共查询到20条相似文献，搜索用时 453 毫秒
1.
在库水位波动和降雨作用的共同影响下，库岸滑坡的变形规律往往更为复杂。以三峡库区麻柳林滑坡为例，基于野外调查、钻探编录、深部位移监测以及数值模拟等手段，分析了库水位波动和降雨作用下滑坡变形特征及演化规律。结果表明:麻柳林滑坡在粉质黏土层和块石层交界处发育一个次级滑带，目前该滑坡主要沿次级滑带运动，导致次级滑动的原因与坡体物质的差异性有关；Si(Sf)指标分析法揭示滑坡的滑带还未完全破坏，滑坡仍处于蠕变状态；根据三峡水库水位调度规律，将一个完整水文年划分为6个阶段，数值模拟结果表明滑坡在库水位缓慢下降阶段变形速率较小、在快速下降阶段和低水位阶段变形速率持续增大、在快速上升阶段和缓慢上升阶段以及高水位阶段变形速率则保持平稳。其中，降雨的直接影响和降雨导致库水位波动进而对滑坡变形造成的间接影响，使得麻柳林滑坡在低水位阶段的变形显著增加、稳定性最差，应加强该时段内滑坡的监测和预警。 相似文献
2.
《山地科学学报》2021,(10)
An accurate landslide displacement prediction is an important part of landslide warning system. Aiming at the dynamic characteristics of landslide evolution and the shortcomings of traditional static prediction models, this paper proposes a dynamic prediction model of landslide displacement based on singular spectrum analysis(SSA) and stack long short-term memory(SLSTM) network. The SSA is used to decompose the landslide accumulated displacement time series data into trend term and periodic term displacement subsequences. A cubic polynomial function is used to predict the trend term displacement subsequence, and the SLSTM neural network is used to predict the periodic term displacement subsequence. At the same time, the Bayesian optimization algorithm is used to determine that the SLSTM network input sequence length is 12 and the number of hidden layer nodes is 18. The SLSTM network is updated by adding predicted values to the training set to achieve dynamic displacement prediction. Finally, the accumulated landslide displacement is obtained by superimposing the predicted value of each displacement subsequence. The proposed model was verified on the Xintan landslide in Hubei Province, China. The results show that when predicting the displacement of the periodic term, the SLSTM network has higher prediction accuracy than the support vector machine(SVM) and auto regressive integrated moving average(ARIMA). The mean relative error(MRE) is reduced by 4.099% and 3.548% respectively, while the root mean square error(RMSE) is reduced by 5.830 mm and 3.854 mm respectively. It is concluded that the SLSTM network model can better simulate the dynamic characteristics of landslides. 相似文献
3.
地下水位预测对滑坡稳定性分析具有重要意义,三峡库区库岸滑坡地下水位时间序列在季节性强降雨和周期性库水位涨落等诸多因素影响下呈现混沌特征。在对地下水位序列进行相空间重构的基础上,采用饱和关联维数法和最大Lyapunov指数法对其混沌特征进行验证。再用预测性能优秀的最小二乘支持向量机(LSSVM)模型对其进行预测,并用粒子群算法优化选取LSSVM模型的参数,以克服LSSVM模型参数选取困难的缺点。以三峡库区三舟溪滑坡前缘STK-1水文孔日平均地下水位序列为例进行了混沌分析,分别运用粒子群优化的LSSVM模型(PSO-LSSVM)和BP神经网络模型对STK-1水文孔地下水位进行了预测。结果表明库岸滑坡地下水位序列存在混沌特征,PSO-LSSVM模型预测结果的均方根误差为0.193m,拟合优度为0.815,说明预测效果较理想,且PSO-LSSVM模型预测精度高于BP网络模型,具有较强的实用性。 相似文献
4.
以奉节新铺下二台滑坡为例, 基于GPS位移监测数据、裂缝数据、降雨量及库水位等多源数据, 总结分析了大型古滑坡的复活规律, 引入滑坡中长期预报模型, 实现了以季度或月份为时间单位的跨水文年滑坡位移预测, 并通过岩土体蠕变压缩模型, 验证了推移式滑坡后缘裂缝形成机理。结果表明: ①降雨是下二台滑坡变形的主导因素, 滑坡变形使得滑体产生裂缝并成为降雨入渗通道, 加剧了岩体破碎与软弱层软化, 降低了滑坡稳定性, 集中持续降雨可使滑坡失稳破坏; ②通过模型预测值与地表监测数据的比较, 将年降雨量作为滑坡中长期预报模型中的主控因素具有实际可操作性且有助于提高滑坡中长预报精度; ③推移式滑坡后缘裂缝由滑坡推移式位移和岩土体压缩形成, 引入蠕变压缩模型计算的裂缝宽度并和监测数据的比较说明, 蠕变压缩模型非常适合该类边坡, 同时应用岩土体蠕变压缩模型反推得到岩土体平均变形模量, 判断岩体破碎程度, 可以为滑坡稳定性分析及后续工程治理提供参考。 相似文献
5.
