甘孜州色达县典型牵引式滑坡地质灾害形成机理分析--以甘孜州甲学乡甲热滑坡为例

甲热滑坡位于甘孜州色达县甲学乡境内,属于典型的牵引式滑坡,滑坡体平均坡度约35°,主要由碎石土组成,滑坡长约195 m,宽约280 m,平均厚约15 m,滑坡体总方量约60万m3,属中型滑坡。滑坡坡体中上部变形现象较明显,若发生滑动,将直接威胁当地41户160人居民的生命财产安全。本文在进行野外现场基础地质调查后,对滑坡体的变形破坏机制进行了定性分析,并利用三位有限元数值模拟进行了定量分析,对以后研究同类滑坡的稳定性具有重要意义。     

基于斜坡破坏模式的软弱变质岩区岩质滑坡易发性评价

滑坡受控于地质环境条件和坡体地质结构,不同地质结构的斜坡失稳破坏的模式存在差异,本文以后龙门山千枚岩区为例,基于现场调查,梳理总结了区内岩质滑坡发生的力学模式与斜坡地质环境、坡体结构之间的关系,进而选取控制滑坡发生的关键因素,运用ARCGIS软件的加权叠加功能定量划分了不同模式滑坡的易发区域,主要取得以下认识：（1）滑移—拉裂式滑坡主要发生在坡度30-45°的顺向飘倾坡内、滑移—溃曲式滑坡发生在坡度30-45°的顺向伏倾坡内、倾倒变形主要发生在岩层倾角大于65°的反向斜坡内;（2）区内倾倒变形易发区面积为8.73km2、滑移拉裂易发区面积为4.31m2、滑移溃曲易发区面积为3.28km2,以倾倒变形类型的滑坡为主,已发生滑坡与易发分区结果比对证明了滑坡易发分区与实际情况基本吻合。     

RS & GIS-based landslide susceptibility mapping of the Balason River basin,Darjeeling Himalaya,using logistic regression (LR) model

The present study deals with the preparation of a landslide susceptibility map of the Balason River basin, Darjeeling Himalaya, using a logistic regression model based on Geographic Information System and Remote Sensing. The landslide inventory map was prepared with a total of 295 landslide locations extracted from various satellite images and intensive field survey. Topographical maps, satellite images, geological, geomorphological, soil, rainfall and seismic data were collected, processed and constructed into a spatial database in a GIS environment. The chosen landslide-conditioning factors were altitude, slope aspect, slope angle, slope curvature, geology, geomorphology, soil, land use/land cover, normalised differential vegetation index, drainage density, lineament number density, distance from lineament, distance to drainage, stream power index, topographic wetted index, rainfall and peak ground acceleration. The produced landslide susceptibility map satisfied the decision rules and ?2 Log likelihood, Cox &; Snell R-Square and Nagelkerke R-Square values proved that all the independent variables were statistically significant. The receiver operating characteristic curve showed that the prediction accuracy of the landslide probability map was 96.10%. The proposed LR method can be used in other hazard/disaster studies and decision-making.     

西藏加查拉岗村巨型古滑坡发育特征与形成机理研究

青藏高原地质构造活跃,内外动力作用强烈,加之气候异常变化,区内大型滑坡发育。以雅鲁藏布江断裂附近新发现的拉岗村古滑坡为研究对象,在现场调查、槽探揭露、地质测年和工程地质分析等基础上,对其发育特征及成因机制进行了分析研究。研究表明,(1)拉岗村滑坡属巨型岩质滑坡,体积达3.6×107 m3,最大水平滑动距离约3050m,滑坡后壁与堆积体前缘高差达965m,最大运动速率达78.1m/s,具明显高速远程特征;(2)受冷冻风化和冰体"楔劈"作用影响,滑坡后部岩体崩裂,全新世以来气候变化冰川逐渐消退,融雪降水入渗加剧劣化岩体结构,降低岩体强度;(3)根据14 C和10Be测年结果,拉岗村古滑坡形成于距今4140~9675a,沿雅鲁藏布江断裂发生的强震可能是该滑坡的直接诱因,岩体受到地震抛掷力作用,原有节理裂隙和新生破裂面发生张剪-拉裂破坏迅速贯通,首先沿断裂附近碎裂结构岩体发生破坏,上部岩体随之失稳并高速下滑。该研究可为认识青藏高原断裂带内大型古滑坡的形成机理提供借鉴。     

逻辑回归模型在边坡稳定性分析中的应用

采用逻辑回归模型和确定性系数CF建立概率模型,使用收集到的22个边坡实例,将重度、内聚力、坡角、坡高、内摩擦角和孔隙压力比六个影响因子作为自变量,边坡状态作为因变量,应用SPSS取不同的滑坡概率P与不滑坡概率1-P的比值的自然对数Z进行回归分析。将获得的滑坡概率拟合模型反馈到样本参数上,对比其误差,选取Z=±10时的函数模型对另外8组边坡进行验证,证明预测模型的合理性。     

