Presentació per part de Vincent Jomelli (CNRS-LPG, França) en el marc de l’acte de clausura del projecte europeu CIRCLE 2 MOUNTain co-organitzat per l'Oficina Catalana del Canvi Climàtic durant els dies 26 i 27 de setembre de 2013.

1. 1
Assessment of Risks on transportation Networks resulting from
slope Instability and Climate change in the Alps

2. Main objectives
A. Document current DF/shallow landslide
activity in the Alps
B. Consequences on transportation network
C. Definition of RCM future climate scenarios
D. DF response considering future climate
conditions and lande use planning
E. Help to practical users users
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3. 3 key regions
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1- French Alps
(Haute-Durance, Savoie)
2- Eastern Italian Alps
(Tagliamento and Adige rivers)
3- Swiss Alps (Zermatt valley)
Grenoble
Briançon
Geneve
Italy
3- Swiss Alps (Zermatt valley)

4. Method: point A (Current DF/landslides activity)
 Current DF databases (historical archives –tree ring)
 Current climate conditions
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- Observed climate data
- Reanalyses climate data
- 27 RCMs downscaled scenarios
France Italy Switzerland
650 DF from 1970 50 DF from 1990s
250 DF+ from 1850

5. Methods: point A (DF/landslides activity related to
current climate conditions)
 In the 3 regions
– Probabilistic and Deterministic models of
occurrence at local scale (Shallow landslide
model) considering climatic components
– Probabilistic model of occurrence at meso scale
(logit simple or hierarchic model) considering
climatic and geomorphologic components
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6. 6
Main results: landslides local scale
Landslide suseptibily considering different precipitation scenarios
defined from meteo stations

7. Main results : Landslides local scale
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 Ubaye Valley - Southern French Alps
 7 shallow forested landslides sampled in the Riou Bourdoux catchment
 759 pine trees - 3096 cores sampled
 1298 growth disturbances dated

8. Main results: landslides local scale
 Landslide reactivation related to temperature anomalies
during spring
 Evolution suggests a shift from snowmelt-induced landslides
(controlled by winter precipitation) to reactivations controlled
by spring temperatures
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N = 61

9.  Local scale with current meteorological
conditions (I/D of precipitation analysis)
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Precipitation during each event
Main results point A: occurrence of
Debris flows-current meteo
Not a good option

10. UNIPAD Contribution 10
Main results point A: occurrence of
Debris flows-current climate
 Meso scale climate variables only
- Pseudo homogeneization of RTM data
to reduce mistakes in the database
- Analyze from 1970
No data or year without
debris flows ?

11. Main results point A: occurrence of
Debris flows-current climate
 Meso scale climate variables only
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Df occurrence
Precipitation (Number
of rainy days)
Temperature
(maximum summer
temperature)

12. UNIPAD Contribution 12
Main results point A: occurrence of
Debris flows- current climate
Debris flow probability=
1 / (1 + EXP((30,23+1*Tx+0,67*Nrd)))
Meteo factors Value Wald Chi-Square Pr > Chi² % correct 0 % correct 1 % correct
Tx 1,064 5,089 0,024
72,47% 72,31% 72%%Nrd 0,671 3,066 0,008

13. Main results point A: DF and
landslides activity
 Local scale
 DF and shallow landslides triggered by
extreme precipitations
 Meso scale
 DF and shallow landslides triggered by
Temperature + precipitation
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14. Main results point A:
Meso scale : climate + geomorphic parameters
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Regional component
(climate variables at annual scale)
Individual component
(catchments characteristics)
Binary probability
for a catchment i for a year t
Statistical modeling: bayesian hierarchical
probabilistic model based on logistic
regression
logit (pit) = a0 + αi + βt

15. Main results point A meso scale
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Individual component
• Elevation
• Area
• Slope
• Lithology
• Land cover
• Permafrost
Regional component
• Number of rainy
days
• Daily max
temperature
• P>10mm/d
• P>20mm/d
• …..

16. 16
Geomorphological
component (R² 0.78)
Climatic component
(R² 0.72)
Total explained variance: 0.84
% of total variance 0.29
1- Permafrost 80%
2- Surface area 13%
3- Forest (land cover) 7%
% of total variance 0.55
1- max T in summer 67%
2- Nb of rainy days 33%
Main results point A (meso scale):
Role of climatic and geomorphic variables
in DF triggerring

17. Point D: Consequences on
transportation network
17
A. Consequences on
transportation network
The 4th of june 2012 a DF event destroyed the road close to Lautaret pass

18. Method: point D
(Impacts of DF/landslides activity on road network)
 DF impact databases in the three regions
 A comparative analysis in normal and
disturbed situation of the network
(Accessibility : distance and time)
 Susceptibility of the network considering
future DF probabilities
 Crisis management analysis (In France only)
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19. Impacts on transportation: Swiss
Alps
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 Loss of accessibility
in Zermatt valley
125 DF events since the19th century

