甘肃省东乡县特大滑坡地质灾害形成机制与治理方法

以野外实际调查资料为依据,总结分析甘肃陇西黄土高原滑坡类型及特征的基础上,从降水(主要指强降雨)改变地形地貌、改变滑坡土的成分构成、改变滑坡的土体结构、改变滑坡的力学强度4个方面阐述了大气降水对黄土滑坡形成的机理。大气降水对黄土滑坡的时空分布存在着较大影响和控制,年际上,同一区域滑坡发生的频次与多年降水的强弱过程呈现良好的相关性,存在丰水年滑坡次数多、规模大而枯水年滑坡次数少、规模小的规律;年内滑坡集中出现于3月份和6～9月份,前者是季节性冻结—融化作用所致,后者是降水在时间上的集中决定了滑坡发生时间的集中性;不同区域,在地形地貌、地层岩性基本相同和植被覆盖率相差不大的条件下,降水量越大,滑坡发生频率越高,反之,亦然。     

空间三维滑坡敏感性分区工具及其应用

对于滑坡敏感性分区目前有三种方法:定性法、统计法和基于岩土定量模型的确定性方法。定性法基于对滑坡敏感性或灾害评估的人为判断;统计法用一个来源于结合了权重因子的预测函数或指标;而确定性法,或者说是物理定量模型法以质量、能量和动量守恒定律为基础。二维确定性模型广泛用于土木工程设计,而无限边坡模型(一维)也用于滑坡灾害分区的确定性模型。文中提出了一个新的基于GIS(地理信息系统)的滑坡敏感性分区系统,这个系统可用于从复杂地形中确认可能的危险三维(3-D)滑坡体。所有与滑坡相关的空间数据(矢量或栅格数据)都被集成到这个系统中。通过把研究区域划分为边坡单元并假定初始滑动面是椭球的下半部分,并使用Monte Carlo随机搜索法,三维滑坡稳定性分析中的三维最危险滑面是三维安全系数最小的地方。使用近似方法假定有效凝聚力、有效摩擦角和三维安全系数服从正态分布,可以计算出滑坡失稳概率。3DSlopeGIS是一个计算机程序,它内嵌了GIS Developer kit(ArcObjects of ESRI)来实现GIS空间分析功能和有效的数据管理。应用此工具可以解决所有的三维边坡空间数据解问题。通过使用空间分析、数据管理和GIS的可视化功能来处理复杂的边坡数据,三维边坡稳定性问题很容易用一个友好的可视化图形界面来解决。将3DSlopeGIS系统应用到3个滑坡敏感性分区的实例中:第一个是一个城市规划项目,第二个是预测以往滑坡灾害对临近区域可能的影响,第三个则是沿着国家主干道的滑坡分区。基于足够次数的Monte Carlo模拟法,可以确认可能的最危险滑坡体。这在以往的传统边坡稳定性分析中是不可能的。     

A temporal model for landslide risk based on historical precipitation

Of the recognized nonsteady-state factors that influence slope stability, probably most critical in many field situations is the character of precipitation and infiltration activity. A groundwater response model used in conjunction with precipitation records can provide a historical catalog of estimated maximum groundwater levels in a particular study area. An extreme-value statistical analysis of this catalog is linked with geotechnical slope stability analyses to provide a landslide hazard model for estimating the probability of slope failure within a given time. This modeling approach can provide meaningful input to risk assessments for landslide mitigation programs and to decision analyses and cost-benefit studies important for land-use planning and resource management.This paper was presented at Emerging Concepts, MGUS 87 Conference, Redwood City, California, 13–15 April 1987.     

基于Newmark模型的概率地震滑坡危险性模型参数优化与应用:以鲁甸地震区为例

应用概率地震危险性评价模型进行地震滑坡危险性区划,是解决潜在地震诱发滑坡危险性评价中震源不确定性与诱发滑坡时空不确定性的有效方法 .通过理论分析,结合鲁甸地震区的实际情况,对基于力学原理的Newmark滑块位移模型与概率地震滑坡危险性分析方法中的参数的不确定性问题进行了分析,将斜坡岩土体地震作用下的强度衰减效应、地震加速度地形放大效应、断层破碎带效应融合到了斜坡累积位移计算模型中,进行了模型计算参数的优化.改进后的分析模型,更好地反映了高陡斜坡地形与断层破碎带对地震滑坡灾害发育的控制作用,在鲁甸地震区域滑坡应用中,优化模型中的滑坡失稳极高风险区与实际地震滑坡分布表现出了较好的一致性,在超越概率2%的滑坡失稳概率分布中,鲁甸地区包谷垴-小河断裂、鲁甸-昭通断裂带及牛栏江河谷地带地震滑坡高-极高风险区分布面积增幅十分显著.因此,在Newmark滑块位移模型中考虑地震动参数与岩土参数动态响应规律与变量间的定量关系,对于提高区域斜坡稳定性分析的可靠性具有重要意义.     

