江西省资溪县西源滑坡成因分析及其治理

以资溪县西源滑坡为研究对象,根据勘察资料采用经典的传递系数法对天然状态和饱水状态滑坡的稳定性进行了计算,表明自然状态滑坡处于基本稳定状态,饱和状态滑坡处于不稳定状态;根据滑坡体勘察成果,采用抗滑支挡和地表排水综合治理措施,取得了良好成效。     

浙江地区引发滑坡的降雨强度-历时关系

由于独特的地理位置,复杂的地质、地形和气候背景,浙江成为中国降雨型滑坡（土体和岩体滑动,也包括泥石流和崩塌等）最频发的地区之一。为评价浙江地区的滑坡灾害,本文对该地区1990年至2003年雨量站记录的降雨数据进行了详细分析,确定了引发土体滑坡-泥石流的降雨强度―历时下限。     

传递系数法和层次分析法在滑坡稳定性评价中的应用

根据滑坡岩土体的物理力学性质及形成原因,采用传递系数法对江西省龙南县某滑坡在降雨作用下的稳定性进行定量评价,并运用层次分析法对该滑坡发生及危害人类生命与财产安全的可能性大小进行计算,为灾害易发性分区和防治分区提供依据。     

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.     

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。     

Evolution of natural risk: analysing changing landslide hazard in Wellington,Aotearoa/New Zealand

This paper addresses the temporal variation of rainfall-triggered landslide hazard within the broader context of natural risk evolution. Analysis of a sequence of aerial photos covering a period of 60 years allowed the establishment of a record of landsliding for a site in the Wellington region, New Zealand. The data show one very dominant peak in the magnitude of landslide occurrence in the late 1970s, followed by a continuous decrease. Landslide hazard can be expressed by the frequency and magnitude of the landslide events, with the total surface area affected used as a surrogate for magnitude. However, the distinct decline of landslide magnitude through time from the 1980s onwards indicates that landslide hazard may change with time. This possibility is further explored by correlating potential landslide triggering storms with the magnitude of the landslide event, using the ‘Antecedent Soil Water Status’ model in combination with daily rainfall. The relation between magnitudes of rainfall and magnitudes of landslide events is found to be weak, suggesting that a given ‘Critical Water Content’ (antecedent soil water status and rainfall on the day) does not produce similar magnitudes of landsliding. Furthermore, the study shows that reactivation of previous landslides before the peak landslide occurrence of the late 1970s is low, while the situation is reversed after this peak and reactivation in the subsequent years plays a larger role. It is concluded that the pattern of landsliding cannot be explained by the pattern of rainfall and other factors are controlling the variation of landslide hazard in time. A possible explanation is a change of the geomorphological system with time, instigated by a massive period of landsliding (the late 1970s peak). Subsequent sediment exhaustion of source areas resulting from this period appears to alter the system’s subsequent reaction to an external trigger such as rainfall. The study demonstrates that landslide hazard analysis in general should not rely on the integral of the frequency–magnitude relationship only, but should include potential non-linear changes of system settings to increase the understanding of future system behaviour, and therefore hazard and risk.

基于确定性系数的降雨型滑坡影响因子敏感性分析

本文选择东南沿海地区具有典型降雨型滑坡的淳安县作为研究区,在完成全县地质灾害详细调查的基础上,选取高程、坡度、坡向、曲率、工程地质岩组、距断层距离、距道路距离、土地利用和植被等9个滑坡影响因子,利用GIS技术与确定性系数分析方法,对这9个影响因子开展敏感性分析。研究结果表明:(1) 寒武、震旦、石炭和白垩系是滑坡易发地层,侵入岩组、紫红色砂岩、碳酸盐岩夹碎屑岩、碳酸盐岩为主的岩组是滑坡高敏感性岩组;滑坡受断层影响总体上随着距离断层由近及远逐渐降低;(2) 坡度范围10°~35°是滑坡的易发坡度,30°~35°滑坡数量达到峰值;SE和S等朝南坡向是滑坡最易发坡向;高程范围为100~200m是滑坡最易发区间;凹坡最易发生滑坡,而凸坡则滑坡敏感性最差;非林地、茶叶、竹林和经济林等是滑坡高敏感植被类型;(3) 住宅用地、耕地、园地等与人类活动密切相关的用地类型是滑坡易发地类;距道路距离因子对滑坡敏感性低,相关性不明显。上述各滑坡影响因子最利于滑坡发生的数值区间确定,将为研究区进一步开展降雨型滑坡区域易发性评价及预测奠定基础。     

