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1.
《地学前缘(英文版)》2023,14(1):101490
Rainfall infiltration poses a disastrous threat to the slope stability in many regions around the world. This paper proposes an extreme gradient boosting (XGBoost)-based stochastic analysis framework to estimate the rainfall-induced slope failure probability. An unsaturated slope under rainfall infiltration in spatially varying soils is selected in this study to investigate the influences of the spatial variability of soil properties (including effective cohesion c′, effective friction angle φ′ and saturated hydraulic conductivity ks), as well as rainfall intensity and rainfall pattern on the slope failure probability. Results show that the proposed framework in this study is capable of computing the failure probability with accuracy and high efficiency. The spatial variability of ks cannot be overlooked in the reliability analysis. Otherwise, the rainfall-induced slope failure probability will be underestimated. It is found that the rainfall intensity and rainfall pattern have significant effect on the probability of failure. Moreover, the failure probabilities under various rainfall intensities and patterns can be easily obtained with the aid of the proposed framework, which can provide timely guidance for the landslide emergency management departments. 相似文献
2.
A key issue in assessment of rainfall-induced slope failure is a reliable evaluation of pore water pressure distribution and its variations during rainstorm, which in turn requires accurate estimation of soil hydraulic parameters. In this study, the uncertainties of soil hydraulic parameters and their effects on slope stability prediction are evaluated, within the Bayesian framework, using the field measured temporal pore-water pressure data. The probabilistic back analysis and parameter uncertainty estimation is conducted using the Markov Chain Monte Carlo simulation. A case study of a natural terrain site is presented to illustrate the proposed method. The 95% total uncertainty bounds for the calibration period are relatively narrow, indicating an overall good performance of the infiltration model for the calibration period. The posterior uncertainty bounds of slope safety factors are much narrower than the prior ones, implying that the reduction of uncertainty in soil hydraulic parameters significantly reduces the uncertainty of slope stability. 相似文献
3.
Abderraouf El Ouazzani Taibi Amro Elfeki Guoping Zhang 《Arabian Journal of Geosciences》2011,4(5-6):1005-1018
The research presented in this paper focuses on the application of a newly developed physically based watershed modeling approach, which is called representative elementary watershed approach. The study stressed the effects of uncertainty of input parameters on the watershed responses (i.e., simulated discharges). The approach was applied to the Zwalm catchment, which is an agriculture-dominated watershed with a drainage area of 114 km2 located in East Flanders, Belgium. Uncertainty analysis of the model parameters is limited to the saturated hydraulic conductivity because of its high influence on the watershed hydrologic behavior and availability of the data. The assessment of output uncertainty is performed using the Monte Carlo method. The ensemble statistical watershed responses and their uncertainties are calculated and compared with measurements. The results show that the measured discharges fall within the 95% confidence interval of the modeled discharge. This provides the uncertainty bounds of the discharges that account for the uncertainty in saturated hydraulic conductivity. The methodology can be extended to address other uncertain parameters as far as the probability density function of the parameter is defined. 相似文献
4.
Renato Macciotta C. Derek Martin Norbert R. Morgenstern David M. Cruden 《Landslides》2016,13(4):765-785
The benefits of quantitative risk assessments for landslide management have been discussed and illustrated in several publications. However, there still are some challenges in its application for low-probability, high-magnitude events. These challenges are associated with the difficulties in populating our models for risk calculations, which largely require the input of expert opinion. This paper presents a quantitative risk assessment to a very slow moving rock slope within a dam reservoir in the Province of British Columbia, Canada. The assessment is focused on the risk to the population in the vicinity of the dam and the populated areas downstream. Expert opinions quantified the slope failure probabilities in the order of 10?3 to 10?1 per year for the smallest failure scenario considered and less than 10?6 for a failure of the entire slope. However, these estimations are associated with high levels of uncertainty. Our approach starts with the calculation and assessment of the magnitude and probability of the potential slope failure consequences, minimizing the uncertainties associated with estimated slope failure probabilities. Then, these consequences and failure probabilities are combined to obtain a measure of risk. The uncertainty associated with the slope failure probabilities is managed by the estimation of plausible ranges for these. The calculated risk levels are then presented as ranges of values and assessed against adopted evaluation criteria. The consequence and risk assessment of the rock slope suggest that the risk to the population exposed in the vicinity of the dam and populated areas downstream is under adequate control. The probability of large consequence scenarios is extremely low, in the order of 10?7 chance of an event causing more than 100 fatalities. We propose an observational technique to assess changes in risk levels and decide when to update the risk management approach or deploy emergency measures. The technique is focused on the detection of changes in the slope deformation patterns that would indicate an increase in the potential failure volumes or an imminent failure. It can be considered an extension to the current early warning system in place, easy to implement and enhanced with the strength of the comprehensive analysis required for a quantitative risk assessment. 相似文献
5.