A time-space based approach for mapping rainfall-induced shallow landslide hazard

A rainfall-induced shallow landslide is a major hazard in mountainous terrain, but a time-space based approach is still an unsettled issue for mapping rainfall-induced shallow landslide hazards. Rain induces a rise of the groundwater level and an increase in pore water pressure that results in slope failures. In this study, an integrated infinite slope analysis model has been developed to evaluate the influence of infiltration on surficial stability of slopes by the limit equilibrium method. Based on this new integrated infinite slope analysis model, a time-space based approach has been implemented to map the distributed landslide hazard in a GIS (Geographic Information Systems) and to evaluate the shallow slope failure induced by a particular rainfall event that accounts for the rainfall intensity and duration. The case study results in a comprehensive time-space landslide hazard map that illustrates the change of the safety factor and the depth of the wetting front over time.     

基于GIS的滑坡灾害危险性区划研究——以重庆市万州区为例

为了弥补滑坡灾害危险性区划研究中影响因子和等级划分的不确定性,结合前人研究成果,依据斜坡几何形态、岩性、地质构造、河流侵蚀、土地利用类型、人类工程活动、降水条件等影响因子与研究区实际已发生的滑坡灾害数之间的关系,编制重庆市万州区滑坡灾害危险性评价标准,并基于GIS技术和信息量模型法,计算滑坡评价因子的信息量,就万州区滑坡危险性进行区划,最后基于乡镇行政区对该区滑坡危险性区划进行细化。结果表明：建设用地、坡高为90～200 m的地形、1 024～1 060 mm的年降雨量以及侏罗系中统上沙溪庙组岩层等因素对万州区滑坡发生影响较大;根据滑坡灾害危险性评价标准,万州区滑坡灾害被划分为高、中、低、极低等4个危险区;应用信息量模型法得到的万州区滑坡危险性区划与实际情况比较吻合;高危险区和中危险区面积分别为564.4 km2和848.6 km2,分别占万州区总面积的16.3%和24.5%,主要分布于长江干流及支流两岸的居民相对集中区以及公路干线地段;高危险和中危险乡镇主要分布在万州区经济较为发达的长江干流两岸,尤其是左岸的黄柏乡、太龙镇、天城镇、李河镇等以及万州主城区。     

卡拉水电站上田滑坡体稳定性分析及评价研究

[摘 要] 为了分析卡拉水电站工程区某滑坡体的稳定性,通过对其滑坡成因、地形地貌、地质构造、 岩土力学参数敏感性等内在因素分析可知,滑坡体随着坡面隆起和坡内扩容加剧,在外界作用下易导致 边坡失稳破坏;其层面与节理裂隙的不良组合为边坡变形失稳提供了边界,陡倾坡内的裂隙,为地下水 的入渗创造了条件;滑坡稳定性随着岩土力学强度参数的提高而增强。通过对降雨、水位升降和地震等 外在因素的敏感性分析可知,库水位骤升骤降对滑坡的稳定性影响较大;短期降雨影响较小,但时间增 长滑坡失稳概率增加;地震峰值对滑坡稳定性影响较为明显。同时根据分析结果对滑坡体进行了工况 及荷载组合,并对各工况组合进行了稳定性计算及评价,得出水位下降时滑坡稳定性处于极限状态,在 蓄水地震工况下失稳概率较大。     

基于蒙特卡罗法的多级黄土滑坡可靠性分析

滑坡稳定性分析目前工程中一般采用极限平衡算法。为了确定滑坡的稳定性系数,在计算过程中要将岩土体、计算模型简化,忽略一些影响滑坡稳定的次要因素,把影响滑坡稳定的各种主要因素作为确定参数。由于滑坡岩土体本身的非均质性及其参数确定具有随机性和变异性,用唯一的稳定系数不能客观地反映整个滑坡的真实安全程度。以陕西省夏呀河滑坡为例,通过野外详细调查、工程勘探和室内土工试验,初步确定该滑坡存在四级滑动面,难以用简单的单一滑动面计算其稳定性。因此,先采用推力传递系数法对滑坡体上的四级滑坡分别进行滑坡稳定性计算,得到该滑坡体上的四级滑坡稳定系数。再采用蒙特卡罗法对该四级滑坡进行可靠性分析,得到其可靠度,定量地表达夏呀河四级滑坡的安全程度。同时对比分析夏呀河四级滑坡的稳定系数和失稳概率,综合评价该滑坡体上的四级滑坡的稳定性及其风险概率,为滑坡的工程治理及预测预警、灾害危险性评价提供依据。     

