Risk management study on impulse waves generated by Hongyanzi landslide in Three Gorges Reservoir of China on June 24, 2015

On June 24, 2015, Hongyanzi slope located in Wushan County of the Three Gorges Reservoir collapsed, generating 5–6-m-high impulse waves, which overturned 13 boats, killed 2 persons, and injured 4 persons. It is the second incident of landslide-generated impulse waves since the 175-m experimental impoundment in 2008. The emergency investigation shows that Hongyanzi landslide is a bedding soil landslide with a volume of 23?×?10⁴ m³ induced by a series of triggering factors such as rainfall, flooding upstream, and reservoir drawdown. The nonlinear Boussinesq water wave model is used to reproduce the impulse waves generated by the landslide of June 24th. The numerical simulation results suggest that the wave propagation process was influenced by the T-shaped geomorphic conditions of river valley, and the coastal areas in the county seat were the major wave-affected areas, which is opposite to the landslide. The numerical wave process accord well with the observed incident, and the investigation values were in good agreement with the calculated values. Moreover, the worst-case scenario of the 7?×?10⁴ m³ deformation mass beside Hongyanzi landslide is potential to generate impulse waves, which was predicted with the same numerical model. This adjacent deformation mass will probably generate impulse waves with maximum height and run-up of 2.2 and 2.0 m, respectively, and only a very few areas in the water course had waves rising to a height of 1 m or above. The research results provide a technical basis for emergency disposal to Hongyanzi landslide and navigation restriction in Wushan waterway. More importantly, it pushes the risk management of the navigation based on the impulse wave generated by landslide. It is advised that the Three Gorges Reservoir and other reservoirs around the world should put more efforts in performing special surveys and studies on the potential hazards associated with landslide-generated impulse waves.     

Numerical modeling of the June 24, 2015, Hongyanzi landslide generated impulse waves in Three Gorges Reservoir,China

Subaerial landslides falling into confined water bodies often generate impulsive waves. Damaging landslide tsunamis in Three Gorges Reservoir, China, have struck several times in the last 15 years. On June 24, 2015, a 23?×?10⁴ m³ slope failure occurred on the east bank of the Daning River opposite Wushan Town. The sliding mass intruded into the Three Gorges Reservoir and initiated a reservoir tsunami that resulted in two deaths and significant damage to shipping facilities. A post-event survey revealed the landslide geometry and wave run-up distribution, while an eyewitness video captured most of the landslide motion. Employing these firm constraints, we applied the Tsunami Squares method to simulate the 2015 Hongyanzi landslide and tsunami. The simulation revealed that the landslide experienced a progressive failure in the first few seconds and impacted the water with a maximum velocity of ~?16 m/s. The initial wave propagated to the opposite shore in an arch shape, and the water surface reached a maximum amplitude of ~?11 m near the landslide. Wave amplitude-time curves at four points on the river cross section show that the initial wave reached Wushan town in about 50 s with an average wave velocity of ~?30 m/s. The maximum wave run-ups on the shoreline opposite the landslide are around 6 m and attenuate to less than 1 m beyond 2-km distance. The landslide simulation matches the observed geological profile and the eyewitness video, and the numerical results coincide with the observed wave run-up heights. Nearly 80% of landslide energy is lost due to frictional resistances, but the remaining fraction imparted to the tsunami carried catastrophic consequences to a large region. The numerical results emphasize the efficiency and accuracy of Tsunami Squares method for a “Quick Look” simulation of a potential landslide.     

