northwestern university tectonics and...

NORTHWESTERN UNIVERSITY

Tectonics and Seismicity of Rifts Past and Present

A DISSERTATION

SUBMITTED TO THE GRADUATE SCHOOL IN PARTIAL FULFILLMENT OF THE REQUIRMENTS

for the degree

DOCTOR OF PHILOSOPHY

Field of Earth and Planetary Sciences

By

Miguel Merino

EVANSTON, ILLINOIS

March 2014

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© Copyright by Miguel Merino 2013

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3

ABSTRACT

Tectonics and Seismicity of Rifts Past and Present

Miguel Merino

I investigated rifts in multiple stages of their formation, from the failed Mid-Continent

Rift (MCR), to the active Red Sea Rift. Each rifting stage presents its own challenges but by

studying each stage individually I have gained insight into the rifting process.

The MCR, an ancient failed rift, stretches through most of the Midwestern U.S. It is

primarily identified by gravity and magnetic anomalies. I model gravity data to explore the

variation in magma volumes along the MCR. The variations are consistent with a microplate

model, which explains the difference in gravity signature for the two rift arms.

The gravity models over the MCR give key insights into the ‘local’ formation tectonics, I

also studied the regional tectonics to further understand how a massive rift failed to break the

continent. I use Geologic, paleomagnetic, and geophysical evidence to formulate a new model

the evolution of the MCR. This model showed that the MCR formed as part of continental

breakup and fails once breakup is complete, removing the stresses needed to continue rifting.

Next I investigated the seismicity of a failed rift and a passive margin. The New Madrid

Seismic Zone (NMSZ), which lies over the failed Reelfoot Rift, has been seismically active since

a series of three ~M7 earthquakes in 1811-1812. I tested suggestions that this sequence of

earthquakes transferred stress to the nearby, geologically similar, Wabash Valley. I quantified

the difference in seismicity between regions and show that it instead probably reflects long

duration aftershocks in the NMSZ. Following up this study, I modeled the seismicity of the east

4

coast of North America and found the largest known earthquakes there likely reflect the length of

the available earthquake catalog rather than the largest possible events.

I examined the Red Sea Rift, an actively spreading region, building on a tomographic

model by Sung-Joon Chang and coauthors that identifies a low velocity channel underlying

recent volcanism in Arabia. Integrating this and other geologic and geophysical evidence I

purpose a scenario in which the northern Red Sea is abandoned and the rift jumps inward into

Arabia, ‘re-rifting’ the continent.

5

Acknowledgements

I want to thank Dr. Seth Stein for being my advisor, without him this dissertation would

not have been possible. He allowed me to grow as a scientist and a person in the last five years.

Perhaps the most important thing he taught me was how to convey my ideas with conviction, and

to always be a skeptic because everything is more than it appears.

Dr. John Weber, a professor at Grand Valley State University, introduced me to the idea

of going to graduate school, and for that I thank him. John also introduced me to Seth, which is

ultimately why I am writing this dissertation. He challenged me in his classes and guided me to

another professor at Grand Valley to do research with.

Two other people advised me during my Ph.D., Dr. Carol Stein and Dr. Randy Keller.

Carol ‘took the blinders off’ when I was looking at data. If I was pointed in one direction

interpreting the data, then she would come in and point out a myriad of other questions that we

could attempt to answer, for this I thank her. I worked with Randy on Chapters 2 and 3 of this

dissertation. He hosted me at the University of Oklahoma where much of the gravity modeling

was done. Randy became an outside mentor who is very candid, and for that I thank him.

The graduate students at Northwestern University kept me grounded while I was here and

there was always someone to go grab a beer when I needed it. I would like to thank Emily Wolin

and Jessica Lodewyk, they allowed me to bounce crazy ideas off of them, edited my writing, and

will forever be life long friends. Greg Lehn sharpened my arguing skills by testing them almost

every day that we saw each other. To this day Greg will never believe a fact I assert without an

immense amount of evidence. My family and friends, back in Michigan, have always been

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supportive of this endeavor. They acted as a relief from the academic world when I needed it and

as a motivator when they thought I needed it, for that I thank them.

I would like to thank everyone who is reading this dissertation and wish him or her good

luck.

7

TABLE OF CONTENTS

Page

Abstract ....................................................................................................................................... 3

Acknowledgements ...................................................................................................................... 5

List of Tables .............................................................................................................................. 10

List of Figures ............................................................................................................................. 11

Chapter 1. Introduction and Overview

1.1. Introduction .................................................................................................................. 15

1.2. Chapter 2: Variations in Mid-Continent Rift magma volumes consistent with

microplate evolution .................................................................................................... 16

1.3. Chapter 3: Was the Mid-Continent Rift part of a successful seafloor-spreading

episode? ........................................................................................................................ 16

1.4. Chapter 4: Comparison of Seismicity Rates in the New Madrid and Wabash Valley

Seismic Zones .............................................................................................................. 17

1.5. Chapter 5: Have We Seen the Largest Earthquakes in Eastern North America? ........ 18

1.6. Chapter 6: Mantle flow beneath Arabia offset from the opening Red Sea .................. 19

1.7. Mapping sediment thickness in Minnesota with horizontal-to-vertical spectral ratios

from USArray data ....................................................................................................... 20

Chapter 2. Variations in Mid-Continent Rift magma volumes consistent with microplate

evolution

2.1. Introduction .................................................................................................................. 22

8

2.2. Gravity Analysis .......................................................................................................... 25

2.3. Results and Interpretation ............................................................................................ 26

Chapter 3. Was the Mid-Continent Rift part of a successful seafloor-spreading episode?

3.1. Introduction .................................................................................................................. 38

3.2. Gravity Analysis .......................................................................................................... 38

3.3. Microplate Formation During Continental Rifting ...................................................... 41

3.4. Apparent Polar Wander Path ....................................................................................... 44

3.5. Laurentia, Amazonia, and the MCR ............................................................................ 45

3.6. Reconstructions Using Paleomagnetic Data ................................................................ 48

3.7. Discussion .................................................................................................................... 49

Chapter 4. Comparison of Seismicity Rates in the New Madrid and Wabash Valley

Seismic Zones

4.1. Introduction .................................................................................................................. 52

4.2. Results .......................................................................................................................... 52

4.3. Discussion .................................................................................................................... 56

Chapter 5. Have We Seen the Largest Earthquakes in Eastern North America?

5.1. Introduction .................................................................................................................. 60

5.2. Methods ........................................................................................................................ 65

5.3. Eastern North America Results and Analysis .............................................................. 67

5.4. Lower Rhine Embayment Seismic Zone Results ......................................................... 74

5.5. Discussion .................................................................................................................... 77

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Chapter 6. Mantle flow beneath Arabia offset from the opening Red Sea

6.1. Introduction .................................................................................................................. 81

6.2. Tomographic Image ..................................................................................................... 83

6.3. Tectonic Interpretation ................................................................................................. 85

Chapter 7. Mapping sediment thickness in Minnesota with horizontal-to-vertical spectral

ratios from USArray data

7.1. Introduction .................................................................................................................. 92

7.2. Data .............................................................................................................................. 93

7.3. Results .......................................................................................................................... 98

Chapter 8. Conclusions and Future Work

7.1. Conclusions and Links ............................................................................................... 112

7.2. Reflections and Future Work ..................................................................................... 114

References ...................................................................................................................................116

10

List of Tables

5.1 Percent of simulations with an earthquake greater than Düren earthquake ..... 77

7.1 HVSR and site depth information ....................................................................... 95

11

List of Figures

2.1 Gravity map of the Mid-Continent Rift with location of models ....................... 23

2.2 Gravity models of the west arm of the Mid-Continent Rift ................................ 28

2.3 Gravity models of the east arm of the Mid-Continent Rift ................................. 29

2.4 Example of grid search used to find best fitting gravity models ........................ 30

2.5 Gravity models of the west arm of the Mid-Continent Rift using the Moho

from NA07 .......................................................................................................... 31

2.6 Gravity models of the east arm of the Mid-Continent Rift using the Moho

from NA07 .......................................................................................................... 32

2.7 Gravity models of the west arm of the Mid-Continent Rift including a

shallow basalt slab .............................................................................................. 33

2.8 Gravity models of the east arm of the Mid-Continent Rift including a

shallow basalt slab .............................................................................................. 34

2.9 Mid-Continent Rift magma variation plots ......................................................... 35

2.10 Schematic Microplate model for the Mid-Continent Rift ................................... 36

3.1 Residual gravity map of the eastern United States showing relevant

tectonic features .................................................................................................. 39

3.2 Complete Bouguer gravity anomaly map for the eastern United States ............. 40

3.3 Gravity anomaly map upward continued to 40km .............................................. 41

3.4 Eastern African Rift and Mesozoic west central African rift system maps ........ 43

12

3.5 Apparent polar wander path and plate reconstruction of Laurentia-

Amazonia ............................................................................................................ 47

4.1 Regional seismicity of the New Madrid and Wabash Valley seismic zones ...... 54

4.2 Frequency-magnitude plots for regional data ..................................................... 55

4.3 Frequency-magnitude plots for global data ........................................................ 57

5.1 Seismicity map of the eastern North American continental margin ................... 63

5.2 Frequency-magnitude plots for the eastern U.S. and eastern Canada ................. 66

5.3 Frequency-magnitude results for three simulated earthquake histories .............. 68

5.4 Apparent Mmax results for the eastern United States and eastern Canada ........... 70

5.5 Example of combined Mmax and b value results for MLE and LSQ ................... 71

5.6 b-value results for the eastern United States ....................................................... 72

5.7 b-value results for the eastern Canada ................................................................ 72

5.8 Combined Mmax and b value results .................................................................... 73

5.9 Recurrence time distribution for M7.6 earthquake ............................................. 73

5.10 Lower Rhine Embayment seismicity map .......................................................... 75

5.11 Apparent Mmax results for the Lower Rhine Embayment .................................... 76

5.12 b-value results for the Lower Rhine Embayment ................................................ 76

5.13 Percentage of simulation with differing standard deviations that recover

the simulations Mmax ........................................................................................... 78

6.1 Regional tectonic map of Arabia ........................................................................ 82

6.2 Cross-sections of the tomographic model ........................................................... 84

13

6.3 Shear wave velocity map at 150 km depth ......................................................... 86

6.4 Schematic tectonic model for the evolution of the Red Sea rift ......................... 88

7.1 Plot of horizontal over vertical spectral ratios for station A32A ........................ 94

7.2 Amplitude spectra and horizontal over vertical spectral ratios for all

stations ................................................................................................................ 99

7.3 Horizontal divided by vertical spectral ratios map of Minnesota ..................... 107

7.4 Spectral ratios versus soft sediment thickness .................................................. 108

7.5 Calculated and actual soft sediment thickness maps for Minnesota ................. 109

7.6 Error analysis plots for soft sediment thickness data ........................................ 110

14

CHAPTER 1

Introduction and Overview

15

1.1 Introduction

Rifts shape the Earth no matter what stage they are in, whether they are successfully

forming present-day oceans, failed and lying dormant within continents, or actively changing the

current landscape. My thesis has been a trek through many different topics with an underlying

theme of rifts. This trek was not intentional, but rather speaks to how pervasive the rifting

process is in our geologic endeavors.

Rifts are not only a scientific curiosity they play a major role in society by their

fundamental roles in sedimentary deposition and intraplate seismicity. Rifting events formed our

present day passive margins and influence the location of basins, both of which are where oil and

gas deposits are commonly found. Intraplate seismicity often occurs on old failed rifts because

they act as pre-existing zones of weakness. This seismicity is important to society because the

locations of intraplate earthquakes are currently unpredictable, in contrast to plate boundaries

where we expect earthquakes. Because the location of intraplate earthquakes is unknown, it is

unclear how much money should be allocated towards earthquake ‘proofing’ buildings in

intraplate regions.

This dissertation presents studies on the tectonics of a failed and active rift system and

studies of intraplate seismicity of failed and successful rift systems, as summarized next. Chapter

2 has been published in Geophysical Research Letters as Merino et al. [2013]. Chapter 3 has

been accepted in Geophysical Research Letters as Stein et al. [2014]. Chapter 4 has been

published in Seismological Research Letters as Merino et al. [2010]. Chapter 5 has been

16

submitted to Tectonophysics as Merino et al. [2014]. Chapter 6 has been published in

Geophysical Research Letters as Chang et al. [2011].

1.2 Chapter 2: Variations in Mid-Continent Rift magma volumes consistent with

microplate evolution

Modeling of gravity data along the central U.S.’s ~1.1 Ga failed Mid-Continent Rift

(MCR) shows systematic patterns in magma volume between and along the rift's two arms. The

volume of magma increases towards the Lake Superior region, consistent with magma flowing

away from a hotspot source there. The west arm experienced significantly more magmatism.

These patterns are consistent with a model in which the two rift arms acted as boundaries of a

microplate. The volume of magma along the west arm increases with distance from the Euler

pole, indicating that it acted essentially as a spreading ridge, whereas the much smaller magma

volumes along the east arm are consistent with its acting as a leaky transform. This view of the

rift system's evolution is compatible with the rift being part of an evolving plate boundary system

rather than an isolated episode of midplate volcanism.

