The mobility of long-runout landslides

Several issues relevant to the mobility of long-runout landslides are examined. A central idea developed in this paper is that the apparent coefficient of friction (ratio of the fall height to the runout distance) commonly used to describe landslide mobility is physically meaningless. It is proposed that the runout distance depends primarily on the volume and not on the fall height, which just adds scatter to the correlation. The negative correlation observed between the apparent coefficient of friction and the volume is just due to the fact that, on the gentle slopes on which landslides travel and come to rest, a large increase in runout distance due to a large volume corresponds to a small increase in the total fall height, hence to a decrease in the apparent coefficient of friction.

It is shown that the spreading of a fluid-absent, granular flow is not able to explain the large runout distances of landslides, and in particular does not allow the centre of mass to travel further than expected for a sliding block. This contrasts with the behaviour of natural landslides, for which the centre of mass is shown to travel much further than expected from a simple Coulomb model. The presence of an interstitial fluid which can partly or entirely support the load of particles allows the effective coefficient of solid friction to be reduced or even suppressed. Air is not efficient for fluidising large landslides and a loose debris cannot slide over a basal layer of entrapped and compressed air, as air would rapidly pass through the debris in the form of bubbles during batch sedimentation. Water is much more efficient as a fluidising medium due to its higher density and viscosity, and its incompressibility. As water is known to enhance the mobility of the saturated debris flows, it is proposed that water is also responsible for the long runout of landslides. This is consistent with the fact that the increase in runout with volume is similar for debris flows and landslides. Field evidence suggests that most landslides are unsaturated with water but not dry, even on Mars.

Comparison of the velocity of well-documented landslides with that predicted by fluid-absent, granular models shows that these models predict landslides that are much faster and less responsive to topography than natural ones. The relatively low velocities of landslides suggest that energy dissipation is dominated by a velocity-dependent stress and that the coefficient of solid friction is very low. This is consistent with the physics of fluidised or partly fluidised debris and suggests that landslide velocity may be controlled by local slope and flow thickness rather than by the initial fall height. In the absence of a supply of fluid at the base, fluidisation requires a net downward flux of sediment, implying some deposition at the base of landslides, which may thus progressively run out of material. In such a model, the spreading of the portion of a landslide beyond a certain distance would primarily depend on the volume passing this distance and not on the total volume of the landslide. Landslide deposits may therefore have self-similar shapes, in which the area covered beyond a certain distance is a constant function of the volume beyond that distance. It is shown that the shape of some well-documented landslide deposits is in reasonable agreement with this prediction. One consequence is that, as recently proposed for debris flows, assessment of hazards related to landslides should be based on the correlation between the volume and the area covered by the deposit, rather than on the apparent coefficient of friction.     

Identification of the affected areas by mass movement through a physically based model of landslide hazard combined with an empirical model of debris flow

In tropical areas, mass movements are common phenomena, especially during periods of heavy rainfall, which frequently take place in the summer season. These phenomena have caused loss of life and serious damage to infrastructure and properties. The most prominent of these phenomena are landslides that can produce debris flows. Thus, this article aims at determining affected areas using a model to predict landslide prone areas (SHALSTAB) combined with an empirical model designed to define the debris flow travel distance and area of deposition. The methodology of this work consists of the following steps: (a) elaboration of a digital elevation model (DEM), (b) application of the deterministic SHALSTAB model to locate the landslide prone areas, (c) identification of the debris flow travel distance and area of deposition, and (d) mapping of the affected areas (landslides and debris flows). This work was developed in an area in which many mass movements occurred after intense rainfall during the summer season (February 1996) in the state of Rio de Janeiro, southeast Brazil. All of the scars produced by that event were mapped, allowing for validation of the applied models. The model results show that the mapped landslide locations can adequately be simulated by the model.     

