An integrated methodology for landslides’ early warning systems

Early Warning Systems (EWS) are efficient tools for preventing and mitigating the risks associated to landslides occurrence. In this paper, an integrated methodology for landslides’ analysis is presented and described. Such methodology is aimed at the creation of early warning systems and is based on the integration between a modern monitoring technique, such as the Ground-Based Interferometric Synthetic Aperture Radar (GBInSAR), along with advanced numerical modelling. The paper also shows the application of the proposed methodology to the case study of a rockslide in central Italy. The integration between monitoring data, thanks to a GBInSAR survey and advanced numerical simulations with the combined Finite-Discrete Elements Method (FDEM), allowed for the definition of a set of surface velocity thresholds to be adopted for the long-term monitoring of the landslide and for the creation of an effective EWS.     

Hazard and risk assessment of earthquake-induced landslides—case study

Landslides as secondary seismic effects are causing some patterns of soil failure that are often considered among the most destructive ones. In fact, the impact from triggered landslides has sometimes exceeded damage directly related to strong shaking and fault rupture. The objective of this research study is landslide hazard and risk assessment considering different water saturation and earthquake scenarios, for a selected area in a sub-urban hilly part of Skopje—the capital of Macedonia. The final product is represented by digital maps of expected permanent displacements for a defined earthquake scenario, in different water saturation conditions of the instable soil layer. Qualitative landslide risk assessment is performed taking into consideration the exposure map of the habitants and local road of the area. As to the target area, it can be concluded that it has the potential for instability that, under certain scenarios, could result in economic and social damage (vulnerability of individual houses, vulnerability of infrastructure and alike). The results from this study referring to potentially affected population and infrastructure present solid base for preventive mitigation activities for reducing the consequences of geotechnical hazards in Skopje City associated with earthquakes.     

Characteristics of earthquake-induced landslides in a heavy snowfall region—landslides triggered by the northern Nagano prefecture earthquake, March 12, 2011, Japan

The northern Nagano Prefecture earthquake, M_JMA?6.7 (Mw?6.2), which is inferred to have been triggered by the huge (Mw?9.0) March 11, 2011 Tohoku earthquake, occurred on March 12, 2011, in northern Nagano Prefecture, an area in Japan famous for heavy snowfall. A large number of landslides were triggered by the 12 March earthquake, and it caused building damage in the area of the epicenter. To clarify characteristics of the distribution and dynamic behavior of these landslides, we analyzed aerial photographs and conducted field surveys in and around the epicentral area. Large-scale landslides with long distance run-outs are a remarkable characteristic of the landslides induced by this earthquake. The long travel distance is considered to be related to the thick snowpack at the time the earthquake occurred. Moderate scale deep-seated landslides and shallow landslides were also observed in the study area. Based on an analysis of landslides with the active fault on which the earthquake is believed to have occurred, most of these landslides were distributed on the hanging wall of the active fault, within a distance of 12?km from the fault.     

Susceptibility evaluation and mapping of China’s landslides based on multi-source data

Landslides are occurring more frequently in China under the conditions of extreme rainfall and changing climate, according to News reports. Landslide hazard assessment remains an international focus on disaster prevention and mitigation, and it is an important step for compiling and quantitatively characterizing landslide damages. This paper collected and analyzed the historical landslide events data of the past 60 years in China. Validated by the frequencies and distributions of landslides, nine key factors (lithology, convexity, slope gradient, slope aspect, elevation, soil property, vegetation coverage, flow, and fracture) are selected to construct landslide susceptibility (LS) empirical models by back-propagation artificial neural network method. By integrating landslide empirical models with surface multi-source geospatial and remote sensing data, this paper further performs a large-scale LS assessment throughout China. The resulting landslide hazard assessment map of China clearly illustrates the hot spots of the high landslide potential areas, mostly concentrated in the southwest. The study implements a complete framework of multi-source data collecting, processing, modeling, and synthesizing that fulfills the assessment of LS and provides a theoretical basis and practical guide for predicting and mitigating landslide disasters potentially throughout China.

