Post on 21-Jul-2016
description
Valutazione della pericolosità a scala di bacino!
F.Catani, A.Ba,s.ni, D.Lagomarsino, A.Rosi, G.Rossi, S.Segoni, N.Casagli!
Sommario
• Il sistema di allerta a 2 livelli • Il livello 1 a soglie pluviometriche • Il livello 2 con modello determinis7co • Lo strumento di monitoraggio • Risulta7 su casi reali in Toscana
Soglie di pioggia Modelli matema.ci
• Computa.onal .me
• Needed field data
+ +
• High spa.al resolu.on • High .me resolu.on
+ +
-‐ -‐ • Spa.al resolu.on • Time resolu.on
• Computa.onal .me
• Needed field data
-‐ -‐
Schemi di previsione frana
Primo livello
Output : Livelli di allerta aggregati bacini idrografici
Soglie pluviometriche locali
Output : mappe di probabilità di fattore di sicurezza in tempo reale
Secondo livello: modello di stabilità distribuito
Sistema a due livelli
Da. di Pioggia
AGuale
S.me da satellite + pluviometri + LAM
A breve
RADAR meteo + pluviometri + LAM
Codici di calcolo
Primo livello Secondo livello
Soglie di pioggia mul.ple
Analisi sta.s.ca dei da. pluviometrici Massive CUMulate Brisk Analyzer
• Relazione intensità-‐durata • Analisi automa7ca • Approccio standardizzato • Definizione di soglie locali • Bilancio tra falsi allarmi e manca7 allarmi
Primo livello di allerta
First level opera.onal chain
Mul.ple-‐thresholds and News event analysis
Rainfall database
Automated analysis
Landslide database
Threshold 1
Threshold i
Threshold n
Calibra.on Thresholds
Valida.on
Error analysis
NEWS DATA MINING
A PRELIMINARY STUDY!
• Diameter à number of triggered landslides in a single rainfall event!• Color à different provinces!
I=13.97D-0.62
Single-‐threshold analysis of I-‐D
Problem: general purpose threshold for EW à lowest envelope equation à false alarms !
A PRELIMINARY STUDY!
general threshold for Tuscany (this preliminary study)
Single-‐threshols analysis of I-‐D
Problem: general purpose threshold for EW à lowest envelope equation à false alarms !
I=13.97D-0.62
A single regional threshold would be affected by a too large degree of
overestimation of hazard!
Example: rain gauge 077 Year 2008:
11 false alarms
A PRELIMINARY STUDY!
Elevation (meters a.s.l)
Single-‐threshold analysis of I-‐D
RAINFALL DATABASE!
• hourly rainfall measurements!• 332 automated rain gauges !• data from the period 2000 – 2009 !
DATA ORGANISATION!
Elevation (meters a.s.l)
Mul.ple thresholds of I-‐D
25 Alert Zones (AZ)!
LANDSLIDES DATABASE!
• 2132 landslides, grouped into 408 events!• accurate temporal and spatial location! !• calibration dataset: period 2000 – 2007!• validation dataset: period 2008 – 2013 !
DATA ORGANISATION!
Elevation (meters a.s.l)
Mul.ple thresholds of I-‐D
Parameters used:!
ANALYSIS!
• I = Critical rainfall intensity (mm/h)!• D = Duration of critical rainfall (h)!• AR = Antecedent rainfall (mm)!
Conceptual model – Intensity duration curves!
From (Aleotti 2004)
Mul.ple thresholds of I-‐D
MACUMBA CODE!
• The triggering rainfall event is characterized in terms of: !
Duration (D)!!Intensity (I)!!60 days Antecedent Rainfall (AR)!! Two main issues:!!1. Time shift within rain path!2. Which recording is best
reproducing the triggering rain?!
!
Calculation of the critical parameters!
AR
D
I
Automa.on of I-‐D analysis
Parameters used:!
ANALYSIS!Analysis of pluviometric paths!
Time (hours)
Cum
ulat
ive
rain
(m
m)
I = Critical rainfall intensity (mm/h)!D = Duration of critical rainfall (h)!AR = Antecedent rainfall (mm)!
Two main issues:!!1. Time shift within rain path!2. Which recording is best
reproducing the triggering rain?!
Mul.ple thresholds of I-‐D
Rainfall Event Splitting! Deep in-event analysis – SUB EVENT ANALYSIS!
main
1
3
2
• Calculate every sub-‐event I, D and return .me
• Compare sub-‐events and main event return .me
• Select the I -‐ D parameters associated to the highest return .me event or sub-‐event
Is it the main event actually the triggering one?!
