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AA glanceglance at the LEWIS Projectat the LEWIS ProjectA A glanceglance at the LEWIS Projectat the LEWIS Project
Giovanna Capparelli & Pasquale Versace
Presentation Outlines
LEWIS Projectj“Integrated systems for
hydrogeological risk monitoring, early warning hydrogeological risk monitoring, early warning and mitigation along the main lifelines”
Landslides triggered by rainfallM h i l M d l i h LEWI P jMathematical Models in the LEWIS Project Application to real casespp
Lewis project: General Purposes
Providing an efficient response to the problem oflandslides forecasting that may affect the roads.f g m y ff .
Allowing the enhancement of services supporting mobility.
Promoting service innovation in environmental monitoring field.
Lewis project: Components
L d hiLeadership
Actuator
COMPONENT OF THE PROJECT (1)
“Geology, geomorphology and landslide susceptibility along a highway gy, g p gy p y g g ysection in northern Calabria” F. Scarciglia
COMPONENT OF THE PROJECT (2)
DISPLACEMENT MEASUREMENTS
AREAL MONITORING SYSTEMS
L-Band radar system GB Interferometric radar
“Radar systems for landslides early warning”G. Di Massa
“Landslides Monitoring”N. Casagli
COMPONENT OF THE PROJECT (3)
DISPLACEMENT MEASUREMENTS
PUNCTUAL DISPLACEMENT SYSTEMS
The SWAN network Position and inclination syst.
“SWAN Smart Wireless Accelerometer Network for Landslide Monitoring”
“POIS: a position and inclination sensor for the monitoring of slopes and structures”f g
P. Orabonag f p
G. Artese
COMPONENT OF THE PROJECT (4)DISPLACEMENT FORECASTINGDISPLACEMENT FORECASTING
MODELS
Complete model- SUSHI
Areal model – GEOTOP
Model of mud-flowi SCIDDICA propagation SCIDDICA 1
SLOW LANDSLIDE FAST LANDSLIDE
Brazil,to(AV)
, 2011Mon
tagut
M
DISPLACEMENTDISPLACEMENTFORECASTINGMEASUREMENTS
measurement of correlated parameters
AREAL MONITORING SYSTEMSPUNCTUAL DISPLACEMENT SYSTEMS MODELS
COMPONENT OF THE PROJECT (5)
TTRANSMISSION AND DATA ACQUISITION
Data transmission network The nodes of the transmission network.
SD
Cisco 1720
BRIS/T
CONSOLE
AUXWIC 0 OK
OK
B2B1
WIC 1 OK
DSUCPU
LNK100FDX
S3
LOOP
LP
“Flexible FPGA implementation to extensive area monitoring on early warning systems”g y g yH. Havancini
COMPONENT OF THE PROJECT (6)
DATA COLLECTING AND PROCESSING CENTER(CAED)( )
COMPONENT OF THE PROJECT (7)INTERVENTION MODELINTERVENTION MODEL
“Event and risk scenarios”P. Versace
COMPONENT OF THE PROJECT (8)
C C R N (CCC)CONTROL CENTER FOR ROAD NETWORK (CCC)
“Landslide Early Warning driving Road Network Management”F. Paoletti
DECISION MAKING
Logical management process
INTERVENTION MODEL
PUNCTUALMONITORING
AREALMONITORING
DATA
Data transmission
WARNING ISSUES –WARNING LEVELS CCC
MONI ORINGDATA
network
ACTIONSMETEOROLOGICAL & HYDROLOGICAL DATA
PROBABILITYOCCURRENCEBY MODELSBY MODELS
COMPONENT OF THE PROJECT (9)
EXPERIMENTAL ACTIVITIESEXPERIMENTAL ACTIVITIES
A16 Candela LacedoniaA16 Candela - Lacedonia
A3 Cosenza AltiliaA3 Cosenza - Altilia
A18 Messina RoccalumeraA18 Messina - Roccalumera