顾及降雨及库水位因素的滑坡时滞分析与预测——以三峡库区新铺滑坡为例 总被引：1，自引：0，他引：1
降雨及库水位涨落是引起库岸滑坡形变失稳的主要诱发因素,但滑坡位移速率对此类诱发因素的响应具有一定的滞后性,影响人类对滑坡所处运动状态的判断与预测。针对常规预测模型中未考虑时滞效应的问题,利用三峡库区新铺滑坡的GNSS位移监测数据、奉节气象站降雨数据以及三峡库区库水位涨落数据,通过对监测区内9个GNSS监测点的位移速率序列与降雨量、库水位高程序列进行时滞互相关分析,确定时滞参数,进而应用多变量灰色系统理论方法,建立了时滞GM(1,3)预测模型,并对滑坡位移速率进行预测验证。结果表明:三峡库区新铺滑坡位移速率与降雨量显著相关,对降雨量的响应滞后时间约为5 d,滑体中后部受降雨影响比前缘更明显;位移速率与库水位高程高度相关,对三峡库区库水位涨落的响应滞后时间约为31 d,滑坡前缘受库水位涨落影响更明显,且离长江越近,滞后时间越短;利用加入时滞参数的时滞GM(1,3)模型进行预测,模型拟合优度达到0.702,相比GM(1,1)模型和未顾及时滞因素的GM(1,3)模型,预测精度分别提升了53.8%和58.3%,平均绝对误差百分比分别降低了7.19%和7.47%,在滑坡位移速率预测及库岸滑坡防灾减灾领域具有一定的工程应用价值。 相似文献
6.
《山地科学学报》2020,17(1):191-202
Many landslides in reservoir areas continuously deform under cyclic water level fluctuations due to reservoir operations. In this paper,a landslide model, developed for a typical colluvial landslide in the Three Gorges Reservoir area, is used to study the effect of cyclic water level fluctuations on the landslide. Five cyclic water level fluctuations were implemented in the test, and the fluctuation rate in the last two fluctuations doubled over the first three fluctuations. The pore water pressure and lateral landslide profiles were obtained during the test. A measurement of the landslide soil loss was proposed to quantitatively evaluate the influence of water level fluctuations. The test results show that the first water level rising is most negative to the landslide among the five cycles. The fourth drawdown with a higher drawdown rate caused further large landslide deformation. An increase of the water level drawdown rate is much more unfavorable to the landslide than an increase of the water level rising rate. In addition, the landslide was found to have an adaptive ability to resist subsequent water level fluctuations after undergoing large deformation during a water level fluctuation. The landslide deformation and observations in the field were found to support the test results well. 相似文献
7.
采用传统ELM算法进行滑坡位移预测时，其网络输出权值由最小二乘估计得出，导致ELM抗差能力较差，从而造成网络训练参数不准确。为此，将M估计与ELM相结合，提出一种基于M估计的Robust-ELM滑坡变形预测方法。该方法利用加权最小二乘方法来取代最小二乘法计算ELM输出权值，以减少滑坡监测数据中粗差对ELM预测的干扰。分别以链子崖、古树屋滑坡体为例，将Robust-ELM进行了单维、多维粗差的抵御性验证。结果表明，该方法能够有效降低粗差对预测的影响，具有良好的抗差能力。 相似文献
8.
研究库水位波动和降雨影响下滑坡的位移变形特征并分析其破坏机制，对了解三峡库区滑坡的演化过程具有重要意义。以奉节曾家棚滑坡为例，基于GPS地表监测位移分析了滑坡在不同特征库水位运行阶段的变化规律，结合灰色关联度模型确定了滑坡不同部位的变形在不同阶段的主要控制因素，借助GEO-Studio软件模拟了曾家棚滑坡在历史降雨和库水位波动耦合作用下的稳定性变化，并与定量分析结果进行了交叉检验。结果表明:曾家棚滑坡的运动状态随时间变化，从缓慢蠕变状态进入阶跃变形状态。平面上，中东部坡体与西部坡体相比，运动更加强烈；剖面上，前缘变形早且变形量大。曾家棚滑坡变形失稳过程为初期蓄水启动了曾家棚古滑坡，前缘首先发生变形；降雨作为中后期主控因素，和库水位波动联合作用共同诱发了滑坡多次阶跃变形，使滑坡前中后部形成贯通裂缝；最终由二十年一遇的暴雨诱发滑坡发生整体破坏。 相似文献
9.
