Sensitivity Analysis of a Physicallybased Landslide Model

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Sensitivity Analysis of a Physically-based
Landslide Model

• From evaluating sensitivity to reporting
  probability

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A Review of Project Goals

• Identify landslide susceptible areas on the
  watershed scale zones with a low Stability Index
  (SI).
• Evaluate the impacts of roads, structures, and
  vegetation on slope stability.
• Develop recommendations for slide-prone locations
  and for the stabilization of open scars.

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Infinite Slope Stability Model
D
Dw
W
T
N
f
q
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Infinite Slope Stability Model
(Hammond et al. 1992)
Cr Cohesion due to roots f Angle of Internal
Friction Cs Cohesion due to soil D Depth
below soil surface q Slope angle Dw Depth
below water table rs Wet soil density rw
Density of Water
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SINMAP

• Stability INdex MAPing (Pack, Tarboton, Goodwin)
• Environment ArcView extension
• Language C and Avenue
• Theoretical basis Infinite Plane Slope Stability
  Model
• Required Data Digital Elevation Model, Parameter
  Calibration Regions, User-Defined Parameters
• Stochastic Element Parameters are allowed to be
  uncertain following uniform distribution between
  specified limits

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Why Perform Sensitivity Analysis?

• Evaluate the precision required of future field
  measurements.
• Assess the stability of model outcome
• Report predictions in probabilistic terms

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Implemented Formula
C dimensionless Cohesion T Transmissivity R
Rate of Recharge (steady state) r density ratio
(rw/rs) a specific catchment area (flow
calculated using D? method)
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Sensitivities of SINMAP User-Defined Parameters

• Water input (R) RainfallThroughfall
• Transmissivity(T) ConductivityDepth Flow
• Cohesion(C) Sc / (Depth Failuregsat)
• Angle of Internal Friction (f) f(Porosity)

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A Statistical Approach

• c N(m,s2) ? C
• n N(m,s2) ? f
• log Ksat N(m,s2) ? T
• rsat N(m,s2) ? C
• Dflow Dfailure ?? ? T, C
• R constant

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Sensitivity Response

• What constitutes sensitivity?
• Changes in the global mean.
• Variability in FS at a range of selected points.
• Total number of grid cells that lie below the
  instability threshold.

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Assessment

• 1. Precision required of future field
  measurements.
• Ksat and f require careful measurement, while
  depth, bulk density, and soil cohesion (in
  non-cemented soils) can be estimated.

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Assessment

• 2. Stability of model outcome
• The locations of zones of predicted instability
  are not sensitive to changes in calibration
  parameters. The fraction of total area predicted
  to be unstable, however, changes significantly at
  the outer range of cumulative parameter
  distribution.

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Assessment

• 3. Reporting predictions in probabilistic terms
• Sensitivity Analysis has allowed us to generate
  an Expected Probability of Failure map. This
  is a considerable improvement over binary
  instability maps.

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General Conclusions

• The SA was pursued in order to reveal the hidden
  instabilities of the model, and it does achieve
  this end.
• Additionally, a rigorous SA gives the modeler
  insight to the variables that truly drive a
  model.
• In this case the SA has become a useful component
  of results presentation, presenting the end-user
  with more complete information on landslide risk
  in the watershed.

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Thank you