     

Exploring the magnitude–frequency distribution: a cellular automata model for landslides

Landslide magnitude–frequency curves allow for the probabilistic characterization of regional landslide hazard. There is evidence that landslides exhibit self-organized criticality including the tendency to follow a power law over part of the magnitude–frequency distribution. Landslide distributions, however, also typically exhibit poor agreement with the power law at smaller sizes in a flattening of the slope known as rollover. Understanding the basis for this difference is critical if we are to accurately predict landslide hazard, risk or landscape denudation over large areas. One possible argument is that the magnitude–frequency distribution is dominated by physiographic controls whereby landslides tend to a larger size, and larger landslides are landscape limited according to a power law. We explore the physiographic argument using first a simple deterministic model and then a cellular automata model for watersheds in coastal British Columbia. The results compare favorably to actual landslide data: modeled landslides bifurcate at local elevation highs, deposit mass preferentially where the local slopes decrease, find routes in confined valley or channel networks, and, when sufficiently large, overwhelm the local topography. The magnitude–frequency distribution of both the actual landslides and the cellular automata model follow a power law for magnitudes higher than 10,000–20,000 m² and show a flattening of the slope for smaller magnitudes. Based on the results of both models, we argue that magnitude–frequency distributions, including both the rollover and the power law components, are a result of actual physiographic limitations related to slope, slope distance, and the distribution of mass within landslides. The cellular automata model uses simple empirically based rules that can be gathered for regions worldwide.     

Post-failure analysis of landslides in spatially varying soil deposits using stochastic material point method

This paper presents the probabilistic analysis of landslides in spatially variable soil deposits, modeled by a stochastic framework which integrates the random field theory with generalized interpolation material point method(GIMP). Random fields are simulated using Cholesky matrix decomposition(CMD) method and Latin hypercube sampling(LHS) method, which represent material properties discretized into sets of random soil shear strength variables with statistical properties. The approach is applie...     

Database of giant landslides on volcanic islands—first results from the Atlantic Ocean

Giant landslides on volcanic islands represent the largest formations which can be created in a single geological moment. Such landslides are distributed across the globe and have attracted a significant amount of research interest. Yet, no coherent attempts have been made to rationalise this information into a single online resource. This report summarises information about the structure of the recently created database of giant landslides on volcanic islands and presents some observations regarding the uncertainties inherent in the inventories. The database is being prepared over a 3-year period: the first year of the project has focused on rationalising information about giant landslides around the Atlantic Ocean while the second and third years will focus on rationalising information about such landslides from the Pacific Ocean and Indian Ocean, respectively. Using this database, it should be possible to interrogate the spatial and temporal patterns of land sliding and landslide reactivation as well as to better assess the hazard and potential risks posed by giant landslides on volcanic islands. It will be particularly interesting to see if any evidence can be found for global triggers, such as eustatic or climatic changes, instead of the more commonly expounded local triggers. Ultimately, it is hoped that the database will benefit both the geoscientific community and those agencies responsible for civil defence. This work is part of the activities of the International Consortium on Landslides, namely its International Programme on Landslides (Project n. 212). The database is available from the giant landslides project webpage: https://www.irsm.cas.cz/ext/giantlandslides.     

A prototype system for space–time assessment of rainfall-induced shallow landslides in Italy

In the last decades, physically based distributed models turned out rather promising to achieve the space–time assessment of shallow landslides at large spatial scale. This technical note deals with the application of a physically based stability model named Shallow Landslides Instability Prediction (SLIP), which has been adopted by the Department of National Civil Protection of Italy as a prototype early warning system for rainfall-induced shallow landslides on national scale. The model is used as a main methodology to create space–time shallow landslide susceptibility maps based on a simple deterministic slope-stability approach, combined with high-resolution rainfall information and geographic information system-based geospatial datasets. The safety factor as an index to measure slope instability is modeled as function of topographic, geologic, geotechnical and hydrologic variables. Although the main aim of this work was to prove the operational viability of such model on a nationwide domain and some simplification are adopted at this stage, hind cast tests on some relevant case histories of shallow landslides occurred between October 2009 and October 2011 showed that the model has skill in representing both timing and location of those shallow landslides.     

