Susceptibility and triggering scenarios at a regional scale for shallow landslides

Geomorphology ◽  
2008 ◽  
Vol 99 (1-4) ◽  
pp. 39-58 ◽  
Author(s):  
G. Gullà ◽  
L. Antronico ◽  
P. Iaquinta ◽  
O. Terranova
Keyword(s):  
Regional Scale ◽  
Shallow Landslides

scholarly journals Regional Analyses of Rainfall-Induced Landslide Initiation in Upper Gudbrandsdalen (South-Eastern Norway) Using TRIGRS Model

Geosciences ◽  
2021 ◽  
Vol 11 (1) ◽  
pp. 35
Author(s):  
Luca Schilirò ◽  
José Cepeda ◽  
Graziella Devoli ◽  
Luca Piciullo
Keyword(s):  
Numerical Simulations ◽  
Regional Scale ◽  
Shallow Landslides ◽  
South Eastern ◽  
Physically Based ◽  
Triggering Conditions ◽  
Cover Thickness ◽  
Regional Analyses ◽  
Factor Maps ◽  
Eastern Norway

In Norway, shallow landslides are generally triggered by intense rainfall and/or snowmelt events. However, the interaction of hydrometeorological processes (e.g., precipitation and snowmelt) acting at different time scales, and the local variations of the terrain conditions (e.g., thickness of the surficial cover) are complex and often unknown. With the aim of better defining the triggering conditions of shallow landslides at a regional scale we used the physically based model TRIGRS (Transient Rainfall Infiltration and Grid-based Regional Slope stability) in an area located in upper Gudbrandsdalen valley in South-Eastern Norway. We performed numerical simulations to reconstruct two scenarios that triggered many landslides in the study area on 10 June 2011 and 22 May 2013. A large part of the work was dedicated to the parameterization of the numerical model. The initial soil-hydraulic conditions and the spatial variation of the surficial cover thickness have been evaluated applying different methods. To fully evaluate the accuracy of the model, ROC (Receiver Operating Characteristic) curves have been obtained comparing the safety factor maps with the source areas in the two periods of analysis. The results of the numerical simulations show the high susceptibility of the study area to the occurrence of shallow landslides and emphasize the importance of a proper model calibration for improving the reliability.

Regional-scale modelling of shallow landslides with different initiation mechanisms: Sliding versus liquefaction

2017 ◽  
Vol 228 ◽  
pp. 346-356 ◽  
Author(s):  
José J. Lizárraga ◽  
Paolo Frattini ◽  
Giovanni B. Crosta ◽  
Giuseppe Buscarnera
Keyword(s):  
Regional Scale ◽  
Shallow Landslides ◽  
Scale Modelling

scholarly journals Determination of rainfall thresholds for shallow landslides by a probabilistic and empirical method

2015 ◽  
Vol 3 (5) ◽  
pp. 3487-3508
Author(s):  
J. Huang ◽  
N. P. Ju ◽  
Y. J. Liao ◽  
D. D. Liu
Keyword(s):  
Early Warning ◽  
Regional Scale ◽  
Warning System ◽  
Rainfall Threshold ◽  
Empirical Method ◽  
Shallow Landslides ◽  
Data Sets ◽  
Threshold Values ◽  
Mountainous Regions ◽  
Hourly Rainfall

Abstract. Rainfall-induced landslides not only cause property loss, but also kill and injure large numbers of people every year in mountainous areas in China. These losses and casualties may be avoided to some extent with rainfall threshold values used in an early warning system at a regional scale for the occurrence of landslides. However, the limited availability of data always causes difficulties. In this paper we present a method to calculate rainfall threshold values with limited data sets for the two rainfall parameters: maximum hourly rainfall intensity and accumulated precipitation. The method has been applied to the Huangshan region, in Anhui Province, China. Four early warning levels (Zero, Outlook, Attention, and Warning) have been adopted and the corresponding rainfall threshold values have been defined by probability lines. A validation procedure showed that this method can significantly enhance the effectiveness of a warning system, and finally reduce the risk from shallow landslides in mountainous regions.

scholarly journals Towards a real-time susceptibility assessment of rainfall-induced shallow landslides on a regional scale

2011 ◽  
Vol 11 (7) ◽  
pp. 1927-1947 ◽  
Author(s):  
L. Montrasio ◽  
R. Valentino ◽  
G. L. Losi
Keyword(s):  
Real Time ◽  
Regional Scale ◽  
Back Analysis ◽  
Early Warning Systems ◽  
Shallow Landslides ◽  
Landslide Risk ◽  
Time Interval ◽  
Slip Model ◽  
Temporal Prediction ◽  
Physically Based