1.3 Chapter 3: Was the Mid-Continent Rift part of a successful seafloor-spreading

episode?

This research was prompted in part by the results found in Chapter 2, where I showed

that the MCR could be viewed as part of a larger plate boundary system. Based on a result

indicating that the MCR was probably not formed by an isolated episode of midplate volcanism,

17

in Chapter 3, I suggest a plausible plate-tectonic scenario. I propose that the MCR formed as part

of the separation of Amazonia (Precambrian northeast South America) from Laurentia

(Precambrian North America) and became inactive once seafloor spreading was established. A

cusp in Laurentia’s apparent polar wander path recorded, at ~1.1Ga, by the MCR's volcanic

rocks likely reflects the rifting. This scenario is suggested by analogy with younger rifts

elsewhere and consistent with the geometry and timing of Precambrian rifting events including

the MCR's extension to southwest Alabama along the East Continent Gravity High, southern

Appalachian rocks having Amazonian affinities, and recent interpretation of large igneous

provinces in Amazonia.

1.4 Chapter 4: Comparison of Seismicity Rates in the New Madrid and Wabash Valley

Seismic Zones

Failed rift systems have societal importance because intraplate earthquakes often occur

on them. In 1811-1812, three large, ~M7, earthquakes occurred in the New Madrid Seismic Zone

(NMSZ), which is located on the failed Reelfoot rift. Based on historical accounts, the

magnitudes of these earthquakes were first inferreed to have been ~M8, and have been steadily

revised downward to ~M7. Li et al. [2005,2007] suggests that these large earthquakes should

have transferred stress to the Wabash Valley seismic zone, a geologically similar nearby region. I

explore this possibility by comparing seismic catalogs for New Madrid and the Wabash Valley. I

combined historical catalogs, starting after the 1811-1812 sequence, with recent instrumental

18

catalogs, to look at the Gutenberg-Richter frequency-magnitude relationship. A low slope,

denoted as the b value in the Gutenberg-Richter relationship, has been interpreted as being

indicative of a high stress region. I find that the Wabash Valley has a b value similar to the

background seismicity in the central U.S. In contrast, New Madrid has an anomalously high b

value that I attribute to a long aftershock sequence from the 1811-1812 events increasing the

number of small events and therefore the b value. This study prompted Chapter 5, which

explores the range in b values, and more importantly the maximum magnitude earthquake, that

we should expect to observe in such low seismicity intraplate regions given that we have a short

catalog.

1.5 Chapter 5: Have We Seen the Largest Earthquakes in Eastern North America?

The assumed magnitude of the largest future earthquakes, Mmax, is crucial in assessing

seismic hazard, especially for critical facilities like nuclear power plants. Absent any theoretical

basis, estimates of Mmax are made using various methods and often prove far too low, as for the

2011 Tohoku, Japan, earthquake. Estimating Mmax is particularly challenging within tectonic

plates, where large earthquakes are infrequent compared to the length of the available earthquake

history, vary in space and time, and sometimes occur on previously unrecognized faults. For

example, it is unclear whether the largest earthquakes possible along the eastern U.S seaboard

and eastern Canada have occurred. I explore this issue by generating synthetic earthquake

histories and sampling them over a few hundred years. The maximum magnitudes appearing

most often in the simulations are essentially those observed, and smaller than the simulation

19

maxima. Future earthquakes along both coasts may thus be significantly larger than those

observed to date.

1.6 Chapter 6: Mantle flow beneath Arabia offset from the opening Red Sea

Continental rifting involves a poorly understood sequence of lithospheric stretching,

volcanism, and mantle flow that evolves to seafloor spreading. I present new insight into the

tectonics of seafloor spreading in the Red Sea and Gulf of Aden associated with the three-arm

rift geometry as Africa splits into Nubia, Somalia, and Arabia. My tectonic analysis builds on

inversion of seismic traveltimes and waveforms beneath Arabia and surroundings performed by

Sung-Joon Chang and coworkers. Their results show low velocities beneath the southern Red

Sea and Gulf of Aden, consistent with active spreading. However, hot material extends not

below the northern Red Sea, but rather is offset eastward beneath Arabia, showing mantle flow

from the Afar hotspot. I start from the observation that this channel is located beneath volcanic

rocks that have erupted since rifting began 30 million years ago, indicating that the mantle flow

moves with Arabia. I propose that the absence of seafloor spreading in the northern Red Sea

reflects the offset flow. I model the kinematics of the three-plate system and show how this

geometry may evolve to spreading in the Northern Red Sea, rifting of Arabia, or both. This

situation has aspects of both active and passive rifting, showing that both can occur before

coalescing to seafloor spreading.

20

1.7 Chapter 7: Mapping sediment thickness in Minnesota with horizontal-to-vertical

spectral ratios from USArray data

Chapter 7 does not fall directly in the rifting theme, but presents an interesting technique

commonly used with very local seismic arrays, which I tested on a large array spanning part of

the Mid-Continent Rift. The spectral ratio between seismic noise recorded on the horizontal and

vertical components (HVSR) of USArray sites in Minnesota shows consistent spatial variations

in peak frequencies due to the variation in sediment thickness. The HVSR thus provides

reasonable estimates of the sediment thickness at sites. This result is consistent with earlier

studies that find this to be true when sediments are similar across a study region and their

impedance contrast with the basement rocks is strong.

21

CHAPTER 2

Variations in Mid-Continent Rift magma volumes consistent with microplate evolution

22

2.1. Introduction

The Mid-Continent Rift (MCR) is one of the most prominent features on the Bouguer

gravity map of the central United States (Figure 2.1). The rift formed at ~1.1Ga, recorded by two

pulses of magmatic activity lasting ~15Myr [White, 1997], making it one of the most extensive

paleorifts in the world [Hinze et al., 1997]. Petrologic and geochemical models favor the MCR

having been formed in the continental interior by a mantle plume [Davis and Green, 1997;

Nicholson et al., 1997; Vervoort et al., 2007]. Alternatively, many tectonic models view the rift

as having formed as a part of the Grenville orogeny [McWilliams and Dunlop, 1978; Gordon and

Hempton, 1986], which is the series of 1.3-0.9 Ga tectonic events associated with the assembly

of Rodinia [Whitmeyer and Karlstrom, 2007]. In such interpretations, northwest-directed

convergence at the southern margin of Laurentia (Proterozoic North America) caused extension

and magmatism to the northwest, including formation of the MCR. Volcanic activity was

followed by deposition of clastic sediments in subsiding basins and subsequent faulting of these

lithified sediments [Halls, 1982; Wold and Hinze, 1982]. Eventually, changing far-field stresses,

as the Grenville orogeny progressed, are proposed to have caused compression that slowed and

stopped the extension, leaving a failed rift [Cannon, 1994].

The 2000-km-long MCR, comparable in length to the presently active East African and

Baikal rifts, has two major arms meeting in the Lake Superior region. One extends

southwestward at least as far as Kansas, and the other extends southeastward at least through

Michigan. Because the rift is hidden beneath Phanerozoic sedimentary rocks, except where

exposed in the Lake Superior region, its location and geological characteristics are primarily

23

inferred from the gravity and magnetic anomalies, extrapolations from the outcrop area, seismic

reflection profiles, and a few basement drill holes.

Figure 2.1: Bouguer anomaly gravity map, from PACES database, of the central United States. White lines represent gravity profile and model locations, which are numbered and cross the anomalies that delineate the rift system. Lines 1, 2, 5, 8, and 9 are located near seismic lines.

Early active source seismic refraction studies indicate that the crust beneath Lake

Superior and portions of the west rift arm is thickened and anomalously dense [Ocola and

Meyer, 1973]. Similar crustal thickening was found in the east arm by Halls [1982]. Seismic

24

reflection data from the GLIMPCE program of active source studies across Lake Superior

[Cannon et al., 1989; Shay and Trehu, 1993] show that the crust was initially thinned to about

one-fourth of its original thickness. The resulting basin was filled with extrusive volcanics and

sediments, and volcanic underplating, producing a rift pillow, subsequently thickened the lower

crust. Such crustal rethickening has been identified in other rifts [Thybo and Nielsen, 2009].

Soon after magma had stopped erupting the normal faults were inverted to reverse motion,

presumably due to the Grenville orogeny [Cannon, 1994].

The highly magnetic and dense mafic igneous rocks filling the rift basin were juxtaposed

by high-angle reverse faulting against the less magnetic and less dense clastic rocks deposited in

the basins that originally overlaid them [King and Zietz, 1971]. The resulting gravity and

magnetic anomalies have been used to map the west arm of the rift, which extends into southern

Kansas and perhaps to southern Oklahoma [Adams and Keller, 1996]. Gravity and magnetic

anomalies also show that the rift continues into the basement beneath the Michigan basin [Oray

et al., 1973]. This interpretation has been confirmed by drilling in the Michigan basin that

encountered a thick section of clastic sedimentary rocks underlain by mafic volcanic rocks [Sleep

and Sloss, 1978], and reflection seismic studies [Brown et al., 1982] that detected the graben

structure sampled by the deep drill hole. The southern limit of the east arm is generally placed in

southeast Michigan, but a series of N-S trending gravity maxima that extend into Ohio, Kentucky

and Tennessee may be continuations of this arm [Halls, 1978; Keller et al., 1982]. Lidiak and

Zietz [1976] also suggested the presence of related rifts in the eastern Kentucky area.

25

2.2 Gravity Analysis

I examine variations in the volume of magmatic rocks along the east and west arms to

seek additional insight into the rift system's evolution. Numerous 2-D gravity and magnetic

models along parts of the MCR have been developed [Hinze et al., 1982; Wold and Hinze, 1982;

Van Schmus and Hinze, 1985; Cannon et al., 1989; Woelk and Hinze, 1991; Hinze et al., 1992;

Thomas and Teskey, 1994]. However, these models were constructed using a variety of software

and modeling schemes, making it difficult to compare results from different profiles. Hence I

conducted consistent modeling across both arms of the rift, allowing direct comparisons.

The gravity data (Figure 2.1) were compiled from the PACES database for land areas

[Keller et al., 2002, 2006; Hinze et al., 2005] and TOPEX satellite data for the Great Lakes

[Sandwell and Smith, 2009]. Only the Bouguer anomaly land data were used to create gravity

models.

Gravity profile locations were selected to give good spatial coverage of the rift arms, and

when possible, correlate with previous seismic reflection and gravity profiles. However, the

seismic data have poor resolution in the lower crust and hence do not significantly impact my

gravity models. Although, the Lake Superior region of the MCR has a significant amount of

seismic data, it was not modeled because the gravity data do not show a simple trend along the

rift. This choice also avoided the need to merge the higher quality land data with TOPEX

satellite data.

I used a generalized model inspired by a COCORP seismic reflection line in Kansas

[Serpa et al., 1984], as reinterpreted by Woelk and Hinze [1991]. This model has mafic

26

intrusions, a sedimentary basin overlying a large basaltic body, and large flanking sedimentary

basins. Thomas and Teskey [1994] infer that sedimentary rock densities in the northern MCR

range from 2.25 to 2.66 g/cm3 depending on the geologic unit. I use densities of 2.63g/cm3 in the

central basin, and 2.55 g/cm3 in the flanking basins.

For simplicity I treat the mafic intrusions as single magmatic bodies represented by

equilateral trapezoids with a density of 3.00 g/cm3 underlain by a Moho extracted from

CRUST2.0 [Bassin et al., 2000] (Figures 2.2, 2.3). A best fitting model for each profile was

found by a grid search (Figure 2.4). I also ran these models with mafic densities of 2.94 and 3.06

g/cm3. Two additional modeling schemes were also tested, one using Moho depths from NA07

[Bedle and van der Lee, 2009] (Figure 2.5, 2.6) and the second including a shallow basalt slab

beneath the central basin (Figure 2.7, 2.8). The volumetric trends are similar for all model sets.

2.3 Results and Interpretation

The models give insight into differences between the arms of the MCR. The Michigan

basin overlies the east arm, and the west arm has a higher central gravity anomaly with large

flanking negative anomalies. Figure 2.2 and 2.3 show how these differences manifest in the

gravity models. Because the Michigan basin is not centered on the rift, its sediments appear as a

gently dipping layer over the entire area that has little effect on the gravity models. The west

arm's more intense central anomalies are modeled by larger rift magmatic intrusions. The

negative anomalies on this arm's flanks are modeled as large sediment-filled flanking basins,

which are deeper than the central basin. This geometry reflects the tectonic inversion that raised

27

the central portion of the rift. Similar flanking basins are also present in the east arm models, but

are similar in depth to the central sediment basin.

By integrating the cross sectional areas of the intrusions along the rift (Figure 2.9), I

estimate the total magma volume, excluding the Lake Superior region, as between 8.69x105 and

1.2x106 km3. Scaling this volume to the total length of the rift gives a range of 1.34x106 to

1.85x106 km3 for the entire MCR. This agrees well with previous estimates for the entire MCR

of 1.3x106 km3 [Hutchinson et al., 1990].

Examination of the variation in cross sectional areas along the rift shows clear trends.

