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

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.

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

Natural Hazards and Earth System Sciences Discussions ◽

10.5194/nhessd-3-3487-2015 ◽

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.

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Modelling supraglacial debris-cover evolution from the single glacier to the regional scale: an application to High Mountain Asia

10.5194/tc-2021-233 ◽

2021 ◽

Author(s):

Loris Compagno ◽

Matthias Huss ◽

Evan Stewart Miles ◽

Michael James McCarthy ◽

Harry Zekollari ◽

...

Keyword(s):

Mass Balance ◽

Temporal Evolution ◽

Regional Scale ◽

Global Scale ◽

High Mountain ◽

Surface Mass ◽

Future Evolution ◽

Debris Cover ◽

Scale Modelling ◽

Spatio Temporal

Abstract. Currently, about 12–13 % of High Mountain Asia's glacier area is debris-covered, altering its surface mass balance. However, in regional-scale modelling approaches, debris-covered glaciers are typically treated as clean-ice glaciers, leading to a potential bias when modelling their future evolution. Here, we present a new approach for modelling debris area and thickness evolution, applicable from single glaciers to the global scale. We implement the module into the Global Glacier Evolution Model (GloGEMflow), a combined mass-balance ice-flow model. The module is initialized with both glacier-specific observations of the debris’ spatial distribution and estimates of debris thickness, accounts for the fact that debris can either enhance or reduce surface melt depending on thickness, and enables representing the spatio-temporal evolution of debris extent and thickness. We calibrate and evaluate the module on a select subset of glaciers, and apply the model using different climate scenarios to project the future evolution of all glaciers in High Mountain Asia until 2100. Compared to 2020, total glacier volume is expected to decrease by between 35 ± 15 % and 80 ±11 %, which is in line with projections in the literature. Depending on the scenario, the mean debris-cover fraction is expected to increase, while mean debris thickness is modelled to show only minor changes, albeit large local thickening is expected. To isolate the influence of explicitly accounting for supraglacial debris-cover, we re-compute glacier evolution without the debris-cover module. We show that glacier geometry, area, volume and flow velocity evolve differently, especially at the level of individual glaciers. This highlights the importance of accounting for debris-cover and its spatio-temporal evolution when projecting future glacier changes.

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Impacts of future climate and land cover changes on landslide susceptibility: regional scale modelling in the Val d’Aran region (Pyrenees, Spain)

Landslides ◽

10.1007/s10346-021-01775-6 ◽

2021 ◽

Author(s):

Marcel Hürlimann ◽

Zizheng Guo ◽

Carol Puig-Polo ◽

Vicente Medina

Keyword(s):

Land Cover ◽

Landslide Susceptibility ◽

Regional Scale ◽

Future Climate ◽

Land Cover Changes ◽

Scale Modelling

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Effects of coupled hydro-mechanical model considering dual-phase fluid flow on potential for shallow landslides at a regional scale

Natural Hazards ◽

10.1007/s11069-021-05114-9 ◽

2021 ◽

Author(s):

Sinhang Kang ◽

Byungmin Kim

Keyword(s):

Fluid Flow ◽

Mechanical Model ◽

Regional Scale ◽

Shallow Landslides ◽

Dual Phase ◽

Phase Fluid

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Regional-scale modelling of the cumulative impact of wind farms on bats

Biodiversity and Conservation ◽

10.1007/s10531-013-0515-3 ◽

2013 ◽

Vol 22 (8) ◽

pp. 1821-1835 ◽

Cited By ~ 26

Author(s):

F. Roscioni ◽

D. Russo ◽

M. Di Febbraro ◽

L. Frate ◽

M. L. Carranza ◽

...

Keyword(s):

Regional Scale ◽

Wind Farms ◽

Cumulative Impact ◽

Scale Modelling

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

Natural Hazards and Earth System Science ◽

10.5194/nhess-11-1927-2011 ◽

2011 ◽

Vol 11 (7) ◽

pp. 1927-1947 ◽

Cited By ~ 61

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.

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

Proceedings ◽

10.3390/proceedings2019030042 ◽

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.

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