Prediction on landslide displacement using a new combination model: a case study of Qinglong landslide in China

Prediction on landslide displacement plays an important role in landslide early warning. Many models have been proposed for this purpose. However, the accuracy of the prediction results by these models often varies under different conditions. Rational evaluation and comprehensive consideration of these results still remain a scientific challenge. A new comprehensive combination model is proposed to predict the landslides displacement. The elementary displacement prediction is made by the support vector machine model, the exponential smoothing model, and the gray model (GM)(1,1). The results of the models are comprehensively evaluated by combining the results and introducing the accuracy matrix. The optimal weight in the evaluation work is obtained. A rational prediction result can be attained based on the so-called combination model. The proposed method has been tested by the application of Qinglong landslides in Guizhou Province, China. The comparison between the prediction results and in situ measurement shows that the prediction precision of the proposed model is satisfactory. The root-mean-square error (RMSE) of the combination model can be reduced to 1.4316 (monitoring site JCK2), 1.2623 (monitoring site JCK4), 2.3758 (monitoring site JCK6), 2.2704 (monitoring site JCK8), 1.4247 (monitoring site JCK11), and 0.9449 (monitoring site JCK12), which is much lower than the RMSE of the individual models.

     

构造活动盆地的层序地层与构造地层分析--以中国中、新生代构造活动湖盆分析为例

中国中、新生代构造相对活动的断陷或陆内前陆盆地充填序列一般可划分出5个级别具有地层对比意义的层序地层单元。层序构成和沉积体系域的发育分布受到盆地形成演化过程中各种构造作用的控制。盆地规模的沉积旋回多是盆地幕式裂陷、多幕挤压挠曲沉降、多期构造反转、断块差异沉降等构造作用的沉积响应;高频层序单元的发育则主要与湖平面和沉积物供给量的变化有关。不同构造演化阶段的层序结构和沉积体系域构成等存在显著差异,主要取决于古构造格架和同沉积构造的活动。构造坡折带是由构造活动所产生的、对沉积作用具有长期控制作用的古沉积斜坡或古地貌突变带,在断陷或前陆等盆地中普遍发育,其识别对阐明盆内沉积体系域,特别是构成重要油气藏的低位域的分布和预测具有重要意义。     

Impact of landslide size and settings on landslide scaling relationship: a study from the Himalayan regions of India

Landslides - The reliable landslide hazard assessment entails a robust understanding of frequency-magnitude analysis of the landslide inventory. Previous studies proposed that the landslide...     

Influences of the snow cover on landslide displacement in winter period: a case study in a heavy snowfall area of Japan

The displacement of a relatively small reactivated landslide in a snowy area in Japan was monitored over a long period. The displacement rate of the landslide, which was approximately of 20 mm d^?1 before the formation of snow cover, decelerated drastically during the continuous snow cover period every winter period. Possible causes included reduction in the amount of water that reached the ground surface (MR: meltwater and/or rainwater) and increase in snow load. Given that the actual displacement of the landslide was far below the predicted value based on the relationship between landslide displacement and MR immediately before the continuous snow cover period, the deceleration of landslide displacement was more likely attributable to the increase in snow load than to the reduction in MR. An investigation of the link between snow load and landslide displacement showed a negative logarithmic relationship. A dynamic analysis based on the limit equilibrium method showed that snow load increases the effective normal stress and the stability of a landslide in which the mean inclination angle of the slip surface is smaller than the internal friction angle. The stability of the actual slope was also analyzed by conducting soil tests on samples collected at the site and using the resultant parameters. The analysis also showed that the increase in snow load increases the safety factor and reduces the landslide displacement. The displacement of a relatively small landslide that has a shallow slip surface was found to be greatly influenced by snow cover.     

