determining the deformations in western anatolia with...

DOKUZ EYLÜL UNIVERSITY

GRADUATE SCHOOL OF NATURAL AND APPLIED SCIENCES

DETERMINING THE DEFORMATIONS IN

WESTERN ANATOLIA WITH GPS AND

GRAVITY MEASUREMENTS

by

Ayça ÇIRMIK

November, 2014

İZMİR

DETERMINING THE DEFORMATIONS IN

WESTERN ANATOLIA WITH GPS AND

GRAVITY MEASUREMENTS

A Thesis Submitted to the

Graduate School of Natural and Applied Sciences of Dokuz Eylül University

In Partial Fulfillment of the Requirements for the Degree of Doctor of

Philosophy in Geophysical Engineering

by

Ayça ÇIRMIK

November, 2014

İZMİR

Ph.D. THESIS EXAMINATION RESULT FORM

We have read the thesis entitled “DETERMINING THE DEFORMATIONS IN

WESTERN ANATOLIA WITH GPS AND GRAVITY MEASUREMENTS”

completed by AYÇA ÇIRMIK under supervision of PROF. DR. ZAFER AKÇIĞ

and we certify that in our opinion it is fully adequate, in scope and in quality, as a

thesis for the degree of Doctor of Philosophy.

Prof. Dr. Zafer AKÇIĞ

Supervisor

Prof. Dr. Mustafa AKGÜN Prof. Dr. Hasan SÖZBİLİR

Thesis Committee Member Thesis Committee Member

Prof. Dr. Ferruh YILDIZ Doç. Dr. Oya PAMUKÇU

Examining Committee Member Examining Committee Member

Prof.Dr. Ayşe OKUR Director

Graduate School of Natural and Applied Sciences

ii

ACKNOWLEDGMENTS

The GPS data (stations of CORS-TR project and General Command of Mapping)

were obtained by Dokuz Eylul University Scientific Research project,

2012.KB.FEN.126.

First of all, I would like to thank my supervisor, Prof. Dr. Zafer AKÇIĞ for his

helps and advices on Ph.D. thesis and Assoc. Prof. Dr. Oya PAMUKÇU for her

suggestions, helps and encouraging and being near me whenever I need during my

all graduate career. I would like to thank members of Ph.D. committee, Prof. Dr.

Müjgan ŞALK and Prof. Dr. Hasan SÖZBİLİR and members of examining

committee, Prof. Dr. Ferruh YILDIZ and Prof. Dr. Mustafa AKGÜN for their

advices for improving the thesis. I am grateful and would like to thank Asst. Prof. Dr.

Tolga GÖNENÇ for his advices and lots of helps. I would like to thank Assoc. Prof.

Dr. Muzaffer KAHVECİ for introducing me with GPS measurements and for his

advices on processing GPS data.

I would like to thank Prof. Dr. Carla BRAITENBERG for her advices and helps

on my research when I was at Trieste University as an Erasmus exchange student and

Jean CHERY for helping me numerical modeling when I was at Montpellier

University. I would like to thank Assoc. Dr. Uğur DOĞAN for improving my

knowledge about geodesy by following his graduate lesson at Yıldız Technical

University, Department of Geomatic Engineering. I would like to thank Prof. Dr.

Bradford Hager for helping me on my research and improving myself by following

his graduate lessons when I was at MIT as the Council of Higher Education scholar. I

would like to thank Prof. Dr. Thomas HERRING and Dr. Bob KING for their

precious advices and answering my questions about GAMIT/GLOBK software,

patiently. I am grateful to Asst. Prof. Dr. Mickael BONNIN for his helps on

processing on ADELI software. I would like to thank Assoc. Prof. Dr. Mehmet

ERGIN and other members of The Scientific and Technological Research Council of

Turkey (TUBITAK), Marmara Research Center, Earth and Marine Science Institute

iii

for helping on providing the GPS data of TURDEP project. I would like to thank the

project manager, Assoc. Prof. Dr. Oya PAMUKÇU and all researchers of TUBITAK

project, No:108Y285 for allowing me to use the GPS results of the project.

I would like to thank my professors and colleagues at Dokuz Eylül University,

Departments of Geophysical and Geological Engineering. I wish to thank all

members of Student Affairs Department of Dokuz Eylul University, Graduate School

of Natural and Applied Science for answering to all my questions patiently during

graduate career.

Finally, but at the top of the list, I thank my dear parents, Sevil & Muammer

YURDAKUL and my dear brother Tolga YURDAKUL for encouraging me at all my

life and being near and helping me in my long academic career. I thank my dear

mother-in-law Semra ÇIRMIK for creating a study environment during the writing of

my thesis. I thank my dear husband Ömer for his unwavering support and

encouragement, not just during the writing of this thesis, but throughout my

undergraduate and graduate career. Finally, I wish to thank my dear son Yiğit

ÇIRMIK for being the meaning of my life. I wish to dedicate my thesis to my dear

family.

Ayça ÇIRMIK

iv

DETERMINING THE DEFORMATIONS IN WESTERN ANATOLIA WITH

GPS AND GRAVITY MEASUREMENTS

ABSTRACT

Western Anatolia is one of the most seismically active and rapidly extending

regions in the world and is currently experiencing an approximately N–S continental

extension. Due to this important case of Western Anatolia, deformations of the

region were examined by GPS and gravity measurement in this study.

Firstly, the GPS stations of TURDEP poject, CORS-TR Project and General

Command of Mapping were processed relative to Eurasia fixed frame and the

velocities of the stations were found as approximately 20-25 mm per year. Besides,

the Anatolian Block and Aegean block solutions the velocity magnitudes were

obtained between approximately 3-15 mm per year. As second step, the GPS and

microgravity data, which were obtained simultaneously at 6 points; Akhisar

(Manisa), Eşme (Uşak), Çal (Denizli), Bademli (İzmir), Borlu (Manisa), Karacasu

(Aydın), were compared for discussing about vertical mass changes on the

measurement points. As third step, obtained GPS velocities by using GAMIT-

GLOBK software were compared with the modeled GPS velocities by Coulomb 3.3

software on the northern normal fault of Gediz graben and southern normal fault of

the Büyük Menderes graben by using Coulomb 3.3 software and coulomb stress

changes were obtained for these faults and compared with earthquakes. As the last

step, the numerical models were created by using finite elements for determining the

deformation of Western Anatolia during the geological time scales.

As a result, all the results were compared with the previous geophysical and

geological studies and earthquake focus depth distributions.

Keywords: Western Anatolia, GPS, gravity, coulomb stress changes, numerical

modeling, finite elements.

v

BATI ANADOLU BÖLGESİNDEKİ DEFORMASYONLARIN GPS VE

GRAVİTE ÖLÇÜMLERİ İLE BELİRLENMESİ

ÖZ

Batı Anadolu dünyadaki sismik olarak çok aktif ve ani açılma gösteren

bölgelerden biridir ve halen yaklaşık K-G yönünde kıtasal açılma göstermektedir.

Batı Anadolu bölgesinin bu önemli durumundan dolayı, bu çalışmada bölgedeki

deformasyonları irdelemek için GPS ve mikrogravite ölçümleri kullanılmıştır.

İlk olarak TURDEP, TUSAGA-AKTİF ve Harita Genel Komutanlığı’ndan temin

edilen GPS verileri Avrasya sabit çözümler ile proses edilmiş, yılda yaklaşık 20-25

mm'lik hızla hareket ettiği saptanmıştır. Ayrıca, rejyonel deformasyonu gözlemlemek

için Ege ve Anadolu blok çözümleri yapılmıştır ve istasyonların hız değişimleri

yaklaşık yılda 3-15 mm olarak saptanmıştır. İkinci adımda, 6 noktada Akhisar

(Manisa), Eşme (Uşak), Çal (Denizli), Bademli (İzmir), Borlu (Manisa), Karacasu

(Aydın), eşzamanlı olarak alınmış GPS ve mikrogravite verileri, düşey yöndeki kütle

değişimini irdelemek için birlikte değerlendirilmiştir. Üçüncü adımda, Gamit-Globk

yazılımı ile elde edilen GPS hızları ile Coulomb 3.3 yazılımıyla modellenen GPS hız

verileri Gediz grabeninin kuzeyindeki normal fay ve Büyük Menderes Grabeninin

güneyindeki normal fay için birlikte değerlendirilmiş ve bu faylardaki Coulomb stres

değişimi elde edilmiştir. Son olarak jeolojik dönemler boyunca Batı Anadolu

bölgesindeki deformasyonu incelemek için sonlu elemanlar yöntemi ile bölgeye ait

sayısal modelleme yapılmıştır.

Sonuç olarak, bu çalışmada elde edilen tüm bulgular, çalışma alanında yapılmış

jeofizik ve jeolojik çalışmaların sonuçlarıyla ve deprem odak derinlik dağılımları ile

karşılaştırılmıştır.

Anahtar Kelimeler: Batı Anadolu, GPS, gravite, coulomb stres değişimleri, sayısal

modelleme, sonlu elemanlar.

vi

CONTENTS

Page

THESIS EXAMINATION RESULT FORM .............................................................. ii

ACKNOWLEDGEMENTS ........................................................................................ iii

ABSTRACT ................................................................................................................ .v

ÖZ ............................................................................................................................... vi

LIST OF FIGURES ..................................................................................................... x

LIST OF TABLES .................................................................................................... xix

CHAPTER ONE – INTRODUCTION .................................................................... 1

CHAPTER TWO – GEOLOGY OF THE STUDY AREA .................................... 4

CHAPTER THREE – DEFORMATION ESTIMATIONS WITH GPS

PROCESSING ............................................................................................................ 8

3.1 The Segments of GPS........................................................................................ 8

3.1.1 The Space Segment.................................................................................... 9

3.1.2 The Control Segment. .............................................................................. 10

3.1.3 The User Segment.................................................................................... 11

3.2 Reference Coordinate System of GPS ............................................................. 11

3.2.1 Earth-Centered Inertial (Space-fixed) (ECI) Coordinate System. ........... 12

3.2.2 Earth-Centered Earth-Fixed (ECEF) Coordinate System ........................ 12

3.2.3 World Geodetic System-1984 (WGS-84) ................................................ 13

3.3 Sources of Errors ............................................................................................. 13

3.3.1 Ephemeris (Orbital Position) Errors ........................................................ 13

3.3.2 Satellite and Receiver Clock Errors ......................................................... 13

3.3.3 Atmospheric Effects ................................................................................ 14

3.3.4 Selective Availability............................................................................... 15

3.3.5 Multipath.................................................................................................. 15

3.3.6 Receiver Antenna Phase Center Error ..................................................... 16

vii

3.4 Differential Observations Based on GPS Measurements ................................ 16

3.4.1 Single Differences ................................................................................... 16

3.4.2 Double Differences .................................................................................. 17

3.4.3 Triple Differences .................................................................................... 17

3.5 The Principle of GPS Measurement ................................................................ 17

3.5.1 The Principle of Phase Measurement ...................................................... 19

3.6 Data Processing Steps ..................................................................................... 24

3.6.1 Processing: The Three-Step Method ....................................................... 24

3.6.2 Pre-Processing Steps ................................................................................ 26

3.6.3 Processing Steps ...................................................................................... 27

3.6.3.1 Processing Steps of GAMIT Program ............................................. 27

3.6.3.2 Processing Steps of GLOBK Program ............................................. 28

3.7 The Applications ............................................................................................. 30

3.7.1 Other Relatively Solutions ....................................................................... 72

3.7.1.1 Anatolian Block Solutions ............................................................... 73

3.7.1.2 Aegean Block Solutions ................................................................... 76

CHAPTER FOUR – ANALYZING MASS CHANGES OF WESTERN

ANATOLIA BY USING MICROGRAVITY AND GPS DATA ......................... 78

4.1 Applications ..................................................................................................... 81

4.1.1 GPS data Processing ................................................................................ 81

4.1.2 Comparison of GPS and Microgravity Results ....................................... 90

CHAPTER FIVE - COULOMB STRESS CHANGES CALCULATIONS ..... 105

5.1 Applications ................................................................................................... 107

5.1.1 Northern Normal Fault of Gediz Graben ............................................... 108

5.1.2 Southern Normal Fault of Büyük Menderes Graben ............................. 117

5.1.3 The Relative Calculations on Study Area .............................................. 125

viii

CHAPTER SIX - NUMERICAL MODELING .................................................. 129

6.1 Physical Problem (continuum) and Equilibrium Equations. ........................ 129

6.2 Constitutive Laws .......................................................................................... 131

6.2.1 Elastoplasticity ....................................................................................... 132

6.2.2 Viscoelasticity........................................................................................ 133

6.3 General Algorithm of the Finite Element Modeling Software (ADELI) ..... 134

6.4 Applications ................................................................................................... 135

CHAPTER SEVEN - CONCLUSIONS ............................................................... 156

REFERENCES ....................................................................................................... 161

ix

LIST OF FIGURES

Page

Figure 2.1 Simplified tectonic map of Turkey showing major neotectonic structures

and neotectonic provinces. Red square shows the study area ................... 4

Figure 3.1 GPS segments ............................................................................................. 9

Figure 3.2 The space segment of GPS ....................................................................... 10

Figure 3.3 The control segment of GPS ..................................................................... 11

Figure 3.4 Sources of signal interference ................................................................... 16

Figure 3.5 General classifications of GNSS Positioning methods ............................. 19

Figure 3.6 Principle of GPS phase measurement ....................................................... 22

Figure 3.7 The GPS stations are located Western Anatolia ....................................... 32

Figure 3.8 The GPS stations which used in the study are shown in general tectonic

structures map of Western Anatolia ........................................................ 33

Figure 3.9 The IGS stations which used in processing are shown by red circle ...... 36

Figure 3.10 The processing solutions of AYD1 for the days between 180th-195th of

the years between 2009-2011 .................................................................. 37

Figure 3.11 The processing solutions of BALK for the days between 180th-195th of


Figure 3.12 The processing solutions of CESM for the days between 180th-195th of

the years between 2009-201 .................................................................... 39

Figure 3.13 The processing solutions of DEIR for the days between 180th-195th of


Figure 3.14 The processing solutions of DENI for the days between 180th-195th of


Figure 3.15 The processing solutions of HARC for the days between 180th-195th of


Figure 3.16 The processing solutions of IZMI for the days between 180th-195th of


Figure 3.17 The processing solutions of KIKA for the days between 180th-195th of


x

Figure 3.18 The processing solutions of MUGL for the days between 180th-195th of


Figure 3.19 The processing solutions of SALH for the days between 180th-195th of


Figure 3.20 The processing solutions of USAK for the days between 180th-195th of


Figure 3.21 The processing solutions of AKHT for the days between 180th-195th of


Figure 3.22 The processing solutions of BDMT for the days between 180th-195th of


Figure 3.23 The processing solutions of BORT for the days between 180th-195th of


Figure 3.24 The processing solutions of CALT for the days between 180th-195th of


Figure 3.25 The processing solutions of ESMT for the days between 180th-195th of


Figure 3.26 The processing solutions of IZMT for the days between 180th-195th of


Figure 3.27 The processing solutions of KRCT for the days between 180th-195th of


Figure 3.28 The processing solutions of KRPT for the days between 180th-195th of


Figure 3.29 The processing solutions of TRBT for the days between 180th-195th of


Figure 3.30 WRMS values for North-East-Up directions from combination of

TURDEP and CORS-TR projects stations for 2009, 2010 and 2011...... 57

Figure 3.31 WRMS values for North (N)-East(E)-Up(U) directions from

combination of IGS for the days between 180th-195th of 2009, 2010

and 2011 .................................................................................................. 58

Figure 3.32 The processing solutions of BAYO for 261st and 262nd days of 2000,

211st and 212nd days of 2001, 123rd and 124th days of 2005 ............ 59

xi

Figure 3.33 The processing solutions of CEIL for 271st and 272nd days of 2000,

211st and 212nd days of 2001 .............................................................. 60

Figure 3.34 The processing solutions of CKOY for 208th and 209th days of 2001,

212nd and 213rd days of 2004 ............................................................. 61

Figure 3.35 The processing solutions of EMET for 271st and 272nd days of 2000,

123rd and 124th days of 2005 .............................................................. 62

Figure 3.36 The processing solutions of LTFY for 89th day of 2000, 97th and 297th

days of 2001 and 157th and 158th days of 2004 .................................. 63

Figure 3.37 The processing solutions of YENF for 258th and 259th days of 2000,

214th and 215th days of 2001 .............................................................. 64

Figure 3.38 The processing solutions of ZEYT for 211st and 212nd days of 2001,

212nd and 213rddays of 2004 ............................................................... 65

Figure 3.39 WRMS values for North-East-Up directions from combination of

General Command Mapping stations for 2000, 2001, 2004 and 2015 66

Figure 3.40 WRMS values for North-East-Up directions from combination of IGS

stations for 2000, 2001, 2004 and 2015 ............................................... 66

Figure 3.41 GPS horizontal velocities and their 95% confidence ellipses in a Eurasia

fixed reference frame for the period of 2009-2011 for TURDEP and

CORS-TR stations which are shown by red vectors and for the period of

2000-2001-2004 and 2005 for General Command Mapping stations

which are shown by green vectors ........................................................ 69

Figure 3.42 a) GPS horizontal velocities of the study McClusky et al. (2000) for the

period 1988-1997 and GPS horizontal velocities of the TUBITAK

project No:108Y285 for the period 2009-2011 with 95% confidence

ellipses in a Eurasia fixed frame are added to the study area stations

given in Figure 3.41 ............................................................................... 70

Figure 3.42 b) The stations which were given at Figure 3.42.a were separated to4

regions ................................................................................................... 71

Figure 3.43 a) The velocity field with 95% confidence ellipses of the stations

computed in Anatolian block frame from 3-year (2009, 2010 and 2011)

GPS data ............................................................................................... 74

xii

Figure 3.43 b) The stations are grouped to 3 regions and shown by red shapes. Line

A shows the boundary of North Anatolian Region (NAR). Line B

shows the separation of the group 1 and 2 ............................................ 75

Figure 3.44 Geological map of Western Anatolia and its surrounding...................... 76

Figure 3.45 The velocity field with 95% confidence ellipses of the stations computed

in Aegean fixed reference frame from 3-year (2009, 2010 and 2011) GPS

data .......................................................................................................... 77

Figure 4.1 a) General tectonic of the Turkey NAFZ: North Anatolian Fault Zone,

WAEP: Western Anatolian Extensional Zone EAFZ:Eastern Anatolian

Fault Zone. b) The locations of GPS and microgravity stations ............. 80

Figure 4.2 WRMS repeatabilities of North-East-Up values from combination of

2007, 2008 and 2009 GPS data ............................................................... 82

Figure 4.3 The daily processing results (between the days 139th and 142nd) of

AKHT stations between the years 2007 and 2009 .................................. 83


BORT stations between the years 2007 and 2009................................... 84


ESMT stations between the years 2007 and 2009.................................. 85


CALT stations between the years 2007 and 2009 ................................... 86


BDMT stations between the years 2007 and 2009 .................................. 87


KRCT stations between the years 2007 and 2009................................... 88

Figure 4.9 GPS horizontal velocities and their 95% confidence ellipses in a Eurasia-

fixed reference frame for the period of 2007-2009 ................................. 89

Figure 4.10 a) Gravity changes of AKHT stations between the years 2007-2009 b)

Displacement changes on vertical direction of AKHT stations between

the years 2007-2009 ................................................................................ 91

Figure 4.11 a) Gravity changes of BDMT stations between the years 2007-2009 b)

Displacement changes on vertical direction of BDMT stations between

the years 2007-2009 ................................................................................ 91

xiii

Figure 4.12 a) Gravity changes of KRCT stations between the years 2007-2009 b)

Displacement changes on vertical direction of KRCT stations between

the years 2007-2009 ................................................................................ 92

Figure 4.13 a) Gravity changes of BORT stations between the years 2007-2009 b)

Displacement changes on vertical direction of BORT stations between

the years 2007-20099 .............................................................................. 92

Figure 4.14 a) Gravity changes of CALT stations between the years 2007-2009 b)

Displacement changes on vertical direction of CALT stations between

the years 2007-2009 ................................................................................ 93

Figure 4.15 a) Gravity changes of ESMT stations between the years 2007-2009 b)

Displacement changes on vertical direction of ESMT stations between

the years 2007-2009 ................................................................................ 93

Figure 4.16 The Earthquakes distributions which occurred between the years 2005-

2014 ......................................................................................................... 95

Figure 4.17 a) Topographic map of study area b) The blue lines show the cross-

sections .................................................................................................... 96

Figure 4.18 a) The topographic changes along to cross-section A-A' b) Earthquake

distributions along to S-N direction near to AKHT station. Small Red

square shows the location of the station .................................................. 97

