Logistic regression versus artificial neural networks: landslide susceptibility evaluation in a sample area of the Serchio River valley,Italy

This article presents a multidisciplinary approach to landslide susceptibility mapping by means of logistic regression, artificial neural network, and geographic information system (GIS) techniques. The methodology applied in ranking slope instability developed through statistical models (conditional analysis and logistic regression), and neural network application, in order to better understand the relationship between the geological/geomorphological landforms and processes and landslide occurrence, and to increase the performance of landslide susceptibility models. The proposed experimental study concerns with a wide research project, promoted by the Tuscany Region Administration and APAT-Italian Geological Survey, aimed at defining the landslide hazard in the area of the Sheet 250 “Castelnuovo di Garfagnana” (1:50,000 scale). The study area is located in the middle part of the Serchio River basin and is characterized by high landslide susceptibility due to its geological, geomorphological, and climatic features, among the most severe in Italy. Terrain susceptibility to slope failure has been approached by means of indirect-quantitative statistical methods and neural network software application. Experimental results from different methods and the potentials and pitfalls of this methodological approach have been presented and discussed. Applying multivariate statistical analyses made it possible a better understanding of the phenomena and quantification of the relationship between the instability factors and landslide occurrence. In particular, the application of a multilayer neural network, equipped for supervised learning and error control, has improved the performance of the model. Finally, a first attempt to evaluate the classification efficiency of the multivariate models has been performed by means of the receiver operating characteristic (ROC) curves analysis approach.     

突发型黄土滑坡监测预警理论方法研究——以甘肃黑方台为例

灌溉诱发的黄土滑坡大多数具有明显的突发性特征;斜坡破坏过程变形量小,历时短,具有较大的危险性。由于此类黄土滑坡加速变形阶段经历时间较短,GNSS系统和裂缝计等传统监测手段难以获取加速变形阶段系统完整的监测数据,更难以提前预警。针对这一难题,自主研发了自适应智能变频裂缝仪,它能够根据滑坡变形快慢自动调整采样频率。基于获取的黑方台多个突发型黄土滑坡的全过程变形-时间曲线,对这些变形曲线特征和规律进行分析研究,建立了针对性的黄土滑坡综合预警模型。将变形速率阈值和改进切线角作为滑坡预警的重要指标,建立了4级预警判据,通过自主研发的"地质灾害实时监测预警系统"实现滑坡的实时自动预警,并将预警信息与当地的群防群测信息平台对接,为防灾应急避让提供直接依据。2017年以来已先后6次对黑方台黄土滑坡实施成功预警,避免了重大人员伤亡,取得显著的防灾减灾效果。     

甘肃天水地区强降雨诱发黄土-泥岩滑坡机理实验研究

在甘肃天水地区每年由降雨诱发的黄土-泥岩滑坡灾害事故很多,给当地人民生命财产造成巨大损失。为探索该类斜坡的滑动破坏过程与机理,在野外地质调查、工程地质钻探及岩土体力学测试的基础上,通过室内大型物理模型实验,研究“上部黄土+下部泥岩”二元结构类型斜坡在强降雨作用下的动态变形演化过程,揭示该类斜坡的破坏机理和破坏模式。结果表明:强降雨作用下斜坡变形破坏以滑动破坏为主,水分的作用主要表现为增加土体自重、引起土体强度降低、降低结构面的抗滑力、产生孔隙水压力及降低有效应力等几个方面,斜坡的破坏模式则主要表现为坡肩侵蚀→微裂隙产生、发展、贯通→斜坡局部滑动破坏→斜坡整体滑动破坏。研究结果对天水地区该类滑坡的早期识别有重要的参考意义,可为该类滑坡的防灾减灾提供科学依据。     

基于GIS和层次分析法的沙溪流域滑坡地质灾害易发性评价

滑坡是沙溪流域主要地质灾害类型之一,开展滑坡灾害易发性评价可为区域地质灾害防治提供数据基础和决策依据。通过沙溪流域生态地质调查,分析了滑坡灾害分布规律和影响因素之间的关系,选取岩性建造、地貌、坡度、坡向、降雨量、距河流距离和距断层距离7项指标,利用层次分析法及地理信息系统空间分析技术,开展沙溪流域滑坡地质灾害易发性评价。结果显示: 沙溪流域滑坡易发性影响因子依次为岩性建造、多年年均降水量、地形地貌、坡度、距河流距离、距断层距离和坡向; 沙溪流域滑坡灾害易发性与坡度、岩性建造、年均降水量表现出明显正相关,即坡度越大、岩性建造性质越软弱、越易风化,年均降水量越多,越易引发滑坡灾害; 滑坡灾害易发性与断裂构造、河流距离与滑坡灾害易发性呈负相关,即距离越近越容易诱发地质灾害; 流域整体以低易发区和极低易发区为主,高易发区主要分布在沙溪流域中南部、东部及东北部地区。这为沙溪流域地质灾害防治提供了基础数据和决策依据。     

