基于TRIGRS模型的浅层滑坡稳定性分析

采用基于网格的瞬态降雨入渗(TRIGRS)模型,以滑坡灾害频发的陕南安康市东部巴山东段白河县为研究区,探讨模型适用性及不同降雨条件下边坡稳定性空间分布规律。根据中国土壤分布图并结合已有研究,选取模拟所需的水土力学参数。将模拟所得研究区稳定性分布图与实际滑坡目录对比分析进行TRIGRS模型精度评估,分别模拟连阴雨和短时间强降雨两种降雨情景,探讨研究区边坡稳定性空间分布规律,结果表明:1)TRIGRS模型在模拟预测降雨诱发型浅层滑坡时,结合受试者特征ROC曲线进行精度评估,曲线下面积为0.752,说明此模型在白河县进行滑坡模拟时具有一定的合理性与准确性,能反应该地区滑坡灾害的空间分布特征;2)连阴雨情景模拟下,极不稳定区域主要集中在北部低山地貌区,以冷水镇和麻虎镇为主,随降雨历时增加向东部和南部增多,西部仓上镇、西营镇和双丰镇的极不稳定区域面积较少,能承受长时间连续性降雨。短时间强降雨对边坡稳定性的影响更为直接,极不稳定区域随降雨强度增大而增加,以冷水镇和麻虎镇为主要防范区域。结合地形分析,极陡峭区域边坡稳定性最差,无法承受持续性降雨和高强度降雨,较陡峭区域更易受到降雨历时和降雨强度的影响,而平缓区域则能承受长时间及高强度的降雨;3)TRIGRS模型根据不同降雨条件预测易发生滑坡灾害的区域,为滑坡实时预报警系统提供了新的可能方法。     

降雨条件下浅层滑坡稳定性探讨

降雨条件下浅层滑坡是一种常见、多发的地质灾害现象,为了解边坡稳定性随降雨入渗过程的变化情况,以Green-Ampt入渗模型为基础,并考虑了动水压力的作用,建立了降雨入渗条件下浅层滑坡的概念模型,分别推导了降雨前有、无地下水位条件下的边坡安全系数与降雨时间的关系表达式。从分析结果中可以看出,对于这两种情况下边坡稳定性发生突变的主要原因归结于：前者为在湿润锋与地下水位面接触的短时间内,滑带处的孔隙水压力迅速增高;后者为滑带在浸水饱和情况下,岩土体的强度迅速降低。在此基础上,根据降雨过程中边坡是否达到饱和,提出边坡饱和临界时间的概念,考虑了初始降雨强度小于土壤入渗能力的情况。这个时间可以作为一个参数指标用于浅层滑坡的预警。     

降雨诱发浅层滑坡稳定性的计算模型研究

我国是一个滑坡灾害频发的国家,众多事实表明：降雨是影响边坡稳定性,导致边坡失稳的最主要和最普遍的环境因素,是浅层滑坡的触发因素。为了更好地对降雨诱发浅层滑坡进行研究,采用非饱和土VG模型与改进的Green-Ampt入渗模型对Mein-Larson降雨入渗模型进行改进,并结合无限边坡提出了一个降雨诱发浅层滑坡的简化计算模型。与以往提出的简化计算模型相比,该模型既考虑了坡面倾斜的影响,又考虑了非饱和土的特性,并可用于两种降雨形式下的边坡浅层稳定性估算,具有更广的应用范围。通过与有限元得到的结果进行比较可得：在不同降雨条件下,该计算模型得到的各项结果与数值解是接近的,安全系数计算结果是偏于安全的,因此,可将该计算模型用于降雨诱发浅层滑坡的近似估算;该计算模型公式简单,便于计算,计算效率较高。     

基于有效雨量的鹰厦铁路降雨诱发滑坡预警预报概率模型

大气降雨是造成铁路滑坡的重要诱因。文章以浅层滑坡SHALSTAB模型为基础,以鹰厦铁路为研究区域,研究了降雨诱发铁路滑坡的机理,进一步分析滑坡与有效雨量的关系。结合滑坡概率预报模型,计算鹰厦铁路降雨诱发滑坡临界雨量,并对研究区的滑坡灾害危险性进行了预警分级。     