基于模型试验的泥石流坡面物源启动预警模型

为进一步探明银洞子沟物源区坡面物源启动机理与降雨的相关性,在进行详细的现场考察与工程勘察工作后选取了典型模型体,并采用20余组人工降雨物理试验方法将降雨强度与坡度设为控制变量,研究了4种坡形、5种雨强条件下,坡面松散物源的失稳机制及破坏模式。试验结果揭示了地表变形与地下物理力学参数变化的定量响应关系,并基于试验发生破坏的临界雨量,建立了银洞子沟传统I-D预警模型。之后提炼可靠预警参数(坡度、深部体积含水率),通过数学回归分析方法并采用Exponential模型,得出IGD、IGM多参数新型预警判别式,实现了传统I-D模型的有效修正,并具一定的可靠性和实用价值。     

辽宁抚顺西露天矿南帮滑坡变形与地下水位关系

结合抚顺西露天矿的地质环境背景,介绍了抚顺西露天矿南帮滑坡变形监测中地下水监测系统的构建情况。从降水入渗、岩体的透水性等角度对比了汛期及非汛期地下水的监测数据,并利用SPSS统计分析软件对单点地下水位变化值和滑坡位移变化值进行曲线估计回归分析并建立模型。结果表明,汛期持续强降雨是诱发西露天矿南帮滑坡变形的重要因素;强降雨入渗过程中,基岩裂隙水的变化存在明显的滞后性;单点地下水位变化值和滑坡位移变化值符合三次项曲线模型;非汛期,地下水位逐渐降低,滑坡地表变形速率也减缓。     

Research Progress and Prospect on Reactivation of Ancient Landslides

The ancient landslide has endured long-term slope evolution which results in its complicated material and special rock-soil properties. The risk of ancient landslide reactivation is substantially increasing due to the increase of intensified human engineering activities and the frequency of extreme weather events. Many ancient landslides have been reactivated all over the world and led to serious fatalities and severe damage to many important engineering facilities such as transportation and hydropower engineering projects. On the basis of the analysis of the research situation about the ancient landslides at home and abroad, the main research advances were summarized including the regional developing laws and recognizing of the ancient landslides, the mechanics properties of ancient landslide body and related sliding zone, reactivation mechanism of ancient landslides, reactivating process and modeling analysis of ancient landslides, early recognization of ancient landslide reactivation, etc. To meet the demands of disaster prevention and reduction, three key scientific issues were put forward to be solved: ①automaticaly establishing the methodology and identification criterions for recognition of ancient landslide; ②revealing the reactivation mechanism of ancient landslide based on a new strength theory; ③establishing the early rapid recognition method and predictive model for ancient landslide reactivation. Solving the above mentioned scientific theory and methodology will facilitate the planning and site selection of major projects as well as the disaster prevention and reduction in ancient landslide developing areas.     

基于逻辑回归的四川青川县区域滑坡灾害预警模型

四川省青川县滑坡灾害群发,点多面广,区域滑坡灾害预警是有效防灾减灾的重要手段,预警模型是成功预警的核心。由于研究区滑坡诱发机理复杂、调查监测大数据及分析方法不足等原因,传统区域地质灾害预警模型存在预警精度有限、精细化不足等问题。文章在青川县地质灾害调查监测和降水监测成果集成整理与数据清洗基础上,构建了青川县区域滑坡灾害训练样本集,样本集包括地质环境、降雨等27个输入特征属性和1个输出特征属性,涵盖了青川县近9年（2010—2018年）全部样本,数量达1 826个（其中,正样本613个,负样本1 213个）。基于逻辑回归算法,对样本集进行5折交叉验证学习训练,采用贝叶斯优化算法进行模型优化,采用精确度、ROC曲线和AUC值等指标校验模型准确度和模型泛化能力。其中,ROC曲线也称为“受试者工作特征”曲线;AUC值表示ROC曲线下的面积。校验结果显示,基于逻辑回归算法的模型训练结果准确率和泛化能力均较好（准确率94.3%,AUC为0.980）。开展区域滑坡实际预警时,按训练样本特征属性格式,输入研究区各预警单元27个特征属性,调用预先学习训练好的模型,输出滑坡灾害发生概率,根据输出概率分段确定滑坡灾害预警等级。当输出概率P≥40%且P<60%时,发布黄色预警;当输出概率P≥60%且P<80%时,发布橙色预警;当输出概率P≥80%时,发布红色预警。     

基于无人机倾斜摄影的黄土滑坡信息多维提取与应用分析

本文针对黄土地区地质灾害调查与评估需求,探索了一种基于无人机倾斜摄影影像和飞控数据的滑坡单体信息多维提取的方法。通过影像处理获得的DEM、DOM和实景三维模型等多维数据,对贾家村滑坡坡形、坡度、相对高差、植被覆盖率、纵坡比降、表面积与物源体积进行定量提取,结合区域气象数据分析了贾家村滑坡年均降雨量时空分布规律,利用相关地质资料分析了其地层岩性特点和区域地质构造情况,为准确评定其稳定性及危险性提供既高效又准确的定性、定量参考依据。