First, the volume of magma increases towards the Lake Superior region (Figure 2.9A), where

thick basalt assemblages are known to exist. This trend is consistent with magma flowing away

from a source in the Lake Superior region. Second, the west arm has significantly more magma.

This difference is not an obvious consequence of flow from a northern source, although it not

precluded by such a model.

28

Figure 2.2 Five gravity models of the west arm used for interpretation. Black dots are observed gravity, from PACES database; black line is calculated gravity.

Basement, Density = 2.67

Mafics, Density = 3.00

Sediments, Density = 2.55


-30

0

30

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Line 1

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Distance (km)

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29

Figure 2.3: Four gravity models of the east arm used for interpretation. Black dots are observed gravity, from PACES database; black line is calculated gravity.

mG

al

-100

102030

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0 50 100 150

Line 9

mG

al

Distance (km)

Dep

th (

km)





Michigan basin sediments Density = 2.63

30

Figure 2.4: Example of misfit plots for mafic trapezoid size. The X/Y axes refer to the size of base 1, and 2 of the basaltic trapezoid in the gravity models. Each contour plot is for a trapezoid of a different height. The grey area of each plot is excluded because base 1 is not allowed to be larger than base 2. Black dot shows the model that was chosen.

31

Figure 2.5: Gravity models of the west arm using the Moho depth from NA07. Black dots are observed gravity, from PACES database; black line is calculated gravity.

mG

al

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West Arm





32

Figure 2.6: Gravity models of the east arm using the Moho from NA07. Black dots are observed gravity, from PACES database; black line is calculated gravity.

mG

al

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33

Figure 2.7: Gravity models of the west arm including a shallow basalt slab 3km thick with a width the same as the central sediment basin. Black dots are observed gravity, from PACES database; black line is calculated gravity.

mG

al

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34

Figure 2.8: Gravity models of the east arm including a shallow basalt slab 3km thick with a width the same as the central sediment basin. Black dots are observed gravity, from PACES database; black line is calculated gravity.

However, the magma volumes are consistent with a model (Figure 2.10) in which the two

rift arms acted as boundaries of a microplate. Chase and Gilmer [1973] found an Euler pole for

such a model by treating offsets in the gravity maxima as transform faults, and using the width of

the central gravity anomaly as a measure of total spreading. As shown, the volume of magma I

infer along the west arm increases with distance from the Euler pole (Figure 2.9B). Thus the

mG

al

-200

2040


Dep

th (

km)

40

30

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al

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East Arm






35

results of analyzing more recent gravity data are also consistent with the microplate model.

Moreover, the much smaller volumes of magma along the east arm are consistent with this arm

being a leaky transform, along which trans-tensional motion permits some magmatism.

Figure 2.9: A) Cross sectional magma areas in the models plotted as a function of distance from the Lake Superior region. The areas increase toward the Lake Superior region and the west arm has significantly more magma than the east arm. B) Cross sectional magma areas in the models plotted against distance from the Chase and Gilmer [1973] Euler pole. Black bars show the range in cross sectional areas for the other four modeling schemes.

Viewing the MCR's evolution as showing rotation of a rigid microplate does not preclude

its having been started by a mantle plume. However, this view is consistent with the rift having

been part of an evolving regional plate boundary system [Whitmeyer and Karlstrom, 2007] rather

than an isolated episode of midplate volcanism.

0

200

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ss S

ectio

nal A

rea

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Mid-Continent Rift Magma Variation

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ss S

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Mid-Continent Rift Magma Variation

A B West armEast arm

West armEast arm

1

2

3

45

67

89 1

2

3

45

67

89

36

Figure 2.10: Schematic microplate model with the Wisconsin Block rotating away from the Superior Province. This microplate model is consistent with the magma variations shown in Figure 2.9B.

37

CHAPTER 3

Was the Mid-Continent Rift part of a successful seafloor-spreading episode?

38

3.1 Introduction

One of the most prominent features on gravity and magnetic maps of North America is

the Mid-Continent Rift (MCR), a band of buried mafic igneous rocks extending from Lake

Superior (Figure 3.1). These rocks outcrop from Minnesota through Wisconsin and the Upper

Peninsula of Michigan. To the south the rift is deeply buried by younger sediments, but easily

traced because the igneous rocks are dense and highly magnetized [Hinze et al., 1992; King and

Zietz, 1971]. Its west arm extends at least to Oklahoma, and perhaps Texas and New Mexico via

similar-age diffuse volcanism [Adams and Keller, 1996]. The east arm goes through Michigan

and extends southward along the Fort Wayne Rift (FWR) and East Continent Gravity High

(ECGH) to Alabama [Keller et al., 1982]. In Alabama, the gravity and magnetic anomalies have

been interpreted as indicating mafic rocks [Steltenpohl et al., 2013].

3.2 Gravity Analysis

The residual Bouguer anomaly gravity map (Figure 3.1) was calculated by upward

continuing complete Bouguer anomaly (CBA) data (Figure 3.2) to 40 km (Figure 3.3) and

subtracting the result point-by-point from the CBA grid. Upward continuation acts as a low pass

filter that attenuates shorter wavelength anomalies and so smoothes the data [Blakely, 1996], as

demonstrated in Figure 3.3. The gravity highs associated with the MCR, FWR, and ECGH still

appear strongly, trending in the same directions as in the CBA map. Subtracting the upward

continuation result removes the long wavelength anomalies and hence emphasizes shallower

39

features (Figure 3.1). The gravity lows associated with the flanking rift are more pronounced,

particularly in Michigan [Buening, 2013].

Figure 3.1: Gravity map showing Midcontinent Rift (MCR), Fort Wayne Rift (FWR), and East Continent Gravity High (ECGH), computed by upward continuing complete Bouguer anomaly (CBA) data to 40 km and subtracting result from CBA, from PACES database. Grenville-age Appalachian inliers with Laurentia and Amazonia affinities are shown as light and dark grey regions. Grenville Front shown by solid line where observed and dashed lined where inferred.

MC

R

Llano Uplift

Grenville

AdirondacksGre

nville

Age

Appal

achia

n Inlie

rs

Front

(map

ped)

FWR

EC

GH G

r en

vil le

Fr o

nt

Oua

chita

Cam

bria

n

Mar

gin

104°W53°N

70°W53°N

70°W27°N

104°W27°N

400 KILOMETERS

-110

-40

-60

-50

056

mGal

40

Figure 3.2: Complete Bouguer gravity anomaly, from PACES database, for eastern United States.

104°W53°N

70°W53°N

70°W27°N

104°W27°N

MILES2,000

-110

-40

-60

-50

0

56mGal

41

Figure 3.3: Gravity anomaly, from PACES database, upward continued to 40 km.

3.3 Microplate Formation During Continental Rifting

In what tectonic setting the MCR formed remains unclear, despite its prominence. It

formed at about 1.109-1.085 Ga within Laurentia, the core of the North American continent

assembled in the Precambrian, by volcanism [Davis and Green, 1997; Nicholson et al., 1997]

and normal faulting followed by subsidence and sedimentation [Cannon, 1992]. Hence it is

104°W53°N

70°W53°N

70°W27°N

104°W27°N

MILES2,000

-110

-40

-60

-50

0

56mGal

42

commonly viewed as a type example of a failed rift that formed and died within a continental

interior, far from its margins, not associated with a plate boundary or successful rifting/seafloor-

spreading event.

A difficulty with this view is that many intracontinental rifts are associated with plate

boundary reorganizations (Figure 3.4). Present-day continental extension in the East African Rift

(EAR) and seafloor spreading in the Red Sea and Gulf of Aden form a classic three-arm rift

geometry as Africa splits into Nubia, Somalia, and Arabia. GPS and earthquake data show that

the opening involves several microplates between the large Nubian and Somalian plates [Saria et

al., 2013]. If the EAR does not evolve to seafloor spreading and dies, in a billion years it would

appear as an isolated intracontinental failed rift similar to the MCR.

Another analogy is the West Central African Rift (WCAR) system formed as part of the

Mesozoic opening of the South Atlantic. Reconstructing the fit between Africa and South

America without overlaps and gaps and matching magnetic anomalies requires microplate

motion with up to 95 km extension within continents [Moulin et al., 2010; Seton et al., 2012].

These rifts failed about when seafloor spreading started along the whole boundary between

South America and Africa, illustrating that intracontinental extension can start as part of

continental breakup and end when full seafloor spreading is established.

Although similar rift systems occur earlier in the geological record, it is harder to identify

them and establish their history because the plates involved are now widely separated and

sometimes affected by subsequent continent-continent collisions that overrode the rifted

43

continental margins. Also, the oceanic seafloor with its magnetic reversal record that formed

after the continents rifted has been subducted.

As just discussed, active rifts within continents with similar lengths to the MCR form

boundaries of microplates within the evolving boundary zone between major plates. Similarly,

the MCR can be described as part of a microplate’s boundary [Chase and Gilmer, 1973]. Magma

volumes inferred from gravity modeling (Chapter 2) [Merino et al., 2013] are consistent with the

western arm opening mainly by extension and the eastern arm in Michigan as a leaky transform.

Figure 3.4: Microplate formation during continental rifting. (A) Present rifting of Africa into three major plates and three microplates, after Saria et al. [2013]. (B) Four-microplate geometry of the west central African rift system, formed during the Mesozoic opening of the South Atlantic, after Moulin et al. [2010].

44

3.4 Apparent Polar Wander Path

The apparent polar wander path for Laurentia in Figure 3.5 contains paleomagnetic poles

from Elming et al. [2009] and Swanson-Hysell et al. [2009]. Prior to the formation of the MCR I

use the 1.235 Ga pole for the Sudbury Dykes (1, blue), 1.204 Ga Upper Bylot (2, blue), and

1.141 Ga pole for the Abitibi Dykes (3, blue). For the MCR, I primarily use the best-dated sites,

those from Mamainse Point (4-8, red) determined by Swanson-Hysell et al. [2009]. These dates

[http://www.swanson-hysell.org/research/keweenawan/] range from about 1.109-1.094 Ga with

the exception of one somewhat younger paleopole. I also use two somewhat younger paleopoles

from Swanson-Hysell et al. [2009] for the ~1.095 Ga Portage Lake Lavas (9, red) and the ~1.087

Ga Lake Shore Traps (10, red).

For the post-rift sediments of the MCR [Ojakangas et al., 2001] I use only those from the

Oronto Group (Copper Harbor Conglomerate (oldest, 11, green), Nonesuch Shale (12, green) and

Freda Sandstone (youngest, 13, green). The Copper Harbor Conglomerate pole plots near the

igneous MCR path, unlike the two younger formations. Halls and Palmer [1981] note that the

direction of magnetization of the Copper Harbor sediments is "virtually indistinguishable" from

the Portage Lake volcanics and thus may have been reset due to the interlayering volcanic

intrusions and/or are of similar age. Thus these sediments may have been deposited during the

rifts opening. Because the Bayfield Group near the MCR may be significantly younger than the

Oronto Group, I do not use its paleomagnetic pole. The youngest pole shown is for the 1.015 Ga

Halliburton Intrusions (14, black).

45

3.5 Laurentia, Amazonia, and the MCR

I propose that the MCR’s formation and shutdown was part of the evolution of the plate

boundary between Laurentia and neighboring plates. The location and timing of key events

relevant to the MCR’s evolution fit nicely into the known history of plate interactions. Absent a

seafloor spreading record, reconstructions based on paleomagnetic data provide a general view

of this evolution.

Interpretation of a loop in Laurentia's apparent polar wander (APW) path (Figure 3.5A),

often referred to as the Logan Loop, has been unclear. The loop could have resulted from an

irregularity in the earth's magnetic field ~1.11 Ga (a reversal asymmetry or non-dipolar field

component) or an unspecified plate tectonic event [Halls and Pesonen, 1982]. Volcanic rocks in

the MCR formed during this period and hence record the change in the earth's magnetic field and

Laurentia's APW path. Using high-resolution paleomagnetic data, Swanson-Hysell et al. [2009]

showed that there was no asymmetry in the reversals. I thus propose that the cusp in Laurentia’s

APW path [Elming et al., 2009; Swanson-Hysell et al., 2009] likely reflects plate motion changes

due to rifting, in part involving the MCR. Cusps in APW paths have been observed when

continents separate and a new ocean forms between the two fragments. For example, cusps in

North America’s path coincide with the 90 Ma rifting of Europe from North America and the

180 Ma rifting of Gondwana from Laurasia [Gordon et al., 1984].

Likely the ~1.11 Ga cusp reflects rifting between Laurentia and Amazonia (Precambrian

northeast South America). In some models, Amazonia was in contact with Laurentia ~1.2 Ga

[Tohver et al., 2002] (Figure 3B), moved left-laterally until about 1.12 Ga [Tohver et al., 2006],

46

and then moved away. These interactions are recorded in the rock record. The absence of

igneous rocks younger than ~1.23 Ga in the Llano uplift (Texas) area is interpreted as indicating

the ending of a subduction episode [Mosher et al., 2008]. By 1.2 Ga, intracontinental rifting in

Amazonia is recorded in the Nova Brasilândia region [Teixeira et al., 2010]. Amazonia’s

subsequent left lateral motion relative to Laurentia is recorded by deformation in the Ji-Paraná

shear network from 1.18-1.12 Ga [Tohver et al., 2006]. The beginning of its separation from

Laurentia is indicated by recently dated ~1.110 Ga mafic rocks in Rincón del Tigre and

Huanchaca in the SW corner of the Amazon craton [Ernst et al., 2013] and renewed igneous

activity in Nova Brasilândia [Teixeira et al., 2010; Tohver et al., 2006].