强降雨条件下气压对滑坡延时效应研究

在强降雨入渗条件下,浅层边坡土体中的气体可能被封闭,孔隙气压力在封闭条件下随着雨水的入渗不断增加。结合湿润峰面受力分析对封闭气体压力的物理意义进行了说明,通过考虑简化的气阻入渗模型,对比经典的Green-Ampt入渗模型,研究了气压对入渗率和下移的湿润峰的影响。应用该入渗模型,对下部为基岩的大面积浅层边坡雨水入渗过程以及边坡稳定性进行分析。研究表明,封闭气压显著降低了边坡体内雨水的入渗率,对安全系数的降低具有明显的延时性,这进一步揭示了部分地区雨后滑坡频繁发生的重要原因。因此,考虑封闭气压对大面积边坡降雨安全预报具有重要意义     

非饱和黄土边坡水热变化过程室内模型试验研究

针对黄土边坡在降雨条件下易发生浅层滑塌失稳破坏问题,探讨降雨入渗及日照蒸发条件下非饱和黄土边坡内水热变化过程。利用填筑室内黄土边坡模型,通过控制降雨–日照循环条件,对黄土边坡模型中温度、水分及坡面位移进行监测,结果表明,非饱和黄土边坡模型在外界降雨–日照条件下其内部温度及含水率的影响范围在30~40 cm之间,其影响深度是有限的,说明通常在降雨入渗作用下黄土边坡失稳破坏的深度有限,多为浅层滑塌破坏;边坡模型的表面位移随着降雨日照条件变化而发生轻微膨胀或收缩。     

考虑降雨类型的基岩型浅层边坡稳定性分析方法

降雨是诱发滑坡尤其是浅层滑坡的主要因素,目前多数降雨作用下基岩型浅层边坡稳定性分析方法都是基于常降雨强度假设,忽略了降雨特性对该类边坡稳定性的影响。文章建立了常规型降雨强度-时间类型,通过控制参数统一均匀型降雨、递增型降雨、递减型降雨、峰值型降雨等类型。根据入渗理论和无限边坡模型,提出了考虑降雨类型的基岩型浅层边坡稳定性分析方法。通过编制MATLAB程序计算一边坡稳定性,结果表明:不同降雨类型对基岩型浅层边坡稳定性影响较大,具有明显的时效性。在实际边坡防治中,应考虑降雨特性对边坡稳定性的影响。     

降雨条件下非饱和土滑坡渗流变形模拟分析及工程治理

以G104国道丁山服务区西侧滑坡为研究对象,根据勘查和室内试验结果,结合反演方法确定滑坡滑带土强度参数。设定了降雨入渗模型、建立滑坡体数值模型,运用非饱和土渗流理论对边坡进行渗流场和应力场耦合分析。通过有限元方法模拟降雨96h,对孔隙水、渗流、位移和边坡稳定性分析。结果表明:降雨过程中,孔隙水压力与坡体位移有明显相关性,坡顶X分量位移较大,坡体的浅层、坡体上部孔压及位移变化较大,因而容易引发后缘拉裂缝、浅层滑塌,降雨后期坡体持续蠕移,引发边缘剪切裂缝,进而诱发整体性滑坡。削坡和挡墙能够提高坡体稳定性,格构、绿化、截排水工程能够减小降雨对坡顶稳定性的影响。     

