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Master II livello in Analisi e Mitigazione del Rischio Idrogeologico Lecture on forecasting the failure time of landslides

Ivan Cipriani 30/06/2012

1


CREEP

(Varnes 1982)

(Terzaghi 1950)


Creep secondary More than 80 sample in triaxial test

(Saito & Uzewa 1961)

Results of field measurement of collapse of a large retaining wall on the Ooigawa Railroad (Saito 1965).


Creep tertiary

(Saito 1969)

ď „1=relative displacement between two measured points l0=initial distance between two measured points


Creep tertiary Semi-empirical approaches for landslide: time of failure prediction

1/Velocity

Linear regression

FAILURE!

(Fukuzono 1985) Time


Creep tertiary

Sviluppo e implementazione di metodologie innovative di monitoraggio per la previsione di frana.


Creep tertiary first stage


Creep tertiary

Azimi et al. (1988) have proposed a new graphical method based an observational settlement prediction of one-dimensional consolidation proposed by Asaoka (1978). This method is equivalent to Saito’s and Fukuzono’s method for the tertiary creep (Eq. 5 for a=2).


Creep secondary and tertiary Integral

for α>1 e α≠2 A e α constants tf=failure time Ωf=spostamento a tf

Integral

(Voight 1988, 1989)


Metodology

(Rose and Hungr, 2007 )


Case study

A’


Landslide monitoring

15/01/10 17.00

16/01/10 9.00


Case study Landslides Dataset: 10 Period: January 2008 - September 2011

Volume: 101 - 104 m3 Thickness: 1- 3 m Type of movement: rotational/translation slide Type of material: weathered gneiss, colluvium, spritz beton

Total time span: from few hours to two weeks Total displacement : from few cms to 1 m Peak of velocity: form 8 mm/s to 66 mm/s Peak of acceleration: from 1mm/h2 to 100 mm/h2

Bozzano F, Mazzanti P, Prestininzi A (2008) A radar platform for continuous monitoring of a landslide interacting with an under-construction infrastructure. Italian Journal of Engineering Geology and Environment. 2:35-50.


Landslides dataset


Decelerazione pre-rottura!

Bozzano, F., I. Cipriani, P. Mazzanti, and A. Prestininzi (2011), Displacement patterns of a landslide affected by human activities: insights from ground-based InSAR monitoring, Natural Hazards, 59(3), 1377-1396, doi: 10.007/s11069-011-9840-6. Sviluppo e implementazione di metodologie innovative di monitoraggio per la previsione di frana.

30/06/2012


Tempo

26/1/09 0.00

25/1/09 12.00

25/1/09 0.00

-80

24/1/09 12.00

24/1/09 0.00

23/1/09 12.00

23/1/09 0.00

22/1/09 12.00

22/1/09 0.00

21/1/09 12.00

21/1/09 0.00

20/1/09 12.00

20/1/09 0.00

19/1/09 12.00

19/1/09 0.00

18/1/09 12.00

18/1/09 0.00

17/1/09 12.00

17/1/09 0.00

Spostamento (mm) 0

-40 100

-60 80

Rottura 60

-100

-120 40

-140 20

-160

-180 0

Precipitazione cumulata (mm) Precipitazione cumulata (mm)

Preliminary results 120

-20


Tempo

26/1/09 0.00

25/1/09 18.00

25/1/09 12.00

25/1/09 6.00

25/1/09 0.00

24/1/09 18.00

24/1/09 12.00

24/1/09 6.00

24/1/09 0.00

23/1/09 18.00

23/1/09 12.00

23/1/09 6.00

23/1/09 0.00

22/1/09 18.00

22/1/09 12.00

VelocitĂ  VelocitĂ  oraria (mm/ora) (mm/ora)

Preliminary results rottura

-10

-9

-8

-7

-6

-5

-4

-3

-2

-1

0


Tempo Rottura

26/1/09 0.00

25/1/09 18.00

25/1/09 12.00

25/1/09 6.00

25/1/09 0.00

0 24/1/09 18.00

24/1/09 12.00

24/1/09 6.00

24/1/09 0.00

23/1/09 18.00

23/1/09 12.00

23/1/09 6.00

23/1/09 0.00

22/1/09 18.00

22/1/09 12.00

!/velocity (mm/h) 1/velocitĂ  (mm/ora)-1

Preliminary results: Fukuzono method

2,5

2

1,5

1

0,5

2

R = 0,72


Step by step back analysis of prediction accuracy

1/Velocity

LINEAR FUKUZONO APPROACH!