Figure 4.19 a) The topographic changes along to cross-section B-B' b) Earthquake

distributions along to S-N direction near to BDMT station. Small Red


Figure 4.20 a) The topographic changes along to cross-section C-C' b) Earthquake

distributions along to S-N direction near to KRCT station. Small Red


Figure 4.21 a) The topographic changes along to cross-section D-D' b) Earthquake

distributions along to S-N direction near to BORT station. Small Red


Figure 4.22 a) The topographic changes along to cross-section E-E' b) Earthquake

distributions along to S-N direction near to CALT station. Small Red


xiv

Figure 4.23 a) The topographic changes along to cross-section F-F' b) Earthquake

distributions along to S-N direction near to ESMT station. Small Red


Figure 5.1 The axis system used for Coulomb stresses calculations of on optimum

failure planes ......................................................................................... 106

Figure 5.2 The parameters of fault geometry ........................................................... 108

Figure 5.3 GPS velocities of North stations (AKHT, BORT, ESMT and CALT) and

South stations (TRGT and SALH ) relative to each other .................... 109

Figure 5.4 Blue vectors represent the obtained GPS velocities by Gamit/Globk and

red vectors represent modeled GPS velocities by Coluomb 3.3 ........... 110

Figure 5.5 The view of ‘stress control panel’ of Coulomb 3.3 software for calculating

Coulomb Stress Changes for the northern normal fault of Gediz Graben

at 6 km depth ......................................................................................... 111

Figure 5.6 a) Coulomb stress changes between the depth of 0-4 km b) Earthquake

focus distributions on the study area. USGS earthquake archive was used

between the years 1970-2014 ................................................................ 112

Figure 5.7 a) Coulomb stress changes at depth 4 km b) Earthquake focus

distributions on the study area. USGS earthquake archive was used





Figure 5.9 a) Coulomb stress changes at depth 6 km b) Earthquake focus



Figure 5.10 GPS velocities of North stations (AYD1, BDMT and CALT) and South

stations (KRPT, KRCT and DENI ) relative to each other ................... 118

Figure 5.11 Blue vectors represent the obtained GPS velocities by Gamit/Globk and

red vectors represent modeled GPS velocities by Coluomb 3.3 ........... 118

Figure 5.12 The view of ‘stress control panel’ of Coulomb 3.3 for calculating

Coulomb stress Changes for the Southern normal fault of Büyük

Menderes Graben at 3 km depth ......................................................... 119

xv




Figure 5.14 a) Coulomb stress changes at 3 km depth b) Earthquake focus



Figure 5.15 a) Coulomb stress changes between the depth of 0-5 km b)

Earthquake focus distributions on the study area. USGS earthquake

archive was used between the years 1970-2014.................................... 122

Figure 5.16 a) Coulomb stress changes at 5 km depth b) Earthquake focus



Figure 5.17 GPS velocities of left side stations (KIKA, AKHT and TRGT shown by

black vectors) and right side stations (DEIR, BORT, USAK and ESMT

shown by red vectors) relative to each other ......................................... 126

Figure 5.18 GPS velocities of left side stations (KIKA, AKHT and TRGT shown by

black vectors) and right side stations (USAK and ESMT shown by red

vectors) relative to each other ............................................................... 126

Figure 5.19 GPS velocities of left side stations (KIKA, AKHT, TRGT, DEIR and

BORT shown by black vectors) and right side stations (USAK and

ESMT shown by red vectors) relative to each other ............................. 127

Figure 5.20 GPS velocities of left side stations (BDMT, AYD1 and KRPT shown by

black vectors) and right side stations (CALT, KRCT and DENI shown by

red vectors) relative to each other ......................................................... 128

Figure 6.1 a) The model of elastoplastic material b) The deformation of elastoplastic

material due to stress ............................................................................. 132

Figure 6.2 a) The model of viscoelastic material b) The behavior of the viscoelastic

solid ....................................................................................................... 133

Figure 6.3 The simple model created with 'gmsh' .................................................... 136

Figure 6.4 The view of 3D meshing with 'gmsh' ..................................................... 136

Figure 6.5 The view of initial model. Green arrows represent the extensional forces

were given the borders .......................................................................... 137

xvi

Figure 6.6 The view of finite strain (deviatoric epsilon) of model after 0.7 Myr .. 138

Figure 6.7 The view of finite strain (deviatoric epsilon) after 1.1 Myr ................. 138

Figure 6.8 The view of the profile length of the numerical model ........................ 140

Figure 6.9 The initial view of the model. ............................................................... 140

Figure 6.10 The topographic cross-section of the study area ................................... 141

Figure 6.11 Crust-mantle interface values ............................................................... 141

Figure 6.12 The temperature distributions on model after 5 Myr for 200K-500K .. 142

Figure 6.13 The finite strain field on model after 5 My for 200ºK-500ºK .............. 142

Figure 6.14 a) The velocity fields on model after 5 Myr for 200ºK-500ºK ............. 143

Figure 6.14 b) The velocity field with vectors on model after 5 Myr ..................... 143

Figure 6.15 The temperature distributions on model after 10 Myr for 200K-500K 144

Figure 6.16 The finite strain field on model after 10 My for 200ºK-500ºK ............ 144

Figure 6.17 a) The velocity fields on model after 10 Myr for 200ºK-500ºK ........... 145

Figure 6.17b) The velocity fields with vectors on model after 10 Myr for 200ºK-

500ºK ..................................................................................................... 145

Figure 6.18 The temperature distributions on model after 15 Myr for 200ºK-500ºK

............................................................................................................... 146

Figure 6.19 The finite strain fields on model after 15 Myr for 200ºK-500ºK ......... 146



500ºK ..................................................................................................... 147

Figure 6.21 The temperature distributions on model after 5 Myr for 273K-773K .. 148

Figure 6.22 The finite strain fields on model after 5 Myr for 273ºK-773ºK ........... 148



773ºK .................................................................................................... 149

Figure 6.24 The temperature distributions on model after 5 Myr for 273ºK-900ºK 150

Figure 6.25 The finite strain fields on model after 5 Myr for 273ºK-900ºK ........... 150



900ºK ..................................................................................................... 151

Figure 6.27 Temperature distributions on model after 5 Myr for 273ºK-1400ºK ... 152

xvii

Figure 6.28 The finite strain fields on model after 5 Myr for 273ºK-1400ºK ......... 152


Figure 6.29 b) The velocity fields with vectors on model after 5 Myr for 273ºK-

1400ºK ................................................................................................... 153

Figure 6.30 The finite strain fields on model after 5 Myr for 273ºK-900ºK with 0.125

Pa ........................................................................................................... 154

Figure 6.31The velocity fields on model after 5 Myr for 273ºK-900ºK with 0.e125

Pa ........................................................................................................... 154

xviii

LIST OF TABLES

Page

Table 3.1 The coordinates and observation days of the stations ................................ 34

Table 3.2 The coordinates and observation days of the General Command of

Mapping Stations ....................................................................................... 35

Table 3.3 The Coordinates of IGS stations which used in the processing ................. 35

Table 3.4 Horizontal GPS velocities of TURDEP and CORS-TR projects stations in

a Eurasian fixed frame and 1-σ uncertainties ............................................ 67

Table 3.5 Horizontal GPS velocities of General command Mapping stations in a

Eurasian fixed frame and 1-σ uncertainties ............................................... 68

Table 3.6 Euler Vectors Relative to Eurasia .............................................................. 72

Table 4.1 Horizontal GPS velocities of study area sites in a Eurasian fixed frame and

1-σ uncertainties ......................................................................................... 90

Table 4.2 Correlation coefficients of GPS and gravity observation results ............... 94

Table 6.1 Physical parameters used in the numerical modeling .............................. 139

xix

CHAPTER ONE

INTRODUCTION


regions in the world and is currently experiencing an approximately N–S continental

extension since at least Miocene time (Şengör et al., 1985; Yılmaz et al., 2000). Due

to this important case of Western Anatolia, deformations of the region were

examined by GPS and gravity measurement in this study.

Firstly, in the second chapter, the geological settings of the study area were given

briefly. In the application sections, in chapter three, the basic information of Global

Positioning System and data processing steps of GAMIT/GLOBK software were

explained. The GPS stations of TURDEP project, CORS-TR project and General

Command of Military were processed by using GAMIT/GLOBK software relative to

Eurasia fixed frame. The velocities of the stations were found as approximately 20-

25 mm/year to SW direction and the solution was compared with the previous study

of McClusky et al. (2000) and the results of TUBITAK project No:108Y285. Due to

the differences on the velocity directions, the study was separated to four regions.

Additionally, for determining the regional deformation, by using Euler vectors, the

Aegean and Anatolian block fixed solutions were presented. In Anatolian block

solutions, the area was separated into 3 groups according to the velocities of the

stations and the magnitude of the velocities was found as approximately 3-15 mm/yr.

Finally, the GPS solutions; Eurasia fixed frame, Anatolian and Aegean block fixed

solutions were compared with each other.

In chapter four, the GPS and microgravity data, which were obtained

simultaneously at 6 points; Akhisar (Manisa), Eşme (Uşak), Çal (Denizli), Bademli

(İzmir), Borlu (Manisa), Karacasu (Aydın), were compared for discussing about

vertical mass changes on the measurement points. For this purpose, the correlation

coefficients between these data set were calculated. The earthquakes distributions

which occurred between the years 2005-2014 and topographic changes were

1

compared together for interpreting the vertical changes on these points with the

relations between the GPS and microgravity.

In chapter five, obtained GPS velocities by using Gamit/ Globk software were

compared with the modeled GPS velocities by Coulomb 3.3 software on the northern

normal fault of Gediz graben and southern normal fault of the Büyük Menderes

graben by using Coulomb 3.3 software. In Gediz Graben application, the modeled

and observed GPS velocities are fitted at AKHT (Akhisar), BORT (Borlu) and

TRGT (Turgutlu). But there is not compliance between the velocities for SALH

(Salihli). Additionally, Coulomb software can not model velocities for ESMT and

CALT stations due to their far away locations from the fault. Then, the coulomb

stress changes were calculated and plotted for the depths of 4 km and 6 km and

additionally for the depth range between 0-4 km and 0-6 km. In Büyük Menderes

graben application, the modeled and observed GPS velocities are fitted for KRPT

and KRCT. The coherence between the modeled and observed velocities for CALT

is not well. Additionally, the modeled and observed velocities of BDMT have same

directions and they are fitted but the magnitude of the modeled velocity is higher

than the observed one. By these parameters the coulomb stress changes were

calculated and plotted for the depths of 3 km and 5 km and additionally for the depth

range between 0-3 km and 0-5 km. Additionally, the coulomb stress changes were

compared with the earthquakes occurred at the region between the years 1970-2014.

Complex structures systems are often too complicated to simply derive

relationships between applied loads and internal stresses. Hence, large structures are

divided up into many individual finite elements; that have a much simpler structural

form. The relationship between load, displacement, stresses and strains in a finite

element can be determined. Thus, it is computationally possible for a complex

structure to be modelled by assembling many individual finite elements. The

assembling process must satisfy equilibrium and continuity (Chandrupatla &

Belegundu, 2002). By this idea, in the last chapter (chapter six), the finite element

software ADELI was used for modeling deformation of Western Anatolia. The south

border of Menderes Extensional Metamorphic Complex (MEMC) at south side and

the North Anatolian Fault zone at north side were chosen as the boundary conditions

2

of the model. To the initial model, 3 mm/yr velocity magnitude was given to the

borders for giving extension to the model. The strain and velocity fields after 5Myr,

10Myr and 15 Myr of deformation were obtained. Finally, the findings were

compared with the topography and bottom topographic map for investigating the

crustal extension.

3

CHAPTER TWO

GEOLOGY OF THE STUDY AREA


regions in the world (Dewey & Şengör, 1979; Şengör & Yılmaz, 1981; Jackson &

McKenzie, 1984; Şengör et al., 1985; Eyidoğan & Jackson, 1985; Şengör, 1987;

Seyitoğlu & Scott, 1992; Bozkurt, 2001). It has continental extension approximately

N–S direction with the rate of 30-40 mm/year (Oral et al., 1995; Le Pichon et al.,

1995, McClusky et al., 2000). Western Anatolia is the part of the ‘Aegean

Extensional Province’ which is the region of distributed extension (Bozkurt, 2001)

(Figure 2.1).

Figure 2.1 Simplified tectonic map of Turkey showing major neotectonic structures and neotectonic

provinces. Red square shows the study area (modified from Bozkurt 2001).

The Aegean Extensional Province has experienced several compressional and

extensional deformational phases which have been summarized in many papers

(Şengör & Yılmaz, 1981; Okay & Tüysüz, 1999; Ring et al., 2010; Rimmelé et al.,

2003; van Hinsbergen et al., 2005, 2010; Çemen et al., 2006 and Jolivet et al., 2013).

All researchers agree that the province has experienced a Cenozoic extensional

tectonics and it is still effective. On the other hand, the initial time of the Cenozoic

4

extension has been controversial. Many researchers recommended that the Cenozoic

extensional tectonics in the western Anatolian began in the Middle Miocene (Yılmaz

et al., 2000) or earliest Miocene (Seyitoğlu et al., 1992). Several recent studies,

however, suggested that the extension began in Late Oligocene in Western Anatolia

(Lips et al., 2001; Catlos & Çemen; 2005; Çemen et al., 2006), or in Early Eocene in

the Rhodope region (Jolivet & Brun, 2010) (Ersoy et al. ,2014).

The cause and origin of the Cenozoic extension has also been controversial. The

proposals fall into five different models:

(1) ‘Tectonic escape’ model: the westward extrusion of the Anatolian block

along its boundary structures since the late Serravalian (12 Ma) (Dewey & Şengör,

1979; Şengör, 1979, 1980, 1987; Şengör & Yılmaz, 1981; Şengör et al., 1985; Görür

et al., 1995; Çemen et al., 1999).

(2) ‘Back-arc spreading’ model: back-arc extension caused by the south–

southwestward migration of the Aegean Trench system. However, there is no

consensus on the inception date for the subduction roll-back process and proposals

range between 60 Ma and 5 Ma (McKenzie, 1978; Le Pichon & Angelier, 1981;

Jackson & McKenzie, 1988; Spakman et al., 1988; Meulenkamp et al., 1994; Jolivet

& Brun, 2010; Jolivet et al., 2013).

(3) ‘Orogenic collapse’ model: the extension is induced by the spreading and

thinning of over-thickened crust following the latest Paleocene collision across

Neotethys during the latest Oligocene–Early Miocene (Seyitoğlu & Scott,1992;

Seyitoğlu et al., 1992).

(4) A three-stage continuous simple shear extensional model as a result of the

'tectonic escape', 'back-arc spreading' and 'orogenic collapse' mechanisms (Çemen et

al., 2006; Gessner et al., 2013).

(5) ‘Episodic’: a two-stage graben model: that involves a Miocene–Early

Pliocene first stage (orogenic collapse), and a Plio-Quaternary second phase

(westward escape of the Anatolian block) of N–S extension (Sözbilir & Emre, 1996;

5

Koçyiğit et al., 1999; Bozkurt, 2000, 2001, 2003; Işık & Tekeli, 2001; Lips et al.,

2001; Sözbilir, 2001, 2002; Bozkurt &Sözbilir, 2004; Koçyiğit, 2005).

Western Anatolia is the most important part of the Aegean Extensional Province

which includes Menderes Extensional Metamorphic Complex (MEMC) (Bozkurt &

Park, 1994; Emre, 1996; Lips et al., 2001; Işık & Tekeli, 2001; Çemen et al., 2006).

MEMC is one largest metamorphic core complexes in the world and began to

develop during the Late Oligocene-Early Miocene extensional deformation (Bozkurt

& Park, 1994; Hetzel et al., 1995; Işık & Tekeli, 2001; Işık et al., 2004; Çemen et al.,

2006; Glodny & Hetzel, 2007) and occurred in poly-phase deformation (Ersoy et al.,

2014).

The MEMC is bounded by NE-SW trending Miocene strike-slip faults along its

eastern and western margins edges (Çemen et al., 2006; Sözbilir et al., 2011; Ersoy et

al., 2011). The NE-SW trending strike-slip faulting along the western side of the

MEMC is known as İzmir-Balıkesir Transfer Zone (İBTZ; Sözbilir et al., 2003;

Erkül et al., 2005; Kaya et al., 2007; Uzel & Sözbilir, 2008; Ersoy et al., 2011;

Gessner et al., 2013). Several Miocene to Recent transtensional areas and basins

were developed along this zone. The eastern side of MEMC is bounded by the NE-

SW trending Southwestern Anatolian Shear Zone (Çemen et al., 2006; Karaoğlu &

Helvacı, 2012) which includes lots of oblique-slip faults and associated extensional

basins (Ersoy et al., 2014).

It has been proposed that the Cenozoic extensional tectonics in the Aegean was

begun as early as in Eocene (~45 Ma) by slab-roll back processes (Dinter & Royden,

1993; Brun & Faccenna, 2008; Brun & Sokoutis, 2012). The Cenozoic extensional

tectonics and related core complex formation migrated to the south with time, and

during the Late Oligocene to Middle Miocene times, Kazdağ, Cycladic and

Menderes Extensional Core Complexes formed (Ersoy et al., 2014).

The northern side of the MEMC was formed in three main stages: (1) latest

Oligocene-Early Miocene detachment faulting along the Simav Detachment Fault

(Işık & Tekeli, 2001; Isik, et al., 2003), (2) Middle Miocene detachment faulting

along Gediz (Alaşehir) Detachment Fault (Emre, 1996; Seyitoğlu et al., 2002) and

6

Büyük Menderes Detachment Fault (Bozkurt, 2000; Çemen et al., 2006; Gürer et al.,

2009), (3) Pliocene-Quaternary high-angle normal faulting, cutting the older

structures throughout the western Anatolia (Yılmaz et al., 2000). Each of these stages

is responsible for deformation, basin formation, sedimentation and extensive

volcanic activity in the upper plate (Ersoy et al., 2014).

By the radiometric age determination studies, it was supported that the first stage

Cenozoic extensional deformation in the northern MECM, along the Simav

Detachment Fault, has begun during the Late Oligocene. Several supra-detachment

basins in the upper plate, such as Demirci, Selendi and Uşak-Güre basins are located

in the northern MECM (Purvis et al., 2005; Çemen et al., 2006; Ersoy et al., 2011).

On the other hand, there is no supradetachment basin in the southern MEMC. It

means that the first-stage exhumation of the MEMC was occurred asymmetrically.

The second stage of the Cenozoic extension in the MEMC occurred in its central

parts, along the north-dipping Gediz (Alaşehir) Detachment Fault and south-dipping

Büyük Menderes Detachment Fault. These faults have also controlled the basins in

the upper plate (Sözbilir, 2002; Çemen et al., 2006; Çiftçi & Bozkurt, 2009; Şen &

Seyitoğlu, 2009; Öner & Dilek, 2013). The episodic forming of the MEMC was

accompanied also by Miocene to Recent NE-SW-trending strike-slip faulting along

its western margin (Ersoy et al., 2011) known as the IBTZ (Sözbilir et al., 2003;

Erkül et al., 2005; Uzel and Sözbilir, 2008; Ersoy et al., 2011; Uzel et al., 2013).

Complex deformation along the IBTZ is also resulted in basin formation and

volcanic activity (Ersoy et al., 2014).

7

CHAPTER THREE

DEFORMATION ESTIMATIONS WITH GPS PROCESSING

The Global Positioning System (GPS) is a satellite-based radio-navigation system

which is developed by the United States Department of Defense since early 1970s.

GPS was opened to civilian use in the 1980s. It is formed by a constellation of 24

satellites in six orbital planes with four satellites in each plane which are 20200 km

above the earth. The principal technique of GPS is to measure the time difference

between the satellite clock and the user’s receiver clock on the Earth and scale it by

speed of light in order to obtain the distance between the receiver and the satellite

observed. The approximate positions of the satellites are broadcasted along with the

GPS signal to the user via navigation messages (almanac and ephemerides).

Therefore, the position of the receiver can be determined by the known positions of

the satellites and the computed distances between the receiver and the satellites (Xu,

2007). On the other hand, a Global Navigation Satellite System (GNSS) is the name

covering all satellite positioning systems from different countries, namely, GPS

(USA), GLONASS (Russia), Galileo (European Union), Compass (China), QZSS

(Japan), IRNSS (India) and SBAS (Satellite Based Augmentation Systems) systems

(Kahveci & Yıldız, 2009).

The free global availability and accuracy of GPS signals for positioning and

timing, combined with the low cost of receiver chipsets, has made GPS the preferred

solution for a very wide and growing range of civilian applications (Locata, nd.)

Some civilian applications of GPS can be written as: surveying, geodesy, geophysics,

aviation, road transport, shipping & rail transport, meteorology, precision agriculture,

recreational activities, etc.

3.1 The Segments of GPS

GPS system consists of 3 segments which are Space, Control and user segments

(Figure 3.1).