三峡库区降雨型滑坡入渗特征及变形机制——基于一维和二维模型试验研究

强降雨诱发古滑坡的浅层变形是三峡库区最为严重的地质灾害,因此,探索暴雨作用下滑坡土体的入渗规律及其浅层变形机制具有重要的研究意义。以三峡库区的降雨型滑坡为研究对象,统计了降雨型滑坡土体的渗透特性分布特征,考虑强降雨作用,分别开展一维土柱入渗试验和二维滑坡模型试验,研究了不同降雨强度条件下滑坡土体的入渗特征以及对应的滑坡浅层变形机制。降雨入渗试验结果表明：降雨入渗土体的速度取决于降雨强度与土体渗透系数的相对大小,当降雨强度小于或等于土体渗透系数时,入渗能力随降雨强度增大而增大。当降雨强度大于土体渗透系数时,入渗能力反而随之减小。模型试验结果表明：强降雨入渗时,会造成地表土体暂态饱和,表层土体以下非饱和区内的气体被暂态封闭并受到表层孔隙水压力作用而压缩,导致孔隙气压力随降雨入渗迅速增大。对于三峡库区的降雨型滑坡,短时的暴雨会产生瞬态饱和区。封闭气体,这也是影响强降雨入渗能力的主要原因;同时封闭气体传递水压使得浅层土体的孔隙水压力骤增,这也是许多滑坡发生浅层变形和破坏的主要原因。     

三峡库区黄土坡滑坡降雨入渗模型研究

传统的入渗模型未考虑坡角和降雨强度对滑坡入渗过程的影响,为了更好地描述黄土坡滑坡降雨入渗过程,在Green- Ampt入渗模型的基础上推导了考虑坡体倾角和小降雨强度影响的降雨入渗模型。为了获取改进的入渗模型参数,在黄土坡滑坡1#崩滑体上进行了双环渗透试验与降雨、土的含水率和基质吸力现场监测。结果表明,黄土坡滑坡1#崩滑体饱和渗透系数为4.81×10-5 m/s;降雨时体积含水率增加,降雨停止后体积含水率降低,深部表现出一定的滞后特性;基质吸力变化趋势与体积含水率相反,降雨使其减小,降雨停止后逐渐增大。通过双环渗透试验与现场监测,获取了黄土坡滑坡降雨入渗模型参数值。将入渗模型计算值与现场监测数据进行对比,该模型计算值与现场监测数据吻合,说明该降雨入渗模型可用于黄土坡滑坡降雨入渗分析。     

A prototype system for space–time assessment of rainfall-induced shallow landslides in Italy

In the last decades, physically based distributed models turned out rather promising to achieve the space–time assessment of shallow landslides at large spatial scale. This technical note deals with the application of a physically based stability model named Shallow Landslides Instability Prediction (SLIP), which has been adopted by the Department of National Civil Protection of Italy as a prototype early warning system for rainfall-induced shallow landslides on national scale. The model is used as a main methodology to create space–time shallow landslide susceptibility maps based on a simple deterministic slope-stability approach, combined with high-resolution rainfall information and geographic information system-based geospatial datasets. The safety factor as an index to measure slope instability is modeled as function of topographic, geologic, geotechnical and hydrologic variables. Although the main aim of this work was to prove the operational viability of such model on a nationwide domain and some simplification are adopted at this stage, hind cast tests on some relevant case histories of shallow landslides occurred between October 2009 and October 2011 showed that the model has skill in representing both timing and location of those shallow landslides.     

Comparing predictive capability of statistical and deterministic methods for landslide susceptibility mapping: a case study in the northern Apennines (Reggio Emilia Province, Italy)

Statistical and deterministic methods are widely used in geographic information system based landslide susceptibility mapping. This paper compares the predictive capability of three different models, namely the Weight of Evidence, the Fuzzy Logic and SHALSTAB, for producing shallow earth slide susceptibility maps, to be included as informative layers in land use planning at a local level. The test site is an area of about 450 km² in the northern Apennines of Italy where, in April 2004, rainfall combined with snowmelt triggered hundreds of shallow earth slides that damaged roads and other infrastructure. An inventory of the landslides triggered by the event was obtained from interpretation of aerial photos dating back to May 2004. The pre-existence of mapped landslides was then checked using earlier aerial photo coverage. All the predictive models were run on the same set of geo-environmental causal factors: soil type, soil thickness, land cover, possibility of deep drainage through the bedrock, slope angle, and upslope contributing area. Model performance was assessed using a threshold-independent approach (the ROC plot). Results show that global accuracy is as high as 0.77 for both statistical models, while it is only 0.56 for SHALSTAB. Besides the limited quality of input data over large areas, the relatively poorer performance of the deterministic model maybe also due to the simplified assumptions behind the hydrological component (steady-state slope parallel flow), which can be considered unsuitable for describing the hydrologic behavior of clay slopes, that are widespread in the study area.     