Deformation and mechanism of landslide influenced by the effects of reservoir water and rainfall, Three Gorges, China

Since the impoundment of the Three Gorges Reservoir in June 2003, numerous preexisting landslides have been reactivated. This paper seeks to find the factors influencing landslide deformation and the relationship between displacement and fluctuation of the reservoir water level, while the displacement and the intensity of rainfall based on monitoring data; 6 years of monitoring were carried out on the Shiliushubao landslide, a old landslide, consisting of a deep-seated main block and two shallow blocks, with a volume of 1,180 × 10⁴ m³ and located on the left bank of the Yangtze River, 66 km upstream of the Three Gorges dam. This landslide was reactivated by the impoundment and since then the landslide body has been experiencing persistent deformation with an observed maximum cumulative displacement of 8,598.5 mm up to December 2009. Based on the monitoring data, we analyzed the relationship between the fluctuation of the reservoir water level and displacement, rainfall and displacement, and found that the rainfall is the major factor influencing deformation for two shallow blocks and the displacement has a positive correlation with the variation of rainfall intensity. The fluctuation of the reservoir water level is the primary factor for main block, and the deformation rate has a negative correlation with the variation of reservoir water level, declined with the rise of the water level and increased with the drawdown of the water level.     

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.     

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。     

库水位骤降时的滑坡稳定性评价方法研究

三峡水库蓄水及水位波动,将极大地改变滑坡体内的水文地质条件,库水位骤降和暴雨入渗是导致滑坡的主要因素。库水位骤降时的滑坡稳定性评价是滑坡防治中的一个难题。根据三峡水库水位调控方案和库区滑坡地下水作用的力学模式,利用有限元模拟库水位从175 m骤降至145 m时的滑坡暂态渗流场。建立了渗透力作用下滑坡稳定性评价的不平衡推力法。研究表明：滑坡的渗透系数和库水位下降速度是影响滑坡稳定性的主要因素,当库区堆积层滑坡渗透系数小于0.864 m/d,库水位发生骤降为2 m/d。库水位骤降时滑坡稳定性降到最小的水位通常在175 m水位以下10～20 m处。其研究为库区 175 m水位滑坡治理提供了科学依据。     

库水下降作用下滑坡动态变形机理分析以三峡库区白水河滑坡为例

在每年的库水位下降期间,三峡库区的许多滑坡都出现了较大变形。为了深入研究库水下降作用下滑坡的动态变形机理,评价和预测此类滑坡的稳定性及发展趋势,本文以白水河滑坡为例,在现场地质调查和详细地质勘查的基础上,充分利用十多年监测数据,分析其变形特征、失稳机理、影响因素及稳定性,预测了其变形发展趋势。研究结果表明在水库水位下降的过程中,由于滑坡岩土体渗透性能较差,地下水来不及及时排出,滞后于水库水位的下降,滑坡受到了坡体内地下水向外的渗透动水压力作用,从而使得滑坡稳定性降低。另外库水位下降速度越快,滑坡的位移速率也越大,表现出阶跃型动态变形特征。     

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。     

结构复杂滑坡活动对库水位变化的响应特征——以三峡库区柴湾滑坡为例

柴湾滑坡是三峡库区结构复杂的大型老滑坡之一,三峡水库蓄水后,该滑坡出现明显复活迹象。本文基于滑坡结构和2007-2015年监测数据,分析了该滑坡活动对库水位变化的响应特征;采用数值模拟手段分析了库水位变化时滑体内渗流场及孔隙水压力变化特征。研究发现,该滑坡在平、剖面上分别呈现牵引式分块与浅、中层分层的缓慢活动特征;当库水位降速>0 8 m/d时,滑坡活动呈现滞后的台阶式加剧趋势;越接近地表,滑坡活动对库水位变化愈敏感。柴湾滑坡活动特征受其复杂结构控制,滑坡中前部地下水与库水密切的水力联系以及中层、深层滑体良好的渗透性决定了滑坡的分块和分层活动特征。库水位上升时透水性较强滑体内的扬压力和库水位下降时透水性较弱滑体内的动水压力是造成滑坡分块分层活动的内在动力。     

