Landslide Triggering Research Articles

Modeling impacts of climate change on return period of landslide triggering

Quantifying the potential influence of climate change on future landslide hazard requires methodologies that allow to properly take into account nonstationarities in the hydro-meteorological causes.In this paper we provide a methodology for estimating return period of landslide triggering under climate change.The methodology capitalizes on the combined use of a stochastic rainfall generator and a hydrological and slope stability model. The stochastic rainfall generator takes into account the statistical dependency between rainfall event duration and intensity through copulas. The hydrological model is based on an analytical solution of a simplified version of the Richards vertical infiltration equation and slope stability is assessed by the infinite slope model. The combined model enables to estimate landslide probability through Monte Carlo simulations. Climate change is then introduced by perturbing the parameters of the rainfall stochastic generator based on factors of change derived from the comparison of future scenarios and the baseline climate as simulated by Regional climate models (RCMs). The Monte Carlo simulations are conducted sequentially on a future moving time window, to derive a yearly series of future landslide triggering probability. This series is then used to compute landslide return period by formulas suitable under nonstationary conditions.An application to the landslide prone region of the Peloritani Mountains, Southern Italy, is carried out to demonstrate the proposed approach. For the application, climate change projections of three RCMs of the MED-CORDEX initiative are used, and a preliminary assessment of the impacts of intermediate- and high-emission Representative concentration pathways (RCPs) 4.5 and 8.5 is carried out.

Landslide analysis of unsaturated soil slopes based on rainfall and matric suction data

Shallow slope failures that occur as a result of a decrease in matric suction after water infiltration from intense rains (unsaturated soil conditions) are the main causes of slope instability in tropical and subtropical regions. This study analyzes the occurrence of shallow landslides in a highway cutting of residual soil originating from aeolian sandstone. Characterization of failure mechanisms and stability analyses have been carried out in different scenarios and supported by surface and subsurface investigations, instrumentation and monitoring of rainfall, matric suction, and water level, field tests, and laboratory tests. The results indicate that the reduction in matric suction induced by rainwater infiltration is the triggering mechanism of slope failure. Conventional slope stability analyses and analyses incorporating unsaturated seepage models present results compatible with the hydrological and geotechnical data collected in the study. On the basis of these analyses, and considering the frequent rainfall events in the study area, a critical geometric configuration is proposed for the triggering of landslides in highway cutting slopes of residual soils of aeolian sandstone.

Numerical simulation of groundwater rising due to rainfall at far field in triggering landslide

Numerical simulation of groundwater rising due to rainfall at far field in triggering landslide

Estimating the Velocity of Landslide Movement Using Visco-Plastic Model in Jeruk Sub-village, Kulon Progo District, Yogyakarta, Indonesia

A ground movement occurred in March and November 2017 on the hills and paddy fields in Jeruk Sub-village, Kulon Progo District, Yogyakarta Special Province. The landslide movement destroyed two houses in the village and the land is still moving especially in the rainy season. The mitigation of landslide hazard requires understanding of landslide triggering factors and its movement mechanism. This paper applies the slope stability analysis and visco-plastic model to predict the movement mechanism and velocity of a translational landslide. The sliding mass is modeled as a low plasticity silt (homogenous soil). The Limit Equilibrium Method is used to estimate the safety factor, whereas the shear strength parameters on the slip surface were determined by using the back analysis approach. The results of the slope stability analysis showed that the shear strength parameters and the fluctuation of groundwater level strongly influence the stability of the landslide. From visco-plastic model simulation, this slope has slow movement velocity with the range of 11.31 to 175.88 mm/day. It is clarified that the velocity of landslide movement is influenced by soil strength parameters, coefficient of dynamic viscosity, and groundwater level fluctuation.

