Time evolution and spatial accumulation of progressive failure for Xinhua slope in the Dagangshan reservoir,Southwest China

This paper presents a preliminary study of time evolution and spatial accumulation of progressive failure for ancient landslide deposits in Xinhua slope. According to the geological response after impoundment, the Xinhua slope has shown the spatial accumulation of deformation, such as ground cracks in the rear edge, toe collapse, local shallow slides in intense rainfall, and progressive creep displacement. Approximately 2 years of monitoring was performed for the Xinhua slope with the assistance of the global navigation satellite system (GNSS), unmanned aerial vehicles (UAVs), and field investigations. The deformation process of a reservoir landslide is considered to be a comprehensive and complicated combination of geological influence from various adverse factors. Field investigations and monitoring indicate that the major serious influence after completion of dam construction comes from the initial large-scale impoundment, the fluctuation of water level, and the existence of a flood season. The creep/slip deformation of slope deposits is a result of integration with adverse hydraulic conditions, e.g., strong rainfall, intense currents and transient seepage flow inside the slope deposits, and activation by water level fluctuation, which can be verified from the twofold evident deformation in the flood season. For the reservoir with daily regulation ability, the occurrence of evident deformations in July highlights that the regulation plan for water level in the flood season is important for controlling the deformation of slope deposits, where the fluctuation of the water level is no more than 10 m in the operation period.     

Analysis of Baishuihe landslide influenced by the effects of reservoir water and rainfall

Since the impoundment of the Three Gorges Reservoir in June 2003, a number of new landslides have occurred and existing landslides have been made worse. The 1,260 × 10⁴ m³ Baishuihe landslide, located at 56 km west of the Three Gorges Dam, began to deform more noticeably after the first impoundment in early July 2003. The sliding of the two blocks comprising the landslide, one an active block and the other a relatively stable block, became apparent after approximately 5 years of monitoring. Field recordings show that the landslide displacement is affected by the combined effects of the rainfall and water level in the reservoir. These effects have been investigated in the present paper, including the deformation characteristics (movement pattern, direction, displacement and velocity) earmarking the temporal evolution of the active block. Based on a practical creep model of a large rock slide, alert velocity thresholds for pre-alert, alert and emergency phases have been computed corresponding to the imminence of failure. The alert velocity thresholds are being proposed to be included as a part of an early-warning system of an emergency plan drawn up to minimize the adverse impact in the event of landslide failure. The emergency plan is intended to be implemented as a risk management tool by the relevant authorities of the Three Gorges Reservoir in the near future.     

基于数据挖掘的三峡库区特大滑坡变形关联规则研究

从实测数据中分析滑坡灾害的成因机理,对于准确识别潜在危险区与及时制定防治措施十分重要。由于现场监测数据的数量庞大、来源多样,常规的数据处理方法难以从海量监测数据中提取出有用的信息,进而对滑坡变形演化趋势作出正确评价和预测。本文基于经典数据挖掘方法中的两步聚类法与关联规则分析,提出了滑坡变形行为的关联分析挖掘技术,并以长江三峡库区新铺滑坡为例,对库水位波动及降雨影响下的特大滑坡位移速率进行了关联分析。结果表明:该滑坡的变形受库水位高程水平、库水位波动速率与降雨强度等因素的多重影响,水位下降、强降雨与滑坡变形密切相关;滑坡不同空间位置处的变形影响因素存在差异,由坡脚至坡顶,库水位波动的影响水平依次降低,降雨强度的影响水平逐渐增强。本文提出的数据挖掘方法可定量分析滑坡变形的控制因素,并通过与实测数据的对比验证了相关规则的可靠性,这对于海量监测数据条件下滑坡灾害的成因分析有重要意义。     