考虑参数空间变异性的非饱和土坡可靠度分析 总被引：2，自引：0，他引：2
在考虑多个土体参数空间变异性的基础上,提出了基于拉丁超立方抽样的非饱和土坡稳定可靠度分析的非侵入式随机有限元法。利用Hermite随机多项式展开拟合边坡安全系数与输入参数间的隐式函数关系,采用拉丁超立方抽样技术产生输入参数样本点,通过Karhunen-Loève展开方法离散土体渗透系数、有效黏聚力和内摩擦角随机场,并编写了计算程序NISFEM-KL-LHS。研究了该方法在稳定渗流条件下非饱和土坡可靠度分析中的应用。结果表明：非侵入式随机有限元法为考虑多个土体参数空间变异性的非饱和土坡可靠度问题提供了一种有效的分析工具。土体渗透系数空间变异性和坡面降雨强度对边坡地下水位和最危险滑动面位置均有明显的影响。当降雨强度与饱和渗透系数的比值大于0.01时,边坡失效概率急剧增加。当土体参数变异性或者参数间负相关性较大时,忽略土体参数空间变异性会明显高估边坡失效概率。 相似文献
6.
Integration of Tracer Test Data to Refine Geostatistical Hydraulic Conductivity Fields Using Sequential Self-Calibration Method 总被引：3，自引：0，他引：3
On the basis of local measurements of hydraulic conductivity,geostatistical methods have been found to be useful in heterogeneity characterization of a hydraulic conductivity field on a regional scale. However,the methods are not suited to directly integrate dynamic production data,such as,hydraulic head and solute concentration,into the study of conductivity distribution. These data,which record the flow and transport processes in the medium,are closely related to the spatial distribution of hydraulic conductivity. In this study,a three-dimensional gradient-based inverse method-the sequential self-calibration (SSC) method-is developed to calibrate a hydraulic conductivity field,initially generated by a geostatistical simulation method,conditioned on tracer test results. The SSC method can honor both local hydraulic conductivity measurements and tracer test data. The mismatch between the simulated hydraulic conductivity field and the reference true one,measured by its mean square error (MSE),is reduced through the SSC conditional study. In comparison with the unconditional results,the SSC conditional study creates the mean breakthrough curve much closer to the reference true curve,and significantly reduces the prediction uncertainty of the solute transport in the observed locations. Further,the reduction of uncertainty is spatially dependent,which indicates that good locations,geological structure,and boundary conditions will affect the efficiency of the SSC study results. 相似文献
7.
将大规模渗流有限元计算与随机响应面法相结合,对双江口心墙堆石坝进行渗透稳定可靠性分析。在基于随机响应面法的可靠度分析框架内,堆石坝稳定渗流有限元计算过程和可靠度分析过程分开独立进行,通过对心墙渗透坡降较大区域的节点建立统一的渗透稳定功能函数,采用渗流有限元分析方法和随机响应面法,计算出该区域每个节点处的渗透破坏失效概率,并将最大失效概率作为心墙的失效概率。最后,分析了心墙渗透系数、覆盖层渗透系数、上游水位与心墙具有最大失效概率节点处渗透坡降的相关关系,以及心墙渗透系数和上游水位的变异性对心墙渗透破坏失效概率的影响。计算结果表明,随机响应面法3阶Hermite展开就能够保证良好的计算精度,且计算耗时较小;双江口堆石坝心墙具有最大失效概率节点处的渗透坡降与上游水位密切相关,而与心墙本身的渗透系数呈弱负相关关系,与覆盖层渗透系数的相关性不显著;随着上游水位变异性的增大,心墙失效概率急剧增大,而这种效应对于心墙渗透系数并不明显。研究成果为随机响应面法在实际工程中的应用奠定了一定的基础。 相似文献
8.
