Thermo-hydro-poro-mechanical responses of a reservoir-induced landslide tracked by high-resolution fiber optic sensing nerves

Thermo-poro-mechanical responses along sliding zone/surface have been extensively studied. However, it has not been recognized that the potential contribution of other crucial engineering geological in- terfaces beyond the slip surface to progressive failure. Here, we aim to investigate the subsurface multi- physics of reservoir landslides under two extreme hydrologic conditions (i.e. wet and dry), particularly within sliding masses. Based on ultra-weak fiber Bragg grating (UWFBG) technology, we employ special- purpose fiber optic sensing cables that can be implanted into boreholes as "nerves of the Earth" to collect data on soil temperature, water content, pore water pressure, and strain. The Xinpu landslide in the middle reach of the Three Gorges Reservoir Area in China was selected as a case study to establish a paradigm for in situ thermo-hydro-poro-mechanical monitoring. These UWFBG-based sensing cables were vertically buried in a 31 m-deep borehole at the foot of the landslide, with a resolution of 1 m except for the pressure sensor. We reported field measurements covering the period 2021 and 2022 and produced the spatiotemporal profiles throughout the borehole. Results show that wet years are more likely to motivate landslide motions than dry years. The annual thermally active layer of the landslide has a critical depth of roughly 9 m and might move downward in warmer years. The dynamic groundwater table is located at depths of 9e15 m, where the peaked strain undergoes a periodical response of leap and withdrawal to annual hydrometeorological cycles. These interface behaviors may support the interpretation of the contribution of reservoir regulation to slope stability, allowing us to correlate them to local damage events and potential global destabilization. This paper also offers a natural framework for interpreting thermo-hydro-poro-mechanical signatures from creeping reservoir bank slopes, which may form the basis for a landslide monitoring and early warning system.