GPS在滑坡监测中的应用——以四川省丹巴县亚喀则滑坡为例

本文通过在四川丹巴县梭坡乡亚喀则滑坡区布设的GPS监测网的测量,阐述了GPS在滑坡监测时监测点位选择、监测网布设、数据处理的方法。亚喀则滑坡的GPS监测结果表明,其精度达到毫米级,完全满足滑坡监测的精度要求。     

A simple method to help determine landslide susceptibility from spaceborne InSAR data: the Montescaglioso case study

On December 3, 2013, a large complex landslide was triggered SW of the town of Montescaglioso (Southern Italy), causing the destruction of roads, commercial buildings and private dwellings, as well as several direct and indirect economic losses. A set of interferometric ground measurements acquired by the Cosmo-SkyMed satellite constellation and processed by means of the SqueeSAR algorithm was used to study the pre-event slope displacements in the entire Montescaglioso municipal area. Data span from January 30, 2012, to December 2, 2013, and show average line-of-sight velocities of 1–10 mm/year in the slope sector ultimately affected by the collapse. In retrospect, a time series analysis of the radar targets was performed in order to identify and characterize all the slope instabilities in proximity of the town. This was based on the setup of characteristic thresholds of displacement. The procedure permitted to locate several areas which recurrently exceeded these previously established thresholds, in consistency with the amount of precipitation. In particular, the major source of potential hazard in the area was indeed found where the December 3, 2013, landslide eventually occurred. The results of this quick data processing technique were validated through comparison with two independently developed landslide maps. This simple method, which is not supposed to diminish the importance of geomorphologic field surveys, could improve both the accuracy and the update rate of landslide susceptibility maps. Not relying on arbitrary or empirically derived approaches, it has the advantage of computing statistically based thresholds specific for each time series. By indicating the slope sectors in higher need of deeper in situ investigation, more support could be provided to administrative bodies for the processes of risk assessment and management.     

A comparative study of methods to reconstruct a periodic time series from an environmental proxy record

The past environment is often reconstructed by measuring a certain proxy (e.g. δ¹⁸O) in an environmental archive, i.e. a biogenic or abiogenic accreting structure which gradually accumulates mass and records the current environment during this mass formation (e.g. corals, shells, trees, ice cores, speleothems, etc.). Proxy analysis usually yields a record along a distance axis. However, to relate the data to environmental variations, the date associated with each data point has to be known too. This transformation from distance to time is not straightforward to solve, since accretion mostly proceeds at a varying and unknown rate. To solve this problem some hypotheses about the growth rate or the time series must be made. Depending on the application, different assumptions may be appropriate, resulting in or requiring a particular method to perform this transformation. The actual method used can hugely influence the final result and hence the interpretation of the data in terms of frequency and timing of events. However, no comparative study has been made so far, and most of the existing methods haven't been thoroughly assessed. Therefore, this paper aims to evaluate and compare the most popular methods. To keep the review manageable the scope was limited to those records where it can be assumed that the time series is periodic. Examples of periods include tidal, seasonal and ENSO (El Niño Southern Oscillation) cycles, and even cycles of thousands of years could be considered, as long as they are resolved in the measured record. Six methods to reconstruct the time base for periodic proxy records are compared in this review. Their performance in the presence of stochastic and systematic errors is tested on simulations and linked to the methods' underlying assumptions. As a final comparison, all methods are applied to a real world example. The goal of this overview is to provide an objective structure and comparison of the methods mostly used, so that the users are aware of the underlying assumptions and their consequences.     

Probabilistic forecasting of landslide displacement accounting for epistemic uncertainty: a case study in the Three Gorges Reservoir area,China

Accurate and reliable displacement forecasting plays a key role in landslide early warning. However, due to the epistemic uncertainties associated with landslide systems, errors are unavoidable and sometimes significant in traditional methods of deterministic point forecasting. Transforming traditional point forecasting into probabilistic forecasting is essential for quantifying the associated uncertainties and improving the reliability of landslide displacement forecasting. This paper proposes a hybrid approach based on bootstrap, extreme learning machine (ELM), and artificial neural network (ANN) methods to quantify the associated uncertainties via probabilistic forecasting. The hybrid approach consists of two steps. First, a bootstrap-based ELM is applied to estimate the true regression mean of landslide displacement and the corresponding variance of model uncertainties. Second, an ANN is used to estimate the variance of noise. Reliable prediction intervals (PIs) can be computed by combining the true regression mean, variance of model uncertainty, and variance of noise. The performance of the proposed hybrid approach was validated using monitoring data from the Shuping landslide, Three Gorges Reservoir area, China. The obtained results suggest that the Bootstrap-ELM-ANN approach can be used to perform probabilistic forecasting in the medium term and long term and to quantify the uncertainties associated with landslide displacement forecasting for colluvial landslides with step-like deformation in the Three Gorges Reservoir area.     

