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

<p>Seasonal snow cover occupies around 33 % of the earth’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.</p>

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.

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 THE FRAMEWORK ON MULTI-SCALE LANDSLIDE HAZARD EVALUATION IN CHINA

2016 ◽  
Vol XLI-B8 ◽  
pp. 105-107 ◽  
Author(s):  
W. Y. Li ◽  
C. Liu ◽  
J. Gao
Keyword(s):  
Hot Spot ◽  
Regional Scale ◽  
Landslide Hazard ◽  
Physical Models ◽  
Slope Instability ◽  
Hazard Evaluation ◽  
Landslide Risk ◽  
Physically Based Model ◽  
Multi Scale ◽  
Physically Based

Nowadays, Landslide has been one of the most frequent and seriously widespread natural hazards all over the world. How landslides can be monitored and predicted is an urgent research topic of the international landslide research community. Particularly, there is a lack of high quality and updated landslide risk maps and guidelines that can be employed to better mitigate and prevent landslide disasters in many emerging regions, including China. This paper considers national and regional scale, and introduces the framework on combining the empirical and physical models for landslide evaluation. Firstly, landslide susceptibility in national scale is mapped based on empirical model, and indicates the hot-spot areas. Secondly, the physically based model can indicate the process of slope instability in the hot-spot areas. The result proves that the framework is a systematic method on landslide hazard monitoring and early warning.

scholarly journals THE FRAMEWORK ON MULTI-SCALE LANDSLIDE HAZARD EVALUATION IN CHINA

2016 ◽  
Vol XLI-B8 ◽  
pp. 105-107 ◽  
Author(s):  
W. Y. Li ◽  
C. Liu ◽  
J. Gao
Keyword(s):  
Hot Spot ◽  
Regional Scale ◽  
Landslide Hazard ◽  
Physical Models ◽  
Slope Instability ◽  
Hazard Evaluation ◽  
Landslide Risk ◽  
Physically Based Model ◽  
Multi Scale ◽  
Physically Based

Nowadays, Landslide has been one of the most frequent and seriously widespread natural hazards all over the world. How landslides can be monitored and predicted is an urgent research topic of the international landslide research community. Particularly, there is a lack of high quality and updated landslide risk maps and guidelines that can be employed to better mitigate and prevent landslide disasters in many emerging regions, including China. This paper considers national and regional scale, and introduces the framework on combining the empirical and physical models for landslide evaluation. Firstly, landslide susceptibility in national scale is mapped based on empirical model, and indicates the hot-spot areas. Secondly, the physically based model can indicate the process of slope instability in the hot-spot areas. The result proves that the framework is a systematic method on landslide hazard monitoring and early warning.

scholarly journals Regional-scale susceptibility modelling of shallow landslides involving the weathered and fractured sub-surface bedrock

2021 ◽  
Author(s):  
Enrico D'Addario ◽  
Leonardo Disperati ◽  
Josè Luis Zezerè ◽  
Raquel Melo ◽  
Sergio Cruz Oliveira
Keyword(s):  
Slope Failure ◽  
Regional Scale ◽  
Shallow Landslide ◽  
Shallow Landslides ◽  
Data Driven ◽  
Field Observations ◽  
Rupture Surface ◽  
Slope Deposits ◽  
Physically Based ◽  
Engineering Geological Properties

<p>Landsliding is a complex phenomenon and its modelling aimed at predicting where the processes are most likely to occur is a tricky issue to be performed. Apart the chosen modelling approach, for both data-driven and physically-based models, paying adequate attention to the predisposing and triggering factors, as well as the input parameters is no less important. Generally, shallow landslides mobilize relatively small volumes of material sliding along a nearly planar rupture surface which is assumed to be roughly parallel to the ground surface. In the literature it is also widely accepted that shallow landslides involve only unconsolidated slope deposits (i.e., the colluvium), then the rupture surface corresponds to the discontinuity between the bedrock and the overlying loose soil. In this work, based on systematic field observations, we highlight that shallow landslides often involve also portions of the sub-surface bedrock showing different levels of weathering and fracturing. Then, we show that the engineering geological properties of slope deposits, as well as those related to the underlying bedrock, must be considered to obtain more reliable shallow landslides susceptibility assessment. As a first task, a multi-temporal shallow landslide inventory was built by photointerpretation of aerial orthoimages. Then, a new fieldwork-based method is proposed and implemented to acquire, process and spatialize the engineering geological properties of both slope deposits and bedrock. To support the regional scale approach, field observations were collected within, in the neighbour and far from the shallow landslide areas. Finally, both physically-based and data-driven methods were implemented to assess and compare shallow landslide susceptibility at regional scale, as well as to analyse the role of spatial distribution of rock mass quality for shallow slope failure development. The results highlight that, according to geology, structural setting and morphometric conditions, bedrock properties spatially change, defining clusters influencing both the distribution and characters of shallow landslides. As a consequence, the physically-based modelling provides better prediction accuracy when two possible rupture surfaces are analysed, the shallower one located at the slope deposit / bedrock discontinuity, and the deeper one located at the bottom of the fractured and weathered bedrock horizon. Even though the physically-based and data-driven models provide similar results in terms of ROC curves, the resulting susceptibility maps highlight quite substantial differences.</p>