三峡库区树坪滑坡变形失稳机制分析

树坪滑坡自2003年三峡水库蓄水以来,就一直持续变形。为了对其稳定性及变形发展趋势进行评价和预测,有必要对其变形失稳机制进行深入研究。为此,采用现场地质调查和勘探的方法确定了滑坡的形态和性质;充分挖掘变形监测数据,详细分析了滑坡的变形特征。在此基础上,深入研究了变形失稳机制及影响因素,并对滑坡的稳定性进行了计算和预测。结果表明,滑坡区地形、岩性及地质构造等地质因素控制了树坪滑坡的形成和发展;库水位下降和大气降雨进一步激励了滑坡的变形。库水位下降,坡体内地下水位随之下降,但其速度远小于库水位下降速度,导致坡体内水力梯度和渗透力明显增大,从而使滑坡稳定性急剧下降,并且库水位下降速度越快,滑坡的位移速率也越大,是典型的水库下降型滑坡。在库水位下降过程中,若出现明显的降雨过程,更加剧了滑坡的变形,有产生大规模滑动的可能性,须采取防护治理措施。     

New data and interpretations of the shallow and deep deformation of Huangtupo No. 1 riverside sliding mass during seasonal rainfall and water level fluctuation

The original Badong County, Hubei, China, was mainly below the highest water level of the Three Gorges Reservoir, which is 175 m above sea level. The new downtown of Badong was rebuilt in the Huangtupo area between 1982 and 1991. After detailed geological investigation in the Huangtupo area, four independent landslides were identified, making it one of the largest and most harmful landslide group in the Three Gorges Reservoir area. Since 2003, abundant data have been obtained from the Huangtupo No. 1 sliding mass about rainfall, water level, earth surface deformation and deep deformation. The monitoring data indicate that the earth surface and deep deformation of this landslide is closely related to the seasonal rainfall and water level fluctuation of the reservoir. During increases in the water level, the earth surface deformation velocity decreases, and then increases obviously in the subsequent water level decreasing stage. Because the water level drawdown period overlaps with the rainy season in this area, the earth surface deformation is affected by both rainfall and water level. The deformation velocity of the earth surface caused by rainfall is about 5 mm/month, while that caused by water level decrease is 5–7 mm/month. On the contrary, the deformation velocity of the deep sliding mass accelerates 2 to 3 times faster than average during water level increase. The distinction of surface and deep deformation regulations indicates that the effects of seasonal rainfall and water level fluctuation on the stability of reservoir wading landslides are different. Based on all monitoring data, we also found that the Huangtupo No. 1 riverside sliding mass is creeping seasonally during the seasonal rainfall and periodic reservoir water level fluctuation. The deformation velocities of the east regions of the sliding body indicate acceleration, making these regions even more dangerous.     

Movement of the Shuping landslide in the first four years after the initial impoundment of the Three Gorges Dam Reservoir, China

The Shuping landslide was reactivated by the initial impoundment of the Three Gorges Dam Reservoir, China in June 2003. For purposes of landslide disaster mitigation in the reservoir area and identification of landslide movement and deformation caused by reservoir level changes, a monitoring system mainly consisting of drum-style extensometers was installed in the eastern part of the Shuping landslide. Systematic monitoring was started in August 2004 with installation of 13 extensometers above the waterline after the initial impoundment. In August 2006, 11 more drum-style extensometers were installed above the high waterline (175 m) and five flexible extensometers were installed along a longitudinal section in the elongation to low waterline. In this paper, the monitoring results from August 2004 to July 2007 are presented and the deforming of the Shuping landslide caused by both reservoir level changes and rainfall is examined.     

长江三峡库区木鱼包滑坡地表变形规律分析

三峡库区木鱼包滑坡自2006年实施专业监测以来,一直持续变形,对三峡大坝工程和长江航道造成巨大威胁。通过多次野外地质调查资料、长期现场巡查、人工GPS位移监测数据、近1年的全自动监测数据等,深入分析该滑坡在库水涨落及降雨条件下的变形特征、演化规律及变形机制。结果表明,滑坡坡体结构、岩性及地质构造等地质因素控制了木鱼包滑坡的变形,库水位是主要的驱动因素。库水位上升过程中,库水位由145 m升到155 m左右,月位移量为最小值;动水压力向坡内,滑坡变形最小;库水位155 m上升至175 m期间,库水入渗前部坡体,对滑坡前部抗滑段形成浮托减重效应,变形有所增加。库水位由175 m下降到170 m左右,累积位移形成阶跃,坡受向坡外动水压力和浮托减重效应作用,月位移达最大值。库水位由170 m降到145 m期间,浮托减重效应作用减小,月位移量降低。目前,木鱼包滑坡变形趋势减小,产生大规模滑动的可能性较小,但须进一步加强监测和机制研究。     