Assessment of shallow landslide susceptibility using the transient infiltration flow model and GIS-based probabilistic approach

This study proposes a probabilistic analysis method for modeling rainfall-induced shallow landslide susceptibility by combining a transient infiltration flow model and Monte Carlo simulations. The spatiotemporal change in pore water pressure over time caused by rainfall infiltration is one of the most important factors causing landslides. Therefore, the transient infiltration hydrogeological model was adopted to estimate the pore water pressure within the hill slope and to analyze landslide susceptibility. In addition, because of the inherent uncertainty and variability caused by complex geological conditions and the limited number of available soil samples over a large area, this study utilized probabilistic analysis based on Monte Carlo simulations to account for the variability in the input parameters. The analysis was performed in a geographic information system (GIS) environment because GIS can deal efficiently with a large volume of spatial data. To evaluate its effectiveness, the proposed analysis method was applied to a study area that had experienced a large number of landslides in July 2006. For the susceptibility analysis, a spatial database of input parameters and a landslide inventory map were constructed in a GIS environment. The results of the landslide susceptibility assessment were compared with the landslide inventory, and the proposed approach demonstrated good predictive performance. In addition, the probabilistic method exhibited better performance than the deterministic alternative. Thus, analysis methods that account for uncertainties in input parameters are more appropriate for analysis of an extensive area, for which uncertainties may significantly affect the predictions because of the large area and limited data.     

Rainfall-induced landslides by deficit field matric suction in unsaturated soil slopes

Landslides are mainly triggered by decrease in the matric suction with deepening the wetting band by rainfall infiltrations. This paper reports rainfall-induced landslides in partially saturated soil slopes through a field study. A comprehensive analysis on Umyeonsan (Mt.) landslides in 2011 was highlighted. The incident involves the collapse of unsaturated soil slopes under extreme-rainfall event. Fundamental studies on the mechanism and the cause of landslides were carried out. A number of technical findings are of interest, including the failure mechanism of a depth of soil and effect of groundwater flow, the downward movement of wetting band and the increase of groundwater level. Based on this, an integrated analysis methodology for a rainfall-induced landslide is proposed in this paper that incorporates the field matric suction for obtaining hydraulic parameters of unsaturated soil. The field matric suction is shown to govern the rate of change in the water infiltration for the landslide analysis with respect to an antecedent rainfall. Special attention was given to a one-dimensional infiltration model to determine the wetting band depth in the absence of the field matric suction. The results indicate that landslide activities were primarily dependent on rainfall infiltration, soil properties, slope geometries, vegetation, and groundwater table positions. The proposed methodology has clearly demonstrated both shallow and deep-seated landslides and shows good agreement with the results of landslide investigations.     

A Simplified Numerical Approach for the Prediction of Rainfall-Induced Retrogressive Landslides

Retrogressive landslides are common geological phenomena in mountainous areas and on onshore and offshore slopes. The impact of retrogressive landslides is different from that of other landslide types due to the phenomenon of retrogression. The hazards caused by retrogressive landslides may be increased because retrogressive landslides usually affect housing, facilities, and infrastructure located far from the original slopes. Additionally, substantial geomorphic evidence shows that the abundant supply of loose sediment in the source area of a debris flow is usually provided by retrogressive landslides that are triggered by the undercutting of water. Moreover, according to historic case studies, some large landslides are the evolution result of retrogressive landslides. Hence the ability to understand and predict the evolution of retrogressive landslides is crucial for the purpose of hazard mitigation. This paper discusses the phenomenon of a retrogressive landslide by using a model experiment and suggests a reasonably simplified numerical approach for the prediction of rainfall-induced retrogressive landslides. The simplified numerical approach, which combines the finite element method for seepage analysis, the shear strength reduction finite element method, and the analysis criterion for the retrogression and accumulation effect, is presented and used to predict the characteristics of a retrogressive landslide. The results show that this numerical approach is capable of reasonably predicting the characteristics of retrogressive landslides under rainfall infiltration, particularly the magnitude of each landslide, the position of the slip surface, and the development processes of the retrogressive landslide. Therefore, this approach is expected to be a practical method for the mitigation of damage caused by rainfall-induced retrogressive landslides.     