Shallow landslides in pyroclastic soils: a distributed modelling approach for hazard assessment

An effective assessment of shallow landslide hazard requires spatially distributed modelling of triggering processes. This is possible by using physically based models that allow us to simulate the transient hydrological and geotechnical processes responsible for slope instability. Some simplifications are needed to address the lack of data and the difficulty of calibration over complex terrain at the catchment's scale. We applied two simple hydrological models, coupled with the infinite slope stability analysis, to the May 1998 landslide event in Sarno, Southern Italy. A quasi-dynamic model (Barling et al., 1994) was used to model the contribution to instability of lateral flow by simulating the time-dependent formation of a groundwater table in response to rainfall. A diffusion model [Water Resour. Res. 36 (2000) 1897] was used to model the role of vertical flux by simulating groundwater pressures that develop in response to heavy rainstorms. The quasi-dynamic model overestimated the slope instability over the whole area (more than 16%) but was able to predict correctly slope instability within zero order basins where landslides occurred and developed into large debris flows. The diffusion model simulated correctly the triggering time of more than 70% of landslides within an unstable area amounting to 7.3% of the study area. These results support the hypothesis that both vertical and lateral fluxes were responsible for landslide triggering during the Sarno event, and confirm the utility of such models as tools for hazard planning and land management.     

Landslide Hazard and Risk Assessment on the Northern Slope of Mt. Changbai, China

Landslide hazard and risk assessment on the northern slope of Mt. Changbai, a well-known tourist attraction near the North Korean-Chinese border, are assessed. This study is divided into two parts, namely, landslide hazard zonation and risk assessment. The 1992 Anbalagan and Singh method of landslide hazard zonation （LHZ） was modified and used in this area. In this way, an Associative Analysis Method was used in representative areas to get a measure for controlling factors （slope gradient, relative relief, vegetation, geology, discontinuity development, weak layer thickness and ground water）. For the membership degree of factor to slope failure, the middle range of limited values was used to calculate LHZ. Based on an estimation of the potential damage from slope failure, a reasonable risk assessment map was obtained using the relationship of potential damage and probable hazard to aid future planning and prediction and to avert loss of life.     

一种基于贝叶斯理论的区域斜坡稳定性评价模型

本文结合滑坡物理模型和统计模型的优点,针对小流域滑坡稳定性分析,建立了一种基于贝叶斯理论的区域斜坡稳定性评价模型。该模型主要采用灾害自身信息来修正原始模型中的参数,解决了区域稳定性评价中参数难以确定的问题。该方法首先设定模型的初始参数分布,然后利用采样点雨前和雨后稳定性不同的信息建立验证方程,再根据马尔科夫链蒙特卡罗模拟和贝叶斯方法确定最终的参数分布,进而得出区域稳定性分布。应用该模型对福建省蔡源小流域的6 13滑坡群发性事件进行分析。结果显示,蔡源小流域地区的无量纲黏聚系数C为0.028,有效摩擦角为16.7,土壤的导水系数T和降雨量q的比值为529.026m,可能不稳定地区和不稳定地区达到76.0%。该模型利用历史灾害数据自动模拟出合适的参数,对区域滑坡稳定性评价具有重要意义。     

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.     

SHIA_Landslide: a distributed conceptual and physically based model to forecast the temporal and spatial occurrence of shallow landslides triggered by rainfall in tropical and mountainous basins

Landslides are a main cause of human and economic losses worldwide. For this reason, landslide hazard assessment and the capacity to predict this phenomenon have been topics of great interest within the scientific community for the implementation of early warning systems. Although several models have been proposed to forecast shallow landslides triggered by rainfall, few models have incorporated geotechnical factors into a complete hydrological model of a basin that can simulate the storage and movement of rainwater through the soil profile. These basin and full hydrological models have adopted a physically based approach. This paper develops a conceptual and physically based model called open and distributed hydrological simulation and landslides—SHIA_Landslide (Simulación HIdrológica Abierta, or SHIA, in Spanish)—that is supported by geotechnical and hydrological features occurring on a basin-wide scale in tropical and mountainous terrains. SHIA_Landslide is an original and significant contribution that offers a new perspective with which to analyse shallow landslide processes by incorporating a comprehensive distributed hydrological tank model that includes water storage in the soil coupled with a classical analysis of infinite slope stability under saturated conditions. SHIA_Landslide can be distinguished by the following: (i) its capacity to capture surface topography and effects concerning the subsurface flow; (ii) its use of digital terrain model (DTM) to establish the relationships among cells, geomorphological parameters, slope angle, direction, etc.; (iii) its continuous simulation of rainfall data over long periods and event simulations of specific storms; (iv) its consideration of the effects of horizontal and vertical flow; and (vi) its inclusion of a hydrologically complete water process that allows for hydrological calibration. SHIA_Landslide can be combined with real-time rainfall data and implemented in early warning systems.     