47

Figure 3.5: (A) Apparent polar wander path for Laurentia, showing cusp approximately at onset of MCR volcanism (1.109 Ga) that likely reflects the rifting. Poles from Elming et al. [2009] and Swanson-Hysell et al, [2009]. (B) Reconstruction of plate positions before Laurentia-Amazonia separation, after [D'Agrella-Filho et al., 2008; Elming et al., 2009; Tohver et al., 2002], schematic rift geometry, and relevant features.

48

Because the MCR formed while Amazonia rifted from Laurentia, it seems likely that the

rifting events are related. Mafic dikes and other intrusions started north and west of Lake

Superior ~1.15 Ga and continued for 40 my [Heaman et al., 2007]. The huge volume of MCR

volcanism started around Lake Superior at ~1.109 Ga [Davis and Green, 1997], approximately

the same time as volcanism within the SW part of the Amazonian craton [Ernst et al., 2013].

3.6 Reconstructions Using Paleomagnetic Data

Paleomagnetic reconstructions (Figure 3.5B) [D'Agrella-Filho et al., 2008] place SW

Amazonia near the southern end of the East Continent Gravity High, an extension of the MCR’s

eastern arm. Hence the MCR probably connected to the extensional system that separated the

two continents. In this scenario, MCR volcanism ended once motion was taken up by seafloor

spreading between Laurentia and Amazonia.

After extension ended, normal faults in the MCR region were reactivated as reverse faults

~1.06±0.02 Ga [Cannon et al., 1993]. The compression is assumed to be associated with

collisional tectonics during the Grenville orogeny [Soofi and King, 2002], the ~1.3-0.98 Ga

assembly of Amazonia and other continents into the supercontinent of Rodinia [Dalziel et al.,

2000; Hoffman, 1991; McLelland et al., 2010]. Most of the best-exposed Grenville deformation

is found along the eastern Canadian margin. Grenville-age orogenic events are also found in the

south and southwestern United States and South America. The Grenville Front in Canada is the

boundary between the deformed Grenville fold and thrust belt and areas in the interior of

Laurentia largely unaffected by Grenville deformation. In most of the United States this

49

boundary is inferred from gravity and magnetic data. In Texas the boundary is called the Llano

Front and associated deformation is recorded in the rocks of the Llano uplift south of the front.

3.7 Discussion

The scenario proposed here is consistent with the recent recognition that the central and

south Appalachians were not part of Laurentia before the Grenville orogeny. Although

Grenville-age Appalachian inlier rocks in the Adirondacks have affinities to Grenville rocks in

Canada, most of those to the south are more similar to Amazonia [Fisher et al., 2010; Loewy et

al., 2003; McLelland et al., 2010]. They lack a petrologic signature of the ~1.5-1.3 Ga Granite-

Rhyolite province formed within Laurentia [Fisher et al., 2010], suggesting that they were not

part of Laurentia before the Grenville orogeny.

My scenario addresses events 1.1 billion years ago, when the geologic record is limited

and sparse because many areas are deeply buried, have been eroded, or have been subsequently

deformed. Because many aspects of Laurentia – Amazonia rifting and Rodina’s assembly during

the Grenville remain unresolved, my scenario is schematic. I attribute MCR formation to

Laurentia – Amazonia rifting, which – depending on unresolved issues in reconstruction - also

may be related to contemporaneous large igneous provinces and possible rifting in the Indian,

Congo, and Kalahari cratons [Ernst et al., 2013] recorded by APW path cusps [Gose et al.,

2013].

In my model rifting does not result from Grenville collisional events, as sometimes

proposed [Gordon and Hempton, 1986]. Instead, it results from rifting during the Grenville at a

50

time when compression was absent or occurred elsewhere. Probably because of lack of

exposure, it is commonly assumed that Grenville-age tectonics along the present U.S. to Mexico

margin should have been similar to those recorded by Grenville-age rocks exposed in Canada.

However, this need not have been the case. This margin’s length is comparable to that from

Turkey to Gibraltar, along which tectonics varies with space and time during the Cenozoic.

Similarly, events associated with the formation of the Paleozoic Appalachian-Caledonian

mountains differ along the length of the system.

In summary, rather than viewing the largest gravity and magnetic anomaly within the

North American craton as an exotic feature, I view the MCR’s formation and evolution in a plate

tectonic context consistent with what we know of plate motions then and analogous rifting

events. Additional data will be required to test this scenario. One promising source is the

EarthScope program, which is acquiring new data about lithospheric structure below the MCR

[Shen et al., 2013; Stein et al., 2011]. Data across its possible extensions to the south and the

Grenville Front will show more about these structures and possible relations between them. My

model suggests that the East Continent Gravity High should appear similar to the MCR, and that

there may be additional evidence of the rifted margin between Amazonia and Laurentia.

51

CHAPTER 4

Comparison of Seismicity Rates in the New Madrid and Wabash Valley Seismic Zones

52

4.1 Introduction

The Wabash Valley seismic zone in southern Illinois and Indiana is the northeastern

extension of the New Madrid seismic zone (Figure 4.1). Like New Madrid, the Wabash zone is

underlain by a failed Precambrian failed rift, which plays a role in controlling the recent faulting

[Braile et al., 1986; Sexton et al., 1986; Bear et al., 1997]. Paleoliquefaction deposits indicate the

past occurrence of large earthquakes in the Wabash zone [Obermeier, 1998] that may have been

comparable to those that occurred in the New Madrid zone in 1811-1812 [Hough et al., 2000].

The two areas seem likely to be mechanically coupled in that stress transfer following large

earthquakes in one could affect earthquake occurrence in the other [Mueller et al., 2004].

Numerical modeling indicates that stress transfer following the 1811-1812 New Madrid

earthquakes may be loading faults in the Wabash zone [Li et al., 2005; 2007].

Despite their similarities, the two zones have an intriguing difference in seismicity rates

[Stein and Newman, 2004]. This difference is shown in Figure 4.2A by comparison of frequency-

magnitude plots. The plots combine the CERI catalog of seismologically recorded small

earthquakes spanning January 1975 - June 2010

(http://www.ceri.memphis.edu/seismic/catalogs/cat_nm.html) and the Nuttli catalog of historic

earthquakes for 1804 - 1974 with magnitudes out to magnitude 6.2 [Nuttli, 1974].

4.2 Results

Both areas show a Gutenberg-Richter distribution of seismicity, log10N = a – bM, where

the logarithm of the annual number (N) of earthquakes above a given magnitude (M) decreases

53

linearly with magnitude (Figure 4.2A). A least squares fit to the New Madrid zone data (defined

as 35-38°N, 88-91°W) yields a=3.45 and b=0.95 � 0.02. The Wabash zone (treated here as

37.6°-39.7°N, 85.8°-88.75°W) yields a=2.13 and b=0.72 � 0.03. (These areas, defined as

rectangular for simplicity, have a slight overlap). Hence the New Madrid and Wabash zones have

similar numbers of magnitude 5-6 earthquakes, but the larger slope (b) indicates that New

Madrid has more small earthquakes.

54

Figure 4.1: Seismicity map of central United States. Main 1811-1812 earthquakes represented by stars. New Madrid Seismic Zone (NMSZ), Wabash Valley Seismic Zone (WVSZ), Reelfoot Rift (RFR).

55

Figure 4.2: (A) Frequency-magnitude plots for New Madrid and Wabash seismic zones and (B) comparison of these zones with the central U.S.

The b value difference does not appear to result from the limitations of the data, which

are common to both zones. This analysis combines instrumentally determined magnitudes for

recent smaller earthquakes with ones inferred from historical records of older larger earthquakes.

The linear trend continues relatively smoothly between the two data types. The results are robust

in that they are consistent with those of previous studies combining the historical data with

progressively longer instrumental records [Nuttli, 1974; Johnston and Nava, 1985; Stein and

Newman, 2004]. Catalog incompleteness appears not to be a problem given the lack of a falloff

at low magnitudes considered. Thus although the specific b values derived here (as in any area)

depend on the dataset and analysis method used, the difference in b values between the two

seismic zones seems real.

Historical

1 2 3 4 5 7Magnitude

6

0.01

0.1

1

10

100

Ear

thqu

ake

Rat

e 1/

yr

1 2 3 4 5 7Magnitude

6

0.01

0.1

1

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100

Ear

thqu

ake

Rat

e 1/

yr

New MadridWabash

Central U.S

Central U.S without NewMadrid and Wabash

A B

56

4.3 Discussion

I see two possible causes for the b value difference. The first is that the Wabash area has

a low b value. A low b value could indicate high stressing rates on faults [Scholz, 1968; Wiemer

and Wyss, 1997]. Hence a low value in the Wabash could mean a higher stressing rate there than

in the New Madrid zone for the period spanned by these data, since 1812. This would be

consistent with the predicted stress migration following the large 1811-1812 earthquakes [Li et

al., 2005; 2007].

Alternatively, the New Madrid zone has a high b value. This situation could arise if many

of the earthquakes there are aftershocks of the large 1811-1812 earthquakes [Ebel et al., 2000;

Stein and Newman, 2004; Hough, 2009; Stein and Liu, 2009]. b values for many aftershock

sequences are higher than those found by including the main shocks [Frohlich and Davis, 1993].

This may be the case here, because the data used do not include the three main shocks, owing to

the complexities in assessing their magnitudes [Hough et al., 2000].

Given that b values for different areas vary widely, largely between 0.5 and 2.0 [Frohlich

and Davis, 1993], I assess whether the values for the two areas are “high” or “low” by

comparing them to those for the entire central U.S., defined here as 34.5°-41°N, 85°-92°W

(Figure 4.1). For this region, a=3.57 and b=0.9 � 0.02 (Figure 4.2B). However, considering

earthquakes in this region but excluding both the New Madrid and Wabash zones yields a=0.9

and b=0.83 � 0.02, because most small events are in the New Madrid zone.

Thus the Wabash valley b value is lower than New Madrid’s but closer to that for the central

U.S. excluding both zones. Hence I view the Wabash value as more typical of the central U.S.,

57

and New Madrid value as unusually high.

This interpretation is supported by the fact that low b values are common for intraplate

areas. Global compilations of intraplate earthquakes with magnitudes between about 4 – 6.5

yield b values of 0.6-0.85 (Figure 4.3). Similar values arise for some specific intracontinental

areas [Jaiswal and Sinha, 2007; Sykes et al., 2008].

Figure 4.3: Frequency-magnitude plots for global intraplate earthquake datasets. Data denoted by squares were not analyzed due to expected catalog incompleteness. Data for intermediate and large magnitudes were analyzed separately. [Okal and Sweet, 2007].

58

Hence although it is typical to view b about 1 as the normal state of affairs, it is not

universal. My view reflects the fact that such b values usually result from data – often primarily

from global datasets primarily from plate boundaries - spanning a broad range of magnitudes up

to magnitude 8 [Okal and Romanowicz, 1994].

It thus appears that the difference between the New Madrid and Wabash b values reflects

the New Madrid seismicity being dominated by aftershocks of the 1811-1812 earthquakes.

Hence the lower Wabash value need not indicate loading by stresses due to these large

earthquakes. Thus assessing whether such loading is occurring will require assessing whether the

associated strain signal is resolvable in GPS data [Galgana and Hamburger 2010]. If so, the

strain rate signal will become increasingly apparent with time because GPS velocity precision

increases for longer measurement intervals [Stein and Wysession, 2003].

59

CHAPTER 5

Have We Seen the Largest Earthquakes in Eastern North America?

60

5.1 Introduction

The 2011 Virginia earthquake that shook much of the northeastern U.S. showed that

earthquakes large enough to cause significant damage occur in eastern North America, a

‘stable’ intraplate region [Wolin et al., 2012] (Figure 5.1). Assessing the hazard of such

earthquakes poses major unresolved issues. Hazard maps, giving the maximum shaking

expected in an area with a certain probability in some time period [Cornell, 1968], require

assuming where and when large earthquakes will occur and how large they will they be.

However, the recent Tohoku, Haiti, and Wenchuan earthquakes illustrate that earthquakes

much larger than expected occur in many places [Geller, 2011; Gulkan, 2013; Kerr, 2011;

Peresan and Panza, 2012; Stein and Okal, 2011; Wyss et al., 2012]. Such surprises arise

because parameters required to reliably estimate the hazards are often poorly known

[Stein et al., 2012].

A crucial parameter is Mmax, the magnitude of the largest earthquake expected on a

fault or in an area [Stein et al., 2012]. The Tohoku, Haiti, and Wenchuan earthquakes were

more damaging than expected because they were much larger than the Mmax assumed in

hazard planning [Kanamori, 2011; Sagiya, 2011; Witze, 2009]. Unfortunately, no theoretical

basis exists to infer Mmax. Even where we know the long-term rate of motion across a plate

boundary fault, or the deformation rate across an intraplate zone, neither predict how

strain will be released. Strain release can occur seismically or aseismically, and seismic

strain release can occur via earthquakes with different magnitudes and rate distributions.

