一、Rainfall-induced landslide stability analysis in response to transient pore pressure——A case study of natural terrain landslide in Hong Kong（论文文献综述）
Veerayut KOMOLVILAS,Weeradetch TANAPALUNGKORN,Panon LATCHAROTE,Suched LIKITLERSUANG[1]（2021）在《Failure analysis on a heavy rainfall-induced landslide in Huay Khab Mountain in Northern Thailand》文中认为On 28 th July 2018, a massive landslide occurred in a mountainous area in Northern Thailand. The landslide after ten days of heavy rainfall generated the movement of uphill mountain soil into the populated village. This study presents a comprehensive failure analysis of local rainfallinduced landslides based on topographical and geological information. Rainfall measurement data were gathered from two rainfall stations close to the study area. The rainfall records show that the total monthly rainfalls in 2018 were significantly higher than the average monthly rainfalls over the past decade. Site investigation started with an unmanned aerial photogrammetric survey to generate a digital elevation model. Then, dynamic probing test, microtremor survey, and electrical resistivity survey were carried out along undisturbed soils beside the failed slope to evaluate the thickness of the soft soil cover on top of the rock basement. During the site survey, residual soil samples were collected to determine engineering properties in the laboratory. Finally, a slope stability analysis was performed to assess the landslide hazard based on the results of aerial photogrammetric survey, field exploration, and laboratory tests. The slope stability analysis and rainfall records revealed that the Huay Khab landslide was mainly caused by an increase in the water content of residual soils due to the prolonged rainfall which led to a sharp decrease in the shear strength. This leads to the conclusion that the proposed landslide investigation program could be used to assess the potential of landslide failure due to prolonged rainfall on a local scale.
CAO Chun-hui,FENG Ji-li,TAO Zhi-gang[2]（2021）在《Triggering mechanism and dynamic process of water-rock flow in Nanfen waste dump in 2010》文中研究说明Water-rock flow is a kind of debris flow with more coarse particles and low viscosity, which occurs in many areas of the world. In this work, the water-rock flow that occurred on May 24, 2010, at Nanfen’s open-pit mine of China was investigated by combining field investigation, meteorological and hydrological survey with numerical simulation to understand its triggering mechanism and dynamic process. The field data shows that the short-term high-intensity rainfall is the most direct inducement to trigger water-rock flow in the waste dump. The loose shallow gravel soil and the V-shaped valley with a certain slope provide the necessary conditions of the occurrence of water-rock flow in the waste dump. Moreover, the possibility criterion of water-rock flow is presented by analyzing the historical rainfall data. In addition, the smoothed particle hydrodynamics（SPH） method was employed to simulate the waterrock flow under the conditions of Newtonian fluid with uniform distribution of water and coarse-grained materials. The simulating results show that the flow distance, velocity, shape, and deposition profile of water-rock flow are in good agreement with the field observation. The present work is beneficial to the risk assessment and mitigation design of water-rock flow disaster in the waste dump.
Xinzhi Zhou,Haijia Wen,Yalan Zhang,Jiahui Xu,Wengang Zhang[3]（2021）在《Landslide susceptibility mapping using hybrid random forest with Geo Detector and RFE for factor optimization》文中研究指明The present study aims to develop two hybrid models to optimize the factors and enhance the predictive ability of the landslide susceptibility models. For this, a landslide inventory map was created with 406 historical landslides and 2030 non-landslide points, which was randomly divided into two datasets for model training（70%） and model testing（30%）. 22 factors were initially selected to establish a landslide factor database. We applied the Geo Detector and recursive feature elimination method（RFE） to address factor optimization to reduce information redundancy and collinearity in the data. Thereafter, the frequency ratio method, multicollinearity test, and interactive detector were used to analyze and evaluate the optimized factors. Subsequently, the random forest（RF） model was used to create a landslide susceptibility map with original and optimized factors. The resultant hybrid models Geo Detector-RF and RFE-RF were evaluated and compared by the area under the receiver operating characteristic curve（AUC） and accuracy. The accuracy of the two hybrid models（0.868 for Geo Detector-RF and 0.869 for RFE-RF） were higher than that of the RF model（0.860）, indicating that the hybrid models with factor optimization have high reliability and predictability. Both RFE-RF Geo Detector-RF had higher AUC values, respectively 0.863 and 0.860, than RF（0.853）. These results confirm the ability of factor optimization methods to improve the performance of landslide susceptibility models.