库岸滑坡体分布广泛,在库水位升降和降雨条件下极易失稳。三板溪水电站东岭信滑坡堆积体总方量2 000×104 m3,最大厚度150 m,2006年水电站蓄水后滑坡体开始出现大变形,每年雨季加剧。首先经野外地质勘察和十余年监测数据整理,探明了地质条件和变形规律;其次使用SEEP/W模块对不同库水位升降速率、2019年库水位结合实测降雨条件下的饱和-非饱和流进行模拟,并采用SLOPE/W分别计算不同时刻的稳定系数。分析认为东岭信为超深层滑坡,其变形过程深受库水位升降和降雨影响;滑坡体具有明显的滞水特征,渗流过程复杂;在库水位上升过程中稳定系数不断下降,而在库水位消落过程中稳定性逐渐增强;在库水位上升和强降雨量共同作用下稳定性下降很快,汛后10 d左右达到最低值,此时的稳定性最差。本研究可用于指导库水位升降和降雨条件下大型滑坡体稳定性评价。 相似文献
10.
动水驱动型滑坡状态识别能更有效地辅助分析滑坡形变规律, 实现滑坡状态的准确识别对深入展开动水驱动型滑坡状态研究具有重要意义。针对目前动水驱动型滑坡突变状态研究较少, 难以获得相关特征, 从而导致状态识别性能不佳的问题, 提出了一种应用于动水驱动型滑坡状态识别的生成对抗网络学习方法。本方法通过构建滑坡状态监测数据矩阵, 依据少量数据样本设计合理的生成器网络完成对滑坡状态的数据扩增并设计判别器网络实现扩增数据的筛选, 通过对抗生成网络实现对滑坡状态的分类, 达到滑坡状态识别的目的。以三峡库区白水河滑坡为研究对象, 将降雨、库水位、深部位移和地表位移等多源监测数据进行了规范化处理, 设计生成器网络和对抗器网络完成了对滑坡状态数据的扩增, 设计滑坡状态识别生成对抗网络完成了对滑坡状态的分类和识别。结果表明, 生成对抗网络对滑坡状态识别具有较高的准确率。研究结果证实本方法能够对目标区域内的动水驱动型滑坡状态进行准确识别和分类, 可直接应用于工程实际。 相似文献
11.
This paper proposes a WD-GA-LSSVM model for predicting the displacement of a deepseated landslide triggered by seasonal rainfall,in which wavelet denoising(WD)is used in displacement time series of landslide to eliminate the GPS observation noise in the original data,and genetic algorithm(GA)is applied to obtain optimal parameters of least squares support vector machines(LSSVM)model.The model is first trained and then evaluated by using data from a gentle dipping(~2°-5°)landslide triggered by seasonal rainfall in the southwest of China.Performance comparisons of WD-GA-LSSVM model with Back Propagation Neural Network(BPNN)model and LSSVM are presented,individually.The results indicate that the adoption of WD-GA-LSSVM model significantly improves the robustness and accuracy of the displacement prediction and it provides a powerful technique for predicting the displacement of a rainfall-triggered landslide. 相似文献
12.