Mul.ple thresholds of I-‐D
The highest return time !among the nearest rain gauges to each landslide!
Automatic selection of the proper rain gauges!
Landslide
MACUMBA CODE!Automa.on of I-‐D analysis
MACUMBA CODE
• I\D graph ! (logarithmic axes)!
• Different color according to different amount of Antecedent Rainfall!
Intensity – Duration graph!
Automa.on of I-‐D analysis
MACUMBA CODE
The procedure is repeated for each landslide within the same Alert Zone!
Iteration!
Each point represents a rainfall condition that has triggered at least one landslide in the past!
Automa.on of I-‐D analysis
MACUMBA CODE
• Classic statistical threshold tracing!• Statistical threshold tracing with statistical predictor!
Automatic tracer of thresholds !
Power law!!
I = α D-β!
Automa.on of I-‐D analysis
CALIBRATION!Rainfalls that did not trigger landslides!
Definition of threshold equations using data from 2000 to 2007.
Optimization of
prediction power with priority given to the reduction of missed
alarms.
Statistical threshold Statistical predictive threshold
Alert Zone A4: Low Serchio
Valley
Thresholds
VALIDATION!Validation period: Jan. 2008 – Jan. 2009!
Alert Zone A4: Low Serchio
Valley
4 events correctly predicted (14 landslides) 1 false alarm
No missed alarms
How many false alarms on an independent rainfall event sample?
Valida.on
VALIDATION!Alert Zone E3: Upper Arno Valley!
Correct predictions: threshold not exceeded, no landslides Correct predictions: threshold exceeded, occurrence of landslides
False alarms: threshold exceeded, no landslides Missed alarms: threshold not exceeded, occurrence of landslides
I = 41.64 D -0.85
JAN 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31
FEB 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29
MAR 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31
APR 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30
MAY 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31
JUN 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30
JUL 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31
AUG 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31
SEP 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30
OCT 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31
NOV 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30
DEC 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31
JAN 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31
Valida.on
I = 79D-0.997
I = 32 D-0.846
0.1
1
10
100
1 10 100
Pioggia senza frane
Frane previste
Mancati allarmi
Falsi allarmi (elevata)
Falsi allarmi (moderata)
Alert Zone A2: Versilia
Rainfall without landslides
Correctly predicted landslides
Missed alarms
False alarms (high)
False alarms (moderate)
Different alert levels for each alert zone!
Large amount of
data needed especially for
landslide activations
On the basis of the number of
triggered landslides
Setup of alert system
t_start
t_end
cumulRain
rainMax
t_rainMax
maxSovrCum
t_maxSovrCum
t_start_Mob: time when event starts in the worst case maxSovrCumMob: maximum value t h a t e x c e e d t h e d a n g e r threshold (or minimum distance from) in the worst case t_maxSovrCumMob: time of occurrence of the previous value
t_start_Mob
Worst scenario research
Rainfall – threshold comparison
Early Warning System
Web-GIS interface – Warning system
Early Warning System
Time of threshold exceedence
Web-GIS interface – Online event database and query system!
Early Warning System
Landslide Event of 24-‐25 October 2010 Nothern Tuscany and Liguria Cinque Terre
Early Warning System – Actual example
Pontremoli Rain Gauge
370 mm total, max: 66 mm/h, 200 mm in 4 h
Landslide Event of 24-‐26 October 2010 Nothern Tuscany and Liguria Cinque Terre
Early Warning System – Actual example
Primo livello
Output : Livelli di allerta aggregati bacini idrografici
Soglie pluviometriche locali
Output : mappe di probabilità di fattore di sicurezza in tempo reale
Secondo livello: modello di stabilità distribuito
Sistema a due livelli
Second Level Determinis.c Model HIgh REsolu.on Slope Stability Simulator
Soil thickness
Geomechanical params
Morfology
P(FoS)
• Physically based, high resolu.on model • Large scale opera.vity • Coded for real-‐.me applica.ons • Fast parallel computa.onal scheme
On areas with Level-‐1 Alert
Hydrology
Model Structure and Governing Equa.ons
Hydrological Model
Slope Stability Model
Pore Pressure
Rainfall Intensity
Factor of Safety
∂h∂ t
dθdh
=∂∂ x
KL h( ) ∂h∂ x
− sinα%&'
()*
+
,-
.
/0 +
∂∂ y
KL h( ) ∂h∂ y%
&'(
)*+
,-
.