Numerical modelling of the long runout character of 2015 Shenzhen landslide with a general two-phase mass flow model

High fluid content or pore-fluid pressure is generally the main reason for the triggering and high mobility of landslides. A catastrophic landslide occurred at Hongao construction waste dumpsite in the Guangming New District of Shenzhen, China, on Dec 20, 2015. Due to the high water content of soil in the source area, this landslide propagated over an extremely long travel distance, with maximum length and width of the affected area 1100 m and 630 m, respectively. High water content pesents a great challenge to numerical methods. In order to simultaneously include the evolution of the solid and fluid components in the mixture, a general two-phase mass flow model of Pudasaini (J Geophys Res 117: F03010, 2012) has been employed in our simulations. The complex interactions between the solid and fluid phases, including buoyancy, the virtual mass force, generalized drag and enhanced non-Newtonian viscous stress, are considered in this two-phase flow model. These are essential aspects in the motion of landslides consisting of viscous fluid and solid particles. Based on the actual geology and engineering conditions, runout characteristics of the Shenzhen landslide were analyzed numerically. The principal reasons for the long runout character and the inundation are discussed based on the physics-based model and high-resolution numerical results.

Identification of flysch landslide triggers using conventional and ‘nearly real-time’ monitoring methods – An example from the Carpathian Mountains, Poland

This paper presents a study of active landslides in the Carpathian flysch in Poland. Site investigation of 15 landslides was conducted during the reconstruction of the Szymbark - Szalowa road. The landslides selected for analysis are located in slopes with inclination from 9o to 18o of the Oligocene age characterized by shallow groundwater levels. These slopes are made of soft clays and claystones, interbedded by sandstones that allow seepage processes. The flysch mixtures of: weak soils and stiff rocks typically pose some difficulties for in-situ and laboratory tests. Therefore, methods for the recognition of landslide size, depth and activity need to be applied. Site investigations and laboratory tests started in 2006 with conventional inclinometer and piezometer monitoring measurements. However, significant time-lags between the measurements made it difficult to quantify landslide triggers. Therefore, a more comprehensive, ‘nearly real-time' landslide monitoring network was deployed on May 2010, the first of this type in Poland. This system consisted of a weather station and three monitoring field stations with continuous recording of 3D inclinometers, in-place tilt sensors and pore-pressure transducers. At depths of 11–15 m, the online measured displacement reached 33–500 mm. Heavy rainfalls, and water infiltration led to pore-pressure changes ranging from 50 to 100 kPa. In June 2010, an acceleration of ground movements occurred after the highest monthly rainfall of 225–303 mm during a major flood in southern Poland and again in July 2011. Slope saturation was found to be the primary cause of landslide activation, and groundwater pore-pressure variations of 100% were found critical, as a trigger for landslide accelerations in the Polish Carpathian flysch. The appearance of high pore-pressures variations could be used as an initial warning signal before the significant movements.

Physically based hydrogeological and slope stability modeling of the Turaida castle mound

This study explores the potential of integrating state-of-the-art physically based hydrogeological modeling into slope stability simulations to identify the hydrogeological triggers of landslides. Hydrogeological models considering detailed morphological, lithological, and climatic factors were elaborated. Groundwater modeling reveals locations with elevated pore water pressures in the subsurface and allows the quantification of temporal dynamics of the pore water pressures. Results of the hydrogeological modeling were subsequently applied as boundary conditions for the slope stability simulations. The numerical models illustrate that the hydrogeological impacts affecting hillslope stability are strongly controlled by local groundwater flow conditions and their conceptualization approach in the hydrogeological model. Groundwater flow itself is heavily influenced by the inherent geological conditions and the dynamics of climatic forcing. Therefore, both detailed investigation of the landslide’s hydrogeology and appropriate conceptualization and scaling of hydrogeological settings in a numerical model are essential to avoid an underestimation of the landslide risk. The study demonstrates the large potential in combining state-of-the-art computational hydrology with slope stability modeling in real-world cases.