基于失效概率的边坡降雨阈值曲面探讨

降雨是诱发边坡变形失稳的主要因素,而针对降雨型边坡的预警预报也一直是工程领域的核心问题。本文将蒙特卡罗方法引入降雨型滑坡的预警预报,首先基于正态分布的岩土体物理力学参数,建立了边坡的有限元数值计算模型,并分析了9种不同型式降雨下边坡稳定性系数的变化情况。结果显示递增型降雨对边坡的稳定性尤为不利,均匀型降雨次之,递减型降雨影响最小。其次,将降雨过程划分为前期降雨+当期降雨,并确定了前期降雨对于当期降雨的有效时间为6 d。最后,论文结合可靠度理论,选取失效概率Pf=10%作为预警指标,通过把前期降雨引入降雨强度-降雨历时关系曲线并作为第三坐标轴,最终将该曲线扩展成为前期降雨(A)-当期降雨(I)-降雨历时(D)曲面(A-I-D阈值曲面),研究结果对于降雨型边坡的预警预报具有一定的指导意义。     

Interpretation of probability of landsliding triggered by rainfall

This paper is a contribution to an important aspect of the systematic and quantitative assessment of landslide hazard and risk. The focus is on site-specific and detailed assessment for rainfall-triggered landslides and, in particular, on the estimation and interpretation of the temporal probability of landsliding. Historical rainfall data over a 109-year period were analysed with particular reference to a site along the Unanderra and Moss Vale Railway Line in the State of New South Wales, Australia. It is shown that the recurrence interval of landsliding and hence annual probability of occurrence is subject to significant uncertainty and that it cannot be regarded as a constant. Accordingly landslide hazard varies spatially as well as being a function of time. For the example case study considered in this paper the annual probability of landslide occurrence was estimated to be in the range 0.026–0.172. However, the mean annual probability of landslide reactivation was estimated to be in the range 0.037–0.078. Utilisation of methods for probability assessment proposed in this paper will contribute to more realistic assessment of hazard and risk and, therefore, to more efficient risk management.     

Seismotectonics and Earth tides

The results of the processing and analysis of the global earthquake distribution (more than 250000 events based on the ISC catalog) and the study of moonquakes distribution (about 900 events based on the published materials) are presented. It was found that the number of events and the energy for both cases show a bimodal distribution with maximums in the middle latitudes, zero values at the polarcaps, and a local minimum in the vicinity of the equator. The probable influence of tectonic processes on the revealed character of the seismic event distribution is analyzed, and the role of Earth tides in the activation of the seismicity in the symmetric zones on both sides of the equator is shown.     

An empirical ensemble rainfall nowcasting model using multi-scaled analogues

Natural Hazards - Short-term rainfall prediction with high spatial and temporal resolution is of great importance to rainfall-triggered natural hazards such as landslide, flood, and debris flow. An...     

Global landslide and avalanche hotspots

Allocating resources for natural hazard risk management has high priority in development banks and international agencies working in developing countries. Global hazard and risk maps for landslides and avalanches were developed to identify the most exposed countries. Based on the global datasets of climate, lithology, earthquake activity, and topography, areas with the highest hazard, or “hotspots”, were identified. The applied model was based on classed values of all input data. The model output is a landslide and avalanche hazard index, which is globally scaled into nine levels. The model results were calibrated and validated in selected areas where good data on slide events exist. The results from the landslide and avalanche hazard model together with global population data were then used as input for the risk assessment. Regions with the highest risk can be found in Colombia, Tajikistan, India, and Nepal where the estimated number of people killed per year per 100 km² was found to be greater than one. The model made a reasonable prediction of the landslide hazard in 240 of 249 countries. More and better input data could improve the model further. Future work will focus on selected areas to study the applicability of the model on national and regional scales.     

Rainfall thresholds for prediction of shallow landslides around Chamoli-Joshimath region,Garhwal Himalayas,India

