降雨型浅层滑坡危险性预测模型

通过分析SHALSTAB和TRIGRS等浅层滑坡物理确定性模型存在的问题,提出了基于降雨入渗动态守恒的瞬态降雨入渗模型,该模型考虑了初期降雨过程、降雨历程以及饱和非饱和入渗过程,证明了SHALSTAB模型是该模型的特殊形式,并克服了TRIGRS模型参数繁多及一维入渗路径的问题.将无限边坡模型、瞬态降雨入渗模型和GIS进行耦合,研发了可用于大范围降雨型浅层滑坡危险性预测的集成系统,根据边坡的地质条件、地形参数和降雨特征即可对降雨条件下浅层滑坡的危险性进行评估.     

四川巴中市滑坡灾害与降雨雨型关系探讨

巴中市地处四川盆地和秦岭造山带的过渡地带,地质构造以宽缓的隔档式褶皱为主,地层岩性主要为砂泥岩互层的红层岩体,红层滑坡灾害多为强降雨诱发。开展滑坡灾害与降雨雨型关系的研究,可为该地区滑坡灾害临界降雨阈值和预警服务提供参考。文章通过统计巴中市强降雨事件与滑坡发生的对应关系,初步揭示了滑坡灾害触发的降雨特征,并在分析降雨强度的基础上,结合降雨历时和降雨过程,对巴中市2007—2016年之间23场月降雨量大于200 mm的降雨事件进行了细分,共划分为单峰型、前峰型、后峰型、递增型、递减型、均匀型6类降雨雨型。对各类降雨雨型下滑坡发生数量进行统计,递增型和单峰型降雨事件下滑坡发生的比例分别为46.90%和25.02%。经稳定性计算分析,递增型和单峰型两类雨型条件下滑坡稳定性有明显降低,降雨过程对滑坡发生具有显著影响。结果表明:强降雨期间应加强降雨雨型的分析,为适时发布区域滑坡灾害预警信息、做好提前避让提供技术支撑。     

湘西陈溪峪滑坡变形机理及稳定性评价

浅层滑坡在我国广泛分布,但在区域范围内分布规律性较差,且具有突发性、隐蔽性和破坏性强等特点。湘西武陵山区地质条件复杂、降雨丰沛、人类工程活动强烈,突发性地质灾害频发,尤以降雨诱发的浅层滑坡为主。文章以湘西地区慈利县陈溪峪滑坡为例,开展了降雨量、基质吸力、地下水位和地表变形等的监测;结合滑坡的现场调查及监测成果,分析滑坡的形成条件和变形机理;在此基础上,考虑基质吸力对边坡稳定性的贡献,将强度折减有限元法推广到非饱和土边坡,计算得到了不同降雨工况下滑坡稳定性。结果表明:当强降雨降落到滑坡体上时,坡内基质吸力值均迅速减小,直至一定值后（9.5 kPa左右）不再变化;坡内地下水位受季节性降雨影响显著,短时强降雨引起地下水变化幅度不如长时间降雨对地下水位造成的影响大;陈溪峪滑坡的地质力学成因为蠕滑推移式土质滑坡,运动形式为沿基覆界面的浅层滑坡;短时强降雨是诱发滑坡变形的最关键因素。陈溪峪滑坡在持续降雨条件下的降雨量预警值约为280 mm,在短时强降雨条件下的降雨强度预警值约为240 mm/d。     

三峡库区湖北段降水时空分布与滑坡灾害的关系

在分析三峡库区湖北段滑坡灾害发育规律的基础上,结合三峡库区湖北段1980-2010年不同时间尺度降水的时间和空间分布特征,得出持续性降雨与暴雨是影响三峡库区湖北段滑坡地质灾害发育的敏感因子。结果发现:三峡库区湖北段滑坡发生区域性强,且库区湖北段降水量的分布与滑坡地质灾害发生的年内变化相一致;库区内多雨中心位于库区鹤峰附近;根据三峡库区降水量分布图,结合库区地质环境,建议将库区强降雨地区作为地质灾害重点防护区和监测区,尽可能以最小代价确保库区稳定性;此外,通过对滑坡灾害与不同时段不同降水类型的相关系数分析,进一步验证前期降水量的累积和强降雨是三峡库区湖北段发生滑坡地质灾害的重要诱因。     