scholarly journals Canadian Continental-Scale Hydrology under a Changing Climate: A Review

Water ◽  
2021 ◽  
Vol 13 (7) ◽  
pp. 906
Author(s):  
Tricia A. Stadnyk ◽  
Stephen J. Déry
Keyword(s):  
Climate Change ◽  
Prediction Models ◽  
Global Climate ◽  
Regional Scale ◽  
Resource Planning ◽  
Drainage Basins ◽  
Continental Scale ◽  
Global Mean Temperature ◽  
Northern Regions ◽  
Hydrologic Change

Canada, like other high latitude cold regions on Earth, is experiencing some of the most accelerated and intense warming resulting from global climate change. In the northern regions, Arctic amplification has resulted in warming two to three times greater than global mean temperature trends. Unprecedented warming is matched by intensification of wet and dry regions and hydroclimatic cycles, which is altering the spatial and seasonal distribution of surface waters in Canada. Diagnosing and tracking hydrologic change across Canada requires the implementation of continental-scale prediction models owing the size of Canada’s drainage basins, their distribution across multiple eco- and climatic zones, and the scarcity and paucity of observational networks. This review examines the current state of continental-scale climate change across Canada and the anticipated impacts to freshwater availability, including the role of anthropogenic regulation. The review focuses on continental and regional-scale prediction that underpins operational design and long-term resource planning and management in Canada. While there are significant process-based changes being experienced within Canadian catchments that are equally—if not more so—critical for community water availability, the focus of this review is on the cumulative effects of climate change and anthropogenic regulation for the Canadian freshwater supply.

scholarly journals Regional physically based landslide early warning modelling: soil parameterisation and validation of the results

2018 ◽  
Author(s):  
Teresa Salvatici ◽  
Veronica Tofani ◽  
Guglielmo Rossi ◽  
Michele D'Ambrosio ◽  
Carlo Tacconi Stefanelli ◽  
...  
Keyword(s):  
Slope Stability ◽  
Real Time ◽  
Early Warning ◽  
Regional Scale ◽  
Early Warning Systems ◽  
Shallow Landslides ◽  
Mean Annual Precipitation ◽  
Good Prediction Accuracy ◽  
Physically Based ◽  
Landslide Early Warning

Abstract. In this work, we apply a physically-based model, namely the HIRESSS (High REsolution Stability Simulator) model, to forecast the occurrence of shallow landslides at regional scale. The final aim is the set-up of an early warning system at regional scale for shallow landslides. HIRESSS is a physically based distributed slope stability simulator for analysing shallow landslide triggering conditions in real time and in large areas using parallel computational techniques. The software can run in real-time by assimilating weather data and uses Monte Carlo simulation techniques to manage the geotechnical and hydrological input parameters. The test area is a portion of the Valle d'Aosta region, located in North-West Alpine mountain chain. The geomorphology of the region is characterized by steep slopes with elevations ranging from 400 m a.s.l. of Dora Baltea's river floodplain to 4810 m a.s.l. of Mont Blanc. In the study area, the mean annual precipitation is about 800–900 mm. These features lead to a high hydrogeological hazard in the whole territory, as mass movements interest the 70 % of the municipality areas (mainly shallow rapid landslides and rock falls). In order to apply the model and to increase its reliability, an in-depth study of the geotechnical and hydrological properties of hillslopes controlling shallow landslides formation was conducted. In particular, two campaigns of on site measurements and laboratory experiments were performed with 12 survey points. The data collected contributes to generate input map of parameters for HIRESSS model. In order to take into account the effect of vegetation on slope stability, the contribution of the root cohesion has been also taken into account based on the vegetation map and literature values. The model was applied in back analysis on two past events that have affected Valle d'Aosta region between 2008 and 2009, triggering several fast shallow landslides. The validation of the results, carried out using a database of past landslides, has provided good results and a good prediction accuracy of the HIRESSS model both from temporal and spatial point of view. A statistical analysis of the HIRESSS outputs in terms of failure probability has been carried out in order to define reliable alert levels for regional landslide early warning systems.

