An InSAR and depth-integrated coupled model for potential landslide hazard assessment

Assessing the hazard of potential landslides is crucial for developing mitigation strategies for landslide disasters. However, accurate assessment of landslide hazard is limited by the lack of landslide inventory maps and difficulty in determining landslide run-out distance. To address these issues, this study developed a novel method combining the InSAR technique with a depth-integrated model. Within this new framework, potential landslides are identified through InSAR and their potential impact areas are subsequently estimated using the depth-integrated model. To evaluate its capability, the proposed method was applied to a landslide event that occurred on November 3, 2018 in Baige village, Tibet, China. The simulated results show that the area with a probability of more than 50% to be affected by landslides matched the real trimlines of the landslide and that the accuracy of the proposed method reached 85.65%. Furthermore, the main deposit characteristics, such as the location of maximum deposit thickness and the main deposit area, could be captured by the proposed method. Potential landslides in the Baige region were also identified and evaluated. The results indicate that in the event of landslides, the collapsed mass has a high probability to block the Jinsha River. It is therefore necessary to implement field monitoring and prepare hazard mitigation strategies in advance. This study provides new insights for regional-scale landslide hazard management and further contributes to the implementation of landslide risk assessment and reduction activities.

     

PCR-SPA-MC模型在滑坡稳定性分析中的应用

破坏概率与随机模拟理论在滑坡稳定性分析中得到了广泛地应用。然而,通过对传统破坏概率与随机模拟方法的具体操作发现,其没有考虑到因素相关性的影响,由此笔者引入主成分-逐步回归算法, 建立了PCR-SPA-MC耦合模型。并结合巴东县赵树岭滑坡研究,进行了工程实例分析。分析表明,PCR-SPA-MC模型给出的结果比传统破坏概率法得出的结果更为理想。     

基于GIS空间数据的滑坡SPH粒子模型研究

针对光滑粒子流体动力学方法（SPH）在滑坡模拟中建立粒子模型的难题,提出了基于地理信息系统（GIS）栅格数据的粒子排列与插入方法。根据该方法,建立了滑坡SPH粒子模型及相关粒子生成程序,进一步以结合摩尔-库仑破坏准则的SPH宾汉流体模型为核心,实现了运用SPH方法模拟滑坡破坏后三维运动的过程。该SPH模型在对唐家山滑坡的模拟中得到了验证,并预测了金坪子滑坡破坏后的影响范围。结果表明：基于GIS空间数据的滑坡SPH粒子模型具有可行性与良好的适用性。以GIS数据库为基础,开展滑坡灾害的模拟研究,将大大提高对滑坡等地质灾害的仿真分析,为滑坡灾害的预测与防治提供参考。     

Numerical SPH analysis of debris flow run-out and related river damming scenarios for a local case study in SW China

A smoothed particle hydrodynamics (SPH) numerical modeling method implemented for the forward simulation of propagation and deposition of flow-type landslides was combined with different empirical geomorphological index approaches for the assessment of the formation of landslide dams and their possible evolution for a local case study in southwestern China. The SPH model was calibrated with a previously occurred landslide that formed a stable dam impounding the main river, and it enabled the simulation of final landslide volumes, and the spatial distribution of the resulting landslide deposits. At four different sites on the endangered slope, landslides of three different volumes were simulated, respectively. All landslides deposited in the main river, bearing the potential for either stable impoundment of the river and upstream flooding scenarios, or sudden breach of incompletely formed or unstable landslide dams and possible outburst floods downstream. With the empirical indices, none of the cases could be identified as stable formed landslide dam when considering thresholds reported in the literature, showing up the limitations of these indices for particular case studies of small or intermediate landslide volumes and the necessity to adapt thresholds accordingly for particular regions or sites. Using the occurred benchmark landslide as a reference, two cases could be identified where a complete blockage occurs that is more stable than the reference case. The other cases where a complete blockage was simulated can be considered as potential dam-breach scenarios.     