A3 SA‐RC
MANCARELLI
Geotechnical
Meteorological
CosenzaTAS A3
HydrologicalMathematical
Altilia
FIEGO
GeotechnicalPOIS
SMAMID
GARCITO‐PIANO D’INFANTE
Hydrological
SMAMID
Mathematical
COMPONENT OF THE PROJECT (4)
DISPLACEMENT FORECASTINGMODELS
Complete model- SUSHI
Models Areal model – GEOTOP
Model of mud-flowti SCIDDICA propagation SCIDDICA 1
SUSHI MODELSaturated Unsaturated Simulation for Hillslope InstabilitySaturated Unsaturated Simulation for Hillslope Instability
MAIN FEATURES
applicability to :layered soilslayered soilsirregular shape domainvariable boundary conditions
analysis of the saturated and unsaturated flows
variable boundary conditions
analysis displacement, strain and stress under the effect of rainfall infiltration
SUSHI MODEL:GENERAL FRAMEWORK
Hydrologicalproperties
SWCC, HCF
Hydro-mechanicalproperties
SSCC
Suction StressCharacteristicCurve (SSCC)
Analysis and Forecasting GeotechnicalHydraulic Forecasting LandslidesmoduleModel
SUSHI MODEL:SOFTWARE STRUCTURE
SUSHI MODEL:SOFTWARE STRUCTURE
Pre-Processing Post- ProcessingProcessing
GEOMETRY AND STRATIGRAPHY OF ANALYZED AREA
INPUT DATA
MESH CREATION
INPUT DATA
SUSHI MODEL:SOFTWARE STRUCTURE
Pre-Processing Post- ProcessingProcessing
h-refinementsCharacterization
finite element
f
p-refinements
. tetraedro lin. . tetraedro parab.
Galerkin method (FEM)
Decoupling ofNumericall ti
Galerkin method (FEM)
Di ti i t lVariablesresolution Discretizzazione temporale
Iterative solution process
SUSHI MODEL:SOFTWARE STRUCTURE
Pre-Processing Post- ProcessingProcessing
DISPLAYING DISPLAYING RESULTS
DATA COLLECTING CENTER
SUSHI MODEL:SOFTWARE WINDOWS
Real Time
Forecasting +3 hours
SUSHI‐FEM PREVISIONE W
+6 hours nfall
ted
Rain
+12 hours
Fore
cast
F
APPLICATION TO A REAL CASE:TORRE ORSAIA LANDSLIDE
SLOPE SECTION
Altered cover layerInclinometer1 & Piezometer
yLayer_residual strength
Marly Clay
STRATO (kN/m3) c’ (kPa) ’ (°) ψ(°) E (kPa) v
Altered Cover 19 0 27 0 7000 0.3
Layer_residual strength 19 0 18 0 7000 0.3
Marly Clay 20 20 27 0 20000 0.3
Displacements measured along the vertical inclinometer
The inclinometer 1 provides the depth of the failure surface, at about 9 meters.
The instrument (placed on 23-Dec-13) showed a displacement value of 1.8 cm on 4-The instrument (placed on 23 Dec 13) showed a displacement value of 1.8 cm on 4Feb-14, and 3 cm on 20-Mar-14
Discretization adopted
Initial ConditionDec, 2014
04/02/2014Run – Simulations
06/03/2014
20/04/2014
01/05/2014
Run – Simulations
DisplacementDisplacement
Comparison between measured and simulated displacements
March
February
ailu
re
m)
February,2014
March,2014 Fa
men
tes
(mD
ispl
acem
D
Time steps
Global stability analysis
reFa
ilur
Groundwater T Initial cond. 23/12/13 4/02/14 6/03/14 20/04/14
Groundwater T. Ground surface
W.G
GEOTOP: IMPROVEMENTSRigon et al, 2006
• spatially distributed• it models:• it models:
- subsurface saturated and unsaturated flows- surface runoff
Formetta et al., IWL 2013
surface runoff- turbulent fluxes across the soil-atmosphere interface.
