Seismic Hazard of American Samoa and Neighboring 

South Pacific Islands—Data, Methods, Parameters, and 

Results

By Mark D. Petersen, Stephen C. Harmsen, Kenneth S. Rukstales, Charles S. Mueller, Daniel E. McNamara, 

Nicolas Luco, and Melanie Walling 

Open-File Report 2012–1087

U.S. Department of the Interior

U.S. Geological Survey
U.S. Department of the Interior

KEN SALAZAR, Secretary

U.S. Geological Survey

Marcia K. McNutt, Director

U.S. Geological Survey, Reston, Virginia: 2012

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Suggested citation:

Petersen, M.D., Harmsen, S.C., Rukstales, K.S., Mueller, C.S., McNamara, D.E., Luco, Nicolas, and Walling,

Melanie, 2012, Seismic hazard of American Samoa and neighboring South Pacific Islands—Methods,

data, parameters, and results: U.S. Geological Survey Open-File Report 2012–1087, 98 p.

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Although this report is in the public domain, permission must be secured from the individual 

copyright owners to reproduce any copyrighted material contained within this report.
iii

Contents

Abstract ...................................................................................................................................................................... 1

Introduction................................................................................................................................................................. 1

Methodology ............................................................................................................................................................... 3

Seismic Sources......................................................................................................................................................... 4

Earthquake Catalog ................................................................................................................................................ 4

Gridded-Seismicity Background Models ................................................................................................................. 5

Subduction Zone Earthquake Source Models......................................................................................................... 5

Source Geometry.................................................................................................................................................... 6

Ground Motion Model ................................................................................................................................................. 7

Summary of Current Ground Motion Prediction Equations ..................................................................................... 7

Strong-Motion Data................................................................................................................................................. 9

Analysis of Ground Motion Prediction Equations .................................................................................................. 11

Logic Tree for Seismic Hazard.................................................................................................................................. 14

Results...................................................................................................................................................................... 15

Conclusion................................................................................................................................................................ 17

References Cited...................................................................................................................................................... 17

Acknowledgments..................................................................................................................................................... 20

Appendix 1. Lessons of the M8.3 Tokachi-Oki and the M9 Tohoku Earthquakes..................................................... 85

Tokachi-Oki Earthquake of September 26, 2003 .................................................................................................. 86

Tohoku Earthquake of March 11, 2011................................................................................................................. 90

Conclusion ............................................................................................................................................................ 94

References Cited .................................................................................................................................................. 95

Appendix 2. Analysis of Ground Motion Prediction Equations .................................................................................. 95

Approach............................................................................................................................................................... 95

Figures 

1. Map showing faults and large earthquakes M ≥ 7 since 1900, depth contours of subducing slab and 

plate tectonic features and slip rates .......................................................................................................... 21

2. Map showing M ≥ 5 earthquakes since 1964, color-coded by depth and cross sections across the 

Tonga and New Hebrides (Vanuatu) subducting slabs............................................................................... 22

3. Focal mechanisms from Global Centroid-Moment Tensor Project Bathymetry from GMT............................. 23

4. Magnitude-frequency plot showing annual rates of earthquakes in the catalog 1900–2010 and 

1964–2010 (not declustered) and the declustered catalog ......................................................................... 24

5. Magnitude-frequency plot showing cumulative number of earthquakes exceeding each magnitude for 

different depth levels................................................................................................................................... 25

6. Magnitude-frequency distribution for the primary shallow-source models (0–50 km depth) showing the 

cumulative number of earthquakes exceeding each magnitude ................................................................. 26

7. Magnitude-frequency plot for New Hebrides region showing fits to the observed data for M ≥ 

7 events since 1900.................................................................................................................................... 27

8. Magnitude-frequency plot showing the fit to the observed Tonga earthquake data M > 7 since 1900 ........... 28

9. Map showing location of sources used in constructing the seismic hazard maps.......................................... 29
iv

10. Plot showing four 1-Hertz Spectral acceleration ground motion prediction equations for M 6.5 and M 7.5 

earthquakes on the A interface and the B intraplate sources...................................................................... 30

11. Plot showing four 5 Hz Spectral acceleration ground motion prediction equations for M 6.5 and M 7.5 

earthquakes on the A interface and the B intraplate sources...................................................................... 31

12. Comparison of the Atkinson and Boore (2003) global, Youngs and others (1997), and Zhao and others 

(2006) intraplate 5-Hertz (Hz) (lower plot) and interface 1-Hz (upper plot) spectral accelerations.............. 32

13. Plot showing three Spectral acceleration ground motion prediction equations (A. 1 Hertz (Hz), B. 5 Hz) 

for an M 7.5 intraplate earthquake as a function of depth........................................................................... 33

14. Ground motion prediction equations showing spectral acceleration at 1 second (sec) (1 Hertz (Hz)) and 

0.2 s (5 Hz) spectral acceleration for distances up to 200 km for the Zhao crustal equations, Zhao 

intraplate, and NGA- Boore and Atkinson (2008) crustal models................................................................ 34

15. Ground motion prediction equations showing spectral acceleration at 1 second (sec) (1 Hertz (Hz)) and 

0.2 s (5 Hz) spectral acceleration for distances up to 200 km for the Zhao crustal equations, Zhao 

intraplate, and NGA- Boore and Atkinson (2008) crustal models................................................................ 35

16. Map showing earthquakes M > 6 and recording stations used in determining weights applied for the 

ground motion prediction equations............................................................................................................ 36

17. Graph showing the Zhao and others 2006 intraslab ground motion model with Pacific strong motion data 

for A, 1 Hz Spectral acceleration and B, Peak horizontal ground acceleration ........................................... 37

18. Magnitude distribution versus A distance and B depth. Red circles represent interface events and blue 

squares represent intraslab events............................................................................................................. 38

19. PGA residuals at each station in natural log units. Station Numbers: 1 is ADK, 2 is AFI, 3 is DAV, 4 is 

GUMO, 5 is HNR, 6 is PET, 7 is RAO, and 8 is TATO ............................................................................... 39

20. Five Hertz residuals at each strong motion station based on natural log units. Station numbers are as 

follows: 1 is ADK, 2 is AFI, 3 is DAV, 4 is GUMO, 5 is HNR, 6 is PET, 7 is RAO, and 8 is TATO .............. 40

21. One Hertz residuals at each station based on natural log units. Station numbers are as follows: 1 is ADK, 

2 is AFI, 3 is DAV, 4 is GUMO, 5 is HNR, 6 is PET, 7 is RAO, and 8 is TATO........................................... 41

22. A, correlated residual PGA versus moment magnitude; B, uncorrelated or single station residual PGA 

versus moment magnitude; C, uncorrelated or single station residual 5 Hertz (Hz) versus moment 

magnitude; D, uncorrelated or single station residual 1Hz versus moment magnitude............................... 42

23. Average single station residuals versus moment magnitude for A, PGA; B, 5Hz; and C, 1 Hz...................... 43

24. Single station residuals as a function of distance for A, PGA and average single station residuals versus 

distance for B, PGA; C, 5 Hz; and D, 1 Hz ................................................................................................. 44

25. Logic tree for subduction-fault sources. Parameters in this table include some aleatory variability as well 

as depicted epistemic uncertainty............................................................................................................... 45

26. Seismic hazard contributed by the Tonga and New Hebrides subduction zones 1 Hertz spectral 

acceleration for 2 percent probability of exceedance in 50 years on a uniform firm rock site condition. 

Focal mechanisms derived for M≥7............................................................................................................ 46

27. Background hazard maps for 5 Hertz Spectral Acceleration 2 percent probability of exceedance in 

50 years on firm rock site condition for earthquake sources with depths A, 0–50 kilometers (km); 

B, 50–100 km; C, 100–200 km; D, 200–750 km......................................................................................... 47

28. Background hazard maps for 1 Hertz Spectral Acceleration 2 percent probability of exceedance in 

50 years on firm rock site condition for earthquake sources with depths A, 0–50 kilometers (km); 

B, 50–100 km; C, 100–200 km; and D, 200–750 km.................................................................................. 48

29. Hazard map with all sources for 1-second Spectral Acceleration 10 percent probability of exceedance 

in 50 years on firm rock site condition......................................................................................................... 49

30. Hazard map with all sources for 1-Hertz Spectral Acceleration 2-percent probability of exceedance 

in 50 years on firm rock site condition......................................................................................................... 50
v

31. Hazard map with all sources for 5-Hertz Spectral Acceleration 10 percent probability of exceedance 

in 50 years on firm rock site condition......................................................................................................... 51

32. Hazard map with all sources for 5-Hertz Spectral Acceleration 2 percent probability of exceedance 

in 50 years on firm rock site condition......................................................................................................... 52

33. Hazard map with all sources for Peak Horizontal Ground Acceleration with a 10 percent probability of 

exceedance in 50 years on firm rock site condition .................................................................................... 53

34. Hazard map with all sources for Peak Horizontal Ground Acceleration with a 2 percent probability of 

exceedance in 50 years on firm rock site condition .................................................................................... 54

35. Deaggregation plots of a site at Pago Pago, American Samoa for 1 second (sec) (1 Hertz (Hz)) and 

0.2 s (5 Hz) spectral accelerations.............................................................................................................. 57

36. Deaggregation plots of a site at Nuku`alofa, Tonga for 1 second (sec) (1 Hertz (Hz)) and 0.2 s (5 Hz) 

spectral accelerations................................................................................................................................. 60

37. Deaggregation plots of a site at Suva, Fiji for 1 second (sec) (1 Hertz (Hz)) and 0.2 s (5 Hz) 

spectral accelerations................................................................................................................................. 63

38. Deaggregation plots of a site at Port Vila, Vanuatu for 1 second (sec) (1 Hertz (Hz)) and 0.2 s (5 Hz) 

spectral accelerations................................................................................................................................. 66

Tables

1. b-values, maximum magnitudes, and rates of earthquakes applied in the hazard model .............................. 67

2. Earthquake and station information ............................................................................................................... 67

3. 1-second spectral acceleration ...................................................................................................................... 72

4. 5 Hz Spectral Acceleration............................................................................................................................. 76

5. Peak Horizontal Ground acceleration ............................................................................................................ 80

6. Systematic Offset of the Zhao and others (2006) equation for Pacific region data ........................................ 84

7. Single Station Sigma, distance ≤ 300 km, M ≥ 6.0 ........................................................................................ 84

8. Station Sigma, distance ≤ 300 km, M ≥ 6.0 ................................................................................................... 84

9. Total Sigma, distance ≤ 300 km, M ≥ 6.0 ...................................................................................................... 84

 
Seismic Ground Shaking Hazard for American Samoa and 

Neighboring South Pacific Islands—Data, Methods, 

Parameters, and Results

By Mark D. Petersen, Stephen C. Harmsen, Kenneth S. Rukstales, Charles S. Mueller, Daniel E. McNamara, 

Nicolas Luco, and Melanie Walling

Abstract

American Samoa and the neighboring islands of the South Pacific lie near active tectonic-plate 

boundaries that host many large earthquakes which can result in strong earthquake shaking and 

tsunamis. To mitigate earthquake risks from future ground shaking, the Federal Emergency 

Management Agency requested that the U.S. Geological Survey prepare seismic hazard maps that can

be applied in building-design criteria. This Open-File Report describes the data, methods, and 

parameters used to calculate the seismic shaking hazard as well as the output hazard maps, curves, and 

deaggregation (disaggregation) information needed for building design. Spectral acceleration hazard for 

1 Hertz having a 2-percent probability of exceedance on a firm rock site condition (Vs30=760 meters 

per second) is 0.12 acceleration of gravity (1 second, 1 Hertz) and 0.32 acceleration of gravity 

(0.2 seconds, 5 Hertz) on American Samoa, 0.72 acceleration of gravity (1 Hertz) and 2.54 acceleration 

of gravity (5 Hertz) on Tonga, 0.15 acceleration of gravity (1 Hertz) and 0.55 acceleration of gravity 

(5 Hertz) on Fiji, and 0.89 acceleration of gravity (1 Hertz) and 2.77 acceleration of gravity (5 Hertz) 

on the Vanuatu Islands.

Introduction

American Samoa and the adjacent South Pacific islands are located in a region where complex 

tectonic interactions produce frequent earthquakes on subduction interfaces; within subducting slabs; 

along the outer rise region of subducting slabs; as well as on numerous fractures, spreading centers, and 

shear zones distributed across the region. Many of the islands along the Samoa archipelago were formed 

between 28 and less than 2 million years ago as the Pacific plate moved westward across a stationary 

hotspot, creating a 485-kilometer (km) long chain of shield volcano islands, seamounts, and atolls 

(Thornberry-Ehrlich, 2008). High seismicity and geodetic strain-rate observations manifest the current 

rapid deformation rates across the region (fig. 1; Pelletier and others, 1998; Bird, 2003). These high 

strains result in frequent large earthquakes; since 1900, 242 M greater than or equal to 7 earthquakes 

have been recorded, or an average rate of more than two large earthquakes per year. 

While most of the historical damage has been caused by earthquake-induced tsunamis, ground 

motions occasionally reach a level that results in building, contents, or infrastructure damage (for 

example, 2010 M 7.5 Vanuatu earthquake). This report focuses on shaking hazard, but the source 

models developed here can also be applied to developing future tsunami, liquefaction, and landslidehazard assessments. For more information on the September 29, 2009 tsunami, we refer the reader to a 

USGS report by Jaffe and others (2010) on the tsunami inundation limits and a report by the UK 
2

Earthquake Engineering Field Investigation Team (2010) on resulting damage and loss. Understanding 

the potential ground-shaking hazard can be useful in mitigating the effects through thoughtful public 

land-use policy; effective disaster mitigation and response plans; and efficient engineering design 

standards for buildings, bridges, highways, utilities, etc. These analyses can be used to develop resilient 

buildings and infrastructure in a cost-effective manner that can save lives and financial resources. 

Earthquake shaking models are developed by using historic seismicity data to model earthquake 

sources as well as by using ground-motion prediction equations (GMPEs, also known as attenuation 

relations) that describe ground shaking from earthquakes with different magnitudes, styles of faulting, 

and distances from the earthquake. In this report, we describe the development of seismic source models 

that are based on historical seismicity rates (obtained from an earthquake catalog) and fault maps. Large 

subduction interface earthquakes contribute most to the seismic hazard at nearby sites and are welldefined by the seismicity patterns and size distribution of historic earthquakes. However, other 

earthquake sources can contribute significantly to the seismic hazard, especially at sites located well

away from the subduction zones. Most of these other sources are not well known, so we construct

“background source models” to account for earthquakes that occur randomly on unmodeled faults (for 

example, deep earthquakes, spreading centers, and outer-rise earthquakes where the slab cracks due to 

bending stresses). 

To calculate hazard from each of the seismic sources, we consider published GMPEs that relate

ground-shaking levels from different sizes and styles of earthquakes (Youngs and others, 1997; 

Atkinson and Boore, 2003; Zhao and others, 2006; Boore and Atkinson, 2008; Campbell and 

Bozorgnia, 2008; Chiou and Youngs, 2008). Ground-motion models estimate shaking from earthquakes 

on the subduction interfaces (interface equations), from deep earthquakes that are thought to be caused 

by bending stresses as the slab bends downward to descend beneath the adjacent tectonic plate (intraslab

or in-slab equations), and shallow crustal earthquakes. We weight the subduction-related models based 

on how well they fit regional strong-shaking data we collected from seismic stations located across the 

Pacific Ocean region. This step ensures that the shaking models we apply are appropriate for this region 

of the South Pacific. We assume that the future shallow crustal earthquakes in this region will have 

similar ground motions compared to those described in shallow crustal ground motion equations 

developed for Japan and global earthquakes. 

In this report, we describe the development of hazard and design maps that will be provided to 

building-code committees for their analysis of American Samoa design procedures. The USGS has 

developed hazard maps over the past 35 years (yr) (for example, Frankel and others, 2002; and Petersen 

and others, 2008) that are applied in seismic provisions of building codes (for example, Building 

Seismic Safety Council, 2009). These methodologies are mostly applied in developing this hazard 

analysis; however, some modifications have been made to account for regional South Pacific tectonics 

and oceanic terrain. For example, we consider a different weighting of GMPEs and include a shallow 

crustal model that was not included in the USGS hazard maps. In addition, we incorporate magnitudefrequency distributions based entirely on historic seismicity data since this region is so rich in 

earthquakes. The study region was expanded beyond American Samoa to include other South Pacific 

islands because in the past years only a few small-scale seismic hazard maps have been pieced together

to make regional maps of this region (for example, the Global Seismic Hazard Assessment Program, 

GSHAP; Giardini and others, 1999) and because our results show that earthquakes across this area have 

similar source and ground-shaking characteristics. In this report, we compare our results to the global 

GSHAP model and a recently developed probabilistic seismic hazard model for Vanuatu (Suckale and 

Grünthal, 2009). 
3

Methodology

For this hazard analysis, we apply the methodology that was used in developing the National 

Seismic Hazard Maps for the Conterminous United States (Frankel and others, 2002; Petersen and 

others, 2008). Probabilistic hazard is calculated using three models: (1) random seismic background 

source models (gridded), (2) subduction zone fault source models, and (3) earthquake ground-shaking 

models. An earthquake catalog is used to define the random seismic sources and to estimate the rate of 

large earthquakes on the subduction-zone sources. The resulting random seismic background model 

accounts for the observation that larger earthquakes occur at or near clusters of previous smaller 

earthquakes (Frankel, 1995), while the subduction model is based on historic seismicity rates and a 

geophysically derived 3D geometry of the fault. 

The earthquake catalog is constructed by merging regional catalogs developed by different 

institutions. Duplicate events and manmade events are deleted because seismic hazard models require a 

declustered earthquake catalog of independent events (foreshocks and aftershocks removed) for 

calculation of Poissonian (time-independent) earthquake rates. The earthquake rates are sensitive to 

completeness levels for the catalog; we do not want the results to be biased by network inadequacies. 

Once we have complete catalog representations, we can calculate regional a- and b-values (defining the 

activity rate and slope of the magnitude frequency distribution, from Gutenberg and Richter, 1944) by

using a maximum likelihood method (Weichert, 1980). 

The earthquake catalog is then used to develop random seismic source models that characterize 

the hazard from earthquakes between about M5.0 and some maximum magnitude determined from 

paleoseismic information, historical seismicity, or global analogs. Random seismicity-derived 

background sources account for two types of earthquakes: those that occur off known faults, and 

moderate-size earthquakes that are not modeled explicitly on faults. Regional zones allow for local 

variability in seismicity characteristics or plate tectonics and are used to incorporate alternative models 

of the b-value or maximum magnitude (Mmax). The seismicity from the earthquake catalog M greater 

than or equal to 4 is smoothed and gridded using a two-dimensional Gaussian smoothing operator 

(Frankel, 1995) from which earthquake rates (10a

 values from the Gutenberg and Richter relationship) 

are calculated. Next, we calculate the hazard from these gridded-seismicity background sources by 

applying a truncated-exponential, Gutenberg-Richter magnitude-frequency distribution (Gutenberg and 

Richter, 1944) using the b-values calculated for each of the zones. Earthquakes smaller than M 6.0 are 

characterized as point sources at the center of each cell, whereas larger earthquakes are assumed to 

occur on hypothetical finite vertical or dipping faults centered on the source grid cell. To calculate 

lengths from a particular magnitude, we precalculate average distances from virtual faults with strike 

directions uniformly distributed from 0 to 180° (appendixes B and C in Petersen and others, 2008). The 

average-distance calculation ensures that no receiver is assigned a biased distance based on an arbitrary

draw from a random-number generator. The virtual fault length is based on a subduction-zone 

earthquake rupture length versus magnitude regression performed by Geomatrix Consultants (1995). 

The formula is: rupture length = 10(M-4.94)/1.39. 

The subduction zone source model is built assuming that future earthquake rates on subduction 

interface sources will be similar to the past observed seismicity rates. Earthquake-recurrence rates and 

geometry for subduction faults are based on geologic measurements, geodesy strain rates, and seismicity 

characteristics. An important consideration in the hazard analysis is estimating the size and frequency of 

earthquakes that can rupture along the subduction interfaces of the Tonga and New Hebrides zones. We 

estimate the a- and b-values of the magnitude-frequency equation by fitting a Gutenberg-Richter 

distribution to the historic seismicity. Alternative source models are then constructed for estimating the 

epistemic uncertainty in the maximum magnitude that is capable of occurring in the zone. This 
4

epistemic uncertainty is described using a logic-tree analysis that characterizes alternative input models 

and their weights at each decision point in the analysis. Aleatory variability is considered directly in the 

seismic hazard code and accounts for random variability in the locations and magnitudes of earthquakes

along the subduction zones. Typically, a given parameter in the analysis contains both epistemic 

uncertainty and aleatory variability components. 

