论滑坡学

滑坡学可分为理论滑坡学和应用滑坡学．前者的分支有：滑坡发生学、滑坡运动学、滑坡组构学、滑坡形态学、滑坡断代－周期学、滑坡分类学、滑坡分布学、滑坡制图学、滑坡编目学和滑坡数据库系统等．应用滑坡学含滑坡研究方法论、技术手段和滑坡防御工程等．

滑坡灾害与滑坡学科略论

本文简述了滑坡灾害与滑坡学的基本内容，对勘测滑坡学和比较滑坡学略加侧重，预期从学理上予以系统化并力求有所提高。指出易滑动理论是滑坡学的基本理论基础，非线性动力学是易滑动理论的基本研究方法之一。同时关于滑坡的预测和防治方面提出了几点看法，强调指出滑坡灾害与环境地学和气候、水文密切相关。

预测滑坡学概要

预测滑坡学是滑坡学与预测科学交叉的分支科学，是滑坡学的主要组成部分。预测滑坡学是利用预测科学的预测理论，结合滑坡学的具体特征及规律，针对滑坡灾害进行预测预报的系统科学。预测滑坡学应用与发展了预测科学的理论与技术方法，从滑坡预测原理、滑坡预测基础、滑坡预测方法与技术手段及滑坡时空预测的实际应用与检验等方面确定了预测滑坡学的基本内容。本文将概要介绍预测滑坡学的这些基本内容，以此推介《滑坡学》的科学专著。

滑坡预测的作用学原理

滑坡预测的作用学原理是根据作用学关于作用的对立统一理论等建立的一种预测滑坡灾害现象发生的科学方法，其主要内容是说明控制滑坡现象发生的作用因素、边坡物质性质因素与滑坡现象发生之间的定量关系，进而给出滑坡预测研究的内容和方法，为人们从事滑坡预测与防治研究指明了方向。

A Comparison of Conventional and Shear-Rate Dependent Mohr-Coulomb Models for Simulating Landslides

Landslides may cause many fatalities and heavy economic losses,so it is vital to understand their mechanics so as to take appropriate measures to mitigate their risk.Phenomenally,the loose soil behaves like frictional material in most circumstances,so Mohr-Coulomb type equations are often used to describe their movement.However,these models generally do not consider the influence of the shearrate on the Mohr-Coulomb friction angle,so the shear-rate dependence effect on the soil flow and landslide runout is not well understood.This paper reports on an application of the incompressible Smoothed Particle Hydrodynamics(SPH) method to the dynamics of dry granular assemblies.The traditional model with a constant friction angle is compared with the modified Mohr-Coulomb model with a variable friction angle related to the shear-rate.It is found that the shear-rate dependence effect is negligible for shallow granular flows along mild slopes.With steeper slopes of the ground and larger aspect ratios of the initial soil column,the rate-dependence effect becomes more important.

Study on distribution rule of sliding pushing force and remnant resistant sliding force acting on anti-sliding pile

Anti-slide pile is one of the important methods to administer landslide geological disaster because of its advantages.It plays important role in administering landslide.It is a premise of reasonable economy and technological advance to know the distribution rule and feature of the force between anti-sliding pile and surrounding rock.To determine the sliding force and remnant resistant sliding force,according to need of study,this paper sets up the geological model and mechanics model in term of a typical landslide,and analyzes the effect rule of sliding body distortion,strength and gravity to the pushing force and remnant resistant sliding force by use of the numerical model.The distribution rule of pushing force and remnant resistant sliding force of the type of landslide is given.

Seismic failure mechanisms for loaded slopes with associated and nonassociated flow rules

Seismic failure mechanisms were investigated for soil slopes subjected to strip load with upper bound method of limit analysis and finite difference method of numerical simulation,considering the influence of associated and nonassociated flow rules.Quasi-static representation of soil inertia effects using a seismic coefficient concept was adopted for seismic failure analysis.Numerical study was conducted to investigate the influences of dilative angle and earthquake on the seismic failure mechanisms for the loaded slope,and the failure mechanisms for different dilation angles were compared.The results show that dilation angle has influences on the seismic failure surfaces,that seismic maximum displacement vector decreases as the dilation angle increases,and that seismic maximum shear strain rate decreases as the dilation angle increases.