斜坡地质结构与地质灾害发育类型研究——以店子街幅灾害为例

岩土体是组成斜坡地质结构的基本单元,斜坡地质结构类型与地质灾害的发育类型密切相关。店子街幅图幅调查范围内主要发育软弱-较坚硬层状泥岩、砂岩岩组,风积黄土单层土体,粉土、砂砾卵石双层土体,粉土、碎石和基岩碎屑多层土体等4类岩土体,这些不同的岩土体组成了6种不同的斜坡地质结构,进而演变形成了不同类型、不同规模的斜坡地质灾害。黄土斜坡结构和黄土—冲洪积层斜坡结构多演变发生小型滑坡灾害、黄土—泥岩斜坡结构多演变发生中—大型黄土泥岩滑坡灾害、泥岩与泥质砂岩互层斜坡结构多演变发生崩塌灾害、泥岩风化堆积层斜坡结构和滑坡堆积层斜坡结构多演变发生小-中型滑坡灾害。研究不同斜坡地质结构与地质灾害发育类型的发育关系,有助于进一步开展区域崩塌、滑坡形成机理研究,研究成果有助于洮河下游地质灾害防治工作的展开,并为地方政府科学制定地质灾害防灾减灾规划提供了技术支持。     

基于最大熵原理的黄土丘陵区地质灾害规模频率分布研究

在分析地质灾害规模分布的基础上,基于最大熵原理在理论上推导出崩塌、滑坡和不稳定斜坡灾害长、宽和厚等参数规模频率负指数分布关系,提出了规模参数频率分布简单而有效的计算公式。最后以黄土丘陵区宝塔区为例,对所提出的公式进行验证,结果表明：（1）宝塔区地质灾害以中型滑坡和中型崩塌为主,但大型地质灾害在控制着滑坡崩塌总面积和总体积中起着重要的作用;（2）滑坡、崩塌和不稳定斜坡规模等级指数主要集中于(5.5,6]级、(4,4.5]级和(5,5.5]级;（3）崩塌、滑坡和不稳定斜坡的长、宽和厚规模频率分布符合更简单的指数关系,且用指数关系拟合的规模频率曲线不会产生偏转效应;（4）对面积和体积取算术平方根和立方根后,它们的规模－频率分布也呈现出负指数分布,并且拟合效果良好（决定系数R2>0.9,概率P<0.05）。     

A large-scale obliquely inclined bedding rockslide triggered by heavy rainstorm on the 8th of July 2020 in Shiban Village,Guizhou, China

A large-scale obliquely inclined bedding rockslide, activated by a heavy rainstorm, occurred on July 8, 2020, at 7:05 (UTC?+?8) in Shiban Village, Songtao Miao Autonomous County, Guizhou Province, China. The loss of life in this event was greatly reduced owing to the local warning system for rainstorm-induced geohazards. To understand the failure characteristics, triggering factors, the genetic mechanism of the landslide, the geomorphological features, geological characteristics, hydrological conditions, and rainfall characteristics were systematically studied by a synthetic approach including field investigations, satellite imagery, unmanned aerial vehicle (UAV) photography, laboratory tests, and rainfall data statistics. The results indicated that the interface between the soft and hard rock, the well-developed joints, and the free face in front of the slope constituted the boundaries of this landslide. The concave topography at the back and southern edge of the landslide, the bare ground, and the cataclastic structure of the rock mass provided favorable conditions for the collection or infiltration of rainwater. The concentrated rainstorm was the direct trigger for the landslide, which led to a rapid inflow and retention of rainfall in the landslide through favorable landform and geological conditions. The groundwater recharge that cannot be drained in time caused the mechanical deterioration of rock mass and induced a rapid increase in pore water pressure in the landslide. Moreover, the water level of the Ganlong River at the toe of the slope also rose rapidly, and the uplift pressure in front of the slope increased accordingly. Under the combined action of these adverse factors, the overall anti-sliding force of the slope was less than the sliding force, finally resulting in the landslide. Remarkably, the local warning system for rainstorm-induced geohazards successfully forecasted the landslide, but the shortcoming is that the forecast time in advance is short. Nevertheless, the prediction has significantly reduced human casualties and provided valuable experience for the prediction of this type of landslide.