The GMPEs relate the source characteristics of the earthquake and propagation path of the 

seismic waves to the ground motion at a site. The predicted ground motion is typically quantified in 

terms of a median value and measure of uncertainty, which is a function of magnitude, distance, style of 

faulting, and other factors. These models assume a lognormal probability density function (aleatory 

variability) of peak horizontal ground acceleration (or spectral accelerations) that is integrated in the 

analysis to obtain the probability of exceedance of a particular ground-motion level. In this hazard 

model, we calculate ground motions from subduction interface sources that are up to 1,000 kilometers 

(km) from the source and intraslab and shallow crustal earthquake that are up to 200 km (epicentral 

distance) from the site. We apply the subduction interface models to account for large (greater than M 7) 

shallow earthquakes (less than 50 km depth) on the subducting fault plane and intraslab equations to 

characterize all other earthquakes. The ground motion alternative models are accounted for in a logic 

tree framework to account for epistemic uncertainty. 

Seismic Sources

Our seismic source model is composed of two subduction source models with 3D geometry and 

background source models for different depth layers, tectonic regimes, and maximum magnitudes. Both 

of these models depend on the earthquake catalog that we produce for this paper. We are not aware of 

slip-rate data or paleoseismic studies for faults on these South Pacific islands. Therefore, the 

earthquakes on subduction zone faults and background seismicity are modeled using historic seismicity. 

This hazard model assumes that earthquakes will continue at the same rate and size distribution as 

observed over the past century. 

Earthquake Catalog

A new seismicity catalog was compiled for this project from three global source catalogs. The 

Engdahl and Villaseñor (2002) catalog (EVC) includes earthquakes greater than about magnitude 6.5 

since 1900 and about magnitude 5.5 since 1964. A second catalog (PDE) was downloaded from the 

USGS Earthquake Hazards Program website and includes earthquakes from 1973 through December, 

2010 (http://earthquake.usgs.gov/earthquakes/eqarchives/epic/epic_rect.php, “Rectangular Area 

Search,” accessed January 6, 2011). A third catalog (ISC) was downloaded from the International 

Seismological Centre website and includes earthquakes from 1907 through May, 2008 

(http://www.isc.ac.uk/search/bulletin/rectang.html, “On-line Bulletin, Rectangular Selection,” accessed 

July 26, 2010). The three source catalogs were reformatted, concatenated, and sorted chronologically.

Moment magnitudes (Mw) were either selected directly from original source catalogs or converted from 

other magnitude types using published relations that account for saturation and other scaling effects; we 

use Sipkin (2003) to convert body-wave magnitude (mb) to moment magnitude (Mw) and bilinear or 

trilinear approximations to the curves plotted by Utsu (2002) for surface wave magnitude (Ms) and local 

magnitude (ML). Duplicate catalog entries were identified and deleted using the preference order: 

Engdahl and Villasenor (2002) catalog greater than Preliminary Determiniation of Epicenter catalog, 

PDE, greater than International Seismic Centre catalog, ISC. For the hazard analysis, foreshocks and 

aftershocks were identified and deleted using the declustering methodology of Gardner and Knopoff 
5

(1974). No special declustering treatment was applied for great earthquakes. The Gardner and Knopoff 

technique only considers earthquakes up to M 8, using a maximum 94-km-radius circular aftershock 

window. Even though this window is circular, the algorithm deletes aftershocks of aftershocks and will 

naturally eliminate more earthquakes along the trend of the fault.

The earthquake catalog is shown in figure 2 for earthquakes with M greater than or equal to 5 

color coded by depth. Cross sections show the dips and depths of earthquakes in the Benioff zone. 

Earthquakes extend down several hundred kilometers along both subducting slabs. Figure 3 shows the 

moment tensors of the Global Centroid-Moment Tensor Project. Strike-slip, reverse, and normal fault 

earthquake mechanisms are distributed across the region. The normal fault earthquakes off both trenches 

are thought to be associated with bending stresses in the outer rise. 

Figure 4 shows the annual rate of earthquakes with M greater than 4.0 since 1900 and 1964 as 

well as the declustered catalogs from the same periods. The earthquakes follow a Gutenberg-Richter 

magnitude-frequency distribution (Gutenberg and Richter, 1944) between M 5 and the upper 

magnitudes; for earthquakes with magnitudes less than M 5, the curve bends over—this suggests an 

incomplete catalog. Therefore, we use M 5.0 since 1964 as our completeness cutoff for the earthquake 

catalog. Most of the declustering occurs for earthquakes less than M 7. The rates calculated for the 1900 

and 1964 catalogs are similar for events greater than M 6.5. 

Gridded-Seismicity Background Models 

We use the declustered catalog as the basis for the background source model. The M greater than 

or equal to 4 earthquakes since 1964 are smoothed using a 50 km smoothing kernel and 10a values 

(which sets the earthquake rate in the Gutenberg and Richter, 1944 relationship) are calculated at grid 

points spaced 0.1 degree apart in longitude and latitude. We calculate the Gutenberg and Richter bvalues based on the 1900–2010 and 1964–2010 catalogs for several regions and depth intervals (figs. 5 

and 6). With one exception, the calculated b-values are generally close to 1.0 for the background and 

outer rise zones, but we use the calculated b-values in this hazard analysis (table 1). The primary outlier 

in this b-value analysis is associated with the zone overlying the upper 50 km of the New Hebrides 

subduction zone, where the b value is about 0.58. We use the calculated a- and b-values to produce a 

magnitude-frequency distribution from M 5.0 to Mmax. The seismicity analysis of Sukale and Grünthal 

(2009) indicates a b-value of 0.71, which is also lower than observed for most similar tectonic 

environments. Sukale and Grünthal used a different declustering algorithm and different completeness 

times, and these differences would account for some of the differences between their b-value 

calculations and ours. 

Subduction Zone Earthquake Source Models 

Subduction-interface earthquakes M greater than or equal to 7 are modeled as rupturing from 

10 km down to 50 km depth. Deeper earthquakes on the Wadati-Benioff zone are modeled using a 

Gutenberg and Richter (1944) magnitude-frequency distribution with the smoothed rate of earthquakes 

and a calculated b-value. Figure 7 shows a magnitude-frequency plot of the 32 shallow M greater than 

or equal to 7 earthquakes associated with the New Hebrides zone. The b-value of 0.58 that was 

calculated from the M greater than or equal to 4 earthquakes does not fit the rates of the larger 

earthquakes. Analysis of figure 7 indicates that a b-value of 1.0 better predicts earthquakes M greater 

than or equal to 7 events in the model. Figure 8 shows a magnitude-frequency plot of the 22 M greater 

than or equal to 7 earthquakes associated with the Tonga subduction zone. The b-value calculated for 

M greater than or equal to 4 earthquakes in this region is consistent with the b-values calculated from 

M greater than or equal to 7 earthquakes within the Tonga zone, so we use the calculated b-value of 
6

0.87 for the entire range of earthquakes from M 5.0 to 7.0. The slip rate varies along the strike of the 

New Hebrides and Tonga subduction zones, so we considered whether or not to allow for variable rates 

of M greater than or equal to 7 events. Figure 1 shows M greater than or equal to 7 earthquakes, and the 

observed rate of earthquakes does not appear to be correlated with the slip-rate variability. For example, 

of the 32 M greater than or equal to 7 events along the New Hebrides zone, 17 events occurred along the 

northern half of the zone and 15 along the southern half of the zone, even though the slip rate varies 

significantly along the strike. Of the 22 M greater than or equal to 7 earthquakes along the Tonga zone, 

12 events occurred in the northern half and 12 events in the southern half of the zone, even though slip 

rates displayed in figure 1 in the northern portion of the zone are more than double slip rates in the 

southern portion of the zone. Moreover, the seismicity appears to be located uniformly along the length 

of these zones, although the Tonga zone exhibits less uniformity and contains two clusters of large 

earthquakes. Therefore, for this assessment, we assume that the seismicity rate does not vary along the 

strike of the subduction zone and is consistent with the historic rate of earthquakes along the entire zone. 

Earthquakes occurring prior to modern seismic instrumentation were sometimes recorded from 

written observations of tsunamis or earthquake effects. Okal and others (2004) suggest that three large 

earthquakes in the early twentieth century on the Tonga-Kermadec arc system were thought to have 

maximum magnitudes between 8.4 and 8.7. They suggest that more recent moment estimates of these 

events led to the perception that maximum magnitude for earthquakes on this subduction zone would 

have moment of 2.5×1028 dyne-centimeter, which is consistent with a lower Mw 8.2 earthquake. Okal 

and others (2004) interpreted regional tsunami data from the November 17, 1865, earthquake as 

originating from a large earthquake on the Tonga-Kermadec arc system with moment of 4 ×1028, which 

is consistent with Mw 8.4. This evidence in combination with the December, 2004 M 9.1 earthquake on 

the Sumatra subduction zone and the March 11, 2011, M 9.0 Tohoku-Oki earthquake near Sendai on the 

Japan subduction zone (both events were greater in size than anticipated) were influential in assessing

the alternative maximum magnitude models that we applied to these subduction zones. We have 

assigned a weight of 1⁄2 to the model in which these earthquakes occur with magnitude up to 8.5 and 

have assigned a weight of 1⁄2 to the model in which these earthquakes are capable of rupturing in 

earthquakes up to magnitude 9.0 on the subduction interface. For all other zones, we typically have 

considered the largest historic magnitude with an additional 0 to 0.2 magnitude units to account for the 

possibility that we have not observed the largest potential earthquake during the past century. Table 1 

shows the parameters applied in our model, including the largest observed earthquakes in each zone as 

well as the maximum magnitudes applied in the model. 

Source Geometry

Figure 9 shows the source zones considered for our model. We separated out 6 zones in the 

model: (1) Tonga subduction interface, (2) New Hebrides subduction interface, (3) Tonga outer rise, (4) 

New Hebrides outer rise, (5) the Fiji zone that encompasses much of the back-arc spreading and fracture 

zones in the Fiji platform, and (6) all the other areas not considered in the previous zones. The geometry 

of the Tonga and New Hebrides subduction-interface models is based on the Slab 1.0 model of Hayes 

and others (2011) which applies bathymetry, seismicity, and reflection-profile data to constrain the 3D 

non-planar geometry of subduction zones from the trenches through the base of the seismogenic layer. 

We define the interface zones as the seismicity contained within the region above the 10 km to 50 km 

depth contours indicated by the Slab 1.0 model. It is clear that some of the seismicity included above 

this depth interval is not located on the interface but may have ruptured within the slab. It would be 

helpful in the future to define a 3D zone or analyze the focal mechanisms to better differentiate the 

interface and intraslab earthquakes. The outer-rise zone parameters were based on the location of 
7

abundant normal fault earthquakes on the leading edge of the subducting slab, in the region where the 

slab bends due to frictional resistance as the tectonic plate descends. The ends of the outer-rise zones are 

defined at the end of the mapped subduction zones of Pelletier and others (1998) and Bird (2003) (fig. 1 

of this report). The northern boundary of the Tonga zone was defined along a lineament of seismicity 

that extends southwest across the map. Seismicity is much sparser to the north of that zone. The Fiji 

zone outlines the Fiji platform which can be observed in the bathymetry data and is defined by many of 

the geologic structures shown by Pelletier and others (1998) and Bird (2003). 

Ground Motion Model

In this section we describe newly processed strong-motion data for large earthquakes across the 

Pacific basin and GMPEs that are used in assessing the ground motions across Southeast Asia. The 

strong-motion data are used to compare the different GMPEs and determine a weighting scheme for the 

hazard analysis. The GMPEs examined in this analysis were the Youngs and others (1997) (also known 

as the Geomatrix Consultants, 1997), the Atkinson and Boore (2003), and the Zhao and others (2006) 

for subduction zone and deep earthquakes, and the Boore and Atkinson (2008), Campbell and 

Bozorgnia (2008), and Chiou and Youngs (2008), and Zhao and others (2006) for shallow crustal 

equations. These equations were used in developing the U.S. National Seismic Hazard Maps (Petersen 

and others, 2008). 

Summary of Current Ground Motion Prediction Equations

Youngs and others (1997) used a global subduction data set containing 350 horizontalcomponent response spectra compiled for earthquakes through 1989; this data set was compiled by 

adding data to a version of the subduction database compiled by Crouse (1991). Youngs and others 

(1997) developed their attenuation relationship for subduction zone interface and intraslab earthquakes 

of moment magnitude M 5 and greater and for distances of 10 to 500 km. In addition, they simulated 

ground motions from large interface earthquakes to determine the appropriateness of their model for 

moment magnitude and distance between the site and the rupture (Rrup) that were not well represented in 

their data set. Specifically, they simulated earthquakes with Mw greater than 8 for interface earthquakes 

and Rrup less than 30 km, as well as distances greater than 300 km, for both interface and intraslab 

earthquakes and provide regression coefficients for rock and soil site classes. They assume that average 

velocity properties of the rock ground motions included in their analysis is similar to a National 

Earthquake Hazards Reduction Program (NEHRP) soil catalogory A (characterized by shear wave 

velocity in the upper 30 meters (m) that is greater than 5000 feet/second (ft/sec) or 1500 meters per 

second (m/sec) but that it is close to a NEHRP B category (characterized by shear wave velocity in the 

upper 30 m between 2,500 ft/sec or 760 m/sec and 5,000 ft/sec.

Atkinson and Boore (2003) used a global subduction data set containing 1,200 horizontalcomponent spectra compiled for earthquakes through 2001. This data set was developed by combining 

the original subduction database from Crouse (1991), the updated subduction database from Youngs and 

others (1997), and additional events from Cascade, Japan, Mexico, and Central America. They also 

updated metadata in the database that may have been incorrect or missing. To check the validity of 

combining regional data sets into a global data set, Atkinson and Boore (2003) investigated whether 

there were systematic differences in ground motions from different regions. They found that the 

Cascade region of the northwest United States and southwest Canada and the area surrounding Japan 

showed regional variations. However, the average residuals for other regions were not significantly

different from zero. Atkinson and Boore (2003) suggested that the regional differences seen in Japan 
8

and the Cascade region were attributable to regional differences in the depth of the typical soil profiles 

of the two regions. Consequently, Atkinson and Boore (2003) developed a global attenuation 

relationship and provided regional correction factors for the Cascade and Japan regions. Atkinson and 

Boore (2003) concluded that there were limitations on the applicability of global relations to any 

specific region and that the applicability of global relations to any region could be improved by using 

average residuals as regional-correction factors. The global attenuation relationship and the regional 

correction factors were optimized for the magnitude and distance range of engineering interest by 

limiting the final regression to data that fell into specific magnitude-distance range bins. The 

performance of the equations at larger distances than those used in the regression was checked by 

examining plots of the residuals and was found, with a few exceptions, to have a mean near zero in the 

important distance range within 100 km of the fault. The regression equations of Atkinson and Boore 

(2003) are given for site classes of rock (NEHRP B) or soil (NEHRP C, D, and E).

Zhao and others (2006) used a global data set containing 4,726 horizontal-component spectra. 

Records from the Japan region made up the majority at 4,518 records. In this data set, 1,285 records

were from crustal events, 1,508 were from interface events, and 1,725 were from intraslab events. 

Twelve records from regions outside Japan were added to their database of Japanese interplate events to 

fill in for missing magnitude-distance ranges, while no records from regions outside of Japan were 

added to the intraslab database. Unlike Youngs and others (1997) and Atkinson and Boore (2003), Zhao 

and others (2006) did not publish or distribute their final database to the user and research community 

(citing data ownership-privacy issues) and thus, the following inferences were made by examining the 

figures provided in their paper (Zhao and others, 2006). Figure 1 of Zhao and others (2006) shows 

magnitude, focal depth, and source-distribution plots of their data set. These plots show the distance 

distribution for the interface events ranging between 30 and 300 km with most recordings occurring at 

distances greater than 50 km, and for intraslab events between 40 and 300 km with most occurring at 

distances greater than 60 km. The magnitude distribution varies between Mw 5 and 8, with most 

earthquakes having magnitudes less than 6.0. The focal-depth distribution for the interface events ranges 

fairly evenly between 15 and 50 km. The intraslab events have distances that are distributed less evenly 

between 20 and 125 km, with most events occurring between 45 and 80 km. Zhao and others (2006) 

consider four site classes: SC I, II, III, and IV, which they claim are similar to rock, hard soil, medium 

soil, and soft soil, respectively. They consider the average shear wave velocity of the SC I category 

(rock) to be about 700 m/sec. Zhao and others (2006) state that the intraslab equations should not be 

used for depths less than about 40 km, since there is little data to constrain these equations in this 

distance range. We considered using the Zhao and others (2006) intraslab equations for shallow crustal 

earthquakes, but felt that this would not be recommended by the authors of the ground-motion model. 

Instead we apply the Zhao and others (2006) crustal and next generation attenuation relations described 

below. 

The Next Generation Attenuation (NGA) project developed ground-motion models for shallow 

crustal earthquakes in active crustal margins. This research effort involved (1) developing a consistent 

database of 3,551 recorded ground motions from 173 earthquakes as well as background information on 

processing and parameters that define the earthquake source, path, and site conditions of the strong 

motion record; and (2) developing five independent ground-motion models by developer teams that 

interacted through workshops and working meetings (Power and others, 2008). The USGS National 

Seismic Hazard Maps applied three equations of Boore and Atkinson (2008), Campbell and Bozorgnia 

(2008), and Chiou and Youngs (2008) based on working group discussions (Petersen and others, 2008). 

These ground-motion-prediction equations were developed for peak ground acceleration, peak ground 

velocity.,and 5-percent damped spectral accelerations in the period range of 0 to 10 sec; the equations 
9

included models for strike-slip, reverse, and normal earthquake mechanisms; they considered ground 

motions for magnitude 5 to 8.5 earthquakes; they developed models for distance ranges of 0 to 200 km; 

and they used shear wave velocity in the upper 30 m (Vs30) site classifications. 

Figures 10 through 13 show primary features of the subduction zone and intraslab (deep) 

GMPEs and illustrate how ground motions decay as a function of distance, magnitude, mechanism of 

earthquake, and depth. These figures show the spectral accelerations for 1 hertz (Hz) and 5 Hz for 

interface and intraplate earthquakes. Results indicate that amplitudes from intraplate (intraslab) events 

are larger near the source but decay faster with distance than ground motions from interplate events for 

similar sizes and distances. Intraslab earthquake ground motions for M 7.5 are greater than the ground 

motions from similar size events occurring on the plate interface at distances less than 100 km, for both 

1 Hz and 5 Hz spectral-acceleration models. 

Each ground-motion model for intraslab earthquakes has terms that allow for increased ground 

motion with depth; however, estimates of the ground shaking are not well constrained for depths below 

200 km, and this data was not typically considered in developing the prediction equations. Atkinson and 

Boore (2003) and Zhao and others (2006) recommend that the ground motions should not continue to 

increase for earthquakes with depths greater than 100 km or 125 km, respectively. Therefore, we limited 

the intraslab ground motions obtained from the Atkinson and Boore (2003) equations from continually 

increasing for depths below 100 km. Similarly, we have limited the intraslab ground motions obtained 

from the other two equations from growing at depths below 125 km. Figure 13 shows how these ground 

motions vary with the earthquake depth. For an M 7.5 earthquake, the ground motions are typically 

lower for deep earthquakes out to about 50 km (epicentral distance) than for shallower earthquakes. 

However, at larger epicentral distances, the curves cross over, and deep earthquakes can generate 

similar or larger ground motions than shallower earthquakes. Future studies should focus on ground 

motions from earthquakes with depths deeper than 200 km since these data not well constrained. 

Figures 14 and 15 show comparisons between the shallow crustal sources and comparisons of 

the crustal, intraslab, and subduction-interface ground-motion models. Figure 14 shows comparisons of 

the Zhao and others (2006) and one of the Next Generation Attenuation ( NGA) equations developed by 

Boore and Atkinson (2008). In general the Boore and others model is lower than the Zhao models for M 

7 to 8 but is a little higher for M 6 earthquakes at 1 and 0.2 second spectral acceleration ground motions. 