As a result, quite different Mmax estimates can be made [Kagan and Jackson, 2013;

61

Kijko, 2004; U.S Nuclear Regulatory Commission, 2012]. Because all one can say with

certainty is that Mmax is at least as large as the largest earthquake in the available record, it

was earlier practice to use that magnitude or add an increment. However, because catalogs

are often short relative to the average recurrence time of large earthquakes [Bell et al.,

2013; McGuire, 1977; Stein and Newman, 2004], larger earthquakes than anticipated often

occur. Another approach is to identify faults and use relations between fault length and

earthquake magnitude [Wells and Coppersmith, 1994] to infer Mmax. Other approaches

extrapolate from current catalogs [Kijko, 2004] or combine areas presumed to be

geologically similar to sample more large earthquakes [Kagan and Jackson, 2013; U.S.

Nuclear Regulatory Commission, 2012].

Estimating Mmax is challenging at plate boundaries, where known plate motion rates

can be compared to earthquake records on known faults to infer the slip in, and thus

magnitude of, large earthquakes. The situation is more complicated within plates, where

deformation rates are poorly known, large earthquakes are rarer and variable in space and

time, and often occur on previously unrecognized faults [Camelbeeck et al., 2007; Clark et

al., 2011; Crone et al., 2003; Leonard et al., 2014; Liu et al., 2011].

I explore this issue for eastern North America and Lower Rhine Embayment (LRE),

which includes portions of Belgium, Germany, and the Netherlands [Camelbeeck et al.,

2007]. Notable events along the U.S. margin include the 1755 Cape Ann Massachusetts and

1886 Charleston earthquakes. Larger earthquakes are known along the Canadian margin,

notably the 1929 Grand Banks and 1933 Baffin Bay events. Thus this passive continental

62

margin, like others, has a moderate level of seismicity [Schulte and Mooney, 2005; Stein et

al., 1979; Stein et al., 1989; Wolin et al., 2012]. The largest known event in the LRE is the M

5.7, 1756 Düren earthquake.

A challenge in assessing the earthquakes’ hazard is that we know little about their

causes, partly because they are relatively rare due to the slow deformation at such margins.

They may reflect reactivation of faults created by previous continental collision and

breakup, given that passive margins are often reactivated [Cloetingh et al., 2008].

Geodynamic modeling predicts stresses from variations in topography and crustal

structure across the margin, combined with sublithospheric mantle flow [Ghosh et al.,

2013].

63

Figure 5.1: Seismicity of the eastern North American continental margin taken from ANSS

and NEDB catalogs. Red and blue dots correspond to the U.S and Canadian margins

respectively. Major historical events are also shown.

64

A crucial issue is how much to rely on past large earthquakes, as illustrated by

successive Geological Survey of Canada hazard maps [Adams, 2011; Wolin et al., 2012]. The

1985 suite of maps concentrate hazard at the sites of the Grand Banks and Baffin Bay

earthquakes, assuming that these recently active areas are especially hazardous. The 2005

maps have an additional ribbon of hazard along the passive margin, assuming that similar

earthquakes can occur anywhere along the margin.

The observed seismicity may be an imperfect sample of a more uniform seismicity

as suggested by seismicity between the Grand Banks and Baffin Bay, some of which may be

aftershocks of prehistoric earthquakes [Basham and Adams 1983; Wolin et al., 2012].

Simulations with short catalogs yield apparent concentrations and gaps that are artifacts of

the sampling [Swafford and Stein, 2007]. Similarly, although seismicity in the eastern U.S is

patchy, geological observations show evidence of slow long-term deformation [Pazzaglia et

al., 2010] and the present seismicity occurs in areas that are not geologically or

geomorphologically different from nearby areas that appear aseismic.

A related question is whether the larger earthquakes and higher seismicity along the

Canadian margin represent a real difference from the roughly-orthogonal U.S. margin. The

difference could be real, perhaps due to stresses associated with deglaciation [Mazzotti et

al., 2005; Sella et al., 2007; Wolin et al., 2012] or how intraplate stresses interact with the

differently oriented margins, or might merely reflect the short earthquake record. I thus

consider the two regions separately and explore their differences.

65

5.2 Methods

Absent reliable ways of assessing Mmax, I use synthetic earthquake histories to

explore what Mmax values would be observed in a short catalog. I assume earthquakes

satisfy a Gutenberg-Richter frequency-magnitude relation, log10 N =a - bM, where N is the

annual number of earthquakes with magnitude ≥M, a defines the seismicity rate, and b is

the slope of the line relating the rates of small and large earthquakes. The recurrence

interval between events for each magnitude is described by a Gaussian distribution about

the predicted mean rate. Thus events with magnitude ≥M have average recurrence time TrM

=10-(a-bM) years, with an assumed standard deviation of 0.4TrM. Each simulation has a

specified Mmax above which no earthquakes occur.

The regional a and b values for eastern North America were estimated from the

Advanced National Seismic System (ANSS) catalog from 1985-2013 for the eastern U.S, and

the Canadian National Earthquake Database (NEDB) from 1985-2013 for eastern Canada.

All earthquakes along the eastern Canadian margin and near Hudson Strait (an area of

weak extension during the opening of the Atlantic) were defined to be eastern Canada

passive margin earthquakes (Figure 5.1). Eastern U.S. earthquakes were selected by taking

all earthquakes within 6° of the margin. Earthquakes near the historical Grand Banks

earthquake are assigned to the eastern Canada margin. The regional a and b values were

calculated by the Maximum Likelihood (MLE) method, which is sensitive to the

completeness of the catalog, with a minimum magnitude cutoff of 4.0 for eastern Canada

and the eastern U.S. (Figure 5.2).

66

A linear Gutenberg-Richter relationship can be fit to a set of frequency-magnitude

data using either MLE or Least Squares (LSQ) estimates, each with advantages and

disadvantages. In general, a least-squares fit characterizes large-magnitude occurrences

better, but thus may not match the rate of the smaller ones well. Conversely, MLE weights

lower magnitudes heavily and so gives more stable estimates of the distribution’s b value

(slope). Thus if one expects that the data come from a Gutenberg-Richter distribution, such

that the deviations from the linear trend are artifacts of sampling or otherwise, MLE

estimation is preferable. As a result, most seismic hazard analyses use MLE. Conversely, if

one approaches the data without this expectation, LSQ can be viewed as a better

characterization of the data themselves.

Figure 5.2: Frequency-magnitude relationships calculated for the eastern U.S (left panel)

and eastern Canada (right panel) datasets. Green line is for the MLE fit. Red line is for the

LSQ fit. The MLE results are used as inputs to the simulations.

−2

−1

0

1

4 5 6

Magnitude

MLE - b = 0.92 ± 0.10

LSQ - b = 1.03 ± 0.03

MLE - b = 0.94 ± 0.09

LSQ - b = 1.00 ± 0.02

Eastern U.S. Eastern Canada

−2

−1

0

1

Log

(N/Y

r)

4 5 6

Magnitude

67

5.3 Eastern North America Results and Analysis

For the U.S. margin I use a=4.24 and b=0.92, calculated from recent seismicity,

corresponding to a M≥7 earthquake on average every ~150 years. I generate four sets of

10,000 histories that are 65,000 years long, assuming that Mmax is 7.0, 7.2, 7.4, and 7.6. We

take a 300-year sample of each history, corresponding to the period over which all large

(M≥6) earthquakes are likely to be known. Samples start 5000 years into the simulation to

ensure that ‘now’ has no significance.

Figure 5.3 illustrates three representative histories. These are long enough to

adequately represent the rates of small earthquakes, which define a line corresponding to

the parent distribution. However, because the 300-year sampling interval corresponds to

the recurrence interval of M=7.3 earthquakes, larger events are undersampled.

As a result, two biases can arise. In one, the largest "observed" earthquake is smaller than

in the parent distribution, so b is biased upward (steeper slope), underestimating the rate

of large earthquakes. In the other, the largest earthquakes are "observed", but their

recurrence interval and thus b are underestimated. Hence the short history causes us to

either underestimate Mmax when earthquakes of this size do not appear, or better estimate

it but conclude that such earthquakes are more common than they really are [Stein and

Newman, 2004]. These effects can be visualized by considering the parent distribution of

recurrence times. Records shorter than the mean recurrence time of the largest events are

likely to not contain these events. If they contain such events, these events have apparent

68

recurrence times shorter than the mean, implying that they are more common than

actually the case.

Figure 5.3: Frequency-magnitude results for three of the histories (different colors)

generated with the eastern U.S simulations with; Mmax=7.6, a=4.24, b=0.92. These histories

are long enough to adequately represent the rates of small earthquakes. However, because

the 300-year sampling interval corresponds to the recurrence interval of magnitude ~7.3

earthquakes, larger events with longer recurrence times are undersampled. As a result,

maximum likelihood (MLE) and least-squares (LSQ) fits to the data differ.

Figure 5.3 also illustrates different ways of inferring the Gutenberg-Richter

distribution’s parameters. If short sampling causes the rate of large earthquakes to deviate

from that extrapolated from small ones, LSQ characterizes larger magnitudes better and

thus may not match the rate of the smaller ones well. MLE [Aki, 1965; Weichert, 1980]

weights the more populous lower magnitudes heavily and thus can misfit larger magnitude

69

data points. Analyses seeking to estimate b typically use MLE. The two methods give

different b values and hence different recurrence time predictions for large events.

Figure 5.4 shows Mmax values “observed” for the U.S. eastern margin synthetic

earthquake histories. The most common values vary depending on the assumed Mmax, but

are ~7.3 for simulations with large Mmax, corresponding to 300-year sampling. Even when

Mmax is significantly larger, it rarely appears. For example, Mmax=7.6 occurs in only 10% of

the simulations. The most common “observed” value is close to the inferred magnitude for

the Charleston earthquake.

Figure 5.4 shows analogous results for eastern Canada for a=4.44 and b=0.94,

calculated from recent seismicity, corresponding to an earthquake with M≥7.2 on average

every 212 years. I simulate histories for Mmax=7.4, 7.6, 7.8, and 8.0 that are 40,000 years

long and are sampled for 100 years, the period over which all large (M≥6) earthquakes are

likely to be known. The most common Mmax values “observed,” about 6.8, reflect the sample

length even when the parent distribution Mmax is significantly larger. For example, Mmax =

8.0 appears in only ~2% of the runs. The most common “observed” value is lower than the

Grand Banks and Baffin Bay earthquakes, but observing M=7.4 like Baffin Bay is not

uncommon.

70

Figure 5.4: Top: Results for four sets of 10,000 simulations for the eastern U.S margin, each

with a different Mmax. Panels show the percentage of simulations in which a given apparent

Mmax is observed. Dashed line represents the actual observed Mmax of 7.0, corresponding

approximately to the Charleston earthquake. Bottom: Simulations for eastern Canada

margin. Dashed line represents the actual observed Mmax of 7.4 from the Baffin Bay

earthquake.

Figure 5.5 illustrates the combined uncertainties in Mmax and b value estimated for

the eastern U.S simulations with Mmax of 7.6. The simulated catalogs are the same for the

MLE and LSQ calculations. MLE yields tightly grouped b values. In contrast, LSQ has more

scatter in b value and a strong tradeoff between b value and Mmax , because the line fits the

larger magnitudes better. As a result, it less likely to recover the parameters of the parent

distribution (dot).

These differences in the b-value distributions are illustrated by the standard

deviations in the eastern U.S margin simulations with an Mmax of 7.6, which are 0.01 and

71

0.06 for MLE and LSQ, respectively (Figure 5.6). The b values calculated by MLE and LSQ

both have Gaussian distributions (Figures 5.6, 5.7). The combined uncertainties for the

eight sets of simulations in figure 5.4 are illustrated in figure 5.8. As expected, b values are

recovered well whereas Mmax is generally underestimated, as the actual value lies well

outside the most frequently estimated values.

Figure 5.5: Distribution of apparent Mmax and b-value results for a set of simulations

sampling a parent distribution whose value is shown by the dot. Left: MLE; Right: LSQ.

The uncertainties in a and b values correspond to uncertainties in the estimated

recurrence times. For the eastern U.S., the 95% confidence range for a M=7.6 earthquake’s

recurrence interval ranges from approximately 430 to 675 years, for the MLE method

(Figure 5.9). This range would give an uncertainty in the estimated hazard and increase it.

Such uncertainty can be included in seismic hazard models via logic trees.

0.75

0.80

0.85

0.90

0.95

1.00

1.05

1.10

1.15

1.20

6.0 6.4 6.8 7.2 7.6Apparent Mmax

1

2

3

4

5

% o

f Si

mul

atio

ns

0.75

0.80

0.85

0.90

0.95

1.00

1.05

1.10

1.15

1.20

b va

lue

6.0 6.4 6.8 7.2 7.6

Apparent Mmax

Eastern United StatesMLEMmax 7.6

Eastern United StatesLSQMmax 7.6

72

Figure 5.6: b-value results for the four sets of 10,000 simulations for the eastern U.S

margin, each with a different Mmax and a=4.24, b=0.92 Top: Panels show the percentage of

simulations in which a given b value, calculated by the MLE method, is observed. Bottom:

Results using the LSQ method to calculate b values.

