scholarly journals Geomorphological control on variably saturated hillslope hydrology and slope instability

2016 ◽  
Vol 52 (6) ◽  
pp. 4590-4607 ◽  
Author(s):  
Formetta Giuseppe ◽  
Silvia Simoni ◽  
Jonathan W. Godt ◽  
Ning Lu ◽  
Riccardo Rigon
Keyword(s):  
Slope Instability ◽  
Hillslope Hydrology

scholarly journals From scenario-based seismic hazard to scenario-based landslide hazard: rewinding to the past via statistical simulations

2021 ◽  
Author(s):  
Luguang Luo ◽  
Luigi Lombardo ◽  
Cees van Westen ◽  
Xiangjun Pei ◽  
Runqiu Huang
Keyword(s):  
Ground Motion ◽  
Land Use Planning ◽  
Landslide Susceptibility ◽  
Additive Model ◽  
Slope Instability ◽  
Susceptibility Map ◽  
Jiuzhaigou Earthquake ◽  
Full Spectrum ◽  
The Past ◽  
Time Invariant

AbstractThe vast majority of statistically-based landslide susceptibility studies assumes the slope instability process to be time-invariant under the definition that “the past and present are keys to the future”. This assumption may generally be valid. However, the trigger, be it a rainfall or an earthquake event, clearly varies over time. And yet, the temporal component of the trigger is rarely included in landslide susceptibility studies and only confined to hazard assessment. In this work, we investigate a population of landslides triggered in response to the 2017 Jiuzhaigou earthquake ($$M_w = 6.5$$ M w = 6.5 ) including the associated ground motion in the analyses, these being carried out at the Slope Unit (SU) level. We do this by implementing a Bayesian version of a Generalized Additive Model and assuming that the slope instability across the SUs in the study area behaves according to a Bernoulli probability distribution. This procedure would generally produce a susceptibility map reflecting the spatial pattern of the specific trigger and therefore of limited use for land use planning. However, we implement this first analytical step to reliably estimate the ground motion effect, and its distribution, on unstable SUs. We then assume the effect of the ground motion to be time-invariant, enabling statistical simulations for any ground motion scenario that occurred in the area from 1933 to 2017. As a result, we obtain the full spectrum of potential coseismic susceptibility patterns over the last century and compress this information into a hazard model/map representative of all the possible ground motion patterns since 1933. This backward statistical simulations can also be further exploited in the opposite direction where, by accounting for scenario-based ground motion, one can also use it in a forward direction to estimate future unstable slopes.

scholarly journals The Impact of Probability Density Functions Assessment on Model Performance for Slope Stability Analysis

Geosciences ◽  
2021 ◽  
Vol 11 (8) ◽  
pp. 322
Author(s):  
Evelina Volpe ◽  
Luca Ciabatta ◽  
Diana Salciarini ◽  
Stefania Camici ◽  
Elisabetta Cattoni ◽  
...  
Keyword(s):  
Probability Density ◽  
Central Italy ◽  
Model Performance ◽  
Probability Density Functions ◽  
Slope Instability ◽  
Complex Nature ◽  
Density Functions ◽  
Umbria Region ◽  
Input Variables ◽  
The Impact

The development of forecasting models for the evaluation of potential slope instability after rainfall events represents an important issue for the scientific community. This topic has received considerable impetus due to the climate change effect on territories, as several studies demonstrate that an increase in global warming can significantly influence the landslide activity and stability conditions of natural and artificial slopes. A consolidated approach in evaluating rainfall-induced landslide hazard is based on the integration of rainfall forecasts and physically based (PB) predictive models through deterministic laws. However, considering the complex nature of the processes and the high variability of the random quantities involved, probabilistic approaches are recommended in order to obtain reliable predictions. A crucial aspect of the stochastic approach is represented by the definition of appropriate probability density functions (pdfs) to model the uncertainty of the input variables as this may have an important effect on the evaluation of the probability of failure (PoF). The role of the pdf definition on reliability analysis is discussed through a comparison of PoF maps generated using Monte Carlo (MC) simulations performed over a study area located in the Umbria region of central Italy. The study revealed that the use of uniform pdfs for the random input variables, often considered when a detailed geotechnical characterization for the soil is not available, could be inappropriate.

scholarly journals Changes in ground deformation prior to and following a large urban landslide in La Paz, Bolivia revealed by advanced InSAR

2018 ◽  
Author(s):  
Nicholas J. Roberts ◽  
Bernhard T. Rabus ◽  
John J. Clague ◽  
Reginald L. Hermanns ◽  
Marco-Antonio Guzmán ◽  
...  
Keyword(s):  
Ground Deformation ◽  
Ground Surface ◽  
Slope Instability ◽  
Small Scale ◽  
Spatial And Temporal Patterns ◽  
La Paz ◽  
Fine Grained ◽  
Measured Displacement ◽  
Optical Satellite Images ◽  
Displacement Patterns