Figure 15 shows that crustal earthquakes are similar to interface earthquake ground motions out to 200 

km distances while the intraslab models predict higher ground motions at shorter distances. 

For this analysis we present seismic hazard maps for shear wave velocity in the upper 30 m 

(Vs30) of 760 meters per second (m/s), which is the soil condition applied in the building codes. We use 

the rock equations for each of the GMPE’s. We recommend that future efforts are put into collecting 

Vs30 data at seismic recording stations and that ground motion models are developed that include a 

Vs30 term. This would bring down the uncertainty associated with these ground motions. 

Strong-Motion Data

Spectral ground motions were measured from over ten years (1995–2007) of strong and weak 

motions of earthquakes located less than 1,000 km from nine permanent United States Geological 

Survey (USGS) Global Seismographic Network (GSN) stations near Pacific Rim subduction zones 

(table 2). The strong motion instrumentation of the GSN consists of a Quanterra Q330HR digitizer and

three-component piSensor Accelerometer and real-time communications. Ground-motion sensors and 

communication-system electronics are housed underground in large waterproof vaults in order to 

achieve good coupling and to protect equipment from damage due to excessive moisture (detailed 

station information can be found online: http://earthquake.usgs.gov/monitoring/operations/.) For 
10

example, the vault at the Samoa station(with the code IU.AFI, fig.16 and .able 2) is a small concrete 

block building set into the ground with the roof at ground level and the concrete floor on solid 

Pleistocene Salani Volcanics basalt bedrock. Seismometers sit on piers that are not isolated from the 

vault floor. Station site resonance was estimated with Nakamura’s method that calculates the horizontal 

component to vertical component ratio (H/V) method using 248 earthquakes recorded at the Samoa 

GSN station (McNamara and others, 2009). The mean H/V estimate at IU.AFI displays no significant 

resonance. We do not have direct measurement of Vs30 at any of our stations. Broadband seismometers 

of the GSN record 40 samples per second, and strong motion instruments record 100 samples per 

second. 

Figure 16 shows the earthquakes and GSN strong-motion stations that recorded M 6.0 to M 8.1 

earthquakes at distances between 47 and 973 km. Figure 17 shows graphs of the strong-motion data 

recorded at these stations, along with the Zhao and others (2006) rock intraslab equation for 1 Hz 

spectral acceleration and peak horizontal ground acceleration. While the data are similar to the 

prediction equations for peak horizontal ground acceleration (PGA), the data recorded at 1-Hertz are 

typically a little higher than the Zhao and others (2006) equation. However, it is important to point out 

that the data have very large scatter about the GMPE. We examined the residuals of the data as a 

function of magnitude and distance to determine the weighting of the GMPEs. This is described in the 

next section.

Figure 18 shows the magnitude, distance, and depth distribution of GSN data that we considered. 

We analyzed 73 moment tensors to assess intraslab and interface earthquakes; our analysis indicated 

that 62 of the records were from intraslab and 11 were from interface earthquakes. More than half of the 

interface earthquakes were from earthquakes in Alaska. Magnitudes are plotted as a function of distance 

and depth for interface and intraslab events. 

During November, 2009, the USGS deployed five portable strong-motion seismometers (Reftek 

Mems seismometers, Reftek RT-130 digitizers) with the goal of recording aftershocks of the 29 

September, 2009, M 8.0 Samoan earthquake. Continuous seismic data and corresponding metadata for 

all stations were retrieved from the online archives of the USGS Albuquerque Seismological Laboratory 

(ASL) Data Collection Center (DCC). All waveform data from both portable and permanent seismic 

stations used in this study are archived and available for download from the Incorporated Research 

Institutions for Seismology (IRIS) Data Management Center (DMC; http://www.iris.edu/data/). In our 

preliminary analysis of these shaking data, we could not distinguish between interface and outer rise 

ground motions (McNamara and others, 2009). 

In analyzing the GSN records, the time-series window was chosen to include all energy from 

crustal P-waves (Pg) to later-arriving upper mantle S-waves (Sn) and surface waves (window bounded 

by seismic velocity of 9 kilometers per second (km/s) to 2 km/s from the earthquake origin time). Origin 

times and magnitudes used in this study were obtained from USGS Preliminary Determination of 

Epicenters (PDE. Additional data processing to obtain absolute ground acceleration included 

deconvolution of the instrument response transfer function from the demeaned and tapered time series.

Finally, the response spectral estimates were measured using the 100 samples per second threecomponent acceleration time series in the frequency band, 0.33 to 20 Hz. All waveforms were visually 

inspected for quality and accuracy. We calculated the geometric mean of the horizontal components for 

each earthquake station for use in this analysis. We calculated spectral acceleration as described in 

McGuire (2004). 
11

Analysis of Ground Motion Prediction Equations

We evaluated three ground GMPEs (Youngs and others, 1997; Atkinson and Boore, 2003; and 

Zhao and others, 2006) to determine how well they fit the ground-motion data we collected in the 

Pacific Arc Island region. We also compare the equations to some large earthquakes that occurred near 

Japan (appendix 1). The purpose of this evaluation was to assist in GMPE selection and weighting for 

this hazard analysis. Two performance measures were considered. The first evaluation assessed how 

well each GMPE modeled the magnitude and distance dependence of the ground-motion amplitudes. 

The second examined if the GMPE systematically over- or under-predicted the ground-motion 

amplitude. Table 2 shows the earthquake parameters and recording station information. Tables 3–5 

show the observed ground motions and the ground motions predicted spectral accelerations of 1 Hertz 

(Hz) (1-second (sec) period) and 5 Hz (0.2-sec period) and peak horizontal ground accelerations 

For this analysis, we restricted the data to events with rupture distances less than 300 km; this 

was the approximate cutoff distance of the three GMPEs considered. This reduced the data set to 73 

horizontal-component response spectra for the geometric mean recorded by eight stations (table 2). Six 

stations (ADK, AFI, GUMO, RAO, HNR and TATO) had six or more recordings; two stations (DAV 

and PET) had only one record. Of the eight stations, AFI recorded the greatest number of events: 17 

(fig. 16). In general, our results do not indicate any particular region of the circum-Pacific varying 

systematically. However, strong motion data recorded at station RAO (near the Kermadec trench) were 

considerably higher than the predicted values. Additional examination of strong motion records from 

RAO did not lead us to exclude these recordings. However, written descriptions of station RAO indicate 

that it is located near the edge of a small island with a 200-foot cliff. Therefore, it is possible that these

records include topographic amplifications. 

Because of the sparse station distribution, no earthquake is recorded at more than one station. 

Some stations recorded more earthquakes than others, which could lead to a bias in the statistical 

analysis. Therefore, we take the station characteristics (including site response) and the number of 

recordings at each station into account in analyzing the residuals. We do not have direct shear wave 

velocity in the upper 30 m (Vs30) measurements at any of the stations; however, most of the stations are 

located on volcanic islands, so it is probable that many of these sites are located on rock or rock which 

is overlain by a thin layer of alluvium. In this analysis, we remove these average site effects based on 

the comparison with the GMPEs for rock, which we assume is close to 760 m/s Vs30. The station 

effects are removed as described below and in Appendix 2. This analysis would be much more robust if 

we had direct Vs30 measurements at each station. 

We use a random-effects regression model that solves for regression-model parameters and the 

systematic offset of the station terms (site effects) using a maximum likelihood approach (Appendix 2). 

We applied the regression model of Abrahamson and Youngs (1992), which is equivalent to a twostaged regression analysis (Brillinger and Preisler, 1985; Joyner and Boore, 1993). This approach 

assumes that if there are two or more observations at a single station, then these observations are 

correlated through site effects. If there are many recordings at a single station, then the random-effects 

model computes a station term that is approximately equal to the average total residual at each station

and represents the overall site effect. If there is only one or a few observations, then the random-effects 

model computes a station term that is based on a combination of the station term variance and a global 

random variance based on the entire data set. 

The random-effects regression was performed on the residuals obtained by subtracting the 

GMPE predicted ground motion (as a function of magnitude, distance, site, etc.) from the observed 

ground motion. The residuals were fit to the following linear model that is similar to the Lin and others 

(2011) approach: 
12

Resid = y − y� = C1 + ηi + ζij (1)

Where: 

y is the data, 

y� is the GMPE, 

C1 is a constant term that accounts for the differences in the model and the regional data set and could 

be considered as a regional source term, 

ηi is the inter-event term and in our case acts as the station term because we use a sparse data set

comprised of earthquakes that are recorded only at a single station, 

ζij is the intra-event term that represents the remaining residual or ‘left-over’ term after the residuals 

have been fit to Equation 1, 

i is the station index, and 

j is the source index. 

The constant term is a systematic offset of the data and essentially accounts for regional 

differences that exist between the ground motion of the data set and the predicted GMPEs. This term 

was added to the random-effects model to accommodate any overall systematic differences between the 

empirical data and the model estimate. We use this term in our analysis to account for a regional shift in 

the median ground motion for our logic tree uncertainty analysis. The station term accounts for the 

station-to-station differences, most likely explained by the site effects at the station. The “left-over 

term,” herein described as “single-station residuals,” accounts for all other un-captured effects that 

contribute to the ground motion variability, such as path effects and aleatory variability. 

In analyzing ground motion residuals for GMPE performance, the analysis should be done using 

the uncorrelated residuals and not the correlated residuals. In this study, this requirement for 

uncorrelated residuals implies that we should remove the contribution to the ground motion from site 

effects and constant offset before analyzing the residuals for unevenly sampled data. If correlated 

residuals were used, results from this analysis would be biased towards the individual source, path, and 

site effects of the events, paths and stations that were sampled the most. 

Figures 19–21 show examples of how we remove the station correlations from the total residuals 

for PGA, 5 Hz, and 1 Hz, respectively. For example, Figure 19A shows the average total residual at each 

station. Figure 19B shows the station term. Figure 19C shows the average single-station residual at each 

station which has the station term and constant offset removed (uncorrelated). This effectively removes 

the site effect based on the average station bias. Figures 20 and 21 show the same details but for 5 Hz

and 1 Hz, respectively. This concept is more fully explained in appendix 2. 

To understand the residual trends, we plotted the single-station residuals as a function of 

magnitude; single-station residuals are the residuals with the systematic offset and station terms 

removed. This is demonstrated by comparing figure 22A and B. Figure 22A shows the total uncorrected 

PGA residuals for moment magnitude. Figure 22B displays the uncorrelated single-station residual 

terms; correlations from station effects and systematic offset of the data have been removed. The 

dispersion of the residuals is noticeably larger in figure 22A than in figure 22B. The single-station 

residuals versus moment magnitude are seen in figure 22B, C, and D for PGA, 5 Hz, and 1 Hz

respectively, in which the blue squares, green triangles and red dots represent the Atkinson and Boore 

(2003), Zhao and others (2006) and the Youngs and others (1997) model residuals, respectively. The 

positive residual trend (negative slope of the blue squares) seen in figure 22A from the Atkinson and 

Boore (2003) model illustrates that their global model under-predicts ground motions at the smaller 

magnitudes and over-predicts at the larger magnitudes. The Zhao and others (2006) residuals appear to 
13

be centered close to zero for M less than 7.4. All of the models over-predict ground motions for large 

magnitudes. 

It is interesting to note that the GMPEs shown in figure 22 over-predict the ground motions for 

earthquakes near M 7.9. There are four earthquakes with M of about 7.9; these earthquakes are recorded 

at stations between 40 and 300 km in the Aleutians (1996, 2003), Samoa (2009), and Solomon Islands 

(2007). The earthquakes are shallow and include both interface and outer rise earthquakes. We do not 

have a good explanation for this bias at large earthquakes. However, it could be related to the small 

number of large earthquake data available for developing the models. To analyze these residuals, we 

first examined the rate of amplitude decay (as a function of both magnitude and distance) for PGA and 

spectral frequencies 5 Hz and 1 Hz. 

We model trends by calculating the average single station residual and the standard deviation 

within different magnitude bins; these average residuals are plotted in figures 23 a, b, and c for PGA, 5 

Hz, and 1 Hz, respectively. For Mw less than 7.4, the average residual was estimated with 10 or more 

points. For Mw greater than 7.4, the average residuals were estimated using only two values and are not 

as well constrained. Figure 23 graphs show that the average residuals for all three GMPEs tend to center 

near zero for M less than 7.4, where the data is most abundant. The average residuals for larger 

earthquakes are significantly larger than for smaller earthquakes for all of the equations. We calculated 

the standard deviation for PGA data in these magnitude bins and found that the Zhao and others (2006) 

equation generally had lower sigmas compared to the other GMPEs, but this was not always the case. 

In a similar manner, the overall rates of amplitude decay with rupture distance were explored by 

computing the average single-station residual for various distance bins. Figure 24A shows all the singlestation residuals as a function of distance for PGA. Figures 24B, C, and D show the average singlestation residuals binned by distance for PGA, 5 Hz, and 1 Hz, respectively. For rupture distances 

between 200 and 300 km, the average residual was estimated using 10 points or more and is fairly well 

constrained. For distances ranging between 40 km and 200 km, the number of points in each distance 

bin averaged between 1 and 5, and is not as well constrained. From inspection of figures 24 b, c, and d, 

all of the equations over-predict ground motions at larger distances and under-predict for short distances 

less than 100 km. The Geomatrix intraslab equation over-predicts more than the other GMPEs at 

distances beyond 300 km (fig. 11). The Zhao and others (2006) equations appear to us to be more 

compatible with the data over the entire range of distances than the other two equations. 

Next, we investigated if a systematic difference existed between the ground motions of the data 

set and the global or regional GMPEs. Table 6 shows systematic offset for the data and the ground 

motion prediction equations. Several ground-motion experts have investigated the validity of using 

GMPEs to adequately represent any one region. Atkinson and Boore (2003) found systematic regional 

differences between the ground motions recorded in the Cascade and Japanese regions and found no 

conclusive regional differences in the Mexico, Peru, and Alaska regions. They explained that the 

regional differences they saw were attributable to the depth of the typical soil profiles of the Cascade 

and Japan regions and recommended correction factors to their model for these two regions. 

Abrahamson and others (2011) found that on average, the ground motions from different regions 

showed no systematic differences, except in the Cascade region. In a similar vein, we checked for 

average regional differences between the Samoa strong motion data set and each GMPE. If they exist, 

we checked if regional correction factors would be appropriate for estimating the ground motion of the 

Samoa Hazard. The regional differences were again investigated by performing the regression using the 

random effects model, including a constant term (regional offset term) that we added to the regression. 

Table 6 lists this data set constant term for the Zhao and others (2006) model at PGA and spectral 

frequencies, 5Hz and 1 Hz. The ground motions computed using the Geomatrix Consultants (1997) 
14

model had the largest offset from the Samoa data set, while the Zhao and others (2006) has the smallest. 

As in the Atkinson and Boore (2003) model, these terms may be used as regional correction factors to 

improve the GMPEs’ estimates of the ground motions in the Pacific region. 

The last measure we used to assess performance of each GMPE was to analyze the standard 

deviation of the residuals at PGA, 5Hz and 1 Hz for each model. Standard deviations for each model are 

recorded in table 7. The Geomatrix Consultants (1997) and Atkinson and Boore (2003) model have the 

largest standard deviations that range between 0.65 and 1.0. Many of these sigmas are larger than 

typical GMPEs for pga and 1 Hz and 5 Hz Spectral accelerations. The Zhao and others (2006) standard 

deviation at 1 Hz of 0.717 is within the range of typical GMPE sigma values. 

Our analyses indicate that the Zhao and others (2006) GMPE captures the ground motion 

amplitude dependence on magnitude and distance better than the other models for this Pacific island 

region. In addition, the Zhao and others (2006) model appears to better fit the strong motion data from 

subduction data off the Japan coast (Appendix 1). Youngs and others (1997) shows a much smaller rate 

of decay in ground-motion amplitude with distance and Atkinson and Boore (2003) shows a much 

larger rate of decay in ground motion amplitude with moment magnitude than observed. In addition, 

each GMPE systematically over- or under-predicts the ground motion amplitudes at PGA and spectral 

frequencies at 5 Hz and 1 Hz. The systematic shift is lowest for the Zhao and others (2006) equation and 

this offset is shown in table 6. This suggests that the ground motions within the Pacific Arc Island 

region may be different than other regions; however, a larger and more complete database is needed to 

confirm this. The epistemic uncertainty concerning whether regional differences exist or not is 

incorporated in the seismic hazard analysis as a branch option of the logic tree. However, because of the 

sparse nature of the data set we compiled, we have given this option lower weight. The average overprediction by the GMPEs can be used as regional correction factors that may better predict the ground 

motions of the Samoa region. Tables 7–9 show the single station sigma, station sigma, and total sigma 

for each of the three evaluated ground motion prediction equations. Using these data we decided to use 

only the Zhao and others (2006) equations for interface and intraslab earthquakes. We applied the 

correction factors shown in Table 6 for the Zhao and others (2006) equations to account for epistemic 

uncertainty in this analysis. We only use the Zhao and others model to capture the magnitude and 

distance dependence of the ground motions because it fits this limited data set best. The rock model of 

Zhao and others (2006) is probably more similar to the Vs30 of 760 m/s that is required in the NEHRP 

building codes. 

The Zhao and others (2006) model is run using the rock site condition for both interface and 

intraslab earthquakes. Zhao and others (2006) indicate that their rock equation is consistent with a Vs30 

of about 700 m/s which is similar to the Vs30 of 760 m/s required by the building codes in the United 

States. We only apply the interface models for earthquakes near or on the interface, and we apply the 

intraslab model for all other earthquakes in the model (table 1). In developing the hazard model we 

decided to use the continental crustal earthquake equations (for example, Next Generation Attenuation 

Relation (NGA); see Petersen and others 2008 for further details) and the Zhao and others (2006) 

shallow crustal ground motion model. 

Logic Tree for Seismic Hazard

The final logic tree that we used for this hazard analysis is shown in figure 25. Branches of the 

logic tree are shown for magnitude uncertainty and ground motion models. As discussed in the sourcemodel section, we considered earthquakes with a maximum magnitude of 8.5 or 9.0. This decision does 

not make a large impact on the ground motions, with the M 9.0 model being higher by about 5 percent

to 10 percent. The implied slip rate from our model with maximum magnitude of 8.5 is about 4.5 
15

centimeters per year (cm/yr) for the New Hebrides and about 2.5 cm/yr for the Tonga Subduction Zone. 

The rate for the model with maximum magnitude of 9.0 is about 9.5 cm/yr for the New Hebrides 

Subduction Zone and about 5 cm/yr for the Tonga Subduction Zone. These implied slip rates account 

for less than half of the total slip rates shown in figure 1. Therefore, it is probable that a significant 

portion of the overall slip rate is occurring aseismically. For the ground-motion models, we assigned 

weights as described above based on the residual analysis. Alternative weights were assigned for 

ground-motion models from earthquakes with depths down to 200 km and for earthquakes located at 

greater depths based on the residual analysis. We found that ground motions for earthquakes between 10 

km and 200 km depth had similar characteristics. 

For this hazard assessment, we apply zero weights to the Atkinson and Boore (2003) and 

Geomatrix Consultants (1997) equations. However, we use the variability in the mean of all of these 

published equations to estimate epistemic uncertainty. This epistemic variability between the three 

published GMPEs in the distance range that contains most of the strong motion data (between 100 km 

and 500 km) is about 25 to 50 percent (figs. 10 and 11). The uncertainty is larger for large magnitude 

(M 9) earthquakes at distances greater than 200 km. We assumed a constant 25 percent epistemic 

uncertainty for the Zhao equation to account for modeling the ground motions. This epistemic 

uncertainty could be modeled as a function of magnitude and distance in the future. 

Most of the weight (70 percent) is applied to the Zhao and others (2006) intraslab equation based 

on our analyses described earlier that shows a good correspondence between the data and GMPE. 

However, we also defined a regional model by using the constant term (shift or offset) that we 

calculated from the random effects model to account for a small bias. This shift is defined in Table 6 

and is a function of the ground motion parameter (that is, PGA, 5 Hz, or 1 Hz), but is most significant 

for 1 Hz. We considered that this regional model did not utilize as much data as applied in the Zhao and 

others (2006) equations. Therefore, we assigned smaller weight (30 percent) for the possibility that there 

are regional differences. This regional model is only applied to the intraslab equations. We apply 100 

percent of the weight to the Zhao and others (2006) interface equation because our regional data set only 

contained 11 geometric mean records (9 after distance was limited to 200 km) for interface earthquakes 

and most of these records were from Alaska and not the Samoa region. The Zhao and others (2006) 

intraslab and interface equations capture the magnitude and distance dependence and seem to have a 

functional form that is more consistent with our data set. 