降雨作用下某滑坡的稳定性研究

以百昆成品油管道建水站MJ053滑坡为分析对象,在结合滑坡野外调查和室内外试验工作的情况下,结合非饱和土的渗流理论,应用数值模拟方法对降雨作用下的滑坡形成机理和稳定性进行研究,分析滑坡在连续3 d强降雨作用下的稳定性变化情况。结果表明：滑坡受强降雨影响明显,滑坡在极端强降雨条件下,滑坡土体位移在短时间内迅速增大,稳定性则下降至不稳定状态,该滑坡必须进行治理。     

强降雨条件下基岩型层状边坡入渗模型及稳定性研究

强降雨作用下基岩型层状边坡易发生失稳破坏,给人们生命财产造成重大损失。为探索基岩型层状边坡的降雨入渗过程,以Green-Ampt入渗模型为基础,考虑了边坡几何特征及饱和带渗流作用,得到了边坡不同入渗阶段入渗率和湿润峰深度的计算式,建立了适用于基岩型层状边坡的降雨入渗计算模型;在分析基岩型层状边坡稳定性时,考虑了饱和带的渗流作用,联合降雨入渗模型与极限平衡法,分析了基岩面与湿润峰面稳定性的变化规律,得到了计算基岩型层状边坡安全系数的解析表达式;结果表明,该模型的计算与试验结果具有一致性。利用该计算模型与传统计算方法对张家湾滑坡进行了强度为30 mm/h的降雨入渗与稳定性分析,得到了不同计算方法下张家湾滑坡湿润峰深度及安全系数随降雨历时增加而发生的变化规律,结果表明该计算模型在分析基岩型层状边坡稳定性时优于传统分析方法。     

降雨型浅层黄土滑坡危险性评价与区划

黄土高原是我国地质灾害最为发育的地区之一,其中降雨诱发的浅层黄土滑坡又最为典型。以典型黄土地貌区-柳林县为例,应用SINMAP模型,探讨模型在黄土地区的适用性,分析了随着研究区内降雨量的增加,滑坡变形失稳区域的面积变化、分布位置和扩展趋势。研究表明,随着降雨量的增加,滑坡所处位置逐渐由稳定状态向失稳状态发展,位于失稳分区的滑坡数量逐渐增加,说明降雨对该研究区的斜坡稳定性影响较为明显。通过将模拟结果与实际发生的由降雨触发的滑坡灾害进行对比分析,可以得出SINMAP模型在黄土地区,对区域性降雨诱发浅层黄土滑坡稳定性的模拟预测有效,可以用于黄土地区浅层滑坡的稳定性评价研究。     

基于有效降雨强度的滑坡灾害危险性预警

选取湖北省恩施地区1 000 km2区域作为典型研究区, 在全面分析该区域历史滑坡资料的基础上, 根据该区滑坡生成与地层岩性之间的关系, 将研究区地层划分为高、中、低3类易发性岩组.分岩组统计降雨监测数据与历史滑坡信息, 得出有效降雨强度与关键降雨持续时间的散点图, 由此确定不同滑坡发生概率的有效降雨强度阈值, 提出该区的滑坡灾害危险性预警判别模型.基于样本区统计数据建立滑坡预测指标体系, 运用GIS得出研究区域的滑坡空间易发性区划结果, 并根据不同易发岩组-有效降雨强度模型, 叠加滑坡灾害易发性分区结果与降雨危险性预警等级分级结果, 对研究区的滑坡灾害危险性进行了预测预警.结果表明: 不同易发岩组-有效降雨强度模型所得预警结果与实际情况吻合, 预警模型具有考虑全面和预警精度高的特点, 在实际预警中切实可用.      

台风暴雨条件下滑坡稳定性影响因素分析

以实验数据为依据,通过数值模拟对台风暴雨条件下滑坡体稳定性的主要影响因素进行模拟研究。台风暴雨条件下滑坡体的主要影响因素为特殊降雨雨型：(1) 在相同雨强程度下,台风暴雨的单峰型降雨水文响应速度、稳定性破坏速度及程度均大于普通均匀型降雨,单峰型降雨导致边坡短时间内达到失稳状态,呈“即雨即滑”情况;(2) 强台风多峰型降雨下,经过第一个峰值强降雨后浅层土质边坡已处于不稳定状态,当第二个强峰值降雨来临时,坡体的稳定性较单峰型降低更为迅速。这些为福建省台风暴雨这一特殊降雨类型条件下滑坡的发生机理探索及预警预报提供了新的思路和科学依据。     