FAILURE!

Time


Step by step back analysis of prediction accuracy

1/Velocity

LINEAR FUKUZONO APPROACH!

FAILURE!

Time


Step by step back analysis of prediction accuracy

1/Velocity

LINEAR FUKUZONO APPROACH!

FAILURE!

Time


Step by step back analysis of prediction accuracy

1/Velocity

LINEAR FUKUZONO APPROACH!

FAILURE!

Time


Step by step back analysis of prediction accuracy

1/Velocity

LINEAR FUKUZONO APPROACH!

FAILURE!

Time


Step by step back analysis of prediction accuracy

1/Velocity

LINEAR FUKUZONO APPROACH!

FAILURE!

Time


Step by step back analysis of prediction accuracy

1/Velocity

LINEAR FUKUZONO APPROACH!

FAILURE!

Time


Step by step back analysis of prediction accuracy

1/Velocity

LINEAR FUKUZONO APPROACH!

FAILURE!

Time


Step by step back analysis of prediction accuracy

1/Velocity

LINEAR FUKUZONO APPROACH!

FAILURE!

Time


Step by step estimation of prediction accuracy: computed error of the whole dataset


ADF (Average Data Fukuzono) method

Landslide n.2

FUKUZONO

ADF AVERAGE

ADF MOVING AVERAGE

Mazzanti P, Bozzano F, Cipriani I, Esposito F (2011) Temporal prediction of landslides failure by continuous TInSAR monitoring. 8th International Symposium on Field Measurements in GeoMechanics. 12-16 Settembre 2011 Berlino. (In press)


( 2  )        A * ( 1  ) * t   ( 1 ) 1  f   f  *   ( 2  )   A * ( 2  )     A * ( 1   ) * t ( 1   )    ( 2  )     1  ( 1 ) A * ( 1  ) * t      f 1  * ( 2  )  A* (   2 )   ( 1 ) ( 1 )  A * (  1 ) * ( t t )      f f  



e ≠


Landslide

Data

Time of failure ( tf)

Velocity

Failure displacement 

A

R2

Computed (recorded) Computed (recorded) Computed (recorded) hour

mm/hour

mm

Table parameters A and α of the entire dataset of landslides

Landslides affected by small excavation covered by spritz-beton 3

4

5

6

8

Average

9.00 (9.00)

9.82 (9.81)

19.02 (20.30)

1.0000 0.5107

0.9930

9.00 (9.00)

10.45 (9.81)

20.29 (20.30)

0.7321 0.7775

0.9876

7.88 (7.88)

37.32 (37.32)

23.31 (23.26)

1.0000 1.6004

0.9453

7.88 (7.88)

39.43 (37.32)

23.26 (23.26)

0.9204 2.1353

0.9549

20.91 (20.92)

8.08 (8.08)

18.57 (21.85)

1.3456 0.3108

0.9067

20.91 (20.92)

11.29 (8.08)

21.84 (21.85)

0.9064 0.6411

0.9521

49.75 (49.75)

10.63 (10.63)

64.03 (63.96)

1.1491 0.1363

0.9920

49.75 (49.75)

8.33 (10.63)

63.94 (63.96)

0.8184 0.1627

0.9851

12.55 (12.55)

27.21 (27.21)

96.44 (99.23)

1.0000 0.2729

0.9895

12.55 (12.55)

27.53 (27.21)

99.23 (99.23)

0.6217 0.7381

0.9937

20.02 (20.02)

19.87 (18.61)

45.74 (45.72)

0.8659 0.8857

0.9761

109

1893

503

598

151

561

Landslides affected by small excavation not-covered by spritz-beton 1

7

9

10

Average

182.35 (182.33)