三峡水库运行过程中库岸滑坡的变形演化往往滞后于库水位的变化, 表现出时间滞后效应, 而且随渗透系数和库水位波动速率的不同, 滞后效应亦不同。以三峡库区白家包滑坡为例, 通过现场调查、监测数据分析以及数值模拟的方法, 研究了滑坡在不同渗透系数k 和不同库水位下降速率v 条件下的变形滞后时间变化规律。研究表明: 滑体渗透系数一定时, 库水位下降速率越大, 地下水滞后越明显; 库水位下降速率一定时, 滑体渗透系数越大, 地下水下降越快。当滑体渗透系数一定时, 库水位下降速率越大, 滑坡的变形滞后时间越短; 滑体渗透系数k =0.85 m/d时不同库水位下降速率作用下滑坡的变形滞后时间为3.74~9 d, 当0.47＜v /k ＜1.18时, 0.24＜相对变形滞后时间＜1;当1.18＜v /k ＜2.38时, 0＜相对变形滞后时间＜0.24。当库水位下降速率一定时, 滑体渗透系数越大, 滑坡变形滞后时间越短, 不同库水位下降速率下滑坡变形滞后时间随渗透系数的变化规律大致相同; 库水位下降速率v =1.8 m/d时不同滑体渗透系数下滑坡的变形滞后时间为1.7~8 d, 当0.52＜v /k ＜0.84时, 0＜相对变形滞后时间＜0.16;当0.84＜v /k ＜2.12时, 0.16＜相对变形滞后时间＜0.43;当2.12＜v /k ＜9时, 0.43＜相对变形滞后时间＜1。研究成果对水库滑坡预测预警具有较强的应用价值。 相似文献
13.
The water level in the Three Gorges Dam reservoir is expected to change between the elevations of 145 m and 175 m, as a function
of the flood control implementation and the intensity of the annual flood. As a matter of fact, the hydraulical and mechanical
loadings, related to the water level modifications, will result in alterations in the slope stability conditions. The town
of Badong (Hubei), of 20 000 inhabitants, is one of the towns which was submerged by the impoundment of the reservoir. As
a consequence, the new town of Badong was constructed on a nearby site which appeared to be partly an unstable site. A part
of this site corresponds to an old landslide, the Huangtupo landslide, the base of which had to be submerged by the water
of the reservoir. The analysis of the Huangtupo landslide, taking into account various events scenarios, drainage and reinforcement
measures and monitoring devices, allows to illustrate the general process implemented all along the reservoir in order to
mitigate the landslide hazard. 相似文献
14.
针对2016年5月发生于秭归县西北部的谭家湾滑坡,结合卫星遥感影像、现场勘查资料以及历史资料等多源数据,初步明确了滑坡的影响区域、特征及发生时序;综合采用钻探、槽探、物探等手段,开展室内外相关实验,明确了滑坡区的地层特性以及岩土体物理力学性质指标,通过分析该区裂缝位移及GPS数据,对该边坡的变形机制进行了探讨,并对该区稳定性进行了评价。结果表明:①谭家湾滑坡属于不规则"圈椅形"中型松散层的水库下降型滑坡,滑坡区的地表形态、地质构造及岩性等因素决定了滑坡的形成和发育,库水位和降雨的共同作用激励了滑坡的变形;②滑坡根据时序共分为3级滑体,总体呈现多次、多层、相互影响的演化特点,第三级滑体具有牵引式特征;③滑坡体内地下水位随库水位下降而下降,但下降速率缓于库水位,随之坡体内水力梯度和渗透力显著变大,此时碰到强降雨,将会导致坡体地下水赋存,岩土体软化,加剧滑坡变形,须施加必要的防护措施。④稳定性分析表明,该滑坡现处于临界稳定状态,一旦发生降雨和库水位变化,局部段可能发生失稳滑动。 相似文献
15.
滑坡灾害应急处置能力是地质灾害减灾防灾的重要方面。目前,基于滑坡灾害预测和预警分级成果,系统性的应急措施分类研究还鲜有展开,因此,以三峡库区白水河滑坡为例,运用时间序列加法模型将滑坡累计位移分解为趋势项位移与周期项位移,并分别应用多项式拟合及自回归（AR）模型对2个分量进行预测,在此结果上采用聚类分析方法将滑坡变形分为匀速变形与加速变形阶段,综合判断滑坡灾害预警等级,开展了针对滑坡预警分级的应急措施研究。结果表明:白水河滑坡预警等级主要为蓝色和黄色2种类型,对处于不同的预警等级下的滑坡,可根据滑坡变形特征快速决策,基于滑坡灾害预测和预警分级结果能更有效地指导滑坡应急处置。 相似文献
16.