边坡失稳是涉及土体大变形的动态演化过程,该过程往往决定了滑坡失事后果。传统的边坡稳定分析方法如极限平衡方法与有限元方法难以模拟边坡失稳演化过程,尤其是失稳后的土体变形破坏过程。边坡失稳受到多重不确定性因素影响,其中一个重要因素是土体参数的空间分布不均匀性。在考虑土体参数的空间不均匀分布情况下,本文采用一种随机极限平衡-物质点法研究边坡不同破坏模式的动态演化过程,同时利用极限平衡方法简单、高效的优点和物质点方法模拟土体大变形破坏的能力。以一个两层不排水土坡算例为例,识别了4种不同的边坡破坏模式（即浅层、中层、深层和渐进）,研究了它们的演化过程与土体参数的空间分布之间的关系。结果表明边坡的破坏模式演化过程与土体参数的空间分布密切相关,强调了岩土工程勘察信息对充分表征土体参数空间变异性的重要作用。 相似文献
9.
Ji Yuan Iason Papaioannou Daniel Straub 《Georisk: Assessment and Management of Risk for Engineered Systems and Geohazards》2019,13(1):20-33
Rainfall-induced landslides occur during or immediately after rainfall events in which the pore water pressure builds up, leading to shallow slope failure. Thereby, low permeability layers result in high gradients in pore water pressure. The spatial variability of the soil permeability influences the probability such low permeability layers, and hence the probability of slope failure. In this paper, we investigate the influence of the vertical variability of soil permeability on the slope reliability, accounting for the randomness of rainfall processes. We model the saturated hydraulic conductivity of the soil with a one-dimensional random field. The random rainfall events are characterised by their duration and intensity and are modelled through self-similar random processes. The transient infiltration process is represented by Richards equation, which is evaluated numerically. The reliability analysis of the infinite slope is based on the factor of safety concept for evaluating slope stability. To cope with the large number of random variables arising from the discretization of the random field and the rainfall process, we evaluate the slope reliability through Subset Simulation, which is an adaptive Monte Carlo method known to be especially efficient for reliability analysis of such high-dimensional problems. Numerical investigations show higher probability of slope failure with increased spatial variability of the saturated hydraulic conductivity and with more uniform rainfall patterns. 相似文献
10.
当土壤转换函数应用于土壤水力性质估计时,对于预测值的不确定性往往容易被忽视。为了有针对性地提出减少这种不确定性的方法和措施,提高土壤转换函数的实际应用能力,以两种现有的土壤转换函数(Vereecken和HYPRES模型)为例,将其应用于山东省平度市土壤饱和导水率的空间预测,并利用拉丁超立方抽样(LHS)方法对预测结果的不确定性进行了分析。结果表明,饱和导水率空间预测的不确定性主要来源于土壤基本性质的空间插值误差和土壤转换函数自身的预测误差。当Vereecken模型应用于饱和导水率空间预测时,预测结果的不确定性主要由土壤基本性质空间插值误差所决定,土壤转换函数预测误差的影响较小,而HYPRES模型则是受二者的双重影响。 相似文献
11.
根据给定渗透系数、孔隙度以及吸附系数的概率分布,采用顺序高斯模拟生成相关的多参数随机场的实现,作为地下水流和溶质运移模型的输入参数,对污染物浓度进行随机分析。研究结果表明,与仅考虑渗透系数空间变异性相比,考虑相关的多参数空间变异性导致污染羽的扩散程度有显著不同。当孔隙度与渗透系数呈正相关关系时,会减少污染羽的扩散程度,反之,当孔隙度与渗透系数为负相关关系时,会加剧污染羽的扩散程度。吸附系数也是如此。在考虑吸附系数的空间变异性之后,污染羽的分布表现出拖尾现象。同时考虑渗透系数、孔隙度以及吸附系数空间变异性时,孔隙度非均质性对溶质运移的影响较吸附系数非均质性的影响更大。 相似文献
12.
黑河流域中下游地下水系统受上游冰冻圈融水和降雨的补给,由气候变暖导致的冰冻圈萎缩致使中下游地下水系统的稳定性面临更多的风险。地下水模型是地下水系统稳定性评估的有效手段,但是地下水模型参数往往存在较大的不确定性。为此,本文提出了基于数据同化算法的不确定性分析方法,通过包含观测资料信息减小模型不确定性。采用所提方法分析了(基于MODFLOW构建)黑河流域中游地下水模型中13个参数的不确定性,讨论了算法超参数的影响及其最优取值,分析了地下水模型参数的不确定性。实验结果证明数据同化算法可有效减小地下水模型参数的不确定性,观测资料的种类与数量对参数不确定性的减小起到重要作用;不同地下水模型参数的不确定性不同,地表水与地下水相互作用频繁的区域参数不确定性较大;含水层渗透系数、含水层给水度以及灌溉回流系数对模型输出的地下水位输出影响显著,河床水力传导系数对模型输出的河流流量影响较大。本研究将为地下水研究提供更加可靠的模型方法,为西北内流区地下水哺育的绿洲生态系统稳定可持续研究提供重要支撑。 相似文献
13.