WANG Xin-gang,LIAN Bao-qin,Liu Kai,Luo Li[4]（2021）在《Trigger mechanism of loess-mudstone landslides inferred from ring shear tests and numerical simulation》文中进行了进一步梳理Whereas loess-mudstone landslides are widely distributed and frequently occurred at the loess Plateau, this type of landslides is hard to detect due to its particularity, and easily generates serious losses. To clarify the shear characteristics and formation mechanism of loess-mudstone landslides, field investigations, ring shear tests and numerical simulation analyses were performed on the loess specimens collected from the Dingjiagou landslide in Yan’an city, China. The test results showed that both the peak strength and residual strength of slip zone soils have a decreasing tendency with moisture content, while the increasing of normal stress caused an increase in the shear strength. These phenomena indicate that the rise in the moisture content induced by precipitation or the decreasing of normal stress due to excavation activities would result in the weakening of slip zone soils. Numerical simulations of the evolution process of slope failure using the finite element method were conducted based on the Mohr–Coulomb criterion. It was found that the heavy precipitation played a more important role in the slope instability compared with the excavation. In addition, the field investigation showed that loess soils with well-developed cracks and underlying mudstone soils provide material base for the formation of loess-mudstone landslides. Finally, the formation mechanism of this type of landslides was divided into three stages, namely, the local deformation stage, the penetration stage, the creeping-sliding stage. This study may provide a basis for understanding the sliding process of loess-mudstone landslides, as well as guidelines for the prevention and mitigation of loess-mudstone landslides.
LI Li-min,CHENG Shao-kang,WEN Zong-zhou[5]（2021）在《Landslide prediction based on improved principal component analysis and mixed kernel function least squares support vector regression model》文中提出Landslide probability prediction plays an important role in understanding landslide information in advance and taking preventive measures. Many factors can influence the occurrence of landslides, which is easy to have a curse of dimensionality and thus lead to reduce prediction accuracy. Then the generalization ability of the model will also decline sharply when there are only small samples. To reduce the dimension of calculation and balance the model’s generalization and learning ability, this study proposed a landslide prediction method based on improved principal component analysis（PCA） and mixed kernel function least squares support vector regression（LSSVR） model. First, the traditional PCA was introduced with the idea of linear discrimination, and the dimensions of initial influencing factors were reduced from 8 to 3. The improved PCA can not only weight variables but also extract the original feature. Furthermore, combined with global and local kernel function, the mixed kernel function LSSVR model was framed to improve the generalization ability. Whale optimization algorithm（WOA） was used to optimize the parameters. Moreover, Root Mean Square Error（RMSE）, the sum of squared errors（SSE）, Mean Absolute Error（MAE）, Mean Absolute Precentage Error（MAPE）, and reliability were employed to verify the performance of the model. Compared with radial basis function（RBF） LSSVR model, Elman neural network model, and fuzzy decision model, the proposed method has a smaller deviation. Finally, the landslide warning level obtained from the landslide probability can also provide references for relevant decision-making departments in emergency response.