20. 20
(>7events/year) = 1/(1+exp (-(-
21,91+0,14*Nrd+0,9Tx)))
Impacts on transportation French
Alps
 Identification of
impacted roads

21. 21
(>7events/year) = 1/(1+exp (-(-
21,91+0,14*Nrd+0,9Tx)))
Main results point D
 Loss of accessibility with national and
international impacts
The 4th of June 2012 a DF event
destroyed the road close to Lautaret
pass

22. 22
>
35
m
m
>35 mm during 1h

23. Rainy event responsible for DF event
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35 mm <10 y return period

24. IT1 : Normal situation
IT2 : Via Gap
IT3 : Via St Jean de
Maurienne
Grenoble-Briançon options.
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Normal way
Road destroyed by the DF event
2 solutions
+ 1h30; 36€
+ 1h10; 66€

25. NCAR/ASP Thompson Lecture Series
Institutionnal vulnerability : crisis management.
Reconstitution of decision-making and organizational process :

26. 26
Impacts on transportation: Italy
 Identification of impacted
roads with local
stakeholders (Tyrol region)
 Probability of dysfonction in
the future

27. Point C: Definition of RCMs future
scenarios
 All simulations are based on the A1B
emission scenario
 24 RCMs until 2050 and 17 RCMs until
2100 from the EU-FP6 project ENSEMBLES.
 Error correction.
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28. Main results point C: error
corrections
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Raw (orange) and corrected (blue) precipitation distributions
at station St. Valent (Tirol). Left: Light and moderate
precipitation; Right: Heavy precipitation.

29. 29
after Météo-France, 2011
Near future (2020-2050)) Far future (2070-2100)
Annual precipitation sum changes
Annual maximum temperature changes
+2°C +4°C
slightly more slightly less
Main results point C
 Future climate change

30. Main results point C: Triggering
climate parameters in the future
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Climate change signal of precipitation types . The number of stations with increasing (arrow up),
decreasing (arrow down), and no change (horizontal arrow (-1 % to +1 %)) for precipitation
frequency of different thresholds is shown. Different colors represent the numbers of stations.

31. Main objectives
A. Document current DF/shallow landslide activity in the Alps
B. Consequences on transportation network
C. Definition of RCM future climate scenarios
D. DF response considering future climate
conditions and lande use planning
E. Help to practical users
31

32. Point D local scale: Results
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Current period
Future period
Model of DF triggering
based on Rcms data
24 RCMs until 2050
17 RCMs until 2100
A1B scenarioModel of DF triggering
forced by future climate
scenarios
2100
2050

33. Point D meso scale: Results
Model of DF triggering
calibrated on Safran data
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Current period
Future period
Interchanging Safran with
RCMs downscaled data
Model of DF triggering
based on Rcms data
24 RCMs until 2050
17 RCMs until 2100
A1B scenario
Model of DF triggering
forced by future climate
scenarios
Step 1
Step 2
Step 3

34. Point E: Help to practical users
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1. Volume and run out estimates from MassMov2D
(physical model) for case studies
2. Crisis amanagment analysis
3. Fonctional disturbance analysis regional and
international scale
 In France
 In Italy
 In Switzerland
1. Volume and run out estimates from MassMov2D (physical
model) for case studies
2. Probability of future dysfonction based on climate scenarios
for cases studies
1. Fonctional disturbance analysis regional and international scale
2. Technical investigations

35. From a case study example: The rif Blanc df
event on 4th of June 2012
Volume and run out estimates from a deterministic model
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36. 36
Volume estimated from peak flow calculation :
(from the video of the 2nd DF at 10am)
1. Number of pictures per second on
the video (30p/sec).
2. Section of the flow
(L x h x WP).
3. Choose a representative block
(B). transported distance/ time
between :
Position 1 at the time T
Position 2 at the time T+1
4. Qp = WS (m²) x velocity (m/s)
5. Rickenmann volume estimation :
Qp = 0.1V0.83
V = 10 760
Debris flow volume (2nd)
= 11 000m3

37. Help to local stakeholders
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Sensitivity tests of local protections to DF on the
Highway France-Italy
<15 year return period <30 year return period

38.  Sensitivity to climate change of the debris flows
which are able to reach the road system along the
considered road
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Help to local stakeholders in italy
Summer
Fall

39. Conclusions
 Current relationships between
DF/landslides and climate depends on the
considered region
 Slope processes strongly impact
transportation network
 Perception of DF Risk depends on the
region
 Mitigation is not perfect ! (No by pass,
underestimation of protected
constructions)
 Good relationhsip with public stakeholders
more difficult with private component
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