滑坡运动距离超越概率评价及危险性区划

针对岩土体物理力学参数不确定性强、动态数值模拟方法对滑坡运动距离预测精度有限的问题,提出一种基于拉丁超立方采样法（LHS）的滑坡运动距离超越概率定量评价方法,以提高滑坡滑程预测结果的可靠性。该方法将滑坡计算参数考虑为服从某种概率分布的随机变量,使用LHS对随机变量进行分层抽样,并基于动态数值模型计算每组随机样本对应的滑坡运动距离,最后,通过构建不同运动距离阈值下的极限状态函数计算运动距离超越某一给定位置的概率。应用该方法对大堡子滑坡运动距离进行评价,得到该滑坡运动距离在95%置信水平下的置信区间为[196 m,302 m];并根据运动距离-超越概率图,提出以50%、10%、1%和0.1%作为分界概率值将该滑坡潜在威胁范围分为极高、高、中、低、极低5个危险性等级。计算结果显示,滑坡实际运动距离在95%置信区间内,实际的威胁范围也在划分的高-极高危险区内,说明评价结果合理,证明了基于运动距离超越概率的滑坡运动危险性评价的有效性。研究成果为滑坡运动距离评价及危险性区划提供了新的思路,具有重要的理论意义和工程实用价值。     

Bayesian active learning for parameter calibration of landslide run-out models

Landslides - Landslide run-out modeling is a powerful model-based decision support tool for landslide hazard assessment and mitigation. Most landslide run-out models contain parameters that cannot...     

Flow slides run-out prediction using a sliding-consolidation model

The estimation of maximum travel distance of flow slides is an important topic to assess the consequence of natural disasters caused by landslides. During debris transportation, dissipation rules of pore-water pressure determine movement properties of flow slides. Based on 1-D Terzaghi consolidation theory, expressions of excess pore-water pressure with three cases of initial conditions are deduced and are programmed using Mathematica^® language. Furthermore, the factors affecting the distribution of pore-water pressure are studied using nondimensional method interactively, such as z/h, u _b /u _a , and T _v , which are fairly significant to investigate soil consolidation during the movement of flow slides. On the basis of the sliding-consolidation model first provided as reported by Hutchinson (Can. Geotech. J. 23(2):115-126, 1986), equations of pore-water pressure, velocity, and travel distance of flow slides are obtained and the physical quantities are coded as mathematical functions using Mathematica^® language characterized by its user-friendly interfaces to study run-out properties of flow slides very easily. The program can be used to compute velocity of flow slide, time, and pore-water pressure at a certain position, and thus judge automatically when and where flow slide will stop on slopes with different slope angles, solving the computing difficulties encountered during the Hutchinson's model application, especially in the last decades when computing technique with computers did not develop so rapidly as at present. At last, back analysis for properties of the 1966 flow slide at Aberfan, South Wales is done to test the model and the program, whose results are compared with those as reported by Hutchinson (Can. Geotech. J. 23(2):115-126, 1986). The results show that the program developed by the authors makes the application of Hutchinson's model more correct and easier.     

BP模型在区域滑坡灾害风险预测中的应用

滑坡灾害具有整体性、动态性、开放性和随机性的特点,而人工神经网络属于非线性动态系统,具有符合区域滑坡灾害风险预测的研究特点。应用BP模型,建立了区域滑坡灾害风险的预测流程,并与GIS技术相结合,对三峡水库蓄水条件下巴东新县城的滑坡灾害进行了危险性、易损性、风险性综合预测研究,证明了BP模型在区域滑坡灾害风险预测中的应用可行性,同时指出了所存在的问题及可能解决的途径。     

自动网格法在大型滑坡模型试验位移测试中的应用

应用非接触式光学测量方法中自动网格法原理,研究了大型滑坡模型试验中的位移测试方法及其分布规律。以石榴树包滑坡模型试验为例,针对自动网格法用于大型滑坡模型试验位移测量时所存在的问题提出了解决措施,并对石榴树包滑坡在不同水位运行工况下的位移规律进行了研究分析。     