GEOTOP: IMPROVEMENTS (1)Rigon et al, 2006
GIS-Jgrass Integration • Computation of input
raster maps• Visualization of outputraster mapsraster maps
Formetta et al., IWL 2013
Model integration goals n.1: enjoy the GIS uDig-JGrass
Create the input maps: dem soil-type Create the input maps: dem, soil type, slope, aspect, curvatures
Visualize model results
Trento 17 June 2011G. Formetta, Trento 24 June 2011Leipzig 05 July 2012G. Formetta, Formetta G., ARS‐USDA‐Fort Collins (CO)Formetta et al., IWL 2013
GEOTOP: IMPROVEMENTS (2)
OMS Integration• Use of automatic
l b calibration algorithms such as PSO, LUCA, DREAMDREAM
GIS-Jgrass Integration • Computation of input
raster maps• Visualization of outputraster maps
Formetta et al., IWL 2013
raster maps
Model integration goals n.2: enjoy calibration algorithms
Use the OMS3 optimization algorithm f r p r m t r stim ti n:for parameter estimation:
- Multisite calibration
37Trento 17 June 2011G. Formetta, Trento 24 June 2011Leipzig 05 July 2012G. Formetta, Formetta G., ARS‐USDA‐Fort Collins (CO)
- Multidata calibration
Formetta et al., IWL 2013
GEOTOP: IMPROVEMENTS (3)
Time and space varying probabilistic infinite slope S.F.
GEOTOP: IMPROVEMENTS (4)
REAL TIME Work-flow
01/07/09 10:00 03/11/09 10:00 03/12/09 10:00
mm
] GEOtop Application: REAL TIME Work-flow
timeon
[m
50 cm
Suct
i
100 cmDep
th
150 cm
1
GEOtop Application: A3 SA-RC, Test Site – Fiego (CS)
2
Model of mud-flow propagation SCIDDICA 1
Cellular Automata model for flow‐like landslides simulation
M.V. Avolio, S. Di Gregorio, V. Lupiano, G.A. Trunfio,
• SPACE is a hexagonal tassellation CA, whosecells enclose a computing unit.
• Cell STATE is composed by sub-states :A is the cell altitude, KH is the debris kinetic headD is the depth of erodable soil coverD is the depth of erodable soil coverTH is the thickness of debris inside the cellX , Y are the co-ordinates of debris mass centreM is the momentumM is the momentumF6 the debris flows toward the six adjacent cells with own TH, KH, X, Y, M.
Model of mud-flow propagation SCIDDICA 1
improvementsI i ibl i d l i h l i d idIt is possible to introduce alterations to morphology in order to considerpossible human works (embankments, canals, wall, bridge, etc.).
Prediction of a future scenario in b f di l k
Effect of containment wall in the absence of remedial works. previous case.
SOPRA URNO DEBRIS FLOWS SIMULATION
Sopra Urno debris flow caused the largest number of casualtiesp gand damages, due to the fact that the flow crossed the village. The simulation shows a good capability of the model to
describe the debris run-out, in particular, in high zone ofslope.
In the urbanized area, differences are noted with path of thereal event, especially in lateral streets, but the result can beconsidered acceptableconsidered acceptable.
Comparison of simulated and real-event (Fig. 4) return avalue of fitness f = 0.74 (Table 2, case 2).
The maximum velocities reached by simulated flows (Fig. 5 y ( ga) are high, as expected, in the steeper areas, and decrease gradually at the outlet in downstream.
Fig. 4: comparison between Sopra Urnocreek debris flows and simulated event
T bl 2Table 2case R (m2) S (m2) f
1 11785,76 15924,21 0,732 19476,87 28066,64 0,743 14168 38 22374 40 0 773 14168,38 22374,40 0,774 9207,63 17049,25 0,705 3768,42 6936,00 0,726 8934,52 13667,88 0,78
Fig. 5: a) maximum velocities; b) maximum detrital thickness; c) eroded regolith.
GIAMPILIERI DEBRIS FLOWS SIMULATION
Comparison between real debris flows and simulated events. a) Loco creek debris flow; b) Punctual creek debris flow; c) and d)Primary school debris flows; d) east of primary school debris flow e) debris flow at East Area. (Respectively 1, 3, 4, 5, 6 in Fig. 2)
Work group – ModelsGabriella La Sala
Giuseppe Formetta
Mirko Vena
Gabriella La Sala
Antonio Donato
Maria V. Avolio
Thomas Zaffino
ConsiderationsConsiderations
The Ews is a sector in great development The Ews is a sector in great development Promoting more and more research activities and
i t ti I t di i li St diexperimentation, Interdisciplinary Studies
For analyzing of the complex phenomena need to put together :
Field analysisDisplacement MonitoringAnalytical modeling of the phenomenonAnalytical modeling of the phenomenon
It takes coordination initiatives