Majority of landslides in the Indian sub-continent are triggered by rainfall. Several attempts in the global scenario have been made to establish rainfall thresholds in terms of intensity-duration and antecedent rainfall models on global, regional and local scales for the occurrence of landslides. However, in the context of the Indian Himalayas, the rainfall thresholds for landslide occurrences are not yet understood fully. Neither on regional scale nor on local scale, establishing such rainfall thresholds for landslide occurrences in Indian Himalayas has yet been attempted. This paper presents an attempt towards deriving local rainfall thresholds for landslides based on daily rainfall data in and around Chamoli-Joshimath region of the Garhwal Himalayas, India. Around 128 landslides taken place in last 4 years from 2009 to 2012 have been studied to derive rainfall thresholds. Out of 128 landslides, however, rainfall events pertaining to 81 landslides were analysed to yield an empirical intensity–duration threshold for landslide occurrences. The rainfall threshold relationship fitted to the lower boundary of the landslide triggering rainfall events is I?=?1.82 D ^?0.23 (I?=?rainfall intensity in millimeters per hour and D?=?duration in hours). It is revealed that for rainfall events of shorter duration (≤24 h) with a rainfall intensity of 0.87 mm/h, the risk of landslide occurrence in this part of the terrain is expected to be high. Also, the role of antecedent rainfall in causing landslides was analysed by considering daily rainfall at failure and different period cumulative rainfall prior to failure considering all 128 landslides. It is observed that a minimum 10-day antecedent rainfall of 55 mm and a 20-day antecedent rainfall of 185 mm are required for the initiation of landslides in this area. These rainfall thresholds presented in this paper may be improved with the hourly rainfall data vis-à-vis landslide occurrences and also data of later years. However, these thresholds may be used in landslide warning systems for this particular region of the Garhwal Himalayas to guide the traffic and provide safety to the tourists travelling along this pilgrim route during monsoon seasons.     

aiNet- and GIS-based regional prediction system for the spatial and temporal probability of rainfall-triggered landslides

We developed a real-time forecasting system, aiNet-GISPSRIL, for evaluating the spatiotemporal probability of occurrence of rainfall-triggered landslides. In this system, the aiNet (a kind of artificial neutral network based on a self-organizing system) and GIS are merged for integrating the rainfall conditions into various environmental factors that influence the landslide occurrence and for simulating the complex non-linear relationships between landslide occurrence and its related conditions. Zhejiang Province (101,800 km² in area), located in the southeast coastal region of China, is highly prone to the occurrence of landslides during intensive rainfall. Since 2003, the aiNet-GISPSRIL has been used to predict landslides during the rainy seasons in the region. The aiNet-GISPSRIL uses the regional 24-h forecast rainfall information and the real-time rainfall monitoring data from the rain-gauge network as its inputs, and then provides 24-h forecast of the landslide probability for every 1 × 1-km grid cell within the region. Verification studies on the performance of the aiNet-GISPSRIL show that the system has successfully predicted the dates and localities of 304 landslides (accounting for 66.2% of reported landslides during the period). During the period from 2003 to 2007, because the system provided the probability levels of landslide occurrences up to 24-h in advance, gave locations of potential landslides, and timely warned those individuals at high-risk areas, more than 1700 persons living in the risk sites had been evacuated to safe ground before the landslides occurred and thus casualty was avoided. This highly computerized, easy-operating system can be used as a prototype for developing forecasting systems in other regions that are prone to rainfall-triggered landslides.     

Transient modeling of regional rainfall-triggered shallow landslides

This study investigates the transient modeling of regional rainfall-triggered shallow landslides in unsaturated soil using the Richards equation. To model shallow landslides within a distributed regional-scale framework, infinite slope stability analysis coupled with the hydrological model with consideration of the fluctuation of time-dependent pore water pressure and the soil–water characteristic curve proposed by van Genuchten was developed. The validity of the proposed model is established through several test problems by comparing the numerical results with the analytical solutions. A new procedure to set up wide-range shallow landslide analysis and to integrate regional distribution variations for input data such as geology, groundwater level, hydrogeological characteristics, and rainfall intensity and duration was presented. The results obtained demonstrate that the computed distribution of the safety factor is consistent with the distribution of actual landslides. In addition, the fluctuation of pore water pressure in unsaturated soil dominates the stability of landslides during typhoons accompanied by heavy rainfall. The findings observed in this study are a fundamental contribution to environmental effects for landslides in areas with higher occurrence and vulnerability to extreme precipitation.     

浙西梅雨滑坡易发性评价模型对比

我国目前滑坡易发性评价研究主要集中在西南地区,对东南部降雨引发特别是梅雨引发的滑坡研究较少.选取浙江省西北部梅雨控制区淳安县为研究区,通过遥感解译结合野外详细调查,共确定滑坡596处,并建立滑坡编录数据库.选取高程、坡向、坡度、曲率、工程岩组、断层、道路、建设用地、植被等9个滑坡影响因子,基于GIS栅格分析方法,采用人工神经网络(ANN)、logistic回归和信息量3种评价模型,分别对32种不同影响因子组合进行滑坡易发性对比评价,得到滑坡易发性指数图.应用评价曲线下面积AUC(area under curve)对评价结果进行检验,ANN、logistic回归和信息量3种模型的正确率分别是93.75%、89.76%和90.06%;采用淳安县2014年梅汛期发生的13处滑坡作为预测样本,3种模型预测率分别是94.75%、94.33%和77.21%.上述分析结果表明:ANN模型优于其他两者.以ANN模型评价结果指数图为基础进行易发性分区,采用滑坡强度指标进行分区结果检验,滑坡强度值由易发性低、较低、中和高依次递增,说明分区结果合理.研究成果可以为浙西降雨型滑坡特别是由梅雨引发滑坡的易发性评价提供参考.      