A comparison of logistic regression-based models of susceptibility to landslides in western Colorado,USA

The Paonia-McClure Pass area of Colorado has been recognized as a region highly susceptible to mass movement. Because of the dynamic nature of this landscape, accurate methods are needed to predict susceptibility to movement of these slopes. The area was evaluated by coupling a geographic information system (GIS) with logistic regression methods to assess susceptibility to landslides. We mapped 735 shallow landslides in the area. Seventeen factors, as predictor variables of landslides, were mapped from aerial photographs, available public data archives, ETM + satellite data, published literature, and frequent field surveys. A logistic regression model was run using landslides as the dependent factor and landslide-causing factors as independent factors (covariates). Landslide data were sampled from the landslide masses, landslide scarps, center of mass of the landslides, and center of scarp of the landslides, and an equal amount of data were collected from areas void of discernible mass movement. Models of susceptibility to landslides for each sampling technique were developed first. Second, landslides were classified as debris flows, debris slides, rock slides, and soil slides and then models of susceptibility to landslides were created for each type of landslide. The prediction accuracies of each model were compared using the Receiver Operating Characteristic (ROC) curve technique. The model, using samples from landslide scarps, has the highest prediction accuracy (85 %), and the model, using samples from landslide mass centers, has the lowest prediction accuracy (83 %) among the models developed from the four techniques of data sampling. Likewise, the model developed for debris slides has the highest prediction accuracy (92 %), and the model developed for soil slides has the lowest prediction accuracy (83 %) among the four types of landslides. Furthermore, prediction from a model developed by combining the four models of the four types of landslides (86 %) is better than the prediction from a model developed by using all landslides together (85 %).     

沟道型滑坡-碎屑流运动距离经验预测模型研究

沟道型滑坡-碎屑流具有隐蔽性强、危险性高、力学机理复杂的特点,研究其运动距离预测模型具有重要的理论意义和实践意义。本文基于遥感GIS技术,结合野外调查,获取了汶川地震触发的38个沟道型滑坡-碎屑流的基础数据。通过相关性分析确定沟道型滑坡-碎屑流最大水平运动距离L的影响因素从大到小依次是滑坡体积V、最大垂直运动距离H、滑源区高差Hs、沟道段坡度β。采用逐步回归方法建立了滑坡-碎屑流最大水平运动距离L的最优多元回归模型,检验结果表明模型具有较高精度。将最优多元回归模型与国际上应用较多的滑坡运动距离和泥石流运动距离预测模型进行对比,表明考虑滑坡体积、地形落差和沟道段坡度的运动距离预测指标体系,具有最高的拟合优度和较好的物理含义,可为沟谷山区滑坡-碎屑流危险性评价提供参考依据。     

影响云南省滑坡泥石流活动的几个自然因素

根据1989～2002年云南省滑坡、泥石流调查资料，在单因素分析的基础上，确定地形、岩土体类型、降雨、地震、活动断裂、气候带和植被覆盖率共7个因素是云南省影响滑坡泥石流的主要自然因素。通过R-型因子分析、逐步回归分析和灰色关联度分析，得出对滑坡影响程度由大到小的因子排序是：海拔和高差、地形坡度、地震、活动断裂、岩组、降雨量；对泥石流影响程度由大到小的因子排序是：活动断裂、海拔和高差、岩组、降雨量、地震。     

Earthquake-induced landslides in Central America

Central America is a region of high seismic activity and the impact of destructive earthquakes is often aggravated by the triggering of landslides. Data are presented for earthquake-triggered landslides in the region and their characteristics are compared with global relationships between the area of landsliding and earthquake magnitude. We find that the areas affected by landslides are similar to other parts of the world but in certain parts of Central America, the numbers of slides are disproportionate for the size of the earthquakes. We also find that there are important differences between the characteristics of landslides in different parts of the Central American isthmus, soil falls and slides in steep slopes in volcanic soils predominate in Guatemala and El Salvador, whereas extensive translational slides in lateritic soils on large slopes are the principal hazard in Costa Rica and Panama. Methods for assessing landslide hazards, considering both rainfall and earthquakes as triggering mechanisms, developed in Costa Rica appear not to be suitable for direct application in the northern countries of the isthmus, for which modified approaches are required.     