Kaleem Ullah Jan KHAN,WANG Chang-ming,Muhammad Wasim Jan KHAN,LIANG Zhu,LI Shuo,LI Bai-long[6]（2021）在《Influence of rainfall infiltration on the stability of unsaturated coal gangue accumulated slope》文中进行了进一步梳理The slope instability is associated with increasing rate of rainfall infiltration which cause shear strength reduction and suction loss and the slope tend to failure. The influences of rainfall infiltration on the stability of clayey and sandy slopes have been analyzed but the effect of rainfall infiltration on the stability of unsaturated coal gangue accumulated slope was needed to study. Therefore, a coal gangue accumulated slope prone to failure in Fuxin area of Northeast China was considered to evaluate its failure mechanism under different rainfall events. The effects after five different rainfall events on slope stability were physically analyzed, numerically investigated and the results from both uncoupled（hydraulic） and coupled（hydromechanical） responses were compared using finite element analysis. It was observed that the decisive soaking and leaching under different rainfall conditions caused maximum deformation at the crest of slope due to maximum value of permeability coefficient of coal gangue. The critical duration of moderate intensity（147 mm/day） of rainfall for the instability of coal gangue accumulated slope is declared as five days. The results from finite element analysis in this paper further clarifies that increase in duration of rainfall infiltration process cause hysteretic change in positive pore-water pressure causing decrease in factor of safety and increase in deformation. It is concluded that the stability of unsaturated coal gangue accumulated slope is greatly influence by the coupled effect of stress and porewater pressure in comparison of uncoupled（hydraulic） analysis as the obtained factor of safety values after five days of rainfall infiltration were 0.9 and 1.1 respectively.
Kaleem Ullah Jan Khan[7]（2021）在《降雨入渗触发非饱和煤矸石堆积边坡失稳的机理研究》文中研究说明土坡的稳定性与降雨渗透过程有关,其特点是剪切强度降低以及吸力损失,从而最终导致了失稳。土坡失稳主要发生在降雨期间或降雨后,虽然已经被证明为降雨渗透导致土体强度降低以及孔隙水压力迅速增加而造成,但引发斜坡失稳的重要影响机理还没有得到充分的讨论。降雨强度和降雨持续时间对边坡稳定性的影响,但降雨渗透过程对煤矸石堆积边坡稳定性的影响尚需深入研究。为此研究降雨入渗过程对土坡稳定性的影响,尤其对世界范围内广泛分布的矿渣堆积体稳定性及环境安全具有重要意义。降雨特征（降雨强度和持续时间）和土体的导水性影响着边坡的稳定状态及失效类型。一般来说,土坡破坏的机理有两种,即降雨湿润锋的传播导致垫层吸力的丧失以及地下水位的上升。到目前为止,仍然没有明确的指标来确定导致矿渣型边坡失效的主导参数。因此,本研究在开展东北阜新地区一煤矸石堆积边坡失稳机制研究中考虑了降雨渗透过程。通过收集已有资料、现场调查、实验室试验和数值模拟方法,较深入研究了煤矸石堆积边坡降雨诱发的失稳过程及其机理。采用渗流-应力耦合和非耦合有限元分析方法,对煤矸石堆积边坡的失效机理进行评价。采用物理模型测试分析了不同降雨条件下土坡中孔隙水压力的分布特征,采用有限元法数值方法按照渗流-应力耦合和非耦合两张方式研究了不同降雨持续时间（1天、2天、3天、4天和5天）和降雨强度对边坡变形破坏的影响。通过在坡面不同位置（坡顶、坡中、坡尖）设置监测点,观察并比较每次降雨后孔隙水压力的变化、变形规律和稳定性。煤矸石的高渗透性与在坡趾附近观察到的因水流而产生的最大变形进一步解释了坡体向下运动的原因,与现场观测和物理模型的观测结果有较好的一致性。研究结果还表明,渗透率的增加导致孔隙水压力的滞后性增加,土坡稳定系数下降。耦合分析中的安全系数（应力和孔隙水压力的耦合效应）与未耦合分析（水力反应效应）相比显着降低。为防止边坡进一步破坏,防止其对道路交通的影响,采用锚固与水平排水相结合的设计。建议在边坡顶部采用混凝土梁锚杆加固路基,在坡脚附近设置桩排。引入水平排水系统,分流雨水,保护边坡和道路的顶部和底部。采用极限平衡Bishop法分析了桩锚加固的效果,评价了加固方案对边坡安全系数的影响。结果表明:桩锚加固土边坡的安全系数由0.9提高到1.14;利用工程价值研究,在滑坡区设计水平排水系统,控制滑坡体内过量降雨入渗,保护坡顶和坡底道路,分流雨水。
