gis-based 3d modelling for landslide hazard assessment:
DESCRIPTION
GIS-based 3D modelling for landslide hazard assessment:. Séverine Bilgot Aurèle Parriaux. Increasing the objectivity of hazard maps. . Introduction. 6% of the Swiss territory affected by landslides Occurrences and potential damages always increasing - PowerPoint PPT PresentationTRANSCRIPT
GIS-based 3D modelling forlandslide hazard assessment:
Séverine BilgotAurèle Parriaux
Increasing the objectivity of hazard maps.
2
Introduction
6% of the Swiss territory affected by landslides
Occurrences and potential damages always increasing
Necessity to have objective and easy to update hazard maps
3
Identification of susceptibility factors
Intrinsic factors: Resisting forces
Cohesion Friction (depends on g, a,
j) g, c, j
For rock material: =f(geotype, grade, D, GSI)
For loose material: =f(granulometry, plasticity)
4
Identification of susceptibility factors
Intrinsic factors: Resisting forces
Cohesion Friction (depends on g, a,
j)
Driving forces Gravity (depends on g, a) Percolation (depends on i)
i= grad h
Measured piezometric level (boreholes, springs, etc)
Spatial distribution of K
5
Identification of susceptibility factors
Extrinsic factors: Vegetation
6
Identification of susceptibility factors
Extrinsic factors: Vegetation
Permafrost melting Depending on:
Location (altitude, aspect)
Susceptibility of the formation =f(granulometry, plasticity)
7
Identification of susceptibility factors
Extrinsic factors: Vegetation
Permafrost melting
Anthropic impact
8
Methodology
Factor of safety
Hazard map
Pre-existingdata
Fielddata+
Hydraulicgradient
Predisposition map
3D parametersmodel
9
Methodology
Hazard map
Pre-existingdata
Fielddata+
Hydraulicgradient
Predisposition mapFactor of
safety
3D parametersmodel
10
Integration of pre-existing data
Collecting datafrom previous
projects
Integrating them in a geodatabase
11
Field mapping Phenomena Geology
Discontinuities Formations Fracturation, grade and GSI Granulometry and plasticity
Hydrology Springs and wet areas Supposed associated aquifer
Vegetation Structures
12
Methodology
3D parametersmodel
Hazard map
Pre-existingdata
Fielddata+
Hydraulicgradient
Predisposition mapFactor of
safety
13
3D parameters model
Determination of the 3D limits of the structural units
Kriging of the dips and strikes in each structural units
Modelling the rock formations with respect to field observation, boreholes information, profiles and dip and strike interpolation
Modelling the loose formations with respect to field observation, boreholes information, profiles and modelled rock formations
Kriging of the parameters inside each polygone or using the database
14
3D parameters model
15
Methodology
Hazard map
Pre-existingdata
Fielddata+
Hydraulicgradient
Predisposition mapFactor of
safety
3D parametersmodel
16
Hydraulic gradient evaluation
Connecting each piezometric level, spring or wet area to the corresponding aquifer
Evaluating the geometry of each aquifer according to the repartition of K in the model
Interpolating the hydraulic head in each aquifer
Calculating the hydraulic gradient
17
Methodology
Hazard map
Pre-existingdata
Fielddata+
Hydraulicgradient
Predisposition mapFactor of
safety
3D parametersmodel
18
3D factor of safety calculation
Calculation of the FoS at each sliding level indicated on boreholes
For each (x,y) couple, calculation of the FoS at each intersection with faults
For each (x,y) without calculated FoS < 1, calculation of the FoS at each z step, keeping the lowest value
19
Methodology
Predisposition map
Hazard map
Pre-existingdata
Fielddata+
Hydraulicgradient
Factor of safety
3D parametersmodel
20
Predisposition map
Applying bayesian probability model to evaluate the weight of frozen soil, vegetation and anthropic infrastructures in the susceptibility to landslides
Calculating the predisposition map
Verifying the coherence of the predisposition map with respect to the map of phenomena
21
Methodology
Hazard map
Pre-existingdata
Fielddata+
Hydraulicgradient
Predisposition mapFactor of
safety
3D parametersmodel
22
Hazard map
23
Conclusion: at local scale
Applicable on most of instable areas (already tested on 10 sites in Switzerland and 2 in Kyrgyzstan)
Allows full transparency of the results and easy updates Data can be easily re-used (high interoperability) Only one common software to use Toolboxes can be used separately in other domains
(natural resources management, tunnel engineering, etc)
In order to reduce the costs and to provide better results, development of equivalent plugins for GRASS (in progress)
24
Indicative maps
Data infrastructure and standardize process allows to change the scale easily
Methodology applicable at larger scale with simple Quaternary structures (without lenses): Using boreholes data and databases to evaluate the
parameters Using geoportals and aerial photographies for maps
of phenomena, vegetation and anthropic impact