CANDIDATE FFS METHODS: Results of SCEC BBP Validation ... · 10/22/2013 · Key lessons learned – past validations Need more transparency... Need to validate against many events

CANDIDATE FFS METHODS: Results of SCEC BBP Validation Evaluation: Overview of the validation process – Part A and B

Validation Group: N. Abrahamson, P. Somerville, F. Silva, P. Maechling, R. Archuleta, J. Anderson, K. Assatourians, G. Atkinson, J. Bayless, J. Crempien, C. Di Alessandro, R. Graves, T. Hyun, R. Kamai, K. Olsen, W. Silva, R. Takedatsu, F. Wang, K. Wooddell,, D. Dreger, G. Beroza, S. Day, T. Jordan, P. Spudich, J. Stewart and their collaborators…

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Introduction Validation framework and schemes Methods and input Results and evaluation tools Evaluation process

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Large collaborative validation of simulations using the SCEC BroadBand Platform

Driven by need of seismic hazard projects to supplement recorded datasets South-Western U.S. utilities (SWUS) PEER NGA-East project (new CENA hazard model) PEER NGA-West projects

Southern California Earthquake Center (SCEC)

BroadBand Platform Set of computational tools for ground motion

simulations, including post-processing

Collaboration of SWUS-SCEC-PEER critical to success.

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Past validations…

Source: Graves and Pitarka (2010)

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Objectives Quantitative validation for forward

simulations in engineering problems Short term goal: supplement recorded data for

development of GMPEs and hazard analyses Long term goal: develop acceptance of

simulations for engineering design Key focus: 5% damped elastic “average”

PSA (f=0.1-100 Hz/ T=0.01-10 s)

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Key lessons learned – past validations Need more transparency... Need to validate against many events Need clear documentation of fixed and optimized

parameters from modelers for each region Need source description that is consistent

between methods Use unique crustal structure (V, Q) for all models Consider multiple source realizations Run simulations for reference site conditions –

correct data with empirical site factors Make all validation metrics computation and plots

in uniform units/format – implement post-processing pipeline on BBP

Need to tie-in to specific code/BBP version 6

Validation schemes A. Validation against recorded earthquake

ground motions

B. Validation against GMPE for generic scenarios Validation allows for development of region-specific rules (source scaling, path)

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Obs, TS, Surf. Sims, TS, Ref.

Site factors

Obs, IM, Ref.

GOF, Ref.

GMPE, IM, Ref.

Sims, IM, Ref.

IM Processors

Obs, IM, Surf.

IM Processors

Event and stations

Obs: observed/recorded Sims: simulated TS: time series IM: Intensity measures (e.g. PSA) Ref.: reference rock site Surf.: surface, soil site GOF: goodness-of-fit

This validation exercise

Part A.

Part B.

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Selection of events and stations Part A (comparison with recordings)

Large dataset (>20 EQs)

Many regions & tectonic environments

Span wide magnitude range (Mw 4.64 to 7.62)

Variety of mechanisms

Well-recorded (17 EQs with> 40 records)

Select a large subset of

stations (~40) that are consistent with mean and standard deviation PSa of the full dataset.

EQ NAME REGION

# RECORDS <200km

(*<1000km)

Mag. (Mw) Type

# SELECTED RECORDS

El Mayor Cucapah WUS 134 7.20 SS 40 Northridge WUS 124 6.72 REV 40

Hector Mine WUS 103 7.13 SS 40 Landers WUS 69 7.22 SS 40

Whittier Narrows WUS 95 5.89 REV OBL 40 Big Bear WUS 42 6.46 SS 28 Parkfield WUS 78 6.00 SS 40

Loma Prieta WUS 59 6.94 REV OBL 40 North Palm Springs WUS 32 6.21 REV OBL 32

Coalinga WUS 27 6.36 REV 27 San Simeon WUS 21 6.50 REV 21 Saguenay CENA 14* 5.90 REV OBL 14