Complex-conductivity imaging for the understanding of landslide architecture

Geophysical methods are widely used for landslide investigation to delineate depth and geometry of the sliding plane. In particular, electrical resistivity tomography (ERT) is often used because both porosity and water saturation control the electrical resistivity of the subsurface materials and are critical for slope stability. Moreover, ERT can be employed to monitor changes in pore-fluid pressure which is an important factor triggering landslides. However, the interpretation of ERT results in clay-rich landslides can be challenging considering that high electrical conductivity values may not only be related to an increase in saturation but also to the surface conduction mechanism, which becomes dominant in the presence of clays. Recently, environmental investigations have demonstrated an improved subsurface characterization through induced polarization (IP) imaging, an extension of the ERT method, which permits to gain information about electrical conductive and capacitive (i.e., polarization effect) properties of the subsurface. As the polarization effect is mainly controlled by surface charge, which is large in clays, IP images are expected to improve the lithological interpretation and overcome the limitations of the ERT method. Additionally, measurements collected over a broad frequency bandwidth, the so-called spectral IP (SIP), have been successfully used in laboratory experiments to quantify textural and hydrogeological parameters. However, the application of SIP field measurements for the delineation of hydrogeological structures in landslides has not been addressed to date. To fill this gap, in this study we present SIP imaging results for data collected at the La Valette landslide (South East French Alps), where an existing geotechnical model of the landslide is available for evaluation. Moreover, our study provides a detailed revision on the collection and processing of SIP datasets, as well as a description of the diverse sources of error in IP surveys, to stress the importance of data-error quantification for a quantitative application of the SIP method. Our results demonstrate that adequate data processing allows obtaining consistent results at different frequencies and independently of the measuring protocol. Furthermore, the frequency dependence of the complex conductivity obtained in the field-scale SIP survey is consistent with earlier laboratory experiments. In conclusion, our study shows the potential of the SIP method to improve our understanding of subsurface properties, and an improved delineation of the contact between the mobilized material and the bedrock as well as variations in the clay content within the landslide and the bedrock.

Trends Analysis of Rainfall Patterns Triggering Landslide over the Gorges Reservoir Region

Rainfall-triggered landslides in the Three Gorges Reservoir Region are related to two rainfall patterns: rainstorm event and long-lasting moderate precipitation event. Trends of the two rainfall patterns are investigated using trend estimation and Mann-Kendall test. For this purpose, the daily rainfall data are obtained from the Yichang station, the Enshi station and the Chongqing station for the period 1952-2011. The results of the trend estimation show that annual average number of rainstorm events increase at the three stations during the period, while opposite trends in long-lasting moderate precipitation events is observed. However, the increasing and decreasing trends are not significant in the Mann-Kendall test.

Landslide inventory for hazard assessment in a data-poor context: a regional-scale approach in a tropical African environment

Landslide hazard remains poorly characterized on regional and global scales. In the tropics in particular, the lack of knowledge on landslide hazard is in sharp contrast with the high landslide susceptibility of the region. Moreover, landslide hazard in the tropics is expected to increase in the future in response to growing demographic pressure and climate and land use changes. With precipitation as the primary trigger for landslides in the tropics, there is a need for an accurate determination of rainfall thresholds for landslide triggering based on regional rainfall information as well as reliable data on landslide occurrences. Here, we present the landslide inventory for the central section of the western branch of the East African Rift (LIWEAR). Specific attention is given to the spatial and temporal accuracy, reliability, and geomorphological meaning of the data. The LIWEAR comprises 143 landslide events with known location and date over a span of 48 years from 1968 to 2016. Reported landslides are found to be dominantly related to the annual precipitation patterns and increasing demographic pressure. Field observations in combination with local collaborations revealed substantial biases in the LIWEAR related to landslide processes, landslide impact, and the remote context of the study area. In order to optimize data collection and minimize biases and uncertainties, we propose a three-phase, Search-Store-Validate, workflow as a framework for data collection in a data-poor context. The validated results indicate that the proposed methodology can lead to a reliable landslide inventory in a data-poor context, valuable for regional landslide hazard assessment at the considered temporal and spatial resolutions.