ABOUBAKAR SIDDIQUE（司迪）[8]（2021）在《Assessment of Landslide Susceptibility Using Gis and Remote Sensing Technologies Along China Pakistan Economic Corridor》文中研究说明The China-Pakistan Economic Corridor（CPEC）is a corridor composed of roads,railways,oil and gas pipelines,optical cables and power lines.The corridor is extended from the north of Kashgar in China to the south of Gwadar Port in Pakistan.CPEC considering the vast area covered project which significantly important to take into account due to its diverse natue,especially natural environment,complex geological conditions,frequent seismic activity and extremely poor regional stability.The landslide natural disasters is one of the major constrain due to widespread mountains in the area which seriously threaten the success of the CPEC and the safety of people’s lives.In this study,landslide susceptibility evaluation using（AHP）weighted overlay model,and weighted information model.Elevation,slope,topographic relief,seismic density,rainfall distribution,distance from the fault,aspect,geology,distance from the river,and distance from the road were considered the drivers of landslide disaster.Then,（ROC）curve was used to evaluate the performance of models to identify more suitable model for the study area susceptible division.The results reviled that landslides are likely to induce geo-hazards in range of elevation between 2660 m and 3470 m above the sea level,slopes between 29°and 350°,terrain relief between 45 m and 70 m,density of the earthquake between 2 and 4 per 102km2,multi-year average rainfall between 430 mm and 530 mm,distance from the fault is less than 5 km,the distance from the river is less than 2 km,and the distance from the road is also less than 2 km likely to induce the landslide.The landslide points of field investigation were used to verify the models results.The susceptibility accuracy of geo-hazards in CPEC based on the weighted information model and AHP overlay model was 0.886 and 0.817 respectively.The results showed 33.6%,29.2%,22.3%,and 14.9%of the total area is extremely susceptible,high susceptible,low susceptible and extremely low susceptible area respectively.The results of the study are expected to provide the scientific foundation for major project design,traffic route selection,urban planning,and other aspects of the CPEC that will benefit safety of regional people’s livelihood and long-term development.