汶川震区暴雨泥石流危险范围预测研究

汶川地震发生后,灾区暴雨泥石流活动进入一个新的活跃期。根据对北川震区2008年9月24日暴雨泥石流调查,泥石流流域中地震诱发大量滑坡导致松散物源巨大,泥石流过程的洪峰流量比通常的要大数倍,应用以往泥石流危险范围预测模型进行计算的结果与实际的误差较大。因此,需要建立适用于强震区的泥石流危险范围预测方法。本文以9.24北川暴雨泥石流为典型实例,结合野外调查,利用震后高分辨航空图像和9.24暴雨后SPOT5图像分别提取泥石流发生前流域中滑坡物源储量及发生后形成的堆积扇特征数据,应用多元回归方法建立了汶川震区泥石流危险范围预测模型,该方法可用于估算泥石流最大堆积距离和堆积宽度。验证和应用结果表明:该模型适用于强震区泥石流危险范围的预测,模型方法可为震区重建中安全地段选择和未来地震区风险管理提供重要依据。     

Pacific Basin tsunami hazards associated with mass flows in the Aleutian arc of Alaska

We analyze mass-flow tsunami generation for selected areas within the Aleutian arc of Alaska using results from numerical simulation of hypothetical but plausible mass-flow sources such as submarine landslides and volcanic debris avalanches. The Aleutian arc consists of a chain of volcanic mountains, volcanic islands, and submarine canyons, surrounded by a low-relief continental shelf above about 1000–2000 m water depth. Parts of the arc are fragmented into a series of fault-bounded blocks, tens to hundreds of kilometers in length, and separated from one another by distinctive fault-controlled canyons that are roughly normal to the arc axis. The canyons are natural regions for the accumulation and conveyance of sediment derived from glacial and volcanic processes. The volcanic islands in the region include a number of historically active volcanoes and some possess geological evidence for large-scale sector collapse into the sea. Large scale mass-flow deposits have not been mapped on the seafloor south of the Aleutian Islands, in part because most of the area has never been examined at the resolution required to identify such features, and in part because of the complex nature of erosional and depositional processes. Extensive submarine landslide deposits and debris flows are known on the north side of the arc and are common in similar settings elsewhere and thus they likely exist on the trench slope south of the Aleutian Islands. Because the Aleutian arc is surrounded by deep, open ocean, mass flows of unconsolidated debris that originate either as submarine landslides or as volcanic debris avalanches entering the sea may be potential tsunami sources.To test this hypothesis we present a series of numerical simulations of submarine mass-flow initiated tsunamis from eight different source areas. We consider four submarine mass flows originating in submarine canyons and four flows that evolve from submarine landslides on the trench slope. The flows have lengths that range from 40 to 80 km, maximum thicknesses of 400–800 m, and maximum widths of 10–40 km. We also evaluate tsunami generation by volcanic debris avalanches associated with flank collapse, at four locations (Makushin, Cleveland, Seguam and Yunaska SW volcanoes), which represent large to moderate sized events in this region. We calculate tsunami sources using the numerical model TOPICS and simulate wave propagation across the Pacific using a spherical Boussinesq model, which is a modified version of the public domain code FUNWAVE. Our numerical simulations indicate that geologically plausible mass flows originating in the North Pacific near the Aleutian Islands can indeed generate large local tsunamis as well as large transoceanic tsunamis. These waves may be several meters in elevation at distal locations, such as Japan, Hawaii, and along the North and South American coastlines where they would constitute significant hazards.     

Numerical simulations of flow motion and deposition characteristics of granular debris flows

Flow motion and deposition characteristics of debris flows are of concern regarding land use planning and management. A simple model for the prediction of mentioned characteristics has been developed, incorporating a friction–collision rheological model. It demonstrated to be able to satisfactorily simulate the two-dimensional behavior of laboratory results and the one-dimensional behavior of two real debris-flow events. The numerical results show that the topography of the channel bed, the yield stress level of the debris flows, and the inflow pattern have significant influence on the simulated flow motion and deposition characteristics of debris flows. In addition, the predicted run-out distance has been compared with analytical solutions and field observations. The model could be employed for the preliminary evaluation of one-dimensional run-out distance of granular debris flows provided that the volume of the debris involved in the initial mobilization is assumed.     