Analysis on the Dynamical Process of Donghekou Rockslide-Debris Flow Triggered by 5.12 Wenchuan Earthquake

Among the geo-hazards caused by the great Wenchuan Earthquake, the rapid and long runout rockslide-debris flow is of primary concern due to the large volume of displaced material and the resultant catastrophic impacts to the landscape and socioeconomic structure. In order to analyze the dynamical process of this kind of geo-hazard, the Donghekou rockslide-debris flow is given as an example in this paper. This event, which killed 780 people, initiated at an elevation of 1300 m with a total long run-out distance of more than 2400 m. The slide mass is mainly composed of dolomite limestone and siliceous limestone of Sinian system, together with carbon slate and phyllite of Cambrian. During the processes from slide initiation to the final cessation of slide movement, five dynamic stages took place, here identified as the initiation stage, the acceleration of movement stage, the air-blast effect stage, the impact and redirection stage and the long runout slidematerial accumulation stage. Field investigations indicate that due to the effects of the earthquake, the dynamics of the Donghekou rockslide-debris flow are apparently controlled by geologic and tectonic conditions, the local geomorphological aspects of the terrain, and the microstructural and macroscopic mechanical properties of rocks which compose the slide mass. These three main factors which dictate the Donghekou rockslide-debris flow dynamics are discussed in detail in this paper, and significant results of field investigations and tests of materials are presented. The above dynamical processes are analyzed in this paper, and some useful conclusions have been gained.

Performance of Slope Behavior Indicators in Unsaturated Pyroclastic Soils

Landslide risk is increasing in many parts of the world due to growth of population and infrastructures. Therefore, an effort has to be made in developing new and cheap sensors for areas susceptible of landslides to continuously control the slope behaviour, until approaching failure conditions. The paper reported experimental data from smallscale physical models about the performance of Time Domain Reflectometry(TDR) and optical fibres, which act as the indicators of the incoming failure of slopes covered by unsaturated granular soils. Obtained results appear encouraging, since both sensors provide continuous information about the state of the slope, in terms of water content profiles and ongoing deformations, induced by rainwater infiltration, even immediately before the triggering of a fast landslide.

Mechanism and Geo-mechanics Models of Landslides Triggered by 5.12 Wenchuan Earthquake

Due to the extremely high magnitude, long duration, and the complicated geo-environment in the disaster area, the great 5.12 Wenchuan Earthquake not only produced a huge number of landslides and rockfalls, but also involved complicated dynamic processes. These processes are quite different from the characteristics of landslides and rockfalls under general gravitational force, and presently human knowledge is very poor in this field. In order to describe the special dynamic processes, some terms such as shattering-cracking, shattering-sliding, shattering-falls and ejection are defined in this paper. Combined with slope structures, a mechanism classification system of strong earthquake-triggered landslide and rockfall is suggested, which is divided into 5 categories and 14 types. This paper also analyzes the basic characteristics, dynamic processes and geo-mechanics conceptual models of some typologies, especial the type of shattering-sliding for most large-scales landsides. This paper initially reveals the formation mechanism, geo-mechanics models and dynamic features of landslides and rockfalls triggered by the great Wenchuan Earthquake.

Mechanical-Mathematical Modeling and Monitoring for Landslide Processes

Landslides are one of the most widespread and dangerous phenomena in the urbanized territories. In Moscow they affect about 3% of the most valuable territory, including churches and historical buildings located at high banks of the Moskva River. Recently the landslide activation occurred. Normal functioning of city infrastructure and implementation of effective slope protection measures require special landslide monitoring. Mechanical-mathematical model of high viscous fluid was applied for the landslide-prone slopes modeling. Equation of continuityand an approximatedNavier-Stockes equation f or slow motions in a thin layer were used. The results of modelling give possibility to define the landslide section with upmost velocity that should be monitored in the first place. Some important parameters used for numerical modelling can be defined from monitoring data.

A TREND DISPLACEMENT ANALYSIS FOR SPACE AND TIME ON XINTAN LANDSLIDE

This paper, having made systematic trend analysis on the front and rear segments of Xintan landslide for space and time respectively by using matbematical statistical principles,discovered that there is obvious trend displacement Of the monitoring points in the rear margin area of the slope and the rates of trend displacement gradually increase with time whereas there is no trend displacement of the monitoring points in the front margin area. This result suggests that the rear margin area of segment is an area of overall sliding and is transforming towards destabilization whereas the front margin area is an area of relative stability. This analytical result well coincides with the conclusion of evaluation on dynamic stability. The analytical result mentioned above shows that the medium to short term forecast and prediction of slope stability can be made by using trend displacement analysis technique in order to achieve the goal of timely evaluation and prevention.