Abstract. In the framework of landslide risk management, it appears relevant to assess, both in space and in time, the triggering of rainfall-induced shallow landslides, in order to prevent damages due to these kind of disasters. In this context, the use of real-time landslide early warning systems has been attracting more and more attention from the scientific community. This paper deals with the application, on a regional scale, of two physically-based stability models: SLIP (Shallow Landslides Instability Prediction) and TRIGRS (Transient Rainfall Infiltration and Grid-based Regional Slope-stability analysis). A back analysis of some recent case-histories of soil slips which occurred in the territory of the central Emilian Apennine, Emilia Romagna Region (Northern Italy) is carried out and the main results are shown. The study area is described from geological and climatic viewpoints. The acquisition of geospatial information regarding the topography, the soil properties and the local landslide inventory is also explained. The paper outlines the main features of the SLIP model and the basic assumptions of TRIGRS. Particular attention is devoted to the discussion of the input data, which have been stored and managed through a Geographic Information System (GIS) platform. Results of the SLIP model on a regional scale, over a one year time interval, are finally presented. The results predicted by the SLIP model are analysed both in terms of safety factor (Fs) maps, corresponding to particular rainfall events, and in terms of time-varying percentage of unstable areas over the considered time interval. The paper compares observed landslide localizations with those predicted by the SLIP model. A further quantitative comparison between SLIP and TRIGRS, both applied to the most important event occurred during the analysed period, is presented. The limits of the SLIP model, mainly due to some restrictions of simplifying the physically based relationships, are analysed in detail. Although an improvement, in terms of spatial accuracy, is needed, thanks to the fast calculation and the satisfactory temporal prediction of landslides, the SLIP model applied on the study area shows certain potential as a landslides forecasting tool on a regional scale.

scholarly journals Integrating Satellite Soil Moisture and Rainfall Data on a Data-Driven Model for the Assessment of Shallow Landslides Hazard

Proceedings ◽  
2019 ◽  
Vol 30 (1) ◽  
pp. 42
Author(s):  
Meisina ◽  
Bordoni ◽  
Lucchelli ◽  
Brocca ◽  
Ciabatta ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Methodological Approach ◽  
Regional Scale ◽  
Shallow Landslides ◽  
Predisposing Factors ◽  
Data Driven ◽  
Triggering Factors ◽  
Physically Based ◽  
Physically Based Models ◽  
Triggering Events

Shallow landslides are very dangerous phenomena, widespread all over the world, which could provoke significant damages to buildings, roads, facilities, cultivations and, sometimes, loss of human lives. It is then necessary assessing the most prone zones in a territory which is particularly susceptible to these phenomena and the frequency of the events, according to the return time of the triggering events, which generally correspond to intense and concentrated rainfalls. Susceptibility and hazard of a territory are usually assessed by means of physically-based models, that quantify the hydrological and the mechanical responses of the slopes according to particular rainfall amounts. Whereas, these methodologies could be applied in a reliable way in little catchments, where geotechnical and hydrological features of the materials affected by shallow failures are homogeneous. Moreover, physically-based models require, sometimes, significant computation power, which limit their implementations at regional scale. Data-driven models could overcome both of these limitations, even if they are generally built up taking into only the predisposing factors of shallow instabilities. Thus, they allow usually to estimate the susceptibility of a territory, without considering the frequency of the triggering events. It is then required to consider also triggering factors of shallow landslides to allow these methods to estimate also the hazard. This work presents the preliminary results of the development and the implementation of data-driven model able to estimate the hazard of a territory towards shallow landslides. The model is based on a Genetic Algorithm Model (GAM), which links geomorphological, hydrological, geological and land use predisposing factors to triggering factors of shallow failures. These triggering factors correspond to the soil moisture content and to the rainfall amounts, which are available for entire a study area thanks to satellite measures. The methodological approach is testing in different catchments of 30–40 km2 located in Oltrepò Pavese area (northern Italy), where detailed inventories of shallow landslides occurred during past triggering events and corresponding satellite soil moisture and rainfall maps are available. This work was made in the frame of the ANDROMEDA project, funded by Fondazione Cariplo.

scholarly journals A physics-based probabilistic forecasting model for rainfall-induced shallow landslides at regional scale

2016 ◽  
Author(s):  
Shaojie Zhang ◽  
Luqiang Zhao ◽  
Ricardo Delgado-Tellez ◽  
Hongjun Bao
Keyword(s):  
Regional Scale ◽  
Sichuan Province ◽  
Shallow Landslides ◽  
Physical Models ◽  
Forecasting Model ◽  
Probabilistic Forecasting ◽  
Prediction Ability ◽  
Technological Support ◽  
New Model ◽  
High Efficient

