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降雨入渗及渗流是导致降雨型滑坡的主要因素,文章对降雨条件下的入渗、变形特征的不同滑坡进行了分析,在此基础上,以降雨入渗形式和降雨运移形式着重对降雨型滑坡的水文地质条件进行了总结分类,同时还简单分析了各种类型的降雨型滑坡的滑动机理。 相似文献
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基于GIS的区域群发性降雨型滑坡时空预报研究 总被引：2，自引：0，他引：2
以滑坡灾害突出的雅安市雨城区为例,综合考虑降雨强度、前期降雨量及下垫面(地形、岩性、植被覆盖等)构建了基于GIS分析获取的易发指数+BP型神经网络时空预报模型。首先通过试验确定了模型的网络参数和网络结构,然后通过危险性区划图获取降雨型滑坡易发指数,并利用GIS的空间插值功能和雨量站数据获取相应降雨型滑坡的雨量数据,将量化后下垫面的易发指数和降雨数据作为神经元输入层数据。将模型应用于研究区,其中46个降雨型滑坡数据作为训练样本,10个降雨型滑坡数据作为检验样本,预测精度达到90%,显示该模型对于降雨型滑坡的时空预报精度较高。 相似文献
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丹巴滑坡的位移特征 总被引：1，自引：0，他引：1
滑坡位移资料可为分析滑坡运动规律、发展趋势和预测预报提供依据。通过对丹巴滑坡治理过程中滑坡前部、中部和后部的位移监测资料分析,滑坡位移速度可划分为两个阶段:位移速度增加阶段和减少阶段。分析了各部位的各个阶段运动特征及其影响因素。对各部位位移速度在增加阶段和减小阶段的速度与时间关系的曲线拟合,表明滑坡在位移速度增加阶段具有相似的运动特征,拟合方程都较好地符合指数方程,而在速度减小阶段受治理工程的影响差别较大,拟合方程分别为对数、线性和指数方程。以监测数据的初始值和累计最大值,利用Lo-gistic模型对各部位的累计位移进行预测,预测值与实测值的拟合程度较高,表明丹巴滑坡在治理过程中的整个累计位移较好地遵循Logistic增长过程。从位移监测资料可以看出,滑坡治理工程有效地控制了滑坡的活动。 相似文献
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《山地学报》2021,(1)
水库滑坡的位移与周期性的库水波动和季节性降雨等诱发因素关系密切,由于库水位升降和降雨的作用,滑坡累计位移变形曲线呈明显的"台阶状",准确、及时地预测此类台阶状位移对提升该变形的认识具有重要意义。为深入了解诱发因素对水库滑坡位移的影响,预测其变形演化趋势,本研究提出了一种基于集合经验模态分解(EEMD)和随机森林回归模型(RFR)的滑坡位移预测模型。以水库滑坡——三峡库区白家包滑坡2007年4月至2018年12月的变形数据为例,进行"台阶状"位移的预测与模型检验。通过EEMD方法将累计位移分解为趋势项和周期项,其中趋势项采取最小二乘法的三次多项式拟合;周期项基于诱发因素组合和滑坡位移的响应变化,建立RFR模型进行预测。根据时间序列加法,将趋势项和周期项预测值叠加,获得总位移预测值。结果表明EEMD-RFR模型基本反映了滑坡累计位移的"台阶状"变化趋势,相关系数R达到0.997。通过与两种BP神经网络预测方法的对比,反映EEMD-RFR模型具有更好的预测效果。本研究为水库滑坡台阶状位移预测提供了一种有效的新方法,对了解水库滑坡长期变形具有一定意义。 相似文献
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在对汶川地震诱发的典型滑坡进行详细野外调查的基础上,根据滑坡的运动特点和运动方式的不同,将滑坡分为4种基本类型:滑动型滑坡、滑动-流动型滑坡、坠落-滑动型滑坡及坠落-弹射-滑动型滑坡,其中滑动型滑坡又按照滑动特点、物质组成特性以及滑体宏观破碎程度的不同,分为整体滑动型滑坡、碎裂滑动型滑坡和碎屑滑动型滑坡,并通过不同类型的典型滑坡实例对每一类滑坡的基本特征,特别是运动特征及运动过程进行了深入细致的分析.这不仅有助于更全面深入地认识地震滑坡的类型和特征,而且也为今后减轻和预防地震滑坡灾害提供了基础. 相似文献
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《山地学报》2017,(6)
浅层蠕动型黄土滑坡通常呈面状发育于相对平缓的沟谷两侧,沿黄土-基岩接触面产生周期性低速蠕动,对附近的工厂、道路和管道等设施造成严重破坏。研究这类滑坡的形成机理对其防灾减灾工作具有重要的指导意义。因此本文以甘肃省天水市罗玉沟流域的一个典型浅层蠕动型黄土滑坡为例展开研究。取滑带泥岩样进行直剪和直剪蠕变试验,以试验数据为基本参数,利用VB编程的二维滑坡运动模型模拟该滑坡的演化过程,并分析了滑坡在运动过程中及河流侵蚀下的稳定性。结果表明,泥岩应力-应变曲线呈弱硬化型,破坏后强度不发生衰减,且其长期强度(φ_∞=10.3°、c_∞=12.8 k Pa)明显低于直剪试验强度(φ_f=11.9°、c_f=40.9 k Pa),有利于滑坡发生蠕动;滑坡演化过程中后缘滑体逐渐向前缘蠕动,滑体稳定系数随之提高,但河流侧蚀又会明显降低其稳定性,导致周期性蠕动下滑;本文采用的二维滑坡运动有限差分模型可较好的模拟这类滑坡的演化过程,可为滑距预测提供依据。 相似文献
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库岸边坡是一个复杂的地质综合体,库岸滑坡是威胁库区安全的地质隐患。多数传统滑坡预测模型为静态模型,未将滑坡变形特征与位移预测二者结合考虑,不能实际反映滑坡演化过程中的动态特性。本文基于溪洛渡库区58处涉水滑坡变形监测结果,归纳了库岸滑坡变形规律,采用机器学习方法实现了不同特征滑坡变形趋势的短期预测。研究结果显示：(1)研究区年平均地表形变速率处于-116.841～265mm·yr-1,负值代表目标地物远离卫星方向位移,正值代表目标地物靠近卫星方向移动,其中存在缓慢变形滑坡13处,根据其累计位移曲线特征划分为：阶跃型、振荡型和持续增长型三类。(2)阶跃型滑坡滑面多为弧线型,其变形主要受库水位周期性变动影响;振荡型滑坡滑面多为折线型,其变形多受库水位和降雨共同作用;持续增长型滑坡滑面多为直线型,其变形主要受自身地质条件控制。(3)针对不同变形特征滑坡,采用长短时记忆(LSTM)神经网络模型考虑多因素耦合和滑坡演化状态建立了滑坡变形动态预测模型,通过评价结果验证,该模型具有较高预测精度及良好的适用性。研究结果可以为溪洛渡库区滑坡系统研究与防治提供依据,为库区不同变形特征... 相似文献
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据优势面分析原理和方法,对金龙山地区斜坡各种结构面所作的优势面分析结果显示:浅层强风化岩体中顺坡向剪切裂隙,是控制浅层顺层滑坡发生发展的滑动优势面;深层弱风化岩体中粘土岩风化软弱夹层、斜坡上段拉张裂隙与斜坡下段顺坡向剪切裂隙三者相组合,是控制深层顺层滑坡发生的滑动优势面。当地受滑动优势面控制的滑坡变形破坏模式有:浅层为蠕滑—拉裂,深层为滑移—弯曲。 相似文献
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采用工程地质钻探、物探、地质测绘及室内试验等技术方法探讨飞鹅山Ⅲ号滑坡形成机理与防治技术。结果表明：1）滑坡体主要岩性为泥质粉砂岩,飞鹅山滑坡属于新形成的深层中型牵引式滑坡,在平面上呈圈椅状。2）滑坡属于双层滑面滑坡,主滑面以中型深层滑坡为主,主滑体上部发育中型中厚层滑坡。3）滑坡产生的原因为：①泥质粉砂岩倾向与坡向基本一致,且岩层倾角为中等倾角;②人工开挖使坡脚形成高陡临空面,抗滑力大为降低;③雨水沿层面及节理裂隙入渗至坡体深部,大大增加岩土体容重,同时泥质粉砂岩遇水软化,抗剪强度显著降低。4）结合该滑坡区地质环境条件,采用坡面削坡+锚杆（索）+格构梁+双排预应力锚拉抗滑桩+三维网植草绿化+截排水+毛石挡墙的综合治理方法进行防治,监测结果显示该滑坡变形及位移已得到有效控制,整治效果良好。 相似文献
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张溪滑坡--台风诱发滑坡成因分析 总被引：6，自引：1，他引：5