The Rwenzori Mountains,a landslide-prone region?

With its exceptionally steep topography, wet climate, and active faulting, landslides can be expected to occur in the Rwenzori Mountains. Whether or not this region is prone to landsliding and more generally whether global landslide inventories and hazard assessments are accurate in data-poor regions such as the East African highlands are thus far unclear. In order to address these questions, a first landslide inventory based on archive information is built for the Rwenzori Mountains. In total, 48 landslide and flash flood events, or combinations of these, are found. They caused 56 fatalities and considerable damage to road infrastructure, buildings, and cropland, and rendered over 14,000 persons homeless. These numbers indicate that the Rwenzori Mountains are landslide-prone and that the impact of these events is significant. Although not based on field investigations but on archive data from media reports and laymen accounts, our approach provides a useful complement to global inventories overlooking this region and increases our understanding of the phenomenon in the Rwenzori Mountains. Considering the severe impacts of landslides, the population growth and related anthropogenic interventions, and the likelihood of more intense rainfall conditions, there is an urgent need to invest in research on disaster risk reduction strategies in this region and other similar highland areas of Africa.     

A new physically based stochastic event catalog for hail in Europe

Hailstorms represent one of the major sources of damage and insurance loss to residential, commercial, and agricultural assets in several parts of Central Europe. However, there is little knowledge of hail risk across Europe beyond local historical damage reports due to the relative rarity of severe hail events and the lack of uniform detection methods. Here we present a new stochastic catalog of hailstorms for Europe. It is based on satellite observations of overshooting cloud tops (OT) that indicate very strong convective updrafts and hail reports from the European Severe Weather Database (ESWD). Historic hail events are defined based on OT detections from satellite infrared brightness temperatures between 2004 and 2011 for the warm seasons (April–September). The satellite-based historical event properties are complemented by hailstone observations from ESWD to stochastically simulate more than 1 million individual events with an event footprint resolution of 10 km. The final hail event catalog presented in this paper is the first one with a spatial event distribution that is based on a single homogeneous observation source over Europe. Areas of high hail probability or hail risk are found over Central and Southern Europe, including mountainous regions such as the Alps or the Pyrenees. Another region of relatively high hail risk is present over central Eastern Europe.     

Landslide susceptibility mapping and factor effect analysis using frequency ratio in a catchment scale: a case study from Garuwa sub-basin,East Nepal

For assessing landslide susceptibility, the spatial distribution of landslides in the field is essential. The landslide inventory map is prepared on the basis of historical information of individual landslide events from different sources such as previously published reports, satellite imageries, aerial photographs and interview with local inhabitants. Then, the distribution of landslides in the study area is verified with field surveys. However, the selection of contributing factors for modelling landslide susceptibility is an inhibit task. The previous studies show that the factors are chosen as per availability of data. This paper documents the landslide susceptibility mapping in the Garuwa sub-basin, East Nepal using frequency ratio method. Nine different contributing factors are considered: slope aspect, slope angle, slope shape, relative relief, geology, distance from faults, land use, distance from drainage and annual rainfall. To analyse the effect of contributing factors, the landslide susceptibility index maps are generated four times using (a) topographical factors and geological factors, (b) topographical factors, geological factors and land use, (c) topographical factors, geological factors, land use and drainage and (d) all nine causative factors. By comparing with the pre-existing landslides, the fourth case (considering all nine causative factors) yields the best success rate accuracy, i.e. 81.19 %, which is then used to produce the final landslide susceptibility zonation map. Then, the final landslide susceptibility map is validated through chi-square test. The standard chi-square value with 3 degrees of freedom at the 0.001 significance level is 16.3, whereas the calculated chi-square value is 7,125.79. Since the calculated chi-square value is greater than the standard chi-square value, it can be concluded that the landslide susceptibility map is considered as statistically significant. Moreover, the results show that the predicted susceptibility levels are found to be in good agreement with the past landslide occurrences.     

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.