Formation Mechanism And Non-linear Prediction Of Landslids Hazards In Longzi County,Tibte

The influence and damage of landslide taken as a global and sudden geological disaster is significant, which often causes the great loss of life and property, seriously destroys the geological ecology environment of human livelihood and hinders the sustainable development of regional economies society. Taking an example, Vajont landslide led to thousands of persons's death and reservoir expired, the new beach landslide raised the Yangtze River to be blocked and unflowed by several days, and 5.12-Wenchuan earthquake induced massive landslides which is the secondary disasters of the earthquake. Therefore, recognizing formation mechanism clearly and appraising of landslide disaster sciencely and effectively have enormous social significance, economic value, which is also an important theoretical basis for the decision-making of prevention and mitigation of disaster.Following academic thought of "mechanism analysis of the geological process" and "the quantitative appraisal", the landslides within the zone of Liemai-Jiayu town, Longzi county in Tibet is taken as the research object, remote sensing and geographic information system spatial analysis can be taken as information technology sources supplemented by three-dimensional electronic sandbox of landslide visualization scenarios, spot investigation and checking primarily as metasynthesis research way. Typical geological feature, growth characteristics, spatial distribution characteristics, formation conditions and influencing factors are analyzed correspondingly. The common law and specific formation mechanism of landslide in the study area is macroscopically discussed. Based on fuzzy matter-element theory and catastrophe theory, the appraisal computation models of landslide risk are suggested separately, and the reliability of landslide hazard prediction are contrastly checked. The maximum sliding distance of the landslide is predicted based on empirical model. The nonlinear mapping and prediction of landslide parameters and maximum sliding distance is completed by BP neural network. The main research conclusions are as follows:(1) The terrain texture of remote sensing image and the digital elevation model are correspondingly mosaic fusion by GIS spatial analysis. The three-dimensional electronic sandbox of terrain texture is made, which demonstrate the landslide disaster body's spatial distribution vividly and improve the timeliness of disaster feature's recognition. It is an effective method of analysis.(2) Spot investigation shows that landslide disasters within the zone of Liemai-Jiayu town, Longzi county in Tibet are mainly distributed at both banks of Longzi river, Juela river and Lunba tributary valley, important transportation route areas and densely populated areas. Landslides in study area have different degrees of potential danger, which bring the threat to the local resident personal safety and property which can not be ignored.(3) Landslide development, spatial distribution, characteristics of the formation conditions and factors:The developmental scale of the landslides is large and the soil landslides in study area are formed by general materials. Generally speaking, the Jurassic layer is the slippery layer. The landslides here are mainly old and traction slope. They are mainly developed in the elevation range of 3500～4000m. The sunny slopes are more fitable to the distribution of landslides. The main layer is Ridang group of Jurassic layer, Weimei group, Zhela group, Lure group. The number of landslides decreases as the influence distances of faults, rivers, roads increase.(4) The Regional regularity of Landslide formation mechanism indicates that based factors (topography, geological structure, lithology, etc.) are intrinsic factors of landslide generation, development and evolution. Induced factors (rainfall intensity, river erosion, human engineering activities, etc.) are external factors of landslide promotion and occurrence. The formation mechanism of landslide is the based and induced factors coupled together, which forms a complex non-linear dynamic system.(5) The formation mechanism of landslides in study area:the landslides in study area are formed by accumulating soil that is made up by many times landslide accumulations. The formation can be concluded as stage of landslide accumulation→stage of deformation developing→stage of sliding. The future deformation styles are mainly slump-crack-type and creep-crack-type which finally lead to the formation of landslide.(6) Based on unique geological environment condition and landslide geological characteristic of Liemai-Jiayu town, Longzi county in Himalayan area, landslide risk assessment system of "analysis of landslide formation mechanism→selection of main evaluating indexes→quantification of evaluating indexes-establishment of mathematical model→calculation and evaluation of model" are established. This system can be used for the analysis of landslide risk in study area.(7) Starting from geological factors, landslide characteristics, environmental factors, altitude, aspect, fault affecting distance, landslide average slope, river affecting distance, land utilization and so on 13 indexes are selected. Based on fuzzy element theory and catastrophe theory, the landslide risk models are separately suggested and the results are verified and compared with field survey results. Landslide risks are divided into high risk, moderate risk, low risk, and the potential risk level of landslides is mainly middle. A new judgment of landslide risk is proposed by catastrophe progression method.(8) The applicability of empirical model was verrified by classical sliding distance of landslide which can choose a proper empirical model to predict the sliding distance in the study area. Based on theory of BP neural network, taking landslide height, landslide volume, landslide average thickness, landslide average slope as the input and landslide maximum sliding distance as output, the author establishs a three-layer BP artificial neural network of 4-9-1 type which builds a relationship between landslide parameters and maximum sliding distance very well. The range of landslide hazards in study area was confirmed and the landslide potential hazard was estimated. The potential hazard of landslides is mainly classified as level of very heavy, heavy, media and light in this study.