Combined methodology for three-dimensional slope stability analysis coupled with time effect: a case study in Germany

High-steep slopes in open pit mines are much more likely to collapse due to mining operations. Challenges such as data acquisition, precise numerical models and adaptable methodologies have impeded more reliable results of slope stability analysis based on the current methods. Within this context, this paper proposes a combined methodology using light detection and ranging technology to capture high-resolution slope geometry, three-dimensional geological and geotechnical modeling technologies for creating high-quality numerical simulation models and finite-element slope stability analyses combined with a new automatic strength reduction technique to analyze complex geotechnical problems. At the end, the methodology introduces a time series analysis to improve the reliability of the calculated factor of safety. A case study in the deepest open pit mine in Hambach, Germany, was conducted to test and demonstrate the effectiveness and applicability of the proposed methodology.     

复合型滑坡固液耦合过程数值模拟分析——以无山坪滑坡为例

固液耦合作用是碎屑流向泥石流转化形成复合型滑坡灾害的关键因素, 会导致成灾范围和规模放大, 是防灾减灾领域研究中的热点和难点问题之一。文中采用自主研发的滑坡后破坏数值模拟平台(LPF3D, Landslides post failure 3D), 以2014年9月强降雨诱发的重庆奉节无山坪滑坡为例, 探讨了滑坡在水动力作用下远程成灾的动力过程, 揭示了固液耦合影响机制。研究结果显示: 水动力作用在滑坡运动过程中主要体现为液化和拖曳两种, 两种力学作用的增程效应明显, 往往使得碎屑流转化为泥石流, 导致远程成灾; 基于光滑粒子流体动力学(SPH)方法的两相耦合计算模型, 考虑流体状态方程、固体黏塑性本构方程和相间作用力的共同影响, 基本还原了强降雨条件下重庆奉节无山坪滑坡两相运动过程; 数值计算结果显示无山坪滑坡最大运动速度为34 m/s, 最大堆积厚度为21.5 m, 堆积面积为0.12 km2, 最远运动距离为1300 m, 模拟结果同实际滑坡的堆积形态基本一致。综上认为, 在高位远程滑坡风险调查与预测过程中, 需充分考虑强降雨工况下孔隙水压力和固液相间作用, 基于LPF3D方法的数值模拟为高位远程滑坡的风险定量评估提供了依据。     

Geo-diversity and its hydrological response in relation to landslide susceptibility in the Himalaya: a GIS-based case study

Assessment and inventory of landslide susceptibility are essential for the formulation of successful disaster mitigation plans. The objective of this study was to assess landslide susceptibility in relation to geo-diversity and its hydrological response in the Lesser Himalaya with a case study using Geographic Information System (GIS) technology. The Dabka watershed, which constitutes a part of the Kosi Basin in the Lesser Himalaya, India, in the district of Nainital, has been selected for the case illustration. The study constitutes three GIS modules: geo-diversity informatics, hydro informatics and landslide informatics. Through the integration and superimposing of spatial data and attribute data of all three GIS modules, Landslide Susceptibility Index (LSI) has been prepared to identify the level of susceptibility for landslide hazards. This resonance study, carried out over a period of five years (2007–2011), found that areas of most stressed geo-diversity (comprising very steep slopes above 30°, geology of Lower Krol and Lariakanta formation, geomorphology of moist areas and debris sites, land use of barren land with a very high drainage frequency and spring density) have a high landslide susceptibility because of high rate of average runoff (33 l/s/km²), flood magnitude (307.28 l/s/km²), erosion (398 tons/km²) and landslide density (5–10 landslides/km²). The areas of least stressed geo-diversity (comprising gentle slopes below 10°, geology of Kailakhan and Siwalik formation, geomorphology of depositional terraces, land use of dense forest with low drainage frequency and spring density) have the lowest landslide susceptibility because of the low rate of average runoff (6.27 l/s/km²), flood magnitude (20.49 l/s/km²), erosion (65.80 tons/km²) and landslide density (1–2 landslides/km²).     

