Displacement and rainfall threshold values for large landslide forecast in real time: the example of the Becca di Nona Landslide (Aosta)

Transcription

1 Projet Interreg III A ALCOTRA n 179 (ex n 46): "Risques hydrogéologiques en montagne : parades et surveillance RiskYdrogeo " Displacement and rainfall threshold values for large landslide forecast in real time: the example of the Becca di Nona Landslide (Aosta) Andrea Tamburini, CESI S.p.A. Davide Martelli, CESI S.p.A.

2 Outline Main features of the Valle D Aosta DSS (Decision Support System): System architecture Automatic data processing workflow Outputs Threshold value evaluation for the forecast of landslide behaviour: Approaches: empirical, statistical or deterministic Requirements, pros and cons Implementation of threshold values in a DSS The Becca di Nona Landslide: Main features Monitoring network Criteria for preliminary threshold value evaluation Conclusions and recommendations

3 EYDENET Valle d Aosta: monitoring network location 4 landslides (Becca di Nona, Bosmatto, Citrin, Vollein 1 data acquisition centre (Aosta)

4 EYDENET DSS main features Warning messages (h24) Data acquisition (h24) Real time data processing (h24) Server (data, system configuration) Reports System maintenance Off-line data processing

5 EYDENET DSS main features EYDENET is a proprietary real-time DSS developed by CESI for real time evaluation of data automatically collected by monitoring systems installed on landslides

6 Network status evaluation workflow Data validation Instrument status evaluation Network status evaluation Event stored in DB no data normal pre-alert alert

7 EYDENET output: general Network status evaluation window (date, hour, status) Network status synthetic panel Analogy button Displayed area Network status color legend

8 EYDENET output: single network detail Each instrument status is displayed with the same color code Area selection

9 EYDENET output: DB query DB query: instrument or network status evaluation

10 EYDENET output: DB query DB query: status evaluation statistics

11 EYDENET output: DB query DB query: status and analogies history

12 The forecast of landslide behaviour The forecast of landslide behaviour depends on the possibility to identify either evidences of activity (DISPLACEMENTS) or triggering parameters (RAINFALLS). MONITORING represents the main tool for carrying out evaluation procedures and criteria for spatial and temporal landslides forecast. Alert threshold values can be set up on: RAINFALLS, defining the critical values of precipitation that can trigger a landslide; DISPLACEMENTS, defining the critical values of velocity and/or acceleration. The APPROACH for threshold value evaluation can be empirical, statistical, deterministic, a combination of different approaches The choice of the approach depends on the DEGREE OF KNOWLEDGE of the phenomenon

13 The forecast of landslide behaviour Empirical approach: e.g. black box models based on the extrapolation of available displacement data to the collapse Statistical approach: based on analogies within phenomena comparable in terms of mechanism, climatic conditions, etc. (triggering parameters) Deterministic approach: can be applied only in case an evolutive model of the considered phenomenon is available (needs data!)

14 Threshold values on RAINFALLS Rainfall is one of the main (not only) factors triggering landslides Deterministic and empirical-deterministic models combine hydrological and hydrogeological data The most common approach is the empirical-statistical one (rainfall amount/intensity vs duration; cumulative rainfall) The deterministic approach is applied to a single phenomenon (monitoring needed); the empirical approach is applied at regional scale (catchment or higher)

15 Thresholds on RAINFALLS: deterministic and empirical-deterministic approach Casadei et al., 2003

16 Thresholds on RAINFALLS: deterministic and empirical-deterministic approach Casadei et al., 2003 Casadei et al., 2003

17 Thresholds on RAINFALLS: empirical and empirical-statistical approach Pedrozzi, 2004

18 Thresholds on RAINFALLS: empirical and empirical-statistical approach WP/WLI, 1993, 1994 Pedrozzi, 2004 WP/WLI, 1993, 1994: 1- California (Wieczorek & Sarmiento, 1988); 2- worldwide (Caine, 1980); 3- Valtellina (Cancelli & Nova, 1985); 4- Puerto Rico (Jibson, 1989); 5- worldwide (Jibson, 1989).