     

Analysis of rainfall-induced infinite slope failure during typhoon using a hydrological–geotechnical model

Rainwater infiltration during typhoons tends to trigger slope instability. This paper presents the results of a study on slope response to rainwater infiltration during heavy rainfall in a mountain area of Taiwan. The Green-Ampt infiltration model is adopted here to study the behavior of rainwater infiltration on slopes. The failure mechanism of infinite slope is chosen to represent the rainfall-induced shallow slope failure. By combining rain infiltration model and infinite slope analysis, the proposed model can estimate the occurrence time of a slope failure. In general, if a slope failure is to happen on a slope covered with low permeability soil, failure tends to happen after the occurrence of the maximum rainfall intensity. In contrast, slope failure tends to occur prior to the occurrence of maximum rainfall intensity if a slope is covered with high-permeability soil. To predict the potential and timing of a landslide, a method is proposed here based on the normalized rainfall intensity (NRI) and normalized accumulated rainfall (NAR). If the actual NAR is higher than the NAR calculated by the proposed method, slope failure is very likely to happen. Otherwise, the slope is unlikely to fail. The applicability of the proposed model to occurrence time and the NAR–NRI relationship is evaluated using landslide cases obtained from the literature. The results of the proposed method are close to that of the selected cases. It verifies the applicability of the proposed method to slopes in different areas of the world. An erratum to this article can be found at     

贵州兴义滑坡特征及过程预警研究

由于滑坡岩土体结构的复杂性和破坏机制的多样性,滑坡预警一直以来都是全球性难题,极具挑战性。本文论述了贵州省兴义滑坡特征及其成功预警,并分析了滑坡成功预警的关键因素。在对滑坡现场进行地质调查的基础上,综合应用卫星遥感、无人机航拍、LiDAR、地表位移监测等技术手段,初步分析结果认为,兴义滑坡属于典型的含软弱夹层的顺层岩质滑坡,滑源区坡体为2014年首次滑动后形成的不稳定斜坡,在不利的坡体结构加之与软弱夹层组合的地质条件下,受到长期重力及地下水作用,最终演变成滑坡地质灾害。兴义滑坡至2014年第一次滑动后,后缘山体对前缘公路和居民就产生了威胁,2019年2月17日凌晨5时53分,贵州省兴义市马岭镇龙井村兴-马大道旁约96×104 m3的山体再次发生顺层滑动。在滑坡发生前,研究人员就在滑坡体上安装了全球导航卫星系统(GNSS)和自适应性裂缝计两种位移监测传感器,对滑坡变形进行持续监控。现场监测数据实时传输到研究人员自主研发的“地质灾害监测预警系统”中,系统通过多种阈值综合预警模型自动计算监测数据并发布预警结果,在滑坡进入临滑阶段后,系统提前53 min发出了红色预警,完全避免了人员和经济损失。该滑坡的成功预警体现了自主研发的地质灾害监测预警系统、预警模型、监测仪器三者的适用性,可为今后类似滑坡的监测预警研究及应用提供借鉴。     

贵州金海湖新区田湾子滑坡活动特征及成因机理分析

2022年1月3日18时55分,贵州毕节市金海湖新区归化街道田湾子发生一起顺层滑坡,形成约3.5×10⁴ m³的堆积体,造成14人遇难,3人受伤。综合应用无人机航拍、现场测试等技术手段,文章详细描述了现场的地质调查,初步分析了滑坡体特征、滑坡发生的运动过程和成因机理,并对滑坡残留体的潜在危险进行了监测和分析,为现场救援行动提出搜救建议。初步研究结果认为,滑坡源区特殊的地形地貌条件、风化碎裂的泥质白云岩和不利的岩体结构面是滑坡形成的内因,边坡开挖扰动致斜坡的地表形态和应力分布发生改变是滑坡发生的外因。田湾子滑坡发生前斜坡无明显的变形迹象,灾害发生具有突发性,造成了较大的人员伤亡和经济损失,深入研究田湾子滑坡的形成过程和成灾机理,对贵州山区存在类似条件的地质灾害隐患防治工作具有现实的指导意义。     

中山市崩塌、滑坡地质灾害发育规律分析

随着社会经济的发展,人类工程活动日趋强烈,中山市崩塌、滑坡地质灾害呈加剧趋势。根据中山市1：50000地质灾害详细调查数据,结合中山市环境地质特征,对中山市崩塌、滑坡地质灾害的发育规律进行了分析。统计分析表明,4~9月是汛期雨季,是中山市崩塌、滑坡地质灾害的高发季节。崩塌、滑坡地质灾害多发生在坡高10~30 m的斜坡带上,均分布于山体坡脚,临近居民区及建筑物,与人类工程活动密切相关。本地区崩塌、滑坡地质灾害具有突发性强、规模小、危害性大等特征,为中山市今后崩塌、滑坡地质灾害防治工作提供基础依据。

