Improving basin scale shallow landslide modelling using reliable soil thickness maps

Segoni, Samuele; Rossi, G.; Catani, Filippo

doi:10.1007/s11069-011-9770-3

Cited by 77 publications

(29 citation statements)

References 29 publications

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“…Lanni et al, 2013) or soil thickness (e.g. Catani et al, 2010;Segoni et al, 2012), is still one of the most difficult and laborious parameters to measure on a catchment scale, yet it is crucial for physically based modelling of slope stability (Dietrich et al, 1995;Lanni et al, 2012;Segoni et al, 2012). It is defined as the thickness of unconsolidated material covering the earth's surface, i.e.…”

Section: Model Parametersmentioning

confidence: 99%

“…Furthermore, the depth of past landslides can be derived from multitemporal, remotely sensed elevation data (Zieher et al, 2016). For regolith depth mapping, regression models correlating regolith depth to either elevation, slope angle or other derivatives were used in previous case studies on shallow landslide susceptibility (Baum et al, 2010;Lanni et al, 2012;Salciarini et al, 2006;Segoni et al, 2012). For the assessment of regolith depth in the Laternser valley, 126 dynamic cone penetration tests (DCPTs) were conducted along four transects.…”

Section: Model Parametersmentioning

confidence: 99%

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Sensitivity analysis and calibration of a dynamic physically based slope stability model

Zieher

Rutzinger

Schneider‐Muntau

et al. 2017

Nat. Hazards Earth Syst. Sci.

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Abstract. Physically based modelling of slope stability on a catchment scale is still a challenging task. When applying a physically based model on such a scale (1 : 10 000 to 1 : 50 000), parameters with a high impact on the model result should be calibrated to account for (i) the spatial variability of parameter values, (ii) shortcomings of the selected model, (iii) uncertainties of laboratory tests and field measurements or (iv) parameters that cannot be derived experimentally or measured in the field (e.g. calibration constants). While systematic parameter calibration is a common task in hydrological modelling, this is rarely done using physically based slope stability models. In the present study a dynamic, physically based, coupled hydrological-geomechanical slope stability model is calibrated based on a limited number of laboratory tests and a detailed multitemporal shallow landslide inventory covering two landslide-triggering rainfall events in the Laternser valley, Vorarlberg (Austria). Sensitive parameters are identified based on a local one-at-a-time sensitivity analysis. These parameters (hydraulic conductivity, specific storage, angle of internal friction for effective stress, cohesion for effective stress) are systematically sampled and calibrated for a landslide-triggering rainfall event in August 2005. The identified model ensemble, including 25 "behavioural model runs" with the highest portion of correctly predicted landslides and non-landslides, is then validated with another landslide-triggering rainfall event in May 1999. The identified model ensemble correctly predicts the location and the supposed triggering timing of 73.0 % of the observed landslides triggered in August 2005 and 91.5 % of the observed landslides triggered in May 1999. Results of the model ensemble driven with raised precipitation input reveal a slight increase in areas potentially affected by slope failure. At the same time, the peak run-off increases more markedly, suggesting that precipitation intensities during the investigated landslide-triggering rainfall events were already close to or above the soil's infiltration capacity.

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Section: Model Parametersmentioning

confidence: 99%

Section: Model Parametersmentioning

confidence: 99%

Sensitivity analysis and calibration of a dynamic physically based slope stability model

Zieher

Rutzinger

Schneider‐Muntau

et al. 2017

Nat. Hazards Earth Syst. Sci.

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“…This is mainly due to: the necessary simplifications introduced in hydrological and geotechnical models (Crosta and Frattini, 2003;, the errors introduced by rainfall predictions (Jakob et al, 2012), the consequences of the uncertainties in the knowledge of morphometric, mechanical and hydrological parameters of soils (Segoni et al, 2012) and the extremely high computational effort required to operate on a basin scale .…”

Section: Introductionmentioning

confidence: 99%

HIRESSS: a physically based slope stability simulator for HPC applications

Rossi

Catani

Leoni

et al. 2013

Nat. Hazards Earth Syst. Sci.

143

115

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Abstract. HIRESSS (HIgh REsolution Slope StabilitySimulator) is a physically based distributed slope stability simulator for analyzing shallow landslide triggering conditions in real time and on large areas using parallel computational techniques. The physical model proposed is composed of two parts: hydrological and geotechnical. The hydrological model receives the rainfall data as dynamical input and provides the pressure head as perturbation to the geotechnical stability model that computes the factor of safety (FS) in probabilistic terms. The hydrological model is based on an analytical solution of an approximated form of the Richards equation under the wet condition hypothesis and it is introduced as a modeled form of hydraulic diffusivity to improve the hydrological response. The geotechnical stability model is based on an infinite slope model that takes into account the unsaturated soil condition. During the slope stability analysis the proposed model takes into account the increase in strength and cohesion due to matric suction in unsaturated soil, where the pressure head is negative. Moreover, the soil mass variation on partially saturated soil caused by water infiltration is modeled.The model is then inserted into a Monte Carlo simulation, to manage the typical uncertainty in the values of the input geotechnical and hydrological parameters, which is a common weak point of deterministic models. The Monte Carlo simulation manages a probability distribution of input parameters providing results in terms of slope failure probability. The developed software uses the computational power offered by multicore and multiprocessor hardware, from modern workstations to supercomputing facilities (HPC), to achieve the simulation in reasonable runtimes, compatible with civil protection real time monitoring.A first test of HIRESSS in three different areas is presented to evaluate the reliability of the results and the runtime performance on large areas.

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“…4); and (2) a map of the soil thickness -interpreted as the depth to bedrock -based on the simplified geomorphologically indexed soil thickness (sGIST) model (Catani et al 2010;Segoni et al 2012) (Fig. 5).…”

Section: Resultsmentioning

confidence: 99%

Debris flow run-out simulation and analysis using a dynamic model

Melo¹,

Asch²,

Zêzere³

2017

Preprint

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Abstract.Only two months after a huge wildfire occurred in the upper part of a valley located in Central Portugal, several debris flows were triggered by intense rainfall. The event caused infrastructural and economical damage, although no life was lost. The present research aims to simulate the run-out of two debris flows occurred during the event as well as to calculate by back-analysis the rheological parameters and the excess rain involved. Thus, a dynamic model was used, which 10 integrates surface runoff, concentrated erosion along the channels, propagation and deposition of flow material. The rheological and entrainment parameters obtained for the most accurate simulation were then used to perform three scenarios of debris flows run-out at the basin scale. Due to the lack of quantitative information to validate these models, the results were compared with historical references of debris flow events in the study area. Six streams were identified, where debris flows occurred in the past and caused material damage and loss of lives. The worst-case scenario carried out at the basin 15 scale shows a potential inundation that may affect 345 buildings at the present day.

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Improving basin scale shallow landslide modelling using reliable soil thickness maps

Cited by 77 publications

References 29 publications

Sensitivity analysis and calibration of a dynamic physically based slope stability model

Sensitivity analysis and calibration of a dynamic physically based slope stability model

HIRESSS: a physically based slope stability simulator for HPC applications

Debris flow run-out simulation and analysis using a dynamic model

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