8

Figure 3.1 GPS segments (Infohost, nd)

3.1.1 The Space Segment

The space segment consists of 24 satellites (currently 31 in November 2014),

nearly circular orbits about 20,200 km above the earth. The satellites are arranged in

6 orbital planes (Figure 3.2). Each plane is tilted at 55 degrees relative to the equator,

to provide polar coverage. Each satellite orbits the earth twice a day. Therefore, at

least four satellites are in view at any time, from any place on the earth’s surface.

This is significant because a GPS receiver requires signals from at least four satellites

in order to determine its location in three dimensions (3D). Each satellite contains

several atomic clocks to keep accurate time. Each satellite continuously broadcasts

low-power radio signals that identify it and provide information about its location in

space, as well as system timing and other data. Each GPS satellite transmits data on

three frequencies: L1 (1575.42 MHz), L2 (1227.60 MHz) and L5 (1176.45 MHz).

Pseudorandom noise (PRN) codes, along with satellite ephemerides, ionospheric

model, and satellite clock corrections are superimposed onto the carrier (Kahveci &

Yıldız, 2009).

9

The L1 and L2 carrier signals are modulated for receiving the information such as

satellite clock corrections, orbital parameters to the receiver by some codes and

navigation messages. In this modulation processing, unique meaningful PRN

(Pseudo Random Noise) code number are given to each satellite. The satellite signal

can be separated from each other by this unique PRN code (Montenbruck & Gill,

2000).

Figure 3.2 The space segment of GPS (Colorado University, nd)

At L1 frequency, there are two PRN codes and navigation message data. These

two codes are called as C/A (Course/Acquisition, Clear/Access) code and P

(Precise/Protected Code) codes. At L2 frequency, there are P code and navigation

message data. In the other words, the C/A code which is available for civil users is

transmitted with L1 frequency. P code which is available only for military is

transmitted both L1 and L2 frequency (Kahveci & Yıldız, 2009).

3.1.2 The Control Segment

The Control Segment consists of tracking stations system located around the

world (Figure 3.3). The Master Control station, located in Colorado, is responsible

10

for overall management of the remote monitoring and transmission sites. It measures

signals from the satellites and it calculates any position or clock errors for each

individual satellite based on information received from the monitor stations. The

corrected data are uploaded by the Master Control station. Finally, the satellites send

the new data over radio signals to the GPS receiver back to earth. The 4 Monitor

Stations located around the world (Hawaii and Kwajalein in the Pacific

Ocean; Diego Garcia in the Indian Ocean; Ascension Island in the Atlantic Ocean)

track up to 11 satellites twice a day (Environmental, nd).

Figure 3.3 The control segment of GPS (Environmental, nd).

3.1.3 The User Segment

The user segment consists of all civil and military GPS users. This segment

requires having an antenna and a receiver for decoding and storing the information

sent from the space segment.

3.2 Reference Coordinate Systems of GPS

In formulating the mathematics of satellite navigation information, it is necessary

to choose a reference coordinate system in which satellite and receiver can be

11

http://www.angelfire.com/hi2/kwa/

http://www.dg.navy.mil/

represented. In this formulation, it is typical to describe satellite and receiver states in

terms of position and velocity vectors measured in a Cartesian coordinate system

(Kaplan & Hegarty, 2006).

3.2.1 Earth-Centered Inertial (Space-fixed) (ECI) Coordinate System

For the purposes of measuring and determining the orbits of the GPS satellites, it

is convenient to use an Earth-centered inertial (ECI) coordinate system, in which the

origin is at the center of the mass of the Earth and whose axes are positing in fixed

directions with the respect to the stars.

In ECI coordinate system, the xy-plane is taken to coincide with the Earth's

equatorial plane, the x-axis is permanently fixed in a particular direction relative to

the celestial sphere, the z-axis is taken normal to the xy-plane in the direction of

North Pole, and the y-axis is chosen to form right-handed coordinate system (Kaplan

& Hegarty, 2006).

3.2.2 Earth-Centered Earth-Fixed (ECEF) Coordinate System

For the purpose of computing the position of a GPS receiver, it is more

convenient to use a coordinate-system that rotates with the Earth, known as an Earth-

centered Earth-fixed (ECEF) system. In such a coordinate system, it is easier to

compute the latitude, longitude and height parameters that the receiver displays. As

in ECI coordinate system, the ECEF coordinate systems' xy-plane is coincide with

the Earth's equatorial plane.

In the ECEF system, the x-axis points in the direction of 0° longitude, the y-axis

points in the direction of 90° E longitude and the z-axis is chosen to be normal to the

equatorial plane in the direction of the geographical North Pole. Therefore, the x, y,

and z-axes rotate with the Earth. The Cartesian coordinates (x, y, and z) of the user's

receiver are computed in ECEF system (Kaplan & Hegarty, 2006).

12

3.2.3 World Geodetic System-1984 (WGS-84)

The standard physical model of the Earth used for GPS applications is World

Geodetic System 1984 (WGS 84). This is the reference system used by U.S.

Department of Defense where has the responsibility of using the GPS system. WGS

84 provides an ellipsoidal model of the Earth's shape. In this model, cross-section of

Earth parallel to the equatorial plane are circular. The equatorial cross-section of the

Earth has radius 6,378.137 km, which is the mean equatorial radius of the Earth

(Kaplan & Hegarty, 2006).

3.3 Source of Errors

GPS system is the highest accurate global positioning and navigation system

although it has some weaknesses as in all other systems. In other words, some

random and systematic deviations are involved in the results of GPS measurements

(Kahveci & Yıldız, 2009). The main sources of errors which affect the distance

measurements between satellites and receivers are explained briefly.

3.3.1 Ephemeris (Orbital Position) Errors

Ephemeris errors are supposed to be a major factor limiting the usefulness

of GPS in high precision geodesy and applications. Even though the satellites

positions are constantly monitored, slight position or "ephemeris" errors can occur.

So, if the satellite location information in GPS navigation message has low accuracy,

this effect is called as ephemeris error. For removing the ephemeris errors, the

satellite orbits should be measured more sensitively by measuring or modeling the

forces acting on satellite with high accuracy (Kahveci & Yıldız, 2009).

3.3.2 Satellite and Receiver Clock Errors

Even though the GPS satellites are very sophisticated they contain some small

errors in the system. The atomic clocks used in GPS satellites are very precise but

13

http://link.springer.com/search?dc.title=Ephemeris&facet-content-type=ReferenceWorkEntry&sortOrder=relevance

they're not perfect. Small discrepancies can occur, and these cause measurement

errors in travel time. Since determining position is based on time measurements, the

greatest source of error is caused by satellite clock drift. These errors are monitored

and corrected by the Master Control Station. This effect can be removed by using

sensitive atomic clocks or using differential observations (Kahveci & Yıldız, 2009).

The role of the receiver and satellite clocks is very important in precise GPS

surveying. The receiver and satellite clock errors are multiplied by the speed of light.

Hence, because of the factor speed of light, a small clock error can cause a very large

code and phase error on the earth. For example a clock error of 1 µs translates to 300

m in range error. GPS receivers use cheap quartz crystal oscillators, to keep the cost

within a reasonable level. These oscillators have also the advantage of being small

devices and consume less power. In absolute positioning, the receiver clock offset

has to be estimated as an unknown parameter in the navigation solution which

estimates the receiver position and receiver clock at the same time. The receiver

clock offset can be estimated within 1 µs or better (Leick, 1995). In relative

positioning, between satellites differencing eliminates the receiver clock error term.

In Network RTK, where double difference is adopted as the main observable,

receiver and satellite clocks are completely eliminated through differencing.

3.3.3 Atmospheric Effects

The ionosphere and troposphere both refract the GPS signals. The ionosphere is

the ionized part of the earth’s atmosphere lying between about 50 km and several

earth radii (Davies, 1990). The amount of free electrons is more enough to change

the propagation of electromagnetic waves. The effects of ionosphere are different on

code and phase measurements. While the ionosphere effects as group delay on code

measurements, it effects as phase advance on phase measurements. Since the

ionospheric effect is frequency dependent, this effect can be removed by using dual-

frequency GPS receiver.

Troposphere is the lowest layer and the non-ionized part of the atmosphere. The

electromagnetic signals are affected by the neutral (non-ionized) atmosphere and this

14

http://tekmon.gr/1-4-2-2-double-difference-observable/

effect is called tropospheric delay. Neutral atmosphere changes the speed and

directions of the electromagnetic waves. The tropospheric delay is frequency

independent and this effect can not be removed by using dual-frequency GPS

receiver. This effect can be decreased by using suitable modeling (Kahveci & Yıldız,

2009).

3.3.4 Selective Availability

Selective Availability (SA) is the intentional degradation (limits accuracy of

satellite signals) of the GPS system by the U.S. Department of Defense for security

reasons. On May 1, 2000 the White House announced a decision to discontinue the

intentional degradation of the GPS signals to the public beginning at midnight.

(Kahveci & Yıldız, 2009).

3.3.5 Multipath

Multipath is the signal refection effect which is occurred when the satellite signals

reach the receiver antenna by two or more paths. The possible sources of reflection

around the receiver antenna are buildings, vehicles, water surfaces (sea, lake, etc.)

and other reflective surfaces (Figure 3.4). If the antenna is kept stable at the same

point a few days, the main effect of antenna signal reflection can be measured.

Therefore, multipath error can be corrected by removing this effect (Kahveci &

Yıldız, 2009).

15

Figure 3.4 Sources of signal interference, multipath (Ashtray, nd).

3.3.6 Receiver Antenna Phase Center Error

The antenna phase center variation differs 1-2 mm up to 1-2 cm from each other

related with the type of antenna. The amount of antenna phase center variation is

different at each antenna type, so it is difficult to model them. Due to the same type

of antenna show similar variations, by directing the antennas to the same direction

(generally to magnetic north) this effect of error is minimized (Kahveci & Yıldız,

2009).

3.4 Differential Observations Based on GPS Measurements

The differences created by code and phase observation are used for correcting the

some sources of errors such as the receiver clock errors, satellite clock errors and

phase initial ambiguity.

3.4.1 Single Differences

The differences between the phase observations which are done simultaneously

by two different receivers respect to the same satellite are called single differences

observation. By this observation, satellite clock error is eliminated. If the single

16

difference observation is done for the single receiver between two satellites, in this

case, receiver clock error is eliminated.

3.4.2 Double Differences

The differences between the two single differences are called double differences

observation. By the double differences observation, both of the clock errors (satellite

and receiver) are removed.

3.4.3 Triple Differences

The differences between the two double differences observations on two receivers

are called triple differences. By triple differences observation, the initial phase

ambiguity is removed (Kahveci & Yıldız, 2009).

3.5 The Principle of GPS Measurement

GPS gives the exact position of any point on the earth by computing precisely

where each satellite is in space, measuring the travel time of radio signals broadcast

by the satellites, and accounting for delays the signals experience as they travel

through the earth’s atmosphere. Firstly, when a GNSS receiver is first turned on, it

downloads orbit information from all the satellites called an almanac. The almanac is

a data file that contains information of orbits and clock corrections of all satellites.

As the second step, the GNSS receiver calculates the distance from each satellite to

the receiver by using the distance formula (distance = velocity x time). The receiver

already knows the velocity, which is the speed of a radio wave or 300 km per second

(the speed of light). To determine the time part of the formula, the receiver times

how long it takes for a signal from the satellite to arrive at the receiver. The GNSS

receiver multiplies the velocity of the transmitted signal by the time it takes the

signal to reach the receiver to determine distance. Consequently, the receiver

determines position by using triangulation. When it receives signals from at least

three satellites the receiver should be able to calculate its approximate position (a 2D

17

position). The receiver needs at least four or more satellites to calculate a more

accurate 3D position. The position can be reported in latitude/longitude, UTM, or

other coordinate system (Nwcg, nd).

Several classifications can be made for GNSS positioning methods. But, there are

mainly two types of positioning methods, namely, absolute and relative positioning.

(Kahveci et al., 2013). A general classification of GNSS positioning methods are

shown in Figure 3.5. In relative positioning, code (pseudorange) and phase (carrier

beat phase) measurements are observed. Code (pseudorange) measurements are

observed for obtaining navigation in real-time applications. In the applications which

need high accuracy and in high precision scientific studies, phase observations are

used (Kahveci & Yıldız, 2009). Therefore, in this study relative static positioning

with phase observations method was used and only the principle of phase

measurement was explained.

Since 1980s until 2000s episodic GPS campaigns with several hours of static

relative phase observations depending on the baseline lengths were widely in use for

scientific studies and researches. Because performing long observation times (from

several hours to 24 hours) was the only way to solve for all unknowns and eliminate

some error sources on GPS baselines. But with the advent of Continuously Operating

Reference Stations (CORS) networks, it is now a usual and economic procedure to

obtain and process necessary GPS/GNSS data continuously and in real time. The

name of such a network in Turkey is CORS-TR and it has been in use since 2009.

18

Figure 3.5 General classifications of GNSS Positioning methods (Kahveci et al., 2013).

3.5.1 The Principle of Phase Measurement

This method achieves only millimeter accuracy on baselines of several

hundred kilometers, so it is used for tectonic movement measurements. The

measurement is made on the carrier phases L1 and L2 with wavelengths of 19

cm and 24.4 cm, respectively. The observation consists of the phase

difference between the signal received from the satellite and generated by the

receiver. It can be written for satellite i and the station j.

Φ𝑖,𝑗(𝑡) = Φ𝑟𝑒𝑐,𝑖,𝑗(𝑡) −Φ𝑔𝑒𝑛,𝑖,𝑗(𝑡) (3.1)

This phase is ambiguous, it is determined with the top part of fractional number

of waves between the satellite and the station cycles (Figure 3.6). The

oscillation between the signal received from the satellite and the output from

the receiver is not measurable as the difference between the satellite clock and

receiver reference time t0. The measurable part of the period is ∆t in Figure 3.6. The

19

observation may be converted into units of cycles by multiplying fo which has the

fundamental frequency, 10.23 MHz At time t1, beginning of the measurement, the

effective observable part, Φ𝑖,𝑗′ :

Then the fractional part of the cycle between the received signal and generated by receiver:

Φ𝑖,𝑗′ (𝑡1) = −Δ𝑡(𝑡1) ∙ 𝑓𝑜 (3.2)

While the measurement is taken in a certain time, the distance between the

satellite and the station varies during the recording. Therefore, the observable Φ𝑖,𝑗′

evolve over the time because of the geometric delay. The phase ambiguity, n, and

initial offsets,∆Φ(𝑡0) , remain constant. The continuous observation of ∆t only

provides information on the evolution of the distance between the satellite and the

receiver. The desired amount remains, however the signal propagation time between

the satellite and the receiver, it corresponds to the geometric delay τ of Figure 3.6.

The relationship between the geometric delay, the observable and the unknown

parameters are given by King et al. (1985). The geometric delay 𝜏𝑖,𝑗 which links the

signal emitted by the satellite i to the j received by the receiver is:

Φ𝑟𝑒𝑐,𝑖,𝑗(𝑡1) = Φ𝑒𝑚,𝑖(𝑡1 − 𝜏𝑖,𝑗(𝑡1)) (3.3)

Here, Φ𝑟𝑒𝑐,𝑖,𝑗(𝑡) is the phase emitted by the satellite at 𝑡1 time, Φ𝑒𝑚,𝑖(𝑡) is the

phase emitted by the satellite at 𝑡1 − 𝜏𝑖,𝑗(𝑡1) time. With a value of approximately

0.1 second, τ is a small variation of the t time of the measurement. Therefore, it is

possible to carry out a limited development of Φ𝑒𝑚(𝑡 − 𝜏) around Φ𝑒𝑚(𝑡):

Φ(𝑡 − 𝜏) = Φ𝑒𝑚(𝑡) −Φ𝑒𝑚′ (𝑡) ∙ 𝜏(𝑡) + Φ𝑒𝑚

′′ (𝑡)2

∙ 𝜏2(𝑡) − … (3.4)

20

A development up to the second order in τ is sufficient, and the terms in τ2 are

negligible. In the simple case of a constant frequency 𝑓𝑜 of the satellite clock, the

phase emitted is written by:

Φ𝑒𝑚(𝑡) = ∫ 𝑓0𝑑𝑡 + Φ𝑒𝑚(𝑡𝑜𝑡𝑡0

) =𝑓0 ∙ (𝑡 − 𝑡0) + Φ𝑒𝑚(𝑡0) (3.5)

and its temporal derivative;

Φ𝑒𝑚′ (𝑡) = 𝑓0

Φ𝑒𝑚′′ (𝑡) = 0

are given. Here 𝑡0 is the beginning of the integration and it is the reference time or

phase emitted has a value of Φ𝑒𝑚(𝑡0). This value is considered as a constant of

integration in Equation 3.5.

By replacing Φ𝑒𝑚 and its temporal derivatives in the Equation 3.4 by the values

previously calculated in Equation 3.5, it is obtained;

Φ𝑒𝑚(𝑡 − 𝜏) = 𝑓0 ∙ (𝑡 − 𝑡0) + Φ𝑒𝑚(𝑡0) − 𝑓0 ∙ 𝜏(𝑡) (3.6)

At the t1 time of measurement and in the case of a stable frequency of the satellite

clock, were taken from the Equation 3.3 and Equation 3.6, the phase received by the

station is:

Φ𝑟𝑒𝑐,𝑖,𝑗(𝑡1) = 𝑓0 ∙ (𝑡1 − 𝑡0) + Φ𝑒𝑚,𝑖(𝑡0) − 𝑓0 ∙ 𝜏𝑖,𝑗(𝑡1) (3.7)

21

Figure 3.6 Principle of GPS phase measurement. When powering up the receiver at the time t0 , it

generates a signal Φgen similar with the signal transmitted by the satellite Φem .The frequency fo of

both signals is considered as constant. At t0 time, the phases have an offset ∆Φ(𝑡0). At t0 time, the

signal arrives from satellite to the receiver with a delay, τ. This moment 𝑡𝑜 + 𝜏 = 𝑡1 is considered as

the beginning of the measurement Φ = Φ𝑟𝑒𝑐 − Φ𝑔𝑒𝑛. If the fraction of the cycle (∆t) can be measured

accurately, the integer part of the cycle or ambiguity of the measure (n) becomes unknown. The

offsets of initial phases (ΔΦ(t0)) are also unknown. The geometric delay τ that it is wanted to

measured is therefore composed of

Δ𝑡 + 𝑛𝑓0

+ ΔΦ(𝑡0)𝑓0

whose only Δt is measurable (Vernant, 2003).

By assuming that the receiver clock is stable (like as satellite clock is stable) and

the frequency f0 is identical to the satellite, then the phase generated is expressed as:

Φ𝑔𝑒𝑛,𝑗(𝑡1) = ∫ 𝑓0𝑑𝑡 + Φ𝑔𝑒𝑛,𝑗(𝑡𝑜

𝑡1𝑡0

) =𝑓0 ∙ (𝑡1 − 𝑡0) + Φ𝑔𝑒𝑛,𝑗(𝑡0) (3.8)

As given previously, Φ𝑔𝑒𝑛,𝑗(𝑡𝑜) is the phase value generated at the beginning

time, 𝑡0, of the integration. This value becomes the integration constant.

At the time, t1, (which may be the beginning of the measurement), found for the

difference between the phase received (Equation 3.7) and the phase generated

(Equation 3.8) by the station is written;

22

Φ𝑟𝑒𝑐,𝑖,𝑗(𝑡1) −Φ𝑔𝑒𝑛,𝑗(𝑡1) = −𝑓0 ∙ 𝜏𝑖,𝑗(𝑡1) + Φ𝑒𝑚,𝑖,𝑗(𝑡0) − Φ𝑔𝑒𝑛,𝑗(𝑡𝑜) (3.9)

𝑓0 ∙ 𝜏𝑖,𝑗(𝑡1) corresponds to the geometric delay (Figure 3.6) is expressed in cycles.

Once the offset of the phases at reference the time subtracted from this period

Φ𝑒𝑚,𝑖(𝑡0) − Φ𝑔𝑒𝑛(𝑡0), therefore, the path is accessed between the satellite and the

station in the form of a decimal number of cycles. This value can be decomposed

into a number n integer and fractional part of cycles ∆t. When the measurement at

time t1, the observable is only the fractional part of the difference between the phase

received and the generated.

The geometric delay 𝜏 is the sum of three terms:

1. The fractional part of measurable cycle without ambiguity,

2. The integer number n of cycles of the signal between the satellite and the

station,

3. The part ΔΦ(𝑡0) =Φ𝑒𝑚,𝑖(𝑡0) − Φ𝑔𝑒𝑛(𝑡0) caused by the offsets of the satellite

phases and the receiver at the time of reference 𝑡0.