scholarly journals Catchment-Scale Integrated Surface Water-Groundwater Hydrologic Modelling Using Conceptual and Physically Based Models: A Model Comparison Study

Water ◽  
2020 ◽  
Vol 12 (2) ◽  
pp. 363 ◽  
Author(s):  
Mohammad Bizhanimanzar ◽  
Robert Leconte ◽  
Mathieu Nuth
Keyword(s):  
Surface Water ◽  
Groundwater Recharge ◽  
Water Table ◽  
Model Comparison ◽  
Unsaturated Flow ◽  
Regional Scale ◽  
Catchment Scale ◽  
Time Step ◽  
Mike She ◽  
Physically Based

This paper presents a comparative analysis of the use of an externally linked (MOBIDIC-MODFLOW) and a physically based (MIKE SHE) surface water-groundwater model to capture the integrated hydrologic responses of the Thomas Brook catchment, in Canada. The main objective of the study is to investigate the effect of simplification in representation of the hydrological processes in MOBIDIC-MODFLOW on its simulation accuracy. To this aim, MOBIDIC and MODFLOW were coupled in order to sequentially exchange the groundwater recharge and baseflow discharges within each computation time step. Using identical sets of hydrogeological properties for the two models, the coefficients of the gravity and capillary reservoirs in MOBIDIC were calibrated so as to closely predict the hydrological budget of the catchment simulated with MIKE SHE. The simulated results show that the two models can closely replicate the observed water table responses at two monitoring wells. However, in very shallow water table locations, the instantaneous response of the water table was not precisely captured in MOBIDIC-MODFLOW. Additionally, the simplified conceptualization of the unsaturated flow in MOBIDIC-MODFLOW resulted in overestimated groundwater recharge during spring and underestimation during summer. Moreover, the computational efficiency of MOBIDIC-MODFLOW, as compared to MIKE SHE, along with less required input data, confirms its potential for regional scale groundwater-surface water interaction modelling applications.

scholarly journals From slope- to regional-scale shallow landslides susceptibility assessment using TRIGRS

2014 ◽  
Vol 2 (12) ◽  
pp. 7409-7464 ◽  
Author(s):  
M. Bordoni ◽  
C. Meisina ◽  
R. Valentino ◽  
M. Bittelli ◽  
S. Chersich
Keyword(s):  
Regional Scale ◽  
Field Measurements ◽  
Shallow Landslides ◽  
Susceptibility Assessment ◽  
Physically Based Model ◽  
Distributed Models ◽  
Landslides Susceptibility ◽  
Physically Based ◽  
Monitoring Activity

Abstract. Rainfall-induced shallow landslides are common phenomena in many parts of the world, affecting cultivations and infrastructures and causing sometimes human losses. Assessing the shallow landslides susceptibility is fundamental for land planning at different scales. This work defines a reliable methodology to extend the slope stability analysis from the local to the regional scale by using a well established physically-based model (TRIGRS-Unsaturated). The model is applied at first for a sample slope and then to the surrounding area of 13.4 km2 in Oltrepo Pavese (Northern Italy). In order to obtain more reliable input data for the model, a long-term hydro-meteorological monitoring has been carried out at the sample slope, that has been assumed as representative of the study area. Field measurements allowed for identifying the triggering mechanism of shallow failures and were used to calibrate the model. After obtaining modelled pore water pressures at the slope scale consistent with those measured during the monitoring activity, more reliable trends have been modelled also for past landslide events, as the April 2009 event that has been assumed as benchmark. The shallow landslides susceptibility assessment obtained using TRIGRS-Unsaturated for the benchmark event appears good for both the monitored slope and the whole study area, with better results if a pedological instead of geological zoning is considered at regional scale. The scheme followed in this work allows for obtaining better results of shallow landslides susceptibility assessment in terms of reduction of overestimation of unstable areas with respect to other distributed models applied in the past.

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