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On going development of a seismic alert management system for the Campania region (southern Italy) A.Zollo(1), G. Iannaccone(2),C.Satriano(1), E.Weber(2),

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Presentation on theme: "On going development of a seismic alert management system for the Campania region (southern Italy) A.Zollo(1), G. Iannaccone(2),C.Satriano(1), E.Weber(2),"— Presentation transcript:

1 On going development of a seismic alert management system for the Campania region (southern Italy) A.Zollo(1), G. Iannaccone(2),C.Satriano(1), E.Weber(2), M. Lancieri (1) and A. Lomax(3) (1) Research Unit RISSC, Dip. di Scienze Fisiche, Università di Napoli Federico II (2) Research Unit RISSC, Osservatorio Vesuviano, INGV, Napoli (3) Anthony Lomax Scientific Software Mouans-Sartoux, France

2 WHY an earthquake early warning system in southern Italy WHAT are the system architecture and components HOW does it work Outline

3 A pilot project to experiment a system for earthquake early warning and rapid evaluation of ground motion scenarios in the Regione Campania Objectives: Early-Warning and Rapid Ground shaking scenarios Remote control and protection of a selected target Time Schedule: end 2005  real-time seismic network completion end 2006  upgrade data transmission system Financial support: Campania Region - Department of Civil Protection AMRA Regional Center for Analysis and Monitoring of Environmental Risks SAMS: A Seismic Alert Management System for the Campania Region

4 Regional historical seismicity Tyrrenian sea Campania Region

5 Peak accelerations & velocities modified from Cabanas et al., 1998 Intensity map, modified from De Rubeis et al., 1996 Ground shaking during the 1980, Irpinia Earthquake, Ms=6.9

6 Recent earthquake activity INGV catalogue ( ), M>2.5

7 Rate of occurrence Probability map of moderate to large earthquakes (M  in Italy for the next 10 years (Cinti et al., G3, 2005) southern Apennines Instrumental data (Boschi et al,2003) M>4.01 event every 1.5 years M>5.01 event every 4 years M>6.01 event every 32 years

8 Potential targets for an EWS in Campania region city of Napoli hospitals fire stations gas/electric pipelines industries railways highways 4 small towns

9 Moderate events (M  4.5) are of interest  social impact, loss of occupancy Short hypocentral distances  narrow “early warning” windows Multiple rupture events  complexity/ reliability of location/magnitude estimations Peculiarities / criticalities

10 EEW seismic network & seismicity “Shake map” network “Early warning” network

11 Three levels of data acquisition and transmission: > Stations (data loggers) > Local Control Center (sub-nets) > Network Control Center (Naples) Network architecture Local Control Centers Sub-nets Stations

12 Data transmission system: data logger  LCC: point-to-point Wireless LAN bridge LCC  LCC : backbone (SDH) / ADSL LCC  Network center (Naples): backbone (SDH) / ADSL Communications 7-23 GHz Mbps 2.4 GHz 54 Mbps

13 Local Control Center: Fully automated. Manages and processes the sub-net data (seedlink protocol & Earthworm data management system) Data logger: on-site computational capabilities (event detection, automatic P time, peak amplitude, P-frequency,..) Fonctionality Local Control Center Seismic station

14 The seismic instruments Embedded Linux and Open Source Software 24-bit AD converter Removable mass storage (2 PCMCIA slots 5Gb) ARM720T processor, supervisory system 6 channels: 3 accelerometers + 3 seismometers (Short Period or Broad Band)

15 1.Event detection (STA1) 2.LCC1 linked to the closest station, verifies the event coincidence, collects and processes P-waveform data (time, amplitude,..) 3.LCC1 estimates the hypocenter location and magnitude with errors (X, DX, M, DM) 4.New data entries from progressively distant stations  LCC1 updates estimates of X,DX,M,DM 5.Alert notifications to end- users is sent after each up- dating step LCC1 STA1 EQK Operational mode

16 To time T_first_P T_S_target 1.5 – 3.5 sec for eqk at depths of 4-16 km 60 km80 km100 km 16 – 18 s22 – 24 s28 – 30 s Latency/computational 3-5 sec Characteristic times for EEW

17 Bagnoli (22 km) Calitri(20 km) 1980 Irpinia earthquake Ms=6.9 TPmax (4sec) M Tpmax Allen & Kanamori,2003 Source parameter estimates Moment/Magnitude:  P and early-S max amplitudes  v^2 plots  instantaneous period Location:  Trigger station order (Voronoi cells)  Equal differential time (Lomax,2004)

18 To + 3 secTo + 4 secTo + 5 secTo + 6 sec P-wave detection capability vs time At each time step, the map shows the number of stations which would record the first-P wave of an earthquake occurring at 12 km depth beneath the network

19 wavefront hypocenter stations (operational) Voronoi cell boundaries Evolutionary earthquake location 1/4

20 “conditional” EDT surface volume defined by stations without arrivals First station detects arrival – constraint is Voronoi cells A B Evolutionary earthquake location 2/4

21 “conditional” EDT surface Wavefront expands – EDT surfaces deform, constraint improves A B Evolutionary earthquake location 3/4

22 “true” EDT surface Second station detects arrival – constraint includes EDT surface A B Evolutionary earthquake location 4/4

23 Voronoi cells of Irpinia network Voronoi cells give the location of the eqk epicenter (no depth!) constrained by a single station trigger

24 Real time eqk location: Simulation The plotted quantity is proportional to the probability of earthquake location at a given point Map at 12 km depth Tnow=0.0 is the time of first-P at the closest station

25 Real time eqk location: Simulation

26 Second station detects P-arrival

27 Real time eqk location: Simulation

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35 P-wave arrives at nine stations within 2 sec from the first-P at the closest station

36 Real time eqk location: Simulation

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38 Conclusions A high-density, high dynamics (strong motion + seismometers) seismic network is under installation in Campania region for “regional” early-warning applications The main targets are strategic infrastructures located at distances such that expected S-wave lead time is around sec The network architecture is designed to have distributed levels of data storage, communication and decisions On going development of methods for earthquake location, magnitude estimation. Need to provide parameter uncertainty variation with time  engineering structural control An example: the evolutionary earthquake location approach


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