黄土-泥岩接触面滑坡的两种雨型模型试验

黄土边坡变形失稳机理研究对于黄土滑坡灾害防治具有重要意义。黄土-泥岩接触面滑坡作为黄土滑坡类型之一,研究人员已对其失稳基本过程与形成机理有较为清晰的认识。但对于其在不同降雨类型下,特别是强降雨条件下的变形破坏过程则有待进一步探讨。因此,本文对黄土-泥岩接触面边坡开展室内降雨模型试验,研究其在强降雨条件下斜坡变形破坏模式。试验设计连续强降雨和间断强降雨两种降雨条件,对比分析两种降雨条件下边坡雨水入渗规律及变形破坏模式。结果表明:在两种典型降雨模式下,雨水入渗速率由边坡前缘至后缘逐渐降低;在坡体表层,随着降雨由间断至连续过渡,入渗速率逐渐增加;在坡体深部,入渗速率受边坡结构影响;间断降雨下边坡呈现滑移-拉裂失稳;在连续降雨条件坡体则表现为蠕滑-拉裂破坏。     

Comparing the performance of TRIGRS and TiVaSS in spatial and temporal prediction of rainfall-induced shallow landslides

This study compares the performance of transient rainfall infiltration and grid-based regional slope stability (TRIGRS) model and time-variant slope stability (TiVaSS) model in the prediction of rainfall-induced shallow landslides. TRIGRS employs one-dimensional (1-D) subsurface flow to simulate the infiltration rate, whereas a three-dimensional (3-D) model is utilized in TiVaSS. The former has been widely used in landslide modeling, while the latter was developed only recently. Both programs are used for the spatiotemporal prediction of shallow landslides caused by rainfall. This study uses the July 2011 landslide event that occurred in Mt. Umyeon, Seoul, Korea, for validation. The performance of the two programs is evaluated by comparison with data of the actual landslides in both location and timing by using a landslide ratio for each factor of safety class (\({\text{LR}}_{\text{class}}\) index), which was developed for addressing point-like landslide locations. Moreover, the influence of surface flow on landslide initiation is assessed. The results show that the shallow landslides predicted by the two models are highly consistent with those of the observed sliding sites, although the performance of TiVaSS is slightly better. Overland flow affects the buildup of the pressure head and reduces the slope stability, although this influence was not significant in this case. A slight increase in the predicted unstable area from 19.30 to 19.93% was recorded when the overland flow was considered. It is concluded that both models are suitable for application in the study area. However, although it is a well-established model requiring less input data and shorter run times, TRIGRS produces less accurate results.     

Analysis of time-varying rainfall infiltration induced landslide

A case study of rainstorm-induced landslide is modeled following the hourly rainfall time series from the stage of infiltration caused by induced slope movement and soil saturated to excess pore pressures—Transient Rainfall Infiltration and Grid-based Regional Slope-Stability Analysis (TRIGRS). The grid-based landslide stability analysis was conducted to model the increased pore pressures and runoff in the study area under the specified rainfall conditions. The generated time variances of pore pressures help determine landslide characteristics and mechanisms under rainfall conditions. Inputs of soil properties and permeability parameters for landslide stability analysis in the study area were prepared by TRIGRS adopted for transient infiltration analysis. Results of the analyses show that under heavy rainfall conditions, the infiltrated slope is unstable and the time of debris masses movement initiated is correlated to the recorded time. In the initiated landslide, characteristics and effects are considered and reflected in the numerical modeling under combinations of topography, land use, climatic and geological conditions. Results reveal that there is a plane failure surface and a potential circular failure surface at the study site besides the rock topple failures in the crest. A grid-based slope-stability analysis incorporated with the GIS spatial functions is more advantageous than the traditional two-dimensional analysis for specified slope profiles to determine the whole behavior of a slope.     

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.     