三峡库岸滑坡变形特征及影响因素分析

三峡库区涉水滑坡主要影响因素是水位和降雨量,也是库区滑坡体失稳的主要影响因素和诱发因素。库区每年重复着水位升降不利于滑坡的稳定,而降雨特别是大强度的降雨也诱发产生滑坡。当水位波动遇到降雨,出现工况叠加,滑坡将加剧。因此,有必要对影响滑坡变形的主导因素进行了解分析。2016年6月三峡库区全面展开了自动化监测,使得数据统计方便可靠。本文采用滑坡变形速率、降雨量、库水位变化、最大水位变化速率、淹没程度,运用灰色关联度分析法对涉水滑坡进行了计算分析。水位下降阶段,文中土质滑坡变形受库水位影响最大。水位上升阶段,该土质滑坡上部变形受降雨影响最大,下部受水位影响最大。文中岩质滑坡总是受库水位影响最大。     

白家包滑坡变形与库水位、降雨相关性定量化分析研究

白家包滑坡是具有滞后性“阶跃型”变形的滑坡代表,通过定性分析初步认为,库水位下降是白家包滑坡变形的主要影响因素,其影响程度大于降雨。为了进一步明确白家包滑坡变形对库水位波动和降雨的响应程度,本文根据库水位每年波动情况,将其划分为5个阶段,运用皮尔逊相关系数法对白家包滑坡变形与库水位、降雨的相关性进行定量计算,计算结果为各监测点变形与库水位、降雨都在5~6月份综合计算中相关程度最高,且变形与库水位最大相关性系数绝对值为0.75左右,大于变形与降雨的最大相关性系数(0.45左右)。为了充分消除库水位与降雨之间的相互影响,运用皮尔逊相关系数分别计算白家包滑坡变形与库水位、降雨的净相关性系数,最后将得到的净相关性系数与新建GPS自动监测点在2017~2018年的日变形位移和库水位、降雨对比分析,进行相关性验证。结果表明:白家包滑坡的变形对库水位下降的响应程度大于变形对降雨的响应程度,在库水位快速下降阶段响应程度最高,且与新建的GPS自动监测点监测结果吻合度较高。此结果与定性分析结果和皮尔逊相关系数法分析结果一致,该研究可对滑坡变形影响因素的定量分析提供科学的依据。     

基于离心模型试验的库岸滑坡变形特征研究

三峡库区蓄水后，大量库岸滑坡发生复活变形，为研究滑坡随库水位升降的变形特征和机制，以库区典型直线形滑面形态滑坡为地质原型，概化设计了大尺度离心模型试验，通过模拟两个水位升降过程，布设高速相机和传感器，获取了滑坡变形演化全过程高清影像、孔压和土压?时间变化曲线，可得以下研究结果：在水位首次下降时，孔压和土压逐渐减小，当下降15 min后滑坡发生整体蠕滑变形，首先是前部产生横向张拉裂缝，中后部则是以竖直位移为主的蠕滑压密变形过程，水位停止下降2 min后变形停止，表明变形对库水位变化具有一定滞后性；当水位再次下降时，前部沿原破裂面再次下滑并失稳，中后部则无变形，变形演化具有典型牵引式特征。在库水首次入渗滑坡时，坡体孔隙水压力对库水位升降具有明显的滞后性，而在下一次水位升降过程中，这种滞后性明显减弱。该类滑坡受水位下降的动水压力效应影响较大，在滑坡变形过程中，中后部滑体变形在竖直方向的蠕滑压密行为使得中后部稳定性有所提高，因此，在后期蓄水过程中不再发生变形，试验现象与实际库岸滑坡吻合。试验揭示了三峡库区该类滑坡在水位升降条件下的变形破坏模式及长期演化趋势，为库区地灾防治提供了参考依据。     