Do Minh Hien[9]（2021）在《越南何江市及周边地区滑坡灾害危险性评价》文中提出本文的总体目标是根据收集的滑坡资料、相关的降雨数据来评估滑坡灾害的现状和各诱发因素在研究区域中的作用,最终制作高精度的滑坡易发性图,以帮助当地居民和政府进行滑坡防灾减灾计划,并将评估结果用于土地规划。首先,基于已有的滑坡数据和降雨数据生成滑坡编录图,得到越南何江市及周边地区浅层滑坡的降雨阈值和贝叶斯概率模型。该计算过程需要每日降雨量数据以及滑坡发生日期。详细的数据分析是开展本文研究工作的前提。因此,要仔细筛选输入的数据以确保研究结果的可靠性。日降雨数据是从越南国家水文气象预报中心获取的包含57年（1957-2013）的雨量站数据,滑坡数据库包含1989到2013的245个历史滑坡数据（其中37个滑坡包含发生日期）。基于滑坡事件的当日降雨数据与先期降雨数据之间的关系计算得到研究区的降雨阈值。结果表明,滑坡发生前三天的降雨数据(已建立降雨阈值:RT=40.8-0.201R3ad)和数据库中的滑坡最相吻合。基于1989年至2009年26个滑坡同一时段的日降雨数据建立一维贝叶斯概率模型,其概率值位于0.03和0.44之间。基于2013年5月、6月和7月发生的11个滑坡的降雨强度和降雨持续时间建立二维贝叶斯概率模型,其概率值位于0.08和0.67之间,然后计算条件概率值。二维贝叶斯模型计算的条件概率值P（A|B）明显受降雨强度>40mm和降雨历时>0.3d的控制。然后,应用不同的区域划分技术建立研究区的滑坡易发性图,包括基于专家知识的模型,例如层次分析法-AHP和空间多准则评价-SMCE和统计方法例如证据权-Wo E和逻辑回归-LR。本部分主要目的是比较综合模型,证据权重模型（Wo E）,层次分析法（AHP）和逻辑回归（LR）模型与Flow-R模型相结合的结果,以进行何江市,越南及周边地区滑坡易发性评价。首先,使用13个滑坡诱发因素计算3个滑坡易发性指标（LSI）图。然后,使用研究区的数字高程模型和坡度图,通过Flow-R模型生成runout图。再计算成功率曲线,预测率曲线和曲线下面积（AUC）来评价预测能力。最终的滑坡易发性图是通过将LSI图与从Flow R模型提取的runout图叠加而成。检验结果表明,AHP-Flow R,Wo E-Flow R和LR-Flow R集成模型中LSI图的AUC值分别为82.89%,88.15%和86.53%,预测准确度分别为80.41%,84.94%和85.71%。Wo E-Flow R（88.15%）和LR-Flow R（86.53%）的组合模型具有最好的预测能力。一般情况下综合模型可提供合理的结果,有助于滑坡预防和土地使用规划。之后,为了估算研究区内的承灾体,本章还将介绍一些基于承灾体和易发性图关系进行暴露分析有关的重要信息如建筑物、交通线路、耕地等。第三,为研究区域内极端降雨事件诱发边坡破坏的机理,采集了一些土壤样品并分析其特性。在耦合模型中,SEEP/W-SLOPE/W,赋予与工程地质相关的主要参数,例如重度,内聚力,内摩擦角和水力条件,以计算受降雨强度和降雨历时影响下的研究区内切坡的稳定性系数（FS）。最后,总结研究结果,并提出了研究区滑坡治理的未来研究方向。提出进行山区滑坡风险评估的方法,应用结构性措施来提高边坡稳定性,以确保居住区和运输路线的安全,并且认为建立适合当地社会经济条件的监测预警系统,是实现可持续发展目标的紧迫任务。
Ahmed Mohamed Youssef,Hamid Reza Pourghasemi[10]（2021）在《Landslide susceptibility mapping using machine learning algorithms and comparison of their performance at Abha Basin,Asir Region,Saudi Arabia》文中认为The current study aimed at evaluating the capabilities of seven advanced machine learning techniques（MLTs）,including,Support Vector Machine（SVM）,Random Forest（RF）,Multivariate Adaptive Regression Spline（MARS）,Artificial Neural Network（ANN）,Quadratic Discriminant Analysis（QDA）,Linear Discriminant Analysis（LDA）,and Naive Bayes（NB）,for landslide susceptibility modeling and comparison of their performances.Coupling machine learning algorithms with spatial data types for landslide susceptibility mapping is a vitally important issue.This study was carried out using GIS and R open source software at Abha Basin,Asir Region,Saudi Arabia.First,a total of 243 landslide locations were identified at Abha Basin to prepare the landslide inventory map using different data sources.All the landslide areas were randomly separated into two groups with a ratio of 70% for training and 30% for validating purposes.Twelve landslide-variables were generated for landslide susceptibility modeling,which include altitude,lithology,distance to faults,normalized difference vegetation index（NDVI）,landuse/landcover（LULC）,distance to roads,slope angle,distance to streams,profile curvature,plan curvature,slope length（LS）,and slope-aspect.The area under curve（AUC-ROC） approach has been applied to evaluate,validate,and compare the MLTs performance.The results indicated that AUC values for seven MLTs range from 89.0% for QDA to 95.1% for RF.Our findings showed that the RF（AUC=95.1%） and LDA（AUC=941.7%） have produced the best performances in comparison to other MLTs.The outcome of this study and the landslide susceptibility maps would be useful for environmental protection.