Multi-geohazards susceptibility mapping based on machine learning—a case study in Jiuzhaigou,China

Jiuzhaigou, located in the transitional area between the Qinghai–Tibet Plateau and the Sichuan Basin, is highly prone to geological hazards (e.g., rock fall, landslide, and debris flow). High-performance-based hazard prediction models, therefore, are urgently required to prevent related hazards and manage potential emergencies. Current researches mainly focus on susceptibility of single hazard but ignore that different types of geological hazards might occur simultaneously under a complex environment. Here, we firstly built a multi-geohazard inventory from 2000 to 2015 based on a geographical information system and used satellite data in Google earth and then chose twelve conditioning factors and three machine learning methods—random forest, support vector machine, and extreme gradient boosting (XGBoost)—to generate rock fall, landslide, and debris flow susceptibility maps. The results show that debris flow models presented the best prediction capabilities [area under the receiver operating characteristic curve (AUC 0.95)], followed by rock fall (AUC 0.94) and landslide (AUC 0.85). Additionally, XGBoost outperformed the other two methods with the highest AUC of 0.93. All three methods with AUC values larger than 0.84 suggest that these models have fairly good performance to assess geological hazards susceptibility. Finally, evolution index was constructed based on a joint probability of these three hazard models to predict the evolution tendency of 35 unstable slopes in Jiuzhaigou. The results show that these unstable slopes are likely to evolve into debris flows with a probability of 46%, followed by landslides (43%) and rock falls (29%). Higher susceptibility areas for geohazards were mainly located in the southeast and middle of Jiuzhaigou, implying geohazards prevention and mitigation measures should be taken there in near future.

     

Slope failures on the flanks of the western Canary Islands

Landslides have been a key process in the evolution of the western Canary Islands. The younger and more volcanically active Canary Islands, El Hierro, La Palma and Tenerife, show the clearest evidence of recent landslide activity. The evidence includes landslide scars on the island flanks, debris deposits on the lower island slopes, and volcaniclastic turbidites on the floor of the adjacent ocean basins. At least 14 large landslides have occurred on the flanks of the El Hierro, La Palma and Tenerife, the majority of these in the last 1 million years, with the youngest, on the northwest flank of El Hierro, as recent as 15 thousand years in age. Older landslides undoubtedly occurred, but are difficult to quantify because the evidence is buried beneath younger volcanic rocks and sediments. Landslides on the Canary Island flanks can be categorised as debris avalanches, slumps or debris flows. Debris avalanches are long runout catastrophic failures which typically affect only the superficial part of the island volcanic sequence, up to a maximum thickness of 1 to 2 km. They are the commonest type of landslide mapped. In contrast, slumps move short distances and are deep-rooted landslides which may affect the entire thickness of the volcanic edifice. Debris flows are defined as landslides which primarily affect the sedimentary cover of the submarine island flanks. Some landslides are complex events involving more than one of the above end-member processes.Individual debris avalanches have volumes in the range of 50–500 km³, cover several thousand km² of seafloor, and have runout distances of up to 130 km from source. Overall, debris avalanche deposits account for about 10% of the total volcanic edifices of the small, relatively young islands of El Hierro and La Palma. Some parameters, such as deposit volumes and landslide ages, are difficult to quantify. The key characteristics of debris avalanches include a relatively narrow headwall and chute above 3000 m water depth on the island flanks, broadening into a depositional lobe below 3000 m. Debris avalanche deposits have a typically blocky morphology, with individual blocks up to a kilometre or more in diameter. However, considerable variation exists between different avalanche deposits. At one extreme, the El Golfo debris avalanche on El Hierro has few large blocks scattered randomly across the avalanche surface. At the other, Icod on the north flank of Tenerife has much more numerous but smaller blocks over most of its surface, with a few very large blocks confined to the margins of the deposit. Icod also exhibits flow structures (longitudinal shears and pressure ridges) that are absent in El Golfo. The primary controls on the block structure and distribution are inferred to be related to the nature of the landslide material and to flow processes. Observations in experimental debris flows show that the differences between the El Golfo and Icod landslide deposits are probably controlled by the greater proportion of fine grained material in the Icod landslide. This, in turn, relates to the nature of the failed volcanic rocks, which are almost entirely basalt on El Hierro but include a much greater proportion of pyroclastic deposits on Tenerife.Landslide occurrence appears to be primarily controlled by the locations of volcanic rift zones on the islands, with landslides propagating perpendicular to the rift orientation. However, this does not explain the uneven distribution of landslides on some islands which seems to indicate that unstable flanks are a ‘weakness’ that can be carried forward during island development. This may occur because certain island flanks are steeper, extend to greater water depths or are less buttressed by the surrounding topography, and because volcanic production following a landslide my be concentrated in the landslide scar, thus focussing subsequent landslide potential in this area. Landslides are primarily a result of volcanic construction to a point where the mass of volcanic products fails under its own weight. Although the actual triggering factors are poorly understood, they may include or be influenced by dyke intrusion, pore pressure changes related to intrusion, seismicity or sealevel/climate changes. A possible relationship between caldera collapse and landsliding on Tenerife is not, in our interpretation, supported by the available evidence.     