三峡库区白家包滑坡变形特征与影响因素分析

针对三峡库区阶跃型滑坡,以白家包滑坡为例,统计分析滑坡位移、变形速率和裂缝监测数据。显示滑坡在2007年6月之前为蠕动变形初期,受降雨和库水位等外界因素的作用,6月滑坡发生剧烈变形,之后一直保持约75°方向滑动。滑坡体中前部位移速率大于后缘,其变形具有牵引式特点。滑体上裂缝与变形位移具有一致性,位移量越大的区域裂缝越发育。将位移速率与降雨、库水位和地下水进行影响机制分析,建立滑坡变形与外界动态影响因素之间的响应关系。结果表明降雨量和库水位变化是引起滑坡季节性变形的主要因素,其中降雨强度、库水位下降及下降速率是导致滑坡位移速率波动大小的关键因子。     

三峡库区巴东红石包滑坡稳定性动态分析

巴东红石包滑坡位于巴东油库场地区,是三峡库区启动的重要地质灾害治理工程项目之一。通过对红石包滑坡内部水平位移和渗透水压力长期监测分析,表明其中的Ⅰ和Ⅱ号滑坡浅层存在缓慢变形,与降雨关系密切;其深层未见变形。说明红石包滑坡体在从2003年6月三峡水库蓄水至今仍处于稳定状态。但后续库水位的的不断抬高以及不同季节库水位频繁变化对滑坡的稳定性极为不利。为确保油库安全,仍应加强监测,密切注视滑坡动态。     

Displacement prediction in colluvial landslides, Three Gorges Reservoir, China

The prediction of active landslide displacement is a critical component of an early warning system and helps prevent property damage and loss of human lives. For the colluvial landslides in the Three Gorges Reservoir, the monitored displacement, precipitation, and reservoir level indicated that the characteristics of the deformations were closely related to the seasonal fluctuation of rainfall and reservoir level and that the displacement curve versus time showed a stepwise pattern. Besides the geological conditions, landslide displacement also depended on the variation in the influencing factors. Two typical colluvial landslides, the Baishuihe landslide and the Bazimen landslide, were selected for case studies. To analyze the different response components of the total displacement, the accumulated displacement was divided into a trend and a periodic component using a time series model. For the prediction of the periodic displacement, a back-propagation neural network model was adopted with selected factors including (1) the accumulated precipitation during the last 1-month period, (2) the accumulated precipitation over a 2-month period, (3) change of reservoir level during the last 1 month, (4) the average elevation of the reservoir level in the current month, and (5) the accumulated displacement increment during 1 year. The prediction of the displacement showed a periodic response in the displacement as a function of the variation of the influencing factors. The prediction model provided a good representation of the measured slide displacement behavior at the Baishuihe and the Bazimen sites, which can be adopted for displacement prediction and early warning of colluvial landslides in the Three Gorges Reservoir.     

降雨和库水位联合作用下库岸滑坡模型试验研究

受库区水位波动和降雨影响,库岸大量老滑坡体变形加剧,地质灾害问题十分突出。为研究库岸滑坡影响因素、变形演化规律及失稳条件,以大型物理模型试验为手段,选取三峡库区黄土坡滑坡临江Ⅰ号崩滑体为对象,通过考虑水位波动、降雨及其组合作用等诱发因素,开展了一系列的库岸滑坡模型试验研究。试验结果表明：水位升降,变形主要集中于模型坡体前缘,其中,水位抬升过程中,滑坡模型变形较小,变形加速阶段出现于水位下降期间,且变形速率与水位下降速率成正比,即临江Ⅰ号崩滑体为典型的动水压力型滑坡;降雨影响下坡体变形在时间和空间上存在明显分区现象,时间上,变形发展主要集中于坡体浅表层饱和之后,即短时降雨对坡体变形未产生显著影响,空间上,坡体前缘和后缘变形剧烈;库水位下降和强降雨联合作用下坡体前缘产生局部流滑破坏,并溯源发展至前缘整体破坏,为典型的牵引式破坏模式。试验揭示处于临滑阶段坡体,其孔隙水压力、土压力变化呈现异常频繁的波动现象,可为滑坡预警预报提供一定参考依据。     