二、Rainfall-induced landslide stability analysis in response to transient pore pressure——A case study of natural terrain landslide in Hong Kong（论文开题报告）
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三、Rainfall-induced landslide stability analysis in response to transient pore pressure——A case study of natural terrain landslide in Hong Kong（论文提纲范文）
（1）Failure analysis on a heavy rainfall-induced landslide in Huay Khab Mountain in Northern Thailand（论文提纲范文）
| 1 Introduction |
| 2 Study Area and Research Framework |
| 3 Site Investigation |
| 3.1 Field exploration |
| 3.1.1 Microtremor survey |
| 3.1.2 Dynamic probing test |
| 3.1.3 Electrical resistivity survey |
| 3.2 Laboratory tests |
| 3.3 Unmanned aerial photogrammetric survey |
| 3.4 Site investigation results |
| 4 Slope Stability Analysis |
| 5 Conclusions and Recommendations |
（7）降雨入渗触发非饱和煤矸石堆积边坡失稳的机理研究（论文提纲范文）
| 摘要 |
| Abstract |
| LIST OF ABBREVIATIONS |
| CHAPTER 1 Introduction |
| 1.1 Concept of slope failure |
| 1.2 Mechanism of slope instability and types of failures |
| 1.3 Factors affecting slope failure |
| 1.4 Background of study |
| 1.5 Problem statement and content of research |
| 1.6 Research route model |
| CHAPTER 2 Concepts and methods in soil slope failure analysis |
| 2.1 Unsaturated soil mechanics |
| 2.2 Stability of Slope |
| 2.3 Permeability |
| 2.3.1 Applications of permeability in slope engineering |
| 2.3.2 Permeability usage |
| 2.4 Hydraulic conductivity (K) |
| 2.4.1 Darcy’s Law |
| 2.4.2 Permeability test (Constant-Head) |
| 2.4.3 Permeability test (Falling-Head) |
| 2.5 LEM for analyzing slope stability |
| 2.6 Finite element method (FEM) |
| 2.7 Slope reinforcement techniques |
| CHAPTER 3 Engineering Geological conditions of coal gangue accumulated landslide |
| 3.1 Geography |
| 3.2 Hydrometeorological conditions |
| 3.3 Geology |
| 3.3.1 Stratigraphic distribution |
| 3.4 Characteristics of Landslide |
| CHAPTER 4 Numerical simulations of landslide by considering rainfall infiltration as atriggering factor |
| 4.1 Methodology |
| 4.1.1 Testing of soil properties |
| 4.1.2 Numerical simulations by finite element method (FEM) |
| 4.1.3 Governing equations |
| 4.2 Results |
| 4.2.1 Pore-water pressure |
| 4.2.2 Strain generation |
| 4.2.3 Response of deformation |
| 4.2.4 Safety factor |
| 4.3 Discussion |
| 4.3.1 Influence of rainfall infiltration in the change of pore-water pressure |
| 4.3.2 Mechanism in the distribution of strain |
| 4.3.3 Effect of rainfall infiltration process on deformation response |
| 4.3.4 Influence of rainfall infiltration process on safety factor |
| CHAPTER 5 Control scheme and stabilization of landslide |
| 5.1 Introduction |
| 5.2 Control scheme for Landslide |
| 5.2.1 Horizontal drainage in landslide |
| 5.2.2 Main components of drainage design |
| 5.3 Stabilization of Landslide |
| 5.3.1 Ground Anchorages |
| 5.3.2 Piles |
| 5.3.3 Anchorages and beam coupled with piles stabilization |
| CHAPTER 6 Conclusions and Recommendations |
| 6.1 Conclusions |
| 6.2 Recommendations |
| LITERATURE CITED |
| Self Introduction and Scientific Research Achievements During Master Degree |
| ACKNOWLEDGEMENTS |
（8）Assessment of Landslide Susceptibility Using Gis and Remote Sensing Technologies Along China Pakistan Economic Corridor（论文提纲范文）