For shallow crustal earthquakes, we apply the Zhao and others (2006) crustal equation with a 

depth of 10 km with half weight and the average of the three NGA equations of Boore and Atkinson 

(2008), Campbell and Bozorgnia (2008), and Chiou and Youngs (2008) with a depth of 10 km with 

appropriate faulting types (normal, strike-slip, and reverse mechanisms).

Results

The relative contributions of each source to the overall ground-motion hazard is displayed in 

figures 26 to 28 for 1 sec (1 Hz) and 0.2 sec (5 Hz) spectral accelerations. Ground motions caused by 

earthquakes on the Wadati-Benioff zone dominate the hazard (fig. 26) and fall off with distance from 

the plate interface. Figure 26 also shows the global moment tensors and ground motions for a 2 percent

probability of exceedance in 50 yr on a uniform firm rock site condition. Ground motions can exceed 1 

g for 1 Hz spectral acceleration over the two subduction zones. Figures 27 and 28 shows the hazard 

contributions from earthquakes at different depth intervals. Ground-motion hazard is highest for the 

seismicity less than 100 km and ground motions decrease with increasing depth beyond 100 km. It is 

important to point out that the ground motions associated with deep earthquakes have not been studied 

well. Future work and data may help us better constrain and understand this shaking from deep 
16

earthquakes that has caused light damage over broad areas (for example, 1994 M 8.2 Bolivia 

earthquake, this earthquake was 642 km deep and caused limited damage).

Spectral accelerations at 1 Hz and 5 Hz and peak horizontal ground-motion hazard maps (with 5-

percent damping) for this South Pacific region at 10 percent and 2 percent probabilities of exceedance in 

50 yr on a uniform firm rock site condition are shown in figures 29 through 34. For assessment of sitespecific hazard, it is critical that further studies should consider local faulting (we did not include any 

crustal faults in this analysis) and ground-motion amplification (we only consider a firm rock site 

condition). These hazard maps were only produced for a single Vs30 =760 m/s site condition, so these 

hazard values need to be modified for appropriate site effects. The map shows some bubbles of hazard 

near American Samoa that are caused by M 5 earthquakes. We examined the data and note that one of 

these earthquakes had M 5.2 and a normal mechanism. 

The GSHAP model for this region shows 10 percent probability of exceedance in 50 yr groundshaking hazard for unspecified site conditions. This model was developed by cobbling together past 

regional hazard assessments and site-specific studies for dams and mines (McCue, 1999). McCue 

(1999) indicates that reasonable design coefficients are 0.2 g for Western Samoa and 0.15 g for 

American Samoa, but it is unclear which site condition or return periods McCue considers. McCue 

indicates that Fiji has experienced damaging earthquakes and that the hazard is comparable to many 

parts of Australia, which the GSHAP map indicates has low to moderate hazard—less than about 0.16 g. 

They also suggest that peak horizontal ground motions across the region are high (4.0 meters per second 

squared (m/s2

), or about 0.4 g) near the subduction zones and moderate (0.8 to 1.6 m/s2 or about 0.1 g) 

near New Caledonia for this 475-yr return period. Our 10 percent probability of exceedance in the 50 yr 

model is consistent with the lower peak ground acceleration hazard values showing about 0.13g near 

Samoa and 0.1 g in southern New Caledonia for a similar return period on a firm rock site condition 

(Vs30=760 m/s). However, our hazard maps for 10 percent probability of exceedance in 50 yr on firm 

rock site condition for Fiji indicate about 0.15 g peak ground acceleration, which is a little higher than 

the GSHAP maps indicate for hazard across Australia. Along the subduction zones, our peak ground 

acceleration hazard values are higher than the GSHAP model, which shows ground motions 

considerably greater than 0.4 g. These differences could relate to our use of different ground-motion 

models or that we have misinterpreted the site conditions of the GSHAP model. For example, in early 

versions of this model, we used the Zhao and others (2006) intraslab to characterize shallow crustal 

earthquakes rather than the crustal models we selected in the final model. This ground-motion-model 

modification resulted in decreased ground motion from about 15 percent to 40 percent in the 2 percent

probability of exceedance in 50 yr ground motions compared with the final models. Other model 

choices could result in higher ground motions estimates since these models are so sensitive in the 

seismic hazard results. 

The probabilistic seismic hazard model for Vanuatu developed by Suckale and Grünthal (2009) 

provides lower estimates of hazard than the model presented here. The Suckale and Grünthal (2009) 

model for peak ground acceleration on stiff soil at Port Vila, Vanuatu, is about 0.7 g for a 10-percent

probability of exceedance in 50-yr level. If we assume that the stiff soil is consistent with a shear wave 

velocity in the upper 30 m (Vs30) of 360 m/s, then we would calculate a PGA hazard of 0.9 g which, is 

about 30 percent higher than the calculated hazard of Suckale and Grünthal (2009). Comparison of the 

0.2 s- and 1-s spectral accelerations under these same assumptions of soil amplification also indicate 

that our values are significantly higher than the model developed by Suckale and Grünthal (2009). 

Again, the difference between our models could be related to the different suite of attenuation relations 

we apply, different b-values, different completeness times, or that we have misinterpreted their soil-
17

classification scheme. We also use a higher maximum magnitude for the New Hebrides subduction zone 

than was applied in their hazard assessment.

Figures 35 to 38 show disaggregation plots that describe the primary contributors to the hazard 

along with the modal magnitude, distance, and epsilon (difference of the calculated ground motion from 

the median ground motion) that contributes most to the hazard. For the Pago Pago, American Samoa 

site, M 7.0 to 7.4 earthquakes at distances about 70 km on the Tonga outer rise are most important to the 

hazard at return periods from 10 to 10,000 yr (fig. 35). However, large subduction interface earthquakes 

with magnitudes of about M 8.4 at large distances of 280 km are also significant, especially at 1 s 

spectral acceleration. For the site in Nuku’alofa, Tonga, the M 7.5 earthquakes at distances less than 110 

km (located on the shallow Fiji platform) contribute most to the hazard, but the large subduction 

interface and Wadati-Benioff earthquakes are also significant, especially at 0.2 s spectral acceleration

(fig. 36). At the Suva, Fiji site, the Fiji platform and Wadati-Benioff earthquakes with magnitudes about 

M 8.0 and distances close to 100 km dominate the seismic hazard for both 1 s and 0.2 s spectral 

accelerations (fig. 37). For the Port Vila, Vanuatu site, several sources contribute to the hazard, 

including the New Hebrides interface and shallow Fiji platform earthquakes (fig. 38). A broad range of 

magnitudes from M 6.3 to 8.7 are important contributors with modal distances for the earthquakes that 

contribute most to the hazard range from 30 km to 114 km. For most of these sites, the high rates of 

earthquakes included in the source model lead to differences between the calculated and median ground 

motions (epsilon in deaggregation plots) that are greater than the median value. Large aleatory 

variability in the ground-motion models tends to increase the hazard across the region, since this is a 

very seismically active region and thus has epsilon values higher than the median. 

These maps are being considered for inclusion in the International Building Code (2012 – 

edition) for ground-motion design in American Samoa. 

Conclusion

The hazard across American Samoa and the adjacent South Pacific islands varies significantly.

Spectral acceleration hazard for 1 Hz, having a 2-percent probability of exceedance on a firm rock site, 

condition (Vs30=760 m/s) is 0.12 g (1 Hz) and 0.32 g (5 Hz) at a site on American Samoa, 0.72 g 

(1 Hz) and 2.5 g (5 Hz) at a site on Tonga, 0.15 g (1 Hz) and 0.55 g (5 Hz) at a site on Fiji, and 0.89 g 

(1 Hz) and 2.8 g (5 Hz) at a site on the Vanuatu Islands. If the site is located on something other than

firm rock, it is important to amplify the hazard by a factor consistent with the soil or rock located at the 

site. The NEHRP has developed factors for this purpose (for example, Petersen and others, 2008). We 

recommend that more detailed, site-specific studies be completed for important structures. 

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20

Acknowledgments

We thank Antonio Villisenor, Gavin Hayes, Emile Okale, George Choy, Art Frankel, and Kevin 

Furlong, for constructive discussions. We also thank Art Frankel and Morgan Moschetti for thoughtful 

reviews of the manuscript. This work was done to support the NEHRP Recommended Provisions for 

Seismic Regulations building codes for American Samoa.
21

Figure 1. Map showing faults and large earthquakes M ≥ 7 since 1900, depth contours of subducing slab 

(Hayes and others, 2011) and plate tectonic features and slip rates (from Pelletier and others,1998; and Bird, 

2003). (h, depth of the earthquake in kilometers; cm/yr, centimeters per year) 
22

Figure 2. Map showing M ≥ 5 earthquakes since 1964, color-coded by depth and cross sections across 

the Tonga and New Hebrides (Vanuatu) subducting slabs. (h, depth of the earthquake in kilometers) 
23

Figure 3. Focal mechanisms from Global Centroid-Moment Tensor Project (http://www.globalcmt.org/) 

Bathymetry from GMT (Wessel and Smith, 2004). (km, kilometers) 
24

Figure 4. Magnitude-frequency plot showing annual rates of earthquakes in the catalog we developed in this 

paper for the time periods of 1900–2010 and 1964–2010. We use the full catalog of earthquakes and decluster the 

catalog to remove dependent events (not declustered). 

0.001

0.01

0.1

1

10

100

1000

4 5 6 7 8 9

Annual rate of earthquakes

Magnitude

Comparison of rates of Samoa/Vanuatu 

catalogs (1900-2010) 

rate all -declustered

rate all not declustered

rate 1964+ declustered

Rate 1964+ not declustered
25

Figure 5. Magnitude-frequency plot showing cumulative number of earthquakes exceeding each magnitude for 

different depth levels (coded by color).

1

10

100

1000

5.25 5.75 6.25 6.75 7.25 7.75 8.25

N 

Magnitude

b-Values Background Background

(elsewhere)

0-50 (b=1.01)

Background

50-100 (b=0.93)

Background

100-200 (b=0.89)

Background

200-300 (b=0.95)

Background

300-400 (b=0.97)

Background

400-500 (b=1.16)

Background

500-600 (b=0.87)

Background

600-723 (b=0.87)
26

Figure 6. Magnitude-frequency distribution for the primary shallow-source models (0–50 km depth) showing the 

cumulative number of earthquakes exceeding each magnitude. (km, kilometers) 

1

10

100

1000

5.25 5.75 6.25 6.75 7.25 7.75 8.25

N 

Magnitude

b-Values

0-50 km

Tonga Outer Rise

0-50 (b=0.99)

New Hebrides

Outer Rise

0-50 (b=1.11)

Tonga subduction

0-50 (b=0.87)

New Hebrides

subduction

0-50 (b=0.58)

Fiji zone

0-50 (b=0.86)

Background

(elsewhere)

0-50 (b=1.01)
27

Figure 7. Magnitude-frequency plot for New Hebrides region showing fits to the observed data for M ≥7 events 

since 1900.

1.0

10.0

100.0

6.5 7.0 7.5 8.0 8.5 9.0

log cumulative number of earthquakes

Magnitude

New Hebrides (Vanuatu) M>7 since 1900, M7+, 32 events

Observed - New

Hebrides

predicted - New

Hebrides, b=0.58

predicted - New

Hebrides, b=0.87

predicted - New

Hebrides, b=1
28

Figure 8. Magnitude-frequency plot showing the fit to the observed Tonga earthquake data M > 7 since 1900.

1

10

100

6.5 7 7.5 8 8.5 9

log number of earthquakes

Magnitude

Tonga M>7 since 1900, b=0.87, M7+ 22 events

Observed-Tonga

predicted-Tonga
29

 

Figure 9. Map showing location of sources used in constructing the seismic hazard maps. (km, kilometers, h, 

depth of the earthquake in kilometers) 
30

Figure 10. Plot showing four 1-Hertz Spectral acceleration (SA) ground motion prediction equations for M 6.5 and 

M 7.5 earthquakes on the A interface and the B intraplate sources. (GMPE, Ground Motion Prediction Equation; 

km, kilometers; m/s, meters per second; Vs30, shear wave velocity in the upper 30 meters) 
31

Figure 11. Plot showing four 5 Hz Spectral acceleration (SA) ground motion prediction equations for M 6.5 and M 

7.5 earthquakes on the A interface and the B intraplate sources. (GMPE, Ground Motion Prediction Equation; km, 

kilometers; m/s, meters per second; Vs30, shear wave velocity in the upper 30 meters) 
32

Figure 12. Comparison of the Atkinson and Boore (2003) global, Youngs and others (1997), and Zhao and others

(2006) intraplate 5-Hertz (Hz) (lower plot) and interface 1-Hz (upper plot) spectral accelerations. (GMPE, Ground 

Motion Prediction Equation; km, kilometers; m/s, meters per second; Vs30, shear wave velocity in the upper 30 

meters) 
33

Figure 13. Plot showing three Spectral acceleration ground motion prediction equations (A. 1 Hertz (Hz), B. 5 Hz) 

for an M 7.5 intraplate earthquake as a function of depth. (km, kilometers; the vertical axis shows the median 

spectral acceleration for period (T) of 1.o and 0.2 seconds) 
34

Figure 14. Ground motion prediction equations showing spectral acceleration at 1 second (sec) (1 Hertz (Hz)) and 

0.2 s (5 Hz) spectral acceleration for distances up to 200 km for the Zhao crustal equations, Zhao intraplate, and 

NGA- Boore and Atkinson (2008) crustal models. (km, kilometers) 
35

Figure 15. Ground motion prediction equations showing spectral acceleration at 1 second (sec) (1 Hertz (Hz)) and 

0.2 s (5 Hz) spectral acceleration for distances up to 200 km for the Zhao crustal equations, Zhao intraplate, and 

NGA- Boore and Atkinson (2008) crustal models. (km, kilometers). The Zhao et al. GMPE represents the Zhao and 

others (2006) Ground motion prediction equation discussed in the text. 
36

Figure 16. Map showing earthquakes M > 6 and recording stations used in determining weights applied for the 

ground motion prediction equations. (km, kilometers) 
37

A 

 Zhao and others 1 Hertz spectral acceleration

 Depth=30 km, Vs30 600 m/s 

B

Figure 17. Graph showing the Zhao and others 2006 intraslab ground motion model with Pacific strong motion 

data for A, 1 Hz Spectral acceleration (SA) and B, Peak horizontal ground acceleration (PGA). (GDSN, Global 

Digital Seismic Network; km, kilometers; m/s, meters per second). The Zhao et al. model represents the Zhao and 

others (2006) ground motion prediction equation.
38

Figure 18. Magnitude distribution versus A distance and B depth. Red circles represent interface events and blue 

squares represent intraslab events. (km, kilometers) 

A B
39

Figure 19. Peak horizontal Ground Acceleration (PGA) residuals at each station in natural log units. Station 

Numbers: 1 is ADK, 2 is AFI, 3 is DAV, 4 is GUMO, 5 is HNR, 6 is PET, 7 is RAO, and 8 is TATO. A, average 

total residual for each station; B, station term obtained by computing approximate mean residual between 

ground-motion data and GMPE at a given station; C, average single station residual at each station, obtained 

by subtracting the station term and systematic offset C1 from the total residual. (km, kilometers) 

A B

C
40

 

Figure 20. Five Hertz residuals at each strong motion station based on natural log units. Station numbers are as 

follows: 1 is ADK, 2 is AFI, 3 is DAV, 4 is GUMO, 5 is HNR, 6 is PET, 7 is RAO, and 8 is TATO. A, average total 

residual for each station; B, station term obtained by computing approximate mean residual between groundmotion data and GMPE at a given station; C, average single station residual at each station, obtained by 

subtracting the station term and systematic offset C1 from the total residual.

A B

C
41

 

Figure 21. One Hertz residuals at each station based on natural log units. Station numbers are as follows: 1 is 

ADK, 2 is AFI, 3 is DAV, 4 is GUMO, 5 is HNR, 6 is PET, 7 is RAO, and 8 is TATO. A, average total residual for 

each station; B, station term obtained by computing approximate mean residual between ground-motion data and 

GMPE at a given station; C, average single station residual at each station, obtained by subtracting the station term 

and systematic offset C1 from the total residual.

A B

C
42

 

Figure 22. A, correlated residual Peak horizontal ground acceleration(PGA) versus moment magnitude; B,

uncorrelated or single station residual PGA versus moment magnitude; C, uncorrelated or single station residual 

5 Hertz (Hz) versus moment magnitude; D, uncorrelated or single station residual 1Hz versus moment magnitude. 

A B

C D
43

Figure 23. Average single station residuals versus moment magnitude for A, peak horizontal ground acceleration 

(PGA); B, 5Hz; and C, 1 Hz spectral acceleration (SA). 

A B

C
44

Figure 24. Single station residuals as a function of distance for A, peak horizontal ground acceleration (PGA) 

and average single station residuals versus distance for B, PGA; C, 5 Hz; and D, 1 Hz spectral acceleration (SA). 

(km, kilometer) 

A B

C D
45

Figure 25. Logic tree for subduction-fault 

sources. Parameters in this table include some 

aleatory variability as well as depicted epistemic 

uncertainty. We treat aleatory variability in ground 

motion in the hazard code. The historic seismicity 

defines the Gutenberg- Richter magnitudefrequency distribution. NGA represents the Next 

Generation Attenuation Relations of Chiou and 

Youngs (2008), Campbell and Bozorgnia (2008), 

and Atkinson and Boore (2008). Each of the 

equations is weighted equally. In zones that 

include subduction zones, we use 30 percent

strike-slip and 70 percent reverse in the groundmotion models. In all other zones, we use half 

strike-slip and half normal faulting mechanisms in 

the ground-motion models, based on the moment 

tensors shown in figures 3 and 24. (km, kilometers; 

ss, strike-slip mechanism; rev, reverse mechanism; 

nor, normal mechanism) 
46

Figure 26. Seismic hazard contributed by the Tonga and New Hebrides subduction zones 1 Hertz spectral 

acceleration for 2 percent probability of exceedance in 50 years on a uniform firm rock site condition. Focal 

mechanisms derived for M≥7. Many of mechanisms correspond to non-subduction processes or intraslab

processes. (Hz, hertz; SA, spectral acceleration; g, acceleration of gravity; km, kilometers ) 
47

Figure 27. Background hazard maps for 5 Hertz Spectral Acceleration 2 percent probability of exceedance in 

50 years on firm rock site condition for earthquake sources with depths A, 0–50 kilometers (km); B, 50–100 km; 

C, 100–200 km; D, 200–750 km. 
48

Figure 28. Background hazard maps for 1 Hertz Spectral Acceleration 2 percent probability of exceedance in 

50 years on firm rock site condition for earthquake sources with depths A, 0–50 kilometers (km); B, 50–100 km; 

C, 100–200 km; and D, 200–750 km. 
49

Figure 29. Hazard map with all sources for 1-second Spectral Acceleration 10 percent probability of 

exceedance in 50 years on firm rock site condition. (%g, percent of the acceleration of gravity; km, kilometer) 
50

 

Figure 30. Hazard map with all sources for 1-Hertz Spectral Acceleration 2-percent probability of exceedance 

in 50 years on firm rock site condition. (%g, percent of the acceleration of gravity; km, kilometer) 
51

 

Figure 31. Hazard map with all sources for 5-Hertz Spectral Acceleration 10 percent probability of exceedance 

in 50 years on firm rock site condition. (%g, percent of the acceleration of gravity; km, kilometer) 
52

Figure 32. Hazard map with all sources for 5-Hertz Spectral Acceleration 2 percent probability of exceedance 

in 50 years on firm rock site condition. (%g, percent of the acceleration of gravity; km, kilometer) 
53

 

Figure 33. Hazard map with all sources for Peak Horizontal Ground Acceleration with a 10 percent probability 

of exceedance in 50 years on firm rock site condition. (%g, percent of the acceleration of gravity; km, kilometer) 
54

Figure 34. Hazard map with all sources for Peak Horizontal Ground Acceleration with a 2 percent probability 

of exceedance in 50 years on firm rock site condition. (%g, percent of the acceleration of gravity; km, kilometer) 
55

A 

B 
56

C 

D
57

E 

Figure 35. Deaggregation plots of a site at Pago Pago, American Samoa for 1 second (sec) (1 Hertz (Hz)) and 

