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TNSMP – Event information (location) ISC and AFAD based information is used to compile the location of earthquakes. Preference Order Epicenter Coordinates.

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Presentation on theme: "TNSMP – Event information (location) ISC and AFAD based information is used to compile the location of earthquakes. Preference Order Epicenter Coordinates."— Presentation transcript:

1 TNSMP – Event information (location) ISC and AFAD based information is used to compile the location of earthquakes. Preference Order Epicenter Coordinates Depth 1ISC 2AFAD 3ISK 4ANSS 5USGS 6SEDHRV 7RCMTSED 8ESMDRCMT 9EMMA

2 TNSMP – Event information (magnitude and faulting mechanism) HRV, SED and RCMT are main sources to compile both Mw and fault solution information. True plane of each double- couple solutions are determined with an expert. Deleuis et al. (2002) study is used to define source parameters of Kocaeli (1999) main shock. Preference Order MwFault solution 1HRV 2SED 3ANSSRCMT 4 ESMD 5USGS 6ESMD Kiratzi and Louvari (2002) 7EMMA Özalaybey et al. (2002) 8CSEMErgin et al. (2004) 9ISK Bohnhoff et al. (2006)

3 TNSMP – Event information (style-of-faulting) The style of faulting information is determined by definitions of faulting style based on plunges of P-, T-, and B-axes by Frohlich and Apperson (1992) definitions of faulting style by Boore et al. (1997), Campbell (1997), and Sadigh et al. (1997), where λ is the rake angle (in degrees) and δ is the dip angle (in degrees).

4 TNSMP – Station information As of 2010, standard penetration tests are applied to 153 sites 241 sites have shear-wave velocity profiles that are determined via MASW method.

5 TNSMP – Finite-fault distance information Except for Kocaeli earthquake, the finite-fault distance metrics are computed from double couple solutions. True plane information is provided by an expert. The assumptions are given below: Nucleation point is assumed to be at the center of the fault. Fault dimensions are computed from equations proposed by Wells and Coppersmith (1994).

6 TNSMP – Record information The non-standard errors are cleared by visual inspection of time series (Douglas, 2003a). Band-pass filtering is applied to remove both low- and high-frequency noise in the Fourier acceleration spectrum (e.g., Boore and Akkar, 2003; Boore and Bommer, 2005; Akkar and Bommer, 2006).

7 RESORCE – Reference databases SourceTimespan Internet site for European strong-motion data (ISESD; Ambraseys et al., 2004a) 1967-2003 Italian accelerometric archive (ITACA, Luzi et al., 2008) 1976-2004 Turkish national strong-motion project (TNSMP, Akkar et al., 2010) 1976-2007 The Swiss Seismological Service (ARKLINK, www.seismo.ethz.ch) 1994-2012 Hellenic Accelerogram Database (HEAD, http://www.itsak.gr/en/db/data; Theodulidis et al., 2004) 1973-1999 French Accelerometric Data (RAP; http://www-rap.obs.ujf-grenoble.fr) 1995-2007

8 Hierarchy applied ISESD and ESMD: major sources for pre-2004 events Earthquake specific studies: used to update event information Italian data: if exists in ISESD, update all the information provided by ITACA Turkish data: For pre-2004 events, update their waveforms but keep the metadata information from ISESD. Include the post- 2004 events in RESORCE. Other data: if they exist in ISESD, keep their event information  as is  unless new studies exist. If they do not exist (post-2004), include them in RESORCE. In any case, update station and site information, if new information exists The above hierarchy is evolved during annual internal review meetings

9 Additional explanation for magnitude When reported moment magnitude (M w ) is unavailable, we searched seismological agencies (e.g. GCMT, RCMT, SED, etc.) we used local studies to obtain M w from other magnitude scales. – Turkish earthquakes: Akkar et al. (2010) conversion equations – Italian earthquakes: Castello et al. 2007) conversion equations – Greek earthquakes: Papazachos et al. (2009) conversion equations

10 Additional explanation for SoF To provide uniform information on SoF, we used the Boore and Atkinson (2007) criteria (SoF based on plunge angle). -Whenever plunge angle is not available, compute it using the strike, dip and rake angle information (Snoke’s program). -If event has no plunge angle, use the existing information provided by the reference database SoFP-axis PlungeT-axis Plunge NormalP-pl>40T-pl<40 ReverseP-pl<40T-pl>40 Strike-slipP-pl<40T-pl<40 SoF - ProvidedSoF - Used Normal Normal-Oblique Normal Reverse Reverse-Oblique Reverse Strike-slip Oblique

11 Additional explanation for site classification National databases are apriori for SM station information. This is followed by the regional (ESMD and ISESD) and global databases. Shear-wave profiles and in-situ measurement info are collected from the reference databases. Measured V S30 is apriori for site classification. References from literature are also studied for site classification of some SM stations. If shear-wave velocity profile does not reach to 30m, the last layer of the profile is extended to 30m for computing V S30.

12 o If the source of distances is ITACA and ISESD, they are taken as they are (unless recent specific studies exist) o For events with known true fault planes: When specific studies exist, use the provided information If only the true fault plane is known Nucleation point is assumed to be at the center Ruptured fault dimensions are computed from Wells and Coppersmith (1994). [Leonard (2010) also gives similar results] o For events with with known double-couple fault plane solutions but unknown true fault plane: Use the assumptions in the previous slide and take the  arithmetic average  of the distances computed from the two planes (suggested – RESORCE provides the distances from both planes as well) Distance Calculations

13 Strong-motion data processing of RESORCE is based on both pre- and post-processing schemes (Boore et al., 2012). Non-standard errors are removed by visual inspection of time series Band-pass acausal filtering is applied to remove low- and high-frequency noises Filter cut-offs are selected from a set of alternatives by inspecting the frequency and time-domain behavior of acceleration, velocity and displacement traces Data Processing

14 Read uncorrected acceleration time series Remove pre-event portion of digital records (So that tapering does not affect the data) Remove mean from the data Taper the beginning and end of data (Do not taper the beginning of S-wave triggered recordings) Apply 4-pole acausal Butterworth filter in frequency domain after identifying low- and high-cut filter frequencies from FAS of mean removed data Double integrate the filtered acceleration to obtain displacement Fit a polynomial of order 6 to the displacement trace (With the coefficients for the zeroth and first order terms constrained to be 0.0) Subtract the second derivative of polynomial from acceleration Apply some zero pads to the end of record


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