Abstract. We characterize and compare creep preceding and following the 2011 Pampahasi landslide (∼ 40 Mm3 ± 50 %) in the city of La Paz, Bolivia, using spaceborne RADAR interferometry (InSAR) that combines displacement records from both distributed and point scatterers. The failure remobilised deposits of an ancient landslide in weakly cemented, predominantly fine-grained sediments and affected ∼ 1.5 km2 of suburban development. During the 30 months preceding failure, about half of the toe area was creeping at 3–8 cm/a and localized parts of the scarp area showed displacements of up to 14 cm/a. Changes in deformation in the 10 months following the landslide are contrary to the common assumption that stress released during a discrete failure increases stability. During that period, most of the landslide toe and areas near the headscarp accelerated, respectively, to 4–14 and 14 cm/a. The extent of deformation increased to cover most, or probably all, of the 2011 landslide as well as adjacent parts of the slope and plateau above. The InSAR-measured displacement patterns – supplemented by field observations and by optical satellite images – indicate that kinematically complex, steady-state creep along pre-existing sliding surfaces temporarily accelerated in response to heavy rainfall, after which the slope quickly achieved a slightly faster and expanded steadily creeping state. This case study demonstrates that high-quality ground-surface motion fields derived using spaceborne InSAR can help to characterize creep mechanisms, quantify spatial and temporal patterns of slope activity, and identify isolated small-scale instabilities. Characterizing slope instability before, during, and after the 2011 Pampahasi landslide is particularly important for understanding landslide hazard in La Paz, half of which is underlain by similar, large paleolandslides.

scholarly journals Formation Patterns of Mediterranean High-Mountain Water-Bodies in Sierra-Nevada, SE Spain

Water ◽  
2021 ◽  
Vol 13 (4) ◽  
pp. 438
Author(s):  
Jose Luis Diaz-Hernandez ◽  
Antonio Jose Herrera-Martinez
Keyword(s):  
Sierra Nevada ◽  
Unknown Origin ◽  
Slope Instability ◽  
Water Bodies ◽  
High Mountain ◽  
Mountain Areas ◽  
Glacial Processes ◽  
The Mediterranean ◽  
Water Volumes

At present, there is a lack of detailed understanding on how the factors converging on water variables from mountain areas modify the quantity and quality of their watercourses, which are features determining these areas’ hydrological contribution to downstream regions. In order to remedy this situation to some extent, we studied the water-bodies of the western sector of the Sierra Nevada massif (Spain). Since thaw is a necessary but not sufficient contributor to the formation of these fragile water-bodies, we carried out field visits to identify their number, size and spatial distribution as well as their different modelling processes. The best-defined water-bodies were the result of glacial processes, such as overdeepening and moraine dams. These water-bodies are the highest in the massif (2918 m mean altitude), the largest and the deepest, making up 72% of the total. Another group is formed by hillside instability phenomena, which are very dynamic and are related to a variety of processes. The resulting water-bodies are irregular and located at lower altitudes (2842 m mean altitude), representing 25% of the total. The third group is the smallest (3%), with one subgroup formed by anthropic causes and another formed from unknown origin. It has recently been found that the Mediterranean and Atlantic watersheds of this massif are somewhat paradoxical in behaviour, since, despite its higher xericity, the Mediterranean watershed generally has higher water contents than the Atlantic. The overall cause of these discrepancies between watersheds is not connected to their formation processes. However, we found that the classification of water volumes by the manners of formation of their water-bodies is not coherent with the associated green fringes because of the anomalous behaviour of the water-bodies formed by moraine dams. This discrepancy is largely due to the passive role of the water retained in this type of water-body as it depends on the characteristics of its hollows. The water-bodies of Sierra Nevada close to the peak line (2918 m mean altitude) are therefore highly dependent on the glacial processes that created the hollows in which they are located. Slope instability created water-bodies mainly located at lower altitudes (2842 m mean altitude), representing tectonic weak zones or accumulation of debris, which are influenced by intense slope dynamics. These water-bodies are therefore more fragile, and their existence is probably more short-lived than that of bodies created under glacial conditions.

scholarly journals Deformation Prediction of Unstable Slopes Based on Real-Time Monitoring and DeepAR Model

Sensors ◽  
2020 ◽  
Vol 21 (1) ◽  
pp. 14
Author(s):  
Mei Dong ◽  
Hongyu Wu ◽  
Hui Hu ◽  
Rafig Azzam ◽  
Liang Zhang ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Real Time ◽  
Monitoring System ◽  
Slope Instability ◽  
Mountainous Area ◽  
Probabilistic Forecasting ◽  
Intelligence Algorithm ◽  
Good Prediction Accuracy ◽  
Artificial Intelligence Algorithm ◽  
Steep Slopes

With increased urbanization, accidents related to slope instability are frequently encountered in construction sites. The deformation and failure mechanism of a landslide is a complex dynamic process, which seriously threatens people’s lives and property. Currently, prediction and early warning of a landslide can be effectively performed by using Internet of Things (IoT) technology to monitor the landslide deformation in real time and an artificial intelligence algorithm to predict the deformation trend. However, if a slope failure occurs during the construction period, the builders and decision-makers find it challenging to effectively apply IoT technology to monitor the emergency and assist in proposing treatment measures. Moreover, for projects during operation (e.g., a motorway in a mountainous area), no recognized artificial intelligence algorithm exists that can forecast the deformation of steep slopes using the huge data obtained from monitoring devices. In this context, this paper introduces a real-time wireless monitoring system with multiple sensors for retrieving high-frequency overall data that can describe the deformation feature of steep slopes. The system was installed in the Qili connecting line of a motorway in Zhejiang Province, China, to provide a technical support for the design and implementation of safety solutions for the steep slopes. Most of the devices were retained to monitor the slopes even after construction. The machine learning Probabilistic Forecasting with Autoregressive Recurrent Networks (DeepAR) model based on time series and probabilistic forecasting was introduced into the project to predict the slope displacement. The predictive accuracy of the DeepAR model was verified by the mean absolute error, the root mean square error and the goodness of fit. This study demonstrates that the presented monitoring system and the introduced predictive model had good safety control ability during construction and good prediction accuracy during operation. The proposed approach will be helpful to assess the safety of excavated slopes before constructing new infrastructures.

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