14号台风“云娜”造成我国东部沿海地区发生多处滑坡地质灾害,张溪滑坡便是其中个案。通过对张溪滑坡成因进行分析,得出了张溪滑坡是在一定厚度覆盖层、特定地形条件、植被条件下,台风风力加载作用及暴雨的淘蚀、软化、增重等一系列过程共同作用下滑动失稳的滑坡。它与暴雨型滑坡的形成机理有显著不同,这一分析成果对类似滑坡的研究和防治具有一定的意义。 相似文献
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Landslide susceptibility mapping using geological data, a DEM from ASTER images and an Artificial Neural Network (ANN) 总被引：7，自引：0，他引：7
An efficient and accurate method of generating landslide susceptibility maps is very important to mitigate the loss of properties and lives caused by this type of geological hazard. This study focuses on the development of an accurate and efficient method of data integration, processing and generation of a landslide susceptibility map using an ANN and data from ASTER images. The method contains two major phases. The first phase is the data integration and analysis, and the second is the Artificial Neural Network training and mapping. The data integration and analysis phase involve GIS based statistical analysis relating landslide occurrence to geological and DEM (digital elevation model) derived geomorphological parameters. The parameters include slope, aspect, elevation, geology, density of geological boundaries and distance to the boundaries. This phase determines the geological and geomorphological factors that are significantly correlated with landslide occurrence. The second phase further relates the landslide susceptibility index to the important geological and geomorphological parameters identified in the first phase through ANN training. The trained ANN is then used to generate a landslide susceptibility map. Landslide data from the 2004 Niigata earthquake and a DEM derived from ASTER images were used. The area provided enough landslide data to check the efficiency and accuracy of the developed method. Based on the initial results of the experiment, the developed method is more than 90% accurate in determining the probability of landslide occurrence in a particular area. 相似文献
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Jaroslav Buša Miloš Rusnák Dávid Kušnirák Vladimír Greif Martin Bednarik René Putiška 《自然地理学》2020,41(2):169-194
ABSTRACTWe employed integrated methods to assess the landslide movement in Sv. Anton town in the Western Carpathians Neogene Volcanic Field (Central Slovakia). The integrated diagnostics required study of the landslide kinematic activity by a combination of Global Navigation Satellite Systems (GNSS) and Electrical Resistivity Tomography (ERT) imaging from November 2013 to March 2015. A topographic model with 2-cm accuracy was constructed from Unmanned Aerial Vehicles (UAV) photogrammetry. Continuous spatial datasets of movement and displacement field vectors were interpolated from the measured movements over the entire study period. Although deformation studies in Slovakia have a long-term tradition, complex interdisciplinary studies in urbanized areas are still lacking. This inspired our main objectives: to identify landslide kinematics and to reconstruct and define the rates of annual landslide movement obtained from geodetic measurement at the monitoring points. Our results demonstrate how landslide integrated diagnostics contribute to the detection of slope instability, with a maximum velocity of 60.82 mm/yr during the summer period. The precipitation effects are consistent with the Sv. Anton landslide displacement acceleration, and the following increases in total monthly precipitations are staggering compared to long-term monthly averages: July precipitation increased by 175.3%, August by 203.3%, and September by 198.1%. 相似文献