| Acknowledgment |
| Abstract |
| List of Abbreviations |
| 1 Introduction |
| 1.1.Background |
| 1.2.What is CPEC? |
| 1.3.Problem Statement |
| 1.4.Overview of the research Work |
| 1.5.The thesis's structure |
| 2 Literature Review |
| 2.1.Introduction |
| 2.2.Current status of domestic and international research |
| 2.3.Inventory mapping for Landslide |
| 2.4.Landslide susceptibility mapping and Geographic Information Systems(GIS) |
| 2.5.Summary of the Chapter |
| 3 Research Methodology |
| 3.1.Data Source |
| 3.2.Road Extraction method |
| 3.3.Research methodology |
| 3.4.Analysis of geological hazard influence factors |
| 3.5.Forms of landslides and their activity |
| 3.6.Triggers and causes |
| 3.7.Landslide and geotechnical issues |
| 3.8.Scale factors in the research |
| 3.9.Landslide susceptibility mapping |
| 3.10.Landslide susceptibility methods |
| 3.11.Quantitative methods |
| 3.12.Summary of the Chapter |
| 4 Research data and Experiement |
| 4.1.Overview and data of the research area |
| 4.2.Landform factors |
| 4.3.Meteorological and hydrological factors |
| 4.4.Geological structural factors |
| 4.5.Human activity factor |
| 4.6.Summary of the Chapter |
| 5 RESULT ANALYSIS |
| 5.1.Geological hazard sensitivity based on different models |
| 5.2.Comparison of sensitivity analysis results |
| 5.3.Geological disaster sensitive zoning |
| 5.4.Verification of the results of geo-hazard sensitive zoning |
| 5.5.Summary of the Chapter |
| 6 CONCLUSIONS AND RECOMMENDATIONS |
| 6.1.Conclusions |
| 6.2.Recommendations |
| References |
| Dataset for the Master’s Thesis |
| AUTHOR CURRICULUM VITAE |
（9）越南何江市及周边地区滑坡灾害危险性评价（论文提纲范文）
| 作者简历 Resume |
| Acknowledgements |
| 摘要 |
| Abstract |
| Chapter 1 Introduction |
| 1.1 Research problem |
| 1.2 Motivation for research |
| 1.3.Research objectives |
| 1.4.Thesis outline |
| Chapter 2 Study area and data used |
| 2.1 Study area |
| 2.2 Data used |
| 2.2.1 Geology |
| 2.2.2 Weathered crust |
| 2.2.3 Topographical data and maps that derive from it |
| 2.2.4 Land cover |
| 2.2.5 Distance to faults,distance to drainages and distance to roads |
| 2.3 Rainfall characteristics |
| Chapter 3 Landslide inventory |
| 3.1.Historical data sources and types of information |
| 3.2.Method used for inventory mapping |
| 3.3.Statistic summary of the landslide inventory |
| 3.4.Discussion and conclusions |
| Chapter 4 Assessing the relationship between rainfall and landslide events in the past |
| 4.1.Introduction |
| 4.2.Landslide and rainfall database |
| Landslide database |
| Rainfall database |
| 4.3.Probability of occurrence of the triggering rainfall threshold |
| 4.3.1 Determination of the rainfall threshold |
| 4.3.2 Results |
| 4.3.3 Validation of rainfall threshold model |
| 4.4.Bayesian probability model |
| 4.4.1 One-dimensional case |
| 4.4.2 Two-dimensional case |
| 4.4.3 Identification of rainfall events |
| 4.4.4 Results |
| 4.5.Discussion |
| 4.6.Conclusions |
| Chapter 5 Landslide susceptibility assessment |
| 5.1.Introduction |
| 5.2.Methodology |
| 5.2.1 Analytical Hierarchy Process(AHP) |
| 5.2.2 Spatial Multi-Criteria Evaluation(SMCE) |
| 5.2.3 Weights of Evidence model(Wo E) |
| 5.2.4 Logistic Regression model(LR) |