基于斜坡单元的山区城镇滑坡灾害易发性评价：以康定为例

山区地质灾害易发性评价对城镇地质灾害风险管理具有重要意义。本文以康定市为例,以斜坡单元为最小评价单元,选取高程、坡度、坡向、曲率、工程地质岩组、距道路距离、距断裂距离、距水系距离和斜坡结构等9个滑坡影响因子,根据各因子滑坡面积比曲线与证据权值曲线的突变点,划分滑坡影响因子二级状态,并对各影响因子进行相关性分析,剔除相关性较高的距道路距离因子,在此基础上,采用证据权模型进行滑坡易发性评价。对已有治理工程的斜坡单元,本文尝试利用折减系数法对其易发性进行进一步评价。结合现场调查,将研究区滑坡易发性程度划分为：极高易发、高易发、中等易发、低易发。评价结果表明,自然工况下极高易发区主要位于康定市炉城镇以及研究区北侧二道桥村一带,高易发区主要位于雅拉河、折多河与瓦斯沟河谷两侧,对治理工程所在的斜坡单元进行折减后,极高易发区面积由11.21%降至8.42%,滑坡比率由4.03降低至2.3,研究结果符合实际情况,模型精度达77.8%。评价结果较好地反映了康定市区的滑坡易发性分布情况,可为城镇精细化评价提供一定的参考依据。     

Integration of a limit-equilibrium model into a landslide early warning system

Landslides are a significant hazard in many parts of the world and exhibit a high, and often underestimated, damage potential. Deploying landslide early warning systems is one risk management strategy that, amongst others, can be used to protect local communities. In geotechnical applications, slope stability models play an important role in predicting slope behaviour as a result of external influences; however, they are only rarely incorporated into landslide early warning systems. In this study, the physically based slope stability model CHASM (Combined Hydrology and Stability Model) was initially applied to a reactivated landslide in the Swabian Alb to assess stability conditions and was subsequently integrated into a prototype of a semi-automated landslide early warning system. The results of the CHASM application demonstrate that for several potential shear surfaces the Factor of Safety is relatively low, and subsequent rainfall events could cause instability. To integrate and automate CHASM within an early warning system, international geospatial standards were employed to ensure the interoperability of system components and the transferability of the implemented system as a whole. The CHASM algorithm is automatically run as a web processing service, utilising fixed, predetermined input data, and variable input data including hydrological monitoring data and quantitative rainfall forecasts. Once pre-defined modelling or monitoring thresholds are exceeded, a web notification service distributes SMS and email messages to relevant experts, who then determine whether to issue an early warning to local and regional stakeholders, as well as providing appropriate action advice. This study successfully demonstrated the potential of this new approach to landslide early warning. To move from demonstration to active issuance of early warnings demands the future acquisition of high-quality data on mechanical properties and distributed pore water pressure regimes.     

Landslide hazard mapping along national highway-154A in Himachal Pradesh,India using information value and frequency ratio

For the socio-economic development of a country, the highway network plays a pivotal role. It has therefore become an imperative to have landslide hazard assessment along these roads to provide safety. The current study presents landslide hazard zonation maps, based on the information value method and frequency ratio method using GIS on 1:50,000 scale by generating the information about the landslide influencing factors. The study was carried out in the year 2017 on a part of Ravi river catchment along one of the landslide-prone Chamba to Bharmour road corridor of NH-154A in Himachal Pradesh, India. A number of landslide triggering geo-environmental factors like “slope, aspect, relative relief, soil, curvature, Land Use and Land Cover (LULC), lithology, drainage density, and lineament density” were selected for landslide hazard mapping based on landslide inventory. The landslide inventory has been developed using satellite imagery, Google earth and by doing exhaustive field surveys. A digital elevation model was used to generate slope gradient, slope aspect, curvature, and relative relief map of the study area. The other information, i.e., soil maps, geological maps, and toposheets, have been collected from various departments. The landslide hazard zonation map was categorized namely “very high hazard, high hazard, medium hazard, low hazard, and very low hazard.” The results from these two methods have been validated using area under curve (AUC) method. It has been found that hazard zonation map prepared using frequency ratio model had a prediction rate of 75.37% while map prepared using information value method had prediction rate of 78.87%. Hence, on the basis of prediction rate, the landslide hazard zonation map, obtained using information value method, was experienced to be more suitable for the study area.     

