Investigating a potential reservoir landslide and suggesting its treatment using limit-equilibrium and numerical methods

A reservoir landslide not only reduces the water storage capacity, but also causes extensive damages to the dam body, power/water transmission lines, roads, and other infrastructures. The Latian Dam, located 35 km north east of Tehran （Iran）, is one of the cases which has encountered serious problems with instability of its rock abutments. This paper addresses the stability analysis of the right abutment of the Latian Dam using limit equilibrium and numerical methods. Geomechanical characteristics of the rock abutment were first estimated based on engineering classification of the rock mass. Different search methods were examined for locating the critical circular/non-circular slip surface in conjunction with the general limit equilibrium method. The effect of variabi]ity of rock mass properties, water table, and earthquake load on the factor of safety （FS） and probability of failure （PF） was studied. In the event of rapid drawdown in the reservoir, the limit equilibrium analysis calculated FS=1.067 and PF=21.1%, and the numerical analysis returned FS=1.01. The results of the analyses suggest that the right abutment of the Latian Dam is prone to slide and needs treatment. Investigations demonstrated that a slope reduction by 15° at the upper part of the abutment would meet stability conditions even in the worst-case scenario （FS=1.297 and PF=2.07%）.

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 interfaces beyond the slip surface to progressive failure.Here,we aim to investigate the subsurface multiphysics 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 specialpurpose 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.

System Reliability Analysis of Reservoir Landslides:Insights from Long-Term Reservoir Operation

The reservoir operation awakens numerous landslides with multiple sliding surfaces known as reservoir landslides,and the systematic stability analysis for such landslides is becoming increasingly urgent.Taking the Majiagou landslide as an example,this paper analyses the comprehensive performance of the landslide from a probabilistic point of view.Under a reservoir operation cycle,a series of numerical analyses are carried out to simulate the migration of the seepage field,then the dynamic stability of the landslide is quantified accordingly.Subsequently,the wetting-drying cycles test is used to model the weakening of strength parameters in hydro-fluctuation belt under the long-term reservoir operation.Considering the weakening effect of long-term reservoir operation on the hydrofluctuation belt,the system reliability is evaluated using the Ditlevsen's bounds.The results suggest that the reservoir operation can affect the stability of the landslide by changing the seepage field.The system failure probability gradually rises as the number of wetting-drying cycles increases.Compared with conventional probabilistic analysis that calculates the failure probability of each sliding surface mechanically,analyzing the landslide in terms of system reliability can effectively narrow the failure probability range,which provides an insightful idea for evaluating the systematic stability of analogous reservoir landslides.

Centrifuge modeling of unreinforced and multi-row stabilizing piles reinforced landslides subjected to reservoir water level fluctuation

With the construction of the Three Gorges Reservoir dam,frequent reservoir landslide events have been recorded.In recent years,multi-row stabilizing piles(MRSPs)have been used to stabilize massive reservoir landslides in China.In this study,two centrifuge model tests were carried out to study the unreinforced and MRSP-reinforced slopes subjected to reservoir water level(RWL)operation,using the Taping landslide as a prototype.The results indicate that the RWL rising can provide lateral support within the submerged zone and then produce the inward seepage force,eventually strengthening the slope stability.However,a rapid RWL drawdown may induce outward seepage forces and a sudden debuttressing effect,consequently reducing the effective soil normal stress and triggering partial pre-failure within the RWL fluctuation zone.Furthermore,partial deformation and subsequent soil structure damage generate excess pore water pressures,ultimately leading to the overall failure of the reservoir landslide.This study also reveals that a rapid increase in the downslope driving force due to RWL drawdown significantly intensifies the lateral earth pressures exerted on the MRSPs.Conversely,the MRSPs possess a considerable reinforcement effect on the reservoir landslide,transforming the overall failure into a partial deformation and failure situated above and in front of the MRSPs.The mechanical transfer behavior observed in the MRSPs demonstrates a progressive alteration in relation to RWL fluctuations.As the RWL rises,the mechanical states among MRSPs exhibit a growing imbalance.The shear force transfer factor(i.e.the ratio of shear forces on pile of the n th row to that of the first row)increases significantly with the RWL drawdown.This indicates that the mechanical states among MRSPs tend toward an enhanced equilibrium.The insights gained from this study contribute to a more comprehensive understanding of the failure mechanisms of reservoir landslides and the mechanical behavior of MRSPs in reservoir banks.