Abstract. Conventional outputs of physics-based landslide forecasting models are presented as deterministic warnings by calculating the safety factor (Fs) of potentially dangerous slopes. However, these models are highly dependent on variables such as cohesion force and internal friction angle which are affected by high degree of uncertainty especially at a regional scale, which result in unacceptable uncertainties of Fs. Under such circumstances, the outputs of physical models are more suitable if presented in the form of landslide probability values. In order to develop such models, a method to link the uncertainty of soil parameter values with landslide probability is devised. This paper proposes the use of Monte Carlo method to quantitatively express uncertainty by assigning random values to physical variables inside a defined interval. The inequality Fs<1 is tested for each pixel in n simulations which are integrated in a unique parameter. This parameter links the landslide probability to the uncertainties of soil mechanical parameters and is used to create a physics-based probabilistic forecasting model for rainfall-induced shallow landslides. The prediction ability of this model was tested in a case study, in which simulated forecasting of landslide disasters associated to heavy rainfalls on July 9 of 2013 in the Wenchuan earthquake region of Sichuan province, China was performed. The proposed model successfully forecasted landslides in 159 of the 176 disaster points registered by the geo-environmental monitoring station of Sichuan province. Such testing results indicate that the new model can be operated in a high efficient way and show more reliable results attributing to its high prediction accuracy. Accordingly, the new model can be potentially packaged into a forecasting system for shallow landslides providing technological support for the mitigation of these disasters at regional scale.

scholarly journals Hazard Maps of Shallow Landslides Associated to Infiltration Processes in the Sapuyes River Basin

2021 ◽  
Vol 41 (1) ◽  
pp. e84611
Author(s):  
Cristhian Rosales
Keyword(s):  
River Basin ◽  
Safety Factor ◽  
Hazard Analysis ◽  
Regional Scale ◽  
Temporal Distribution ◽  
Shallow Landslides ◽  
Hazard Mapping ◽  
Theoretical Approaches ◽  
Hazard Level ◽  
Infiltration Processes

Hazard mapping of shallow landslides associated with infiltration processes at a regional scale was carried out by means of the spatial and temporal distribution of safety factor and its classification, within hazard level ranges, into cells that represent hillside units in Sapuyes river basin, located near the city of Pasto in the Nariño department. Hazard assessment follows the theoretical approaches of the Iverson model (2000), which takes into account the redistribution of underground pore pressures associated with the transient infiltration of the rain and its effects on the time and location of landslides, considering that shallow landslides are associated with periods of rain with a short duration and greater intensity. Results showed that both the pressure heads and the safety factor are valid approximations for hazard analysis at regional scale and allow observing the transient physical process involved in the development of shallow landslides.

Envisaging post-earthquake snowmelt-induced shallow landslides under climate change

2020 ◽  
Author(s):  
Srikrishnan Siva Subramanian ◽  
Xuanmei Fan ◽  
Ali. P. Yunus ◽  
Theo van Asch ◽  
Qiang Xu ◽  
...  
Keyword(s):  
Climate Change ◽  
Prediction Models ◽  
Risk Mitigation ◽  
Regional Scale ◽  
Numerical Approach ◽  
Shallow Landslides ◽  
Slope Instability ◽  
Time Step ◽  
Macro Scale ◽  
Physically Based

&lt;p&gt;Seasonal snow cover occupies around 33 % of the earth&amp;#8217;s surface and draws the underlying landscape to serious natural hazards under climate change. The frequency of shallow landslides in seasonal cold regions is increasing, i.e., in the French Alps, Umbria in Italy, and Hokkaido in Japan. Further, tectonically active seasonally cold areas are more susceptible to spring landslides if an earthquake occurs during pre-winter. Hazard assessment and risk mitigation of snowmelt-induced landslides in such a scenario requires physically-based prediction models. However, studies focusing on the impacts of future snowmelt on shallow landslides are scarce. To comprehend these, the complex interactions between the atmosphere, hydrological, and geomechanical systems within a catchment under future climate need detailed studies. Present methods for snowmelt induced soil slope instability analysis are single-slope based and applied for individual cases. The challenge remain is to simulate the interactions between the atmosphere, hydrological, and geomechanical systems by coupling micro and macro-scale processes within a catchment for regional-scale future forecasts. In this perspective, we developed a novel spatially distributed, a physically-based numerical approach to compute slope stability within a basin, explicitly considering the atmosphere-ground, hydrology, and mechanical interactions on a day to day time step. Using this model, we envisaged future snowmelt-induced landslides under increased and decreased melt rates and post-earthquake settings. We obtained the probability density curves of these future landslides and found that under slower snowmelt rates, the occurrence probability of individual landslides remains the same, whereas, under rapid and increased snowmelt rates, the size-distribution of the landslides increase one magnitude and doubles if rapid snowmelt follows an earthquake.&lt;/p&gt;

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