Liang Qiao Xing-min Meng Guan Chen Yi Zhang Peng Guo Run-qiang Zeng Ya-jun Li 《山地科学学报》2017,14(6):1113-1123
A colluvial landslide in a debris flow valley is a typical phenomena and is easily influenced by rainfall. The direct destructiveness of this kind of landslide is small, however, if failure occurs the resulting blocking of the channel may lead to a series of magnified secondary hazards. For this reason it is important to investigate the potential response of this type of landslide to rainfall. In the present paper, the Goulingping landslide, one of the colluvial landslides in the Goulingping valley in the middle of the Bailong River catchment in Gansu Province, China, was chosen for the study. Electrical Resistivity Tomography (ERT), Terrestrial Laser Scanning (TLS), together with traditional monitoring methods, were used to monitor changes in water content and the deformation of the landslide caused by rainfall. ERT was used to detect changes in soil water content induced by rainfall. The most significant findings were as follows:(1) the water content in the centralupper part (0~41 m) of the landslide was greater than in the central-front part (41~84 m) and (2) there was a relatively high resistivity zone at depth within the sliding zone. The deformation characteristics at the surface of the landslide were monitored by TLS and the results revealed that rainstorms caused three types of deformation and failure: (1) gully erosion at the slope surface; (2) shallow sliding failure; (3) and slope foot erosion. Subsequent monitoring of continuous changes in pore-water pressure, soil pressure and displacement (using traditional methods) indicated that long duration light rainfall (average 2.22 mm/d) caused the entire landslide to enter a state of creeping deformation at the beginning of the rainy season. Shear-induced dilation occurred for the fast sliding (30.09 mm/d) during the critical failure sub-phase (EF). Pore-water pressure in the sliding zone was affected by rainfall. In addition, the sliding L1 parts of the landslide exerted a discontinuous pressure on the L2 part. Through the monitoring and analysis, we conclude that this kind of landslide may have large deformation at the beginning and the late of the rainy season. 相似文献
17.
由于具有类似的工程地质和水文地质条件, 在高度相关的降雨作用下, 同一个区域中的降雨诱发浅层斜坡失稳灾害常成群出现。在区域尺度预测浅层斜坡失稳灾害对滑坡灾害的防灾减灾工作具有重要的意义。为此, 提出了一种基于力学原理的降雨诱发浅层斜坡失稳灾害预测新模型RARIL。该模型采用修正Green-Ampt模型进行降雨入渗分析, 采用无限体边坡模型进行安全系数计算, 利用可靠度原理考虑区域斜坡稳定性分析中的参数不确定性。该模型具有可考虑降雨诱发浅层斜坡的失稳力学机理、可考虑区域内斜坡土体参数不确定性, 以及计算效率高、易于在GIS平台上实现等优点。案例分析表明, RARIL模型较为准确地预测了2010年8月12日11∶00至2010年8月14日9∶00期间强降雨在四川省汶川县映秀镇附近的303省道K0-K20段沿线区域引发的滑坡灾害, 研究结果证明RARIL模型在预测降雨诱发区域斜坡失稳灾害方面有很好的应用前景。 相似文献
18.
李晓斌 《大地测量与地球动力学》2022,42(6):588-593
为准确掌握库区滑坡变形潜势,在变形监测成果统计基础上,首先利用极限位移准则开展滑坡现状变形潜势分析;然后以相关向量机为理论基础,通过优化处理保证其参数最优性,构建滑坡变形预测模型,并以预测结果开展滑坡变形潜势的发展趋势评价;最后结合两种分析结果,实现滑坡综合变形潜势分析。结果表明,不同监测点的现状变形潜势状态存在一定差异,由不利原则可知,现状变形潜势等级为Ⅳ级,潜势程度属严重状态;滑坡变形仍会进一步增加,变形潜势趋于不利方向发展。综合两种分析结果可知,滑坡变形潜势处于不利状态,后期失稳可能性较大,应加强灾害防治,避免成灾损失。 相似文献
19.
?????????????????????????????Sigmoidal??Sine??Hardlim??????????????????????????????????????????????????????б??????????????????????????????????????????????????????????????????????磬?????Sigmoidal???????????????????????? 相似文献
20.
Based on the principle of 3D particle flow code, a numerical landslide run-out model is presented to simulate the failure process of the Zhenggang landslide (in southwestern China) under the effect of water after a rainfall. The relationship between the micro-mechanical parameters and the macro-shear strength of the grain material is determined through numerical calibrations. Then the rainfall effect is considered in numerical simulations and rain-induced sliding processes are performed, which help us to discuss the mechanism of deformation and failure of this landslide together with field observations. It shows the Zhenggang landslide would most likely be activated in Zone I and would gain momentum in Zone II. In order to prevent the potential disaster, a tailing dam is advised to be designed about 175 m downstream from the current landslide boundary of Zone II. Verified by field observations, the presented landslide model can reflect the failure mechanism after rainfall. It can also provide a method to predict the potential disaster and draft disaster prevention measures. 相似文献