Spatial sensitivity assessment based on landslide trigger factors

Kelkit Çayı Vadisi heyelan yoğunluğu bakımından Türkiye ortalamasının üzerindedir. Bu vadi yamaçlarının üst kesimlerinde yapısal düzlüklerin bulunduğu alanlarda kış aylarında biriken kar ilkbahar aylarında aniden erimektedir. Eriyen kar, bu düzlüklerin önündeki eğimli yamaçlarda su çıkışlarına neden olmakta ve büyük katastrofik heyelanları tetiklemektedir. Gözlem ve literatür araştırmaları sonucunda bu tetiklenmenin kış aylarında vadideki bazı yamaçlarda karın uzun süre tutunması, ilkbaharda güneş radyasyonuna bağlı eridikten sonra sızması ve akışa geçmesiyle gerçekleştiği tespit edilmiştir. Bu etkinin yüksek olduğu yamaçlarda heyelan hassasiyetinin de yüksek olduğu bilinmektedir. Tetikleyici faktör bakımından yamaç hassasiyetini belirlemek çalışmanın amacını oluşturmaktadır. Bu amaçla çalışma alanı 3600 fiziki yamaç ünitesine bölümlenmiştir. Bu ünitelerin tutunma, sızma ve akış hassasiyetini belirlemek için, uzman görüşütarafından etken faktörler ve etki derecelerinin belirlendiği M-AHP yöntemi kullanılmıştır. Tutunma modeli için çok çözünürlüklü vadi taban düzlüğü indeksi, yükselti ve bakı, sızma modeli için solar radyasyon, Topoğrafik Nemlilik İndeksi (TNİ) ve Hidrolojik Toprak Grubu (HTG), akış modeli için ise eğim, rölyef ve HTG parametreleri kullanılmıştır. Tutunma, sızma ve akış için en yüksek kararın alındığı yamaç üniteleri belirlenerek ana tetikleyici kar erimelerinin mekânsal hassasiyet üzerinde etkisi ortaya konulmuştur. Elde edilen sonuçlarda birden fazla modelin çıktısının en yüksek (örn. tutunma-sızma-akış) değerini taşıyan yamaçlarda mekânsal hassasiyetin daha yüksek olduğu tespit edilmiştir. Bu yamaçların özellikle kuzey blokta heyelanların başlangıç bölgelerine karşılık geldiği ortaya çıkmıştır. Heyelana elverişli zemini hazırlayan “tutunma-sızma” yamaçlarının ise eski heyelan içlerine, “sızma-akış” yamaçlarının ise özellikle kuzey yamaçlar olmak üzere heyelanların transfer zonlarına karşılık geldiği tespit edilmiştir. Kuzey yamaçlarda sızmanın yüksek olmasından kaynaklı su içeriğinin fazla olması bu yamaçlarda heyelanın tektiklenmesine neden olmaktadır. Bunun dışında çalışma alanının güney bloğunda ise “tutunma-akış”ın etkin olduğu yamaçlar bulunmaktadır.

Causes and trigger of landslide that occurred on B55 viaduct, motorway Prishtina – Hani i Elezit

This article is not available for publication.

Prediction of landslide displacement with an ensemble-based extreme learning machine and copula models

Research on the dynamics of landslide displacement forms the basis for landslide hazard prevention. This paper proposes a novel data-driven approach to monitor and predict the landslide displacement. In the first part, autoregressive moving average time series models are constructed to analyze the autocorrelation of landslide triggering factors. A linear ensemble-based extreme learning machine using the least absolute shrinkage and selection operator is applied in predicting the displacement of landslides. Five benchmarking data-driven models, the support vector machine, neural network, random forest, k-nearest neighbor, and the classical extreme learning machine, are considered as baseline models for validating the ensemble-based extreme learning machines. Numerical experiments demonstrated that the proposed prediction model produces the smallest prediction errors among all the algorithms tested. In the second part, parametric copula models are fitted on the predicted displacement, to investigate the relationship between the triggering factors and landslide displacement values. The Gumbel-Hougaard copula model performs best, which indicates strong upper tail correlation between the triggering factors and displacement values. Thresholds for the triggering factors can be obtained by monitoring the landslide moving patterns with large displacement values. The effectiveness and utility of the proposed data-driven approach have been confirmed with the landslide case study in the region of the Three Gorges Reservoir.