19 Thresholds on RAINFALLS: empirical and empirical-statistical approach Govi et al., 1985

20 Thresholds on RAINFALLS: empirical and empirical-statistical approach Crosta & Frattini, 2005 Crosta, 1998

21 Thresholds on RAINFALLS: problems, weak points Comparing different methods is difficult Uncertainties for what concerning cause and effect relationships Is the response time taken into account? Long series of data are needed (both causes and effects) Few event records are available at catchment scale Approach vs scale Geotechnical parameters, land use, morphology, are not taken into account (empirical-statistical approach) Available formulas do not account for all landslide types

22 Threshold values on DISPLACEMENTS Long term phenomena ( slope creep : Terzaghi, 1950; Haefeli, 1953) are controlled by time-dependent failure laws Observational approach ( learn-as-you-go : Terzaghi, 1945): monitoring, comparing the results to the forecast and acting according to the results (monitoring system integration, further investigations and studies, threshold value adjustment, etc.) Deterministic methods require a lot of data, which are generally unavailable when designing an Early Warning Sistem Empirical methods are more commonly applied Recently developed monitoring techniques (Satellite Borne and Ground Based InSAR, Laser Scanner, etc.) provide very detailed displacement maps, but real time warning is based on local ( punctual ) measurements Ikuta et al., 1994

23 Threshold values on DISPLACEMENTS: empirical approach Aleotti & Polloni, 2005 failure Gisotti & Benedini, 2000 displacement rate pre-failure post-failure reactivation time landslide is active displacement rate (mm/day)

24 Threshold values on DISPLACEMENTS: empirical approach Saito (1965, 1969): displacement rate vs time relationship Voight (1988, 1989): time of failure prediction by extrapolation of measured displacement values Borsetto et al., 1991 Petley & Petley (2004): v -1 vs time Crosta & Agliardi (2002): threshold values from evolution patterns

25 Thresholds on displacements: problems, weak points Deterministic approach is in most cases applicable only to back analysis Threshold values on displacements can t be easily extrapolated Non linear time dependency of displacements Seasonal effects Black box empirical models work only during the displacement rate increase stage The analysis of displacements could be not necessarily exhaustive?

26 Becca di Nona landslide controlled since 1998 reactivated during October 2000 meteorological event (max displacement rate ~ 6 mm/hr) approx. volume 2 Mm3 displacement rate: 5-7 cm/yr planimetric < 5 cm/yr vertical

27 Becca di Nona landslide monitoring system 4 wire extensometers 2 automatic GPS stations 1 meteorological station 7 GPS benchmarks (manual reading)

28 Becca di Nona landslide monitoring system data transmission: via radio acquisition rate: 1 hour (extens., meteo) 6-12 hour (automatic GPS)

29 Becca di Nona landslide monitoring system automatic GPS stations meteo and RTU station wire extensometer

30 Becca di Nona landslide: thresholds on DISPLACEMENTS Only surface displacements can be measured Surface displacements are provided by wire extensometers and automatic near-real-time GPS stations Available data are not suitable for evolution pattern definition Initial threshold values have been proposed according to the max displacement rates observed during the October 2000 reactivation (4.5 to 6 mm/h) Independent manual GPS measurements are periodically carried out

31 Becca di Nona landslide: thresholds on DISPLACEMENTS Extensometers E1, E2, E4 threshold value pre-alert alert avg 24 h displacement rate 1.2 mm/h 2.4 mm/h Only surface displacements (2 can subs. be obs.) measured Surface displacements are provided 2.4 mm/h by wire extensometers and automatic near-real-time Extensometer GPS E3 stations and Automatic GPS stations Available data are not suitable thresholdfor valueevolution pattern pre-alert definition avg 24 h displacement rate 1.5 mm/h Initial threshold values have been proposed according to avg 4 h displacement rate the max displacement rates observed during the October 2000 reactivation (4.5 to 6 mm/h) Independent manual GPS measurements are periodically carried out avg 4 h displacement rate alert 3.0 mm/h (2 subs. obs.) 3.0 mm/h