Landslide susceptibility and hazard assessment in San Ramón Ravine, Santiago de Chile, from an engineering geological approach

Debris flows and soil and rock slides are among the main geological hazards in the mountain foothills of Central Chile. Geological risk associated with the development of landslides, especially debris flows triggered in the basins of ravines that drain into the capital city, Santiago, has increased in time due to accelerated urban expansion. A landslide hazard evaluation in the San Ramón Ravine, located within the foothills of Santiago is presented. Hazard evaluation is based on a methodology that combines the determination of landslide susceptibility calculated by integration of conditioning factors, with the assessment of slope failure and runout probabilities incorporating geotechnical engineering approaches. The methodology is appropriate for medium or subregional scale studies with limited data. The results show that in San Ramón Ravine the landslide hazard consists mainly of debris flows, rock block slides, rock falls and shallow soil slides. Among these, debris flows are the most important due to the urban area that can be affected. Other case studies show that the method can be used in other regions with minor adaptations for territorial planning or for engineering and environmental purposes.     

Advances in landslide nowcasting: evaluation of a global and regional modeling approach

The increasing availability of remotely sensed data offers a new opportunity to address landslide hazard assessment at larger spatial scales. A prototype global satellite-based landslide hazard algorithm has been developed to identify areas that may experience landslide activity. This system combines a calculation of static landslide susceptibility with satellite-derived rainfall estimates and uses a threshold approach to generate a set of ‘nowcasts’ that classify potentially hazardous areas. A recent evaluation of this algorithm framework found that while this tool represents an important first step in larger-scale near real-time landslide hazard assessment efforts, it requires several modifications before it can be fully realized as an operational tool. This study draws upon a prior work’s recommendations to develop a new approach for considering landslide susceptibility and hazard at the regional scale. This case study calculates a regional susceptibility map using remotely sensed and in situ information and a database of landslides triggered by Hurricane Mitch in 1998 over four countries in Central America. The susceptibility map is evaluated with a regional rainfall intensity–duration triggering threshold and results are compared with the global algorithm framework for the same event. Evaluation of this regional system suggests that this empirically based approach provides one plausible way to approach some of the data and resolution issues identified in the global assessment. The presented methodology is straightforward to implement, improves upon the global approach, and allows for results to be transferable between regions. The results also highlight several remaining challenges, including the empirical nature of the algorithm framework and adequate information for algorithm validation. Conclusions suggest that integrating additional triggering factors such as soil moisture may help to improve algorithm performance accuracy. The regional algorithm scenario represents an important step forward in advancing regional and global-scale landslide hazard assessment.     

Effects of soil heterogeneity on susceptibility of shallow landslides

Uncertainties in parameters of landslide susceptibility models often hinder them from providing accurate spatial and temporal predictions of landslide occurrences. Substantial contribution to the uncertainties in landslide assessment originates from spatially variable geotechnical and hydrological parameters. These input parameters may often vary significantly through space, even within the same geological deposit, and there is a need to quantify the effects of the uncertainties in these parameters. This study addresses this issue with a new three-dimensional probabilistic landslide susceptibility model. The spatial variability of the model parameters is modeled with the random field approach and coupled with the Monte Carlo method to propagate uncertainties from the model parameters to landslide predictions (i.e., factor of safety). The resulting uncertainties in landslide predictions allow the effects of spatial variability in the input parameters to be quantified. The performance of the proposed model in capturing the effect of spatial variability and predicting landslide occurrence has been compared with a conventional physical-based landslide susceptibility model that does not account for three-dimensional effects on slope stability. The results indicate that the proposed model has better performance in landslide prediction with higher accuracy and precision than the conventional model. The novelty of this study is illustrating the effects of the soil heterogeneity on the susceptibility of shallow landslides, which was made possible by the development of a three-dimensional slope stability model that was coupled with random field model and the Monte Carlo method.

     

油气长输管道滑坡地质灾害危险性评价专家系统研究

以运营的油气长输管道工程为依托,在收集、整理、综合分析既有资料基础上,通过对大量滑坡案例进行分析,明确了滑坡地质灾害的主要诱发因素与稳定性控制指标,建立了滑坡危险性评价指标体系。应用专家系统研究方法,建立油气长输管道线路滑坡地质灾害危险性评价专家系统,并对具体工程进行了地质灾害危险性评估,结果符合实际,可为油气长输管道工程地质灾害减灾防灾提供技术支撑。