Topography and landslides in weathered granitic rock areas—Hai Van landslide in central Vietnam

Many landslides occur every year during heavy rains at the Hai Van Pass and surrounding area in central Vietnam, where granitic rocks are distributed. As is common in granite areas, these landslides often occur as small-scale flow-type and slump-type landslides. However, several horseshoe-shaped loose slopes of widths and lengths of 500 to 800 m, which incorporate these landslides, are observed on slopes across the area. These topographies resemble those formed by past and present large-scale landslides. The presence of such a topography and the repeated occurrences of landslides within this topography are rare in granite areas, where shallow flow-type landslides are generally frequent. To understand the mechanism causing the landslides in the Hai Van region, and as a support for future risk assessment, the factors and processes leading to the formation of such a topography and their relationship with these landslides must be identified and assessed. This study investigated the history of past landslide movement in the Hai Van Pass and surrounding area through observations of drill cores and outcrops, and analysis of the direction of remanent magnetism in the granitic rocks. Mineral compositions, cracks, degrees of weathering, and topographic shapes of the granitic rocks and their relationship to the landslides occurring today were also investigated. The results of the study reveal no variation in the direction of remanent magnetism in the granitic rocks in the region that would indicate disturbance of the ground due to a past large-scale landslide. No evidence of such an event could also be found both in the drill cores and the rock outcrops. Further, results of the analysis of cracks and weathering pattern confirm that the topography of the region is affected by the weathering of the granitic rocks that progresses in concentric circles of various sizes. Thus, it can be concluded that these topographies were not formed by a singular large-scale landslide of the past, but rather by a composite of relatively shallow landslides occurring on the slope of dome structures unique to granite areas, which are formed by differential weathering and denudation regulated by cracks.     

The rainfall intensity–duration control of shallow landslides and debris flows: an update

A global database of 2,626 rainfall events that have resulted in shallow landslides and debris flows was compiled through a thorough literature search. The rainfall and landslide information was used to update the dependency of the minimum level of rainfall duration and intensity likely to result in shallow landslides and debris flows established by Nel Caine in 1980. The rainfall intensity–duration (ID) values were plotted in logarithmic coordinates, and it was established that with increased rainfall duration, the minimum average intensity likely to trigger shallow slope failures decreases linearly, in the range of durations from 10 min to 35 days. The minimum ID for the possible initiation of shallow landslides and debris flows was determined. The threshold curve was obtained from the rainfall data using an objective statistical technique. To cope with differences in the intensity and duration of rainfall likely to result in shallow slope failures in different climatic regions, the rainfall information was normalized to the mean annual precipitation and the rainy-day normal. Climate information was obtained from the global climate dataset compiled by the Climate Research Unit of the East Anglia University. The obtained global ID thresholds are significantly lower than the threshold proposed by Caine (Geogr Ann A 62:23–27, 1980), and lower than other global thresholds proposed in the literature. The new global ID thresholds can be used in a worldwide operational landslide warning system based on global precipitation measurements where local and regional thresholds are not available..     

Linear discriminant analysis to describe the relationship between rainfall and landslides in Bogotá, Colombia

Bogotá is located in the central Andean region of Colombia, which is frequently affected by landslide processes. These processes are mostly triggered during the rainy season in the city. This fact remarks the importance of determining what rain-derived parameters (e.g. intensity, antecedent rain, daily rain) are better related with the occurrence of landslides. For this purpose, the linear discriminant analysis (LDA), a technique derived from multivariate statistics, was used. The application of this type of analysis led to obtain simple mathematical functions that represent the probability of occurrence of landslides in Bogotá. The functions also allow to identify the most relevant variables derived from records of rainfall linked to the generation of landslides. A proof of concept using the proposed methodology was done using historic rainfall data from a 9-km² area of homogenous climatology and geomorphology in the south part of Bogotá. Landslides needed to be grouped for the LDA. Each one of these grouping categories represents landslides that occurred in similar geomorphologic conditions. Another set of events with no landslides was generated synthetically. Results of the proof of concept show that rainfall parameters such as normalized rainfall intensity I _MAP, normalized daily rainfall R _MAP and rainy-days normal RDN have the best statistical correlation with the landslides observed in the zone of analysis.     