Velocity and runout simulation of destructive debris flows and debris avalanches in pyroclastic deposits,Campania region,Italy

The Campanian Apennines are characterized by the presence of monocline ridges, mainly formed by limestone. During the periods of volcanic activity of the Somma-Vesuvius and Phlegrean Fields, the ridges were mantled with pyroclastic materials in varying thickness. The pyroclastics have been involved in destructive landslides both in historical time and in the recent past (1997, 1998, 1999). The landslides occur following intense and prolonged rainfalls. In some cases, landslides extended up to 4 km into the surrounding lowlands and reached towns, causing severe destruction and over 200 deaths. Generally, the landslides begin as small debris slides that develop into large, shallow debris avalanches or debris flows involving pyroclastic horizons and colluvial soils (0.5–2 m thick) on steep and vegetated slopes, often at the heads of gullies. During motion, the landslide materials eroded vegetation and soils from the slope, so that the moving material volume tended to increase. Then, proceeding towards and beyond the base of the slopes, the phenomena evolved into hyperconcentrated streamflow due to dilution by incorporating water. The results of motion analyses are described. An empirical rheological relationship was used including two principal terms that depend on the total normal stress and on the flow velocity. On this basis, the model has simulated the velocity and duration of debris avalanches and the distribution of the deposits. The selected areas were those of Sarno/Quindici and Cervinara, where a large amount of data is available both on the material properties and geomorphological setting. It was found that the majority of the cases at the two sites can be simulated successfully with only one specific pair of rheologic parameters. This provides the possibility for first-order predictions to be made of the motion of future landslides. Such predictions will be a valuable tool for outlining potential hazard areas and designing remedial measures.     

Distribution and characteristics of landslides induced by the Iwate–Miyagi Nairiku Earthquake in 2008 in Tohoku District, Northeast Japan

The Iwate–Miyagi Nairiku Earthquake in 2008, whose seismic intensity was M. 7.2 in Japan Meteorological Agency (JMA) scale, induced innumerable landslides on the southern flank of Mt. Kurikoma volcano allocated along the Ou Backbone Range in Northeast Japan. Most landslides are detected in a hanging wall side of the seismic fault. Those landslides are classified into five types: deep-seated slide, debris slide, shallow debris slide, secondary shallow debris slide, and debris flow. Most common landslide types induced by the earthquake are shallow debris slides and subsequent debris flows. They are intensively distributed along steep gorges incising a volcanic skirt of Mt. Kurikoma, consisting of welded ignimbrite of the Pleistocene age. Debris flows are also distributed even along gentle river floors in the southern lower flank of the volcano. The area of densely distributed debris slides, shallow debris slides, and debris flows is concordant with that of severe seismic tremor. Thus, genetic processes of landslides induced by the Iwate–Miyagi Nairiku Earthquake in 2008 are attributed to multiple causative factors such as geology, topography, and seismic force.     