0.2 s (5 Hz) spectral accelerations. A, Plot of percent contribution to hazard and mean return time in years, showing 

the relative contribution to the overall hazard for different return times. The area between the curves represents the 

contribution of that source to the overall hazard for 1 s and 0.2 s spectral accelerations at Pago Pago. B, Plot 1 s

(1 Hz) showing the magnitudes, distances, and epsilons for 2 percent probability of exceedance in 50 years that 

contribute most to the hazard. C, Plot 0.2 s (5 Hz) showing the magnitudes, distances, and epsilons for 2 percent

probability of exceedance in 50 years that contribute most to the hazard. D, Geographic deaggregations that show 

the contributions of earthquake sources on a map to the1 s (1 Hz) overall hazard. E, Geographic deaggregations 

that show the contributions of earthquake sources on a map to the 0.2 s (5 Hz) overall hazard. (km, kilometers; 

SA, Spectral Acceleration; sec, seconds; g, acceleration of gravity; Mw or M, Moment magnitude;) 
58

A 

B 
59

C 

D 
60

E 

Figure 36. Deaggregation plots of a site at Nuku`alofa, Tonga for 1 second (sec) (1 Hertz (Hz)) and 0.2 s (5 Hz) 

spectral accelerations. A, Plot of percent contribution to hazard and mean return time in years showing the relative 

contribution to the overall hazard for different return times. The area between the curves represents the contribution 

of that source to the overall hazard for 1 and 0.2 s spectral accelerations at Pago Pago. B, Plot 1 second (1 Hz) 

showing the magnitudes, distances, and epsilons for 2 percent probability of exceedance in 50 years that contribute 

most to the hazard. C, Plot 0.2 s (5 Hz) showing the magnitudes, distances, and epsilons for 2-percent probability 

of exceedance in 50 years that contribute most to the hazard. D, Geographic deaggregations that show the 

contributions of earthquake sources on a map to the 1-s (1 Hz) overall hazard. E, Geographic deaggregations that 

show the contributions of earthquake sources on a map to the 0.2-s (5 Hz) overall hazard. (km, kilometers; SA, 

spectral acceleration; sec, seconds; g, define here; M and Mw, both represent moment magnitude) 
61

A 

B 
62

C 

D 
63

E 

Figure 37. Deaggregation plots of a site at Suva, Fiji for 1 second (sec) (1 Hertz (Hz)) and 0.2 s (5 Hz) spectral 

accelerations. A, Plot of percent contribution to hazard and mean return time in years showing the relative 

contribution to the overall hazard for different return times. The area between the curves represents the contribution 

of that source to the overall hazard for 1 and 0.2 s spectral accelerations at Pago Pago. B, Plot 1 second (1 Hz) 

showing the magnitudes, distances, and epsilons for 2 percent probability of exceedance in 50 years that contribute 

most to the hazard. C, Plot 0.2 s (5 Hz) showing the magnitudes, distances, and epsilons for 2 percent probability 

of exceedance in 50 years that contribute most to the hazard. D, Geographic deaggregations that show the 

contributions of earthquake sources on a map to the1-s (1 Hz) overall hazard. E, Geographic deaggregations that 

show the contributions of earthquake sources on a map to the 0.2-s (5 Hz) overall hazard. (km, kilometers; SA, 

spectral acceleration; sec, seconds; g, acceleration of gravity; Mw, and M, represent moment magnitude) 
64

A 

B 
65

C 

D 
66

E 

Figure 38. Deaggregation plots of a site at Port Vila, Vanuatu for 1 second (sec) (1 Hertz (Hz)) and 0.2 s (5 Hz) 

spectral accelerations. A, Plot of percent contribution to hazard and mean return time in years showing the relative 

contribution to the overall hazard for different return times. The area between the curves represents the contribution 

of that source to the overall hazard for 1 and 0.2 s spectral accelerations at Pago Pago. B, Plot 1 second (1 Hz) 

showing the magnitudes, distances, and epsilons for 2 percent probability of exceedance in 50 years that contribute 

most to the hazard. C, Plot 0.2 s (5 Hz) showing the magnitudes, distances, and epsilons for 2 percent probability 

of exceedance in 50 years that contribute most to the hazard. D, Geographic deaggregations that show the 

contributions of earthquake sources on a map to the1 s (1 Hz) overall hazard. E, Geographic deaggregations that 

show the contributions of earthquake sources on a map to the 0.2 s (5 Hz) overall hazard. (km, kilometers; SA, 

spectral acceleration; g, acceleration of gravity; Mw, and M, represent moment magnitude)
67

Table 1. b-values, maximum magnitudes, and rates of earthquakes applied in the hazard model. (NGA, Next Generation Attenuation Relations of 

Chiou and Youngs (2008), Campbell and Bozorgnia (2008), and Atkinson and Boore (2008); km, kilometers) 

Source Model (depth) Calculated

b-value

b-value

standard 

deviation

Maximum 

recorded

magnitude 

since 1900

Maximum 

recorded 

magnitude

since 1964

Maximum 

magnitude 

for 

calculations

Rate of M≥7 

since 1900

Type of 

source

S=smooth

F=fault

Model source

depth (km)

Ground motion 

models

Tonga Outer Rise (0–50 km) 0.99 0.07 8.2 8.1 (8.0*) 8.2 S 10 Crustal Zhao and 

NGA 

New Hebrides Outer Rise (0–50 km) 1.11 0.10 7.7 7.7 8.2 S 10 Crustal Zhao and 

NGA

Tonga Subduction Zone interface 

(0–50 km)

0.87 0.03 8.5 7.9 (8.0*) 7.0 (see 

interface 

zone 

below)

S 10 Crustal Zhao and 

NGA

New Hebrides Subduction Zone Interface 

(0–50 km)

0.58 0.04 7.9 7.8 7.0 (see 

interface 

zone 

below)

S 10 Crustal Zhao and 

NGA

Fiji zone (0–50 km) 0.86 0.03 7.8 7.7 8.0 S 10 Crustal Zhao and 

NGA

Background (elsewhere; 0–50 km) 1.01 0.07 7.1 7.1 7.3 S 10 Crustal Zhao and 

NGA

Background (50–100 km) 0.93 0.05 8.2 8.1 8.2 S 75 Intraslab

Background (100–200 km) 0.89 0.04 7.8 7.8 8.0 S 150 Intraslab

Background (200–300 km) 0.95 0.05 7.9 7.1 8.0 S 250 Intraslab

Background (300–400 km) 0.97 0.07 8.0 7.2 8.0 S 350 Intraslab

Background (400–500 km) 1.16 0.09 7.5 7.3 8.0 S 450 Intraslab

Background (500–600 km) 0.87 0.05 7.8 7.6 8.0 S 550 Intraslab

Background (600–723 km) 0.87 0.07 7.7 7.7 8.0 S 650 Intraslab

Tonga Subduction Zone Interface 

(0–50 km)

M7–M9, 1900–2010

0.87

(fixed)**

8.5 7.9 

(8.0(fixed)*)

8.5, 9.0 22 events 

/ 110 

years

F H=25, top 

of zone is 

10 km

Inter-face

New Hebrides Subduction Zone Interface 

(0–50 km)

M7–M9, 1900–2010

1.0

(fixed)**

7.9 7.8 8.5, 9.0 32 events 

/ 110 

years

F H=25, top 

of zone is 

10 km

Inter-face
68

Table 2. Earthquake and station information. 

Earthquake origin 

time

Magnitude Latitude Longitude Strike Depth Distance

1

Distance

2

Slab 

(1=yes)

Station Weight

19960819041916 6.0 51.45 181.63 80 33 131.2 127.3 1 ADK. 0.4203

19990918212833 6.0 51.21 157.56 50 60 224.3 220.7 1 PET. .3193

19991219004836 6.0 12.87 144.57 0 50 99.3 97.4 1 GUMO .4806

20010201181930 6.0 51.44 182.2 80 33 97.1 94.6 1 ADK. .4876

20021016141312 6.0 -15.68 186.95 12 33 241.8 239.4 1 AFI. .3066

20030610084030 6.0 23.52 121.63 20 44 167.4 165.5 1 TATO .3687

20040414013305 6.0 -17.85 185.44 12 143 548.1 546.1 1 AFI. .203

20060430193318 6.0 -15.52 186.9 12 10 228.6 226.4 1 AFI. .3153

20060707072612 6.0 -15.24 186.39 12 35 248.7 246.9 1 AFI. .3019

20080728214047 6.0 -10.58 163.1 -60 10 368.9 365.1 1 HNR. .2483

20090929175605 6.0 -15.35 186.84 12 10 218.6 216.4 1 AFI. .3225

20090929234503 6.0 -15.83 187.45 12 10 228.6 226.5 1 AFI. .3152

20091019224938 6.0 -15.36 187.74 12 18 170.3 167.6 1 AFI. .3664

20091128092117 6.0 -29.22 182.98 12 28 93.4 92 1 RAO. .4946

20100209010344 6.0 -15.05 186.51 12 10 224.1 222 1 AFI. .3184

20100804044620 6.0 -26.92 182.76 12 18 266.9 264.9 1 RAO. .2914

19980914231646 6.1 51.62 186.85 80 33 248.4 244 1 ADK. .3087

20020128135028 6.1 49.38 155.59 50 33 460.2 455.8 1 PET. .2259

20021126004815 6.1 51.47 186.46 80 20 223.7 219.4 1 ADK. .3256

20050117105032 6.1 10.99 140.68 0 12 539.3 537.4 1 GUMO .208

20050604145046 6.1 -6.32 146.85 75 26 344.1 345.2 1 PMG. .2596

20060401100219 6.1 22.87 121.28 20 9 234.1 231.8 1 TATO .3167

20070402104917 6.1 -7.22 156.24 -60 34 478 474.5 1 HNR. .2214

20070826123731 6.1 -17.46 185.66 12 127 496.6 494.2 1 AFI. .2169

20071006123849 6.1 18.73 147.15 0 20 619.7 618.6 1 GUMO .1939

20080819163013 6.1 -15.09 186.52 12 8 225.2 223.1 1 AFI. .3229

20081102134842 6.1 51.55 185.63 80 36 168.8 164.5 1 ADK. .376

20081121070534 6.1 -8.95 159.55 -60 118 136.7 135.5 1 HNR. .4143

20090817101056 6.1 23.43 123.52 20 15 267.8 266.7 1 TATO .2953

20091002010739 6.1 -16.33 186.53 12 8 324.3 321.7 1 AFI. .2689

20091003173606 6.1 23.63 121.45 20 28 151.9 148.9 1 TATO .3952

20091128181020 6.1 5.33 126.29 -15 38 211.8 208.9 1 DAV. .3337

20100213023428 6.1 -21.9 185.23 12 11 874.6 872.6 1 RAO. .1633

20100421172029 6.1 -15.27 186.78 12 35 218.9 216.8 1 AFI. .3275

20100624053227 6.1 -5.51 151.16 75 40 618.5 616.4 1 PMG. .1942

20101123090106 6.1 -5.96 148.97 75 68 435.3 434.9 1 PMG. .2312

19961203125656 6.2 -18.35 187.73 12 32 495.6 493.6 1 AFI. .2206

20000421043517 6.2 51.42 181.86 80 33 118.3 113.9 1 ADK. .4593
69

Table 2. Earthquake and station information.—Continued

Earthquake origin 

time

Magnitude Latitude Longitude Strike Depth Distance

1

Distance

2

Slab 

(1=yes)

Station Weight

20001219131147 6.2 11.77 144.76 0 33 204.3 201.3 1 GUMO .3454

20011002004818 6.2 -16.18 186.18 12 106 350.6 347.5 1 AFI. .2629

20030317185547 6.2 51.29 177.97 80 33 379.1 372.5 1 ADK. .254

20030328173147 6.2 -15.32 186.49 12 41 247.4 244 1 AFI. .3138

20030503050303 6.2 -15.14 186.25 12 33 255 252 1 AFI. .3088

20031007045528 6.2 -16.53 189.81 12 10 336.6 334.7 1 AFI. .2679

20040519070411 6.2 22.66 121.5 20 20 257 254.3 1 TATO .3074

20040903190447 6.2 -15.25 186.66 12 10 225.2 221.7 1 AFI. .3292

20050518102706 6.2 -15.32 186.76 12 10 221.9 219.1 1 AFI. .3312

20070402120223 6.2 -8.71 157.62 -60 14 268.8 264.5 1 HNR. .3014

20070402232023 6.2 -8.62 157.39 -60 18 295.8 291.9 1 HNR. .2869

20070906175126 6.2 24.34 122.22 20 53 114.4 113.1 1 TATO .4609

20080603162050 6.2 -10.51 161.27 -60 84 205.1 201.9 1 HNR. .345

20100109055130 6.2 -9.13 157.63 -60 12 257.6 253.2 1 HNR. .308

19950116181449 6.3 51.26 179.17 80 33 298.2 291.9 1 ADK. .2915

20000126132650 6.3 -17.27 186 12 33 443.5 439.9 1 AFI. .2375

20010802234106 6.3 56.26 163.79 50 14 491.5 484 1 PET. .2264

20031022114530 6.3 -6.06 147.73 75 53 379.1 379 1 PMG. .2558

20040109223531 6.3 -6.07 149.4 75 57 448.1 445.6 1 PMG. .236

20050202023025 6.3 14.08 144.71 0 158 167.9 166.5 1 GUMO .3859

20060214152723 6.3 20.82 146.18 0 40 814.2 812.3 1 GUMO .1748

20100207061000 6.3 23.49 123.61 20 21 271.5 269.8 1 TATO .3032

20100304001851 6.3 22.92 120.79 20 21 239.3 235.6 1 TATO .3245

20100710114332 6.3 11.14 146 0 13 297.7 294.8 1 GUMO .2901

20101004132838 6.3 24.27 125.15 20 32 380.1 378.2 1 TATO .2561

19991207212949 6.4 -15.91 186.02 12 137 351.9 348.3 1 AFI. .2711

20030314125412 6.4 -17.42 184.82 12 274 599.8 595.9 1 AFI. .2073

20030902182800 6.4 -15.23 186.78 12 10 214.1 209.4 1 AFI. .3497

20050122203017 6.4 -7.73 159.48 -60 29 198.2 195.1 1 HNR. .3623

20051015155108 6.4 25.31 123.35 20 192 270.5 268.3 1 TATO .3089

20070404063435 6.4 -7.76 156.49 -60 17 423.7 418.2 1 HNR. .2474

20090118141148 6.4 -30.2 182.05 12 33 110.9 106 1 RAO. .4915

20091219130217 6.4 23.8 121.61 20 57 142.3 138.2 1 TATO .4304

19960608231915 6.5 51.49 181.87 80 33 114.1 107.6 1 ADK. .4954

20010703131042 6.5 21.64 142.98 0 290 959.5 955.9 1 GUMO .1662

20020814135752 6.5 14.1 146.2 0 30 157.7 155.2 1 GUMO .4125

20070816083928 6.5 -9.83 159.46 -60 15 70.7 68.5 1 HNR. .6209

20090516005351 6.5 -31.55 181.17 12 43 274.1 267.4 1 RAO. .3143
70

Table 2. Earthquake and station information.—Continued

Earthquake origin 

time

Magnitude Latitude Longitude Strike Depth Distance

1

Distance

2

Slab 

(1=yes)

Station Weight

20100426025951 6.5 22.18 123.63 20 14 379 375.6 1 TATO .2652

19971217043851 6.6 51.19 178.87 80 20 319.2 309.8 1 ADK. .2964

19990128081005 6.6 52.89 190.88 80 67 532.3 521.7 1 ADK. .2284

20021107151406 6.6 51.2 179.33 80 33 289.3 280.1 1 ADK. .3118

20031125201946 6.6 -5.58 150.88 75 35 591.5 585.2 1 PMG. .2157

20050116201752 6.6 10.93 140.84 0 24 528.6 524.4 1 GUMO .2279

20050205033425 6.6 16.01 145.87 0 142 321.6 316.3 1 GUMO .2934

20070130213744 6.6 20.98 144.71 0 20 819 814.4 1 GUMO .1828

20071127114958 6.6 -10.95 162.15 -60 16 294.5 286.5 1 HNR. .3083

20080719092701 6.6 -11.04 164.49 -60 11 529.3 520.4 1 HNR. .2287

20090830145132 6.6 -15.22 187.43 12 11 168.6 161.9 1 AFI. .4101

20100103214805 6.6 -8.74 157.48 -60 26 283 275.5 1 HNR. .3144

20040125114311 6.7 -16.83 185.8 12 129 435.1 427.6 1 AFI. .2562

20050208144821 6.7 -14.25 167.26 -16 206 981 973.8 1 HNR. .1697

20100626053019 6.7 -10.63 161.45 -60 35 214.5 205.1 1 HNR. .3698

19960322032420 6.8 51.22 178.7 80 20 330.4 317.3 1 ADK. .3018

20031210043811 6.8 23.04 121.36 20 10 215.2 205.3 1 TATO .3752

20041008082753 6.8 -10.95 162.16 -60 36 297.4 286.2 1 HNR. .3178

20080509215129 6.8 12.52 143.18 0 76 231.2 225.6 1 GUMO .3579

20081209062359 6.8 -31.23 183.08 12 18 241.3 233 1 RAO. .3522

20091124124715 6.8 -20.71 185.96 12 18 791.1 782.8 1 AFI. .1921

20091124124716 6.8 -20.71 185.96 12 18 785.6 782.8 1 AFI. .1921

20100105121532 6.8 -9.02 157.55 -60 15 267.8 257.5 1 HNR. .335

20100411094025 6.8 -10.88 161.12 -60 21 206 196.3 1 HNR. .3837

20060928062209 6.9 -16.59 187.97 12 28 299.9 287.9 1 AFI. .3215

20061226123413 6.9 21.97 120.49 20 10 348.8 336.7 1 TATO .2973

20070930020830 6.9 10.45 145.72 0 14 360.1 349 1 GUMO .292

20080908185206 6.9 -13.5 166.97 -16 110 895.8 886.1 1 HNR. .1832

20100718130409 6.9 -5.97 150.43 75 28 525.4 515 1 PMG. .2404

20011012150216 7.0 12.69 144.98 0 37 106.9 93.3 0 GUMO .5728

20090218215345 7.0 -27.42 183.67 12 25 257.4 243.9 1 RAO. .3543

20020426160607 7.1 13.09 144.62 0 85 104.8 96.8 1 GUMO .5706

20030317163617 7.1 51.27 177.98 80 33 379.1 358.5 0 ADK. .2964

20100103223627 7.1 -8.8 157.35 -60 25 295.2 277.8 0 HNR. .3367

20000108164720 7.2 -16.92 185.75 12 183 464.3 447.4 1 AFI. .2691

20071031033015 7.2 18.9 145.39 0 207 625.7 608.4 1 GUMO .2308

20071219093027 7.2 51.36 180.49 80 34 207.8 185.8 0 ADK. .4176

19960610152456 7.3 51.48 183.15 80 26 53.5 49.5 0 ADK. .8205
71

Table 2. Earthquake and station information.—Continued

Earthquake origin 

time

Magnitude Latitude Longitude Strike Depth Distance

1

Distance

2

Slab 

(1=yes)

Station Weight

20100718133459 7.3 -5.93 150.59 75 35 541.4 520.4 0 PMG. .253

20070928133857 7.5 22.01 142.67 0 260 995.9 966.8 1 GUMO .1907

20090319181740 7.6 -23.04 185.34 12 31 762.6 723.9 1 RAO. .2233

20091007220314 7.7 -13.01 166.51 -16 45 820 786.7 0 HNR. .217

20031117064306 7.8 51.15 178.65 80 33 336.9 278.2 1 ADK. .3697

19960610040335 7.9 51.56 182.37 80 33 81.6 41.2 0 ADK. .9735

20060503152640 8.0 -20.19 185.88 12 55 741.7 665.1 1 AFI. .2452

20070401203958 8.1 -8.47 157.04 -60 24 338.4 246.8 0 HNR. .4076

20090929174810 8.0 -15.49 187.9 12 18 179.1 101.3 1 AFI. .6284
72

Table 3. 1-second spectral acceleration. 

