Reservoir accumulation landslides pose a significant challenge to hydropower projects, with their instability risks exacerbated by uncertainties in failure patterns due to the spatial variability of geomaterial properties and dynamic environmental conditions. This study pioneers an in-depth investigation into the instability pattern uncertainty of reservoir accumulation landslides, a critical yet understudied aspect of landslide risk, exemplified by the Baijiabao landslide in the Three Gorges Reservoir area. A stochastic finite element limit analysis, integrating comprehensive field investigations and laboratory experiments, was conducted to model the spatial variable shear strength in the sliding mass and slip zone. Employing the Gaussian mixture model expectation maximization algorithm, the risk associated with instability patterns was identified and quantified, revealing a significant influence of seismic activity over water level on failure probabilities. The findings delineate two primary instability patterns of reservoir accumulation landslides: deep-seated instability along the slip zone and localized shallow instability within the sliding mass, both of which initiate at the leading edge, manifesting a sequence of retrogressive and progressive failures. This study offers a novel approach to understanding instability pattern uncertainty and establishes a feasible framework for risk assessment of reservoir landslides.

The modified Cam-clay model (MCC model) is capable of representing the consolidation process of the soil under a complex stress path and thus is extensively adopted in the numerical analysis of excavation engineering. For reliability problems of ground surface settlement of excavation, minimal attention has been paid to investigating the effect of spatial variable MCC model parameters on the settlement during the staged construction of the excavation. Based on laboratory tests and sensitivity analysis, this study launched the probabilistic transient hydro-mechanical coupling analysis of excavation settlement considering spatial variable deformation parameters (λ and κ) using an MCS-FORM hybrid approach. The results show that: (1) Both the deformation parameters have a positive relationship with the settlement, and κ has a more significant effect than λ. (2) The observed maximum settlement and the location with maximum settlement follow a log-normal distribution. (3) An increasing COV of parameters leads to an enhanced surface settlement, expansion of the significant influence region, and decreased reliability. (4) The reliability index is greatly enhanced with the delimited controlled standard value of the surface settlement, H_con, and it decreases significantly at the preliminary stage and then decreases progressively until stable during excavating. Overall, adopting the deterministic analysis without considering the spatial variability of MCC parameters leads to underestimating the risk due to the settlement and the significant influence region.

Saturated hydraulic conductivity (K_s) is spatially variable in accumulation landslide sites that exert significant effort onto landslide seepage and deformation behavior. To better understand spatial variability and the effect of K_s on the slide mass of an accumulation landslide, this study introduced the surface nuclear magnetic resonance (SNMR) technology to study a representative reservoir accumulation landslide field in the Three Gorges Reservoir area (TGRA), the Baishuihe landslide, to obtain a series of relative reliable spatial measurements of K_s effectively on the basis of calibration in terms of the field tests measurements. The estimated K_s values were distributed log‐normally for the overall landslide mass site with a wide range of 3.00 × 10⁻⁶∼7.80 × 10⁻³ cm/s, which reaches about 3 orders of magnitude. Variogram analysis indicated that the K_s values have the range (A) of 295.89 m and 65.56 m for the overall site and major cross‐sectional analysis, respectively. A finite‐element seepage‐stress analysis associated with a Kriging‐interpolated spatial K_s variable calculation model based on the best‐fitted theoretical variogram was subsequently performed to study the seepage and deformation behavior of the landslide. The available monitored data and simulated results of the finite‐element seepage‐stress analysis indicated that the Baishuihe landslide is a progressive landslide, and the main factor influencing the deformation is rainfall and reservoir water fluctuation. This study provides an unconventional framework for studying the heterogeneous geomaterial and contributes to a better understanding of the spatial variation of the hydraulic property of accumulation reservoir landslides at a field scale.