Prediction of Landslide Runout - IPGPstep.ipgp.fr/images/c/c1/05_05_Runout_Analysis.pdf ·...

26
Prediction of Landslide Runout Oldrich Hungr and Scott McDougall University of British Columbia Earth and Ocean Sciences α = fahrböschung α’ = travel angle Center of gravity Theoretically, in a frictional material (dry sand, broken rock), the travel angle should equal the angle of friction, φ. The angle α equals approximately α’. If the travel angle is less than φ, pore-pressure is involved Fahrböschung (travel angle)

Transcript of Prediction of Landslide Runout - IPGPstep.ipgp.fr/images/c/c1/05_05_Runout_Analysis.pdf ·...

Page 1: Prediction of Landslide Runout - IPGPstep.ipgp.fr/images/c/c1/05_05_Runout_Analysis.pdf · Prediction of Landslide Runout Oldrich Hungr and Scott McDougall University of British Columbia

1

Prediction of Landslide Runout

Oldrich Hungr and Scott McDougallUniversity of British ColumbiaEarth and Ocean Sciences

α = fahrböschung

α’ = travel angle

Center of gravity

Theoretically, in a frictional material (dry sand, broken rock), the travel angle should equal the angle of friction, φ. The angle α equals approximately α’.If the travel angle is less than φ, pore-pressure is involved

Fahrböschung (travel angle)

Page 2: Prediction of Landslide Runout - IPGPstep.ipgp.fr/images/c/c1/05_05_Runout_Analysis.pdf · Prediction of Landslide Runout Oldrich Hungr and Scott McDougall University of British Columbia

2

1x104 1x105 1x106 1x107 1x108 1x109 1x1010 1x1011

VOLUME (m3)

0.1

1

0.2

0.3

0.40.50.60.70.80.9

TAN

a

1x105 1x106 1x107 1x108 1x109 1x1010 1x1011

VOLUME (m3)

0.1

1

0.2

0.3

0.4

0.50.60.70.80.9

TAN

a“Scheidegger plot”(1973)

Center of gravity displacement (Hungr, 1981)

Mobility increases with volume

Corominas (1996)

All landslides

Debris flows

Page 3: Prediction of Landslide Runout - IPGPstep.ipgp.fr/images/c/c1/05_05_Runout_Analysis.pdf · Prediction of Landslide Runout Oldrich Hungr and Scott McDougall University of British Columbia

3

University of British ColumbiaLog Initial Volume (m3)

Angle α(deg.)

Travel angle α

Debris flows in Hong Kong

(Wong et al., 1997)

GIS-based susceptibility analysis

Hong Kong, 2003

Delivery paths

Page 4: Prediction of Landslide Runout - IPGPstep.ipgp.fr/images/c/c1/05_05_Runout_Analysis.pdf · Prediction of Landslide Runout Oldrich Hungr and Scott McDougall University of British Columbia

4

Empirical Methods• area-volume relationships

for geometrically similar deposits:area ∝ volume(2/3)

1x105 1x106 1x107 1x108 1x109 1x1010 1x1011

VOLUME (m3)

1x104

1x105

1x106

1x107

1x108

AR

EA

(m2 )

(Li 1983; Iverson et al. 1998)

Equivalent Fluid

Dynamic modelling:concept of equivalent fluid

Prototype Model

Page 5: Prediction of Landslide Runout - IPGPstep.ipgp.fr/images/c/c1/05_05_Runout_Analysis.pdf · Prediction of Landslide Runout Oldrich Hungr and Scott McDougall University of British Columbia

5

St.Venant Equation, Lagrangian

Acceleration = Gravity – friction + pressure term (P)

MovingCoordinatesystem

dxdHgk

HTg

dtdv α

ρα cossin +−=

(Savage and Hutter, 1988)

H

x

T

P

Dynamic equilibrium of a column

T = resisting stress

Pressure term:

αγ cosHdsdHkP =

k – lateral pressure coefficient

Page 6: Prediction of Landslide Runout - IPGPstep.ipgp.fr/images/c/c1/05_05_Runout_Analysis.pdf · Prediction of Landslide Runout Oldrich Hungr and Scott McDougall University of British Columbia