三峡库区巫山县塔坪H1滑坡变形机制

自2008 年三峡库区175 m试验性蓄水以来,受库水波动及强降雨影响,沿江库岸发生多起顺向古滑坡变形灾害。以三峡库区巫山县塔坪H1滑坡为例,结合近十年滑坡调查勘察与变形监测资料,分析了该滑坡蓄水后的变形特征。通过研究分析认为:（1）塔坪H1滑坡为顺层古岩质滑坡,岩体呈碎裂状,岩性主要为三叠系香溪组软硬相间的砂岩、泥页岩,岩层间夹多套软弱夹层,形成了多级滑带控制的滑坡变形。（2）滑坡变形分为3个区域,位移量变形最大的滑坡前缘消落带区域,最大水平位移已达80 cm,其次是处于缓慢变形状态的曲尺场镇前部区域和后部相对稳定的曲尺场镇区域。（3）数值模拟结果显示,库水位周期性波动影响着滑坡前缘涉水区域稳定性变化,短时强降雨沿岩体结构面入渗会加速滑坡中前部区域稳定性快速下降。在水位波动和短时强降雨的共同影响下,塔坪H1滑坡在每年汛期呈现缓慢变形。目前塔坪H1滑坡中前部处于持续变形阶段,亟需开展滑坡防治工程,提高滑坡稳定性,确保场镇安全。     

多元时间序列分析的滑坡演化阶段划分

滑坡的时间-位移曲线一般具有3个阶段特征,即初始变形阶段、等速变形阶段和加速变形阶段,不同演化阶段加速度具有不同的变化特点.目前往往是依据对加速度曲线特征的分析来人为划分演化阶段,缺少相应的理论支持和定量计算.针对上述问题,选取月降雨量、月库水位高程变化量对滑坡的累计位移建立多因素的时间序列预测模型.然后利用Chow分割点检验理论,以所建模型中F和LR统计量最大值点作为分割点对滑坡演化阶段进行划分.以新滩滑坡和三峡库区白水河滑坡为例,利用累计位移、降雨及库水位变化数据进行计算验证.结果表明,对多元时间序列模型进行Chow分割点检验可对滑坡的演化阶段进行准确划分,为滑坡的临滑预警预报提供重要判据.      

Understanding the triggering mechanism and possible kinematic evolution of a reactivated landslide in the Three Gorges Reservoir

More than 5000 landslides or potential landslides have been induced in the Three Gorges Reservoir (TGR) region since the impoundment in 2003, which have caused great damage and remain a huge threat to the dam and people living in the reservoir area. Understanding the deformation characteristics and failure mechanism of the landslides can be helpful in stability evaluation and landslide prediction. The primary aim of this study is to research the characteristics of the landslide motion and its relationships with environmental triggers, taking the Quchi landslide, a large, slow-moving, reactivated landslide in the TGR region, as an example. The instability clearly showed visible signs of movements since 2002, and after that, the slope has been experiencing persistent deformation. By combining 4 years of meteorological, hydrological data with displacement measurements from open fractures, deep boreholes, and surface points, as well as in situ observations, this paper reports the geological and geotechnical investigations performed to define the movement. The deformation is believed to be governed by reservoir water levels, while the precipitation has a minor effect. Seasonally, the slope movement has a very distinctive pattern with large deformation starting abruptly right after reservoir drawdown in June and lasting into late summer (September). Then there is a rapid transition to constant deformation (almost no displacement) as the reservoir level rises. The slope displacements appear to gradually increase every year, which suggests very high possibility of the large and overall failure of the slide. Both monitoring results and geomorphological observations have highlighted that the two active slide masses Q1 and Q2 would probably collapse in different kinematic evolution modes, i.e., the multistage failure and whole sliding motion.     

