Real-Time Estimation of Earthquake Location and Magnitude for Seismic Early Warning in

Campania Region, southern Italy

A. Zollo and RISSC-Lab Research Group*with A.Lomax (A.Lomax Scientific Software)

is a joint seismological research group between University of Naples - Dept of Physics and INGV – Osservatorio Vesuviano

is a joint seismological research group between University of Naples - Dept of Physics and INGV – Osservatorio Vesuviano

*

Work Motivation

• Development and testing of a Seismic Early-Warning System for automated risk mitigation actions in Campania Region

• Need for robust and reliable real-time estimates of eqk location and magnitude to be obtained in an evolving, continually updated form.

• Need to provide with parameter uncertainty variation with time engineering structural control

1980 Irpinia earthquake, Ms=6.9

Historical Earthquakes

INGV catalogue(1981-2002)M2.5

INGV catalogue(1981-2002)M2.5

Early Warning Network29 sitesOsiris 24-bit Data Logger6 channels:

3 accelerometers3 seismometers (Short Period or Broad Band)

Real time data analysis

Early Warning Network29 sitesOsiris 24-bit Data Logger6 channels:

3 accelerometers3 seismometers (Short Period or Broad Band)

Real time data analysis

Recent Seismicity

SEW System Peculiarities

Totime

1.5 - 3.5 s

eqk at 4-16 km depth

TP first

16 - 18 s

22 - 24 s

28 - 30 s

TS target

Latency &

computation

3-5 s

High spatial density : Station spacing < 15 km

Characteristic times:

Wide-Dynamics: Unsaturated signals up to 1 g

60 km

80 km

100 km

Real-Time Earthquake Location

Basic Ideas:Constraint from “not-yet-triggered” stationsTracing and crossing Equal Differential

Time (EDT) surfacesProbabilistic estimation of eqk location vs

time (Evolutionary Approach)

Basic Ideas:Constraint from “not-yet-triggered” stationsTracing and crossing Equal Differential

Time (EDT) surfacesProbabilistic estimation of eqk location vs

time (Evolutionary Approach)

•When a first station Sn triggers at tn = tnow, we can already place limits on a pdf volume that is likely to contain the hypocenter (Voronoi cell). These limits are given by conditional EDT surfaces on which the P travel time to the first triggering station A is equal to the travel-time to each of the not-yet-triggered stations.

•As the current time tnow progresses we gain the additional information that the not-yet-triggered stations can only trigger with tl > tnow

•When the second and later stations trigger, we construct standard, true EDT surfaces between each pair of the triggered stations.These EDT surfaces are stacked with the volume defined by the not-yet-triggered stations to form the current hypocentral pdf volume.

Real-time Evolutionary Location

Earthquake location probability

Seconds from first trigger

Seconds from earthquake Origin Time

Triggered stations

Earthquake location probability

Synthetic Examples

Real-Time Magnitude Estimate

Basic Ideas• Use both early P- and S-wave information based

on the high density / wide dynamics of the network

• Correlate low-pass filtered peak amplitudes with Magnitude in increasing time windows

• Regression analysis based on the European strong motion Data-Base (ESD, Ambraseys, 2004)

Basic Ideas• Use both early P- and S-wave information based

on the high density / wide dynamics of the network

• Correlate low-pass filtered peak amplitudes with Magnitude in increasing time windows

• Regression analysis based on the European strong motion Data-Base (ESD, Ambraseys, 2004)

European Strong Motion Data Base** Ambraseys et al. (2004)* Ambraseys et al. (2004)

• 207 Events with 4≤MW≤7.4 (Kokaeli,1999)

• 376 three-component records

• Epicentral distance ≤ 50 km

• Low-pass filter: 3 Hz

• Magnitude bin: 0.3

• 207 Events with 4≤MW≤7.4 (Kokaeli,1999)

• 376 three-component records

• Epicentral distance ≤ 50 km

• Low-pass filter: 3 Hz

• Magnitude bin: 0.3

Ver

tica

l

3Hz low-pass filtered acceleration at station Bagnoli (1980, Irpinia Eqk, Ms=6.9) – Epicentral Distance: 20 Km

3Hz low-pass filtered acceleration at station Bagnoli (1980, Irpinia Eqk, Ms=6.9) – Epicentral Distance: 20 Km

Ho

rizo

nta

l

H(t)=NS2(t)+EW2(t)H(t)=NS2(t)+EW2(t)

Measurement of Peak Amplitude

1-sec

2-sec

Log(PGDt) vs Magnitude

magnitude

Log(

disp

lace

men

t) P-wave

S-wave

Single data pointSingle data point

Mean valueMean value

2-Weighted Standard Error

2-Weighted Standard Error

A possible explanationThe “far-field” approximation for displacement (f=3Hz, D> 5-6 km):

moment rate

Dynamic stress drop vs M Rise-time vs M

Rupture dynamics Rupture kinematics

The observed correlation between log(PGXt) and Magnitude would imply that

“dynamic stress release” and/or “rise-time” scale with earthquake size in the very early stage of seismic

ruptures

Slip-rate vs M Active slip area vs M

Summary A high-density, wide-dynamics seismic network is being

installed in southern Italy for “regional” early-warning applications

The system will implement a real-time eqk location method based on an evolutionary, probabilistic approach

Early P- and S- signal amplitudes (less the 2 sec from first arrival) correlate with magnitude (4≤Mw≤7.4) as from the analysis of the European Strong Motion Data Base

A combination of magnitude estimations obtained by “early P/S peak amplitudes” and “predominant periods” (Allen & Kanamori,2003) measured at different stations as a function of time may significantly improve the accuracy of the earthquake size estimation in real-time procedures.

The End

Multiple Events

Each time a new pick is available, the algorithm:

1. Temporarily associates the pick to the current event

2. Relocates the event

3. Checks the travel-time RMS for the maximum likelihood hypocenter

4. If RMS < RMSthresh the pick is definitively associated, otherwise a new event is declared

Vertical

Modulus of horizontal componen

ts

Strong Motion DataDe Natale et al., BSSA,1987

Kanamori & Rivera, BSSA, 2004

Log(PGXt) vs Magnitude

Early P-Wave Early S-Wave

accele

rati

on

velo

cit

yd

isp

lacem

en

t