Analysis of the relationship of landslide occurrence with rainfall: a case study of Wudu County,China

Landslides are a significant hazard in many parts of the world and represent an important geohazard in China. Rainfall is the primary triggering agent for landslides and often used for prediction slope failures. However, the relationship between rainfall and landslide occurrences is very complex. Great efforts have been made on the study of regional rainfall-induced landslide forecasting models in recent years; still, there is no commonly accepted method for rainfall-induced landslide prediction. In this paper, the quantitative antecedent soil water status (ASWS) model is applied to investigate the influence of daily and antecedent rainfall on the triggering of landslides and debris flows. The study area is Wudu County in Gansu Province, an area which exhibits frequent landslide occurrences. The results demonstrate a significant influence of high intensity rainfall events on landslide triggering. Still, antecedent rainfall conditions are very important and once a threshold of approximately 20 mm is exceeded, landslides and debris flows can occur even without additional rainfall. The study presented could also facilitate the implementation of a regional forecasting scheme once additional validation has been carried out.     

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.     

Modeling debris flow initiation and run-out in recently burned areas using data-driven methods

In the framework of the landslide susceptibility assessment, the maps produced should include not only the landslide initiation areas, but also those areas potentially affected by the traveling mobilized material. To achieve this purpose, the susceptibility analysis must be separated in two distinct components: (1) The first one, which is also the most discussed in the literature, deals with the susceptibility to failure, and (2) the second component refers to the run-out modeling using the initiation areas as an input. Therefore, in this research we present a debris flow susceptibility assessment in a recently burned area in a mountain zone in central Portugal. The modeling of debris flow initiation areas is performed using two statistical methods: a bivariate (information value) and a multivariate (logistic regression). The independent validation of the results generated areas under the receiver operating characteristic curves between 0.91 and 0.98. The slope angle, plan curvature, soil thickness and lithology proved to be the most relevant predisposing factors for the debris flow initiation in recently burned areas. The run-out is simulated by applying two different methods: the empirical model Flow Path Assessment of Gravitational Hazards at a Regional Scale (Flow-R) and the hydrological algorithm D-infinity downslope influence (DI). The run-out modeling of the 36 initiation areas included in the debris flow inventory delivered a true positive rate of 83.5% for Flow-R and 80.5% for DI, reflecting a good performance of both models. Finally, the susceptibility map for the entire basin including both the initiation and the run-out areas in a scenario of a recent wildfire was produced by combining the four models mentioned above.     

汶川八级地震滑坡高速远程特征分析

汶川地震触发的高速远程滑坡主要沿龙门山主中央断裂带汶川映秀安县高川北川县城平武南坝青川一线地震破裂带展布。由于获得了1.5g以上的抛掷加速度,具有明显的气垫效应,估计最大滑动速度一般大于70ms-1,滑动距离一般为滑体启动时长度的数倍甚至10多倍,堆积成坝形成多处堰塞湖,最大滑行距离达3.2km。本文重点解剖了位于地震破裂带南西段(初始震中)的汶川映秀牛圈沟滑坡碎屑流、位于地震破裂带中段的北川城西滑坡和位于地震破裂带北东段青川东河口滑坡碎屑流3个典型实例,认为具有如下特征:(1）岩性条件:母岩遭受长期构造动力作用,呈碎裂岩体,后期被强烈风化,岩体极为破碎;(2）抛掷效应:位于汶川地震主断裂带或附近,垂直加速度大于水平加速度,强地面运动持时长,岩体发生振胀和抛掷;(3）碰撞效应:上部滑坡体发生高位剪出和高位撞击,致使岩体碎屑化;(4）铲刮效应:撞击作用导致下部山体被铲刮,形成次级滑坡,为碎屑流体提供了足够展翼和抛洒物源体积;(5）气垫效应:碎屑化岩体快速抛掷导致下部沟谷空气迅速谷状圈闭和向下紊流,形成气垫效应,或者,在下部地形开阔地带压缩空气呈层流状态致使滑体凌空飞行。     