降雨及库水位联合作用下秭归八字门滑坡稳定性预测

针对三峡库区库水位调控方案和极端降雨情况,对秭归县八字门滑坡稳定性分析设置了10种计算工况,采用SEEP/W软件模拟该滑坡在降雨入渗及库水位联合作用下的暂态渗流场,并利用SLOPE/W软件,将暂态孔隙水压力分布用于该滑坡的极限平衡分析中,确定不同工况下（不同降雨强度）的滑坡稳定性系数,据此采用降雨量对该滑坡进行失稳预测。研究认为：150 mm/d以上的降雨量对该滑坡影响较大,降雨入渗具有滞后性;在相同的降雨量情况下,1 d的降雨强度比5 d的连续降雨对滑坡体的稳定性影响更明显;在水位从175 m降至145 m的过程中,临界雨量为100 mm/d时,滑坡就可能失稳;水位从145 m升至175 m的过程中和175 mm稳定水位时,当临界雨量为200 mm/d时,滑坡才可能失稳,即水位骤降过程中滑坡失稳概率大。不同工况下的滑坡土体含水率分析结果表明,降雨影响的主要是上部土体,下部土体含水率受控于地下水位,即降雨更容易引起浅层滑坡与局部滑坡     

The July 1, 2017 Wangjiawan landslide in Ningxiang County,China

Many landslides were triggered by heavy rainfall from 29 June to 1 July 2017 in Ningxiang County, Hunan Province, China. A field investigation into one of the landslides, known as the Wangjiawan landslide, was undertaken on July 3, 2017, to understand the landslide mechanisms and the factors that triggered the event. The landslide is a translational and rotational slide that degraded downslope to an earth flow. It occurred on a steeply dipping mud-rich slate intercalation. Field investigation shows that the landslide had a movement rate of more than 25 m/s and had been triggered by up to 338 mm of continuous rainfall over 2 days. The landslide was fast-moving because it occurred on a steep slope and showed a rapid reduction in shear strength. The landslide resulted in nine fatalities and 19 injuries, most during initial rescue efforts. To mitigate a possible secondary landslide disaster, later emergency measures including evacuation of the survivors, setting up warning signs, and covering landslide cracks with plastic sheeting were adopted.     

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。     

三峡库区提升库水位下降速率条件下沟边上滑坡稳定性评价

三峡库区对非汛期库水位下降速率（0.6 m/d）的严格控制,预防了近千处涉水库岸滑坡大规模下滑入江,但控制消落期库水位下降速率在某种程度上却限制了防洪和蓄水发电效益的发挥,本文主要通过研究在非汛期时候,增加库水位下落速率是否具有可行性,使用Geo-studio中的SEEP/W、SLOPE两个模块对沟边上滑坡进行渗流分析和稳定性分析评价,以计算结果来确定库水位消落期的水位下降速率,对库区调控水位下降速率的调整有重大现实意义和科学价值。     

Field monitoring of groundwater responses to heavy rainfalls and the early warning of the Kualiangzi landslide in Sichuan Basin,southwestern China

The Kualiangzi landslide was triggered by heavy rainfalls in the “red beds” area of Sichuan Basin in southwestern China. Differing from other bedrock landslides, the movement of the Kualiangzi landslide was controlled by the subvertical cracks and a subhorizontal bedding plane (dip angle < 10°). The ingress of rainwater in the cracks formed a unique groundwater environment in the slope. Field measurement for rainfall, groundwater movement, and slope displacement has been made for the Kualiangzi landslide since 2013. The field monitoring system consists of two rainfall gauges, seven piezometers, five water-level gauges, and two GPS data loggers. The equipments are embedded near a longitudinal section of the landslide, where severe deformation has been observed in the past 3 years. The groundwater responses to four heavy rainfall events were analyzed between June 16 and July 24 in 2013 coincided with the flood season in Sichuan. Results showed that both of the water level and the pore-water pressure increased after each rainfall event with delay in the response time with respect to the precipitation. The maximum time lag reached 35 h occurred in a heavy rainfall event with cumulative precipitation of 127 mm; such lag effect was significantly weakened in the subsequent heavy rainfall events. In each presented rainfall event, longer infiltration period in the bedrock in the upper slope increased the response time of groundwater, compared to that of in the gravels in the lower slope. A translational landslide conceptual model was built for the Kualiangzi landslide, and the time lag was attributed to the gradual formation of the uplift pressure on the slip surface and the softening of soils at the slip surface. Another important observation is the effect on the slope movement which was caused by the water level (H _w) in the transverse tension trough developed at the rear edge of the landslide. Significant negative correlation was found for H _w and the slope stability factor (F _s), in particular for the last two heavy rainfall events, of which the drastic increase of water level caused significant deterioration in the slope stability. The rapid drop (Δ?=?22.5 kPa) of pore-water pressure in the deep bedrock within 1 h and the large increase (Δ?=?87.3 mm) of surficial displacement were both monitored in the same period. In the end, a four-level early warning system is established through utilizing H _w and the displacement rate D _r as the warning indicators. When the large deformation occurred in flood season, the habitants at the leading edge of the landslide can be evacuated in time.     

