A distributed physically based model to predict timing and spatial distribution of
rainfall-induced shallow landslides.
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A distributed physically based model to predict timing and spatial distribution of rainfall-induced shallow landslides

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Shallow landslides induced by rainfall are among the most costly and deadly natural hazards, which mostly afflict mountainous and steep terrain regions. Crucial role in the initiation of these events is attributed to subsurface hydrology and how changes in the soil water regime can affect significantly the soil shear strength. Rainfall infiltration results in a decrease of matric suction, which is followed by a rapid drop in apparent cohesion. Especially on steep slopes in shallow soils, this loss of shear strength can lead to failure even in the unsaturated zone before positive water pressures are developed. Evidently, fundamental elements for an efficient prediction of rainfall-induced landslides are the interdependence of shear strength and suction, as well as the temporal evolution of suction during the wetting and drying process. A distributed physically based model, raster-based and continuous in space and time, was developed in order to investigate the interactions between surface and subsurface hydrology and shallow landslides initiation. In this effort emphasis is given to the modelling of the temporal evolution of hydrological processes and their triggering effects to soil slip occurrences. Specifically, the 3D variably saturated flow through soil and the resulting water balance is modelled using the Cellular Automata concept. Evapotranspiration, root water uptake and soil hydraulic hysteresis are taken into account for the continuous simulation of soil water content during storm and inter-storm periods. A multidimensional limit equilibrium analysis is utilized for the computation of the stability of every cell by taking into account the basic principles of unsaturated soil mechanics. A test case of a serious and diffused in space landslide event in Switzerland is investigated for the verification of the model.

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A distributed physically based model to predict timing and spatial distribution of rainfall-induced shallow landslides

  1. 1. A distributed physically based model to predict timing and spatial distribution of rainfall-induced shallow landslides. Grigorios G. Anagnostopoulos and Paolo Burlando Institute of Environmental Engineering, ETH Zurich, Switzerland correspondence: anagnostopoulos@ifu.baug.ethz.ch 1. Introduction 3. Geotechnical Component 5. Test case: Napf catchment A distributed physically based model, raster-based and continuous in space and time, was developed in order to investigate the interactions between surface and subsurface hydrology and shallow landslides initiation. In this effort emphasis is given to the modelling of the temporal evolution of hydrological processes and their triggering effects to soil slip occurrences. A multidimensional limit equilibrium analysis is utilized for the computation of the stability of every cell by taking into account the basic principles of unsaturated soil mechanics. Abstract No: NH 31B-1548 Napf catchment is located in Kanton Bern, Switzerland. It spans over an area of 2, 5 km2 , 48 % of which is forested. A 3-hour precipitation event on 15-16 July 2002 caused many soil slips. 2. Hydrological Component Particular weight is given to the modeling of hydrological processes in order to investigate the hydrological triggering mechanisms and the importance of continuous modeling of water balance to detect timing and location of soil slip occurrences. • Evapotranspiration is computed using the Priestley-Taylor method. • The failure surface is assumed to be planar and plastic limit equilibrium conditions are considered. • At the upslope and downslope faces we assume that active and passive stresses respectively are developed. A 3x3 m DEM is available and the soil map of Switzerland is used for the identification of the soil classes present in the catchment. As meteorological input the historical record of the Napf station was used, which is located 5 km north of the cathcment. • At the lateral faces earth pressures at rest develop and the shear resistance is also taken into account. • Root cohesion is considered at both lateral faces and at the base of the column. x y • Root water uptake is taken into account. • Surface run-off is routed using the kinematic wave approach. z σv Ka σv (i-1,j) qsurface Hponded (i,j-1) (i,j-1,0) σv Fa Active stresses P F0 Kp σv φ φ W Τlat 0 K0 σv Τlat φ φ F'0 Fp Passive stresses Ν Τ The output of our model is tested against a state-of-the-art model (TRIGRS, Baum and Godt 2010) and against the inventory of observed landslides. θ • The model correctly captures most of the observed landslides (True Positive Rate: 43,2% against 23,5% of TRIGRS). 4. Soil depth modeling Soil depth is one of the most significant parameters controlling the factor of safety (FS) , especially for depths of less than 1.5 m, within which small variations produce very rapid changes in the FS. The approach of Pelletier et al. is to solve numerically the steady-state form of the landscape evolution. • It reduces the overestimation of landsliding cells, which is a main artifact of most of the existing models (sliding area: 6.5% against 13% of TRIGRS). • The continuous modeling of soil moisture and the inclusion of many feedback mechanisms improved the predictive ability of the model. The timing is also affected compared to TRIGRS mainly due to the more detailed hydrological component. (i,j) qinf (i,j-1,1) (i,j+1) (i,j-1,2) (i,j+1,0) (i,j+1,1) (i,j-1,k) x σv A • The 3-D flow of water through soil and the resulting water balance is considered, by taking into account both saturated and unsaturated conditions • Soil hydraulic hysteresis is also included because it can be crucial for the continuous simulation of soil water content during storm and inter-storm periods. z qinflow (i,j+1,2) qoutflow (i,j+1,k) (i,j-1,n) (i,j+1,n) @h @t p ph ⇢b 2 e (h0 1+|rz|2 + = ⇢s P0 1 + |rz| ⇣ ⌘ hrz D3 r 1 (|rz|/Sc )2 The parameters were determined by searching through the parameter space the parameter set that minimizes the root-mean-square difference between predicted and measured soil depth data. References [1] G.G. Anagnostopoulos, P. Burlando, (2011). Object-oriented computational framework for the simulation of variably saturated flow, using a reduced complexity model, Submitted in Environmental Modelling & Software [2] R.L. Baum, J.W. Godt, (2010). Estimating the timing and location of shallow rainfall-induced landslides using a model for transient, unsaturated infiltration. Journal of Geophysical Research, Vol 115 [3] J. Pelletier, C. Rasmussen (2009). Geomorphically based predictive mapping of soil thickness in upland watersheds. Water Resources Research, Vol 45

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