     

辽宁抚顺西露天矿地质灾害时空分布特征及影响因素分析

已有百年开采历史的抚顺西露天矿进入闭坑期,由于资源的开采,导致西露天矿长期受地质灾害的威胁。为了总结西露天矿地质灾害发生规律、保障矿区及近矿城区的生产生活安全,同时为其他同类露天矿的灾害分析、安全防护提供可参考案例,从时间和空间尺度对抚顺西露天矿滑坡、地裂缝的分布规律和影响因素进行研究分析,基于DPSR模型,从驱动力响应、压力响应、状态响应三个方面提出对应的断链减灾和安全防护措施。地质灾害的时空分布特征为：滑坡灾害最早出现于1927年南帮西部,滑坡主要位置由南帮西部区域向西端帮、北帮西部、北帮中部、北帮东部方向发展,近年南帮出现大规模岩质边坡滑移变形,1970—2000年期间,滑坡灾害最为频发,2000年以后滑坡灾害频次减少,且滑坡灾害多发生在5—9月份;北帮附近地裂缝出现于1960年后,上世纪70、80年代加速发育,走向与F1、F1A断层走向基本一致,南帮地裂缝分布在南帮巨大滑移变形体后缘,呈弧扇型分布,于2009年出现,2012年后迅速发展。通过对灾害影响因素分析发现,滑坡与地裂缝存在同源性和互为因果性的链式关系,影响矿区地质灾害发生的主要因素为地质构造和不良工程地质环境控制、采矿活动驱动、降雨及地下水因素的诱发。     

地震作用下甘肃天水地区黄土-泥岩接触面滑坡机理

以甘肃天水地区渭河北岸大型黄土-泥岩滑坡为研究对象,通过野外地质调查、工程地质钻探、室内力学试验以及FLAC3D数值计算的方法,对该类滑坡的发育特征及地震作用下的稳定性进行分析评价。结果表明:该类滑坡多属于历史地震滑坡,其破坏类型为滑移拉裂型。通过对滑坡的稳定性进行计算分析可知,静力作用下滑坡处于稳定状态;地震作用下,稳定性明显降低,坡体可能再次滑动,预测滑面位于黄土-泥岩接触带位置,与野外调查观测结果一致。研究结果对天水地区该类滑坡的早期识别有重要参考意义,可为该类滑坡的防灾减灾提供科学依据。     

顺层岩质滑坡渐进破坏进入加速的能量学判据

顺层岩质滑坡是最常见的斜坡灾害,研究其渐进破坏过程、建立预报判据对于防灾减灾具有重要意义.以秭归杉树槽滑坡为例,在野外调查和室内岩石试验的基础上,利用JRC-JCS模型及GSI法估算得出滑坡基本力学参数;通过FLAC3D模拟滑坡渐进破坏过程,分析顺层岩质滑坡变形破坏的发展规律;基于能量守恒和虚功原理,提出了顺层岩质滑坡迈入加速变形的能量学判据.研究表明:杉树槽滑坡由后缘向前渐进破坏,后缘变形累积的总位移值不断增大,前缘切层段的锁固作用使变形迅速降低,当临近破坏时,前缘位移由前向后发展,滑面快速贯通;滑体沿滑动方向应变曲线可近似表示为"S"型曲线,随渐进破坏该曲线向坡下发展;以滑体动能增量大于0作为滑坡迈入加速变形的能量学判据,其结果符合滑坡地质演化观点,与FLAC3D模拟结果吻合.      

公路沿线花岗岩风化区滑坡危险度评价--以日本49号国道合户地区为例

对公路沿线边坡进行稳定性评价及滑坡灾害分析，对于由滑坡、泥石流等引起的公路灾害的防治具有重要指导意义。为了评价处于花岗岩风化区的日本福岛县合户地区49号国道沿线边坡的滑坡危险程度，在调查和分析了该地区的表层破坏模式、并通过简易探测方法摸清了风化土层的厚度分布后，将研究区域划分为边坡单元(Slopeunit)，使用椭球体下半部模拟滑动面的形状，通过随机试算法确定各边坡单元危险滑动面的位置及空间形状；采用一种基于GIS的边坡稳定性三维分析模型计算各边坡单元最小安全系数以及滑坡发生概率，定量评价滑坡灾害危险程度。所有的计算过程及结果显示均在一个基于GIS平台的系统中完成，为如何利用GIS技术更好地为滑坡灾害防治工作服务拓宽了思路。     