Figure 5.7: b-value results for the four sets of 10,000 simulations for the eastern Canada

margin, each with a different Mmax and a=4.44, b=0.94. Top: Percentage of simulations in

which a given b value, calculated by the MLE method, is observed. Bottom: Results using

the LSQ method to calculate b values.

73

Figure 5.8: Distributions of MLE estimates for the eight sets of simulations in figure 5.4. As

expected, b values are recovered well whereas Mmax is generally underestimated. Dot

indicates parent distribution parameters.

Figure 5.9: Recurrence time distribution for a M=7.6 earthquake in the eastern U.S.

corresponding to the results of simulations with an Mmax of 7.6. Left: MLE; Right: LSQ.

Dashed line is the parent distribution average value of 565 years.

0

5

10

15

20

25

0 30

0 60

0 90

0 12

00

1500

18

00

2100

24

00

2700

30

00

3300

36

00

% o

f S

imul

atio

ns

Recurrence Time

% o

f S

imul

atio

ns

0

5

10

15

20

325

375

425

475

525

575

625

675

725

775

825

% o

f Si

mul

atio

ns

Recurrence Time

EUSM = 7.6MLE

EUSM = 7.6LSQ

74

5.4 Lower Rhine Embayment Seismic Zone Results

I also briefly examined these issues for the LRE (Figure 5.10). I simulate histories for

Mmax= 6.2, 6.5, 6.8, and 7.1 that are 250,000 years long and are sampled for 700 years, the

period over which the historical seismicity is known for events with M ≥ 5 . Figure 5.11

shows results for the LRE seismic zone for a=2.772 and b=0.942, values calculated by the

Royal Observatory of Belgium by integrating recent and historical seismicity. The MLE

results (Figure 5.12) for the LRE seismic zone have a larger spread than the U.S. margin

because the smaller number of M ≥ 4.0 earthquakes, ~70 versus ~1100, which makes the

MLE results less stable. The most common Mmax value “observed” is 6.0. This case differs

from the eastern North America scenarios in that the simulations’ observed Mmax is likely

larger than the largest earthquake in the historical catalog (M5.7). For example, 78% of the

simulations with an Mmax of 7.1 yield an apparent Mmax greater than M5.7 (Table 5.1).

75

Figure 5.10: Map of Lower Rhine Embayment seismicity from Vanneste et al., [2013].

76

Figure 5.11: Results for four sets of 10,000 simulations for the Lower Rhine Embayment

seismic zone, each with a different Mmax. Panels show the percentage of simulations in

which a given apparent Mmax is observed. Dashed line represents the actual observed Mmax

of 5.7, corresponding to the 1756 Düren earthquake.

Figure 5.12: b-value results for the four sets of 10,000 simulations for the Lower Rhine

Embayment, each with a different Mmax and a=4.44, b=0.94. Top: Percentage of simulations

in which a given b value, calculated by the MLE method, is observed. Bottom: Results using

the LSQ method to calculate b values.

0

5

10

15

20

5.0

5.3

5.6

5.9

6.2

6.5

6.8

7.1

% o

f Si

mul

atio

ns

Apparent Mmax

0

5

10

15

20

5.0

5.3

5.6

5.9

6.2

6.5

6.8

7.1

% o

f Si

mul

atio

ns

Apparent Mmax

LREMmax 7.1

LREMmax 6.8

0

5

10

15

20

5.0

5.3

5.6

5.9

6.2

6.5

6.8

7.1

% o

f Si

mul

atio

ns

Apparent Mmax

LREMmax 6.5

% o

f S i

mu l

atio

ns

0

5

10

15

20

5.0

5.3

5.6

5.9

6.2

6.5

6.8

7.1

% o

f Si

mul

atio

ns

Apparent Mmax

LREMmax 6.2

0

10

20

30

0.40

0.

55

0.70

0.

85

1.00

1.

15

1.30

1.

45

1.60

% o

f Si

mul

atio

ns

b value

0

10

20

30

0.40

0.

55

0.70

0.

85

1.00

1.

15

1.30

1.

45

1.60

% o

f Si

mul

atio

ns

b value

0

10

20

30

0.40

0.

55

0.70

0.

85

1.00

1.

15

1.30

1.

45

1.60

% o

f Si

mul

atio

ns

b value

0

5

10

15

20 0.

40

0.55

0.

70

0.85

1.

00

1.15

1.

30

1.45

1.

60

% o

f Si

mul

atio

ns

b value

0

5

10

15

20

0.40

0.

55

0.70

0.

85

1.00

1.

15

1.30

1.

45

1.60

% o

f Si

mul

atio

ns

b value

0

5

10

15

20

0.40

0.

55

0.70

0.

85

1.00

1.

15

1.30

1.

45

1.60

% o

f Si

mul

atio

ns

b value

LRE, Mmax

6.5 LRE, Mmax

6.8 LRE, Mmax

7.1

b = 0.90 ± 0.07 b = 0.90 ± 0.07 b = 0.90 ± 0.07

b = 0.97 ± 0.15 b = 0.94 ± 0.16 b = 0.92 ± 0.17

0

10

20

30

0.40

0.

55

0.70

0.

85

1.00

1.

15

1.30

1.

45

1.60

% o

f Si

mul

atio

ns

b value

% o

f Si

mul

atio

n ss

b value

0

5

10

15

20

0.40

0.

55

0.70

0.

85

1.00

1.

15

1.30

1.

45

1.60

% o

f Si

mul

atio

ns

b value

LRE, Mmax

6.2

b = 1.02 ± 0.13

b = 0.90 ± 0.07

77

Mmax 6.2 Mmax 6.5 Mmax 6.8 Mmax 7.1 Percent of

simulations with observed Mmax >

M5.7

65% 73% 75% 78%

Table 5.1: Percent of simulations with differing Mmax that have apparent maximum

magnitudes above the 1756 Düren earthquake (M5.7).

5.5 Discussion

The simulations suggest that future earthquakes along both margins may be larger

than observed to date. Mmax for both margins may be the same, although if the higher

seismicity in Canada is real rather than a sampling artifact, large events would be more

common there. A complexity is that some of the higher Canadian seismicity rate may reflect

aftershocks of the two recent large earthquakes or of prehistoric earthquakes [Basham and

Adams, 1983; Wolin et al., 2012).

More generally, these simulations demonstrate that Mmax cannot be reliably

estimated from earthquake catalogs. The largest earthquake observed likely reflects the

length of the history used, even if larger earthquakes occur (Figure 5.13). Although the

precise fraction depends on the distribution of recurrence times, a catalog shorter than an

earthquake’s mean recurrence time is likely to not contain an event of that size.

78

Figure 5.13: Percentages of simulations that recover the input Mmax for varying catalog

lengths. Catalog lengths are given as a fraction of the mean recurrence time for earthquakes

with magnitude Mmax. Colors show results for Gaussian distributions of recurrence times

with standard deviation equal to the indicated fraction of the mean. A catalog shorter than

an earthquake’s mean recurrence time is likely to not contain an event of that size.

This effect is significant within plates where large earthquakes are infrequent, as in

the LRE seismic zone [Camelbeeck et al., 2007] or Australia [Leonard et al., 2014]. However,

as recent examples discussed earlier illustrate, it also arises at plate boundaries for

earthquakes larger than observed in the record used. Estimates of Mmax may be improved

by substituting space for time (ergodic assumption), though there is always an issue

whether different regions are “alike”. Estimates of the lower bound for Mmax can be

improved by paleoseismic investigation of active and apparently-inactive faults to assess

the size of past earthquakes over periods longer than the instrumental catalog [e.g.,

Camelbeeck et al., 2007]. Geodetic studies can constrain the minimum magnitude of future

0

20

40

60

80

100

0.1 0.25 0.5 1 2

% o

f Si

mul

atio

ns

Catalog lengthMmax mean recurrence time

SD 1.0

SD 0.4 SD 0.2

79

earthquakes from the strain accumulation rate and time since the last large earthquake

[Manaker et al., 2008]. However, there is no reliable way to infer an upper bound, although

various plausible assumptions can be made. Thus the only certainty about Mmax, is that is at

least as large as that observed to date, as in the adage “anything that did happen, can

happen.”

80

CHAPTER 6

Mantle flow beneath Arabia offset from the opening Red Sea

81

6.1 Introduction

The primary question about continental rifting is the chicken�and�egg issue of how

mantle flow and lithospheric extension are related. The initiation of rifting can be described by

end member models of either active rifting initiated by hot mantle material upwelling below a

continent and weakening it, or passive rifting initiated by stresses within the lithosphere due in

most cases to plate motions that thin the continent, causing mantle upwelling and volcanism

[Sengör and Burke, 1978]. The combined effects of these processes, whose sequence and relative

roles are unclear and likely vary between rifts, sometimes cause rifting to progress from

stretching and faulting the continental lithosphere to active seafloor spreading.

The relative roles of active and passive rifting are hard to resolve because they are

ongoing today in only a few places. The best examples are associated with the rifting of Arabia

from Africa (Figure 6.1). During the past 30 Ma, Arabia’s motion away from Nubia (West

Africa) and Somalia (East Africa) formed the Red Sea and Gulf of Aden [Le Pichon and

Gaulier, 1988; Bosworth et al., 2005; Garfunkel and Beyth, 2006]. The spreading centers in

these young ocean basins, together with the East African rift, are the arms of the Afar triple

junction. This system appears to have evolved as a result of a major episode of magmatism and

uplift beginning about 30–40 Ma that is interpreted as the beginning of the Afar hotspot [Ebinger

and Sleep, 1998; Courtillot et al., 1999] and forces due to the subduction of the Tethyan ocean

lithosphere beneath Eurasia that is presently closing the Persian Gulf [McQuarrie et al., 2003].

Two arms present a consistent picture between lithospheric extension, volcanism, and

mantle flow. The Ethiopia arm is undergoing continental extension and volcanism, underlain by

82

Figure 6.1: Tectonics of the Nubia�Arabia�Somalia three�plate system showing relative and absolute plate motions [ArRajehi et al., 2010], locations of volcanism and dikes [Dixon et al., 1989; Camp and Roobol, 1992], and selected focal mechanisms from CMT catalog.

83

low velocity � presumably hot � material [Debayle et al., 2001]. Shear�wave splitting data

[Gashawbeza et al., 2004] show the fast direction parallel to the rift, consistent with mantle flow

along it. The Gulf of Aden arm shows seafloor spreading, recorded by the magnetic anomalies in

crust formed at the spreading center, along its entire length [Cochran, 1982].

However, the Red Sea arm is more complicated. Seafloor magnetic anomalies and normal

faulting earthquakes typically associated with slow spreading ridges occur almost exclusively

south of 21°N where a deep axial trough is present [Chu and Gordon, 1998; Cochran and

Karner, 2007]. To the north, only a few isolated anomalies are identified, and the sea is floored

by rotated fault blocks. Thus the northern area is interpreted as continental crust being stretched

and faulted with only minor volcanic activity, whereas the southern area has evolved to the point

that new lithosphere is being produced at a spreading axis. This situation has been viewed as

transient until the extension in the northern area evolves into seafloor spreading. This model is

consistent with magnetic and GPS data showing that the rate of opening decreases from about 18

mm/yr at 16°N to about 10 mm/yr at 26°N [Chu and Gordon, 1998; ArRajehi et al., 2010].

6.2 Tomographic Image

Co-workers and I investigated this transition using a seismic tomographic image of

velocity structure, made by Sung-Joon Chang, beneath Arabia and surroundings derived by joint

inversion of a compilation of data. The compilation includes global and regional data sets of

arrival times, body wave waveforms, regional multimode S and surface wave trains, surface

wave group velocities, and constraints on Moho depth from active source seismic studies, gravity

84

surveys, global geological and geophysical interpretations, and receiver functions.

The results are shown in cross sections across the Red Sea and Gulf of Aden (Figure 6.2).

Low velocities indicating hot mantle are visible below 50 km beneath spreading axes in the Gulf

of Aden (profiles G�g, H�h, and I�i) and southern Red Sea (profiles D�d, E�e, and F�f).

However, below the northern Red Sea the slowest material is offset to the east, below Arabia

(profiles A�a, B�b, and C�c).

Figure 6.2: Shear wave velocity cross�sections across the Red Sea and Gulf of Aden. Seafloor and surface topography are shown by black solid lines with tenfold vertical exaggeration. Moho depth is also shown. Black arrow indicates location of the ridge on each cross section. White circles on the map correspond to ticks in the cross sections.

85

This difference is illustrated by an image at 150 km (Figure 6.3). Low velocities occur

beneath the Gulf of Aden and southern Red Sea. However, the lowest velocity material beneath

the southern Red Sea does not extend northwestward below the Red Sea, but instead forms a

channel trending northward beneath Arabia. Shear wave splitting directions show northward

flow parallel to the channel rather than to the Red Sea [Hansen et al., 2006; Sebai et al., 2006].

