology to investigate the thermo-hydro-mechanical (THM) behaviors of frozen loess. A combined method was proposed to measure in-situ ice content, providing critical parameters for understanding THM coupled effects. To characterize the soil freezing-thawing process, we further carried out subsurface automated multiphysics monitoring at a site located on the Loess Plateau, China, during 2020/2021 winter by employing quasi-distributed fiber optic sensing arrays. The inner mechanism of frost heave was revealed via field monitoring data and correlation analysis, which directly promoted the development of a semiempirical frost heave prediction method. For this study area, the proposed method requiring only temperature data as inputs was validated using our field monitoring results.

The data presented here are the monitoring data of in-situ temperature, moisture content,  and soil displacement. The results of frost heave prediction based on the field monitoring data are shown in the files.