6

AvalancheLake runup,Northwest Territories

600 m

0 1000 2000 3000 4000DISTANCE (m)

800

1200

1600

2000

2400

ELE

VA

TIO

N (m

)

0 1000 2000 3000 4000DISTANCE (m)

800

1200

1600

2000

2400

ELE

VA

TIO

N (m

)

“Frictional fluid”

fluid

Page 7: Prediction of Landslide Runout - IPGPstep.ipgp.fr/images/c/c1/05_05_Runout_Analysis.pdf · Prediction of Landslide Runout Oldrich Hungr and Scott McDougall University of British Columbia

7

Resisting force, TFrictional:

φσ tan)( uT −=

φφ tan)1(tan ub r−=

bT φσ tan=or:

Where Φb is the “Bulk Friction Angle (modified by pore-pressure

Resisting force, T

Plastic:

Viscous:

Bingham:

Voellmy:

τ=T

HVT µ3

=

ξγµσ

2VT +=

Yield stress + viscous effect

Page 8: Prediction of Landslide Runout - IPGPstep.ipgp.fr/images/c/c1/05_05_Runout_Analysis.pdf · Prediction of Landslide Runout Oldrich Hungr and Scott McDougall University of British Columbia

8

Pseudo-3D (Hungr, 1995)

Simulate path width

Pseudo-3D 3D(Hungr, 1995) McDougall and Hungr, 2004)

Simulate path width

Page 9: Prediction of Landslide Runout - IPGPstep.ipgp.fr/images/c/c1/05_05_Runout_Analysis.pdf · Prediction of Landslide Runout Oldrich Hungr and Scott McDougall University of British Columbia

9

• the new model ...based on “Smoothed Particle Hydrodynamics”...

DAN 3D

xx x z yx z zx x

v h h eh hg k k vt x y t

ρ ρ σ σ τ ρ ∂ ∂ ∂ ∂ = + − + − + − ∂ ∂ ∂ ∂

yy y z xy z zy y

v h h eh hg k k vt y x t

ρ ρ σ σ τ ρ∂ ∂ ∂ ∂ = + − + − + − ∂ ∂ ∂ ∂

yx vh v eht x y t

∂ ∂ ∂ ∂+ + = ∂ ∂ ∂ ∂

Acceleration =

gravity – friction – pressure - momentum correction(McDougall and Hungr, 2004)

Mass Balance

Momentum equilibrium

Governing equations

Page 10: Prediction of Landslide Runout - IPGPstep.ipgp.fr/images/c/c1/05_05_Runout_Analysis.pdf · Prediction of Landslide Runout Oldrich Hungr and Scott McDougall University of British Columbia

10

• model testing

DAN3DDAN3D

experiment #1

model

DAN3D Model Verification

Page 11: Prediction of Landslide Runout - IPGPstep.ipgp.fr/images/c/c1/05_05_Runout_Analysis.pdf · Prediction of Landslide Runout Oldrich Hungr and Scott McDougall University of British Columbia

11

Eaux Froides rock avalanche, Switzerland (courtesy J.-D. Rouiller)

EauxFroides

DAN-WDeposit

DAN-W paths

Page 12: Prediction of Landslide Runout - IPGPstep.ipgp.fr/images/c/c1/05_05_Runout_Analysis.pdf · Prediction of Landslide Runout Oldrich Hungr and Scott McDougall University of British Columbia

12

Eaux Froides: Voellmy (µ = 0.13, ξ = 450 m/s2)

Left Side Right Side

Voellmy

µ = 0.13

ξ = 450 m/s2

(DAN-W Calibrated)

Eaux

Froides

Page 13: Prediction of Landslide Runout - IPGPstep.ipgp.fr/images/c/c1/05_05_Runout_Analysis.pdf · Prediction of Landslide Runout Oldrich Hungr and Scott McDougall University of British Columbia

13

Model Calibration:1. Select cases similar to the slide in question2. Compile data on path geometry and character,

debris distribution, velocities3. Run program to obtain requisite runout4. Compare debris thickness, velocity distribution5. Select the “best fit” rheology and parameters6. Use the best fit model and parameters for prediction

e.g.(Hungr et al. 1984)

