30/06/2012 1
Ivan Cipriani
Master II livello in Analisi e Mitigazionedel Rischio Idrogeologico
Lecture on forecasting the failure time of landslides
CREEP
(Terzaghi 1950)
(Varnes 1982)
(Saito & Uzewa 1961)
More than 80 samplein triaxial test
Results of field measurement ofcollapse of a large retaining wall on theOoigawa Railroad (Saito 1965).
Creep secondary
(Saito 1969)
1=relative displacement between two measured pointsl0=initial distance between two measured points
Creep tertiary
Time1/
Velo
city
FAILURE!
Linear regression
(Fukuzono 1985)
Semi-empirical approaches for landslide: time of failure prediction
Creep tertiary
Sviluppo e implementazione di metodologie innovative di monitoraggio per la previsione di frana.
Creep tertiary
Creep tertiary first stage
Creep tertiary
Azimi et al. (1988) have proposed a new graphical method based an observationalsettlement prediction of one-dimensional consolidation proposed by Asaoka (1978). Thismethod is equivalent to Saito’s and Fukuzono’s method for the tertiary creep (Eq. 5 fora=2).
for α>1 e α≠2A e α constantstf=failure time Ωf=spostamento a tf
Integral
(Voight 1988, 1989)
Creep secondary and tertiary
Integral
(Rose and Hungr, 2007 )
Metodology
Case study
A’
15/01/10 17.00 16/01/10 9.00
Landslide monitoring
Bozzano F, Mazzanti P, Prestininzi A (2008) A radar platform for continuous monitoring of a landslide interactingwith an under-construction infrastructure. Italian Journal of Engineering Geology and Environment. 2:35-50.
Case study
Landslides Dataset: 10Period: January 2008 - September 2011
Volume: 101 - 104 m3
Thickness: 1- 3 mType of movement: rotational/translation slideType of material: weathered gneiss, colluvium,spritz beton
Total time span: from few hours to two weeksTotal displacement : from few cms to 1 mPeak of velocity: form 8 mm/s to 66 mm/sPeak of acceleration: from 1mm/h2 to 100 mm/h2
Landslides dataset
30/06/2012Sviluppo e implementazione di metodologie innovative di monitoraggio per la previsione di frana.
Decelerazione pre-rottura!
Bozzano, F., I. Cipriani, P. Mazzanti, and A. Prestininzi (2011), Displacement patterns of a landslide affected byhuman activities: insights from ground-based InSAR monitoring, Natural Hazards, 59(3), 1377-1396, doi:10.007/s11069-011-9840-6.
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Prec
ipita
zion
e cu
mul
ata
(mm
)
Rottura
Tempo
Spos
tam
ento
(mm
)
Prec
ipita
zion
e cu
mul
ata
(mm
)
Preliminary results
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Velo
cità
ora
ria (m
m/o
ra)
rottura
Tempo
Velo
cità
(mm
/ora
)
Preliminary results
Rottura
R2
= 0,720
0,5
1
1,5
2
2,5
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!/vel
ocity
(mm
/h)
Tempo
1/ve
loci
tà (m
m/o
ra)-
1
Preliminary results: Fukuzono method
Step by step back analysis of prediction accuracy
Time
1/Ve
loci
ty
FAILURE!
LINEAR FUKUZONO APPROACH!
Time
1/Ve
loci
ty
FAILURE!
Step by step back analysis of prediction accuracy
LINEAR FUKUZONO APPROACH!
Time
1/Ve
loci
ty
FAILURE!
Step by step back analysis of prediction accuracy
LINEAR FUKUZONO APPROACH!
Time
1/Ve
loci
ty
FAILURE!
Step by step back analysis of prediction accuracy
LINEAR FUKUZONO APPROACH!
Time
1/Ve
loci
ty
FAILURE!
Step by step back analysis of prediction accuracy
LINEAR FUKUZONO APPROACH!
Time
1/Ve
loci
ty
FAILURE!
Step by step back analysis of prediction accuracy
LINEAR FUKUZONO APPROACH!
Time
1/Ve
loci
ty
FAILURE!
Step by step back analysis of prediction accuracy
LINEAR FUKUZONO APPROACH!
Time
1/Ve
loci
ty
FAILURE!
Step by step back analysis of prediction accuracy
LINEAR FUKUZONO APPROACH!
Time
1/Ve
loci
ty
FAILURE!
Step by step back analysis of prediction accuracy
LINEAR FUKUZONO APPROACH!
Step by step estimation of prediction accuracy:computed error of the whole dataset
ADF (Average Data Fukuzono) method
Landslide n.2
ADF AVERAGE ADF MOVING AVERAGEFUKUZONO
Mazzanti P, Bozzano F, Cipriani I, Esposito F (2011) Temporal prediction of landslides failure by continuousTInSAR monitoring. 8th International Symposium on Field Measurements in GeoMechanics. 12-16 Settembre2011 Berlino. (In press)
)1()2(
)1(ff
)1()2(
1f
)tt(*)1(*A
t*)1(*A*
)2(*A1
)1()2(
)1()2(
ff
t*)1(*A
t*)1(*A*
)2(*A1
e ≠
Landslide Data Time of failure ( tf) Velocity Failure displacement A R2
Computed (recorded) Computed (recorded) Computed (recorded)
hour mm/hour mm
Landslides affected by small excavation covered by spritz-beton
3 109 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
4 1893 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
5 503 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
6 598 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
8 151 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
Average 561 20.02 (20.02) 19.87 (18.61) 45.74 (45.72) 0.8659 0.8857 0.9761
Landslides affected by small excavation not-covered by spritz-beton
1 2189 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
7 829 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
9 4741 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
10 332 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
Average 2023 168.50 (168.48) 38.86 (38.87) 340.52 (325.99) 340.52 0.0856 0.9828
Landslide not affected by excavation
2 4238 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
i) higher R2 value;
ii) higher similarity between the modelled andmeasured time series of displacement(based on the authors experience) in caseof R2 difference lower than 0.020
iii) computation of a value by the Cornelius andVoight (1995) approach based on theinclination of the linear regression of data inthe velocity vs. acceleration diagram
Table parameters A and α of the entiredataset of landslides
Genetic algorithms
for α>1 e α≠2A e α constantstf=failure time Ωf=displacement a tf
Double integralVoight 1988
Crosta e Agliardi 2003
for α>1 e α≠2A e α constantstf=failure time Ωf=displacement a tf
Double integralVoight 1988
1st order of anchored bulkhead
2nd order of anchored bulkhead
Landslide of March 2007
Inclinometric monitoring
3rd order of anchored bulkhead
Tunnel excavation
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 interactingwith infrastructures. Second World Landslide Forum. 3 - 9 September 2011 Rome. (In press)
Fukuzono (1985)
Method to forecast the timeof failure for landslides thatdid not reached thecollapse
Excavation phase
Period of excavation Excavation f f A tf R2 Monitoring data
meter mm/hour mm 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
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)
A and α parameters
L. 1
L. 7
L. 9
L. 2
Landslides without spritz‐beton77.5 0.29
Hours before max cross‐value Normalized time max cross‐value
Graphs of precipitation and displacement of four landslides
L. 3
L. 6
L. 8
L. 4
Hours before max cross‐value Normalized time max cross‐valueLandslides with spritz‐beton1.3 0.09
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)
Cross-correlation of precipitation and displacement