Earthquake origin time Observed AB-Cascadia AB-Global Geomatrix Zhao and others

(2006)

19960819041916 5.40E-03 3.60E-03 3.27E-03 1.24E-02 4.72E-03

19990918212833 1.58E-03 1.04E-03 9.41E-04 5.28E-03 2.21E-03

19991219004836 1.29E-02 6.79E-03 6.17E-03 1.81E-02 8.93E-03

20010201181930 1.24E-02 6.86E-03 6.24E-03 1.88E-02 7.91E-03

20021016141312 2.32E-03 7.70E-04 7.00E-04 4.61E-03 1.43E-03

20030610084030 5.02E-03 2.03E-03 1.84E-03 8.37E-03 3.27E-03

20040414013305 3.33E-03 7.51E-05 6.83E-05 1.07E-03 5.31E-04

20060430193318 7.49E-04 8.34E-04 7.58E-04 5.06E-03 1.27E-03

20060707072612 2.29E-03 7.12E-04 6.48E-04 4.38E-03 1.37E-03

20080728214047 2.39E-04 2.09E-04 1.90E-04 2.23E-03 4.56E-04

20090929175605 1.37E-03 9.39E-04 8.54E-04 5.45E-03 1.39E-03

20090929234503 1.03E-03 8.33E-04 7.57E-04 5.05E-03 1.27E-03

20091019224938 4.17E-03 1.82E-03 1.66E-03 8.21E-03 2.46E-03

20091128092117 1.15E-02 7.18E-03 6.52E-03 1.95E-02 7.89E-03

20100209010344 8.22E-04 8.78E-04 7.99E-04 5.23E-03 1.32E-03

20100804044620 4.65E-03 5.57E-04 5.07E-04 3.89E-03 9.99E-04

19980914231646 6.20E-04 9.14E-04 8.31E-04 5.20E-03 1.61E-03

20020128135028 7.16E-04 1.33E-04 1.21E-04 1.76E-03 3.94E-04

20021126004815 1.73E-03 1.17E-03 1.06E-03 6.20E-03 1.75E-03

20050117105032 1.30E-04 6.78E-05 6.16E-05 1.30E-03 2.08E-04

20050604145046 8.18E-04 3.28E-04 2.98E-04 2.88E-03 7.12E-04

20060401100219 4.46E-03 9.77E-04 8.88E-04 5.66E-03 1.40E-03

20070402104917 5.08E-04 1.15E-04 1.05E-04 1.63E-03 3.59E-04

20070826123731 1.03E-03 1.31E-04 1.19E-04 1.52E-03 8.08E-04

20071006123849 7.38E-04 3.93E-05 3.58E-05 1.00E-03 1.53E-04

20080819163013 1.36E-03 1.08E-03 9.79E-04 6.03E-03 1.50E-03

20081102134842 1.55E-03 2.51E-03 2.28E-03 9.77E-03 3.56E-03

20081121070534 5.63E-03 5.04E-03 4.58E-03 1.31E-02 1.16E-02

20090817101056 4.54E-04 6.78E-04 6.17E-04 4.48E-03 1.12E-03

20091002010739 7.10E-04 3.85E-04 3.50E-04 3.25E-03 6.95E-04

20091003173606 4.91E-03 3.10E-03 2.82E-03 1.14E-02 3.95E-03

20091128181020 2.32E-03 1.40E-03 1.27E-03 6.71E-03 2.30E-03

20100213023428 2.00E-05 7.66E-06 6.96E-06 5.26E-04 4.75E-05

20100421172029 4.44E-03 1.26E-03 1.14E-03 6.32E-03 2.08E-03

20100624053227 3.55E-04 4.24E-05 3.85E-05 1.01E-03 1.88E-04

20101123090106 4.40E-04 1.74E-04 1.58E-04 1.91E-03 6.29E-04

19961203125656 1.55E-03 1.25E-04 1.13E-04 1.78E-03 3.72E-04

20000421043517 4.34E-03 7.16E-03 6.51E-03 1.91E-02 7.82E-03
73

Table 3. 1-second spectral acceleration.—Continued

Earthquake origin time Observed AB-Cascadia AB-Global Geomatrix Zhao and others 

(2006)

20001219131147 2.45E-03 1.89E-03 1.72E-03 8.25E-03 2.75E-03

20011002004818 1.32E-03 5.11E-04 4.65E-04 3.33E-03 1.83E-03

20030317185547 8.09E-04 3.30E-04 3.00E-04 2.95E-03 7.49E-04

20030328173147 7.87E-03 1.17E-03 1.07E-03 6.05E-03 2.04E-03

20030503050303 2.19E-03 1.05E-03 9.53E-04 5.74E-03 1.76E-03

20031007045528 1.30E-03 4.31E-04 3.91E-04 3.55E-03 7.59E-04

20040519070411 1.77E-03 9.84E-04 8.94E-04 5.65E-03 1.51E-03

20040903190447 1.41E-03 1.38E-03 1.25E-03 7.07E-03 1.81E-03

20050518102706 1.10E-03 1.42E-03 1.29E-03 7.21E-03 1.85E-03

20070402120223 4.33E-03 8.66E-04 7.87E-04 5.29E-03 1.31E-03

20070402232023 2.36E-03 6.63E-04 6.03E-04 4.49E-03 1.11E-03

20070906175126 8.51E-03 7.71E-03 7.01E-03 1.93E-02 9.68E-03

20080603162050 6.98E-03 2.19E-03 1.99E-03 8.22E-03 4.57E-03

20100109055130 1.86E-03 9.72E-04 8.83E-04 5.69E-03 1.41E-03

19950116181449 1.43E-03 8.68E-04 7.89E-04 5.22E-03 1.51E-03

20000126132650 6.75E-04 2.37E-04 2.16E-04 2.57E-03 5.88E-04

20010802234106 2.47E-04 1.59E-04 1.45E-04 2.16E-03 3.82E-04

20031022114530 6.13E-04 4.15E-04 3.77E-04 3.34E-03 1.03E-03

20040109223531 2.25E-04 2.44E-04 2.21E-04 2.51E-03 7.25E-04

20050202023025 1.56E-02 5.47E-03 4.97E-03 1.27E-02 1.16E-02

20060214152723 9.80E-05 1.90E-05 1.73E-05 8.35E-04 1.10E-04

20100207061000 1.26E-03 1.05E-03 9.52E-04 5.95E-03 1.58E-03

20100304001851 6.58E-03 1.52E-03 1.38E-03 7.43E-03 2.09E-03

20100710114332 1.39E-03 7.95E-04 7.23E-04 5.13E-03 1.21E-03

20101004132838 3.52E-04 3.92E-04 3.57E-04 3.35E-03 8.37E-04

19991207212949 6.52E-03 8.74E-04 7.94E-04 4.49E-03 3.01E-03

20030314125412 8.54E-04 1.95E-04 1.77E-04 1.74E-03 7.79E-04

20030902182800 4.78E-03 2.49E-03 2.27E-03 1.03E-02 2.76E-03

20050122203017 2.71E-03 3.16E-03 2.87E-03 1.15E-02 3.84E-03

20051015155108 1.20E-03 2.22E-03 2.02E-03 6.96E-03 5.32E-03

20070404063435 3.33E-03 3.37E-04 3.06E-04 3.27E-03 6.63E-04

20090118141148 3.00E-02 1.29E-02 1.18E-02 2.72E-02 1.21E-02

20091219130217 1.58E-02 7.77E-03 7.06E-03 1.91E-02 9.64E-03

19960608231915 1.58E-02 1.56E-02 1.41E-02 3.02E-02 1.38E-02

20010703131042 2.41E-04 2.71E-05 2.46E-05 8.47E-04 2.03E-04

20020814135752 9.44E-03 6.84E-03 6.22E-03 1.85E-02 6.96E-03

20070816083928 1.50E-01 3.66E-02 3.33E-02 5.07E-02 2.44E-02

20090516005351 4.67E-03 1.80E-03 1.63E-03 8.09E-03 2.75E-03

20100426025951 3.94E-03 5.97E-04 5.43E-04 4.59E-03 9.72E-04
74

Table 3. 1-second spectral acceleration.—Continued

Earthquake origin time Observed AB-Cascadia AB-Global Geomatrix Zhao and others 

(2006)

19971217043851 2.29E-03 1.38E-03 1.25E-03 7.34E-03 1.87E-03

19990128081005 1.14E-03 2.79E-04 2.53E-04 3.00E-03 8.58E-04

20021107151406 2.55E-03 1.91E-03 1.74E-03 8.65E-03 2.64E-03

20031125201946 5.12E-04 1.61E-04 1.47E-04 2.45E-03 4.55E-04

20050116201752 4.10E-04 2.40E-04 2.18E-04 2.98E-03 5.50E-04

20050205033425 6.15E-03 1.86E-03 1.69E-03 7.09E-03 5.12E-03

20070130213744 2.38E-04 3.51E-05 3.19E-05 1.34E-03 1.44E-04

20071127114958 4.56E-03 1.71E-03 1.55E-03 8.34E-03 2.12E-03

20080719092701 7.20E-04 2.38E-04 2.16E-04 3.02E-03 4.92E-04

20090830145132 7.42E-03 7.31E-03 6.64E-03 1.99E-02 6.23E-03

20100103214805 2.42E-03 1.96E-03 1.78E-03 8.89E-03 2.55E-03

20040125114311 4.63E-03 8.60E-04 7.82E-04 4.94E-03 2.99E-03

20050208144821 4.77E-04 3.01E-05 2.73E-05 1.12E-03 2.61E-04

20100626053019 3.86E-02 5.51E-03 5.01E-03 1.61E-02 5.93E-03

19960322032420 3.27E-03 2.01E-03 1.82E-03 9.38E-03 2.43E-03

20031210043811 3.45E-03 6.36E-03 5.79E-03 1.83E-02 5.39E-03

20041008082753 1.50E-02 2.84E-03 2.58E-03 1.11E-02 3.57E-03

20080509215129 9.61E-03 6.10E-03 5.54E-03 1.60E-02 8.70E-03

20081209062359 7.57E-03 4.71E-03 4.28E-03 1.52E-02 4.55E-03

20091124124715 7.92E-04 6.69E-05 6.09E-05 1.96E-03 2.21E-04

20091124124716 7.92E-04 6.69E-05 6.09E-05 1.96E-03 2.21E-04

20100105121532 1.20E-02 3.58E-03 3.25E-03 1.31E-02 3.61E-03

20100411094025 8.55E-03 7.35E-03 6.68E-03 1.96E-02 6.56E-03

20060928062209 3.08E-03 3.40E-03 3.09E-03 1.26E-02 3.81E-03

20061226123413 3.56E-03 2.04E-03 1.85E-03 9.78E-03 2.26E-03

20070930020830 4.24E-03 1.85E-03 1.68E-03 9.23E-03 2.17E-03

20080908185206 2.09E-03 5.94E-05 5.40E-05 1.82E-03 4.31E-04

20100718130409 2.21E-03 5.14E-04 4.67E-04 4.80E-03 9.68E-04

20011012150216 1.55E-01 3.86E-02 3.56E-02 4.30E-02 2.68E-02

20090218215345 1.42E-02 6.63E-03 6.03E-03 1.85E-02 6.12E-03

20020426160607 7.81E-02 7.97E-02 7.24E-02 6.68E-02 7.08E-02

20030317163617 1.25E-03 7.66E-03 7.06E-03 7.99E-03 4.63E-03

20100103223627 9.45E-03 1.05E-02 9.70E-03 1.19E-02 7.10E-03

20000108164720 1.41E-02 2.67E-03 2.42E-03 9.29E-03 5.95E-03

20071031033015 1.81E-03 8.98E-04 8.17E-04 5.52E-03 2.64E-03

20071219093027 2.72E-02 2.53E-02 2.33E-02 2.38E-02 1.47E-02

19960610152456 8.74E-02 9.19E-02 8.46E-02 9.62E-02 7.74E-02

20100718133459 1.10E-03 6.15E-03 5.67E-03 5.70E-03 2.93E-03

20070928133857 1.01E-03 2.29E-04 2.08E-04 3.74E-03 9.75E-04
75

Table 3. 1-second spectral acceleration.—Continued

Earthquake origin time Observed AB-Cascadia AB-Global Geomatrix Zhao and others 

(2006)