Evaluation of TRIGRS (transient rainfall infiltration and grid-based regional slope-stability analysis)’s predictive skill for hurricane-triggered landslides: a case study in Macon County,North Carolina

The key to advancing the predictability of rainfall-triggered landslides is to use physically based slope-stability models that simulate the transient dynamical response of the subsurface moisture to spatiotemporal variability of rainfall in complex terrains. TRIGRS (transient rainfall infiltration and grid-based regional slope-stability analysis) is a USGS landslide prediction model, coded in Fortran, that accounts for the influences of hydrology, topography, and soil physics on slope stability. In this study, we quantitatively evaluate the spatiotemporal predictability of a Matlab version of TRIGRS (MaTRIGRS) in the Blue Ridge Mountains of Macon County, North Carolina where Hurricanes Ivan triggered widespread landslides in the 2004 hurricane season. High resolution digital elevation model (DEM) data (6-m LiDAR), USGS STATSGO soil database, and NOAA/NWS combined radar and gauge precipitation are used as inputs to the model. A local landslide inventory database from North Carolina Geological Survey is used to evaluate the MaTRIGRS’ predictive skill for the landslide locations and timing, identifying predictions within a 120-m radius of observed landslides over the 30-h period of Hurricane Ivan’s passage in September 2004. Results show that within a radius of 24 m from the landslide location about 67% of the landslide, observations could be successfully predicted but with a high false alarm ratio (90%). If the radius of observation is extended to 120 m, 98% of the landslides are detected with an 18% false alarm ratio. This study shows that MaTRIGRS demonstrates acceptable spatiotemporal predictive skill for landslide occurrences within a 120-m radius in space and a hurricane-event-duration (h) in time, offering the potential to serve as a landslide warning system in areas where accurate rainfall forecasts and detailed field data are available. The validation can be further improved with additional landslide information including the exact time of failure for each landslide and the landslide’s extent and run out length.     

典型黄土丘陵区浅层黄土滑坡稳定性评价——以延安市志丹县为例

黄土丘陵地区地质环境脆弱,每到雨季极易诱发浅层黄土滑坡,对居民的生命和财产安全构成威胁也阻碍着当地经济的发展。对浅层滑坡进行稳定性评价,不仅有助于认识浅层滑坡的发生发展过程,而且对防灾减灾和地区规划建设具有十分重要的指导意义。本研究选择SINMAP模型作为评价浅层黄土滑坡的重要工具,评价了陕西省延安市志丹县黄土丘陵区浅层滑坡的稳定性,评价结果表明:1)研究区整体稳定性程度较高,在降雨量为8.6 mm、15 mm、25 mm、50 mm和100 mm时不稳定区域(包括极不稳定、不稳定和潜在不稳定)面积分别占研究区总面积的9.12%、18.93%、23.17%、30.94%和38.67%,不稳定区域的面积不超过整个研究区面积的一半,极不稳定区域的滑坡密度最大,其次为不稳定区域和潜在不稳定区域;2)随着降雨量的增大,潜在不稳定和不稳定区域的面积会逐渐扩大,极不稳定区始终位于坡度大且水流侵蚀强烈的地方,变化幅度小;3)浅层滑坡的稳定性很大程度上依赖于当地的地形条件:坡度分布为20°~51°,高程分布范围为1302~1606 m,在坡向上阴坡的发生数量多于阳坡,西向和西北向浅层滑坡最为发育;4)流域内的滑坡多属降雨诱发的山体滑坡,确定性模型SINMAP为预测这一类滑坡提供了强大的工具,不仅评估了现有的已发生的滑坡的稳定性,也预测了未来在不同降雨条件下可能发生滑坡的地区。分析结果可为预防和减轻滑坡灾害带来的损失,合理的城市规划和道路选址等提供参考。     

Predictive Power Evaluation of a Physically Based Model for Shallow Landslides in the Area of Oltrepò Pavese,Northern Italy