The deformation analysis of Wenjiagou giant landslide by the distributed scatterer interferometry technique

After the deadly Ms 8.0 Wenchuan earthquake, the Wenjiagou landslide produced steep topography, a narrow gully and abundant loose sediments; these factors have contributed to the high debris flow risk in the Wenjiagou area during subsequent rainy seasons. At least five debris flows have occurred in the Wenjiagou area between September 24, 2008, and September 18, 2010, which resulted in seven casualties and an economic loss of approximately 446 million RMB. To reduce the risk of debris flows and landslides, the Wenjiagou Valley Debris Flow Control Project (WVDFCP), which cost over 2 billion RMB, was carried out and completed in 2011. The control measures of the project effectively reduced the scale and damage of the following debris flows. In this paper, the recent deformation of the giant landslide and its effect on the WVDFCP are evaluated by applying a time-series interferometric synthetic aperture radar (InSAR) technique based on distributed scatterers (DSs) to the Radardat-2 SAR data collected from June 2014 to September 2015. In addition, the experimental results show that most areas of the landslide are stable, with an average deformation rate of less than 5.0 mm/year. The results demonstrate that the control measures of the WVDFCP not only reduced the damage caused by the later debris flows but also contributed to the consolidation of the loose sediments in the Wenjiagou landslide area. The time-series InSAR technique based on the DSs of high-resolution SAR images is an important tool for deformation monitoring of earthquake-induced landslides.     

5.12震源区牛眠沟暴雨滑坡泥石流预测模型

牛眠沟研究区位于2008-05-12汶川大地震线性震源的南端,受强烈地震力作用,区内山体遭受严重破坏,发生多处滑坡和泥石流灾害。根据已建立的暴雨滑坡、泥石流预测概念模型,暴雨滑坡、泥石流预测可视为判断滑坡形成的地质环境和确定触发滑坡的降雨特征。查明研究区地质环境及灾害特征,确定了产生滑坡、泥石流的必要地质环境因子,以数字滑坡技术获取这些因子数据,代入模型,即可评价研究区各处、各沟谷发生滑坡、泥石流的危险程度;与相似地质环境及气候条件进行类比,确定研究区触发滑坡、泥石流的降雨特征及降雨量阈值后,最终建立暴雨滑坡、泥石流预测模型。据此模型进行研究区暴雨滑坡、泥石流预测,实地验证表明滑坡、泥石流发生位置的准确率>90%。     

Relationships between natural terrain landslide magnitudes and triggering rainfall based on a large landslide inventory in Hong Kong

Rain-induced landslides are recognized as one of the most catastrophic hazards on hilly terrains. To develop strategies for landslide risk assessment and management, it is necessary to estimate not only the rainfall threshold for the initiation of landslides, but also the likely magnitudes of landslides triggered by a storm of a given intensity. In this study, the frequency distributions of both open hillside landslides and channelized debris flows in Hong Kong are established on the basis of the Enhanced Natural Terrain Landslide Inventory (ENTLI) with 19,763 records in Hong Kong up to 2013. The landslide magnitudes are measured in terms of the number, scar area, volume, or density of landslides. The mean values of the scar areas and volumes are 55.2 m² and 102.0 m³, respectively, for the open hillside landslides and 91.3 m² and 166.5 m³, respectively, for the channelized debris flows. Empirical correlations between the numbers, scar areas, and volumes of hillside landslides or channelized debris flows and the maximum rolling rainfall intensities of different periods have been derived. The maximum rolling 4- to 24-h rainfall amounts provide better predictions compared with those with the maximum rolling 1-h rainfall. Maximum rolling rainfall intensity-duration thresholds identifying the likely rainfall conditions that yield natural terrain landslides or debris flows of different magnitudes are also proposed. The initiation rainfall thresholds are identified as 75, 90, 100, 120, 150, 180, and 200 mm for the maximum rolling 1-, 2-, 4-, 6-, 8-, 12-, and 24-h rainfall, respectively.