The upper�mantle low�velocity region has been imaged, first as a broad zone and then

as a channel, in successive earlier regional studies with progressively increasing resolution

[Hadiouche and Zurn, 1992; Debayle et al., 2001; Pasyanos and Nyblade, 2007; Sicilia et al.,

2008]. The dataset Sung-Joon and coworkers used to create the tomographic image combines

much of the data used in these studies in a joint inversion. The resulting improved resolution

shows that the low velocity channel is shallow (extending from 100–300 km), narrow (less than

500 km wide), and displaced eastward rather than extending under the northern Red Sea. This

geometry supports the earlier interpretation of northward flow in the mid upper�mantle from the

Afar hotspot [Park et al., 2008], but shows that the channel is offset from the northern Red Sea

and hence does not represent mantle flow along the Red Sea. Resolution tests in the auxiliary

material show that the low�velocity region is a narrow channel rather than a broad regional

anomaly, and that this channel occurs below Arabia rather than the northern Red Sea.

6.3 Tectonic Interpretation

The geometry of the low velocity anomaly and the shear wave splitting directions jointly

favor their being due to mantle flow, as observed elsewhere [Russo et al., 2010]. However, this

86

geometry differs from cases in which the splitting directions can be interpreted as mantle flow

driven by absolute plate motions [Silver, 1996], because Arabia’s SW�NE absolute motion does

not match the N�S flow and splitting directions. The narrowness of the velocity anomaly and its

depth extent preclude its being due to lithospheric thickness [Rychert and Shearer, 2009].

Figure 6.3: Shear wave velocity map at 150 km depth, showing perturbations relative to reference velocity. Shear wave splitting data are from Gashawbeza et al. [2004] and Hansen et

87al. [2006].

The new data also suggest how the flow may have evolved. Prior to the availability of

tomographic data, the presence of upwelling mantle beneath Arabia was proposed based on the

presence of elevated topography and 20–30 Ma volcanism and dike swarms trending parallel to

the Red Sea but up to several hundred km eastward [Dixon et al., 1989]. Because little uplift and

volcanism occur on the west side of the Red Sea, the asymmetric volcanism and uplift were

hypothesized to reflect the initial location of upwelling that caused the Red Sea rifting as Arabia

migrated northeastward over the upwelling which was assumed to be fixed in the mantle.

However, the tomographic data show that the hot mantle flow is not beneath the Red Sea.

Instead, it occurs beneath the loci of two distinct phases of volcanism in western Arabia. As

previously observed [Camp and Roobol, 1992], the older (pre�15 Ma) northwest�trending

volcanism and younger north�trending volcanism that continues to the present, overlap with

different trends. Thus I hypothesize that the flow from the fixed or slow�moving hotspot forms a

channel that has lengthened with time and been deflected by Arabia’s northeastward absolute

motion, such that it remains below Arabia but rotated to a more north�south trend consistent

with that of the younger volcanics. Figure 6.4 shows such a scenario, in which present plate

motions are used throughout because their detailed history is not well known. The deflection is

favored by the fact that Arabia’s absolute motion is almost perpendicular to the Red Sea.

Analogous deflection of upwelling mantle by absolute plate motion has been proposed for the

Eifel hotspot [Walker et al., 2007].

This model is schematic in several ways. The channel geometry is reasonably but not

88perfectly resolved. A similar direction of anisotropy is observed east of the channel, where

Figure 6.4: (Top) Schematic model for the evolution of the low velocity channel, assuming flow from a fixed hotspot has been deflected by Arabia’s northeastward absolute motion. (Bottom) Possible future geometries in which (Left) extension in the northern Red Sea develops into seafloor spreading or ceases as rifting develops within Arabia along the low velocity channel and (Right) progresses to seafloor spreading.

lithosphere is thicker [Stern and Johnson, 2010], consistent with the view that anisotropy can

arise from both mantle flow and lithospheric structure [Hansen et al., 2006]. Not all volcanism is

89directly above the channel, presumably because the locations of volcanism also reflect

structures

in the lithosphere or due to ongoing opening of the Red Sea. Most intriguingly, the volcanism

occurred in pulses rather than continuously. However, the model offers a general explanation for

the persistence of volcanism with changing trend above the channel’s current location. It is

consistent with geochemical data [Camp and Roobol, 1992; Krienitz et al., 2009] interpreted as

showing that the Arabian volcanics reflect melting that progressed northward and involved a

plume source.

This geometry may have evolved as flow from the hotspot was channeled by the

pre�rifting structure of the base of the lithosphere [Ebinger and Sleep, 1998] and may still be

affected by lithospheric structure. In particular, Cenozoic volcanic activity is absent in the Afif

Terrane that contains some of the oldest crust in the Arabian Shield, of Paleoproterozoic age, but

present to the west [Stoeser and Frost, 2006]. Similarly, the locus of rifting may have been

controlled by preexisting weakness in the continental lithosphere [Dixon et al., 1989; Cloetingh

et al., 1995].

This situation shows aspects of both active and passive rifting models, and could remain

as is or evolve in either direction (Figure 6.4). There is no reason to believe that active sea floor

spreading will begin soon in the northern Red Sea, because the hot mantle flow remains to the

east. The present regime of extension in the north seems stable, as also suggested by the

basement fault geometry [Cochran and Karner, 2007]. It could eventually evolve into sea floor

spreading, in which case the mantle flow should be deflected to the northern Red Sea, as

90observed below the Gulf of Aden. At present this seems not to be occurring, given the

shear�wave splitting data. Alternatively, active rifting could evolve in Arabia above the channel,

given that some extension occurs along the active volcanic trend [Camp and Roobol, 1992;

Pallister et

al., 2010]. Ultimately, the northern Red Sea rift could be abandoned. This “re-rifting” situation

would be similar those observed in the North Atlantic, where volcanism associated with hotspots

produced renewed continental rifting that eventually developed into new seafloor spreading axes

[Skogseid et al., 2000; Mu�ller et al., 2001].

Arabia and its surroundings thus illustrate how many complexities of the rifting process

observed in the geological record [Corti et al., 2003; Huismans and Beaumont, 2003] can arise.

The order, timing, magnitude, and locations of volcanism and extension have varied during

rifting, as shown by the fact that the East Africa rift has considerable volcanism and little

extension, whereas the Gulf of Aden has less volcanism but more extension. The fact that in the

Red Sea and Arabia a situation with aspects of both active and passive rifting occurs and seems

stable for some time illustrates that lithospheric extension and mantle flow can act somewhat

independently in different places for a long time before coalescing to seafloor spreading.

91

Chapter 7

Mapping sediment thickness in Minnesota with horizontal-to-vertical spectral ratios from

USArray data

92

7.1 Introduction

The spectral ratio of seismic noise recorded on the horizontal and vertical components of

a seismometer (HVSR) has been shown to be an inexpensive and useful tool for characterizing

near-surface structure [Nakamura, 1989]. When sediments with low shear wave velocity overlie

higher-velocity bedrock, the HVSR typically has a pronounced peak at the fundamental resonant

frequency fr of the sediment layer fr = V s / 4h, where V s is the average shear wave velocity in

the layer and h is the layer thickness.

As a result, HVSR studies can be used to estimate the fundamental frequency for

earthquake engineering applications [Bindi et al., 2000]. The HVSR can also be used to infer the

layer thickness and thus depth to bedrock. Because the inferred depths are in good agreement

with those measured directly in boreholes [Ibs-von Seht and Wohlenberg, 1999; Parolai et al.,

2002; Nguyen et al., 2004; Chandler and Lively, 2011], HVSR studies can be used to infer

basement depths in areas with few borehole sites [Lane et al., 2008].

Lachet and Bard [1994] show that HVSR peaks have the following properties: the peak

frequencies are independent of the source excitation function and the amplitude of the peak is

related to the velocity contrast at the rock-sediment interface and the Poisson’s ratio of the

93sediment. Thus this technique gives best results where sediments have a high impedance

contrast, a factor of two or more, with the bedrock.

The origin of the HVSR peak remains under discussion. Some researchers suggest the

HVSR peak is due to fundamental mode Rayleigh waves [Lachet and Bard, 1994; Konno and

Ohmachi, 1998], while others explain the HVSR peak as resulting from vertically incident SH

waves [Nakamura, 2000]. As a result, although the resonance frequency of sedimentary sites

seems to be well estimated by the method, it remains unclear how to use the peak amplitude to

infer site amplification at this frequency.

Typically, HVSR studies are conducted by moving a few, often one, seismometers from

site to site and collecting short samples of data. In contrast, USArray provides the opportunity

for analogous studies using a network spanning a large area that can provide long lengths of data.

7.2 Data

Minnesota was chosen as the study area because Chandler and Lively [2011] have

obtained good HVSR results with short seismic records, prompting me to explore application of

the longer records at sites available from USArray data. Most of the state is covered by

sediments from the past recent glaciation, which are thought to have a high impedance contrast

with the bedrock. Sediment thickness values are available from work by the Minnesota

Geological Survey [Jirsa et al., 2010], which provides a mapped surface created from an

irregularly spaced grid of well data.

94 I used data from the USArray transportable array (TA) and the Superior Province

Rifting Earthscope Experiment (SPREE), a multi-institutional flex array (FA) program to study

the Mid-Continent Rift and surroundings [Stein et al., 2011] that was deployed to coincide with

the TA deployment.

USArray provides much more data than traditionally used in HVSR studies. With a single

seismometer, it is typical to record several 15-minute segments of data at a site and then average

their spectra. I used 10 days of data broken up into 20-minute segments, which are then stacked

to create robust average spectra. Each day's averaged HVSR shows consistent spectral patterns

with the other days (Figure 7.1).

95Figure 7.1: Station A32A showing the consistency of spectra from all 10 days of data. The different days are shown in different colors with the final stacked spectrum in black. Ideally each day consists of 72 20-minute segments.

The study used data from 10 consecutive days, February 5th to the 14th, 2012. Only sites

with soft sediment were used. The data were obtained from the Incorporated Research

Institutions for Seismology data management center. Data with mass re-centers, mass clips or an

error in the time series on any component were removed from all the stations. 33% of the stations

had some data removed. Of the 33%, 45.5% had one to four 20 minute segments removed,

45.5% had one to five days removed due to time series data errors, and 9% had to be completely

removed. The data were processed using Seismic Analysis Code [Goldstein et al., 2003;

Goldstein and Snoke, 2005].

First the data were cut into 20-minute segments. The linear trend was removed from by

subtracting a least squares straight-line. A symmetric Hanning taper with a width of 0.05 was

then applied before the Fast Fourier Transform (FFT) was taken. An arithmetic mean smoothing

algorithm with a sliding window width of 50 points was applied to the amplitude spectrum three

times. Each segment's amplitude spectrum was used to compute a HVSR

HVSR(ω ) =[FNS

2 (ω ) + FEW2 (ω )]

2FV2(ω )

1/ 2

(Equation 7.1)

where FNS(ω), FEW(ω), FV(ω), HVSR(ω) are the North-South, East-West, vertical, and HVSR

amplitudes from the FFT.

96 Every 20-minute HVSR segment for a given station was then averaged to yield the

final HVSR for that station (Table 7.1). The depth of soft sediment at the site was taken from the

Minnesota Geological Survey grid.

Station

Network

Latitude

Longitude

fHVSR (Hz)

AHVSR

hdata (m)

hcalc (m)

Difference (%)

A31A TA 48.93 -97.19 0.80 8.9 63 116 -84 A32A TA 48.92 -96.49 1.32 4.8 110 69 37 A33A TA 48.94 -95.39 2.73 8.0 51 33 35 B32A TA 48.40 -96.54 1.33 8.5 111 69 38 B33A TA 48.27 -95.59 2.02 4.8 73 45 39 B34A TA 48.49 -94.65 1.50 7.0 40 61 -53 B35A TA 48.36 -93.73 3.83 6.4 23 23 2

C32A TA 47.83 -96.53 1.00 9.7 86 93 -8 C33A TA 47.76 -95.77 1.29 6.4 116 71 39 C34A TA 47.65 -94.91 0.75 8.7 127 124 2 C35A TA 47.70 -93.98 2.32 9.5 28 39 -40 C36A TA 47.76 -92.84 6.86 5.6 4 13 -204 C39A TA 47.82 -90.13 7.05 6.9 15 12 18 D33A TA 47.14 -95.84 0.64 8.1 189 146 23 D34A TA 47.09 -95.20 0.57 8.4 133 167 -25 D35A TA 47.08 -94.05 1.48 7.7 34 62 -80 D36A TA 47.18 -93.16 1.87 7.2 97 48 50 E33A TA 46.50 -96.01 0.84 8.8 148 110 25 E34A TA 46.51 -95.17 0.84 4.5 100 110 -10 E35A TA 46.56 -94.40 1.29 5.5 69 71 -3 E36A TA 46.52 -93.26 1.72 4.2 18 53 -185 F33A TA 45.84 -96.29 2.07 5.4 42 43 -4 F34A TA 45.80 -95.26 1.52 4.4 93 60 36 F35A TA 45.86 -94.57 1.39 7.4 56 66 -17 F36A TA 45.86 -93.52 6.07 7.2 27 14 47 G33A TA 45.19 -96.44 1.83 4.7 39 49 -28 G34A TA 45.24 -95.64 1.18 5.4 55 78 -41 G35A TA 45.22 -94.49 1.26 7.3 90 73 19 G36A TA 45.23 -93.75 1.70 6.3 111 53 52 H34A TA 44.67 -95.78 1.46 6.1 53 62 -18 H35A TA 44.70 -94.83 1.36 7.5 89 67 25 H36A TA 44.58 -93.93 0.78 4.9 164 119 27 H37A TA 44.58 -92.92 2.22 5.9 44 40 8

