Research On Prediction And Forecast Of Progressive Bank Landslide In The Three Gorges Reservoir

Reservoir at home and abroad, especially in the large reservoir, the cycle of periodic fluctuations of water level often induce the production of new or revived old landslide. Such landslides affected by reservoir water and conceived by bank slope are often referred to as bank landslides. A large number of surveys and studies show that the landslides caused by reservoir operation and the phenomenon of generation and resurrection are widespread in the hills and mountains. The consequences of failure often cause very serious damages, sometimes are even catastrophic. At present in the work of geological disaster prevention, landslide monitoring and forecasting is one of the important means to avoid and reduce the bank landslides hazards.In the current research of landslide, landslide prediction is one of the most important and cutting-edge research focuses. Despite several decades of development, the methods and theory of landslide prediction has made considerable progress, and in practice also had some success. However, many landslide forecasting and warning practice has shown that the present theory, model or criterion of landslide prediction still can not make accuracy forecast of the deformation evolution behavior and the specific failure real time. For the reason, on the one hand the most of the prediction theories, models or criterion are lack of solid geological, mechanical and physical basis which is inadequately combined with the specific deformation and evolutionary mechanisms of the single landslide; on the other hand it emphasis too much on exploring the models or criterion to predict the failure time, while ignoring the dynamical prediction in facts of environment (rainfall and water level change) and the prediction of long-term deformation trends based on real time monitoring information as well as landslide evolution stage discrimination. Such forecast ideas separate the inherent evolution law of preparation-deformation-instability. For the prediction of reservoir landslide, under the complex fluctuation of reservoir water, in particular, overlapped with the rainfall and other factors, the deformation mechanism and its manifestations are different. Therefore, in view of the complexity and diversity, it is not enough only depending on the forecasting models or criterion for predicting specific failure time in terms of the prediction of bank landslides.In view of the above problems, based on the long displacement monitoring data of about 80 large-scale bank landslides in head region of the Three Gorges Reservoir Area and a large number of field investigations, integrated with geology, landslide science, rock and soil mechanics, reliability theory, numerical simulation technology, statistical analysis and nonlinear theory, combining the prediction issues of progressive landslide in the Three Gorges Reservoir Area, the paper develops its research systematically:Centering on the mechanical process of progressive failure of reservoir landslide and its manifestations, combined with the joint action effects of rainfall and changes of the reservoir water level, progressive failure probability of reservoir landslide is studied; Besides, according to the displacement information of actual landslide, the method of landslide deformation evolutionary stage identification and quantification prediction model of landslide failure are also studied. The main results and conclusions are as follows:(1) On the basis of landslide classification theory, according to the deformation and stress states of landslide, the geological model classification which can reflect the temporal evolution characteristics of landslide deformation is put forward. The landslide can be grouped into six types, respectively, progressive lapsed landslide, progressive and tractive landslide, progressive translational landslide, mutational lapsed landslide, mutational tractive landslide, mutational and translational landslide.(2) study the reservoir landslide influencing factors based on a large number of actual monitoring data of the landslide instances in long time and a lot of field work:I find that the progressive landslide's slope body, whose structure is loose and material composition is uneven which can provide deformation development space for landslide local inhomogeneous deformation, is mainly consist of loose deposits in reservoir head. At the same time, I can discovery that the slip zone or potential slip zone of progressive landslides is composed of gravel soil,stony clay or gravel soil and clay mainly whose shear strength has a strength difference between peak intensity and residual intensity in some degree. Moreover, I acquire that landslide slope body especially potential slip surface feature has a good relationship with the form of progressive failure about landslides, the main type of the slip surface in pull landslides is nearly straight, below steep-middle slow-up steep and up steep-bellow slow, but the main type of the slip surface in push landslides is up steep-bellow slow. Finally, according to the correlation analysis to the acceleration process of landslide instances,rainfall and the changing of reservoir water level,I conclude that the combined effect of rainfall and changed reservoir water level is major motivation for the progressive failure of landslides.Meanwhile, based on soil progressive failure theory, I summarize the progressive failure mechanism of landslides under the combined effect of rainfall and changed reservoir water level.(3) Based on the landslide "incident" forecasting under the condition of rainfall and changed reservoir water level,I found the traditional landslide transition probability analysis methods have two problems that the two adjacent blocks sliding along different paths have the same transition probability and don't analyze the landslides with non-homogeneous slip soil. At the same time, I have derived landslide progressive failure probability analysis method considering slip soil strain softening characteristics on the condition that strain softening geotechnical materials are ideal brittle materials and don't consider the randomness among blocks. At last, combined with the combined effect of double factors to the influence for landslide seepage field between a very small probability extreme rainfall and the real changed reservoir water level in Three Gorges Reservoir Area, I have established the progressive destruction probability prediction model of bank landslides under the condition including rainfall and the changed reservoir water level according to the unsteady seepage analysis method.(4) Using extreme value I Distribution function the 26 years of rainfall data of Badong in the reservoir head were analyzed, and obtained the fitting parameters of the characteristic extreme rainfall and largest of many days cumulative precipitation and characteristic of rainfall process. Based on the 2938 group of shear strength test data using K-S fit contrast method set classification of goodness of fit test, and found that in the 5 categories of landslide prone strata of Three Gorges reservoir, the probability statistics features of shear strength parameters of slip soil is:generally acceptable normal distribution and lognormal distribution, but the optimal distribution of different types slip soil parameters are different.Generally, internal friction angle (φ) of optimal distribution submit to normal distribution is more than the cohesion (c) value, and lognormal distribution less. For parameter variability, no matter in what state, coefficient of variation of cohesion (c) values were higher than the corresponding value of the friction angle(φ).