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Landslides whose slide surface is gentle near the toe and relatively steep in the middle and rear part are common in the Three Gorges Reservoir area, China. The mass that overlies the steep part of the slide surface is termed the "driving section", and that which overlies the gentle part of the slide surface is termed the "resisting section". A driving–resisting model is presented to elucidate the deformation mechanism of reservoir landslides of this type, as exemplified by Shuping landslide. More than 13 years of field observations that include rainfall, reservoir level, and deformation show that the displacement velocity of Shuping landslide depends strongly on the reservoir level but only slightly on rainfall. Seepage modeling shows that the landslide was destabilized shortly after the reservoir was first impounded to 135 m, which initiated a period of steady deformation from 2003 to 2006 that was driven by buoyancy forces on the resisting section. Cyclical water level fluctuations in subsequent years also affected slope stability, with annual "jumps" in displacement coinciding with drawdown periods that produce outward seepage forces. In contrast, the inward seepage force that results from rising reservoir levels stabilizes the slope, as indicated by decreased displacement velocity. Corrective transfer of earth mass from the driving section to the resisting section successfully reduced the deformation of Shuping landslide and is a feasible treatment for huge reservoir landslides in similar geological settings. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Landslides whose slide surface is gentle near the toe and relatively steep in the middle and rear part are common in the Three Gorges Reservoir area, China. The mass that overlies the steep part of the slide surface is termed the driving section and that which overlies the gentle part of the slide surface is termed the locking section. A driving-locking model is presented to elucidate the deformation mechanism of reservoir landslides of this type, as exemplified by Shuping landslide. More than 13 years of field observations that include rainfall, reservoir level and deformation show that the deformation velocity of Shuping landslide depends strongly on the reservoir level but only slightly on rainfall. Seepage modelling shows that the landslide was destabilized shortly after the reservoir was first impounded to 135 m, which initiated a period of steady deformation from 2003 to 2006 that was driven by buoyancy forces on the locking section. Cyclical water-level fluctuations in subsequent years also affected slope stability, with annual jumps in displacement coinciding with drawdown periods that produce outward seepage forces. In contrast, the inward seepage force that results from rising reservoir levels stabilizes the slope, as indicated by decreased deformation velocity. Corrective transfer of earth mass from the driving section to the locking section successfully reduced the deformation of Shuping landslide, and is a feasible treatment for huge reservoir landslides in similar geological settings. [ABSTRACT FROM AUTHOR]

A theoretical, dimensionless rainfall-runoff model was used to simulate the discharge of Wulongdong spring in western Hubei province, South China. The single parameter (time constant τ) in the model is easy to obtain by fitting the recession rate of the observed hydrographs. The model was scaled by simply matching the total annual flow volume of the model to the observed value. Annual distribution of actual evapotranspiration was embedded in the model input to calculate the accumulated deficit of soil moisture before each rain event. Hourly precipitation input data performed better than daily data, defining τ of 0.85 days and returning a Nash-Sutcliffe efficiency of 0.89 and the root mean square error of 0.07. This model offers an effective way to simulate the discharge of karst springs that respond sensitively to rainfall events. The model parameters of a successful simulation can be used to estimate the recharge area and indicate the intrinsic response time of the basin. Copyright © 2016 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Five large and many small landslides are developed in Jurassic strata along the lower reaches of Xiangxi River, where interbedded weak and hard bedrock layers foster the development of landslides with a "stair-step" sliding surface. The paper investigates the evolution characteristics of these landslides and presents a novel forecasting model for their displacements. The distribution characteristics and behavior of landslides developed along Xiangxi River is revealed by the database of landslides in the larger Zigui basin, of which this area is part. Most landslides occur at rather low elevations of <300 m and in areas of moderate rainfall. The geological evolution of landslides in the Xiangxi River valley can be divided into four stages, beginning with anticline formation, followed by valley incision, then by weathering and erosion, and culminating in formation of the colluvial landslides. The accumulative displacement curves of landslides with a stair-step sliding surface in Xiangxi River region also present obvious, step-like characteristics. A novel GA-CEEMD-RF algorithm was developed to predict the displacement of these stair-step landslides, which helps to define the combination of induced factors and weak stableness of prediction results using a single displacement prediction model and the multi-field monitoring data. • The distribution characteristics of landslides developed along lower reaches of Xiangxi River was revealed. • Interbedded weak and hard bedrock layers foster the development of landslides with a "stair-step" sliding surface. • The geological evolution of landslides in the Xiangxi River valley can be divided into four stages. • A novel GA-CEEMD-RF algorithm was developed to predict the displacement of stair-step landslides. [ABSTRACT FROM AUTHOR]