Therefore τ can be written as:

𝜏(𝑡1) = ∆Φ(𝑡0)𝑓0

+ Δ𝑡 + 𝑛𝑓0

(3.10)

The right side of Equation 3.9 is written as;

−𝑓0 ∙ 𝜏𝑖,𝑗(𝑡0) + Φ𝑒𝑚,𝑖,𝑗(𝑡0) −Φ𝑔𝑒𝑛,𝑗(𝑡0) = −𝑓0 ∙ Δ𝑡 − 𝑛 (3.11)

For the observable Φ𝑖,𝑗′ = −𝑓0 ∙ Δ𝑡 so it is given like:

Φ𝑖,𝑗′ (𝑡1) = −𝑓0 ∙ 𝜏𝑖,𝑗(𝑡1) + Φ𝑒𝑚,𝑖,𝑗(𝑡0) −Φ𝑔𝑒𝑛,𝑗(𝑡0) + 𝑛𝑖,𝑗 (3.12)

Equation 3.10 is the measurable part of Equation 3.1 at a given moment. By

23

knowing the ambiguity n and the value of the initial offset phasesΔΦ(𝑡0), 𝜏𝑖,𝑗 and

therefore the station-satellite distance is precisely determined. The variable 𝜏𝑖,𝑗 is the

only time-dependent in Equation 3.9. Therefore, in the general case of continuous

recording and without knowledge of ambiguity, Φ𝑖,𝑗(𝑡) shows only variations in

distance between the satellite and the receiver. The offset of the phases and the

ambiguity remain constant as long as the signal is not interrupted. After each loss of

signal, the ambiguity n of the phase measurement takes a new value. Continuous

observations during a certain time used to estimate by indirect methods, the values of

these parameters.

3.6 Data Processing Steps

3.6.1 Processing: The Three-Step Method

In this study GPS data is processed by using GAMIT/GLOBK software (Herring

et. al, 2010a, 2010b, King & Bock, 2009) which is created by three-step approach

described by Feigl et. al, (1993); Oral, (1994) and Dong et. al, (1998).

GAMIT/GLOBK is a comprehensive GPS analysis package developed at MIT,

the Harvard-Smithsonian Center for Astrophysics (CfA), and the Scripps Institution

of Oceanography (SIO) for estimating station coordinates and velocities, stochastic

or functional representations of post-seismic deformation, atmospheric delays,

satellite orbits, and Earth orientation parameters (Herring et al., 2010a).

In the first step, the weighted least squares algorithm are used to estimate the

relative positions of a set of stations, orbital and Earth-rotation parameters(EOPs),

zenith delays, and phase ambiguities by fitting to doubly differenced phase

observations and applying loose apriori constraints to all parameters (McClusky et. al,

2000). This process includes 3 or 4 International GNSS System (IGS) stations for

linking the regional networks with global networks. These calculations are performed

by GAMIT (King & Bock, 2009) part of the software. GAMIT produces estimations

and an associated covariance matrix ("quasi-observations") of station positions and

24

orbital and Earth-rotation parameters which are then used as the input files at second

step (GLOBK part).

In the second step, the loosely constrained estimates of station coordinates, orbits

and EOPs and their daily covariance are used as quasi-observations in a Kalman

filter for estimating a consistent set of coordinates and velocities. Then, for each day

the quasi-observations from the regional (local) analysis combined with the quasi-

observations of a global analysis of IGS data performed by SOPAC (McClusky et al.,

2000). These calculations are done by GLOBK part.

Kalman filter which is used in various branches of engineering (Cannon et al.,

1986, Schwards et al., 1989, Donellan et al., 1993, Feigel et al., 1993, Lu &

Lachapelle, 1994), becomes a method used in deformation analysis (Pelzer, 1986;

Çelik, 1998). By this method, the parameters (constant disruptive acceleration and

system noises) which are related to period and explained as stochastic can be solved

with modeling and especially the rapid changes on the point can be modeled (Demir,

1999). Additionally, even if the measurement quantities are less than the parameter

amounts, movement parameters can be estimated by the stochastic model which is

chosen by Kalman filter. It can be said that if the suitable stochastic model is created

for the linear or non-linear changes, the Kalman filter method can be affected on

determining the deformation (Ünver, 1994; Doğan, 2002).

In the third step, the reference frame for the velocity estimates are defined and

this frame is constrained on each day using a reliable set of global IGS stations with

realization of ITRF (International Terrestrial Reference Frame) no-net-rotation

(NNR) frame (Ray et al., 2004), while estimating the translation, orientation and

scale parameters for each day with the origin fixing module (glorg) of GLOBK part

of the software.

In parameter estimation based on least-squares, the conventional measure of

goodness-of-fit is the χ2 (chi-square) statistic, defined for uncorrelated data as the

sum of the squares of each observation residual (post-fit observed minus computed

observation, “o-c”) divided by its assigned uncertainty. In a GPS analysis parameter

correlations arise so the computation of χ2 in GAMIT or GLOBK involves a

25

complex matrix operation (see Dong et al., [1998]), but the idea is the same. The

value of χ2 is usually normalized by dividing by the “degrees of freedom” (df), the

number of observations minus the number of parameters estimated, so that the ideal

value for properly weighted, independent random observations is 1.0 (For details

Herring et al. (2010a) and Herring et al. (2010b) can be checked) .

3.6.2 Pre-Processing Steps

Before beginning the process in GAMIT/GLOBK software, there are some files

needed to prepare.

First of all it is needed to create an experiment directory (with the name of

processing year, as an example 2009) with two subdirectories: ‘tables’ and ‘Rinex’.

The session day files (Rinex files) of the IGS stations (which are downloaded from

http://sopac.ucsd.edu/dataArchive/dataBrowser.html) and study field local GPS

stations which are planned to use in processing must be copied into the "Rinex"

directory

Then, under the experiment directory (e.g. 2012), with running "sh_setup"

command:

sh_setup -yr 2012

all of the required templates and tables are linked and copied to "tables" subdirectory

automatically. "tables" directory contains lost of the files, but some of them are

needed to prepare before processing.

At below the needed changes on the files are described briefly. (The details can be

found at Herring et al. (2010a)). These are:

1. Process.defaults : In this file, only change is needed on ITRF (International

Referance Frame) version (ITRF2000, ITRF2005 or ITRF2008).

2. Sittbl. : In this file, it is need to write the confidence interval of GPS stations.

This file contains the confidence interval of IGS stations but it is needed to

26

add the GPS stations of the study area. If the coordinates of GPS stations are

confident, “NNN 0.005 0.005 0.01” is written after the name and code of

station such as:

IZMT IZMT_GPS NNN 0.005 0.005 0.01

3. Sites.defaults : This file contains the information about which local and IGS stations are to be used and how station data are to be handled. izmt_gps tusa localrx xstinfo glrepu

Here "izmt_gps" is the station code; "tusa" is the 4 lettered name of the data

group. "localrx" means that the information of the stations are not obtained

from ftp, this information will be obtained from the "station.info" file which

is prepared by the user. "glrepu" means stations will be used in GLRED

repeatability solutions

4. Station.info: This file is the most important file of the program. It must be

prepared very carefully. It contains general information of the stations (start

and finish time of the session, Antenna height, Antenna type, Height

measurement code, receiver type, hardware and software versions, Serial

numbers of receiver and Antenna)

5. Sestbl. : This file has the information about the files using during the

processing. The changes can be done on 'mapping function' type and 'ocean

tide loading', 'atmospheric loading'.

After preparing these files, the GPS data are ready for processing.

3.6.3 Processing Steps

3.6.3.1 Processing Steps of GAMIT Program

For starting the process on GAMIT program, "sh_gamit" command should be run.

The full command is:

sh_gamit -expt [4 lettered name of the data group] –s [year] [start day of session]

[final day of session] -orbit IGSF –yrext

27

or

sh_gamit –d [year] [1st day 2nd day.....final day of the session] -expt [4 lettered

name of the data group] -orbit IGSF –yrext

After "-s" command, the start day and final day of the session are written. As an

example; by writing " -s 2012 180 185 " the program process all days between 180

and 185th days of year of 2012. The days are given in Julian days.

If "-d" command is written, all processing days must be added. As an example;

" -d 2012 180 181 182 183 184 185 "

After "–expt" command 4 lettered data group name is written. The name must be

same which is written in "sites.defaults" file.

After "-orbit" the orbit files is specified. Here, IGSF (IGS Final Orbits) is chosen.

There are different options for orbit files.

By writing "–yrext" command the session day files are created like as 2012_180,

2012_181...etc.

Consequently, the outputs are downloaded and created at the session day files

(exp. 2012_180, 2012_181,etc.).

3.6.3.2 Processing Steps of GLOBK Program

GLOBK, is a global Kalman filtering program and it combines the geodetic

results which are created by GAMIT pogram. Besides, GLOBK is combined the

results which are created by other GPS processing program (e.g. Bernese, GIPSY)

successfully.

The main applications are succeed by GLOBK are given such as:

1) Combining analysis: It evaluates the position and orbital results which obtained by

GPS networks with daily GPS data.

28

2) Repeatability Analysis: It creates time-series of the daily GPS data

3) Velocity Analysis: It combines the daily data for creating velocity estimations.

Before beginning these processing steps, a file namely, ‘gsoln’ is created and all

of the steps are run under this file. At the day directories obtained by GAMIT have h-

files which contain daily solutions files from analysis of primary observations of the

stations. These h-files must be converted to binary h-files for using in Kalman filter

as the input files. This converting can be succeed by ‘htoglb’ command. ;

htoglb ../glbf ../glbf/svt f=NAME ../2012*/hNAME*

Here, ‘NAME’ is the 4 lettered name of the data group, 2012* presents the day

directories of year of 2012. Now, h-files can be used for combining solutions and all

daily h-files are copied to ‘glbf’ file.

For combining solutions, all h-files are needed to be in a single file as a list. For

collecting these h-files,

ls ../glbf/*.glx > NAME.gdl

command is used. Therefore, all h-files are collected in the same file as a list namely

NAME (4 lettered name of the data group).

For viewing the day solutions, the repeatabilities files are created by ‘glred’

command. For this purpose ‘glorg’ (glorg.cmd) and ‘globk’ (globk.cmd) command

files should be prepared carefully (for understanding how to prepare these files,

Herring et al. (2010a) can be checked).

glred 6 NAME_R01.prt NAME_R01.log NAME.gdl globk.cmd

ensum 2 su NAME _R01.ens va NAME _R01.ens NAME _R01.org

By these commands repeatability files (time-series) are created. For plotting the

time-series files,

29

multibase ../vaNAME_R01.ens –y

sh_base1c3n –year –o 1 –f mb*

commands are used. By these time-series files, the displacements can be obtained as

days or years.

For plotting the velocity vectors, ‘globk’ command is runned;

globk 6 NAME.prt NAME. log NAME.gdl globk.cmd

by this command, .prt and .log files are created by using .gdl file. For creating local

apriori (.apr) file for the study stations and getting position information of the

stations “sh_exglk” command is used:

sh_exglk –f NAME.org -apr NAME.apr –pos NAME.pos

The new created apriori file (NAME.apr) which contain the coordinates of the study

stations are added to globk.cmd file. Then, these command (globk and sh_exglk) are

rerun. Finally for plotting the velocities of the stations;

sh_plotvel –f NAME.pos –color –arrow_label mm –ps NAME -

RX1/X2/Y1/Y2

command is run. This command is to plot the figures on GMT (Generic Mapping

Tools). After –ps command, it is needed to write the name of the plotting file. After

“-R”, the coordinates of the plotting area need to given.

3.7 The Applications

The GPS stations which are located at Western Anatolia were chosen for

investigating the extension of the area. For this purpose, the stations of "Multi-

Disciplinary Earthquake Researches in High Risk Regions of Turkey Representing

Different Tectonic Regimes" (TURDEP) Project were reached from The Scientific

and Technological Research Council of Turkey (TUBITAK), Marmara Research

Center, Earth and Marine Science Institute and the stations of “Continuously

Operating Reference Stations-Turkey” (CORS-TR) project were provided from

30

General Directorate of Land Registry and Cadastre, Map Department and

additionally, the other GPS stations data were attained from General Command of

Mapping (Figure 3.7).

As the first step, the 11 continuous GPS stations of CORS-TR projects; AYD1

(Aydın, City Center), BALK (Balıkesir, City Center), CESM (Çeşme, Izmir), DEIR

(Demirci, Manisa), DENI (Denizli, City Center), HARC (Harmancık, Bursa), IZMI

(Izmir, City Center), KIKA (Kırkağaç, Manisa), MUGL (Muğla, City Center), SALH

(Salihli, Manisa), USAK (Uşak, City Center) and 10 continuous GPS stations of

TURDEP Project; AKHT (Akhisar, Manisa), BDMT (Bademli, Izmir), BORT (Borlu,

Manisa), CALT (Çal, Denizli), ESMT (Eşme, Uşak), IZMT (Izmir, City Center),

KRCT (Karacasu, Aydin), KRPT (Karpuzlu, Aydin), TRBT (Torbali, Izmir) and

TRGT (Turgutlu, Manisa) (Figure 3.8) were processed together by using

GAMIT/GLOBK for the days between 180th – 195th (as Julian days) of 2009-2010-

2011 years. The coordinates of the stations are given at Table 3.1.

As the second step, the stations of General Command of Mapping were processed.

In Figure 3.7, it is seen that there are 17 stations of General Command of Mapping

which shown by blue marks. But in the processing, the statistical (weighted root

mean square (wrms)) solutions were found too high. Therefore, 10 stations were

removed from the processing. Consequently, 7 stations; BAYO (Bağyolu, Manisa),

CEIL (Çeşme, Izmir), CKOY (Çiftlikköy, Izmir), EMET (Emet, Kütahya), LTFY

(Lütfiye, Bursa), YENF (Yenifoça, Izmir), ZEYT (Zeytinalan, Izmir) were processed

by using GAMIT/GLOBK for the days which was given at Table 3.2. Therefore, the

stations shown in Figure 3.8 were used in the processing.

31

Figure 3.7 The GPS stations are located Western Anatolia. Pink marks present TUBITAK/TURDEP

project station, yellow marks present CORS-TR project stations and blue marks present the stations of

General Command of Mapping. This figure is created by using Google-Map tool.

32

Figure 3.8 The GPS stations which used in the study are shown in general tectonic structures map of

Western Anatolia. Pink colored stations are the stations of TURDEP project, yellow colored are the

stations of CORS-TR project and blue colored are stations of General Command of Mapping

( Modified from Bozkurt, 2001).

33

Table 3.1 The coordinates and observation days of the stations.

Site Longitude (º) Latitude (º) Observation Days

STATIONS OF CORS-TR PROJECT

AYD1 27.83788 37.84073 2009-2011 / 180th-195th

BALK 27.89363 39.63937 2009-2011 / 180th-195th

CESM 26.37257 38.30382 2009-2011 / 180th-195th

DEIR 28.64840 39.03485 2009-2011 / 180th-195th

DENI 29.09213 37.76210 2009-2011 / 180th-195th

HARC 29.15276 39.67774 2009-2011 / 180th-195th

IZMI 27.08182 38.39481 2009-2011 / 180th-195th

KIKA 27.67221 39.10599 2009-2011 / 180th-195th

MUGL 28.36444 37.21636 2009-2011 / 180th-195th

SALH 28.12355 38.48309 2009-2011 / 180th-195th

USAK 29.40522 38.67921 2009-2011 / 180th-195th

STATIONS OF TURDEP PROJECT

AKHT 27.89513 38.99753 2009-2011 / 180th-195th

BDMT 28.04087 38.12027 2009-2011 / 180th-195th

BORT 28.55090 38.75191 2009-2011 / 180th-195th

CALT 29.40375 37.99182 2009-2011 / 180th-195th

ESMT 29.10617 38.42497 2009-2011 / 180th-195th

IZMT 27.19424 38.37510 2009-2011 / 180th-195th

KRCT 28.66741 37.82766 2009-2011 / 180th-195th

KRPT 27.81555 37.58215 2009-2011 / 180th-195th

TRBT 27.39112 38.31378 2009-2011 / 180th-195th

TRGT 27.90726 38.41491 2009-2011 / 180th-195th

34

Table 3.2 The coordinates and observation days of the General Command of Mapping Stations.

Site Longitude (º) Latitude (º) Observation Days

BAYO 27.30801 38.71103

2000 / 261th-262nd

2001 / 211th- 212nd

2005 / 123th -124th

CEIL 26.38529 38.31084 2000 / 271st – 272nd

2001 / 211st -212nd

CKOY 26.23337 38.28772 2001 /208th – 209th

2004 / 212nd -213rd

EMET 29.24559 39.33510 2000 / 271st – 272nd

2005 / 123th -124th

LTFY 28.41285 39.99288

2000 / 89th

2001 / 97th -297th

2004 / 157th -158th

YENF 26.79080 38.74109 2000 / 258th 259th

2001 / 214th -215th

ZEYT 26.49654 38.20466 2001/ 211th- 212nd

2004 / 215th -216th

Table 3.3 The Coordinates of IGS stations which used in the processing.

Site Longitude (º) Latitude (º)

TUBI 29.45068 40.78672 ISTA 29.01934 41.10445 BUCU 26.12574 44.46394 GLSV 30.49673 50.36418 NICO 33.39644 35.14099 MATE 16.70446 40.64913 MIKL 31.97284 46.97278 PENC 19.28153 47.78960 WTZR 12.87891 49.14420 ZECK 41.56506 43.78839

In order to define the station coordinates and velocities, 10 IGS stations of which

has a good processing and measurement history as well as which can be used to

calculate the velocity vectors were chosen to circulate the network area. For defining

Eurasia fixed reference frame; TUBI (Turkey), ISTA (Turkey), ZECK (Russia),

NICO (Cyprus), MIKL (Ukraine), GLSV (Ukraine), BUCU (Romania), PENC

35

(Hungary), WTZR (Germany) and MATE (Italy) were chosen as IGS stations

(Figure 3.9). For the processing of GPS observations, in addition to study area

stations, observations of 10 IGS stations were also included in order to make a link

between the local and global networks. The coordinates of the IGS stations were

given at Table 3.3. The GPS data were proceed by using ITRF 2008 (International

Terrestrial Reference Frame) relative to Eurasia fixed frame. The GAMIT/GLOBK

software was used to process the data by the steps which were explained previous

part. Firstly, with GAMIT day folders were created and then by GLOBK these daily

solutions were combined and processing solutions as time-series for TURDEP and

CORS- TR stations were plotted (Figure 3.10 up to Figure 3.29).

Figure 3.9 The IGS stations which used in processing are shown by red circle.

36

Figure 3.10 The processing solutions of AYD1 for the days between 180th-195th of the years between

2009-2011

37

Figure 3.11 The processing solutions of BALK for the days between 180th-195th of the years between

2009-2011

38

Figure 3.12 The processing solutions of CESM for the days between 180th-195th of the years between

2009-2011

39

Figure 3.13 The processing solutions of DEIR for the days between 180th-195th of the years between

2009-2011.

40

Figure 3.14 The processing solutions of DENI for the days between 180th-195th of the years between

2009-2011.

41

Figure 3.15 The processing solutions of HARC for the days between 180th-195th of the years between

2009-2011.

42

Figure 3.16 The processing solutions of IZMI for the days between 180th-195th of the years between

2009-2011.

43

Figure 3.17 The processing solutions of KIKA for the days between 180th-195th of the years between

2009-2011.

44

Figure 3.18 The processing solutions of MUGL for the days between 180th-195th of the years

between 2009-2011.

45

Figure 3.19 The processing solutions of SALH for the days between 180th-195th of the years between

2009-2011.

46

Figure 3.20 The processing solutions of USAK for the days between 180th-195th of the years between

2009-2011.

47

Figure 3.21 The processing solutions of AKHT for the days between 180th-195th of the years between

2009-2011.

48

Figure 3.22 The processing solutions of BDMT for the days between 180th-195th of the years

between 2009-2011.

49

Figure 3.23 The processing solutions of BORT for the days between 180th-195th of the years between

2009-2011.

50

Figure 3.24 The processing solutions of CALT for the days between 180th-195th of the years between

2009-2011.

51

Figure 3.25 The processing solutions of ESMT for the days between 180th-195th of the years between

2009-2010.

52

Figure 3.26 The processing solutions of IZMT for the days between 180th-195th of the years between

2009-2011.

53

Figure 3.27 The processing solutions of KRCT for the days between 180th-195th of the years between

2009-2011.

54

Figure 3.28 The processing solutions of KRPT for the days between 180th-195th of the years between

2009-2011.

55

Figure 3.29 The processing solutions of TRBT for the days between 180th-195th of the years between

2009-2011.

56

The wrms values (repeatabilities) give information about consistency among

observation days of the stations. For giving the clear information about the GPS

stations, the wrms repeatabilities were given as graphics (Figure 3.30 and 3.31). In

Figure 3.30, it can be seen that North, East and Up components of the stations are

below 10 mm which is the acceptable value in this study. Also, the wrms

repeatabilities of IGS stations are good for the processing days (180th- 195th days of

2009, 2010 and 2011) (Figure 3.31).