A new data assimilation procedure to develop a debris flow run-out model

Parameter calibration is one of the most problematic phases of numerical modeling since the choice of parameters affects the model’s reliability as far as the physical problems being studied are concerned. In some cases, laboratory tests or physical models evaluating model parameters cannot be completed and other strategies must be adopted; numerical models reproducing debris flow propagation are one of these. Since scale problems affect the reproduction of real debris flows in the laboratory or specific tests used to determine rheological parameters, calibration is usually carried out by comparing in a subjective way only a few parameters, such as the heights of soil deposits calculated for some sections of the debris flows or the distance traveled by the debris flows using the values detected in situ after an event has occurred. Since no automatic or objective procedure has as yet been produced, this paper presents a numerical procedure based on the application of a statistical algorithm, which makes it possible to define, without ambiguities, the best parameter set. The procedure has been applied to a study case for which digital elevation models of both before and after an important event exist, implicating that a good database for applying the method was available. Its application has uncovered insights to better understand debris flows and related phenomena.     

SHALSTAB模型在浙南林溪流域滑坡预测中的应用

受台风暴雨影响,浙南林溪流域滑坡频发。针对该区域滑坡规模小、长度与厚度比值大的特点,采用浅层滑坡稳定性模型(SHALSTAB)对潜在滑坡进行了预测,以log(降雨量q/土壤的导水系数T)作为划分标准,结果显示随着log(q/T)值的提高,预测的滑坡区域逐渐扩大,预测捕获率升高的同时,误判率也随之上升。以log(q/T)≤-3.1作为预测滑坡的判别标准,模型效果较好,预测捕获率为62.50%,误判率(17.79%)较低。预测结果显示,滑坡潜在区域主要位于斜坡下部、土体厚度大和坡度陡峭的地区,山体顶部、土体厚度薄和地形平坦的区域斜坡稳定。     

灰色理论模型在矿区滑坡变形预测中的应用

灰色理论模型具有利用“少数据”、“小样本”的优点,使得其在滑坡预测分析中显示出极大的优势。利用矿区滑坡监测数据建立起GM(1, 1)模型,通过数据对比、验证和分析,证明了灰色理论模型能更好的反映观测目标的变形趋势。     

Application of Dempster-Shafer theory of evidence to GIS-based landslide susceptibility analysis

GIS-based spatial data integration tasks for predictive geological applications, such as landslide susceptibility analysis, have been regarded as one of the primary geological application issues of GIS. An efficient framework for proper representation and integration is required for this kind of application. This paper presents a data integration framework based on the Dempster-Shafer theory of evidence for landslide susceptibility mapping with multiple geospatial data. A data-driven information representation approach based on spatial association between known landslide occurrences and input geospatial data layers is used to assign mass functions. After defining mass functions for multiple geospatial data layers, Dempster’s rule of combination is applied to obtain a series of combined mass functions. Landslide susceptibility mapping using multiple geospatial data sets from Jangheung in Korea was conducted to illustrate the application of this methodology. The results of the case study indicated that the proposed methodology efficiently represented and integrated multiple data sets and showed better prediction capability than that of a traditional logistic regression model.     

贝叶斯信息标准在滑坡因子敏感性分析中的应用

滑坡因子敏感性分析是滑坡预测和治理的重要前提。以巫山县新址西区作为试验区,运用滑坡影响因素与历史滑坡之间建立的Logistic回归模型,通过贝叶斯信息标准进行模型优劣程度的比较,以期得出本区滑坡因子的敏感程度。设计了逐个加入影响因子进行非嵌套模型的优劣程度对比的试验方法。试验区滑坡因子敏感程度计算结果排队依次为：岩性、高程、距有影响构造线距离、坡度、坡向、坡形。试验为区域斜坡稳定性评价提供了一种新的、可靠的方法。     