/0 +
∂∂ z
KZ h( ) ∂h∂ z
− cosα%&'
()*
+
,-
.
/0
h Z( ) = Zβ 1− dZ
#$%
&'(+ Z I
KZ
R tZ 2 / 4D0 cos
2α
#
$%&
'(*
+,
-
./
h Z( ) = Zβ 1− dZ
#$%
&'(+ Z I
KZ
R tZ 2 / 4D0 cos
2α
#
$%&
'(− R t − T
Z 2 / 4D0 cos2α
#
$%&
'(*
+,
-
./
FS = tanϕtanα
+c '
γ NSzsinα+ua − uw( ) tanϕ b
γ NSzsinα
FS = tanϕtanα
+c '
γ NS z − h( ) + γ Sh( )sinα−
h z,t( )γ w tanϕγ NS z − h( ) + γ Sh( )sinα
Unsaturated conditions
Saturated conditions
During rainfall
After rainfall
Hydrological model • Parallel code solution of Richards equations • Inclusion of hydraulic diffusivity in the model • Real-time computational steps (during rainfall event)
Slope Stability Model • Infinite slope with distributed cell • Suction effects • Variable soil density with saturation • Variable depth analysis
Second Level Determinis.c Model
3100 Km2 - 10 m res = 5⋅107 pixels
Physical model
Monte Carlo simulations
(avg)
Multiple depth slope
stability calculation
24 h prediction at 1 h time step
5⋅1011 FLO
5⋅1014 FLO
3.6⋅1016 floating point operations
1.5⋅1015 FLO
Computa.onal issues Example for 1 rainfall event with dura.on 24 h, .me step 1 h
Second Level Determinis.c Model
Supercomputers (HPC)
Multi-CPU workstation Shared memory
Hybrid or distributed memory
Up to 24 CPU
Some thousands of CPUs
• Processor: IBM Power6 4.7 Ghz • 5376 CPU • 21 TB RAM • 1.2 PB hard disk space • Internal network Infiniband x4 DDR
IBM SP6/5376
HIRESSS testing hardware
Second Level Determinis.c Model
WEB Mobile devices
SERVER UNIFI
Monitoring system
min max
Level 1 – Cri.cality defini.on
Moderate High Ordinary None
Rela.ve triggering probability
Level 2
Monitoring system
Monitoring GUI
Monitoring GUI
Monitoring GUI
Monitoring GUI
Monitoring GUI
First level opera.onal chain
Mul.ple-‐thresholds and News event analysis
Rainfall database
Automated analysis
Landslide database
Threshold 1
Threshold i
Threshold n
Calibra.on Thresholds
Valida.on
Error analysis
NEWS DATA MINING
Con.nuous Valida.on and Upda.ng The News Search System
World Wide Web! Data Mining! Geocoded disaster database!Disaster News!
Presence in News Headlines Italian term for Landslide (“Frana”)
Presence in News Headlines English Term “Landslide”
Presence in News Headlines English Term “Landslide”
WEB News
Broadcasted as FEED (units of informa.on)
RSS and XML Atom derivated
collected by FEED aggregators
Continuous data mining flow
Automated News Data Mining
CONTENUTO DELLA NOTIZIA
INDIVIDUAZIONE DEI TOPONIMI
(DB GEOITALY)
RANKING OF PLACE-NAMES
- Uppercase characters; - Surrounding words; - Sentence positioning; - Articles and prepositions; - Possible generic meanings; - Person names; - Hierarchical chains; - Number of citations; - Existence of similar or identical place-names in DB;
GEOLOCATION OF MOST PROBABLE
PLACE-NAME
GOOGLE NEWS
CHECK SE GIÀ CATALOGATA
GOOGLE MAPS
GEOCODING
ANALISI DELLA NOTIZIA
Based on searching GEOLOCATION terms in the News Our case: Database GEOITALY with the following categories of toponyms: • 20 regions; • 110 provinces; • 8100 municipali.es; • 30983 loca.on names; • 461 rivers; • 206 lakes; • 1838 mountains.
Geoloca.on of News
NEWS ANALYSIS
CHECK IF ALREADY IN DB
PARSING OF NEWS CONTENT
EXTRACTION OF CANDIDATE GEOLOCATION TERMS
Each news is filtered and classified according to: • Alleged relevance of the news; • Magnitude of news (number of single FEEDS connected to the news);
• Filtering of false alarms through nega.ve ranking keywords
Classifica.on and filtering of News
News and loca.on sources in Italy
News Search GUI
Landslide events found 2014
Landslide events found
2011-‐2014