Displacement Trends of Slow-moving Landslides: Classification and Forecasting

A framework is proposed to characterize and forecast the displacement trends of slow-moving landslides, defined as the reactivation stage of phenomena in rocks or fine-grained soils, with movements localized along one or several existing shear surfaces. The framework is developed based on a thorough analysis of the scientific literature and with reference to significant reported case studies for which a consistent dataset of continuous displacement measurements is available. Three distinct trends of movement are defined to characterize the kinematic behavior of the active stages of slow-moving landslides in a velocity-time plot: a linear trend-type I, which is appropriate for stationary phenomena; a convex shaped trend-type II, which is associated with rapid increases in pore water pressure due to rainfall, followed by a slow decrease in the groundwater level with time; and a concave shaped trend-type III, which denotes a non-stationary process related to the presence of new boundary conditions such as those associated with the development of a newly formed local slip surface that connects with the main existing slip surface. Within the proposed framework, a model is developed to forecast future displacements for active stages of trend-type II based on displacement measurements at the beginning of the stage. The proposed model is validated by application to two case studies.

A back-propagation neural-network-based displacement back analysis for the identification of the geomechanical parameters of the Yonglang landslide in China

Xigeda formation is a type of hundredmeter-thick lacustrine sediments of being prone to triggering landslides along the trunk channel and tributaries of the upper Yangtze River in China. The Yonglang landslide located near Yonglang Town of Dechang County in Sichuan Province of China, which was a typical Xigeda formation landslide, was stabilized by anti-slide piles. Loading tests on a loading-test pile were conducted to measure the displacements and moments. The uncertainty of the tested geomechanical parameters of the Yonglang landslide over certain ranges would be problematic during the evaluation of the landslide. Thus, uniform design was introduced in the experimental design,and by which, numerical analyses of the loading-test pile were performed using Fast Lagrangian Analysis of Continua(FLAC3D) to acquire a database of the geomechanical parameters of the Yonglang landslide and the corresponding displacements of the loadingtest pile. A three-layer back-propagation neural network was established and trained with the database, and then tested and verified for its accuracy and reliability in numerical simulations. Displacement back analysis was conducted by substituting the displacements of the loading-test pile to the well-trained three-layer back-propagation neural network so as to identify the geomechanical parameters of the Yonglang landslide. The neuralnetwork-based displacement back analysis method with the proposed methodology is verified to be accurate and reliable for the identification of the uncertain geomechanical parameters of landslides.

Using Statistical Learning Algorithms in Regional Landslide Susceptibility Zonation with Limited Landslide Field Data

Regional Landslide Susceptibility Zonation(LSZ) is always challenged by the available amount of field data, especially in southwestern China where large mountainous areas and limited field information coincide. Statistical learning algorithms are believed to be superior to traditional statistical algorithms for their data adaptability. The aim of the paper is to evaluate how statistical learning algorithms perform on regional LSZ with limited field data. The focus is on three statistical learning algorithms, Logistic Regression(LR), Artificial Neural Networks(ANN) and Support Vector Machine(SVM). Hanzhong city, a landslide prone area in southwestern China is taken as a study case. Nine environmental factors are selected as inputs. The accuracies of the resulting LSZ maps are evaluated through landslide density analysis(LDA), receiver operating characteristic(ROC) curves and Kappa index statistics. The dependence of the algorithm on the size of field samples is examined by varying the sizes of the training set. The SVM has proven to be the most accurate and the most stable algorithm at small training set sizes and on all known landslide sizes. The accuracy of SVM shows a steadilyincreasing trend and reaches a high level at a small size of the training set, while accuracies of LR and ANN algorithms show distinct fluctuations. The geomorphological interpretations confirm the strength of SVM on all landslide sizes. Our results show that the strengths of SVM in generalization capability and model robustness make it an appropriate and efficient tool for regional LSZ with limited landslide field samples.