Time series prediction of reservoir bank landslide failure probability considering the spatial variability of soil properties

Historically,landslides have been the primary type of geological disaster worldwide.Generally,the stability of reservoir banks is primarily affected by rainfall and reservoir water level fluctuations.Moreover,the stability of reservoir banks changes with the long-term dynamics of external disastercausing factors.Thus,assessing the time-varying reliability of reservoir landslides remains a challenge.In this paper,a machine learning(ML)based approach is proposed to analyze the long-term reliability of reservoir bank landslides in spatially variable soils through time series prediction.This study systematically investigated the prediction performances of three ML algorithms,i.e.multilayer perceptron(MLP),convolutional neural network(CNN),and long short-term memory(LSTM).Additionally,the effects of the data quantity and data ratio on the predictive power of deep learning models are considered.The results show that all three ML models can accurately depict the changes in the time-varying failure probability of reservoir landslides.The CNN model outperforms both the MLP and LSTM models in predicting the failure probability.Furthermore,selecting the right data ratio can improve the prediction accuracy of the failure probability obtained by ML models.

Fiber optic monitoring of an anti-slide pile in a retrogressive landslide

Anti-slide piles are one of the most important reinforcement structures against landslides,and evalu-ating the working conditions is of great significance for landslide mitigation.The widely adopted analytical methods of pile internal forces include cantilever beam method and elastic foundation beam method.However,due to many assumptions involved in calculation,the analytical models cannot be fully applicable to complex site situations,e.g.landslides with multi-sliding surfaces and pile-soil interface separation as discussed herein.In view of this,the combination of distributed fiber optic sensing(DFOS)and strain-internal force conversion methods was proposed to evaluate the working conditions of an anti-sliding pile in a typical retrogressive landslide in the Three Gorges reservoir area,China.Brillouin optical time domain reflectometry(BOTDR)was utilized to monitor the strain distri-bution along the pile.Next,by analyzing the relative deformation between the pile and its adjacent inclinometer,the pile-soil interface separation was profiled.Finally,the internal forces of the anti-slide pile were derived based on the strain-internal force conversion method.According to the ratio of calculated internal forces to the design values,the working conditions of the anti-slide pile could be evaluated.The results demonstrated that the proposed method could reveal the deformation pattern of the anti-slide pile system,and can quantitatively evaluate its working conditions.

A Predictive,Two-Parameter Model for the Movement of Reservoir Landslides

Monitoring data show that many landslides in the Three Gorges region,China,undergo step-like displacements in response to the managed,quasi-sinusoidal annual variations in reservoir level.This behavior is consistent with motion initiating when the reservoir water level falls below a critical level that is intrinsic to each landslide,with the subsequent displacement rate of the landslide being proportional to the water depth below that critical level.Most motion terminates when the water level rises back above the critical level,so the annual step size is the time integral of the instantaneous displacement rate.These responses are incorporated into a differential equation that is easily calibrated with monitoring data,allowing prediction of landslide movement from actual or anticipated reservoir level changes.Model successes include(1)initiation and termination of the annual sliding steps at the critical reservoir level,producing a series of steps;(2)prediction of variable step size,year to year;and(3)approximate prediction of the shape and size of each annual step.Annual rainfall correlates poorly with step size,probably because its effect on groundwater levels is dwarfed by the 30 m annual variations in the level of the Three Gorges Reservoir.Viscous landslide behavior is suggested.

Reservoir-induced landslides and risk control in Three Gorges Project on Yangtze River,China

The Three Gorges region in China was basically a geohazard-prone area prior to construction of the Three Gorges Reservoir （TGR）. After construction of the TGR, the water level was raised from 70 m to 175 m above sea level （ASL）, and annual reservoir regulation has caused a 30-m water level difference after impoundment of the TGR since September 2008. This paper first presents the spatiotemporal distribution of landslides in six periods of 175 m ASL trial impoundments from 2008 to 2014. The results show that the number of landslides sharply decreased from 273 at the initial stage to less than ten at the second stage of impoundment. Based on this, the reservoir-induced landslides in the TGR region can be roughly classified into five failure patterns, i.e. accumulation landslide, dip-slope landslide, reversed bedding landslide, rockfall, and karst breccia landslide. The accumulation landslides and dip-slope landslides account for more than 90%. Taking the Shuping accumulation landslide （a sliding mass volume of 20.7 × 106 m^3） in Zigui County and the Outang dip-slope landslide （a sliding mass volume of about 90 × 106 m^3） in Fengjie County as two typical cases, the mechanisms of reactivation of the two landslides are analyzed. The monitoring data and factor of safety （FOS） calculation show that the accumulation landslide is dominated by water level variation in the reservoir as most part of the mass body is under 175 m ASL, and the dip-slope landslide is controlled by the coupling effect of reservoir water level variation and precipitation as an extensive recharge area of rainfall from the rear and the front mass is below 175 m ASL. The characteristics of landslide-induced impulsive wave hazards after and before reservoir impoundment are studied, and the probability of occurrence of a landslide-induced impulsive wave hazard has increased in the reservoir region. Simulation results of the Ganjingzi landslide in Wushan County indicate the strong relationship between landslide-induced surge and water variation with high potential risk to shipping and residential areas. Regarding reservoir regulation in TGR when using a single index, i.e. 1-d water level variation, water resources are not well utilized, and there is also potential risk of disasters since 2008. In addition, various indices such as 1-d, 5-d, and 10-d water level variations are proposed for reservoir regulation. Finally, taking reservoir-induced landslides in June 2015 for example, the feasibility of the optimizing indices of water level variations is verified.