Figure 3.30 WRMS repeatabilities for North-East-Up directions from combination of TURDEP and

CORS-TR projects stations for 2009, 2010 and 2011.

0

2

4

6

8

AYD1

BALK

CESM DE

IRDE

NI

HARC

IZM

IKI

KAM

UGL

SALH

USA

KAK

HTBD

MT

BORT

CALT

ESM

TIZ

MT

KRCT

KRPT

TRBT

TRGT

Wrm

s (m

m)

Stations

N

E

U

57

Figure 3.31 WRMS repeatabilities for North (N)-East(E)-Up(U) directions from combination of IGS

for the days between 180th-195th of 2009, 2010 and 2011.

The same steps were done for stations of General Command of Mapping and

time-series were plotted (Figure 3.32 up to Figure 3.38).

0

2

4

6

8

10

12

TUBI ISTA BUCU GLSV MATE MIKL NICO PENC WTZR ZECK

Wrm

s (m

m)

Stations

N

E

U

58

Figure 3.32 The processing solutions of BAYO for 261st and 262nd days of 2000, 211st and 212nd days

of 2001, 123rd and 124th days of 2005.

59

Figure 3.33 The processing solutions of CEIL for 271st and 272nd days of 2000, 211st and 212nd days

of 2001.

60

Figure 3.34 The processing solutions of CKOY for 208th and 209th days of 2001, 212nd and 213rd days

of 2004.

61

Figure 3.35 The processing solutions of EMET for 271st and 272nd days of 2000, 123rd and 124th days

of 2005.

62

Figure 3.36 The processing solutions of LTFY for 89th day of 2000, 97th and 297th days of 2001 and

157th and 158th days of 2004.

63

Figure 3.37 The processing solutions of YENF for 258th and 259th days of 2000, 214th and 215th days

of 2001.

64

Figure 3.38 The processing solutions of ZEYT for 211st and 212nd days of 2001, 212nd and 213rddays

of 2004.

65

The wrms repeatabilities were given as graphics in Figure 3.39 and Figure 3.40.

In Figure 3.39, it can be seen that North, East and Up components of the stations are

below 10 mm except ZEYT. For ZEYT the value of Up component is near to 10 mm.

Also, the wrms repeatabilities of IGS stations seem good for the processing days

(Figure 3.40).

Figure 3.39 WRMS repeatabilities for North-East-Up directions from combination of General

Command of Mapping stations for 2000, 2001, 2004 and 2015.

Figure 3.40 WRMS repeatabilities for North-East-Up directions from combination of IGS stations for

2000, 2001, 2004 and 2015.

0

2

4

6

8

10

12

BAYO CEIL CKOY EMET LTFY YENF ZEYT

Wrm

s (m

m)

Stations

N

E

U

0

2

4

6

8

TUBI ISTA BUCU GLSV MATE MIKL NICO PENC WTZR ZECK

Wrm

s (m

m)

Stations

N

E

U

66

The velocities of the all stations with relative to Eurasia-fixed reference frame are

shown in Figure 3.41 and listed in Table 3.4 and Table 3.5. Generic Mapping Tools

(GMT) were used for presenting figures (Wessel & Smith, 1998). Table 3.4 Horizontal GPS velocities of TURDEP and CORS-TR projects stations in a Eurasian fixed

frame and 1-σ uncertainties (plotted with 95% confidence ellipses in Figure 3.41) (Here, σν E and σνN

are 1-σ uncertainties of E (east) and N (north) respectively, ρνEνN is correlation coefficient between E

(east) and N (north) uncertainties).

Site Longitude (º)

Latitude (º) νE (mm/year

)

νN (mm/year)

σνE (mm/year

)

σνN (mm/year

)

ρνEνN

STATIONS OF CORS-TR PROJECT AYD1 27.83788 37.84073 -17.40 -16.78 0.70 0.85 -0.022 BALK 27.89363 39.63937 -18.37 -6.54 0.36 0.49 -0.042 CESM 26.37257 38.30382 -16.46 -22.11 0.56 0.71 0.028 DEIR 28.64840 39.03485 -20.47 -8.07 0.40 0.54 -0.115 DENI 29.09213 37.76210 -18.03 -12.80 0.54 0.71 -0.109 HARC 29.15276 39.67774 -21.64 -2.73 0.39 0.51 -0.123 IZMI 27.08182 38.39481 -19.57 -17.17 0.53 0.68 -0.008 KIKA 27.67221 39.10599 -19.68 -11.08 0.40 0.53 -0.049 MUGL 28.36444 37.21636 -14.47 -20.01 0.59 0.76 -0.079 SALH 28.12355 38.48309 -22.22 -10.52 0.57 0.72 -0.028 USAK 29.40522 38.67921 -19.57 -8.37 0.40 0.56 -0.150

STATIONS OF TURDEP PROJECT AKHT 27.89513 38.99753 -20.02 -10.37 0.34 0.49 -0.059 BDMT 28.04087 38.12027 -18.73 -13.61 0.43 0.58 -0.061 BORT 28.55090 38.75191 -21.50 -9.38 0.39 0.53 -0.114 CALT 29.40375 37.99182 -19.07 -8.16 0.40 0.57 -0.193 ESMT 29.10617 38.42497 -18.53 -9.98 0.77 1.10 -0.240 IZMT 27.19424 38.37510 -18.30 -17.83 0.40 0.55 -0.001 KRCT 28.66741 37.82766 -21.03 -15.31 0.80 0.93 -0.064 KRPT 27.81555 37.58215 -18.11 -22.43 0.41 0.59 -0.058 TRBT 27.39112 38.31378 -19.15 -16.50 0.44 0.59 -0.024 TRGT 27.90726 38.41491 -19.84 -15.39 0.71 1.08 -0.150

IGS STATIONS TUBI 29.45068 40.78672 -2.67 -1.57 0.33 0.43 -0.190 ISTA 29.01934 41.10445 0.98 -2.17 0.29 0.38 -0.163 BUCU 26.12574 44.46394 0.75 -1.70 0.30 0.34 -0.006 GLSV 30.49673 50.36418 -0.35 -0.00 0.35 0.58 0.342 NICO 33.39644 35.14099 -2.67 3.21 0.42 0.69 -0.630 MATE 16.70446 40.64913 1.15 2.89 0.57 0.42 0.576 MIKL 31.97284 46.97278 0.93 0.08 0.42 0.47 0.227 PENC 19.28153 47.78960 0.73 -0.10 0.48 0.40 -0.474 WTZR 12.87891 49.14420 -0.26 -1.69 0.74 0.44 -0.512 ZECK 41.56506 43.78839 1.65 2.34 0.73 0.36 -0.269

67

Table 3.5 Horizontal GPS velocities of General Command of Mapping stations in a Eurasian fixed

frame and 1-σ uncertainties (plotted with 95% confidence ellipses in Figure 3.41) (Here, σν E and σνN

are 1-σ uncertainties of E (east) and N (north) respectively, ρνEνN is correlation coefficient between E

(east) and N (north) uncertainties).

Site Longitude (º)

Latitude (º)

νE (mm/yea

r)

νN (mm/year)

σνE (mm/year)

σνN (mm/yea

r)

ρνEνN

BAYO 27.30801 38.71103 -23.12 -15.53 0.65 0.74 -0.076 CEIL 26.38529 38.31084 -24.54 -27.60 4.65 5.07 -0.069

CKOY 26.23337 38.28772 -18.23 -24.92 1.06 1.18 -0.166 EMET 29.24559 39.33510 -23.30 -7.08 0.48 0.57 -0.153 LTFY 28.41285 39.99288 -19.16 -4.31 0.76 0.77 -0.074 YENF 26.79080 38.74109 -20.05 -16.85 4.53 4.18 -0.066 ZEYT 26.49654 38.20466 -19.55 -23.18 1.53 1.72 -0.116

IGS stations TUBI 29.45068 40.78672 0.33 -3.82 0.18 0.23 -0.261 ISTA 29.01934 41.10445 3.27 -3.60 0.16 0.21 -0.241

BUCU 26.12574 44.46394 -0.04 -1.11 0.15 0.17 -0.075 GLSV 30.49673 50.36418 -1.26 0.63 0.19 0.32 0.371 NICO 33.39644 35.14099 -4.70 3.56 0.26 0.42 -0.632 MATE 16.70446 40.64913 1.36 3.59 0.34 0.24 0.569 MIKL 31.97284 46.97278 -0.04 -0.80 1.61 1.98 -0.050 PENC 19.28153 47.78960 0.56 -0.06 0.29 0.24 -0.485 WTZR 12.87891 49.14420 -0.22 -0.82 0.43 0.23 -0.606 ZECK 41.56506 43.78839 0.69 2.90 0.45 0.21 -0.284

In Figure 3.41, it was seen that the velocity values were similar and

approximately 20-25 mm/yr for all stations. It was noticed that the directions of

velocities began to change from North to South. Although, the locations of TRGT

and SALH were close to each other, the velocity directions were different. Due to

this case, it may be said that these stations were located on the different mechanisms

from each other. Additionally, it was shown that the rotation of the velocity

directions to SW direction was started from the area between TRGT and SALH

stations.

68

Figure 3.41 GPS horizontal velocities and their 95% confidence ellipses in a Eurasia-fixed reference

frame for the period of 2009-2011 for TURDEP and CORS-TR stations which are shown by red

vectors and for the period of 2000-2001-2004 and 2005 for General Command of Mapping stations

which are shown by green vectors.

The obtained velocities from this study and the velocities of previous study which

were obtained by McClusky et al., (2000) and TUBITAK project No:108Y285 were

plotted together for examining the velocity changes of the study area during the years

(Figure 3.42 a). In the study of McClusky et al. (2000), GPS data were belong to the

years between 1988-1997 and in the TUBITAK project No:108Y285, GPS data were

belong to the years between 2009-2011.

Generally, it can be said that there was no big change from 1997 until 2011 on the

directions and magnitudes of the velocities (Figure 3.42 a). On the other hand,

69

according to differences on velocity directions of the stations, the study area was

separated to four regions (Figure 3.42 b).

Figure 3.42 a) GPS horizontal velocities of the study McClusky et al. (2000) for the period 1988-1997

which are shown by black vectors and GPS horizontal velocities of the TUBITAK project

No:108Y285 for the period 2009-2011 which are shown by navy vectors with 95% confidence ellipses

in a Eurasia fixed frame are added to the study area stations given in Figure 3.41.

70

Figure 3.42 b) The stations which were given at Figure 3.42.a were separated to 4 regions and shown

by purple rectangulars.

In the 1st region, the directions of velocities were approximately westward. It was

shown that the rotation of the velocity directions was started from the south border of

the 1st region. In the 2nd region, the directions of velocities were approximately

southwest. In the 3rd and 4th regions, the southern components of velocities began to

dominate. The directions of the velocities in the 3rd region which includes Izmir and

its surrounding were separated from the 2nd region with their dominant Southwestern

components. In the 4th region, the south components of velocities were more

dominant than 3rd region stations. Consequently, it can be said that the velocity

directions of the stations rotated from west to southwest direction from North to

South (Figure 3.42 b).

71

Additionally, in four points there were closer stations. For the points of AKHT

and AKGA the directions of velocities didn't change from 1997 to 2011. For DEIR

and DMIR, it was seen that the velocity direction (of DEIR) moved to SW

(clockwise direction) relative to previous velocity (DMIR). For MUGL and MULA,

the motions of the points were coherently. In these studies, there were two common

stations as CESM and BAYO. For CESM, it was seen that the points moved with the

same velocity between the years 1997 and 2011. For BAYO, the point moved at anti-

clockwise direction from 1997 to 2005 (Figure 3.42).

3.7.1 Other Relatively Solutions

Reilenger et al. (2006) developed an elastic block model in Africa-Arabia-Eurasia

continental collision zone for constraining present-day plate motions (relative Euler

vectors), regional deformation within the interplate zone, and slip rates for major

faults. The block boundaries were determined by mapped faults, seismicity, and

historic earthquakes. They separated Turkey to 3 blocks/plates as Anatolian (AN)

block, Aegean (AG) block and Southwest Anatolian (SWAN) block. They calculated

the Euler Vectors relative to Eurasia for determining the block model. Euler vectors

for Anatolian block and Aegean block (fixed reference frame) relative to Eurasia

were given at Table 3.6. In this study, Aegean and Anatolian block fixed velocity

vectors were calculated by using Euler vectors (Reilinger et al., 2006) which

represent general kinematics in relative coordinate system (Figure 3.43 and Figure

3.45).

Table 3.6 Euler Vectors Relative to Eurasia (Reilinger et al., 2006)

Block Name Latitude (°N) Longitude (°E) Rate (°/Myr)

Anatolian 30.8 32.1 1.231

Aegean 15.9 52.3 0.563

72

3.7.1.1 Anatolian Block Solutions

The Anatolian Block solutions were obtained relative to the Euler vectors for

stations of TURDEP and CORS-TR project (Figure 3.43 a). According to the

velocity directions, the stations were grouped as 3 regions and 2 lines (Figure 3.43 b).

In Figure 3.43 b, it was noticed that the velocity directions of BALK and HARC

were towards approximately northward (the opposite side relative to the other

stations). Due to this case, it can be said that BALK and HARC were located at the

northern side of the North Anatolia Region (NAR) boundary which was given at the

study of Özkaymak et al. (2013). Besides, this case was coherent with the Northern

boundary on Western Anatolia which was given by in tectonic models of McKenzie

(1978), Dewey & Şengör (1979), Sözbilir & Emre, 1996 and Çemen et al. (2006).

Additionally, the Northern detachment fault which was given at study of Ersoy et al.

(2014) (Figure 3.44) may be the reason of this separation between the BALK-HARC

and the other stations.

The NE-SW directional grabens; Gördes, Demirci and Selendi grabens, were

located between the 1st and 2nd regions. This separation was symbolized by Line B in

Figure 43.b. These grabens may be the reason of the differences on the velocity

directions between the stations of 1st and 2nd regions. Although the velocity

directions of these stations were different, the magnitudes of velocities were similar

for these stations.

3rd region stations were affected by W-E directional graben system. Although, the

velocity directions of 1st and 3rd region were similar, the velocity magnitudes of 3rd

region stations were larger than the other.

CESM and MUGL were located outside of the graben system and the velocity

directions were different from the other stations. Although the stations were located

far away from each other, surprisingly, the directions and magnitudes of velocities

were found as similar.

73

Although, SALH and TRGT were located closer to each other, the differences on

the velocity directions were obtained as quite large (Figure 3.43.b). Same result for

these two stations was pointed out at Eurasia fixed frame solution (Figure 3.41).

Figure 3.43 a) The velocity field with 95% confidence ellipses of the stations computed in Anatolian

block frame from 3-year (2009, 2010 and 2011) GPS data.

74

Figure 3.43 b) The stations are separated to 3 regions and shown by red shapes. Line A shows the

boundary of North Anatolian Region (NAR). Line B shows the separation of the group 1 and 2.

75

Figure 3.44 Geological map of Western Anatolia and its surrounding (Modified from Ersoy et al.,

2014). The pink circles represent the 3 regions which were described in the text.

3.7.1.2 Aegean Block Solutions

In Figure 3.45, it was seen that the velocities of southern stations were slower

than the northern stations. It was noticed that the velocity directions of CESM and

MUGL were different from the other stations. While BALK and HARC moved

differently from the other stations in Anatolian block solutions, in Aegean block

solutions they moved together with the other stations. Additionally, the velocity of

KRPT station was very slow relative to Anatolian block and Eurasia fixed frame

solutions.

76

Figure 3.45 The velocity field with 95% confidence ellipses of the stations computed in Aegean fixed

reference frame from 3-year (2009, 2010 and 2011) GPS data.

77

CHAPTER FOUR

ANALYZING MASS CHANGES OF WESTERN ANATOLIA BY USING

MICROGRAVITY AND GPS DATA

Microgravity is a geophysical method which defines density changes under the

surface. The method is affected directly by subsurface density distribution and

especially the existence of the cavities creating a mass loss according to surrounding

environment. This also provides a great convenience to describe the underground

structure (Butler, 1984; Ioane & Ion, 2005; Reci et al., 2011). In the study of

Ergintav et al. (2007), the change in microgravity values at the same measurement

points were examined together with vertical changing of GPS data for determining

vertical deformation in the Marmara region.

At the present day, gravity studies carry out on the subjects such as monitoring

geothermal reserves, groundwater levels, volcanic activities, determination of fault

systems and mechanic connections of these systems, monitoring horst-graben areas,

and their stress deformation (Jentzsch et al., 2001; Battaglia et al., 2003; Carbone et

al., 2003; Zeeuw-van Dalfsen et al., 2006). This type of relations shows the vertical

surface movements, besides, represents the density and mass changes in the

subsurface structures. Continuous visualization of the movements in the investigation

area is an important key point for understanding seismic risk of the region (Pamukçu

et al., 2014 in-press).

In the studies of Dewey & Şengör, (1979) and Şengör et al., (1985), Western

Anatolian Region is defined as continental extensional area which deformed under

the effect of extensional forces in N-S direction since Miocene (Figure 4.1a). Also,

Western Anatolian region moves toward the SW with a velocity of cs. 2.0 cm per

year due to the convergence of African, Eurasian and Anatolian plates bordered by

Northern Anatolian fault zone (NAFZ) (Figure 4.1a) By this idea, GPS and

microgravity network system measurements of "Multi-Disciplinary Earthquake

Researches in High Risk Regions of Turkey Representing Different Tectonic

Regimes" (TURDEP) Project, which were realized between the years 2007 and 2009

in Western Anatolia, were evaluated together. In Figure 4.1, the locations of sites are

78

given. The data of the project were provided from The Scientific and Technological

Research Council of Turkey (TUBITAK), Marmara Research Center, Earth and

Marine Science Institute.

In this study, tectonically compensation or uncompensation concept of Western

Anatolia was investigated. According previous studies about isostatic model of

Western Anatolia (Pamukcu &Yurdakul, 2008) was defined as elastic plate model. In

this model, the lithosphere is gently flexed into broad upwards and downwards in the

region of large loads. The warping induces bending stresses. These stresses will be

relieved by brittle faulting in the upper crust and by some form of ductile flow in its

lower part. In between the brittle and ductile deformation fields there is an elastic

core, which apparently is able to support the stresses induced by flexure on long

geological time-scales (Watts, 2001; Pamukcu & Yurdakul, 2008). All these

consequences are the isostatic model of the Western Anatolia region which does not

fit the local Airy model and are consistent with the finding that 6 km of the Western

Anatolian lithosphere may be more resistant to the stresses induced by long time

scaled geological flexure (Pamukcu & Yurdakul, 2008). Besides these, in the region

that corresponds to high topography and low amplitude Bouguer gravity anomaly,

there is no significant increase in the depth of crust-mantle interface (Pamukcu &

Yurdakul, 2008). This result pointed out that there are uncompensation parts in the

region. These regions are defined as a structure involved high seismic, lots of porous

and liquid (Maggi et al., 2000; Watts, 2001).

According to this knowledge, the vertical directional behavior was examined of

the study region on the scope of compensation or uncompensation mechanism by

using GPS and microgravity data. In the study, for 3 years (2007-2008-2009) data of

the continuous GPS stations (Figure 4.1.b) and microgravity, which were obtained

simultaneously in the points of GPS stations, were used. The GPS data were

processed with GAMIT/GLOBK software and the Up values of solutions were used

for comparing with the microgravity data. After performing base corrections on

microgravity data, the graphics were prepared for GPS and microgravity data. The

relations between the changes on the graphics were tested by statistical method. The

positive, negative or non-relation between two data sets were examined. At the last

79

step, the results were interpreted with the earthquake distributions occurred in the

study area.

Figure 4.1 a) General tectonic of the Turkey NAFZ: North Anatolian Fault Zone, WAEP: Western

Anatolian Extensional Zone EAFZ:Eastern Anatolian Fault Zone. b) The locations of GPS and

microgravity stations.