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Objective landslide detection and surface morphology mapping using high-resolution airborne laser altimetry 总被引：6，自引：0，他引：6
A map of extant slope failures is the most basic element of any landslide assessment. Without an accurate inventory of slope instability, it is not possible to analyze the controls on the spatial and temporal patterns of mass movement or the environmental, human, or geomorphic consequences of slides. Landslide inventory maps are tedious to compile, difficult to make in vegetated terrain using conventional techniques, and tend to be subjective. In addition, most landslide inventories simply outline landslide boundaries and do not offer information about landslide mechanics as manifested by internal deformation features. In an alternative approach, we constructed accurate, high-resolution DEMs from airborne laser altimetry (LIDAR) data to characterize a large landslide complex and surrounding terrain near Christchurch, New Zealand. One-dimensional, circular (2-D) and spherical (3-D) statistics are used to map the local topographic roughness in the DEMs over a spatial scale of 1.5 to 10 m. The bedrock landslide is rougher than adjacent unfailed terrain and any of the statistics can be employed to automatically detect and map the overall slide complex. Furthermore, statistics that include a measure of the local variability of aspect successfully delineate four kinematic units within the gently sloping lower half of the slide. Features with a minimum size of surface folds that have a wavelength of about 11 to 12 m and amplitude of about 1 m are readily mapped. Two adjacent earthflows within the landslide complex are distinguished by a contrast in median roughness, and texture and continuity of roughness elements. The less active of the earthflows has a surface morphology that presumably has been smoothed by surface processes. The Laplacian operator also accurately maps the kinematic units and the folds and longitudinal levees within and at the margins of the units. Finally, two-dimensional power spectra analyses are used to quantify how roughness varies with length scale. These results indicate that no dominant length scale of roughness exists for smooth, unfailed terrain. In contrast, zones with different styles of landslide deformation exhibit distinctive spectral peaks that correspond to the scale of deformation features, such as the compression folds. The topographic-based analyses described here may be used to objectively delineate landslide features, generate mechanical inferences about landslide behavior, and evaluate relatively the recent activity of slides. 相似文献
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Comparison of landslide susceptibility based on a decision-tree model and actual landslide occurrence: The Akaishi Mountains, Japan 总被引：7，自引：0，他引：7
This paper proposes a statistical decision-tree model to analyze landslide susceptibility in a wide area of the Akaishi Mountains, Japan. The objectives of this study were to validate the decision-tree model by comparing landslide susceptibility and actual landslide occurrence, and to reveal the relationships among landslide occurrence, topography, and geology. Landslide susceptibility was examined through ensemble learning with a decision tree. Decision trees are advantageous in that estimation processes and order of important explanatory variables are explicitly represented by the tree