An integrated approach to investigate slope instability affecting infrastructures

This article focuses on an area located at the northern border of the Monte Poro plateau along the Tyrrhenian coast of Calabria (southern Italy). The area is characterized by weathered gneissic rocks involved in widespread landslides. This research employed an integrated approach concerning the relationships between the geological and geomorphological setting and landslides triggered during the construction of a road. The data were obtained by geological, geomorphological, structural, and geomechanical field surveys, coupled with a geomorphological analysis carried out through a combination of aerial photographs, satellite images, and digital elevation models (DEMs). Rock mass classifications of the weathered gneissic materials were applied to evaluate the quality of the rock masses and to define the potential stability conditions of the slopes. Furthermore, a DEMs analysis of pre- and post-road construction was also performed to define a detailed evolution of the instability conditions affecting the studied escarpment. A total of 32 landslides were recognized before the road construction, while 27 landslides were collected after the road construction. Rotations are the most frequent type of mass movements and involved the more weathered rocks or eluvial/colluvial deposits. Complex landslides are less widespread than the previous ones involving different weathering grades. The results showed that the roadworks had a great impact on the geomorphological scenario in terms of landslide trigger in an area already characterized by a high landslide susceptibility. The approach used can provide a reliable tool to evaluate the hazard conditions in other regions with similar geological features.

What we have learned from the 2008 Wenchuan Earthquake and its aftermath: A decade of research and challenges

The 2008 Mw 7.9 Wenchuan Earthquake (Sichuan, China) was possibly the largest and most destructive recent earthquake as far as the geo-hazards are concerned. Of the nearly 200,000 landslides triggered originally, many remobilized within a few years after the initial event by rainfall, which often caused catastrophic debris flows. The cascades of geo-hazards related to the Wenchuan Earthquake motivated research worldwide to investigate the triggering and mechanisms of co-seismic landslides, their rainfall-induced remobilization, the generation of debris flows, the evolution of their controlling factors, and the long-term role of earthquakes in shaping the topography. On the eve of the 10th anniversary of the 2008 Wenchuan Earthquake, we present a short review of the recent advances in these topics, discuss the challenges faced in the earthquake-related geo-hazards mitigation practice, and suggest priorities and guidelines for future research.

Analysis of Potential Landslides Using Geographic Information System (GIS) on Rail Tunnel in Gunung Gajah Village, Lahat Regency of South Sumatra

Lahat Regency is one of the cities which is prone to geological disasters such as landslides. The landslide is caused by a varied topography such as flat, hilly or mountainous. On January, 23rd 2016, the landslide occurred on the mouth of a railway tunnel in Gunung Gajah Village, Lahat Regency. The purpose of this study is to determine the influence of geological factor on the slope stability. The method of research is a survey method based on geographic information systems in the form of interpretation and analysis of the causes and triggers of landslides with a direct approach in the field by doing scoring an overlay technique. The analysis obtained the parameters of landslides such as: slope, lithology/physical properties of rocks, geological structure and land use. The results and conclusions of this research are the landslide potential distribution map in Gunung Gajah Village, Lahat Regency consisting of three classes of landslide vulnerability: low, medium and high and in the focus areas of research entering the high level of vulnerability.

Hazard assessment of landslide disaster using information value method and analytical hierarchy process in highly tectonic Chamba region in bosom of Himalaya

The present study is focused on a comparative evaluation of landslide disaster using analytical hierarchy process and information value method for hazard assessment in highly tectonic Chamba region in bosom of Himalaya. During study, the information about the causative factors was generated and the landslide hazard zonation maps were delineated using Information Value Method (IV) and Analytical Hierarchy Process (AHP) using ArcGIS (ESRI). For this purpose, the study area was selected in a part of Ravi river catchment along one of the landslide prone Chamba to Bharmour road corridor of National Highway (NH-154A) in Himachal Pradesh, India. A numeral landslide triggering geoenvironmental factors i.e. 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. 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 were validated using Area Under Curve (AUC) plots. It is found that hazard zonation map prepared using information value method and analytical hierarchy process methods possess the prediction rate of 78.87% and 75.42%, respectively. Hence, landslide hazard zonation map obtained using information value method is proposed to be more useful for the study area. These final hazard zonation maps can be used by various stakeholders like engineers and administrators for proper maintenance and smooth traffic flow between Chamba and Bharmour cities, which is the only route connecting these tourist places.