20090319181740 1.71E-02 6.17E-04 5.61E-04 7.14E-03 1.18E-03

20091007220314 1.69E-03 6.36E-03 5.86E-03 4.88E-03 1.81E-03

20031117064306 5.41E-03 2.68E-02 2.44E-02 4.03E-02 1.83E-02

19960610040335 9.09E-02 1.89E-01 1.74E-01 1.60E-01 1.75E-01

20060503152640 8.89E-03 2.35E-03 2.14E-03 1.40E-02 3.74E-03

20070401203958 1.49E-02 7.53E-02 6.93E-02 4.46E-02 2.93E-02

20090929174810 8.63E-02 2.74E-01 2.49E-01 1.44E-01 1.36E-01
76

Table 4. 5-Hz spectral acceleration

Earthquake origin time Observed AB-Cascadia AB-Global Geomatrix Zhao and 

others

19960819041916 3.59E-02 9.68E-03 1.26E-02 4.10E-02 2.24E-02

19990918212833 7.35E-03 3.52E-03 4.59E-03 1.41E-02 8.58E-03

19991219004836 6.32E-02 2.20E-02 2.87E-02 6.53E-02 4.99E-02

20010201181930 4.79E-02 1.87E-02 2.44E-02 6.85E-02 4.12E-02

20021016141312 6.15E-03 1.97E-03 2.57E-03 1.20E-02 4.58E-03

20030610084030 1.54E-02 6.00E-03 7.83E-03 2.51E-02 1.44E-02

20040414013305 3.42E-03 5.15E-04 6.72E-04 1.95E-03 7.62E-04

20060430193318 8.43E-04 1.70E-03 2.22E-03 1.34E-02 3.85E-03

20060707072612 1.56E-02 1.85E-03 2.42E-03 1.12E-02 4.31E-03

20080728214047 6.65E-04 4.01E-04 5.23E-04 4.84E-03 8.08E-04

20090929175605 3.88E-03 1.92E-03 2.51E-03 1.47E-02 4.37E-03

20090929234503 2.37E-03 1.70E-03 2.21E-03 1.34E-02 3.84E-03

20091019224938 1.45E-02 4.13E-03 5.39E-03 2.45E-02 9.55E-03

20091128092117 7.65E-02 1.86E-02 2.43E-02 7.18E-02 4.04E-02

20100209010344 2.16E-03 1.79E-03 2.34E-03 1.40E-02 4.07E-03

20100804044620 2.02E-02 1.21E-03 1.58E-03 9.67E-03 2.71E-03

19980914231646 1.33E-03 2.24E-03 2.92E-03 1.31E-02 4.85E-03

20020128135028 7.75E-04 2.97E-04 3.87E-04 3.39E-03 5.15E-04

20021126004815 6.06E-03 2.53E-03 3.30E-03 1.62E-02 5.44E-03

20050117105032 3.74E-04 1.18E-04 1.54E-04 2.33E-03 1.77E-04

20050604145046 5.40E-04 7.15E-04 9.33E-04 6.26E-03 1.41E-03

20060401100219 2.44E-03 1.88E-03 2.46E-03 1.45E-02 3.96E-03

20070402104917 4.25E-04 2.58E-04 3.37E-04 3.09E-03 4.38E-04

20070826123731 2.28E-03 7.50E-04 9.79E-04 2.82E-03 1.38E-03

20071006123849 1.64E-03 7.16E-05 9.35E-05 1.69E-03 9.62E-05

20080819163013 1.53E-03 2.06E-03 2.69E-03 1.57E-02 4.35E-03

20081102134842 1.38E-02 6.55E-03 8.55E-03 2.86E-02 1.45E-02

20081121070534 2.93E-02 3.07E-02 4.01E-02 4.10E-02 7.56E-02

20090817101056 9.19E-04 1.37E-03 1.79E-03 1.09E-02 2.84E-03

20091002010739 1.03E-03 7.07E-04 9.23E-04 7.29E-03 1.39E-03

20091003173606 7.79E-03 7.51E-03 9.80E-03 3.45E-02 1.64E-02

20091128181020 2.26E-03 3.65E-03 4.77E-03 1.79E-02 8.10E-03

20100213023428 2.00E-05 1.14E-05 1.49E-05 7.58E-04 9.89E-06

20100421172029 1.25E-02 3.18E-03 4.15E-03 1.66E-02 7.00E-03

20100624053227 3.36E-04 9.46E-05 1.24E-04 1.70E-03 1.31E-04

20101123090106 8.61E-04 5.59E-04 7.30E-04 3.76E-03 1.05E-03

19961203125656 3.90E-03 2.59E-04 3.38E-04 3.25E-03 3.99E-04

20000421043517 4.35E-02 1.78E-02 2.32E-02 6.20E-02 3.54E-02

20001219131147 1.06E-02 4.51E-03 5.89E-03 2.18E-02 9.33E-03
77

Table 4. 5-Hz spectral acceleration.—Continued

Earthquake origin time Observed AB-Cascadia AB-Global Geomatrix Zhao and 

others

20011002004818 3.65E-03 2.41E-03 3.14E-03 7.05E-03 4.96E-03

20030317185547 1.31E-03 7.30E-04 9.53E-04 6.07E-03 1.32E-03

20030328173147 2.01E-02 2.98E-03 3.89E-03 1.48E-02 6.12E-03

20030503050303 1.07E-02 2.45E-03 3.20E-03 1.39E-02 4.94E-03

20031007045528 7.03E-03 7.67E-04 1.00E-03 7.65E-03 1.40E-03

20040519070411 2.25E-03 2.01E-03 2.63E-03 1.36E-02 3.98E-03

20040903190447 2.48E-03 2.58E-03 3.37E-03 1.80E-02 5.12E-03

20050518102706 2.98E-03 2.66E-03 3.48E-03 1.84E-02 5.30E-03

20070402120223 7.21E-03 1.66E-03 2.16E-03 1.26E-02 3.23E-03

20070402232023 3.32E-03 1.31E-03 1.71E-03 1.02E-02 2.50E-03

20070906175126 2.39E-02 2.35E-02 3.06E-02 6.27E-02 4.82E-02

20080603162050 2.15E-02 8.78E-03 1.15E-02 2.17E-02 1.95E-02

20100109055130 4.57E-03 1.83E-03 2.39E-03 1.38E-02 3.59E-03

19950116181449 1.88E-03 1.91E-03 2.49E-03 1.16E-02 3.51E-03

20000126132650 1.69E-03 4.88E-04 6.38E-04 4.82E-03 7.61E-04

20010802234106 2.38E-04 2.65E-04 3.46E-04 3.90E-03 3.78E-04

20031022114530 5.20E-04 1.08E-03 1.41E-03 6.68E-03 1.86E-03

20040109223531 3.49E-04 6.39E-04 8.34E-04 4.69E-03 1.02E-03

20050202023025 7.37E-02 4.53E-02 5.92E-02 3.53E-02 6.53E-02

20060214152723 7.81E-04 3.57E-05 4.67E-05 1.20E-03 3.15E-05

20100207061000 5.48E-03 2.06E-03 2.69E-03 1.37E-02 3.79E-03

20100304001851 3.19E-03 3.02E-03 3.95E-03 1.80E-02 5.70E-03

20100710114332 1.02E-02 1.42E-03 1.86E-03 1.14E-02 2.54E-03

20101004132838 7.49E-04 8.22E-04 1.07E-03 6.71E-03 1.38E-03

19991207212949 8.85E-03 5.17E-03 6.75E-03 9.12E-03 8.28E-03

20030314125412 2.62E-03 4.17E-03 5.44E-03 2.80E-03 7.83E-04

20030902182800 1.69E-02 4.31E-03 5.63E-03 2.57E-02 7.63E-03

20050122203017 2.17E-02 6.66E-03 8.69E-03 2.94E-02 1.22E-02

20051015155108 3.64E-03 2.38E-02 3.11E-02 1.57E-02 2.00E-02

20070404063435 1.22E-03 5.70E-04 7.45E-04 6.16E-03 8.42E-04

20090118141148 2.02E-01 2.95E-02 3.85E-02 8.55E-02 5.19E-02

20091219130217 4.07E-02 2.23E-02 2.92E-02 5.50E-02 4.21E-02

19960608231915 7.19E-02 3.40E-02 4.44E-02 9.21E-02 5.69E-02

20010703131042 2.77E-04 5.59E-04 7.30E-04 1.09E-03 4.36E-05

20020814135752 3.63E-02 1.42E-02 1.86E-02 5.01E-02 2.46E-02

20070816083928 4.51E-01 6.77E-02 8.84E-02 1.75E-01 1.01E-01

20090516005351 2.25E-02 4.05E-03 5.29E-03 1.79E-02 6.90E-03

20100426025951 5.03E-03 9.56E-04 1.25E-03 8.85E-03 1.40E-03
78

Table 4. 5-Hz spectral acceleration.—Continued

Earthquake origin time Observed AB-Cascadia AB-Global Geomatrix Zhao and 

others

19971217043851 3.25E-03 2.31E-03 3.02E-03 1.50E-02 3.48E-03

19990128081005 3.90E-03 6.88E-04 8.98E-04 4.95E-03 8.49E-04

20021107151406 3.72E-03 3.71E-03 4.85E-03 1.84E-02 5.86E-03

20031125201946 5.62E-04 2.80E-04 3.66E-04 3.84E-03 2.99E-04

20050116201752 1.14E-03 3.82E-04 4.99E-04 4.89E-03 4.42E-04

20050205033425 3.47E-02 1.08E-02 1.41E-02 1.44E-02 1.51E-02

20070130213744 2.79E-04 4.73E-05 6.17E-05 1.81E-03 3.39E-05

20071127114958 3.88E-03 2.78E-03 3.62E-03 1.76E-02 4.25E-03

20080719092701 1.02E-03 3.32E-04 4.34E-04 4.98E-03 3.79E-04

20090830145132 1.57E-02 1.19E-02 1.56E-02 5.18E-02 1.92E-02

20100103214805 2.26E-03 3.55E-03 4.64E-03 1.90E-02 5.58E-03

20040125114311 1.16E-02 3.98E-03 5.20E-03 8.69E-03 5.51E-03

20050208144821 8.75E-04 2.40E-04 3.14E-04 1.38E-03 4.94E-05

20100626053019 7.26E-02 1.08E-02 1.41E-02 3.77E-02 1.71E-02

19960322032420 2.35E-03 3.08E-03 4.02E-03 1.83E-02 4.21E-03

20031210043811 6.47E-03 9.27E-03 1.21E-02 4.21E-02 1.36E-02

20041008082753 1.40E-02 5.20E-03 6.79E-03 2.25E-02 7.49E-03

20080509215129 2.03E-02 1.72E-02 2.25E-02 3.54E-02 2.75E-02

20081209062359 8.06E-02 7.35E-03 9.59E-03 3.33E-02 1.07E-02

20091124124715 9.41E-04 8.21E-05 1.07E-04 2.61E-03 5.63E-05

20091124124716 9.41E-04 8.21E-05 1.07E-04 2.61E-03 5.63E-05

20100105121532 1.38E-02 5.36E-03 6.99E-03 2.76E-02 7.66E-03

20100411094025 5.17E-02 1.20E-02 1.57E-02 4.56E-02 1.79E-02

20060928062209 1.46E-02 5.50E-03 7.18E-03 2.50E-02 7.51E-03

20061226123413 4.77E-03 2.68E-03 3.50E-03 1.83E-02 3.40E-03

20070930020830 1.40E-02 2.52E-03 3.29E-03 1.70E-02 3.17E-03

20080908185206 2.22E-03 1.70E-04 2.22E-04 2.26E-03 1.07E-04

20100718130409 2.52E-03 7.51E-04 9.81E-04 7.55E-03 7.73E-04

20011012150216 4.01E-01 7.80E-02 1.03E-01 1.20E-01 9.22E-02

20090218215345 1.00E-01 1.02E-02 1.33E-02 3.83E-02 1.38E-02

20020426160607 2.66E-01 2.29E-01 2.83E-01 1.80E-01 3.29E-01

20030317163617 1.46E-03 5.33E-03 8.54E-03 1.41E-02 5.17E-03

20100103223627 3.31E-03 9.40E-03 1.45E-02 2.31E-02 1.12E-02

20000108164720 2.09E-02 1.71E-02 2.23E-02 1.48E-02 9.38E-03

20071031033015 9.53E-03 6.85E-03 8.95E-03 7.76E-03 2.15E-03

20071219093027 4.91E-02 3.46E-02 4.93E-02 5.21E-02 3.32E-02

19960610152456 7.76E-01 1.93E-01 2.58E-01 2.82E-01 2.68E-01

20100718133459 1.27E-03 2.30E-03 4.13E-03 8.42E-03 1.54E-03

20070928133857 6.80E-04 2.25E-03 2.94E-03 4.15E-03 1.76E-04
79

Table 4. 5-Hz spectral acceleration.—Continued

Earthquake origin time Observed AB-Cascadia AB-Global Geomatrix Zhao and 

others

20090319181740 4.61E-02 6.28E-04 8.21E-04 8.87E-03 3.84E-04

20091007220314 2.23E-03 8.99E-04 1.92E-03 5.79E-03 2.73E-04

20031117064306 6.28E-03 3.10E-02 4.05E-02 6.98E-02 3.65E-02

19960610040335 3.80E-01 3.80E-01 4.95E-01 4.05E-01 4.88E-01

20060503152640 1.11E-02 2.63E-03 3.44E-03 1.72E-02 1.81E-03

20070401203958 8.70E-03 6.91E-02 1.10E-01 7.64E-02 4.14E-02

20090929174810 1.02E-01 2.67E-01 3.49E-01 3.12E-01 4.35E-01
80

Table 5. Peak horizontal ground acceleration. 

Earthquake origin time Observed AB-Cascadia AB-Global Geomatrix Zhao and 

others (2006)

19960819041916 1.17E-02 3.48E-03 5.55E-03 2.01E-02 1.06E-02

19990918212833 2.54E-03 1.75E-03 2.79E-03 7.10E-03 4.00E-03

19991219004836 2.40E-02 9.90E-03 1.58E-02 3.17E-02 2.38E-02

20010201181930 1.52E-02 6.77E-03 1.08E-02 3.33E-02 1.99E-02

20021016141312 4.49E-03 6.90E-04 1.10E-03 6.02E-03 2.18E-03

20030610084030 5.97E-03 2.46E-03 3.93E-03 1.24E-02 6.73E-03

20040414013305 1.58E-03 6.90E-04 1.10E-03 1.02E-03 4.04E-04

20060430193318 5.34E-04 4.44E-04 7.09E-04 6.75E-03 1.84E-03

20060707072612 1.08E-02 6.65E-04 1.06E-03 5.66E-03 2.05E-03

20080728214047 2.50E-04 1.01E-04 1.62E-04 2.49E-03 4.08E-04

20090929175605 3.15E-03 5.03E-04 8.03E-04 7.38E-03 2.09E-03

20090929234503 1.69E-03 4.43E-04 7.07E-04 6.74E-03 1.84E-03

20091019224938 6.40E-03 1.21E-03 1.94E-03 1.22E-02 4.53E-03

20091128092117 2.98E-02 6.33E-03 1.01E-02 3.48E-02 1.96E-02

20100209010344 1.58E-03 4.69E-04 7.49E-04 7.02E-03 1.95E-03

20100804044620 6.29E-03 3.48E-04 5.55E-04 4.89E-03 1.31E-03

19980914231646 4.41E-04 7.83E-04 1.25E-03 6.52E-03 2.29E-03

20020128135028 3.58E-04 9.88E-05 1.58E-04 1.74E-03 2.70E-04

20021126004815 1.51E-03 7.53E-04 1.20E-03 8.07E-03 2.58E-03

20050117105032 1.53E-04 2.94E-05 4.69E-05 1.21E-03 9.84E-05

20050604145046 3.50E-04 2.23E-04 3.56E-04 3.18E-03 6.95E-04

20060401100219 2.14E-03 4.85E-04 7.74E-04 7.23E-03 1.89E-03

20070402104917 1.71E-04 8.67E-05 1.38E-04 1.59E-03 2.31E-04

20070826123731 1.42E-03 8.28E-04 1.32E-03 1.46E-03 7.03E-04

20071006123849 6.50E-04 1.94E-05 3.10E-05 8.82E-04 5.63E-05

20080819163013 8.89E-04 5.26E-04 8.39E-04 7.80E-03 2.08E-03

20081102134842 3.48E-03 2.43E-03 3.87E-03 1.40E-02 6.79E-03

20081121070534 9.89E-03 3.28E-02 5.24E-02 2.00E-02 3.41E-02

20090817101056 3.58E-04 3.78E-04 6.03E-04 5.44E-03 1.37E-03

20091002010739 5.51E-04 1.76E-04 2.81E-04 3.69E-03 6.84E-04

20091003173606 3.34E-03 2.52E-03 4.02E-03 1.69E-02 7.70E-03

20091128181020 9.29E-04 1.37E-03 2.19E-03 8.89E-03 3.80E-03

20100213023428 1.30E-05 2.60E-06 4.14E-06 4.02E-04 7.00E-06

20100421172029 9.68E-03 1.15E-03 1.83E-03 8.26E-03 3.29E-03

20100624053227 1.65E-04 3.32E-05 5.30E-05 8.89E-04 7.60E-05

20101123090106 3.01E-04 2.94E-04 4.68E-04 1.93E-03 5.33E-04

19961203125656 2.79E-03 8.45E-05 1.35E-04 1.66E-03 2.13E-04

20000421043517 1.11E-02 6.40E-03 1.02E-02 2.97E-02 1.68E-02

20001219131147 3.83E-03 1.59E-03 2.54E-03 1.07E-02 4.36E-03
81

Table 5. Peak horizontal ground acceleration.—Continued

Earthquake origin time Observed AB-Cascadia AB-Global Geomatrix Zhao and 

others (2006)

20011002004818 3.85E-03 2.10E-03 3.35E-03 3.54E-03 2.35E-03

20030317185547 5.90E-04 2.48E-04 3.96E-04 3.06E-03 6.55E-04

20030328173147 1.29E-02 1.16E-03 1.84E-03 7.34E-03 2.87E-03

20030503050303 7.85E-03 8.55E-04 1.36E-03 6.88E-03 2.34E-03

20031007045528 4.52E-03 1.96E-04 3.12E-04 3.83E-03 6.89E-04

20040519070411 8.65E-04 5.94E-04 9.47E-04 6.75E-03 1.89E-03

20040903190447 1.59E-03 6.74E-04 1.08E-03 8.86E-03 2.43E-03

20050518102706 1.59E-03 6.97E-04 1.11E-03 9.08E-03 2.51E-03

20070402120223 2.23E-03 4.52E-04 7.21E-04 6.23E-03 1.55E-03

20070402232023 1.28E-03 3.73E-04 5.95E-04 5.10E-03 1.21E-03

20070906175126 1.04E-02 1.09E-02 1.74E-02 3.01E-02 2.26E-02

20080603162050 7.32E-03 5.97E-03 9.52E-03 1.06E-02 8.90E-03

20100109055130 1.37E-03 4.88E-04 7.79E-04 6.81E-03 1.71E-03

19950116181449 6.42E-04 6.60E-04 1.05E-03 5.75E-03 1.67E-03

20000126132650 1.15E-03 1.63E-04 2.60E-04 2.43E-03 3.90E-04

20010802234106 1.38E-04 6.87E-05 1.10E-04 1.97E-03 2.01E-04

20031022114530 2.45E-04 4.72E-04 7.53E-04 3.34E-03 9.15E-04

20040109223531 1.54E-04 2.90E-04 4.63E-04 2.36E-03 5.20E-04

20050202023025 2.81E-02 8.04E-02 1.28E-01 1.70E-02 2.90E-02

20060214152723 2.47E-04 1.20E-05 1.91E-05 6.19E-04 2.08E-05

20100207061000 2.16E-03 6.13E-04 9.78E-04 6.74E-03 1.80E-03

20100304001851 2.06E-03 9.08E-04 1.45E-03 8.83E-03 2.68E-03

20100710114332 2.81E-03 3.80E-04 6.07E-04 5.63E-03 1.22E-03

20101004132838 3.85E-04 2.75E-04 4.39E-04 3.35E-03 6.85E-04

19991207212949 4.66E-03 6.71E-03 1.07E-02 4.50E-03 3.84E-03

20030314125412 1.71E-03 2.97E-02 4.74E-02 1.42E-03 4.21E-04

20030902182800 1.36E-02 1.13E-03 1.80E-03 1.24E-02 3.57E-03

20050122203017 8.04E-03 2.24E-03 3.57E-03 1.42E-02 5.63E-03

20051015155108 1.69E-03 6.39E-02 1.02E-01 7.66E-03 8.95E-03

20070404063435 8.73E-04 1.56E-04 2.49E-04 3.06E-03 4.27E-04

20090118141148 7.66E-02 1.07E-02 1.70E-02 4.02E-02 2.45E-02

20091219130217 1.91E-02 1.09E-02 1.74E-02 2.61E-02 1.93E-02

19960608231915 1.93E-02 1.23E-02 1.96E-02 4.30E-02 2.67E-02

20010703131042 2.07E-04 4.50E-03 7.19E-03 5.58E-04 3.04E-05

20020814135752 1.12E-02 4.88E-03 7.78E-03 2.37E-02 1.13E-02

20070816083928 1.18E-01 1.95E-02 3.12E-02 8.06E-02 4.98E-02

20090516005351 9.45E-03 1.60E-03 2.55E-03 8.65E-03 3.20E-03

20100426025951 2.11E-03 2.54E-04 4.05E-04 4.35E-03 6.92E-04
82

Table 5. Peak horizontal ground acceleration.—Continued

Earthquake origin time Observed AB-Cascadia AB-Global Geomatrix Zhao and 

others (2006)

19971217043851 1.25E-03 6.72E-04 1.07E-03 7.25E-03 1.65E-03

19990128081005 1.19E-03 3.49E-04 5.57E-04 2.45E-03 4.42E-04

20021107151406 1.43E-03 1.29E-03 2.05E-03 8.86E-03 2.73E-03

20031125201946 2.45E-04 9.28E-05 1.48E-04 1.91E-03 1.65E-04

20050116201752 3.99E-04 1.12E-04 1.78E-04 2.42E-03 2.35E-04

20050205033425 8.96E-03 1.51E-02 2.40E-02 6.96E-03 6.79E-03

20070130213744 1.41E-04 1.23E-05 1.96E-05 9.16E-04 2.22E-05

20071127114958 1.89E-03 7.72E-04 1.23E-03 8.47E-03 2.00E-03

20080719092701 3.61E-04 8.21E-05 1.31E-04 2.46E-03 2.02E-04

20090830145132 1.20E-02 3.20E-03 5.11E-03 2.44E-02 8.86E-03

20100103214805 9.54E-04 1.13E-03 1.80E-03 9.15E-03 2.60E-03

20040125114311 5.74E-03 4.58E-03 7.31E-03 4.23E-03 2.61E-03

20050208144821 1.48E-04 6.55E-04 1.04E-03 6.97E-04 3.45E-05

20100626053019 2.18E-02 3.91E-03 6.23E-03 1.78E-02 7.76E-03

19960322032420 1.30E-03 8.95E-04 1.43E-03 8.72E-03 1.97E-03

20031210043811 2.58E-03 2.43E-03 3.88E-03 1.97E-02 6.18E-03

20041008082753 7.71E-03 1.87E-03 2.98E-03 1.07E-02 3.44E-03

20080509215129 1.04E-02 1.05E-02 1.68E-02 1.67E-02 1.22E-02

20081209062359 2.62E-02 2.12E-03 3.38E-03 1.57E-02 4.90E-03

20091124124715 6.06E-04 2.09E-05 3.33E-05 1.30E-03 3.55E-05

20091124124716 6.06E-04 2.09E-05 3.33E-05 1.30E-03 3.55E-05

20100105121532 8.39E-03 1.48E-03 2.36E-03 1.30E-02 3.52E-03

20100411094025 1.94E-02 3.64E-03 5.80E-03 2.13E-02 8.11E-03

20060928062209 6.67E-03 1.78E-03 2.84E-03 1.18E-02 3.44E-03

20061226123413 1.84E-03 6.82E-04 1.09E-03 8.70E-03 1.60E-03

20070930020830 5.06E-03 6.73E-04 1.07E-03 8.11E-03 1.50E-03

20080908185206 8.76E-04 1.38E-04 2.20E-04 1.12E-03 6.88E-05

20100718130409 1.18E-03 2.31E-04 3.69E-04 3.66E-03 3.99E-04

20011012150216 1.70E-01 3.87E-02 6.14E-02 5.42E-02 4.21E-02

20090218215345 3.60E-02 3.20E-03 5.10E-03 1.78E-02 6.19E-03

20020426160607 9.08E-02 1.61E-01 2.40E-01 8.10E-02 1.46E-01

20030317163617 6.00E-04 4.10E-03 6.51E-03 6.65E-03 2.95E-03

20100103223627 2.24E-03 6.45E-03 1.02E-02 1.08E-02 5.95E-03

20000108164720 1.06E-02 3.91E-02 6.24E-02 7.01E-03 4.31E-03

20071031033015 3.09E-03 2.06E-02 3.28E-02 3.72E-03 1.09E-03

20071219093027 1.85E-02 1.94E-02 3.08E-02 2.38E-02 1.63E-02

19960610152456 1.88E-01 8.74E-02 1.39E-01 1.24E-01 1.22E-01

20100718133459 6.56E-04 2.22E-03 3.53E-03 3.99E-03 1.02E-03

20070928133857 4.02E-04 1.23E-02 1.96E-02 2.01E-03 1.13E-04
83

Table 5. Peak horizontal ground acceleration.—Continued

Earthquake origin time Observed AB-Cascadia AB-Global Geomatrix Zhao and 

others (2006)

20090319181740 2.19E-02 1.91E-04 3.05E-04 4.22E-03 2.12E-04

20091007220314 8.07E-04 1.23E-03 1.95E-03 2.75E-03 2.34E-04

20031117064306 2.57E-03 1.07E-02 1.71E-02 3.17E-02 1.52E-02

19960610040335 1.39E-01 1.55E-01 2.32E-01 1.76E-01 2.29E-01

20060503152640 6.31E-03 1.10E-03 1.76E-03 8.06E-03 8.98E-04

20070401203958 5.94E-03 3.78E-02 6.00E-02 3.44E-02 2.19E-02

20090929174810 9.13E-02 7.88E-02 1.26E-01 1.37E-01 1.82E-01
84

Table 6. Systematic Offset of the Zhao and others (2006) equation for Pacific region data. (PGA, peak horizontal 

ground acceleration, 5 Hz and 1 Hz represent 5 and 1 Hertz or 0.2 seconds and 1.0 second periods. km, kilometers ) 

PGA 5HZ 1HZ

ZHAO -0.0542 0.0777 0.2018

Table 7. Single Station Sigma, distance ≤ 300 km, M ≥ 6.0. (PGA, peak horizontal ground acceleration, 5 Hz and 

1 Hz represent 5 and 1 Hertz or 0.2 seconds and 1.0 second periods; km, kilometers)

Zhao and others (2006) Geomatrix Atkinson and Boore (2003)

PGA 0.7356 0.8199 0.9952

5HZ .792 .852 .8874

1HZ .6538 .6928 .7234

Table 8. Station Sigma, distance ≤ 300 km, M ≥ 6.0. (PGA,peak horizontal ground acceleration, 5 Hz and 1 Hz 

represent 5 and 1 Hertz or 0.2 seconds and 1.0 second periods; km, kilometers)

Zhao and others (2006) Geomatrix Atkinson and Boore (2003)

PGA 0.5685 0.5156 0.5934

5HZ .5616 .5863 .5017

1HZ .2568 .2695 .2176

Table 9. Total Sigma, distance ≤ 300 km, M ≥ 6.0. (PGA, peak horizontal ground acceleration, 5 Hz and 1 Hz 

represent 5 and 1 Hertz or 0.2 seconds and 1.0 second periods; km, kilometers)

Zhao and others (2006) Geomatrix Atkinson and Boore (2003)

PGA 0.9297 0.9685 1.1587

5HZ .9709 1.0342 1.0194

1HZ .7024 .7434 .7554
85

Appendix 1. Lessons of the M8.3 Tokachi-Oki and the M9 Tohoku Earthquakes

By Stephen Harmsen

The ideal data set for predicting future ground motions in American Samoa from TongaKermadec subduction events would be composed of extensive strong-motion recordings of past TongaKermadec subduction events for a range of distances and event magnitudes that span the expected 

events. However, such data are extremely sparse. We examined Global Digital Seismic Network 

(GDSN) records from several Pacific Ocean trench regions, including Tonga and Kermadec, and found 

several strong ground motion records that either are or are suspected to be from oceanic-platesubduction events. The criteria for considering the event subduction are that they are relatively shallow 

(hypocenters in the 0 to 50 kilometer (km) range), with epicenters in the subducting slab region and 

Harvard moment tensor solutions with strongly reverse-slip motion. We recognize that these criteria are 

necessary but not sufficient to make such a determination. One source of potential ambiguity is that 

outer rise earthquakes can nucleate very close to the top of the subducting slab and tend to have reverseslip (compressional) mechanisms prior to large nearby subduction events, whereas they tend to have 

normal (tensional) mechanisms after large subduction events (Lay and others, 1989). 