Why do landslides impact farmland abandonment? Evidence from hilly and mountainous areas of rural China

Natural Hazards - In hilly and mountainous areas of China, landslides are a common geological hazard that threatens agricultural production and has a profound impact on farmers’ production...     

The monitoring of slow-moving landslides and assessment of stabilisation measures using an optical–mechanical crack gauge

It is possible to monitor slow-moving landslides and assess landslide stabilisation measures over protracted periods using an optical–mechanical crack gauge called a TM-71. This technical note outlines the theoretical background to the gauge and illustrates its practical application through a number of case studies. These studies are drawn from a range of landslide types and stabilisation measures. In terms of monitoring slow-moving landslides, three studies of deep-seated deformations are presented. The Taukliman coastal landslide on the Black Sea Coast is characterised by vertical and horizontal displacements of up to 0.2?mm?year^?1 and sudden earthquake-induced dilations of up to 6?mm. The Parohy ridge spreading landslide in the Malá Fatra Mountains is characterised by gravitationally induced vertical displacements of 0.7?mm?year^?1. The slope deformation that formed Cyrilka Cave in the Beskydy Mountains is characterised by very slow sinistral strike–slip movements of 0.8?mm?year^?1. In terms of assessing landslide stabilisation measures, two studies are presented from Orava Castle in Slovakia and Tetín in the Czech Republic. The data recorded at these sites demonstrate that the constructed stabilisation measures have successfully alleviated the potential landslide hazard in both localities. These case studies clearly demonstrate that the gauge represents an important tool with which to monitor slow-moving landslides and assess landslide stabilisation measures. It is able to provide a precise three-dimensional record of deformation, withstand harsh environmental conditions, and record reliable data over protracted periods.     

Karst landslides hazard during 1940–2002 in the mountainous region of Guizhou Province, Southwest China

Mountain landslide has been an environmental geological problem and occurs frequently in China, especially in the karst region of Guizhou Province, Southwest China. The data of karst mountain landslide are collected and analysed, which occurred in the period of 1940–2002. The collection includes 321 events in the karst region of Guizhou Province. The characteristics of mountain landslides may be classified as two types, namely natural mountain landslides (287 events) and the other induced by human activities (34 events). The results indicate that natural mountain landslide causes especially high damage and is still the main type of natural hazard in the study area owing to the extremely fragile karst geological environment.     

An open dataset for landslides triggered by the 2016 Mw 7.8 Kaikōura earthquake,New Zealand

On November 14, 2016, the northeastern South Island of New Zealand was hit by the magnitude Mw 7.8 Kaikōura earthquake, which is characterized by the most complex rupturing mechanism ever recorded. The widespread landslides triggered by the earthquake make this event a great case study to revisit our current knowledge of earthquake-triggered landslides in terms of factors controlling the spatial distribution of landslides and the rapid assessment of geographic areas affected by widespread landsliding. Although the spatial and size distributions of landslides have already been investigated in the literature, a polygon-based co-seismic landslide inventory with landslide size information is still not available as of June 2021. To address this issue and leverage this large landslide event, we mapped 14,233 landslides over a total area of approximately 14,000 km². We also identified 101 landslide dams and shared them all via an open-access repository. We examined the spatial distribution of co-seismic landslides in relation to lithologic units and seismic and morphometric characteristics. We analyzed the size statistics of these landslides in a comparative manner, by using the five largest co-seismic landslide inventories ever mapped (i.e., Chi-Chi, Denali, Wenchuan, Haiti, and Gorkha). We compared our inventory with respect to these five ones to answer the question of whether the landslides triggered by the 2016 Kaikōura earthquake are less numerous and/or share size characteristics similar to those of other strong co-seismic landslide events. Our findings show that the spatial distribution of the Kaikōura landslide event is not significantly different from those belonging to other extreme landslide events, but the average landslide size generated by the Kaikōura earthquake is relatively larger compared to some other large earthquakes (i.e., Wenchuan and Gorkha).