关键影响因子作用下三峡库区堆积层滑坡分布规律及变形破坏响应特征

三峡库区崩滑地质灾害频发,堆积层滑坡是最常见的滑坡类型。在分析三峡库区145处库岸堆积层滑坡资料基础上,选取地形地貌、地质岩性和斜坡构造作为控制因素、降水和库水波动作为主要诱发因素,探究堆积层滑坡在上述关键影响因子下的分布发育规律及变形破坏响应特征,阐明内在机理,结果表明:(1)受区域地质构造和基岩地层岩性显著控制,滑坡发育频次和规模沿长江存在显著空间差异性;(2)砂页岩夹煤层岩组(SC)和泥灰岩与砂泥岩互层岩组(MSM)对库区堆积层滑坡危害最大,软岩、“软-硬”互层二元结构和水-岩(土)相互作用是主导滑坡发育的主要影响因素;(3)大多数滑坡涉水,主要发育在10°~30°斜坡上,前缘高程集中在100~175 m,受库水波动影响严重,岸别和斜坡结构对堆积层滑坡发育没有明显控制作用;(4)库区滑坡主要由降雨-库水下降联合诱发滑体前缘滑移-拉裂,引发牵引式滑坡,降雨与库水波动各自对滑体的影响格局和程度存在明显差异。以期研究成果为有针对性的库区滑坡总体防治提供一定的科学指导。     

The determination of statistical and deterministic hydrological landslide-triggering thresholds

 Hydrological landslide-triggering thresholds separate combinations of daily and antecedent rainfall or of rainfall intensity and duration that triggered landslides from those that failed to trigger landslides. They are required for the development of landslide early warning systems. When a large data set on rainfall and landslide occurrence is available, hydrological triggering thresholds are determined in a statistical way. When the data on landslide occurrence is limited, deterministic models have to be used. For shallow landslides directly triggered by percolating rainfall, triggering thresholds can be established by means of one-dimensional hydrological models linked to the infinite slope model. In the case of relatively deep landslides located in topographic hollows and triggered by a slow accumulation of water at the soil-bedrock contact, simple correlations between landslide occurrence and rainfall can no longer be established. Therefore real-time failure probabilities have to be determined using hydrological catchment models in combination with the infinite slope model. Received: 15 October 1997 · Accepted: 25 June 1997     

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。     

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。     

地形坡度对鄂渝地区水库型堆积层滑坡贡献率研究

堆积层滑坡是库区常见的滑坡类型之一,而地形坡度是滑坡发育的重要内因,研究地形坡度与堆积层滑坡发生概率之间的关系对水库型堆积层滑坡的危险性评价具有重要意义。以三峡库区及丹江口库区的139处堆积层滑坡为例,首先,将滑坡地形坡度以每隔5划分为一个区间,总共分为7个区间; 在此基础上,采用贡献率方法,定量研究了地形坡度分别对滑坡数量、面积、体积的贡献率; 最后,通过迭加统计,得到了不同坡度区间对滑坡发生的综合贡献率。结果表明, 15～25的地形坡度对水库型堆积层滑坡的贡献率最高, 10～15及25～30的地形坡度对水库型堆积层滑坡的贡献率中等,小于10及大于30的地形坡度对水库型堆积层滑坡的贡献率最小。研究结果可为具有类似地质背景的水库型堆积层滑坡危险性评估及防治规划提供参考依据。