Using wavelet tools to analyse seasonal variations from InSAR time-series data: a case study of the Huangtupo landslide

Synthetic aperture radar interferometry (InSAR) has proven to be a powerful tool for monitoring landslide movements with a wide spatial and temporal coverage. Interpreting landslide displacement time-series derived from InSAR techniques is a major challenge for understanding relationships between triggering factors and slope displacements. In this study, we propose the use of various wavelet tools, namely, continuous wavelet transform (CWT), cross wavelet transform (XWT) and wavelet coherence (WTC) for interpreting InSAR time-series information for a landslide. CWT enables time-series records to be analysed in time-frequency space, with the aim of identifying localized intermittent periodicities. Similarly, XWT and WTC help identify the common power and relative phase between two time-series records in time-frequency space, respectively. Statistically significant coherence and confidence levels against red noise (also known as brown noise or random walk noise) can be calculated. Taking the Huangtupo landslide (China) as an example, we demonstrate the capabilities of these tools for interpreting InSAR time-series information. The results show the Huangtupo slope is affected by an annual displacement periodicity controlled by rainfall and reservoir water level. Reservoir water level, which is completely regulated by the dam activity, is mainly in ‘anti-phase’ with natural rainfall, due to flood control in the Three Gorges Project. The seasonal displacements of the Huangtupo landslide is found to be ‘in-phase’ with respect to reservoir water level and the rainfall towards the front edge of the slope and to rainfall at the higher rear of the slope away from the reservoir.     

PFR model and GiT for landslide susceptibility mapping: a case study from Central Alborz, Iran

In northern parts of Iran such as the Alborz Mountain belt, frequent landslides occur due to a combination of climate and geologic conditions with high tectonic activities. This results in millions of dollars of financial damages annually excluding casualties and unrecoverable resources. This paper evaluates the landslide susceptible areas in Central Alborz using the probabilistic frequency ratio (PFR) model and Geo-information Technology (GiT). The landslide location map in this study has been generated based on image elements interpreted from IRS satellite data and field observations. The display, manipulation and analysis have been carried out to evaluate layers such as geology, geomorphology, soil, slope, aspect, land use, distance from faults, lineaments, roads and drainages. The validation group of actual landslides and relative operation curve method has been used to increase the accuracy of the final landslide susceptibility map. The area under the curve evaluates how well the method predicts landslides. The results showed a satisfactory agreement of 91% between prepared susceptibility map and existing data on landslide locations.     

A coupling of mixed and continuous Galerkin finite element methods for poroelasticity I: the continuous in time case

In this paper, we formulate a finite element procedure for approximating the coupled fluid and mechanics in Biot’s consolidation model of poroelasticity. Here, we approximate the pressure by a mixed finite element method and the displacements by a Galerkin method. Theoretical convergence error estimates are derived in a continuous in-time setting for a strictly positive constrained specific storage coefficient. Of particular interest is the case when the lowest-order Raviart–Thomas approximating space or cell-centered finite differences are used in the mixed formulation, and continuous piecewise linear approximations are used for displacements. This approach appears to be the one most frequently applied to existing reservoir engineering simulators.     

Shallow landslide susceptibility assessment under future climate and land cover changes: A case study from southwest China