80

4.1 Applications

4.1.1 GPS Data Processing

GPS and microgravity measurements were obtained simultaneously at 6 sites of

the TURDEP project for 4 days. The GPS measurements at AKHT (Akhisar,

Manisa), BORT (Borlu, Manisa), ESMT (Eşme, Uşak), CALT (Çal, Denizli), BDMT

(Bademli, İzmir) and KRCT (Karacasu, Aydın) were measured 24 hours for each day

between the days 139th and 142nd (as Julian days) of 2007, 2008 and 2009. In order to

define the site coordinates and velocities 9 IGS stations of which has a good

processing and measurement history as well as which can be used to calculate the

velocity vectors were chosen to circulate the network area. For defining Eurasia fixed

reference frame; TUBI (Turkey), ZECK (Russia), NICO (Cyprus), MIKL (Ukraine),

GLSV (Ukraine), BUCU (Romania), PENC (Hungary), WTZR (Germany) and

MATE (Italy) were chosen as IGS (International GNSS Service) stations. For the

processing of GPS observations, in addition to study area stations, observations of 9

IGS stations were also included in order to make a link between the local and global

networks. The GAMIT/GLOBK software were used to process the data and also

performed in order to determine the consistency among them by examining GPS

repeatabilities (Figure 4.2). From the repeatabilities it can be seen that North, East

and Up components of the stations are below 5 mm. The GPS data were proceed by

using ITRF 2008 relative to Eurasia fixed frame. The daily solutions (time-series) of

the stations were given in (Figure 4.3, 4.4, 4.5, 4.6, 4.7 and Figure 4.8).

81

Figure 4.2 WRMS repeatabilities of North-East-Up values from combination of 2007, 2008 and 2009

GPS data.

82

Figure 4.3 The daily processing results (between the days 139th and 142nd ) of AKHT stations between

the years 2007 and 2009.

83

Figure 4.4 The daily processing results (between the days 139th and 142nd ) of BORT stations between


84

Figure 4.5 The daily processing results (between the days 139th and 142nd ) of ESMT stations between


85

Figure 4.6 The daily processing results (between the days 139th and 142nd ) of CALT stations between


86

Figure 4.7 The daily processing results (between the days 139th and 142nd ) of BDMT stations between


87

Figure 4.8 The daily processing results (between the days 139th and 142nd ) of KRCT stations between


88

In the next step GPS data were processed by using ITRF 2008 (International

Terrestrial Reference Frame) relative to Eurasia fixed frame (Figure 4.9 and Table

4.1).

Figure 4.9 GPS horizontal velocities and their 95% confidence ellipses in a Eurasia-fixed reference

frame for the period of 2007-2009.

89

Table 4.1 Horizontal GPS velocities of study area sites in a Eurasian fixed frame and 1-σ uncertainties

(plotted with 95% confidence ellipses in Figure 4.9)

Site Longitude

(º)

Latitude

(º)

νE

(mm/year)

νN

(mm/year)

σνE

(mm/year)

σνN

(mm/year) ρνEνN

AKHT 27.89513 38.99753 -21.80 -13.58 0.68 1.01 -0.139

BORT 28.55090 38.75190 -20.21 -9.51 0.77 1.08 -0.195

ESMT 29.10617 38.42497 -18.53 -9.98 0.77 1.10 -0.240

CALT 29.40375 37.99182 -18.06 -9.05 0.82 1.17 -0.264

BDMT 28.04087 38.12027 -18.72 -14.48 0.87 1.21 -0.130

KRCT 28.66741 37.82766 -19.28 -16.46 0.83 1.20 -0.200

σνE and σνN are 1-σ uncertainties of E (east) and N (north) respectively.

ρνEνN is correlation coefficient between E (east) and N (north) uncertainties.

4.1.2 Comparison of GPS and Microgravity Results

The gravity changes of the stations between the years of 2007 and 2009 were

given in Figure 4.10 a), 4.11 a), 4.12 a), 4.13 a), 4.14 a) and in Figure 4.15 a).

The Height (Up) values of the GPS daily solutions (at the 3rd graphics of Figure

4.3, 4.4, 4.5, 4.6, 4.7 and 4.8), which present vertical displacements were used for

calculating the displacement changes on the vertical directions from the years of

2007 to 2009. These displacement changes were given in Figure 4.10 b), 4.11 b),

4.12 b), 4.13 b), 4.14 b) and in Figure 4.15 b).

90

Figure 4.10 a) Gravity changes of AKHT stations between the years 2007-2009 b) Displacement

changes on vertical direction of AKHT stations between the years 2007-2009

Figure 4.11 a) Gravity changes of BDMT stations between the years 2007-2009 b) Displacement

changes on vertical direction of BDMT stations between the years 2007-2009

91

Figure 4.12 a) Gravity changes of KRCT stations between the years 2007-2009 b) Displacement

changes on vertical direction of KRCT stations between the years 2007-2009

Figure 4.13 a) Gravity changes of BORT stations between the years 2007-2009 b) Displacement

changes on vertical direction of BORT stations between the years 2007-2009

92

Figure 4.14 a) Gravity changes of CALT stations between the years 2007-2009 b) Displacement

changes on vertical direction of CALT stations between the years 2007-2009

Figure 4.15 a) Gravity changes of ESMT stations between the years 2007-2009 b) Displacement

changes on vertical direction of ESMT stations between the years 2007-2009

93

In this step, GPS and gravity measurement results according to time (their

increase/decrease relations) are valuable data for explaining deformation of station

region. In this study, after preliminary analyses, statistical relations were investigated

by correlation analyses. As it is known, correlation coefficients ( 11 ≤≤− r ) having

positive values show positive relation between two variables and negative values

show the opposite. Formula of the correlation coefficient was given in Equation 4.1.

Correlation coefficients calculated from GPS and gravity measurement results were

given in Table 4.2.

∑ ∑

∑

∑∑∑

−

−

−

−

==−−

−−

2222

YYXX

YYXX

yx

yxr

ii

ii

ii

ii (4.1)

Table 4.2 Correlation coefficients of GPS and gravity observation results.

Station Id r

AKHT -0.346885691

BDMT 0.246857117

KRCT -0.096857941

BORT 0.918876629

CALT 0.83879388

ESMT 0.525559851

For discussing the stations, it is needed earthquakes and topography map of the

study area. For this purpose, the earthquakes occurred between the latitude 36.40º

and 39.50º, longitude 26.20º and 30.00º; between the years 2005 and 2014, with the

amplitude range between 2.5 and 9.0, were taken from Boğaziçi University Koeri

National Earthquake Monitoring Center (Figure 4.16). Additionally, topographic

map of the study area was drawn by using the topographic data TOPEX (Figure

94

4.17.a). For discussing the earthquakes and topographic changes on the station point,

the cross-sections were taken which was shown in Figure 4.17.b.

Figure 4.16 The Earthquakes distributions which occurred between the years 2005-2014.

95

Figure 4.17 a) Topographic map of study area b) The blue lines show the cross-sections

The earthquakes distributions near to all stations and topographic changes along

to the cross sections (Figure 4.17 b) were shown in Figure 4.18, 4.19, 4.20, 4.21, 4.22

and Figure 4.23.

96

Figure 4.18 a) The topographic changes along to cross-section A-A' b) Earthquake distributions along

to S-N direction near to AKHT station. Small Red square shows the location of the station.

Figure 4.19 a) The topographic changes along to cross-section B-B' b) Earthquake distributions along

to S-N direction near to BDMT station. Small Red square shows the location of the station.

97

Figure 4.20 a) The topographic changes along to cross-section C-C' b) Earthquake distributions along

to S-N direction near to KRCT station. Small Red square shows the location of the station.

Figure 4.21 a) The topographic changes along to cross-section D-D' b) Earthquake distributions along

to S-N direction near to BORT station. Small Red square shows the location of the station.

98

Figure 4.22 a) The topographic changes along to cross-section E-E' b) Earthquake distributions along

to S-N direction near to CALT station. Small Red square shows the location of the station.

Figure 4.23 a) The topographic changes along to cross-section F-F' b) Earthquake distributions along

to S-N direction near to ESMT station. Small Red square shows the location of the station.

99

For understanding the vertical directional behavior of the region and the active

tectonic structures in the Western Anatolia extensional system, the vertical (Up)

solutions of GPS data and microgravity data were compared together. Results related

to vertical displacement belonging to time dependent microgravity and GPS data

between 2007 and 2009 years were presented in between Figure 4.10 and Figure

4.15.

If the correlation coefficient value is negative and near to -1, it can be said that the

region is in compensation balance and there is not any structural problem on crust. In

a balanced region while movement is in negative direction (-) according to isostasy,

gravity value should be positive. According to Table 4.2 which gave the correlation

coefficient between GPS and microgravity data, some opinions were expressed about

the measurement stations.

AKHT (Akhisar/Manisa) :

AKHT station which is located northern side of Gediz graben (Figure 4.17 a). It

has approximately 780 m height (Figure 4.18 a).

The correlation coefficient (r) of the station is negative but below −0.5

(r=−0.346885691) (Table 4.2). This result shows that in the station there is not an

expected relation (r = -1 or near to -1) between the GPS and microgravity data. It is

noticed that while the amplitude of the gravity, which are related with the deep

subsurface structures, are increasing year by year (Figure 4.10 a), the vertical

displacement is decreasing and then increasing (Figure 4.10 b)

In Figure 4.18b), it is seen that the earthquakes occurred up to 20 km depth. The

high seismicity may be the reason of lack of expected relation between GPS and

gravity data.

Additionally, it can be said that the seismic activity of the region may be the

source which causes irrelevant on equilibration mechanism of surface and subsurface

structures.

100

BDMT (Bademli, Ödemiş/İzmir):

BDMT station is located southern side of Küçük Menderes graben (Figure 4.17 a)

It has approximately 400 m. height and it is located on a flat area between two uplift

structures (Figure 4.19 a).

The correlation coefficient (r) of the station is positive but below +0.5 (r = 0.2)

(Table 4.2). If the value is below 0.5, it means that there is not an expected relation

(r=-1 or near to -1) between the GPS and microgravity data in this station.

In Figure 4.19b) it is noticed that the station point doesn't show seismic activity. It

can be said that existing of the Ödemiş geothermal source causes the non-seismicity.

Therefore, the lack of linear relation between the data sets may be explained by

existing of the geothermal sources.

The low density values of the geothermal sources decrease the amplitude of the

gravity. In Figure 4.11a), it is seen that the amplitude of gravity was decreasing year

by year. Therefore, the decreasing of gravity amplitude supports this information.

In Figure 4.11b), it is noticed that the vertical movement is increasing and then

decreasing. According to the uplift and collapse in vertical movement, it can be

suggested that the geothermal sources cause the irrelevant on equilibration

mechanism of surface and subsurface structures.

It can be said that there is a crustal problem on the station point because of the

uncompensation of surface and subsurface loadings.

KRCT (Karacasu/Aydın):

KRCT station is located southern side of Büyük Menderes graben (Figure 4.17 a)

and it is seen at cross-section in Figure 4.20.a it is located on the descending area.

Besides, it has approximately 700 m. height.

The correlation coefficient (r) of the station is negative but below −0.5 (r = −0.09)

(Table 4.2). This result shows that in the station there is not an expected relation (r =

-1 or near to -1) between the GPS and microgravity data.

101

In Figure 4.20 b), it is noticed that while the northern side of the KRCT station

has high seismic activity, the southern side has low seismic activity relative to the

northern side. It can be said that this station is located on a boundary.

BORT (Borlu/Manisa):

BORT station is located northern side of Gediz graben (Figure 4.17 a) and it is

seen at cross-section in Figure 4.21a) it is located on the rising area. Besides, It has

approximately 600 m. height.

The correlation coefficient (r) of the station is positive (r = 0.9) (Table 4.2) and

there is a positive relation between GPS and gravity data. The station presents

increased and decreased gravity value in response to increased and decreased vertical

changes (Figure 4.13 a). It means that the surface loadings and subsurface loadings

move at the same direction. Therefore, it can be said that the station has not any

isostatic balance. This may be possibly considered as uncompensation in load

distribution arising from mass loss occurring subsurface due to the effects of

geothermal environment, subsurface water, or seismic activity (Pamukcu et al.,

2014).

BORT station is near to Köprübaşı-Saraycık geothermal system. (Mineral

Research & Exploration General Directorate [MTA], 2005). At this region, the hot

water goes up to the surface by itself. This system is related with a young basin,

which is arised by NNS-SSW directional oblique fault at Quaternary. The basin

occurred at uplifting area between two important grabens at Northern and Southern

sides and completed formation at the end of the Miosen. This basin is the youngest

geothermal system in Western Anatolia (MTA, 2005).

In Figure 4.21b), it is seen that there is not high seismic activity in BDMT station

point. The existing of geothermal activity is coherent with the non-seismicity in the

region.

102

CALT (Çal/Denizli):

CALT station is located at eastern side of the graben system with approximately

800 m height (Figure 4.17 a).


there is a positive relation between GPS and gravity data. The station presents

decreased gravity value in response to decreased vertical changes (Figure 4.14 a-b).

It means that the surface loadings and subsurface loadings move at the same

direction. It can be said that in CALT station point there is not any isostatic balance.

Additionally, due to the decreasing the amplitude of gravity, it can be said that there

is a crustal problem at this station region.

The Karaahayıt geothermal region is approximately 30 km far away as the crow

flies from CALT station. In this geothermal region, lots of hot water sources go up to

surface and the bed rock is quartzite and marble (Şimşek & Eşder, 1981; MTA,

2005).

In Figure 4.22b) it is noticed that while the southern side of the CALT station has

high seismic activity, the northern side has low seismic activity relative to the other

side. It can be said that this station is located on a boundary. The fault system has

non-stabile structures which causes high deformation.

ESMT (Eşme/Uşak):

ESMT station is located at eastern side of the graben system with approximately

780 m height (Figure 4.17 a).


there is a positive relation between GPS and gravity data.

In Figure 4.15a) it is noticed that the amplitude of gravity was decreasing year by

year. It can be said that there is a crustal problem on the station point because of the

uncompensation of surface and subsurface loadings (Pamukçu & Yurdakul, 2008;

Çifçi et al., 2011 and Pamukçu et al., 2014).

103

The ESMT station is near to the Örencik geothermal region. Hot waters go up to

surface through the N-S and E-W directional faults. The reverse volcanic activities

continued up to Quaternary in the region (Iça, 1978; MTA, 2005).

In Figure 4.23b), it is noticed that the seismic activity is low at the station point.

This case can be related with the existing of Örencik geothermal source.

104

CHAPTER FIVE

COULOMB STRESS CHANGES CALCULATIONS

Coulomb 3.3 software (Toda et. al, 2005; Lin & Stein, 2004) is used for

calculating static displacements (at GPS stations), strains, and stresses at any depth

caused by fault slip In this software, the calculations are performed in an elastic half

space with uniform isotropic elastic properties which explained by Okada (1992).

The Coulomb stress change which is on a specified fault depends on the fault

geometry and sense of slip, and the coefficient of friction but it is independent of

regional stress (King et al., 1994). In this study this method was used to resolve

stress changes on Northern and Southern Normal faults of Gediz Graben.

In the Coulomb criterion, when the Coulomb stress σ f exceeds a specific value,

failure consists on a plane is given as;

σ f = τβ - µ (σβ - p) (5.1)

where τβ is the shear stress on the failure plane, σβ is the normal stress, p is the pore

fluid pressure and µ is the coefficient of friction. The value of τβ must be positive in

this statement. The stress on fault plane get negative or positive value depends on

whether the slip of fault is right or left lateral. Therefore, the sign of τβ must be

chosen properly (King et al., 1994).

If the failure plane is directed at β to the σ1 axis (Figure 5.1), the stress

components can be described in the terms of principal stresses,

𝜎𝛽 = 12

(𝜎1 + 𝜎3) − 12

(𝜎1 − 𝜎3) cos 2𝛽 (5.2)

𝜏𝛽 = 12

(𝜎1 − 𝜎3) sin 2𝛽 (5.3) where σ1 is the biggest, σ3 is the smallest principal stress. In this way, Equation 5.1

becomes;

105

𝜎𝑓 = 12

(𝜎1 − 𝜎3)(𝑠𝑖𝑛2𝛽 − 𝜇𝑐𝑜𝑠2𝛽) − 12𝜇(𝜎1 + 𝜎3) + 𝜇𝑝 (5.4)

Figure 5.1 The axis system used for Coulomb stresses calculations of on optimum failure planes.

Compression and right-lateral shear stress on the failure plane are taken as positive. The sign of 𝜏𝛽 is

negative for calculations of right-lateral Coulomb failure on specified failure planes. (King et. al, 1994)

Pore fluid pressure affects the normal stress across the fault plan, as given in

equation (1). If the rock stress is changed faster than fluid pressure, p can be related

to stress in the rock by a coefficient which calls Skempton’s pore pressure parameter,

B. The value of B varies between 0 and 1. Therefore, Equation 5.1 can be simplified

by taking account assumptions for pore fluid pressure and Equation 5.1 becomes;

𝜎𝑓 = 𝜏𝛽 − 𝜇′𝜎𝛽 (5.5)

where the coefficient of friction is described by µ' = µ (1-B) (King et al.,1994).

If the x and y axes and fault displacements are at horizontal direction, and fault

planes are at vertical direction (along z direction), stress on a plane at an angle

ψ from the x-axis (as shown in Figure 5.1) is given as (King et al.,1994),

𝜎11 = 𝜎𝑥𝑥𝑐𝑜𝑠2𝜓 + 2𝜎𝑥𝑦𝑠𝑖𝑛𝜓𝑐𝑜𝑠𝜓 + 𝜎𝑦𝑦𝑠𝑖𝑛2𝜓

106

𝜎33 = 𝜎𝑥𝑥𝑠𝑖𝑛2𝜓 + 2𝜎𝑥𝑦𝑠𝑖𝑛𝜓𝑐𝑜𝑠𝜓 + 𝜎𝑦𝑦𝑐𝑜𝑠2𝜓

𝜏13 = 12

�𝜎𝑦𝑦 − 𝜎𝑥𝑥�𝑠𝑖𝑛2𝜓 + 𝜏𝑥𝑦𝑐𝑜𝑠2𝜓 (5.6)

5.1 Applications

Coulomb 3.3 graphic-rich stress change software (Toda et. al, 2005; Lin & Stein,

2004) was used for GPS velocity modeling and resolving stress changes on the faults

which have enough GPS stations at their northern and southern sides (Figure 3.7).

Therefore, according to locations of the GPS stations, Northern normal fault of Gediz

Graben and Southern normal fault of Büyük Menderes Graben were modeled.

The GPS data were processed with GAMIT/GLOBK (Herring et al., 2010a,

Herring et al., 2010b) software. In GPS processing, the solutions were done relative

to the stations which were located on opposite sides of the fault. It means that when

calculating the velocity of the stations which were located at one side, the opposite

side stations were assumed like as stabile (not moving). Therefore, the effect of the

fault on the GPS stations can be interpreted.

In the second step, by using the fault parameters (rake angle, dip angle, frictional

coefficient) (Figure 5.2) (Bozkurt & Sözbilir (2004) for Gediz Graben and Sümer et

al. (2013) for Büyük Menderes Graben), and elastic parameters (Poisson's ratio,

Young Modulus, Byeerlee's law friction), Coulomb 3.3 software modeled GPS

velocity vectors. By taking into account the GPS velocities which are obtained by

GAMIT/ GLOBK software, two types of GPS velocities (modeled and obtained)

were compared and tried to do best fitting between them.

In the third step; the coulomb stress changes were calculated by using the best

fitting fault parameters, which were determined from the observed and modeled GPS

vectors. Finally as the last step, the coulomb stress changes were compared with the

occurred earthquakes between the years 1970 and 2014.

107

Figure 5.2 The parameters of fault geometry (Aki & Richards, 1980).

5.1.1 Northern Normal Fault of Gediz Graben

For GAMIT/GLOBK processing, the stations; AKHT (Akhisar, Manisa), BORT

(Borlu, Manisa), ESMT (Eşme, Usak) and CALT (Çal, Denizli) which were located

at north side and TRGT (Turgutlu, Manisa) and SALH (Salihli, Manisa) were located

at south side of Northern Normal fault of Gediz Graben were chosen. In Figure 3.7, it

was noticed that BAYO was located near to the fault but its observation days were

not same with the other stations. Therefore, BAYO couldn’t be taken into processing

with the other stations.

The GPS velocities of northern side stations (AKHT, BORT, ESMT, CALT) were

calculated relative to Southern stations (by assuming the movements of southern

stations are zero) and GPS velocities of southern side stations (TRGT and SALH)

were calculated relative to Northern stations (by assuming the movements of

Northern stations are zero) for the days between 180th and 195th, the years of 2009,

2010 and 2011 (Figure 5.3).

As the second step, in Coulomb 3.3 software, Poisson ratio; 0.25, Young

Modulus; 8·105 bars, and friction coefficient; 0.4 were chosen as elastic parameters.

For the fault parameters, dip angle; 60°, rake; -70° and strike; 117° were given the

best fitting between the observed by GAMIT/GLOBK and modeled by Coulomb 3.3

(Figure 5.4) GPS velocities. Additionally, the bottom depth of the fault was given 4

km by taking the study result of Çiftçi & Bozkurt (2010).

108

In Figure 5.3, it was noticed that the movements of TRGT and SALH were

different from each other and besides, the movements of ESMT and CALT were

different from BORT as in the Chapter three in Eurasia, Anatolia and Aegean block

fixed results (Figure 3.43 and Figure 3.45).