32 Becca di Nona landslide: thresholds on RAINFALLS Threshold values are only relevant to debris flow occurrence in the Comboè river catchment Only one event (October 2000) has been recorded Initial threshold values taken from literature have been proposed A conservative approach has been adopted, considering the lowest among published rainfall amount vs duration curves

33 Becca di Nona landslide: thresholds on RAINFALLS 180 Altezza di precipitazione (mm) Threshold values are only relevant to debris flow occurrence in the Comboè river catchment Only one event (October 2000) has been recorded Initial threshold values taken from literature have been proposed A conservative approach has been adopted, Durata precipitazione (hh) considering Ceriani et al. ('94) In(%)=D^-0.55*2.01 the lowest among published rainfall Ceriani et al. ('92) I=D^-0.46*16.24 Ceriani et al. ('94) I=D^-0.55*20 Cancelli - Nova ('85) Moser - Hohensinn ('83) Log(I)= *Log(D) Caine ('80) I=D^-0.39*14.82 amount Cannon ('85) D= *10^3*In+7.4*10^4*In^2 vs duration curves Wieczorek ('84) D=0.90/(I-0.17) Deganutti, Marchi, Arattano [Torrente Moscardo] ('00) I=15*D^-0.70 Ceriani et al. ('92) P.M.A.(%)=-3.65*Ln(I) per I > 2 mm/h

34 Becca di Nona landslide: thresholds on RAINFALLS 180 Altezza di precipitazione (mm) Threshold values are only relevant to debris flow occurrence in the Comboè river catchment Only one event (October 2000) has been recorded Initial threshold values taken threshold from valueliterature have Rainfall intensity 1h been proposed A conservative approach has been adopted, Durata precipitazione (hh) Rainfall intensity 6h considering Ceriani et al. ('94) In(%)=D^-0.55*2.01 the lowest among published rainfall Ceriani et al. ('92) I=D^-0.46*16.24 Ceriani et al. ('94) I=D^-0.55*20 Cancelli - Nova ('85) Moser - Hohensinn ('83) Log(I)= *Log(D) Rainfall intensity Caine 12h ('80) I=D^-0.39*14.82 amount Cannon ('85) D= *10^3*In+7.4*10^4*In^2 vs duration curves Wieczorek ('84) D=0.90/(I-0.17) Deganutti, Marchi, Arattano [Torrente Moscardo] ('00) I=15*D^-0.70 Rainfall intensity 3h Rainfall intensity 24h Becca di Nona pluviometer Ceriani et al. ('92) P.M.A.(%)=-3.65*Ln(I) per I > 2 mm/h alert 14.8 mm/h 29 mm/h 42.6 mm/h 58.3 mm/h 79.6 mm/h Rainfall intensity 36h 95.1 mm/h

35 The forecast of landslide behaviour: conclusions and recommendations The behaviour of landslides can be predicted but: landslides are different a proper observation method must be adopted Indicators of landslide activity: geomorphological evidences instrumental data The best approach: installing an Early Warning System as soon as possible in order to collect data since failure or reactivation occurs The goal is not only installing the monitoring system, but following the evolution of the monitored phenomenon through the analysis of collected data, in order to modify/integrate the monitoring system according to the results Verifying the reliability of punctual (local) data by means of independent periodical manual measurements (GPS or traditional topographic measurements, GB-SAR Interferometry, Laser Scanner, etc.) Measuring displacements during snowmelt is very important in order to identify evidences of reactivation of landslides located at high altitude The overcome of threshold values does not necessarily imply the collapse; by the way, the following statement by Erismann & Abele, 2000, relevant to landslide spread area evaluation, shouldn t never be forgotten: the expert has to bear in mind the fact that he risks nothing but his personal reputation of infallibility if he predicts an exaggerated reach, but that human lives are at stake in the opposite case.