Variations of reservoir water level and seasonal precipitation have resulted in significant movement and destabilization of landslides in the Three Gorges Reservoir (TGR) region of China since reservoir impoundment in 2003. An example is the Baijiabao landslide, a large, actively creeping landslide located in the steep lower valley of the Xiangxi River, about 55 km upstream of the TGR dam in the Yangtze River. Twelve years of monthly monitoring at four GPS stations and routine, monthly field observations show cumulative GPS displacements as large as >1.5 m and widely developed ground cracks. GPS monitoring results show that most movement takes place in rapid steps that coincide with the rainy season and the period of annual reservoir drawdown, with particularly large steps in 2009, 2012 and 2015. This step-like pattern of displacement is also shown by daily data from an automatic monitoring system installed in 2017. The total period of acceleration shown by these daily data was about six weeks long, with rapid movement starting during rapid reservoir drawdown, and terminating when the reservoir began to rise again. In particular, most of the 2018 displacement occurred in only two weeks. Different subzones of the landslide move at different rates and exhibit different features of deformation. The neighborhood rough set theory is used to identify the triggering factors responsible for landslide deformation. The most important triggering factors vary between different sites, data types and the time interval used to define them. The surface deformation and ground crack widening are controlled by the combination of rainfall and variations in the reservoir water levels, whereas the deformation of the sliding zone is most sensitive to the latter. The results show that daily data are needed to capture important, short-term landslide responses. The neighborhood rough set theory for determination of triggering factors is suggested for deformation prediction, stability evaluation, and prevention and control of reservoir landslides in this and other regions. • Spatiotemporal deformation characteristics of Baijiabao landslide over a twelve-year period are analyzed in detail. • Different acceleration periods and threshold hydraulic conditions are observed from daily and monthly monitoring data. • Neighborhood rough set theory is used to identify the triggering factors responsible for landslide deformation. • The most important triggering factors vary between different sites, data types and the time interval used to define them. [ABSTRACT FROM AUTHOR]

• A modified Bayesian sequential updating approach is proposed to estimate GSI. • Multi-source information can be integrated in the approach. • GSI can be estimated using limited data based on various rock mass classifications. • Evaluated probabilistic characteristics of the GSI agree with the observed GSI data. • Rational result is achieved by taking model uncertainties as random normal variables. Explicit determination of geotechnical parameters is an important but difficult task in rock engineering. Paradoxically, data are often limited even though data from multiple sources (e.g., different testing procedures, testing positions, and estimation models) are commonly available, and the integration of multi-source information for the determination of geotechnical parameters in a probabilistic context remains a great challenge. We have modified an existing Bayesian sequential updating approach and used it for the first time to estimate the geological strength index (GSI) of rock masses by integrating multi-source information in a way that considers prior information, multiple estimation models and probabilistic properties of model uncertainties. The argillaceous siltstone in Zigui County in the Three Gorges Reservoir region of China was used to quantitatively illustrate this method. Three data sets using rock mass rating (RMR)-, tunneling quality index (Q)-, and rock mass index (RMi)-based estimation models were sequentially incorporated into the Bayesian sequential updating framework, through which the information on the mean value and standard deviation of the GSI can be updated. Then a large number of equivalent GSI samples were generated through Markov chain Monte Carlo (MCMC) simulation for further statistical analysis. The results showed that the proposed Bayesian sequential updating approach can provide reasonable probabilistic estimates of the GSI, which compared well with observed data using the standard GSI chart. The Bayesian sequential updating approach is a promising tool for geotechnical parameter estimation and can combine large amounts of information, thereby effectively depicting the probabilistic characteristics of GSI. [ABSTRACT FROM AUTHOR]