Riviere-du-Loup CENA 98* 4.64 REV 40 Mineral, VA CENA 94* 5.70 REV 40

Tottori JAPAN 171 6.86 SS 40 Chuetsu-Oki JAPAN 286 6.80 REV 40

Niigata JAPAN 246 6.65 REV 40 Iwate JAPAN 186 6.90 REV 40

Kocaeli TURKEY 14 7.51 SS 14 Chi-Chi TAIWAN 257 7.62 REV OBL 40

L' Aquila ITALY 40 6.30 NML 40 Christchurch NEW ZEALAND 26 6.20 REV OBL 26

Darfield NEW ZEALAND 24 7.00 SS 24

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Simulation Methodologies Broadband using Green’s functions

U. Nevada Reno Composite Source Model (CSM)

U. California Santa Barbara (UCSB) Stochastic methods (e.g. Brune spectrum)

SMSIM (point source) – not formally evaluated EXSIM

Hybrid - Green’s functions LF, Stochastic HF Graves and Pitarka (G&P) – sub-fault source

spectra San Diego State University (SDSU) –

scattering functions

Methods and Input

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Input – Path (region-specific) For Green’s functions

LF: 1D velocity structures: Vs, Vp, rho, Qs, Qp

UCSB & UNR: Modified “equivalent” profile to account for Q(f)

All use a standard shallow velocity profile with Vs30 = 863 m/s

Stochastic methods Use region-specific empirical

models for Q(f), geometrical spreading and duration

Methods and Input

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Process and nomenclature For each scenario, specification of: Source: Mw, geometry, location, hypocenter Path: consistent with 1D velocity model Site (as-recorded to reference): empirical site

correction factors from Boore et al. 2013 NGA-West2

For each scenario, seismograms generated for: 50 source realizations ~ 40 stations 2 horizontal dir.

Part A (comparison with recordings)

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4,000 time series

Evaluation products Qualitative evaluation of velocity time series and

Husid plot based on Arias intensity


SIMULATED Vs30 = 863 m/s

RECORDED Vs30 = 822 m/s

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Evaluation products Part A (comparison with recordings)

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Evaluation products Goodness-of-fit

measures for PSA and PGA Average GOF with

T for all stations within an event


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measures for PSa and PGA Average GOF with


Average GOF for all realizations (all stations)


Period (s)

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measures for PSa and PGA Average GOF with



Average GOF with distance (all realizations)


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Goodness-of-fit measures for PSa and PGA Average GOF with



Average GOF with distance (all realizations)

Map of GOF (all relizations)


Evaluation products

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GOF plots also developed for NGA-West1

(2008) GMPEs SMSIM

Allows to see trends/event terms


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Evaluation products

Evaluation products Part A (comparison with recordings)

Summary table for GOF T bins R bins Events/M bins Mechanism

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Scenario selection Selected 3 scenarios for which NGA-

West1&2 GMPEs are well constrained by data: M6.2 SS, 20 and 50 km M6.6 SS, 20 and 50 km M6.6 REV, 20 and 50 km

50 realizations of the source, WITH randomized hypocenter location for each

Simulations for two velocity models: NorCal and SoCal

Part B (comparison with GMPEs)

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Evaluation criteria Part B (comparison with GMPEs)

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Summary of Simulated Events

Tottori

Niigata

Whittier

Landers

Loma Prieta

Northridge

North Palm Springs

GMPEs 3 scenarios

Summary - Parts A and B

Evaluation 1. Documentation and self-assessment from Modelers – where is the method expected to work based on technical basis behind method

Evaluation

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Evaluation 2. Evaluation committee Evaluate the method developer’s self-

assessments, request justification Evaluate the GOF for part A and B

PSA controlling factor in evaluation Various numerical criteria for bins of M, R, T:

(e.g. improvement relative to GMPEs, trends with distance)

“Verdict” for each methodology Applicable NOW for a given region, distance,

bandwidth? Limitations (close R, large M, etc.)? Method needs refinement?