三峡树坪滑坡动力学的有限元模拟

三峡工程是迄今为止最大的水利工程,对库区滑坡灾害的监测和机制研究一直是重要的研究课题。本文利用Terra SAR-X的强度图进行相关计算,求解出2009年5月20日至8月5日期间三峡树坪滑坡的形变场。该形变场特征和树坪滑坡体的地形特征吻合甚好,位移大小、方向和三峡大学对滑坡体的野外观测结果基本吻合。以此高精度位移场为外部约束,结合野外观测资料对滑坡体介质力学性质进行分类并选取边界条件,利用有限元方法对滑坡活动进行动力学计算模拟。计算过程中对滑坡体的滑动面形状、因降雨引起材料参数变化和三峡水库水位等因素分别反演和调整,得出符合其变形和发展过程的滑坡动力学特征。发现软弱带的物性参数决定滑坡体总体滑动量,滑坡体的物性参数决定位移分布的峰值位置。在确定了滑坡动力学特征之后,进一步讨论降雨和库区水位下降对滑坡产生的贡献权重,得出降雨是树坪滑坡的决定因素。     

三峡库区藕塘滑坡变形特点及复活机制研究

为深入研究库区古滑坡变形特征及其复活机理,文章以三峡库区藕塘滑坡为研究对象,通过对钻孔、探槽及平硐等现场勘查资料和监测资料的深入分析,并结合数值模拟方法,探讨了藕塘滑坡的时-空变形特点及影响因素,并揭示其复活机制。电子自旋共振试验和现场勘查结果表明藕塘滑坡由三个次级滑体组成。监测数据显示:总体上,地表累计位移-时间曲线呈阶跃状变化,即雨季滑坡变形速率急剧加快,旱季则骤减;在空间上滑坡的变形速率随高程的增加而增加。库水和降雨是导致藕塘滑坡变形破坏的主要因素:滑坡下部区域变形主要受库水影响,而滑坡中、上部区域变形主要受降雨影响。数值模拟结果也进一步揭示了影响滑坡孔隙水压力响应的主控因素随滑坡高程的变化而变化。库水骤降使得坡体前部渗透压增大,同时强降雨使得坡体中部及上部孔隙水压力升高,二者共同作用下导致滑坡复活。此外库水位下降或降雨量增加,均会不同程度降低边坡的稳定性。以上结论对于指导实际工程及深化库区古滑坡的研究具有一定的理论意义,同时加强古滑坡的研究有助于丰富滑坡稳定性评价及预测预报方法,为古滑坡的治理提供一定的理论依据。     

Using an extreme learning machine to predict the displacement of step-like landslides in relation to controlling factors

In the evolution of landslides, besides the geological conditions, displacement depends on the variation of the controlling factors. Due to the periodic fluctuation of the reservoir water level and the precipitation, the shape of cumulative displacement-time curves of the colluvial landslides in the Three Gorges Reservoir follows a step function. The Baijiabao landslide in the Three Gorges region was selected as a case study. By analysing the response relationship between the landslide deformation, the rainfall, the reservoir water level and the groundwater level, an extreme learning machine was proposed in order to establish the landslide displacement prediction model in relation to controlling factors. The result demonstrated that the curves of the predicted and measured values were very similar, with a correlation coefficient of 0.984. They showed a distinctive step-like deformation characteristic, which underlined the role of the influencing factors in the displacement of the landslide. In relation to controlling factors, the proposed extreme learning machine (ELM) model showed a great ability to predict the Baijiabao landslide and is thus an effective displacement prediction method for colluvial landslides with step-like deformation in the Three Gorges Reservoir region.