岩土参数的随机性会直接影响边坡稳定性评价结果的精度。首先,依据边坡参数的常用分布特征,利用拉丁超立方抽样法生成若干组边坡土性参数和几何参数的随机样本,用有限元强度折减法求解各组样本对应的边坡安全系数。再考虑土性参数的空间变异性,在二维随机场模型下将蒙特卡罗模拟和有限元强度折减法相结合求解各组样本对应的边坡失效概率。然后,利用样本数据及其安全系数和失效概率对径向基函数（RBF）神经网络进行训练和测试,从而建立边坡安全系数和失效概率的预测模型。算例表明,二维随机场模型能相对精确地考虑参数的空间变异性;在此基础上建立的神经网络模型对边坡的安全系数和失效概率具有较高的预测精度,且能极大地节省边坡稳定性分析的时间。 相似文献
14.
This paper presents probabilistic assessment of seismically-induced slope displacements considering uncertainties of seismic ground motions and soil properties.A stochastic ground motion model representing both the temporal and spectral non-stationarity of earthquake shakings and a three-dimensional rotational failure mechanism are integrated to assess Newmark-type slope displacements.A new probabilistic approach that incorporates machine learning in metamodeling technique is proposed,by combining relevance vector machine with polynomial chaos expansions(RVM-PCE).Compared with other PCE methods,the proposed RVM-PCE is shown to be more effective in estimating failure probabilities.The sensitivity and relative influence of each random input parameter to the slope displacements are discussed.Finally,the fragility curves for slope displacements are established for sitespecific soil conditions and earthquake hazard levels.The results indicate that the slope displacement is more sensitive to the intensities and strong shaking durations of seismic ground motions than the frequency contents,and a critical Arias intensity that leads to the maximum annual failure probabilities can be identified by the proposed approach. 相似文献
15.
Steven B. Meyerhoff Reed M. Maxwell Wendy D. Graham John L. Williams III 《Hydrogeology Journal》2014,22(6):1329-1343
Subsurface heterogeneity is one of the largest sources of uncertainty associated with saturated hydraulic conductivity. Recent work has demonstrated that uncertainty in hydraulic conductivity can impart significant uncertainty in runoff generation processes and surface-water flow. Here, the role of site characterization in reducing hydrograph prediction bias and uncertainty is demonstrated. A fully integrated hydrologic model is used to conduct two sets of stochastic, transient simulation experiments comprising different overland flow mechanisms: Dunne and Hortonian. Conditioning hydraulic conductivity fields using values drawn from a simulated synthetic control case are shown to reduce both mean bias and variance in an ensemble of conditional hydrograph predictions when compared with the control case. The ensemble simulations show a greater reduction in uncertainty in the hydrographs for Hortonian flow. The conditional simulations predict surface ponding and surface pressure distributions with reduced mean error and reduced root mean square error compared with unconditional simulations. Uncertainty reduction in Hortonian and Dunne flow cases demonstrates different temporal signals, with more substantial reduction achieved for Hortonian flow. 相似文献
16.
Monte Carlo Simulation (MCS) method has been widely used in probabilistic analysis of slope stability, and it provides a robust and simple way to assess failure probability. However, MCS method does not offer insight into the relative contributions of various uncertainties (e.g., inherent spatial variability of soil properties and subsurface stratigraphy) to the failure probability and suffers from a lack of resolution and efficiency at small probability levels. This paper develop a probabilistic failure analysis approach that makes use of the failure samples generated in the MCS and analyzes these failure samples to assess the effects of various uncertainties on slope failure probability. The approach contains two major components: hypothesis tests for prioritizing effects of various uncertainties and Bayesian analysis for further quantifying their effects. Equations are derived for the hypothesis tests and Bayesian analysis. The probabilistic failure analysis requires a large number of failure samples in MCS, and an advanced Monte Carlo Simulation called Subset Simulation is employed to improve efficiency of generating failure samples in MCS. As an illustration, the proposed probabilistic failure analysis approach is applied to study a design scenario of James Bay Dyke. The hypothesis tests show that the uncertainty of undrained shear strength of lacustrine clay has the most significant effect on the slope failure probability, while the uncertainty of the clay crust thickness contributes the least. The effect of the former is then further quantified by a Bayesian analysis. Both hypothesis test results and Bayesian analysis results are validated against independent sensitivity studies. It is shown that probabilistic failure analysis provides results that are equivalent to those from additional sensitivity studies, but it has the advantage of avoiding additional computational times and efforts for repeated runs of MCS in sensitivity studies. 相似文献
17.