Modeling regional initiation of rainfall-induced shallow landslides in the eastern Umbria Region of central Italy

We model the rainfall-induced initiation of shallow landslides over a broad region using a deterministic approach, the Transient Rainfall Infiltration and Grid-based Slope-stability (TRIGRS) model that couples an infinite-slope stability analysis with a one-dimensional analytical solution for transient pore pressure response to rainfall infiltration. This model permits the evaluation of regional shallow landslide susceptibility in a Geographic Information System framework, and we use it to analyze susceptibility to shallow landslides in an area in the eastern Umbria Region of central Italy. As shown on a landslide inventory map produced by the Italian National Research Council, the area has been affected in the past by shallow landslides, many of which have transformed into debris flows. Input data for the TRIGRS model include time-varying rainfall, topographic slope, colluvial thickness, initial water table depth, and material strength and hydraulic properties. Because of a paucity of input data, we focus on parametric analyses to calibrate and test the model and show the effect of variation in material properties and initial water table conditions on the distribution of simulated instability in the study area in response to realistic rainfall. Comparing the results with the shallow landslide inventory map, we find more than 80% agreement between predicted shallow landslide susceptibility and the inventory, despite the paucity of input data.     

Modeling landslide recurrence in Seattle, Washington, USA

To manage the hazard associated with shallow landslides, decision makers need an understanding of where and when landslides may occur. A variety of approaches have been used to estimate the hazard from shallow, rainfall-triggered landslides, such as empirical rainfall threshold methods or probabilistic methods based on historical records. The wide availability of Geographic Information Systems (GIS) and digital topographic data has led to the development of analytic methods for landslide hazard estimation that couple steady-state hydrological models with slope stability calculations. Because these methods typically neglect the transient effects of infiltration on slope stability, results cannot be linked with historical or forecasted rainfall sequences. Estimates of the frequency of conditions likely to cause landslides are critical for quantitative risk and hazard assessments. We present results to demonstrate how a transient infiltration model coupled with an infinite slope stability calculation may be used to assess shallow landslide frequency in the City of Seattle, Washington, USA. A module called CRF (Critical RainFall) for estimating deterministic rainfall thresholds has been integrated in the TRIGRS (Transient Rainfall Infiltration and Grid-based Slope-Stability) model that combines a transient, one-dimensional analytic solution for pore-pressure response to rainfall infiltration with an infinite slope stability calculation. Input data for the extended model include topographic slope, colluvial thickness, initial water-table depth, material properties, and rainfall durations. This approach is combined with a statistical treatment of rainfall using a GEV (General Extreme Value) probabilistic distribution to produce maps showing the shallow landslide recurrence induced, on a spatially distributed basis, as a function of rainfall duration and hillslope characteristics.     

Influences of soil water characteristic curve on rainfall-induced shallow landslides

The analysis of slope instability induced by rainfall was usually performed using the main drying curve as the measurement of the main wetting curve is a more time-consuming and costly task. In this study, the influences of the main drying and wetting curves on rainfall-induced shallow landslides are examined. Three designed scenarios and a real case scenario are used to conduct this examination. The prediction of shallow landslide occurrence is related to the main drying and wetting curves due to the strong relation between groundwater pressure head and hysteresis effect. The main wetting curve may have a less minimum landslide-triggering rainfall amount and a less rainfall duration threshold for landslide occurrence than the drying wetting curve. For safety’s sake, an underestimation of shallow landslide occurrence may be produced by the commonly used main drying curve. In addition, besides the shallow landslide occurrence, the failure depth and the time to failure are also influenced by the main drying and wetting curves. The hysteresis effect should be taken into account for assessing rainfall-induced shallow landslides.