structures. Topographic characteristics (elevation, slope angle, profile curvature, plan curvature, and dissection and undissection height) and geological data were used as the explanatory variables. These topographic characteristics were calculated from digital elevation models (DEMs). The objective variables were landslide occurrence and reactivation data between 1992 and 2002 that were depicted by satellite image analysis. Landslide susceptibility was validated by comparing actual data on landslides that occurred and reactivated after the model was constructed (between 2002 and 2004).This study revealed that, from 2002 to 2004, landslides tended to occur and reactivate in catchments with high landslide susceptibility. The landslide susceptibility map thus depicts the actual landslide occurrence and reactivation in the Akaishi Mountains. This result indicates that the decision-tree model has appropriate accuracy for estimating the probabilities of future landslides. The tree structure indicates that landslides occurred and reactivated frequently in the catchments that had an average slope angle exceeding ca. 29° and a mode of slope angle exceeding 33°, which agree well with previous studies. A decision tree also quantitatively expresses important explanatory variables at the higher order of the tree structure. 相似文献
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Predictive modelling of rainfall-induced landslide hazard in the Lesser Himalaya of Nepal based on weights-of-evidence 总被引：12，自引：0，他引：12
Ranjan Kumar Dahal Shuichi Hasegawa Atsuko Nonomura Minoru Yamanaka Santosh Dhakal Pradeep Paudyal 《Geomorphology》2008,102(3-4):496-510
Landslide hazard mapping is a fundamental tool for disaster management activities in mountainous terrains. The main purpose of this study is to evaluate the predictive power of weights-of-evidence modelling in landslide hazard assessment in the Lesser Himalaya of Nepal. The modelling was performed within a geographical information system (GIS), to derive a landslide hazard map of the south-western marginal hills of the Kathmandu Valley. Thematic maps representing various factors (e.g., slope, aspect, relief, flow accumulation, distance to drainage, soil depth, engineering soil type, landuse, geology, distance to road and extreme one-day rainfall) that are related to landslide activity were generated, using field data and GIS techniques, at a scale of 1:10,000. Landslide events of the 1970s, 1980s, and 1990s were used to assess the Bayesian probability of landslides in each cell unit with respect to the causative factors. To assess the accuracy of the resulting landslide hazard map, it was correlated with a map of landslides triggered by the 2002 extreme rainfall events. The accuracy of the map was evaluated by various techniques, including the area under the curve, success rate and prediction rate. The resulting landslide hazard value calculated from the old landslide data showed a prediction accuracy of > 80%. The analysis suggests that geomorphological and human-related factors play significant roles in determining the probability value, while geological factors play only minor roles. Finally, after the rectification of the landslide hazard values of the new landslides using those of the old landslides, a landslide hazard map with > 88% prediction accuracy was prepared. The methodology appears to have extensive applicability to the Lesser Himalaya of Nepal, with the limitation that the model's performance is contingent on the availability of data from past landslides. 相似文献