Anthropogenic Earth-Change： We Are on a Slippery Slope, Breaking New Ground and It＇s Our Fault---A Multi-disciplinary Review and New Unified Earth-System Hypothesis

Human activity could be changing the Earth＇s foundations themselves, as we affect multiple systems interacting in feedback mechanisms changing the atmosphere, hydrosphere, cryosphere, biosphere, and even the lithosphere （solid surface） and asthenosphere （deformable semi-molten rock layer beneath）. Anthropogenic movement of ice, water and sediment alters viscosity and movement of the asthenosphere; this induces earthquakes, tsunamis, volcanism and rifting, and may induce plate-tectonic-change. These processes may account for the timing of unexplained contemporary Icelandic, New Zealand, Chilean, Japanese and Indonesian seismicity, volcanism and magma movement. Climate-change and sea-level rise are creating： slip-planes from differential water pore-pressures and/or weakening of previous fault-planes; sediment-change and altered hydrology and reservoir-mass, inducing isostasy and further change in pore-pressure. Loss of plant biomass and diversity alter hydrology, precipitation and transpiration, causing isostasy and further sediment- and climate-change. Increased ocean-mass, temperatures and acidity, reduced oceanic oxygenation, and increased transport of （organic） sediments elevate the production and destabilisation of gas-hydrates, causing slumps and tsunamis. Isostasy and altered viscosity of the asthenosphere increase seismicity, slope and faulting, which are the prime triggers for slumping and tsunamis. Altered asthenosphere flows hasten subduction and rifting landward of subduction, enhancing volcanism. All of these processes predominantly coincide, temporally and spatially, in the coasts and continental margins, and the Pacific ring-of-fire, although response times and extents may vary from immediate to multi-millennial scales and from negligible to catastrophic. Contemporary Icelandic seismic and volcanic activity is explained by depleted magma reserves on the north-western side of the mid-ocean ridge as asthenosphere moves from the constructive boundary under deglaciating and rising Greenland.

Study on Landslide Surge in Reservoir Area

Landslide surge is a fluid-solid coupling problem involving multidisciplinary intersections such as landslide dynamics, fluid mechanics and mechanics along the way, which has important research value. The construction of the reservoir will affect the natural geological conditions of the slope of the reservoir area, slope rock under the joint effect of the waves and the reservoir water level changes, which will cause the reservoir bank collapse and even landslides. The occurrence of landslide will cause some loss. In this paper, the types of landslide generation, disaster classification, research methods and existing problems are reviewed. It makes people understand the basic research ideas of landslide surge. Through the analysis and discussion of the different research methods of landslide surges, the shortcomings of these analytical methods are analyzed, which provide important basis for future research and indicate the future research methods and direction.

Algorithms for intelligent prediction of landslide displacements

Landslides represent major threats to life and property in many areas of the world,such as the landslides in the Three Gorges Dam area in China's Mainland.To better prepare for landslides in this area,we explored how several machine learning algorithms(long short term memory(LSTM),random forest(RF),and gated recurrent unit(GRU))might predict ground displacements under three types of landslides,each with distinct step-wise displacement characteristics.Landslide displacements are described with trend and periodic analyses and the predictions with each algorithm,validated with observations from the Three Gorges Dam reservoir over a one-year period.Results demonstrated that deep machine learning algorithms can be valuable tools for predicting landslide displacements,with the LSTM and GRU algorithms providing the most encouraging results.We recommend using these algorithms to predict landslide displacement of step-wise type landslides in the Three Gorges Dam area.Predictive models with similar reliability should gradually become a component when implementing early warning systems to reduce landslide risk.

Multi-scale chemo-mechanical analysis of the slip surface of landslides in the Three Gorges, China

Multi-scale chemo-mechanical effects and microscopic failure modes are explored in the evolution of strength change of slip surface. Direct shear equipments, scanning electro-microscope and X-ray diffraction are used to trace the change in strength of remodeled soils of slip surfaces in the Three Gorges area. Results show that there is a release of alkali metals and concentration of clay minerals on the surface. During the tests, potassium ions were released, the cementation was reduced, and the ratio of interlayer minerals varied associated with strength change. Accordingly, illites or montmorillonite-illite mixtures turned into montmorillonite. So the strength change originates from the release of alkali metal ions on molecular scale that leads to the concentration and transition of clay minerals on meso-scale. The evolution of slip surface and soil strength is a typical process involving multi-scale processes of structure changes and chemo-mechanical coupling.