Evaluation

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References Atkinson, G. M., D. M. Boore, K. Assatourians, K. Campbell and D. Motazedian (2009). A guide to differences between stochastic

point-source and stochastic finite-fault simulations, Bull. Seism. Soc. Am. 99, 3192-3201. Beresnev, I., and G. Atkinson (1998a).FINSIM: a FORTRAN program for simulating stochastic acceleration time histories from finite

faults, Seism. Res. Lett. 69, 27–32. Boore, D. M, Stewart, J. P., Seyhan, E and Atkinson, G. M. (2013) “NGA-West2 Equations for Predicting Response Spectral

Accelerations for Shallow Crustal Earthquakes,” Pacific Earthquake Engineering Research Center report 2013/05. Boore, D. M. (2009). Comparing stochastic point-source and finite-source ground-motion simulations: SMSIM and EXSIM, Bull.

Seism. Soc. Am. 99, 3202-3216. Boore, D. M. (2005). SMSIM--Fortran Programs for Simulating Ground Motions from Earthquakes: Version 2.3--A Revision of OFR

96-80-A , U.S. Geological Survey Open-File Report Brune, J. N. (1970). Tectonic stress and the spectra of seismic shear waves from earthquakes, J. Geophys. Res., 76, 5002. Graves, R. A. Pitarka (2010). Broadband ground motion simulation using hybrid approach, Bulletin of Seismological Society of

America. Bull. Seism. Soc. Am., 100, 5A, 2095-2123. Irikura, K. and H. Miyake (2010). Recipe for Predicting Strong Ground Motion from Crustal Earthquake Scenarios, Pure and Applied

Geophysics, DOI 10.1007/s00024-010-0150-9. Liu, P., R. J. Archuleta and S. H. Hartzell (2006). Prediction of broadband ground-motion time histories: Hybrid low/high-frequency

method with correlated random source parameters, Bull. Seismol. Soc. Am., 96, 2118-2130, doi: 10.1785/0120060036. Mai, P.M., Imperatori, W., Olsen, K.B. (2010), Hybrid Broadband Ground-Motion Simulations: Combining Long-Period Deterministic

Synthetics with High-Frequency Multiple S-to-S Backscattering, BSSA, 100(5A), pp. 2124-2142. Mena, B. and Mai, P. M., Olsen, K. B., Purvance, M. D. and Brune, J. N. (2010). Hybrid Broadband Ground-Motion Simulation Using

Scattering Green's Functions: Application to Large-Magnitude Events, Bull. Seism. Soc. Am. 100, 2143-2162. Motazedian, D., and G. M. Atkinson (2005). Stochastic finite-fault modeling based on a dynamic corner frequency, Bull. Seismol.

Soc. Am. 95, 995 – 1010. Dreger, D. S., Beroza, G. C., Day, S. M., Goulet, C. A., Jordan, T. H., Spudich, P. A and Stewart, J. P. (2013) Evaluation of SCEC

Broadband Platform Phase 1 Ground Motion Simulation Results. SCEC internal report, Aug. 1 2013. Schmedes, J., R. J. Archuleta, and D. Lavallée, (2012). A kinematic rupture model generator incorporating spatial interdependency

of earthquake source parameters, Geophys. J. Int., doi: 10.1093/gji/ggs021 Schmedes, J., R. J. Archuleta, and D. Lavallée (2010). Correlation of earthquake source parameters inferred from dynamic rupture

simulations, J. Geophys. Res., 115, B03304, doi:10.1029/2009JB006689. Schmedes, J., R. J. Archuleta, and D. Lavallée (2010). Dependency of supershear transition and ground motion on the

autocorrelation of initial stress, Tectonophysics, 493, 222-235, doi: 10.1016/j.tecto.2010.05.013 Somerville, P. G., Callaghan, S., Maechling, P., Graves, R. W., Collins, N., Olsen, K. B., Imperatori, W., Jones, M., Archuleta, R.,

Schmedes, J., And Jordan, T.H. (2011). The SCEC Broadband Ground Motion Simulation Platform, SRL, 82(2), p. 275, 10.1785/gssrl.82.2.273.

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Zhu, L. & Rivera, L. A. (2002) A note on the dynamic and static displacements from a point source in multilayered media, Geophysical Journal International, Volume 148, Issue 3, pp. 619-627.

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CANDIDATE FFS METHODS: Results of SCEC BBP Validation ... · 10/22/2013 · Key lessons learned – past validations Need more transparency... Need to validate against many events