Figure 5.3 GPS velocities of North stations (AKHT, BORT, ESMT and CALT) and South stations

(TRGT and SALH ) relative to each other.

109

Figure 5.4 Blue vectors represent the obtained GPS velocities by Gamit/Globk and red vectors

represent modeled GPS velocities by Coluomb 3.3

In Figure 5.4, it was seen that, the modeled and observed GPS velocities were

fitted at AKHT, BORT and TRGT. But there was not compliance between the

velocities for SALH. Additionally, Coulomb software can not model velocities for

ESMT and CALT stations due to their far away locations from the fault.

According to observed and modeled GPS velocities (Figure 5.3 and Figure 5.4), it

can be said that BORT and TRGT stations were coherent with the N-S directional

extension system. However, SALH was not moving properly with this system. It was

thought that this case was occurred since its location was near to Northern normal

fault as well as Southern normal fault of Gediz Graben. Therefore, it can be said that

SALH was affected by both faults (Figure 5.3 and Figure 5.4).

In the next step, by using the best fitting parameters (Figure 5.5), which obtained

from the observed and modeled GPS vectors, the coulomb stress changes were

110

calculated and plotted for the depths of 4 km and 6 km and additionally for the depth

range between 0-4 km and 0-6 km (Figure 5.6, 5.7, 5.8 and Figure 5.9).

Figure 5.5 The view of ‘stress control panel’ of Coulomb 3.3 software for calculating Coulomb Stress

Changes for the northern normal fault of Gediz Graben at 6 km depth.

111

(a)

(b)

Figure 5.6 a) Coulomb stress changes between the depths of 0-4 km. b) Earthquake focus distributions

on the study area. USGS earthquake archive was used between the years 1970-2014.

112

(a)

(b)

Figure 5.7 a). Coulomb stress changes at depth 4 km. b) Earthquake focus distributions on the study

area. USGS earthquake archive was used between the years 1970-2014.

113

(a)

(b)

Figure 5.8 a) Coulomb stress changes between the depths of 0-6 km. b) Earthquake focus distributions

on the study area. USGS earthquake archive was used between the years 1970-2014.

114

(a)

(b)

Figure 5.9 a) Coulomb stress changes at depth 6 km. b) Earthquake focus distributions on the study


115

It was noticed that for the all different depth figures (Figure 5.6 a), 5.7 a), 5.8 a)

and Figure 5.9 a)) the coulomb stress change values were similar on the stations

points. Additionally, the SALH was located on the main stress region caused by the

fault because its location was very near to the fault. Besides, this case can be the

reason of the inability of the previous step for SALH. As the result of the seismic

activity, the non-stabile duration of subsurface structures which were in the stress

region can contain air, water, etc. Therefore, it can be seen some problems on

modeling of the non-stabile region like as SALH.

For investigating the stress source depth, the coulomb stress changes were

calculated for the depths of 4 km and 6 km (Yurdakul, 2007; Pamukçu & Yurdakul,

2008) and additionally for the depth range between 0-4 km and 0-6 km (Figure 5.6 a,

5.7 a, 5.8 a and Figure 5.9 a). It is determined that the depth of fault (4 km), which

was given at previous Coulomb GPS velocity modeling step, is the initial depth of

the stress (Figure 5.6 a and Figure 5.7 a) and it is seen that the stress still continue at

6 km depth (Figure 5.8 a and Figure 5.9 a). Consequently, it can be said that the

stress area has regional effects for the depth range between 0-4 km. At deeper depth

than 4 km, the stress area (deformed area) had total regional effects.

As the last step, the coulomb stress change values were compared with the

earthquake focus distributions which were obtained from USGS (United States

Geological Survey) between the years 1970-2014. For this study the earthquakes

which occurred up to 7km depth were drawn since the bottom depth of the fault was

chosen as 4 km (Figure 5.6 b, 5.7 b, 5.8 b and Figure 5.9 b). It was noticed that the

earthquakes which occurred near the modeled fault are seen on high stress region

(red colored areas) and at the NW side of the modeled fault (Figure 5.6 b, 5.7 b, 5.8 b

and Figure 5.9 b). The earthquakes were coherent with the high stress region at the

west and east boundaries of the fault. But there was an incompatible case at NW of

the fault. In the study, this NW side of the fault could not be modeled. AKHT station

was located north side of the fault, but also it was needed southern stations for

relatively calculations. Unfortunately, the GPS observation days of BAYO, YUNT

stations (Figure 3.7) were less as well as not the same days with the other stations to

process together. Therefore, the fault was modeled as the limits of the locations of

116

GPS stations. For better solutions, it is needed to build more GPS stations for

investigating the effects of the faults.

Finally, Coulomb 3.3 software calculated the earthquake magnitude by using the

input fault parameters as M=4.0. The earthquakes occurred with magnitude 4

intensively, between the years 1970-2014 at the study area. These two values are

coherent with each other.

5.1.2 Southern Normal Fault of Büyük Menderes Graben

The stations; BDMT (Bademli, Manisa), AYD1 (Aydın, Merkez), CALT (Çal,

Manisa) which were located at north side and KRPT (Karpuzlu, Aydın), KRCT

(Karacasu, Aydın) and DENI (Denizli, Merkez) which were located at south side of

Southern Normal fault of Büyük Menderes Graben were chosen and were processed

by using GAMIT/GLOBK. The GPS velocities of northern side stations (BDMT,

AYD1, CALT) were calculated respect to Southern stations (by assuming the

movements of southern stations are zero) and GPS velocities of southern side

stations (KRPT, KRCT, DENI) were calculated respect to Northern stations (by

assuming the movements of Northern stations are zero) for the days between 180th

and 195th, the years of 2009, 2010 and 2011 (Figure 5.10).

In Coulomb 3.3, for elastic parameters; Poisson ratio; 0.25, Young Modulus;

8⋅105 bars, friction coefficient; 0.4 were chosen as elastic parameters. In this part, the

fault was designed as two faults. For the 1st fault parameters; rake; -95º and dip

angle; 70º and for 2nd fault, rake; -75º and dip angle; 77º were given the best fitting

between the observed and modeled (Figure 5.11) GPS velocities. Additionally, the

bottom depths of the fault were chosen as 5 km for the 1st fault and 3 km for the 2nd

fault (Çiftçi et al., 2011).

In the Coulomb 3.3 software GPS velocity modeling step, DENI and AYD1

stations were moved from the calculations. Since according to GAMIT/GLOBK

processing results, DENI has no velocity and the velocity of AYD1 is in the error

ellipses (Figure 5.10).

117

Figure 5.10 GPS velocities of North stations (AYD1, BDMT and CALT) and South stations (KRPT,

KRCT and DENI ) relative to each other.

Figure 5.11 Blue vectors represent the obtained GPS velocities by GAMIT/GLOBK and red vectors

represent modeled GPS velocities by Coluomb 3.3. No: 1 represents 1st fault and No: 2 represents 2nd

fault.

118

In Figure 5.10, it can be said that KRPT and CALT were moving coherently with

the main N-S extensional features of the Western Anatolia. Also, as well as the

magnitude of velocities of BDMT and KRCT were small, they were moving

coherently with the N-S extensions. AYD1 was moving differently from the other

stations but at the same time the velocity magnitude was in the error ellipse. The

location of the station where was very near to the fault may be the reason of this

problem. From the relatively solutions DENI was found as stabile respect to opposite

side stations (Figure 5.10).

In Figure 5.11, it was seen that, the modeled and observed GPS velocities were

fitted for KRPT and KRCT. The coherence between the modeled and observed

velocities for CALT was not well. Additionally, the modeled and observed velocities

of BDMT had same directions and they were fitted but the magnitude of the modeled

velocity was higher than the observed one (Figure 5.11).

As the next step, for calculating the coulomb stress changes, the software got the

mean values of dip and rake angles of two fault automatically (Figure 5.12) By these

parameters the coulomb stress changes were calculated and plotted for the depths of

3 km and 5 km and additionally for the depth range between 0-3 km and 0-5 km

(Figure 5.13, 5.14, 5.15 and Figure 5.16).

Figure 5.12 The view of ‘stress control panel’ of Coulomb 3.3 for calculating Coulomb stress changes

for the Southern normal fault of Büyük Menderes Graben at 3 km depth.

119

(a)

(b)

Figure 5.13 a) Coulomb stress changes between the depths of 0-3 km. b) Earthquake focus

distributions on the study area. USGS earthquake archive was used between the years 1970-2014.

120

(a)

(b)

Figure 5.14 a) Coulomb stress changes at 3 km depth. b) Earthquake focus distributions on the study


121

(a)

(b)

Figure 5.15 a) Coulomb stress changes between the depths of 0-5 km. b) Earthquake focus

distributions on the study area. USGS earthquake archive was used between the years 1970-2014.

122

(a)

(b)

Figure 5.16 a). Coulomb stress changes at 5 km depth. b) Earthquake focus distributions on the study


123

For investigating the stress source depth, the coulomb stress changes were

calculated for the depths of 3 km and 5 km and additionally for the depth range

between 0-3 km and 0-5 km (Figure 5.13 a, 5.14 a, 5.15 a and Figure 5.16 a).

Figure 5.13.a showed the coulomb stress changes at the depth range between 0-3

km and it was seen that KRCT, KRPT and CALT stations were in the high stress

region. However, in Figure 5.14.a which showed the coulomb stress changes at 3 km

depth, KRCT and KRPT were in low stress region. Therefore, it can be said that

surface and shallow structures up to 3 km effect KRCT and KRPT stations. Similar

opinions can be said for Figure 5.15.a which showed the coulomb stress changes at

depth range between 0-5 km and Figure 5.16.a which was drawn for 5 km for KRCT

and KRPT stations. BDMT station was located at low stress region at all depths and

Coulomb GPS vector modeling showed good fitting for this station. Contrarily, the

GPS vector modeling was not good and additionally, CALT was located at high

stress region at all depths. Consequently, it can be said that Büyük Menderes graben

was affected by stress area up to 3 km. At the depth deeper than 3 km, the stress area

(deformed area) had total regional effects.

As the last step, the coulomb stress change values compared with the earthquake

focus distributions which were obtained from USGS (United States Geological

Survey) between the years 1970-2014. For this study the earthquakes which occurred

up to 7 km depth were drawn since the bottom depth of the fault was chosen as 5 km

for the 1st fault and 3 km for the 2nd fault. The occurred earthquakes were coherent

with the coulomb stress change regions (Figure 5.13 b, 5.14 b, 5.15 b and Figure 5.16

b).

The normal faults of Küçük Menderes Graben and northern normal fault of Büyük

Menderes Graben can not be modeled due to the less station around these faults.

Additionally, the southern normal fault of Gediz Graben couldn't be modeled since

there is not enough GPS station surrounds the fault. As seen in Figure 3.7, there are

TRGT, SALH stations but they are located on the fault plane. If it is noticed that

there is only CALI station at the southern side but unfortunately the GPS data are not

enough for processing. Therefore because of the lack of GPS stations, the northern

normal fault of Gediz Graben cannot be modeled.

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5.1.3 The Relative Calculations on Study Area

For investigating the relative movements of the stations for different directions

some processing were done (Figure 5.17, 5.18, 5.19 and Figure 5.20).

Firstly, KIKA, AKHT and TRGT were chosen left side stations and DEIR,

BORT, USAK and ESMT were chosen as right side stations. Their movements were

processed relatively each other like described at previous part.

In Figure 5.17, it was noticed that the velocity directions of DEIR and BORT

were different from ESMT and USAK. Because of this inconsistency DEIR and

BORT were moved from the processing stations and the stations were processed

again (Figure 5.18). It was seen that after moving DEIR and BORT, the same group

stations ESMT and USAK did not effected but in other group stations KIKA, AKHT

and TRGT were affected. In the next step, DEIR and BORT were added to left

station group. In Figure 5.19, it was noticed that the velocity directions of DEIR and

BORT were different from the same group stations. Consequently, it can be said that

DEIR and BORT were located in a different structures from the surrounding stations.

125

Figure 5.17 GPS velocities of left side stations (KIKA, AKHT and TRGT shown by black vectors)

and right side stations (DEIR, BORT, USAK and ESMT shown by red vectors) relative to each other.

Figure 5.18 GPS velocities of left side stations (KIKA, AKHT and TRGT shown by black vectors)

and right side stations (USAK and ESMT shown by red vectors) relative to each other.

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Figure 5.19 GPS velocities of left side stations (KIKA, AKHT, TRGT, DEIR and BORT shown by

black vectors) and right side stations (USAK and ESMT shown by red vectors) relative to each other.

In the next step, same application was done for the stations near to Büyük

Menderes Graben. Because at the previous processing of the stations near to Büyük

Menderes Graben, the velocity of AYD1 was calculated differently from the other

stations and DENI was found as approximately stabile (Figure 5.20). It was noticed

that BDMT, AYD1 and KRPT were moving to South, on the other hand, KRCT,

DENI and CALT were moving to North.

Consequently, for the relative applications of the stations near to Gediz Graben

and Büyük Menderes Grabens, it can be pointed out that there may be a zone at N-S

direction between the left and right stations. For relative solution results Gediz

Graben were consistent with the North part of IBTZ (Izmir- Balıkesir Tranfer Zone)

which was studied by Ersoy et al. (2014).

127

Figure 5.20 GPS velocities of left side stations (BDMT, AYD1 and KRPT shown by black vectors)

and right side stations (CALT, KRCT and DENI shown by red vectors) relative to each other.

128

CHAPTER SIX

NUMERICAL MODELING

Numerical modeling with finite element analysis is a computational tool that can

be used for calculating forces, deformations, stresses and strains throughout a bonded

structure. These predictions can be made at any point in the structure including

within the adhesive layer. Furthermore, the element mesh can accurately describe the

geometry of the bond line so the influence of geometrical features, such as the shape

of model and boundaries. Simulate the deformation of a continuous medium involves

performing set of equations that are not usually resolving directly. The spatial

discretization of the medium finite element associated with the time discretization is

used to give a digital nature to equations.

In this study, western Anatolia was modeled to investigating the deformation

during the geological scales. In this scope, the finite element modeling software,

namely, ADELI (Chery & Hassani, 2002) which was developed by using theoretical

equations given in Zienkiewicz (1977), Owen & Hinton (1980), Dhatt & Thouzot

(1981), Salençon (1995) was used for modeling the deformation. Additionally, the

details of the equations and the algorithm used in ADELI were given in Hassani

(1994) and Huc (1997).

6.1 Physical Problem (continuum) and Equilibrium Equations

Modeling of deformation on the lithosphere as a continuous medium is mainly

based on the equilibrium equations of the environment, the laws of behavior of this

medium, the boundary conditions of the environment as well as some initial

conditions.

The medium is considered as continuous which allows using the concepts of the

mechanical continuum to calculate the equilibrium of the system. Discontinuities

corresponding the faults modeled this behavior by law Coulomb friction-type are

treated as a boundary condition of a particular type. The equilibrium equations of the

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medium are defined on the current configuration Ct. If the medium continuously

occupied at time t Ct configuration, and if every point M belonging to Ct (is subject

volume) to the external forces 𝑓(M) and surface 𝐹(M), the resultant force is written

as (Salençon, 1995):

∫ 𝑓(𝑀) 𝑑Ω + ∫ 𝐹(𝑀)∂𝐶𝑡𝐶𝑡𝑑Γ = ∫ ρ(𝑀)𝐶𝑡

γ(𝑀)𝑑Ω (6.1)

and the resultant moment is:

∫ 𝑂𝑀 ∧ 𝑓(𝑀)𝑑Ω + ∫ 𝑂𝑀 ∂𝐶𝑡𝐶𝑡 ∧ 𝐹(𝑀)𝑑Γ = ∫ 𝑂𝑀 ∧ρ(𝑀)𝐶𝑡

γ(𝑀)𝑑Ω (6.2)

with ρ (m) density at point M and γ (m) acceleration at the same point.

For all volumes D included in Ct, if we assume that the efforts (stress, strain) of

the rest surface of the medium and are dependent on the normal n to the ∂D surface

Equation 6.1 becomes:

∀D ⊂ Ct ∫ 𝑓(𝑀) 𝑑Ω + ∫ T∂𝐷𝐷 �𝑀, n�𝑑Γ = ∫ ρ(𝑀)𝐷 γ(𝑀)𝑑Ω

(6.3)

For fixed M, T(𝑀,𝑛�) is a linear transformation function. T �𝑀, n � is contracted

product between the stress tensor Cauchy 𝜎� (M) and the normal 𝑛�:

T �𝑀, n � = 𝜎� (M) ⋅ n (6.4)

In Equation 6.2 if the stress tensor Cauchy 𝜎� (M) is symmetrical, Equation 6.4

becomes:

∀D ⊂ Ct ∫ �ργ − 𝑓� 𝑑Ω − ∫ σ �∂𝐷𝐷 n𝑑Γ = 0 (6.5)

130

Using the divergence, Equation 6.5 becomes:

∀D ⊂ Ct ∫ �ργ − 𝑓 − 𝑑𝑖𝑣(𝜎�)�𝐷 𝑑Ω = 0 (6.6)

As this relationship with the regardless of the volume D, the term goes to zero

under the integral (provided it is continuous) (Curnier, 1993). Therefore, we have:

in Ct ργ = 𝑓 + 𝑑𝑖𝑣(𝜎�) (6.7)

Here, ργ, 𝑓 and 𝑑𝑖𝑣(𝜎�) represent the acceleration forces, the external forces (volume

and surface) and the internal forces (stresses) respectively.

The stresses 𝑓 in the Equation 6.7:

-forces of volume: the density of force per unit volume is given by the field vectors:

𝑓𝑣 on Ct

The boundary conditions of the problem are:

-if kinematic: 𝑣 = 𝑣𝑑 on 𝜕𝐶𝑡𝑉 (limited velocity )

-if static : 𝜎� n = 𝑓𝑠 on 𝜕𝐶𝑡𝑃 (limited pressure)

-if the more specific terms as the contact between two bodies:

𝑓𝑐 on 𝜕𝐶𝑡𝐶 (mixed constraints limited on contact)

The overall outline of the medium is:

𝜕𝐶𝑡 = 𝜕𝐶𝑡𝑉 ∪ 𝜕𝐶𝑡𝑃 ∪ 𝜕𝐶𝑡𝐶 (6.8)

6.2 Constitutive laws

The constitutive equations are used to connect the stresses and strains of a given

medium. For describing the lithospheric rheology, while elastoplastic material is

131

used at low pressure and low temperature, viscoelastic material is used at high

pressure and high temperature. One of the differences between two types of material

is the time-related behavior. While viscoelasticity is time-dependent, elastoplasticity

behavior is not dependent on time. In this sense the definitions of them are different

adopted in geology, where plasticity can also correspond to a viscous behavior.

6.2.1 Elastoplasticity

The behavior laws identify a perfectly elastic solid plastic. The simple analog

model corresponds to a linear spring and a pad in series given as in Figure 6.1.a. The

solid behaves elastic before reaching the threshold (limit) (σs). If reached, the solid

deforms plastically (Figure 6.1.b). The behavior is simpler than the rocks because the

constraint evolves beyond the threshold, which is not quite true for rock mechanics,

for which one can be problems positive (hardening) or negative (softening).

Figure 6.1 a) The model of elastoplastic material. b) The deformation of elastoplastic material due to

stress (modified from Vernant, 2003).

There are several laws to describe the elastic-plastic behavior of rocks. In this

study, two types of material, the Von Mises and Drucker-Prager materials were used.

In Von Mises material the threshold is constant and it is pressure-independent. On

the other hand, in the Drucker-Prager material, the threshold of plasticity changes are

related with mean stress, thereby increasing the resistance of rock is related with the

increasing of pressure (Jaeger & Cook, 1976; Byerlee, 1978).

The law used in our study is to Drucker-Prager material. The criterion load of the

form is (Leroy & Ortiz, 1989):

132

𝑓(𝜎) = 𝐽2(𝜎) − 𝛼(𝑘) ∙ �𝜎� + 𝑐𝑡𝑎𝑛𝜑

� < (6.9)

here, 𝐽2 is finite strain and given as;

𝐽2(𝜎) = �32‖𝑑𝑒𝑣𝜎‖

𝛼 = 6𝑠𝑖𝑛𝜑

3 − 𝑠𝑖𝑛𝜑

𝜎� = −13𝑡𝑟(𝜎) (6.10)

where dev is the deviatoric part of the tensor, σ is the average stress, φ is angle of

internal friction and c is cohesion (Vernant, 2003).

6.2.2 Viscoelasticity

Viscoelasticity is the property of materials that exhibit both viscous and elastic

characteristics when undergoing deformation. The viscoelastic behavior occurs at

higher pressure and temperature, its movements associated with dislocation or

diffusion. Maxwell model which described the viscoelastic

behavior, behaves steady as a perfect fluid when the applied strain (deformation)

rate is constant. On the other hand, short-term model responds instant access to a

sudden load. The Maxwell model can be represented by a damper purely viscous (η)

and a purely elastic spring with Young's modulus (E) connected in series (Vernant,

2003) (Figure 6.2).