The 1.0-second (sec) spectral acceleration data from interface events, as we define them, are 

shown in Figure 1–1, and are compared with Zhao and others (2006) subduction event predictions for 

sources having magnitude in the range 6 less than M less than 8. The curves in fig. 1–1 are based on an 

assumed site average shear-wave velocity (Vs30) in the top 30 m of 600 meters per second (m/s). The 

GDSN data are from stations that are generally located on volcanic rock outcrops, which may have 

Vs30 more or less than this value. Figure 1–1 shows that there are too few GDSN data in our study to 

provide strong constraints on which model or models to use for predicting ground motions. As is 

commonly done in probabilistic seismic hazard analysis (PSHA) studies, we study information from 

similar, but distant, tectonic environments to try to guide our choice of models for predicting American 

Samoa ground motions. 
86

Figure 1–1. 1-second spectral acceleration data from Global Digital Seismic Network for known or suspected 

interface earthquakes and predictions of SA from the Zhao and others (2006) model. Data and model correspond 

to the geometric mean of the peak motions on the two horizontal-component response functions. (km, kilometers; 

g, acceleration of gravity) 

Tokachi-Oki Earthquake of September 26, 2003

The Tokachi-Oki mainshock was well recorded by Japan’s KiKNet and KNet seismograph 

networks, with at least 360 stations providing usable seismograms. Japan’s dense KiKNet and K-Net 

seismograph networks were installed beginning in 1996 following the 1995 Hyogoken-nanbu (Kobe) 

earthquake. Tokachi-Oki seismograms were processed to supply spectral response and peak ground 

velocity, with results available at the USGS Shake Map site:

http://earthquake.usgs.gov/earthquakes/shakemap/atlas/shake/200309251950/, last accessed May 4, 

2011. To compare the motions with available ground-motion prediction equations (GMPEs), we need a 

geometry model of the part of the plate interface that ruptured during that earthquake. Figure 1–2 shows 

the projection of the Tokachi-Oki rupture plane to the Earth’s surface. In Figure 1–2 and later we use 

the rupture model of Kamae and Kawabe (2004) to infer closest distance, rcd. In their model, the rupture 

surface has length 128 km and width 80 km. Its dip is 26°. For comparison, the Geomatrix Consultants 

(1995) expected length of an M8.3 subduction source is 261 km. The compactness of the source may in 

part be due to its relatively great width, with an aspect ratio of 1.6. Many subduction sources may be 

expected to have aspect ratios of 2.5 or greater. We use the Geomatrix expected length to predict rupture 

length of M7 to M9 subduction events on the Tonga-Kermadec and New Hebrides interfaces.
87

Figure 1–2. Map of a portion of Japan showing locations of KiKNet stations (brown symbols) and KNet stations 

(black symbols) as well as rupture zones for two important subduction events, Tokachi-Oki and Tohoku. All pictured 

stations provided records from the Tohoku main shock, whereas only about 1/3 of them provided data from 

Tokachi-Oki. (km, kilometers) 

Figure 1–3 shows the Tokachi-Oki peak horizontal ground accelerations ( PGA) data (geometric 

mean of the two horizontal components) and three GMPEs for subduction events with M8.3, assuming a 

uniform 600 m/s site condition, that is, National Earthquake Hazard Reduction Program (NEHRP) Class 

C soil classification. In the 200 to 300 km range, where predictions are important to the American 

Samoa seismic hazard, these models tend to over-predict the motion, with the Zhao and others (2006) 

model exhibiting the least bias. Site condition for most of these data is NEHRP Class C, D, or E soil, 

reported at http://www.k-net.bosai.go.jp/. Given these site conditions, a factor of two (plus or minus) 

soil amplification compared to rock at the same location is to be expected. The curves, which 

correspond to a very stiff soil or firm rock, are clearly biased high compared to Tokachi-Oki data, 

especially if those data had been scaled to a common site condition of 600 m/s Vs30, at distances in the 

200–500 km range. 
88

Figure 1–3. Tokachi-Oki main shock data and three ground-motion models for peak ground acceleration from 

subduction source with M8.3 and depth 25 km. The data are mostly from sites located on soil with NEHRP site 

class C, D, and E. The curves, however, correspond to an upper-C site class. (GMPEs, ground-motion prediction 

equations, m/s, meters per second; g, acceleration of gravity; km, kilometers; NEHRP, National Earthquake Hazard 

Reduction Program) 

Figure 1–4 shows the 0.3-s spectral acceleration data and three GMPE models, again computed 

for a 600 m/s site condition. The 0.3-s data are here used as a proxy for 0.2-s data, because 0.2-s data are 

not available at the Shake Map web site, but seismic hazard at 0.2-s period is discussed in this report. 

Stations in the Tokyo subnet of K-Net are highlighted in red. These Tokyo stations are on thin to thick 

soil, often NEHRP class D or even E, as are most other K-Net stations. In the 200 to 300 km range, 

these GMPEs tend to over predict the data, especially when a factor of two (plus or minus) is divided 

out to remove expected soil amplification. The Zhao and others (2006) GMPE clearly exhibits the least 

high bias in that distance range.
89

Figure 1–4. Tokachi-Oki main shock data and three ground-motion models for pseudo spectral acceleration (pSA) 

at 0.3-s period (5 percent damping) from subduction source with M8.3 and depth 25 km. The data are mostly from 

sites located on soil with NEHRP site class C, D, and E. The curves, however, correspond to an upper-C site class.

(km, kilometers; GMPEs, ground-motion prediction equations, m/s, meters per second; s, seconds; g, acceleration 

of gravity; km, kilometers; NEHRP, National Earthquake Hazard Reduction Program) 

Figure 1–5 below shows the Tokachi-Oki ground motion data and three GMPEs for 1-s spectral 

acceleration. The data correspond to soil sites, and if they are reduced by a factor of two (plus or minus) 

to remove soil amplification, they tend to fall below the curves in the important distance range of 200 to 

500 km. Again, the Zhao and others (2006) model tends to have the smallest bias in this distance range. 

The models have comparable amplitudes in the near source distance range (Rcd less than 100 km). 
90

Figure 1–5. Tokachi-Oki main shock data and three ground-motion models for pseudo spectral acceleration (SA) 

at 1.0-s period (5 percent damping) from subduction source with M8.3 and depth 25 km. (GMPEs, ground-motion 

prediction equations, m/s, meters per second; s, seconds; g, acceleration of gravity; km, kilometers; NEHRP, 

National Earthquake Hazard Reduction Program) 

Tohoku Earthquake of March 11, 2011

Besides the obvious lesson that M9 subduction events produce large, destructive tsunamis (often 

with columns of water having 10-m depth rushing inland and destroying everything and everyone in 

their path) the Tohoku earthquake provides valuable information about ground acceleration at a broad 

range of distances as recorded on a variety of soil and rock sites. Approximately 1,200 K-Net and 

KiKNet instruments provided useful seismograms from the Tohoku earthquake. These seismograms 

were processed to supply spectral response and peak ground velocity, with results available at the USGS 

Shake Map site: http://earthquake.usgs.gov/earthquakes/eqinthenews/2011/usc0001xgp/, last accessed 

May 4, 2011. To compare the motions with available GMPEs, we need a geometry model of the part of 

the plate interface that ruptured during that earthquake. In figure 1–2 above, and in the below figures, 

we use the rupture model of Gavin Hayes, USGS, which has length 621 km and width 254 km. The 

Hayes model is more fully described at 

http://earthquake.usgs.gov/earthquakes/eqinthenews/2011/usc0001xgp/finite_fault.php. For comparison, 

the Geomatrix expected length of an M9 megathrust event is 833 km. According to the Hayes model, 

the shorter length of the Tohoku rupture is more than compensated by the greater than usual width, 
91

which corresponds to a very gentle interface dip of about 10 ̊. The Tonga trench interface has a much 

steeper dip, and is expected to produce relatively long ruptures for a given magnitude. 

Most of the stations in Japan’s KiKNet network are located on sedimentary rock or on thin soil 

over sedimentary rock, and correspond, more often than not, to the NEHRP Class C geotechnical site 

class, 350 less than Vs30 less than 600 m/s. Most of the stations in the K-Net network are located on 

thin to thick sediment over sedimentary rock, and mostly correspond to NEHRP Class E (120 to 180 

m/s) and Class D (180 to 350 m/s) site classes. Detailed geotechnical logs are available for many of 

these KNet stations at http://www.k-net.bosai.go.jp/. This report, however, primarily focuses on seismic 

hazard corresponding to rock at the NEHRP B/C interface, with Vs30 = 760 m/s. When comparing 

prediction curves with data, we choose a uniform 600 m/s rock site condition, which is a compromise 

between the data and the American Samoa modeling work.

Figure 1–6 below shows the PGA data (geometric mean of the two horizontal components) and 

three GMPE models. The data generally plot below the models except at near-source distances, where 

several data plot two to three times above the prediction. If we could remove site response from the 

data, they would tend to plot even further below the predictions, except at relatively near-source 

distances, where they would be close to the predictions. For sites in American Samoa, the distance to the 

Tonga-interface source is about 200–250 km. Samoa does not lie in the direction of slip. Pago Pago and 

the rest of American Samoa are northeast of the trench, just as Tokyo is southwest of the Tohoku 

rupture, although only 60 km or so distant. Tokyo KNet data are plotted as red triangles in figure 1–6. 

Figure 1–6 clearly shows that of the three GMPEs we have been considering, only the Zhao 2006 model 

does a reasonably good job of fitting the data in the inner 300 km. Although the Zhao ground-motion 

model was not designed to fit data beyond 300 km, we continue to employ it to predict ground motions 

to a maximum distance of 1,000 km. 
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Figure 1–6. Peak ground acceleration models and data for an M9 megathrust earthquake. (GMPEs, groundmotion prediction equations, m/s, meters per second; g, acceleration of gravity; km, kilometers)

Figure 1–7 below shows the 0.3-s Tohoku data (geometric mean of the two horizontal 

components) and three subduction GMPEs. As in figure 1–6, the Zhao 2006 model outperforms the 

others in goodness-of-fit. These data tend to justify the exclusive use of the Zhao 2006 model, given 

these three GMPEs to choose among. Data corresponding to 0.2-s spectral period were not available 

from the Shake Map web site, so we are using these 0.3-s spectral period data to guide our thinking 

about the expected behavior of 0.2-s data.
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Figure 1–7. Data and GMPEs for 0.3-s pseudo spectral acceleration (pSA). Rcd is the closest distance from the 

site to the rupture surface. (GMPEs, ground-motion prediction equations, m/s, meters per second; s, seconds; g, 

acceleration of gravity; km, kilometers; NEHRP, define here)

Figure 1–8 below shows the 1.0-s Tohoku data (geometric mean of the two horizontal 

components) and three GMPEs for an M9 interface earthquake. As usual, the Zhao 2006 model clearly 

outperforms the others at most distances and this plot tends to justify the exclusive use of the Zhao 2006 

model with subduction-source branches of the logic tree.
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Figure 1–8. Data and GMPEs for 1.0-s pseudo spectral acceleration (pSA). Rcd is the closest distance from the 

site to the rupture surface. (s, seconds; km, kilometers; GMPEs, ground-motion prediction equations, m/s, meters 

per second; g, acceleration of gravity; km, kilometers; NEHRP, define here)

The extensive KiKNet and K-Net data from the M9 Tohoku earthquake begin to fill in a big gap 

in strong-motion data from megathrust events. Questions remain about the applicability of these data to 

other tectonic plates with their unique rock properties, slab dips, and convergence rates. Still, we believe 

that data from similar events and tectonic environments are preferable to no data as aids when making 

decisions about models to use in the American Samoa PSHA. 

 

Conclusion

Figures 1–3 to 1–8 strongly suggest that there is no basis for raising the Zhao curve from the 

predicted value the way we have done for 1.0-s and for 0.2-s SA associated with intraplate sources, and 

no reason to give other GMPEs a positive weight, at least at for source-to-station distances greater than 

about 80 km. For interface source ground-motion prediction, we use the Zhao and others (2006) model 

as published, with 25 percent uncertainty branches on the median when M less than 8.5, and 50 percent 

uncertainty branches on the median when M greater than or equal to 8.5. This additional epistemic 

uncertainty is used as a substitute for alternate published GMPEs, which we found less appropriate for 

modeling the data sets we studied. 
95

References Cited

Geomatrix Consultants, 1995, Seismic design mapping state of Oregon: Oakland, Calif., Geomatrix 

Consultants, prepared for Oregon Dept. of Transportation, Transportation Building, Salem, Oreg., 

Section 3, 17 p. 

Kamae, K., and Kawabe, H., 2004, Source model composed of asperities for the 2003 Tokachi-Oki, 

Japan, earthquake (MJMA=8.0) estimated by the empirical Green’s function method: Earth Planets 

Space, v 56, p. 323–327. 

Lay, Thorne, Astiz, Luciana, Kanamori, Hiroo, and Christensen, D.H., 1989, Temporal variation of 

large intraplate earthquakes in coupled subduction zones: Physics of the Earth and Planetary Interiors, 

v. 54, p. 258–312 

Appendix 2. Analysis of Ground Motion Prediction Equations

By Melanie Walling

The performance of the three ground motion prediction equations (GMPEs) was evaluated as a 

step toward setting the epistemic weights on the GMPE branches of the logic tree in the probabilistic 

seismic-hazard assessment of the Samoa Island region. The ground-motion data available for this 

performance evaluation is sparse in event recording, meaning that no event was recorded more than 

once. A description of the ground-motion records is given in Analysis of Ground Motion Prediction 

Equations and this appendix is intended to clarify how the ground motion residuals were calculated. The 

criteria for selecting usable data was ground-motion records recorded within the approximate cutoff 

distance of the three GMPEs considered, which was rupture distances less than approximately 300 km. 

This reduced the data set to 72 horizontal-component response spectra recorded by 8 stations. Six 

stations (ADK, AFI, GUMO, RAO, HNR, and TATO) had six or more recordings; two stations (DAV 

and PET) had only one record. Of the eight stations, AFI recorded the greatest number of events: 17. 

The performance measures that were assessed to evaluate the GMPEs’ performances were the 

accurate prediction of ground-motion amplitude fall off in both magnitude and distance. An analysis of 

residuals was performed to evaluate each measure. The procedure followed in this Open-File Report to 

analyze the residuals was similar to other procedures commonly performed in ground motion residual 

analysis that first eliminate correlations within the residuals before performing the evaluation on the 

residual terms. These correlations are the correlations created from having unevenly sampled data in 

source and in station, in both space and time. This appendix describes the approach that was taken to 

eliminate the correlations within the residuals that was performed prior to evaluating the performance of 

each GMPE. 

Approach

In most applications of ground motion residual analyses, the correlations of the ground motion 

caused by unevenly sampled data are addressed by either performing a random effects regression 

analysis (Abrahamson & Youngs, 1992) or its equivalent: a two-staged regression analysis (Brillinger 

and Preisler, 1985; Joyner and Boore, 1993). In both cases, the residuals are separated into the 

explainable, or fixed effects, and the unexplainable, or random effects. These effects are estimated by 

fitting the residuals to the following linear model: 

Resid = y − y = ηi + ξij (2-1) 
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where, 

Resid is the total residual, 

y is the data, 

ybar, is the ground motion prediction model, 

ηi is inter-event term, which is the explained effect estimated in the regression, and 

i is the source index; 

ξij, is the intra-event residual, or unexplained, or random effect, and 

j is the station index. 

When the ground motion data set has many recording per earthquake, ηi approximates the 

average source-effects for a given event. 

In comparison to the approach just described, the correlation within the residuals from the 

Pacific Island Arch sparse ground motion data set were addressed differently by performing a randomeffects regression on the total residuals using the following linear model: 

Resid = C1 +ηi + ξij (2-2) 

where, 

C1 is a constant term estimated in the regression, 

i is now the site index, and 

j is the source index. 

Equation (2-2) is different than (2-1) because it includes a constant term, C1, to account for any 

systematic difference between the overall mean of the selected data and the data set used by the GMPE. 

The equations also differ because, in (2-2), i is the site index instead of the source index. This means 

that ηi now approximates the average station effect and is described as a station term, where before it 

approximated the average source effect. This makes the intra-event term, ξij, uncorrelated-in-stationeffects or single station residuals.

Figure 2–1 illustrates the importance of estimating C1 prior to performing the residual analysis 

by plotting the total residuals at 1 Hz for Zhao and others (2006) versus magnitude (1A) and closest 

distance to fault (1B). In frames A and B, the positive offset of the residuals is approximately equal to 

0.2 ln units; this means that the Zhao and others (2006) GMPE is systematically under-predicting the 

ground motion of the selected data set by 0.2 ln units. We interpret this systematic difference as a 

regional bias term, which can be addressed as an additional source of epistemic uncertainty that gets 

handled by the logic tree. Describing this offset as a regional bias seems appropriate given that Zhao and 

others’ (2006) data set was primarily composed of recordings from Japanese events, not of ground 

motions recorded throughout the Pacific Arc Island region. 

Figure 2-1 illustrates the importance of estimating the station terms prior to performing the 

residual analysis by plotting the residuals at ADK station versus magnitude (2A) and distance (2B). The 

residuals shown here are the residuals after C1 was subtracted. In frames A and B, the residuals are 

negatively offset. The station term for ADK is equal to -0.4 and is approximately equal to the average 

residual at ADK. This suggests that the site response at station ADK is either less than the site response 

effect predicted by the Zhao and others (2006) rock equation or that ADK station is not on the same 

rock type. Once the average station effects were removed from the data by subtracting off the station 

terms, the single-station residuals were next evaluated for any residual effects. Figure 3 is a plot of the 

single-station residuals versus magnitude (3A) and distance (3B). In both these two frames, the residuals 

are now centered around zero. 

An alternative method to estimate the station terms using the random-effects regression is to 

directly remove the correlations using a known site-response function for each station and then subtract 
97

it from each record. The advantage to this approach is that it uses empirical site-response data, which 

addresses the problem more directly. However, we do not have this information; therefore, the randomeffects approach was applied to estimate the station terms. 

References Cited

Abrahamson, N.A., and Youngs, R.R., 1992, A stable algorithm for regression analyses using the 

random effects model: Bulletin of the Seismological Society of America, v. 82, p. 505–510. 

Brillinger, D.R., and Preisler, H.K., 1985, Further analysis of the Joyner-Boore attenuation data: 

Bulletin of the Seismological Society of America, v. 75, p. 611–614. 

Joyner, W.B., and Boore, D.M., 1993, Methods for regression analysis of strong-motion data: Bulletin 

of the Seismological Society of America, v. 83, p. 469–487. 

Zhao, J.X., Zhang, J., Asano, A., Ohno, Y., Oouchi, T., Takahashi, T., Ogawa, H., Iridura, K., Thio, H. 

K., Somerville, P.G., Fukushima, Y., and Fukushima, Y., 2006, Attenuation relations of strong ground 

motion in Japan using site classification based on predominant period: Bulletin of the Seismological 

Society of America, v. 96, p. 898–913. 

 A B

 

Figure 2–1. The total residuals computed using the selected data set vs. A magnitude and B distance. The red line 

is the average offset of the total residuals. The positive offset trend means that, on average, the Zhao and others

(2006) ground motion prediction equation (GMPE) is under-predicting the ground motions within the Pacific Arc 

Island sparse data set. This offset is treated as a regional bias effect between the selected data set and the data 

set used in the Zhao and others’ (2006) GMPE and is later removed from the total residuals. (km, kilometers)
98

 A B

 

Figure 2–2. The ADK station residual terms calculated by subtracting C1 term from the total residual vs. A

magnitude and B distance. The red line is the ADK station term estimated by performing the random effects 

regression using Eqn 2. The station terms approximate the average station effect. The station term is later 

subtracted from the residuals shown as triangles to calculate the single station residuals. (km, kilometers) 

 A B

 

Figure 2–3. The ADK single-station residuals equal to the total residual - C1 - ADK station term vs. A, magnitude 

and B, distance. The single-station residuals are uncorrelated in station effects and are centered near zero. The 

residual analysis for evaluating the performance of each GMPE is done using the single-station residuals.