There is no doubt that land cover and climate changes have consequences on landslide activity, but it is still an open issue to assess and quantify their impacts. Wanzhou County in southwest China was selected as the test area to study rainfall-induced shallow landslide susceptibility under the future changes of land use and land cover (LULC) and climate. We used a high-resolution meteorological precipitation dataset and frequency distribution model to analyse the present extreme and antecedent rainfall conditions related to landslide activity. The future climate change factors were obtained from a 4-member multi-model ensemble that was derived from statistically downscaled regional climate simulations. The future LULC maps were simulated by the land change modeller (LCM) integrated into IDRISI Selva software. A total of six scenarios were defined by considering the rainfall (antecedent conditions and extreme events) and LULC changes towards two time periods (mid and late XXI century). A physically-based model was used to assess landslide susceptibility under these different scenarios. The results showed that the magnitude of both antecedent effective recharge and event rainfall in the region will evidently increase in the future. Under the scenario with a return period of 100 years, the antecedent rainfall in summer will increase by up to 63% whereas the event rainfall will increase by up to 54% for the late 21st century. The most considerable changes of LULC will be the increase of forest cover and the decrease of farming land. The magnitude of this change can reach + 22.1% (forest) and –9.2% (farmland) from 2010 until 2100, respectively. We found that the negative impact of climate change on landslide susceptibility is greater than the stabilizing effect of LULC change, leading to an over decrease in stability over the study area. This is one of the first studies across Asia to assess and quantify changes of regional landslide susceptibility under scenarios driven by LULC and climate change. Our results aim to guide land use planning and climate change mitigation considerations to reduce landslide risk.     

Response of a loess landslide to rainfall: observations from a field artificial rainfall experiment in Bailong River Basin,China

Rainfall-induced landslides are a significant hazard in many areas of loess-covered terrain in Northwest China. To investigate the response of a loess landslide to rainfall, a series of artificial rainfall experiments were conducted on a natural loess slope, located in the Bailong River Basin, in southern Gansu Province. The slope was instrumented to measure surface runoff, pore water pressure, soil water content, earth pressure, displacement, and rainfall. The hydrological response was also characterized by time-lapse electrical resistivity tomography. The results show that most of the rainfall infiltrated into the loess landslide, and that the pore water pressure and water content responded rapidly to simulated rainfall events. This indicates that rainfall infiltration on the loess landslide was significantly affected by preferential flow through fissures and macropores. Different patterns of pore water pressure and water content variations were determined by the antecedent soil moisture conditions, and by the balance between water recharge and drainage in the corresponding sections. We observed three stages of changing pore water pressure and displacement within the loess landslide during the artificial rainfall events: Increases in pore water pressure initiated movement on the slope, acceleration in movement resulting in a rapid decrease in pore water pressure, and attainment of a steady state. We infer that a negative pore water pressure feedback process may have occurred in response to shear-induced dilation of material as the slope movement accelerated. The process of shear dilatant strengthening may explain the phenomenon of semi-continuous movement of the loess landslide. Shear dilatant strengthening, caused by intermittent or continuous rainfall over long periods, can occur without triggering rapid slope failure.     

GIS based landslide susceptibility mapping using a fuzzy logic approach: A case study from Ghurmi-Dhad Khola area, Eastern Nepal

Landslides cause extensive loss of life and property in the Nepal Himalaya. Since the late 1980s, different mathematical models have been developed and applied for landslide susceptibility mapping and hazard assessment in Nepal. The main goal of this paper is to apply fuzzy logic to landslide susceptibility mapping in the Ghurmi-Dhad Khola area, Eastern Nepal. Seven causative factors are considered: slope angle, slope aspect, distance from drainage, land use, geology, distance from faults and folds, soil and rock type. Likelihood ratios are obtained for each class of causative factors by comparison with past landslide occurrences. The ratios are normalized between zero and one to obtain fuzzy membership values. Further, different fuzzy operators are applied to generate landslide susceptibility maps. Comparison with the landslide inventory map reveals that the fuzzy gamma operator with a γ-value of 0.60 yields the best prediction accuracy. Consequently, this operator is used to produce the final landslide susceptibility zonation map.     

Evaluation of the consistency of landslide susceptibility mapping: a case study from the Kankai watershed in east Nepal

GIS-based landslide susceptibility maps for the Kankai watershed in east Nepal are developed using the frequency ratio method and the multiple linear regression technique. The maps are derived from comparing observed landslides with possible causative factors: slope angle, slope aspect, slope curvature, relative relief, distance from drainage, land use, geology, distance from faults and mean annual rainfall. The consistency of the maps is evaluated using landslide density analysis, success rate analysis and spatially agreed area approach. The first two analyses produce almost identical quantitative results, whereas the last approach is able to reveal spatial differences between the maps and also to improve predictions in the agreed high landslide-susceptible area.