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SECOND EUROPEAN CONFERENCE ON EARTHQUAKE ENGINEERING AND SEISMOLOGY

SECOND EUROPEAN CONFERENCE ON EARTHQUAKE ENGINEERING AND SEISMOLOGY ISTANBUL | Turkey | Aug . 25-29, 2014. Feasibility study of a nation -wide Early Warning System: the application of the EEW software PRESTo on the Italian Strong Motion Network (RAN).

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SECOND EUROPEAN CONFERENCE ON EARTHQUAKE ENGINEERING AND SEISMOLOGY

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  1. SECOND EUROPEAN CONFERENCE ON EARTHQUAKE ENGINEERING AND SEISMOLOGY ISTANBUL | Turkey| Aug. 25-29, 2014 Feasibilitystudy of a nation-wide EarlyWarning System: the application of the EEW software PRESTo on the Italian Strong Motion Network (RAN) Matteo Picozzi, Aldo Zollo, Luca Elia, Claudio Martino, Piero Brondi, Simona Colombelli, Antonio Emolo, Gaetano Festa, and Sandro Marcucci

  2. Worldwide EEWS At the nation-wide scale, the Japanesesystemuses ~1,000 seismic instruments across Japan, 200 operated by JMA and 800 by NIED, and integrates methodologies developed by JMA andNIED

  3. The Italian Strong Motion Network (RAN) • 272Free Field Stations: • Force Balance 3-C. Accelerometer • 18 bit digitizer • GSM modem • PGA via SMS • 192 Stations in Cabins • Force Balance 3-C. Accelerometer • 24 bit digitizer • GPRS router. No wait for coda to send data. • PGA via e-mail • RAN • RAN + ISNet The Communication Network Needs to be Expanded and Improved! • Seismicity • ~ 500Digital Strong Motion Stations: • Local Storage on PCMCIA disk • GSM / GPRS Modem to send waveforms cut between triggering and de-triggering Trigger at 0.1% g acceleration or on STA/LTA threshold (newer stations) • Message containing PGA within 5 min.

  4. Feasibility of EW in Italy based on RAN • Workinghypotheses: • RAN in itsactualconfigurationisupgraded to operate in real-time mode • Telemetry and data processing delays (1+1 sec) are thosemeasuredat ISNET usingPRESTo Effect of network geometry Offline analysis of recentM≥4.5 earthquakes Simulationanalyses and scenario studies CONCLUSION

  5. PLUS PRESTo ProbabilisticandevolutionaRyEarlywarningSysTem Automatic procedures for the probabilistic and evolutionary estimation of source parameters and prediction of ground motion shaking. http://www.prestoews.org/ ON-SITE • On-Site Alerts • PGx Prediction at Targets REGIONAL • RT Magnitude Estimation P • RT Earthquake Location • Automatic Picking An integrated software platform for real data processing and seismic alert notification Satriano & Elia (2010). PRESTo, the earthquake early warning system for Southern Italy: Concepts, capabilities and future perspectives. Soil Dyn Earthquake Eng

  6. Effect of network geometry Four Macro-Zones based on Mmax from PSHA : I) Seismic Zones (ZS) with Mmax ≥ 6.5 (1 st.in ~300 km2, aver. Inter-st. Dist. 17.6 km, ~ K-NET in Japan 19 km ) II) ZS with 6.5 > Mmax ≥ 6(1 st. in ~ 540 km2; ~ 23 km) III) ZS with 6 > Mmax > 5(1 st. in ~ 620 km2; ~ 25 km) IV) Outside ZS (1 st. in ~ 1100 km2; ~ 34 km) Mmax=5 PSHA (37 Seismic Zones, 16921 nodes) from INGV (http://esse1-gis.mi.ingv.it/ s1_en.php)

  7. First Alertusing 3 & 6 stations 3 stations 6 stations Time of first alertbetween 5 and 15 sec Time of first alertbetween 4 and 12 sec PSHA Each of the 16921 nodes from PSHA is considered a source

  8. Blind Zone using 3 & 6 stations To compute the BZ radius: P-arrival time, P-wave time window, averagetelemetry and computationtimesat ISNET. 3 stations 6 stations Blind Zone Radiusbetween 35 and 57 km Blind Zone radiusbetween 30 and 49 km PSHA

  9. Effectivness of EW: Potentialdamage zone vs BZ zone Example on the ‘80 Irpinia Mw 6.9 scenario BZ Municipalities EWZ (PGV+1σ) Lead-time 33.6 s EWZ (PGV aver.) Lead-time 15.9 s EWZ (PGV-1σ) Lead-time 5.8 s DM definedas the PGV+σcorresponding to the Instr.Int. VII class from Faccioli & Cauzzi (2006)

  10. Offline analysis of recentearthquakes 40 EQs, Mw≥4.5, 2002-2013 from ITACA 2.0 (http://itaca.mi.ingv.it; Luzi et al., 2008; Pacor et al., 2011) RTMAG ΔM < 0.5 Using 3 stations T 1st Alert T 1st Alert RTLOC Error on hypocenteral location

  11. Real-time location perfomance For each node, the P-wave arrival times at 3 stations, are extracted assuming a gaussian reading error of 1 second RTLOC 16921 hypotheticalseismicsources (0.05x0.05°) spacing Average Performance at National scale over 10 runs

  12. Real-Time magnitudeestimation Performance at the National scale using 3 stations • Percentage of successes(MestMtrue±0.5) at a national scale, using the first 3 stations. • At eachnode : 10 simulatedsequences in 50 years with 5<MW>Mmax

  13. Conclusions • This study does not include the EW operability, which asks for massive experimental testing and close involvement of end-users • The analysis of historicalearthquakerecordings and syntheticssuggeststhat the integration of the RAN and PRESTo in an EEWS can provide, especially for the higherseismichazardareas, reliablealertmessageswithinabout5-10 seconds • Expectederrors on location and magnitudeestimation,although large, are acceptable for peakgroundmotionpredictions. • The RAN seems to have the potential for a Nation-wide EEWS, but: • TheCommunication Network Needs to be Expanded and Improved • A Blind Zone extent of 30km is not acceptable for M 6 eqks The station density must be increased and onsite method should be used Thanks for your attention

  14. Real-Time magnitudeestimation For a given earthquake source and the closest RAN stations, the peak displacement (PD) is randomly extracted from the PD-M relationship. Example for the 50 years EQ. sequencesat the node of the 1980’ Irpinia event PD values Input vs EEW M values Success: MestMtrue±0.5 False: Mest>Mtrue+ 0.5 Missed:Mest<Mtrue- 0.5 Average RTMag success, false, and missed rate (in %) for the four MZ in case three stations are used.

  15. Outline • INTRODUCTION • EarthquakeEarlyWarning • The ItalianAccelerometric Network (RAN) Geometricalconsiderations Playbacks on historicalEQs Extensivetests on scenarios CONCLUSION

  16. Real-Time magnitudeestimation For a given earthquake source and the closest RAN stations, the peak displacement (PD) is randomly extracted from the PD-M relationship. Example for the 50 years EQ. sequencesat the node of the 80’ Irpinia event Performance at National scale (3 st.) PD values Input vs EEW M values Average RTMag success, false, and missed rate (in %) for the four MZ in case three stations are used.

  17. With 6 stations

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