Forced Vortex Equation (superelevation)

plan x-section

RgvBH2

=∆

Estimation of velocity in the field

Page 14: Prediction of Landslide Runout - IPGPstep.ipgp.fr/images/c/c1/05_05_Runout_Analysis.pdf · Prediction of Landslide Runout Oldrich Hungr and Scott McDougall University of British Columbia

14

Example back-analysis:Mt. Cayley rock avalanche, 1983

Field observations

0 1000 2000 3000 4000 5000DISTANCE (m)

0102030405060708090

100

VE

LOC

ITY

(m/s

)

Voellmy, 0.1,500Voellmy, 0.2, 1500FrictionalBingham

Frictional: fi=30, ru=0.45Bingham: tau=18kPa, viscosity=1 kPa.s

1000 2000 3000 4000DISTANCE (m)

1000

1200

1400

1600

1800

2000

ELE

VAT

ION

(m)

1000 2000 3000 4000DISTANCE (m)

1000

1200

1400

1600

1800

2000

ELE

VAT

ION

(m)

1000 2000 3000 4000DISTANCE (m)

1000

1200

1400

1600

1800

2000

ELE

VAT

ION

(m)

Debris distribution (Frank Slide)

Frictional

Voellmy

Bingham

Magnified 5x

Page 15: Prediction of Landslide Runout - IPGPstep.ipgp.fr/images/c/c1/05_05_Runout_Analysis.pdf · Prediction of Landslide Runout Oldrich Hungr and Scott McDougall University of British Columbia

15

Frank Slide debris

Velocity comparison(23 rock avalanches Hungr and Evans, 1996)

0 20 40 60 80 100FIELD VELOCITY (m/s)

0

20

40

60

80

100

CA

LCU

LATE

D (m

/s)

Voellmy

Frictional

Bingham

“Opportunistic” field velocity estimates

Page 16: Prediction of Landslide Runout - IPGPstep.ipgp.fr/images/c/c1/05_05_Runout_Analysis.pdf · Prediction of Landslide Runout Oldrich Hungr and Scott McDougall University of British Columbia

16

0 5000 10000 15000ACTUAL RUNOUT (m)

0

5000

10000

15000C

ALC

ULA

TED

RU

NO

UT

(m)

FIDAZ

TURBID CK.

SHERMAN

ONTAKE

Voellmy model with fixed parametersfirst – order prediction for rock avalanches

µ = 0.1

ξ = 500 m2/s

Sarno, 1998 (courtesy, F.Guadagno)

Page 17: Prediction of Landslide Runout - IPGPstep.ipgp.fr/images/c/c1/05_05_Runout_Analysis.pdf · Prediction of Landslide Runout Oldrich Hungr and Scott McDougall University of British Columbia

17

Map of Sarno area

Sarno: DAN back-analyses

f=0.07

Ksi=200(Revellino et al.,2002)

Page 18: Prediction of Landslide Runout - IPGPstep.ipgp.fr/images/c/c1/05_05_Runout_Analysis.pdf · Prediction of Landslide Runout Oldrich Hungr and Scott McDougall University of British Columbia

18

Summary of Calibration results1) Small, “dry” rock avalanches - frictional, Φb=30º

(e.g. Strouth et al., 2005)

2) Campania debris avalanches - Voellmy, µ = 0.07, ξ = 200 m/sec2

(Revellino et al., 2002)

3) “Normal” waste dump flow slides - frictional, Φb=20º(Hungr et al., 2002)

4) Debris avalanches in Hong Kong - frictional, Φb=20º(Ayotte and Hungr, 2001)

5) Typical rock avalanches - Voellmy, µ = 0.1, ξ = 500 m/sec2

(Hungr and Evans, 1996)

6) Large rock avalanches involving ice - Voellmy, µ = 0.05, ξ = 1000

7) Landslides involving clay - Bingham Model (Geertsema et al., 2006)

Material entrainment (Sassa, 1985)

Page 19: Prediction of Landslide Runout - IPGPstep.ipgp.fr/images/c/c1/05_05_Runout_Analysis.pdf · Prediction of Landslide Runout Oldrich Hungr and Scott McDougall University of British Columbia

19

Nomash Slide, Vancouver Island, B.C.