基于多层次物理力学参数的小区域地震滑坡危险性评估——以长江上游石棉县城及周边为例

通过实地调查、遥感解译、资料收集等手段,获取滑坡崩塌体编录、松散堆积层、地质单元的岩土体物理力学参数,使得滑坡编录、地质调查数据与区域Newmark位移模型有机结合。研究表明,在滑坡编录等3个层次中,由第一层次到第三层次,物理力学参数精度逐渐下降,这也反映了滑坡编录在危险性评价中所占据的重要性,更能与实际相吻合。通过对长江上游石棉县城地质灾害潜在危险性的评估,得出了不同尺度峰值加速度下危险性分布区域与规律,经与危险性线性拟合,在峰值加速度a=0.3时,区域危险区面积呈大规模急剧上升,为区域毁灭性灾难的临界值。同时,石棉县城随着峰值加速度数值增大,危险区从滑坡编录控制逐渐过渡到坡度控制,显示了多层次物理力学参数下危险性评估的合理性。      

Landslide risk evaluation and hazard zoning for rapid and long-travel landslides in urban development areas

Risk evaluation for earthquake-induced rapid and long-travel landslides in densely populated urban areas is currently the most important disaster mitigation task in landslide-threatened areas throughout the world. The research achievements of the IPL M-101 APERITIF project were applied to two urban areas in megacities of Japan. One site is in the upper slope of the Nikawa landslide site where previous movements were triggered by the 1995 Hyogoken-Nambu earthquake. During detailed investigation, the slope was found to be at risk from a rapid and long-travel landslide induced by sliding surface liquefaction by earthquakes similar in scale to the 1995 event. A new plan to prevent the occurrence of this phenomenon was proposed and the plan was implemented. Another area is the Tama residential area near Tokyo. A set of field and laboratory investigations including laser scanner, geological drilling and ring-shear tests showed that there was a risk of sliding surface liquefaction for both sites. A geotechnical computer simulation (Rapid/LS) using the quantitative data obtained in the study allowed urban landslide hazard zoning to be made at individual street level.     

缓倾煤层采空区上覆山体滑坡形成机制分析

下伏采空区的缓倾斜坡,由于采空区大小、方位不同和斜坡结构特征的差异,多存在地表沉陷、拉裂、局部崩塌、滑坡等工程地质问题,常常会诱发大规模的地质灾害。马达岭滑坡发育于存在软弱夹层和煤层采空区的缓倾斜坡中,由采空区的破坏和降雨诱发形成,体积达190104m3。调查和分析表明,脆弱的地质结构和坡体下伏采空区的破坏是滑坡形成的主要原因,降雨的促进作用加速了滑坡的发生; 马达岭滑坡的破坏模式为塌落-拉裂-剪切滑移,滑坡的形成机制和发展过程可以分为以下3个阶段: 斜坡后缘拉裂阶段,滑面贯通阶段和滑坡整体破坏阶段。崩滑体崩解后顺着沟谷向下游流动,形成长1.5km的泥石流碎屑堆积区,淹没大量农田。     

川东红层缓倾岩质滑坡的演化过程及其识别标志探讨

通过对典型案例的调查研究,总结提出了川东缓倾顺层岩质滑坡的变形演化阶段划分理论,并提出不同演化阶段下的识别标志特征。结论表明:（1) 初期短距离启动阶段,斜坡后缘主要表现为深大裂隙;（2) 中期槽谷扩张阶段,斜坡后缘主要表现为沟槽、拉陷槽或者斜坡具有汇水聚集发生剧滑的地形特征,如圈椅状地形、三沟环绕或双沟同源地形、后缘洼地地形等。（3) 大型、特大型顺层岩质滑坡大多为斜坡二次、甚至三次启动滑动的结果,识别古（老) 滑坡是圈定大型、特大型顺层岩质滑坡的重要途径之一。（4) 在地调详查中,应特别注重对斜坡微地貌和后缘拉张破坏区的调查,重点排查初期短距离拉槽启动阶段及中期槽谷扩张阶段的隐伏性斜坡。本研究为区内滑坡的预测预防和大型、顺层岩质滑坡隐患点的判定提供指导。     

地质灾害防治工作中容易混淆的术语和问题探讨

结合正在实施的科研项目,笔者等就斜坡、边坡与滑坡,勘察与勘查,工程地质测绘与调查等容易混淆的术语,地质灾害与非地质灾害野外判别、不稳定斜坡术语的含义及特点等问题进行研究探讨,初步建立山区地质灾害与非地质灾害典型识别图谱。