Physically based modeling of the origins of rainfall intensity-duration landslide triggering thresholds

Physically based modeling of the origins of rainfall intensity-duration landslide triggering thresholds

Near‐Real‐Time Modeling of Landslide Impacts to Inform Rapid Response: An Example from the 2016 Kaikōura, New Zealand, Earthquake

Reliable methods for the near‐real‐time modeling of landslide hazard and associated impacts that follow an earthquake are required to provide crucial information to guide emergency responses. After the 2016 Kaikoura earthquake in New Zealand, we undertook such a near‐real‐time modeling campaign in an attempt to pinpoint the location of landslides and identify the locations where roads and rivers had been blocked. The model combined an empirical analysis of landslide hazard (based on previously published global relationships) with a simple runout model (based on landslide reach angles). It was applied manually, with a first iteration completed within 24 hrs of the earthquake and a second iteration (based on updated shaking outputs) within ∼72 hrs . Both models highlighted the expectation that landsliding would be widespread and that impacts to roads likely meant that the township of Kaikoura was cut off from the surroundings. These results were used by responders at the time to formulate aerial reconnaissance flight paths and to identify the risk that landslide dams could cause further damage. Subsequent model verification based on available landslide inventories shows that although these models were able to capture a large percentage of landslides and landslide impacts, the outputs were overpredicted, limiting their use for pinpointing the precise locations of triggered landslides. To make future versions of the model more useful for informing emergency responses, continued work must be done on modification and adaptation of the approach so that this overprediction is minimized. Nevertheless, the results from this study show that the model is a promising initial attempt at near‐real‐time landslide modeling and that efforts to automate the approach would greatly increase the utility and speed of modeling in future earthquakes.

Threshold contour production of rainfall intensity that induces landslides in susceptible regions of northern Turkey

This study is aimed at developing rainfall intensity contour lines to illustrate upper and lower rainfall intensity limits that trigger landslides. The first phase began by developing precipitation empirical thresholds as follows: (i) the relationship between intensity (I) and accumulative rainfall (E) and date (I-date and E-date, respectively); (ii) the antecedent rainfall up to 3, 5, 10, 15, and 30 days prior to landslide occurrence; (iii) the relationship between the I and the duration (D); and (iv) the relationship between the cumulative rainfall event and the D (ID and ED, respectively). The data recorded by two rain gauges (Rize and Rize–Pazar) in the province of Rize in Northwest Turkey were used to analyze 24 previous landslide events during the period 1985 to 2006. The second phase began by developing surface interpolation maps after deriving threshold and assumption of normality, thereby producing contours of the rainfall intensity data of the rain gauges. All thresholds were verified by no-rainfall events, and the ID threshold successfully distinguished 97 and 95% (in Rize and Rize–Pazar, respectively) of false alarm days with the highest accuracy among the thresholds (antecedent rainfall days, I-date, and E-date thresholds). Thus, a descriptive analysis was conducted using the rainfall data of selected rain gauges to test the normality of rainfall between the selected rain gauges in the study area. The linear correlation coefficient was found at 0.75, and other tests verified the normality with optimistic results. A universal or collaborative kriging interpolation (UK) in a geographic information systems’ environment was used to estimate the spatial distribution of rainfall intensity because rainfall is controlled robustly by topography and other factors. This distribution corresponds to the landslide day event and hole-effect mathematical models that are used to forecast un-sampled values in the study area. Topographic elevation, slope, and normalized difference vegetation index (NDVI) maps were integrated into the landslide day events by using rainfall intensity. The UK map was validated by a cross-validation procedure using root-mean-square error. The highest interpolated surface map accuracy was reached without using an external drift (using rainfall intensity values only) and when using an NDVI as the external drift. The optimal model was selected by comparing the measured and predicted values at approximately 78% accuracy. Ultimately, the rainfall intensity contour lines were used to illustrate the upper and lower rainfall intensity limits that trigger landslides. This study used well-documented spatio-temporal data of landslide events and introduced a primary threshold that can be validated for any future event.