(Photos D.Ayotte)

Page 20: Prediction of Landslide Runout - IPGPstep.ipgp.fr/images/c/c1/05_05_Runout_Analysis.pdf · Prediction of Landslide Runout Oldrich Hungr and Scott McDougall University of British Columbia

20

ROCK SLIDE

COARSE DEBRIS AVALANCHE

DEPOSITION

0 400 800 1200 1600 2000 2400

DISTANCE (m)

200

400

600

800

1000

ELEV

ATIO

N (

m)

0 400 800 1200 1600 2000 2400

DISTANCE (m)

-1500-1000

-5000

50010001500

YIEL

D R

ATE

(m3 /

m)

ROCKDEBRISEROSION

0 400 800 1200 1600 2000 2400

DISTANCE (m)

0100000200000300000400000500000600000700000

VOLU

ME

PAS

SIN

G (

m3 ) ROCK

DEBRISTOTAL

DEPOSITS

Nomash River

Profile

Yield rate(m3/m)

Volume balance

0 500 1000 1500 2000 2500

DISTANCE (m)

0

100

200

300

PAT

H W

IDTH

(m

)

300400500600700800900

ELEV

ATIO

N (

m)

WIDTH

EROSION

0 500 1000 1500 2000 2500

DISTANCE (m)

0

10

20

30

40

VELO

CIT

Y (m

/s)

FRONTTAIL

Model with material entrainmentNomash River slide, 1999 (Hungr and Evans, 2004)Source volume: 370 000 m3Entrained debris: 400 000 m3

Frictional Voellmy (0.05, 400)

Page 21: Prediction of Landslide Runout - IPGPstep.ipgp.fr/images/c/c1/05_05_Runout_Analysis.pdf · Prediction of Landslide Runout Oldrich Hungr and Scott McDougall University of British Columbia

21

0m 1000m

measured trimline

simulated source slide

simulated entrainment zone

Nomash River rock slide – debris avalanche

Nomash River rock slide – debris avalancheSimulation with entrainment(McDougall and Hungr, 2005)

Page 22: Prediction of Landslide Runout - IPGPstep.ipgp.fr/images/c/c1/05_05_Runout_Analysis.pdf · Prediction of Landslide Runout Oldrich Hungr and Scott McDougall University of British Columbia

22

Real case, 2D analysis:

Real case: estimate flow energy at x=390 m

Calibration

tanΦ

b

Page 23: Prediction of Landslide Runout - IPGPstep.ipgp.fr/images/c/c1/05_05_Runout_Analysis.pdf · Prediction of Landslide Runout Oldrich Hungr and Scott McDougall University of British Columbia

23

Real case, 3D:

New location

Real case, 3D:

b) with proposed berma) existing conditions

protected areaberm

1) influence of a proposed berm

• berm could potentially be effective

Page 24: Prediction of Landslide Runout - IPGPstep.ipgp.fr/images/c/c1/05_05_Runout_Analysis.pdf · Prediction of Landslide Runout Oldrich Hungr and Scott McDougall University of British Columbia

24

Another real case, Indonesia

Page 25: Prediction of Landslide Runout - IPGPstep.ipgp.fr/images/c/c1/05_05_Runout_Analysis.pdf · Prediction of Landslide Runout Oldrich Hungr and Scott McDougall University of British Columbia

25

Page 26: Prediction of Landslide Runout - IPGPstep.ipgp.fr/images/c/c1/05_05_Runout_Analysis.pdf · Prediction of Landslide Runout Oldrich Hungr and Scott McDougall University of British Columbia

26

Factory, Switzerland

Conclusions:1. Landslides are complex, but predictions are possible2. Our approach is to concentrate on the external aspects

of behaviour. We consider the micro-mechanics intractable.

3. We should be open-minded about the rheologicalcharacter of landslide motion

4. Analysis must consider the character of material forming the path

5. Material entrainment should be considered6. Model verification and calibration are essential