Model test of the influence of cyclic water level fluctuations on a landslide

Many landslides in reservoir areas continuously deform under cyclic water level fluctuations due to reservoir operations. In this paper,a landslide model, developed for a typical colluvial landslide in the Three Gorges Reservoir area, is used to study the effect of cyclic water level fluctuations on the landslide. Five cyclic water level fluctuations were implemented in the test, and the fluctuation rate in the last two fluctuations doubled over the first three fluctuations. The pore water pressure and lateral landslide profiles were obtained during the test. A measurement of the landslide soil loss was proposed to quantitatively evaluate the influence of water level fluctuations. The test results show that the first water level rising is most negative to the landslide among the five cycles. The fourth drawdown with a higher drawdown rate caused further large landslide deformation. An increase of the water level drawdown rate is much more unfavorable to the landslide than an increase of the water level rising rate. In addition, the landslide was found to have an adaptive ability to resist subsequent water level fluctuations after undergoing large deformation during a water level fluctuation. The landslide deformation and observations in the field were found to support the test results well.

Physical Prediction Model of Compound Hydrodynamic Unload-Load Response Ratio and Its Application in Reservoir Colluvium Landslide

It is well known that the deformation and damage of reservoir colluvium landslides are often determined by the combined dynamics of reservoir water level change and rainfall.Based on the systematic analysis of the change law of reservoir water level,rainfall and displacements of reservoir colluvium landslide,this paper proposes the compound hydrodynamic action of rainfall and reservoir water as the unload-load parameter,and the landslide displacement as the unload-load response parameter.Based on this,a physical prediction model of the compound hydrodynamic unload-load response ratio of reservoir colluvium landslide was established,and the quantitative relationship between the compound hydrodynamic unload-load response ratio and its stability evolution was in-depth analyzed and determined.On the basis of the above research,taking Shuping landslide,a typical hydrodynamic pressure landslide as an example,the unload-load response ratio model is used to systematically evaluate and predict the stability evolution law and the change trend of the landslide under compound hydrodynamic action.The prediction result shows that the variation law of the compound hydrodynamic unload-load response ratio is consistent with the dynamic evolution law of its stability.Therefore,the above studies show that the compound hydrodynamic unload-load response ratio parameter is an effective displacement dynamic evaluation parameter for reservoir colluvium landslides,so it can be used in the prediction of the reservoir colluvium landslides.

Probing multi-physical process and deformation mechanism of a largescale landslide using integrated dual-source monitoring

The implementation of isolated heterologous monitoring systems for spatially distant borehole deployments often comes with substantial equipment costs,which can limit the effectiveness of geohazard mitigation and georisk management efforts.To address this,we have developed a novel monitoring system that integrates fiber Bragg grating(FBG)and microelectromechanical system(MEMS)techniques to capture soil moisture,temperature,sliding resistance,strain,surface tilt,and deep-seated inclination.This system enables real-time,simultaneous data acquisition and cross-validation analyses,offering a costeffective solution for monitoring critical parameters in geohazard-prone areas.We successfully applied this integrated monitoring system to the Xinpu landslide,an active super-large landslide located in the Three Gorges Reservoir Area(TGRA)of China.The resulting strain profile confirmed the presence of two shallow secondary sliding surfaces at depths of approximately 7 m and 12 m,respectively,in addition to the deep-seated sliding surface at a depth of28 m.The lower secondary sliding surface was activated by extreme precipitation,while the upper one was primarily driven by significant changes in reservoir water levels and secondarily triggered by concentrated rainfalls.Anti-slide piles have remarkably reinforced the upper moving masses but failed to control the lower ones.The gap between the pile heads and the soil amplified the rainwater erosion effect,creating a preferential channel for rainwater infiltration.Multi-physical measurements revealed a mixture of seepage-driven and buoyancy-driven behaviors within the landslide.This study offers an integrated dual-source multi-physical monitoring paradigm that enables collaborative management of multiple crucial boreholes on a large-scale landslide,and contributes to the evaluation and improvement of engineering measures in similar geological settings.