17.07 (17.07)

142.38 (144.61)

142.38 0.0618

0.9960

182.35 (182.33)

10.70 (17.07)

144.59 (144.61)

144.59 0.0847

0.9546

69.01 (69.00)

29.96 (29.96)

108.37 (105.13)

108.37 0.0560

0.9507

69.01 (69.00)

8.02 (29.96)

105.12 (105.13)

105.12 0.1026

0.9195

395.04 (395.00)

44.37 (44.37)

960.42 (906.33)

960.42 0.0157

0.9918

395.04 (395.00)

23.21 (44.37)

906.24 (906.33)

906.24 0.0333

0.9773

27.59 (27.58)

64.06 (64.06)

150.92 (147.88)

150.92 0.2089

0.9928

27. 59 (27.58)

46.21 (64.06)

147.86 (147.88)

147.86 0.4609

0.9892

168.50 (168.48)

38.86 (38.87)

340.52 (325.99)

340.52 0.0856

0.9828

2189

829

4741

332

2023

Landslide not affected by excavation 2

353.08 (353.08)

11.75 (13.23)

843.25 (769.25)

1.0000 0.0138

0.9925

353.05 (353.08)

8.31 (13.23)

769.33 (769.25)

0.6449 0.0169

0.9946

4238

i)

higher R2 value;

ii)

higher similarity between the modelled and measured time series of displacement (based on the authors experience) in case of R2 difference lower than 0.020

iii) computation of a value by the Cornelius and Voight (1995) approach based on the inclination of the linear regression of data in the velocity vs. acceleration diagram


Genetic algorithms


Voight 1988

Double integral

for α>1 e α≠2 A e α constants tf=failure time Ωf=displacement a tf

Crosta e Agliardi 2003


Voight 1988

Double integral

for α>1 e α≠2 A e α constants tf=failure time Ωf=displacement a tf


Landslide of March 2007 Inclinometric monitoring

1st order of anchored bulkhead Tunnel excavation 2nd order of anchored bulkhead 3rd order of anchored bulkhead


Semi-empirical forecasting method based on the tertiary creep theory

Bozzano F, Cipriani I, Martino S, Mazzanti P, Prestininzi A (2011a). Forecasting methods for landslides interacting with infrastructures. Second World Landslide Forum. 3 - 9 September 2011 Rome. (In press)


Method to forecast the time of failure for landslides that did not reached the collapse

Fukuzono (1985)


Excavation phase

Period of excavation

Excavation  f

f

meter

mm/hour mm



A

tf

R2

Monitoring data

hour

First

17/11/2009-01/12/2009

6-12

4.13

36.90 0.81

0.13

54.63

0.9609 Topographical

Second

11/01/2010-15/01/2010

12-17

5.00

38.08 0.87

0.14

69.91

0.9524 TInSAR

Third

26/01/2010-28/01/2010

22-28

2.67

44.65 1.01

0.06

94.88

0.9864 TInSAR


A and α parameters

BOZZANO F, CIPRIANI I, MAZZANTI P, (2012) Assessing of failure prediction methods for slope affected by human activities. 11th International & 2nd North American Symposium on Landslides. Alberta, Canada 2 – 8 June 2012 (In press)


Graphs of precipitation and displacement of four landslides Normalized time max cross‐value

77.5

0.29

L. 9

L. 7

L. 1

Hours before max cross‐value

L. 2

Landslides without spritz‐beton


Cross-correlation of precipitation and displacement Hours before max cross‐value

Normalized time max cross‐value

1.3

0.09

L. 4

L. 8

L. 6

L. 3

Landslides with spritz‐beton

CIPRIANI I, MAZZANTI P, (2012) Analisi del comportamento deformativo pre-rottura di frane superficiali tramite monitoraggio con Interferometria SAR Terrestre. IV Congresso Nazionale AIGA. Perugia 6-7 February. (Extended Abstract)


Lecture Master II livello in Analisi e Mitigazione del Rischio Idrogeologico