| 5.2.5 Flow-R model(runout model) |
| 5.3.Results |
| 5.3.1 Application of AHP method |
| 5.3.2 Application of SMCE method |
| 5.3.3 Application of Wo E model |
| 5.3.4 Application of Logistic Regression Model |
| 5.3.5 Statistic summary of landslide susceptibility maps |
| 5.3.6 Application of Flow-R modeling |
| 5.3.7 Final susceptibility maps |
| 5.4.Validation of the landslide susceptibility maps |
| 5.5.Exposure analysis |
| 5.5.1 Introduction |
| 5.5.2 Landslide exposure and risk information |
| 5.5.3 Discussion and conclusions |
| 5.6.Discussion |
| 5.7.Conclusions |
| Chapter 6 Assessing the stability of cut slopes |
| 6.1.Introduction |
| 6.2.Rainfall events and slope failures in2013 |
| 6.3.Characteristics of cutting slopes in the study area |
| 6.3.1 Collecting the soil samples |
| 6.3.2 Physical properties of slope materials |
| 6.4.Slope stability analysis |
| 6.4.1 Seepage modeling |
| 6.4.2 Slope stability modeling |
| 6.5.Discussion |
| 6.6.Conclusions |
| Chapter 7 Conclusion and recommendations |
| 7.1.Landside inventory |
| 7.2.Rainfall threshold analysis |
| 7.3.Landslide hazard assessment |
| 7.4.Assessing the stability of cut slopes |
| 7.5.Highlights of the research |
| 7.6.Scope for future research |
| 参考文献Bibliography |
四、Rainfall-induced landslide stability analysis in response to transient pore pressure——A case study of natural terrain landslide in Hong Kong（论文参考文献）
- [1]Failure analysis on a heavy rainfall-induced landslide in Huay Khab Mountain in Northern Thailand[J]. Veerayut KOMOLVILAS,Weeradetch TANAPALUNGKORN,Panon LATCHAROTE,Suched LIKITLERSUANG. Journal of Mountain Science, 2021(10)
- [2]Triggering mechanism and dynamic process of water-rock flow in Nanfen waste dump in 2010[J]. CAO Chun-hui,FENG Ji-li,TAO Zhi-gang. Journal of Mountain Science, 2021(10)
- [3]Landslide susceptibility mapping using hybrid random forest with Geo Detector and RFE for factor optimization[J]. Xinzhi Zhou,Haijia Wen,Yalan Zhang,Jiahui Xu,Wengang Zhang. Geoscience Frontiers, 2021(05)
- [4]Trigger mechanism of loess-mudstone landslides inferred from ring shear tests and numerical simulation[J]. WANG Xin-gang,LIAN Bao-qin,Liu Kai,Luo Li. Journal of Mountain Science, 2021(09)
- [5]Landslide prediction based on improved principal component analysis and mixed kernel function least squares support vector regression model[J]. LI Li-min,CHENG Shao-kang,WEN Zong-zhou. Journal of Mountain Science, 2021(08)
- [6]Influence of rainfall infiltration on the stability of unsaturated coal gangue accumulated slope[J]. Kaleem Ullah Jan KHAN,WANG Chang-ming,Muhammad Wasim Jan KHAN,LIANG Zhu,LI Shuo,LI Bai-long. Journal of Mountain Science, 2021(06)
- [7]降雨入渗触发非饱和煤矸石堆积边坡失稳的机理研究[D]. Kaleem Ullah Jan Khan. 吉林大学, 2021(01)
- [8]Assessment of Landslide Susceptibility Using Gis and Remote Sensing Technologies Along China Pakistan Economic Corridor[D]. ABOUBAKAR SIDDIQUE（司迪）. 北京交通大学, 2021
- [9]越南何江市及周边地区滑坡灾害危险性评价[D]. Do Minh Hien. 中国地质大学, 2021
- [10]Landslide susceptibility mapping using machine learning algorithms and comparison of their performance at Abha Basin,Asir Region,Saudi Arabia[J]. Ahmed Mohamed Youssef,Hamid Reza Pourghasemi. Geoscience Frontiers, 2021(02)
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