(5) Take the Zaozishuping Landslide for example, in the conditions of rainfall and changes of reservoir water level, the prediction results showed that:in the state of different reservoir water level, the initial damage occurred in the different parts of the landslides, and the damage possibility was also not the same. When the initial damage occurred in different rainfall conditions, the potential scale of landslide progressive failure was different. If the landslide occurred, the potential damage under different conditions had different modes, may lapse damage or progressive traction damage. But in the vast majority of cases will not be a progressive failure to complete the process. In the different pattern of deformation and failure, there were different anti-skid lots or locking lots. The landslide had many forms of progressive failure. When made the threshold value of whole failure probability as the prediction criterion, the potential risk is completely different, which has highest risk when in the 175m water level and stack the 50-year return period rainfall. We can use the prediction result of potential failure probability in the landslide monitoring and predicting. Combined with the relevant threshold value of criterion, we can make landslide event prediction in the rainfall and changes of reservoir water level. The goals of prediction include the possible, potential initial damage location, failure modes and the scale of the destruction of the most dangerous, and can guide the layout of key point in the monitoring prediction.(6) Based on the generation order rules of landslide fault structure and stage matching characteristics of landslides fissure summarized by previous, this paper build and improve the ground crack criterion on the stage of the landslide deformation and evolution by the analysis of landslide ground crack genetic mechanism. On the basis of general characteristics of progressive landslide failure process, this paper combined the approach degree of displacement rate and cumulative acceleration and cumulative jerk criterion of landslide, and considered the relationship of monitoring point acceleration and jerk on the different spatial location of sliding mass, and built improved displacement dynamics parameters criterion; the criterion is not only retains the original criterion reflect on regularity in the evolution of time of landslide deformation and failure process but also considered development law of landslide spatial deformation in the landslide different deformation stages. In the actual monitoring and prediction, based on the correlation analysis with external factors, it not only accurately discriminant that the landslide slide into the acceleration phase as a whole, but also more accurately discriminant the process of intermittent acceleration when the local displacement of the landslide appeared a "step-type" speed up change.(7) This paper presented three basic problems about quantitative instability prediction of landslide, namely:problems about the initial state of landslide reflect the dynamic information sources of landslide and suitability of landslide prediction model. It pointed out:the emergence of a whole accelerated deformation phase of is an important turning point of landslide deformation and evolution process. Forecast before the stage of landslide accelerated deformation all are the medium and long term forecast, and then carried out short-term prediction after the stage of accelerated deformation. Long-term forecast could considered to established prediction model or criteria using theories and methods of non-linear scientific which is more effective to treat complexity problem, and took the deformation trend of the landslide or concrete displacement value as the main forecast objective(unstable time as the secondary target). Short temporary forecast can consider establishing a stronger deterministic model or criteria to predict and take the forecast failure time as the main target, on the same time, forecasting impending slide must select suitable models and methods according to different type of landslide, and on the basis of the exact displacement data on the speed stage (or before sliding accelerated phase), it may come relatively accurate prediction results.(8) Based on the stage of progressive landslide deformation, it has proposed R/S analysis method to predict long-term deformation trends, displacement time series prediction-Neural Network Model and improved Verhulst Model for temporary sliding forecast. The relevant results are:Landslide time series of surface displacement monitoring has consistently reflected the Nonlinear characteristics of landslide deformation trend, depicted that Complex nonlinear time series of R/S analysis method can be used to do analysis effectively, but the more analysis structure is Incremental Displacement. The Hurst index H can not only decide timely trends and strength of displacement of different monitoring points, but also can judge the space (at the same time) landslide characteristics in different parts of deformation trend.What is more, it furthered the accelerate deformation stage to judge the concept of landslide model criterion. Displacement time series prediction-neural network model forecasted by monitoring the displacement of the total decomposition, and considered the influence factors and displacement response relationship to realize the landslide deformation and displacement of dynamic integrated analysis, so as to improve the prediction accuracy and reliability. Displacement and conventional forecast results usually combine empirical criterion threshold, unstable landslide prediction. Taking the maximum displacement rate as a failure time prediction value, the original Verhulst model has a lagged forecast error, the displacement rate can be raised as a forecast parameter, displacement, filling and emptying rates of acceleration and displacement as the maximum moment of failure time prediction upper and lower limits. When the Startup type is not clear,the temporary landslide forecast according to the value of the minimum and maximum time frame is more reasonable. When the monitoring period is constant, the time gap between the upper and lower limits is only associated with the model parameters a.(9)Any single forecasting model or method has its own limitations, carrying out comprehensive information landslide forecast is a inevitable way to achieve a relatively accurate prediction of the landslide. Taking Wo Shaxi and Zigui Baishuihe landslides both of which appeared significant danger since the Three Gorges reservoir impoundment for example, This thesis analyzed the practical application of comprehensive information forecast and test verification proposed in this thesis based on the systematic analysis of geological background, monitoring tools, macro-deformation history and the accumulated displacement curves. The results show that the proposed process of progressive failure of landslides based on relevant scientific and reasonable prediction method proposed in this thesis has certain practical and universal.The above research results and conclusions can not only enhance and improve the predictive and forecasting theory, provide some interesting new ideas and methods, but also has a very positive significance in monitoring of geological disasters in Three Gorges Reservoir Area for early warning and ecological environment construction and other practical work.