97I34A TA 44.04 -95.86 1.01 5.4 80 92 -15 I35A TA 43.86 -94.98 0.84 8.5 95 110 -16 I36A TA 44.02 -94.01 1.07 7.4 90 86 4 I37A TA 44.01 -93.40 2.62 4.6 30 34 -12 I38A TA 44.04 -92.33 14.06 5.0 3 6 -94

SM23 SPREE 46.03 -92.37 3.12 3.5 25 28 -12 SM24 SPREE 45.99 -92.54 4.19 6.4 11 21 -83 SM31 SPREE 45.35 -92.75 1.43 5.0 60 64 -7 SM32 SPREE 45.27 -92.83 3.24 6.6 37 27 26 SM33 SPREE 44.67 -93.48 0.94 6.5 114 99 13 SM34 SPREE 44.67 -93.48 1.09 4.8 125 84 33 SM36 SPREE 44.46 -93.39 2.43 6.7 46 37 19 SM39 SPREE 44.05 -93.20 2.51 4.4 37 36 5 SM40 SPREE 43.91 -93.10 2.49 4.5 34 36 -7 SM41 SPREE 43.77 -93.08 2.96 7.7 30 30 1 SM42 SPREE 43.63 -93.05 2.76 6.0 11 32 -197 SN43 SPREE 46.75 -93.21 1.59 5.2 42 57 -36

SN44 SPREE 46.72 -93.13 2.30 5.8 63 39 39 SN45 SPREE 46.66 -93.04 1.75 4.2 57 52 10 SN46 SPREE 46.61 -92.92 2.04 5.5 49 44 9 SN47 SPREE 46.53 -92.83 16.35 4.0 13 5 61 SN48 SPREE 46.45 -92.69 0.61 6.5 184 153 17 SS65 SPREE 44.02 -94.80 1.70 4.5 29 53 -84 SS66 SPREE 44.02 -94.80 1.35 5.4 30 68 -124 SS68 SPREE 44.06 -93.89 1.46 6.9 62 63 -1 SS69 SPREE 44.03 -93.74 1.95 3.4 76 46 39 SS70 SPREE 44.01 -93.64 1.34 6.6 62 68 -9 SS72 SPREE 44.04 -93.27 3.02 4.3 27 29 -9 SS73 SPREE 44.03 -93.14 2.08 6.9 45 43 4 SS74 SPREE 44.03 -93.00 2.65 8.5 54 34 38 SS75 SPREE 44.04 -92.88 4.72 5.7 19 18 4 SS76 SPREE 44.03 -92.74 11.47 5.1 11 7 32 SS77 SPREE 44.02 -92.59 2.47 4.8 29 36 -24 SS78 SPREE 43.97 -92.38 3.89 6.8 17 23 -36

Table 7.1: fHVSR = HVSR peak frequency; AHVSR = Amplitude of HVSR peak; hdata = Depth of soft sediment from Minnesota Geological Survey; hcalc = calculated soft sediment thickness from regression fit (equation 7.3); Difference % = [(hdata - hcalc)/hdata] x 100

98 The data quality varies by location and network. Thicker sediments generally yield

narrower HVSR peaks. Only one station in the TA network did not show a coherent HVSR peak,

while eight SPREE stations were discarded due to poor HVSR peaks.

I examined whether the peaks resulted from a high horizontal component, a low vertical

component, or both. 48% of the SPREE stations have both a low vertical, and high horizontal

component, compared to 79% of TA stations (Figure 7.2). However, I found no obvious spatial

patterns in which components caused the peak (Figure 7.3).

7.3 Results

The HVSR peak frequencies show a consistent pattern throughout Minnesota (Figure

7.3). Following Ibs-von Seht and Wohlenberg [1999], I assumed that the HVSR peak frequency

fHVSR is related to the soft sediment thickness h in meters at each site by

h = afHVSRb

(Equation 7.2)

The constants a and b were estimated by taking the logarithm and computing a linear

regression, yielding

h = 91.95 f HVSR−1.029 (Equation 7.3)

The regression fits the data well, yielding a R2 of 0.74 (Figure 7.4). Both networks fit about

equally well by the regression curve. Given that the SPREE sites are in a limited area, this

implies that sediment properties are similar across the region, making a single curve fit better.

99Encouragingly my regression results are similar to those obtained by Chandler and Lively

[2011], which use different sites and surveying methods.

107

Figure 7.2: Examples of HVSR spectral ratios and their related spectra. For each station the top panel shows the HVSR spectral ratio with a vertical black line showing the selected HVSR peak frequency. The bottom panel shows the ten day averaged spectra leading to the HVSR. The vertical, north-south, and east-west components are shown in red, blue and green respectively. The black line is the selected HVSR peak frequency.

108

Figure 7.3: HVSR peak frequency map showing a smooth trend across the study area. Black squares are stations with both a low vertical component and a high horizontal component. Inverted triangles have only a low vertical component. Triangles have only high horizontal components. Which components contribute to the peak has no general pattern.

0 100 200

km

0

2

4

6

8

10

12

14

16

180 100 200

km

HV

SR

pea

k fr

eque

ncy

(Hz)

109

Figure 7.4: A) Data and best fit for the relation between peak frequency and sediment thickness. Orange line is Chandler and Lively [2011] relation, and the black line is this study. Blue dots are TA stations, green dots are SPREE stations. The two networks give similar results. B) Data and best fit for Iowa TA sites. Red dots are TA stations.

I also conducted a similar study for Iowa using the TA sites there and sediment thickness

values from the Iowa Geological Survey [Witzke et al., 2010], I found that the scatter was

significantly greater, shown by a R2 of 0.49 (Figure 7.4B). This is probably due to the sediment

to bedrock contrast being less strong and sediment properties being more laterally variable,

presumably because not all of Iowa was recently glaciated.

0

20

40

60

80

100

120

140

160

180

200

0 2 4 6 8 10 12 14 16 18 20

Sof

t sed

imen

t thi

ckne

ss (

m)

HVSR peak frequency (Hz)

0

20

40

60

80

100

120

140

160

180

200

0 2 4 6 8 10 12 14 16 18 20

Sof

t sed

imen

t thi

ckne

ss (

m)

HVSR peak frequency (Hz)

TA

SPREE

Minnesota Iowa

TA A B

110

Figure 7.5: A) Sediment thickness map from taking values at study sites from Minnesota Geological Survey and contouring. B) Sediment thickness map from taking regression curve values at study sites and contouring. Black triangles are TA stations, white triangles are SPREE stations.

The map of sediment thickness for Minnesota inferred from the peak frequencies at each

site using equation 7.3 is similar to one derived from sampling the Minnesota Geological

Survey’s sediment thickness map at the sites (Figure 7.5). The differences are shown by a

histogram and as percentages in figure 7.6. The absolute sediment thickness difference at each

site is reasonable and does not have any clear bias. Not surprisingly, the largest percentage

differences arise for sites with thin sediment.

Soft sediment thickness Calculated soft sediment thickness

A

Met

ers

0

20

40

60

80

100

120

140

160

180

2000 100 200

kmA BBA

111

Figure 7.6: Left: Histogram of differences in sediment thickness at sites between the Minnesota Geological Survey sediment thickness map and thickness inferred from HVSR peak frequencies. Right: Differences shown as percentages as a function of sediment thicknesses. Red and green lines show ±50% and ±25%.

The HVSR method using data from the USArray thus provides good way to estimate the

sediment thickness at sites. This result is consistent with earlier studies that find this to be true

when sediments are similar across a study region and their impedance contrast with the basement

rocks is strong.

-250

-200

-150

-100

-50

0

50

100

0 50 100 150 200

Mis

fit (

%)

Soft sediment thickness (m)

TA

SPREE 0

2

4

6

8

10

12

14

16

18

-60

-50

-40

-30

-20

-10 0 10

20

30

40

50

60

Num

ber

of s

ites

Absolute thickness errors (m)

112CHAPTER 8

Conclusions and Future Work

1138.1 Conclusions and Links

In this dissertation I have presented research in two related fields, the tectonics of rifting

and intraplate seismicity. Chapter 7, which diverges somewhat from this theme, is linked to

Chapters 4 and 5 in that H/V results can be applied to seismic hazard analysis.

In Chapter 2, I modeled gravity data and found that the east arm of the MCR has less

magma than the west arm, and proposed a plausible microplate model that gives an explanation

for why. Chapter 3 extends this analysis by placing the microplate model in the regional plate

tectonic context. It proposes that the MCR formed as part of the separation of Amazonia

(Precambrian northeast South America) from Laurentia (Precambrian North America) and

became inactive once seafloor spreading was established. This new view is important in that

instead of viewing the MCR as an isolated and failed isolated episode of mid-plate volcanism, it

is viewed as part of a successful rifting event forming an integral part of the assembly of

Rodinia.

Chapter 4 looks at a seismically active failed rift system in the interior of a plate. I

examine whether the seismicity supports a modeling prediction that the 1811-1812 earthquakes

transferred stress from the New Madrid seismic zone to the Wabash Valley seismic zone. I

combine historical seismicity catalogs with recent catalogs to define the Gutenberg-Richter

relationship for the two geologically linked regions. I conclude that the seismicity difference is

not indicative of stress transfer to the WVSZ.

Chapter 5 continues the theme of using seismic catalogs, to infer earthquake hazards. I do

so by sampling simulated catalogs to see what parameters can be reliably estimated from the

114short earthquake catalogs available. I find that the b values inferred depend on the method

used to estimate them. In Chapter 4, I used the least squares method to derive the b value. In

Chapter 5, I show that least squares has significantly more scatter than the maximum likelihood

estimate method but is a better description of the data itself. While the total scatter in the b

values is an important result, most of that variation is due to larger earthquakes. The number of

small earthquakes is more stable, which is where the difference in the New Madrid and Wabash

Valley seismic zones arises. Hence the conclusion in Chapter 4 that the New Madrid seismic

zone has more small earthquakes, probably due to being aftershocks of the 1811-1812 events, is

still valid.

The variation in b values inferred for both the MLE and LSQ methods shown in Chapter

5 could have significant impact on hazard modeling. An even more interesting result is that the

observed Mmax for the areas I studied are those most frequently arising in my simulations, rather

than the actual maximum in the simulations. This indicates that we have probably not observed

the largest earthquakes. This method does not predict the largest earthquake in a given region,

but illustrates the need for paleoseismology, ideally a systematic effort looking at both dormant

and active intraplate faults.

Chapter 6 explores rifting in an active system, the Red Sea. I propose a scenario in which

the Red Sea may stop rifting because hot sublithospheric flow causes ‘re-rifting’ in the interior of

Arabia. This possibility is akin to the view in Chapter 3 that the rifting process can lead to much

more complex tectonic evolution than often assumed.

115

8.2 Reflections and Future Work

My research on the tectonics of rifting has sparked many more questions than it has

answered. The MCR scenario that I proposed suggests that many ‘isolated’ intraplate magmatic

events that appear to have “failed,” in that they did not break the continent, were actually part of

successful regional plate reorganizations. A natural extension to chapters 2 and 3 would be to

investigate other isolated and apparently failed rifts to see if they were associated with a

successful rifting event.

In Chapter 2 I modeled the MCR gravity anomalies as a lower crustal intrusion. This

explains the first order effects in the gravity anomalies and is a good way to compare the two rift

arms, but is not a full view of the magma intrusions. A question that interests me is what is the

ratio of lower crustal intrusion to diking events? Furthermore is there a relationship between

deep intrusions and surface extension? Answering these questions would likely need seismic

refraction or reflection data, but could lead to key insights into how magma intrusions and

extension relate. The results could also indicate how rifts subside, and how heat flow evolved

through time in a rift, both of which are important factors in hydrocarbon formation.

The next step for the maximum magnitude studies is to test different methods of

predicting Mmax on simulated catalogs. I also want to use different earthquake simulation

techniques, either a time independent recurrence model or the Epidemic-Type Aftershock

Sequence Model. Understanding how major earthquakes migrate in intraplate zones could

significantly improve seismic hazard models. Paleoseismology could help via a systematic

116

investigation of active and, perhaps more importantly, apparently-inactive faults to gain insight

into how major earthquakes migrate through time.

More broadly this research points to weak points in seismic hazard modeling. The failure

of earthquake hazard maps indicated by the destructive Tohoku, Haiti, and Wenchuan

earthquakes has drawn attention to the fact that we do not know how well seismic hazard models

actually predict shaking over a given period of time? One way to address this would be to

compare the amount of predicted shaking in a given region to the amount of actual shaking in

that region. I think this is a key step in evaluating hazard models that would give us insights

about how to further improve them. Given that long time periods are needed to accumulate

enough real data for this purpose, synthetic catalog experiments are an alternative that can give

valuable insight.

117

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