The use of real-time landslide early warning systems is attracting the attention of the scientific community, since it allows to assess “where” and “when” a shallow rainfall-induced landslide might occur by coupling rainfall amounts, hydrological models and slope-stability analysis. The paper deals with the main results of a back analysis, which refers to the application of a physically based stability model [Shallow Landslides Instability Prediction (SLIP)] on regional scale. The analysis concerns the occurrence of some recent rainfall-induced shallow landslides in the municipal territory of Broni, in the area of Oltrepò Pavese (Northern Italy). The study area is a hilly region 2.4 km² wide, where more than 40 % of the territory has slopes steeper than 15° and altitudes are between 90 and 250 m a.s.l. As regards the geologic setting, clayey-silty shallow colluvial deposits, with a maximum thickness of about 3 m, overlap a bedrock made of clayey shales, calcareous flysch and marls. The SLIP model is based on the limit equilibrium method applied to an infinite slope and on the Mohr–Coulomb strength criterion for the soil. By assuming that the main hydro-geotechnical process that leads to failure is the saturation of parts of the soil, the model allows to take into account the condition of partial saturation of the soil. The safety factor (F _S ) of a slope is also function of previous rainfalls. After the implementation of the model at territory scale, the input data have been introduced through a geographic information systems platform. In the current paper we mainly intend to evaluate the performance of SLIP at catchment scale, by comparison to (1) observed landslide events and (2) another well-established physically based model (TRIGRS). Further, we want to assess the suitability of the model as early warning tool. The results produced by the model are analyzed both in terms of safety factor maps, corresponding to some particular rainfall events, and in terms of the time-varying percentage of unstable areas over a 2-year span period. The paper shows the comparison between observed landslide localizations and model predictions. A quantitative comparison between the SLIP model and TRIGRS is presented, only for the most important event that occurred during the analyzed period. Overall, the results of the stability analyses based on observed rainfalls show the capability of the SLIP model to predict, in real-time and on a wide area, the occurrence of the analyzed phenomena.     

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.     

A distributed hydrological–geotechnical model using satellite-derived rainfall estimates for shallow landslide prediction system at a catchment scale

This paper describes the potential applicability of a hydrological–geotechnical modeling system using satellite-based rainfall estimates for a shallow landslide prediction system. The physically based distributed model has been developed by integrating a grid-based distributed kinematic wave rainfall-runoff model with an infinite slope stability approach. The model was forced by the satellite-based near real-time half-hourly CMORPH global rainfall product prepared by NOAA-CPC. The method combines the following two model outputs necessary for identifying where and when shallow landslides may potentially occur in the catchment: (1) the time-invariant spatial distribution of areas susceptible to slope instability map, for which the river catchment is divided into stability classes according to the critical relative soil saturation; this output is designed to portray the effect of quasi-static land surface variables and soil strength properties on slope instability and (2) a produced map linked with spatiotemporally varying hydrologic properties to provide a time-varying estimate of susceptibility to slope movement in response to rainfall. The proposed hydrological model predicts the dynamic of soil saturation in each grid element. The stored water in each grid element is then used for updating the relative soil saturation and analyzing the slope stability. A grid of slope is defined to be unstable when the relative soil saturation becomes higher than the critical level and is the basis for issuing a shallow landslide warning. The method was applied to past landslides in the upper Citarum River catchment (2,310 km²), Indonesia; the resulting time-invariant landslide susceptibility map shows good agreement with the spatial patterns of documented historical landslides (1985–2008). Application of the model to two recent shallow landslides shows that the model can successfully predict the effect of rainfall movement and intensity on the spatiotemporal dynamic of hydrological variables that trigger shallow landslides. Several hours before the landslides, the model predicted unstable conditions in some grids over and near the grids at which the actual shallow landslides occurred. Overall, the results demonstrate the potential applicability of the modeling system for shallow landslide disaster predictions and warnings.     

Landslide and debris-flow hazard analysis and prediction using GIS in Minamata–Hougawachi area, Japan

On July 20, 2003, following a short duration of heavy rainfall, a debris-flow disaster occurred in the Minamata–Hougawachi area, Kumamoto Prefecture, Japan. This disaster was triggered by a landslide. In order to assess the landslide and debris-flow hazard potential of this mountainous region, the study of historic landslides is critical. The objective of the study is to couple 3D slope-stability analysis models and 2D numerical simulation of debris flow within a geographical information systems in order to identity the potential landslide-hazard area. Based on field observations, the failure mechanism of the past landslide is analyzed and the mechanical parameters for 3D slope-stability analysis are calculated from the historic landslide. Then, to locate potential new landslides, the studied area is divided into slope units. Based on 3D slope-stability analysis models and on Monte Carlo simulation, the spots of potential landslides are identified. Finally, we propose a depth-averaged 2D numerical model, in which the debris and water mixture is assumed to be a uniform continuous, incompressible, unsteady Newtonian fluid. The method accurately models the historic debris flow. According to the 2D numerical simulation, the results of the debris-flow model, including the potentially inundated areas, are analyzed, and potentially affected houses, river and road are mapped.