Federica Lucà Gabriele Buttafuoco Gaetano Robustelli Antonio Malafronte 《Environmental Earth Sciences》2014,72(9):3353-3367
Assessing spatial variability of soil thickness is a critical issue for understanding and predicting slope processes. The present work was aimed at estimating the spatial scales at which the variation of pyroclastic cover thickness occurs in a sample area in the Sorrento Peninsula (Italy). Stochastic simulation was used to understand the spatial variability of pyroclastic cover thickness on Mount Pendolo and to assess its spatial uncertainty. In the study area, covering about 0.7 km2, thickness measurements were collected using electrical resistivity tomography profiles, continuous core drillings and steel rod penetrometric tests. Variographic analysis revealed the occurrence of an anisotropic behaviour along the N50 and N140 directions. In the latter anisotropic direction, a nested variogram was fitted including (1) a long-range component which could be related to large-scale factors, like the curvature of the slope and contributing area and (2) a shorter scale variation which is probably associated with the occurrence of denudation processes or to the articulate cover/bedrock interface. To assess the spatial variability and uncertainty of pyroclastic cover thickness, a stochastic simulation algorithm was used and 500 equally probable images of cover thickness were yielded. The results showed that a better thickness distribution map can be drawn by simulating the data collected on the slope and at the footslope separately. The approach also allowed delineating the areas characterized by greater uncertainty, suggesting supplementary measurements to further improve the cover thickness distribution model, thus reducing the uncertainty. 相似文献
18.
Pinom Ering G. L. Sivakumar Babu 《Georisk: Assessment and Management of Risk for Engineered Systems and Geohazards》2017,11(4):285-298
The study presents a recent slope failure in India which resulted in the burial of a village and claimed large number of lives. Current methods of probabilistic back analysis incorporate uncertainty in the analysis but do not consider spatial variability. In this study, back analysis is performed using Bayesian analysis in conjunction with random field theory. The probabilistic method is shown to be efficient in back-analysing a slope failure. It also provides confidence in parameter values to be used for post-failure slope design. The back analysis method which does not consider spatial variability overestimates the uncertainty in analysis, which can lead to uneconomical slope remediation design and measures. 相似文献
19.
降雨诱发滑坡是世界上最普遍的地质灾害,而关于降雨入渗对边坡的可靠度分析,优势入渗的影响被长期忽视。使用Comsol Multiphysics对降雨条件下优势入渗做数值求解,利用无限边坡模型计算边坡安全系数;并应用改进Cholesky分解法生成空间相关随机场,使用蒙特卡洛方法分析降雨过程中边坡的可靠度。结合确定性与可靠度计算对比均质入渗与优势入渗在降雨过程中边坡安全性变化：（1）降雨强度较低时,优势入渗安全性较好,而降雨强度较高时,均质入渗更稳定;（2）均质入渗中参数空间变异性是边坡失稳破坏的关键因素,而优势入渗的边坡失稳则由湿润峰快速推进所导致;（3）针对优势入渗模型研究,发现基质域与优势域水力交换强度较大时边坡有更大概率失稳,而较小的水力交换强度可能影响边坡底部的失稳破坏。 相似文献
20.
降雨条件下考虑饱和渗透系数变异性的边坡可靠度分析 总被引：1，自引：0，他引：1
土体饱和渗透系数表现为天然的变异性,为此基于Green-Ampt模型建立了考虑饱和渗透系数变异性的降雨入渗物理模型,并藉此模型确定了坡体湿润锋深度和含水率分布。然后结合无限长非饱和土边坡稳定模型得到解析形式的反映边坡稳定性的极限状态函数。采用Monte Carlo法对饱和渗透系数进行随机抽样并最终建立降雨条件下考虑饱和渗透系数变异性的边坡概率分析框架。针对一假想边坡,探讨了饱和渗透系数的变异系数、降雨持时和降雨强度对边坡破坏概率以及破坏发生时间概率分布的影响,结果表明：在降雨初期,边坡的破坏概率随饱和渗透系数变异性的增强而逐渐增加,但随着降雨的持续,破坏概率开始随变异性的增强而显著降低;滑坡最可能发生时间的大小并不受饱和渗透系数变异性的影响,而是直接取决于降雨强度;滑坡最可能发生时间所对应的概率却随变异性的增强而逐渐减小。 相似文献