Figure 6.2 a) The model of viscoelastic material. b) The behavior of the viscoelastic solid (Modified

from Vernant, 2003).

133

http://en.wikipedia.org/wiki/Viscosity

http://en.wikipedia.org/wiki/Elasticity_(physics)

http://en.wikipedia.org/wiki/Deformation_(engineering)

6.3 General Algorithm of the Finite Element Modeling Software (ADELI)

For 3D modeling of large deformations with code ADELI, computing

environment is discretized by tetrahedral finite elements with four nodes. The

discretization of the dynamic equation transforms the problem "continuum" in a

system of finite vector equations (three equations by mesh node).

The terms are obtained by assembling the contribution of each element, with the

M mass matrix, Fext the vector of external forces, Fint the vector of internal forces,

Fcont the contact force vector and the vector accelerations �̈� are given as (Vernant,

2003):

𝑀�̈� = 𝐹𝑒𝑥𝑡 + 𝐹𝑖𝑛𝑡 + 𝐹𝑐𝑜𝑛𝑡 (6.11)

According to Hassani (1994), the algorithm is as followings:

1. Calculation of the external forces: (𝐹𝑒𝑥𝑡)𝑛

2. Calculation of free residual: (𝑟𝑓)𝑛 = (𝐹𝑒𝑥𝑡)𝑛 + (𝐹𝑖𝑛𝑡)𝑛

3. Calculation of the acceleration:

�̈� = 𝑀−1 �(𝑟𝑓)𝑛 − 𝛼 ∙ 𝑠𝑔𝑛 ��̇�𝑛−12� �(𝑟𝑓)𝑛 + (𝐹𝑐𝑜𝑛𝑡)𝑛��

4. Calculation of velocity and displacement:

For velocity : ��̇�𝑓�𝑛+12 = ��̇��

𝑛−12 + ∆𝑡��̈��𝑛

For displacement: �𝑢𝑓�𝑛+1

= �𝑢�𝑛

+ ∆𝑡��̇��𝑛−12 + 1

2∆𝑡2��̈��

𝑛

5. Calculation of contact forces: (𝐹𝑐𝑜𝑛𝑡)𝑛+1

6. Corrections of velocity and displacement:

134

For velocity : ��̇��𝑛+12 = ��̇�𝑓�

𝑛+12 + ∆𝑡𝑀−1 (𝐹𝑐𝑜𝑛𝑡)𝑛+1

For displacement: �𝑢�𝑛+1

= �𝑢𝑓�𝑛+1

+ 12∆𝑡2𝑀−1 (𝐹𝑐𝑜𝑛𝑡)𝑛+1

7. Updating coordinates: 𝑥𝑛+1 = 𝑋 + 𝑢𝑛+1

(X is the vector of initial coordinates)

8. Calculation of stress and the internal forces:

For stress : 𝜎𝑛+1

For internal forces: (𝐹𝑖𝑛𝑡)𝑛+1

9. Calculations of strain rate; 𝜀̇, for mantle and sub-lithospheric mantle:

𝜀̇ = 𝐴 · 𝜎𝑛 exp �− 𝑄𝑅∙𝑇�

Here, T; temperature, 𝜎 ; differential stress, A; viscosity parameter, n; stress

exponent, Q; activation energy, R; ideal gas constant.

6.4 Applications

In this study, Western Anatolia was modeled to investigating the deformation

during the years. In this scope, the finite element modeling software, namely, ADELI

(Chery & Hassani, 2002) which was developed by using theoretical equations given

in Zienkiewicz (1977), Owen & Hinton (1980), Dhatt & Thouzot (1981), Salençon

(1995) was used. Additionally, the details of the equations and the algorithm used in

ADELI were given in Hassani (1994) and Huc (1997).

Before starting the modeling with finite element code, ADELI, it was needed to

create the model with meshes. Therefore, for generating the meshes, a three-

dimensional finite element mesh generator tool, namely, ‘Gmsh’ (Geuzaine &

Remacle, 2009) was used. After processing, for viewing the outputs, a parallel

visualization application tool, namely, ‘Paraview’ (Moreland K., 2013) was used.

135

For giving idea about ADELI, a simple model was created. In this simple model,

the length; 20 km, weight; 10 km and the depth; 10 km were given. Firstly, the

geometry of model was drawn (Figure 6.3), then it was meshed in 3D (Figure 6.4).

Therefore, the model was ready for processing and in Figure 6.5, the initial model

was shown.

Figure 6.3 The simple model created with ‘gmsh’.

Figure 6.4 The view of 3D meshing with ‘gmsh’.

136

The density; 2.9 gr/cm3, Young modulus; 1.e11 and Poisson ratio; 0.25, the

viscosity parameter; 3e-22, stress exponent; 15 were given as model parameters.

However, temperature and pressure were ignored. In the model, center of the

material a curve was given. In the numerical modeling, for extend the model, the

extensional forces were given to two opposite surfaces of the initial model with the

2.5 mm/yr velocities (Figure 6.5). The modeling time was chosen as 1.1 Myr. For the

example, the deformed models which were created after 0.7 Myr and 1.1 Myr were

given in Figure 6.6 and Figure 6.7. By the years, the initial model was deformed,

extended and the finite strain changes were shown in these figures.

Figure 6.5 The view of initial model. Green arrows represent the extensional forces were given the

borders.

137

Figure 6.6 The view of finite strain (deviatoric epsilon) of model after 0.7 Myr.

Figure 6.7 The view of finite strain (deviatoric epsilon) after 1.1 Myr.

In this study, Western Anatolia was modeled from south to north for modeling the

extension. The south border of Menderes Extensional Metamorphic Complex

(MEMC) at south side and the North Anatolian Fault zone at north side were chosen

as the boundary conditions of the model (Figure 6.8). The length of the model was

chosen as 250 km, the weight was chosen as 20 km and the depth was chosen as 30

km (Figure 6.9).

138

In the modeling, the continental crust was modeled up to 30 km. The modeled

was separated to 3 layers at z-direction. First layer depth was chosen as 4 km since

the depth of Gediz graben is approximately 4 km (Çiftçi & Bozkurt, 2010). Second

layer depth was 7 km since the effective elastic thickness was approximately 7 km on

Western Anatolia (Yurdakul, 2007; Pamukçu & Yurdakul, 2008). The depth of third

layer was as 30 km for modeling the crust up to Moho depth (Pamukçu & Yurdakul,

2008, Zhu et al., 2006). At the first layer, 3 weakness zones were given in the initial

model (Figure 6.9).

For continental crust, rheologic parameter (Activation energy, viscosity parameter

and stress exponent) of Gleason & Tullis (1995) based on wet quartzite were used

(Table 6.1). As elastic parameters; Young modulus E = 1011 Pa and Poisson ratio ν=

0.25 (Turcotte & Schubert, 2002) were given. As density 2.4 g/cm3 for first layer, 2.9

g/cm3 for second layer and 3.1 g/cm3 for third layer were given. The densities of the

weakness zones at the first layer shown as No:1, 2 and 3 in Figure 6.4, were chosen

as 2.4 g/cm3. For giving extension to the model, the forces were affected to the x

direction. The velocities were given to the south and north borders of the model and

additionally, to the south border of the No:1 weakness zone and north border of the

No:3 weakness zone. In Chapter 3 at the Anatolian block solutions, the velocities

were found approximately 3 mm/yr (Figure 3.43). Therefore, this magnitude of

velocity used in the modeling. The all parameters used in the modeling were given at

Table 6.1. The finite element modeling software, ADELI, was used the equations

explained in the previous sections during the modeling.

Table 6.1 Physical parameters used in the numerical modeling.

Parameters Values Young Modulus (Pa) 1011

Poisson ratio 0.25 Viscosity Parameter (Pa-n s-1 )(A) 1.10-28

Activation Energy (kJ/mol) 223 Stress Exponent (n) 4 Frictional Coefficient 0.3 Pressure (Pa) 0.e25

139

Figure 6.8 The view of the profile length of the numerical model. In this figure Google Earth tool was

used.

Figure 6.9 The initial view of the model. No:1, No:2 and No:3 represent the weakness zones.

The topography (Figure 6.10) and crust-mantle interface values (Figure 6.11)

which were represented the Moho depth of the study area (Pamukçu & Yurdakul,

2008) were used as surface and subsurface limits of the boundary conditions on the

140

model. Therefore, by taking into account these knowledge, the models were created

for different temperature values, geological scales and pressure values. The

temperature values which were used in modeling were based on the results of

Dolmaz et al. (2005) and Şalk et al. (2005).

Figure 6.10 The topographic cross-section of the study area. The longitude is 27º and the latitude

changes between 37.2º and 39.7º. BMG; Büyük Menderes graben, KMG; Küçük Menderes graben,

GG; Gediz Graben.

Figure 6.11 Crust-mantle interface values (Pamukçu & Yurdakul, 2008).

In the first application, 200ºK was given at the top of the model and 500ºK was

given at the bottom of the model as temperature values. As a result, the velocity

fields and finite strain fields of deformation which were obtained after 5 Myr, 10Myr

and 15 Myr were shown in the figures from Figure 6.12 to Figure 6.20.

141


Figure 6.13 The finite strain fields on model after 5 Myr for 200ºK-500ºK

142

(a)

(b)

6.14 a) The velocity fields on model after 5 Myr for 200ºK-500ºK b) The velocity fields with vectors

on model after 5 Myr for 200ºK-500ºK

143



144

(a)

(b)

Figure 6.17 a) The velocity fields on model after 10 Myr for 200ºK-500ºK b) The velocity fields with

vectors on model after 10 Myr for 200ºK-500ºK

145



146

(a)

(b)



It was seen that the finite strain and velocity fields of deformation increased by

increasing geologic time from 5 Myr to 15 Myr. Especially, the collapse and lifting

on the bottom increased on center of the weak zone. It was noticed that the model

deformations are too high after 10 Myr and 15 Myr for 200ºK-500ºK. Therefore, the

software was run for only 5 Myr for higher temperature applications.

147

In the second application, 273ºK was given at the top of the model and 773ºK was


fields and finite strain fields of deformation which were obtained after 5 Myr were

shown in Figure 6.21, 6.22 and 6.23.



148

(a)

(b)



If these deformed models (for 273ºK-773ºK) showed in Figure 6.22 and 6.23 were

compared with the results for 200ºK-500ºK (Figure 6.13 and 6.14 ) it was noticed

that the finite strain and velocity fields of deformations were looking similar. In the

other words, the deformation didn't increased by increasing the bottom temperature

from 500ºK to 773ºK.

In the third application, 273ºK was given at the top of the model and 900ºK was


149





150

(a)

(b)



In the forth application, 273ºK was given at the top of the model and 1400ºK was




151



152

(a)

(b)



If the results were compared according to different temperature values, it was

noticed that from the figures (Figure 6.22-6.23, Figure 6.25-6.26, Figure 6.28-6.29)

the finite strain fields enlarged on N-S direction (x-axis) along depth by increasing

the temperature of Moho from 500 ºK to 1400ºK. On the other hand, the velocity

values decreased and the velocity vectors directions changed by increasing the

temperature.

153

In the previous applications, the pressure value was 0.e25 Pa for all different

temperature models. For investigating the deformation changes with decreasing the

pressure values, the pressure was decreased to 0.e125 Pa for the model which had

273ºK-900ºK (Figure 6.30, 6.31).

Figure 6.30 The finite strain fields on model after 5 Myr for 273ºK-900ºK with 0.e125 Pa

Figure 6.31 The velocity fields on model after 5 Myr for 273ºK-900ºK with 0.e125 Pa

If the velocity fields of the model with 273ºK-900ºK (Figure 6.26a) and 0.e25 Pa

compared with the model with 273ºK-900ºK and 0.e125 Pa (Figure 6.31), it was

154

noticed that the velocity began to decreasing from the center of the deformed area to

the borders along to the x-direction by decreasing the pressure. At the same time, the

finite strain fields were larger at 0.e25 Pa (Figure 6.25) than at 0.e125 Pa (Figure

6.30).

At all modeling results at the deformed area, there were high deformation, low

magnitudes of GPS velocities relative to Anatolian block solution, low the Curie

depth points and high heat flow values (Dolmaz et al., 2005), high pressure values,

low gravity anomalies, less earthquakes, shallow crustal structure (Zhu et al, 2006;

Pamukçu & Yurdakul, 2008), Moho ondulations (Çifçi et al., 2011) and lots of

geothermal areas.

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CHAPTER SEVEN

CONCLUSIONS

Western Anatolia is one of the most tectonically active and rapidly deforming

regions of continental crust in the world. Due to the important case of Western

Anatolia, examining the kinematic mechanism of study area using GPS and gravity

measurements is the objective of this study.

For this purpose as the first step of the application sections, the GPS stations of

the TURDEP and CORS-TR projects which were obtained between the years 2009-

2011 and General Command of Mapping stations which were obtained 2000, 2001,

2004 and 2005 were processed relative to Eurasia fixed frame and additionally,

Anatolian and Aegean block fixed frames by using GAMIT/GLOBK software. In

Eurasia fixed frame solutions, the velocity magnitudes of the stations seemed similar

with each other and approximately 20-25 mm/yr for all stations. The obtained

velocities from this study and the velocities of previous study which were obtained

by McClusky et al., (2000) and TUBITAK project No:108Y285 were plotted

together for examining the velocity changes of the study area during the years. It can

be said that there was no big change from 1997 until 2011 on the directions and

magnitudes of the velocities. According to differences on velocity directions of the

stations, the study area was separated to four regions. Generally, it was pointed out

that the velocity directions of the stations rotated from west to southwest direction

from North to South. The Anatolian Block and Aegean block solutions were obtained

relative to the Euler vectors (Reilinger et al., 2006) for stations of TURDEP and CORS-

TR project for investigating the regional deformation and found that the velocity

magnitudes were between approximately 3-15 mm/ yr. In Anatolian block solutions,

the stations were grouped as 3 regions and 2 lines according to the velocity

directions. In Aegean block solutions, it was pointed out that the velocities of

southern stations were slower relative to the northern stations. It was noticed that the

velocity directions of CESM (Çeşme) and MUGL (Muğla) were different from the

other stations. BALK (Balıkesir) and HARC (Harmancık, Bursa) moved together

156

with the other stations. Additionally, the velocity of KRPT (Karpuzlu, Aydın) station

was very slow relative to other solutions.

As the second step of the application sections, the vertical components of GPS

and microgravity data were compared to investigating vertical mass changing on 6

points; Akhisar (AKHT), Bademli (BDMT), Borlu (BORT), Karacasu (KRCT), Çal

(CALT) and Eşme (ESMT) where obtained two data set on the same point

simultaneously. According to the relationship between GPS and microgravity data,

the deformation were interpreted with considering the earthquake distributions and

topography changes on station areas. For AKHT, BDMT and KRCT, it can be said

that there were not an expected relation between two data set. In AKHT, there was

high seismic activity so; this high seismicity may be the reason of lack of expected

relation between GPS and gravity data and irrelevance on equilibration mechanism

of surface and subsurface structures. According to seismicity, while the northern side

of the KRCT station has high seismic activity, the southern side has low seismic

activity relative to the northern side; oppositely, while the southern side of the CALT

station has high seismic activity, the northern side has low seismic activity relative to

the other side. Therefore, it can be said that KRCT and CALT stations were located

on a boundary. There were positive relations for BORT, CALT and ESMT between

two data set. It means that the surface loadings and subsurface loadings moved at the

same direction. It can be said that there were crustal problems on these station points.

There were geothermal sources near to BORT, BDMT, CALT and ESMT stations,

therefore it can be suggested that the geothermal sources cause the irrelevant on

equilibration mechanism of surface and subsurface structures and low seismic

activity in the station points.

As the third step of the application sections, on the northern normal fault of Gediz

Graben and southern normal fault of Büyük Menderes graben, GPS velocities of the

stations which were located surroundings of these fault were processed relatively

each other by GAMIT/GLOBK software. For northern normal fault of Gediz Graben

according to observed and modeled GPS velocities it can be said that BORT (Borlu,

Manisa) and TRGT (Turgutlu, Manisa) stations were coherent with the N-S

157

directional extension system. On the other hand, SALH (Salihli, Manisa) was not

moving properly with extension system. It was thought that SALH was affected by

both faults. In the next step, the coulomb stress changes were calculated for the

depths of 4 km and 6 km and for the depth range between 0-4 km and 0-6 km.

Consequently, it can be said that the stress area has regional effects for the depth

range between 0-4 km. The stress area (deformed area) had regional effects of total

deeper depth than 4 km. For southern Normal fault of Büyük Menderes Graben,

according to observed GPS velocities, it can be said that KRPT, CALT, BDMT and

KRCT were moving coherently with the main N-S extensional system. AYD1

(Aydın) was moving differently from the other stations, but its velocity was in the

error ellipse. The location of the AYD1 where was very near to the fault may be the

reason of this problem. DENI (Denizli) was found as stabile relative to opposite side

stations. While the observed and modeled GPS velocities for KRPT, BDMT and

KRCT were fitted, for CALT were not. As the next step, the coulomb stress changes

were calculated for the depths of 3 km and 5 km and additionally for the depth range

between 0-3 km and 0-5 km. Consequently, it can be said that Büyük Menderes

graben was affected by stress area up to 3 km. At the depth deeper than 3 km, the

stress area (deformed area) had total regional effects.

Additionally, for investigating the relative movements of the stations for different

directions some processing were done. Firstly, KIKA, AKHT and TRGT were

chosen left side stations and DEIR, BORT, USAK and ESMT were chosen as right

side stations. It was noticed that the velocity directions of DEIR and BORT were

different from ESMT and USAK. Then, DEIR and BORT were moved from the

processing stations and the stations were processed again. It was seen that after

moving DEIR and BORT, the same group stations ESMT and USAK did not

affected but in opposite group stations KIKA, AKHT and TRGT were affected.

Then, DEIR and BORT were added to left station group. It was found that the

velocity directions of DEIR and BORT were different from the same group stations.

Consequently, it can be said that DEIR and BORT were located in a different

structures from the surrounding stations. In other step, same application was done for

the stations near to Büyük Menderes Graben. It was noticed that BDMT, AYD1 and

158

KRPT were moving to South, on the other hand, KRCT, DENI and CALT were

moving to North. Consequently, for the relative applications it can be pointed out

that there may be a zone at N-S direction between the left and right stations.

At the last step of this study, Western Anatolia was modeled by finite element

modeling method for investigating the deformation changes by ADELI software. In

the modeling as the boundary conditions, the south border of Menderes Extensional

Metamorphic Complex (MEMC) at south side and the North Anatolian Fault zone at

north side were chosen. The continental crust was modeled up to 30 km. The

modeled was separated to 3 layers at z-direction. In the first application, 200ºK and

500ºK were given to the top and bottom of the model, respectively. It was seen that

the finite strain and velocity fields of deformation increased by increasing geologic

time from 5 Myr to 15 Myr. Especially, the collapse and lifting on the bottom

increased on center of the weak zone. It was noticed that the model deformations

were too high after 10 Myr and 15 Myr for 200ºK-500ºK. Therefore, the software

was run for only 5 Myr for higher temperature applications. In the second

application, 273ºK and 773ºK were given to the top and bottom of the model,

respectively. If the deformed models (for 273ºK-773ºK) were compared with the

results for 200ºK-500ºK, it was noticed that the finite strain and velocity fields of

deformations were looking similar. In the other words, the deformation didn't

increase by increasing the bottom temperature from 500ºK to 773ºK. In the third

application, 273ºK and 900ºK and in the forth application, 273ºK and 1400ºK were

given to the top and bottom of the model, respectively. As a result, it was noticed that

the finite strain fields enlarged on N-S direction along depth by increasing the

temperature of Moho from 500 ºK to 1400ºK. The velocity values decreased and the

velocity vectors directions changed by increasing the temperature. For investigating

the deformation changes with decreasing the pressure values, the pressure was

decreased to 0.e125 Pa for the model which had 273ºK-900ºK. It was found that the

velocity was decreasing from the center of the deformed area to the borders along to

the x-direction by decreasing the pressure and the finite strain fields were larger at

0.e25 Pa than at 0.e125 Pa. Consequently, the obtained model by ADELI software

159

which has 273ºK -1400ºK temperature, 0.e25 Pa pressure for 5 My is determined

coherent with Anatolian block solutions.

If the deformation models obtained by ADELI were compared with the results of

GPS and microgravity data (discussed in Chapter 4), it was noticed that all of the

stations (Figure 4.1) were located on the deformed area.

As suggestion for the numerical modeling step, different temperature and

different pressure values can be tested for interpreting the deformation in details.

The all results of this study were discussed with seismological and geological data

in related chapters.

160

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