三维激光扫描技术在滑坡物理模型试验中的应用

大型滑坡物理模型试验中常采用高精度的特征点监测,缺少整体变形资料;而三维激光扫描技术可以高精度、快速、完整地扫描实物,获得海量的点云数据,构建实物的数字化模型,从而详细描述表面细部状况。将三维激光扫描技术引入到滑坡物理模型试验坡体表面整体变形监测中,通过数字仿真试验对点云数据4种变形测量方式进行了对比和评价,推导了点云数据单个扫描点的空间位置精度的评价模型,对点云密度进行了理论分析。通过滑坡物理模型试验实例,采用点云比较、重心法、点云叠加方法测量模型的整体变形和单个监测点的位移,对滑坡不同演化阶段变形特征进行了综合分析。研究表明:空间位置精度的评价模型、点云密度模型为三维激光扫描变形监测的测量成果评定,测量方案的优化设计提供了必要的理论基础。点云叠加、点云比较为面测量,可以获得整个模型坡面的变形和位移情况,测量模型的变形趋势和变形量级,重心法、拟合法则属于点测量,可以获得单个监测点准确的位移量。基于三维激光扫描技术坡面监测是结合点测量和面测量的优势,在保证高精度特征点监测同时,获得模型坡面的整体变形和位移。     

红外热像技术在滑坡物理模型试验中的应用

将红外辐射成像技术引入滑坡物理模型试验中,通过红外热像仪与三维激光扫描仪所搭建的监测系统,对滑坡模型坡体表面变形破坏全过程进行温度与位移的监测。基于滑坡表面监测数据,将原始红外热像监测图形进行数据修正与差值处理,采用处理后获得的温度场数据,将其与模型坡表位移演化规律进行对比分析。结果表明,滑坡模型在进入加速变形阶段前,潜在破裂区域温度随荷载的增大而均匀上升,破裂带内、外温差较小;滑坡模型进入加速变形阶段后,会在潜在破裂区域的红外热像上出现条形的高温异常区域,破裂区域的破裂带内、外温差迅速拉大,两者相差最高为0.49°C,整体滑动失稳前夕,平均红外辐射温度-时间曲线上再表现出破裂带内温度陡增后降低的规律。研究结果表明,红外热像技术可以应用于滑坡模型试验,利用温度可对滑坡进行预测预报提供参考。     

优化方法在库岸斜坡稳定性评价中的应用

对三峡库区归州老滑坡在库水位从175m下降到145m过程的滑坡稳定性进行研究,通过黄金分割方法优化计算时步,利用MIDAS/GTS有限元软件分析了库水位下降时岸坡内孔隙水压力的变化及由此引起的岸坡稳定性变化,确定了库水位下降量与库岸斜坡稳定安全系数的关系,结果表明:将优化方法用到库岸斜坡稳定性分析中,可提高计算效率;在库水位下降过程中,斜坡的稳定安全系数不是单调降低,而存在一个极小值;三峡库区归州老滑坡基本稳定。     

灰色GM（2,1）模型在滑坡变形预测中的应用

应用灰色模型对滑坡变形进行预测,目前常用灰色GM(1,1)模型,而灰色GM(2,1)模型应用较少.在实际建模中发现,取不同长度的数据序列,建立的模型也不一样,所得的预测结果也有所不同.针对上述问题,本文基于统计的方法,得出白店子滑坡灰色预测模型最佳数据序列长度,在此基础上建立GM(2,1)模型对该滑坡深部位移进行预测,并与GM(1,1)模型预测结果进行了对比.结果表明,总体精度上GM(2,1)模型略高,预测误差较小,有很好的应用价值.     

机器学习模型在滑坡易发性评价中的应用

机器学习在滑坡的易发性评价中面临两个难点,一是评价指标的客观量化,二是训练样本的选择。鉴于此,采用频率比法实现了评价指标的客观量化,利用k均值聚类算法实现了非滑坡样本数据的筛选。结果表明,以k均值聚类算法筛选非滑坡为前提,神经网络的训练精度由73%提升到了97%,支持向量机的训练精度由75%提升到了96%。基于GIS平台,将神经网络和支持向量机模型计算的全区易发性指数按自然断点法分为五个区域,分区图与历史灾害点的叠加分析统计结果显示,神经网络在全局范围内的评价结果优于支持向量机模型,全局精度分别为76%和74%。研究结果可为南江县的防灾减灾工作提供参考。