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HYDROCHEMICAL CHARACTERIZATION AND NUMERICAL MODELING OF GROUNDWATER FLOW IN A PART OF THE HIMALAYAN

A dissertation submitted to Kent State University in partial fulfillment of the requirements for the degree of Doctor of Philosophy

By

Muhammad Asim December, 2005

Dissertation written by Muhammad Asim B.Sc. (Honors), University of , 1992 M. Sc., University of Peshawar, 1993 M. Phil., University of Peshawar, 1997 Ph.D., Kent State University, 2005

Approved by

Dr. Peter Dahl, Chair, Doctoral Dissertation Committee

Dr. Yoram Eckstein, Member, Doctoral Dissertation Committee

Dr. Neil Wells, Member, Doctoral Dissertation Committee

Dr. Mandy Munro-Stasiuk, Member, Doctoral Dissertation Committee

Dr. Eugene C. Gartland, Member, Doctoral Dissertation Committee

Accepted by

Dr. Donald F. Palmer, Chair, Department of Geology

Dr. Jerry Feezel, Dean, College of Arts and Sciences

ii TABLE OF CONTENTS

List of Figures ……………………………………………………………………...... vi

List of Tables ……………………………………………………………………………xi

ACKNOWLEDGEMENTS …………………………………………………………….xii

CHAPTER

1 INTRODUCTION………………………………………………………...1

1.1 Objectives of the study…………………………………………….1

1.2 Significance of the research……………………………………….4

1.3 The study area……………………………………………………..5

1.4 The Himalayan Foreland Basin…………………………………...9

1.5 Literature review…………………………………………………11

1.6 Field and analytical procedures………………………………….14

2 TECTONICS AND STRATIGRAPHY…………………………………22

2.1 Tectonic framework……………………………………………...22

2.2 Stratigraphy………………………………………………………26

2.3 The Peshawar intermontane basin……………………………….38

iii

3 HYDROGEOLOGY……………………………………………………..42

3.1 General hydrogeology……………………………………………42

3.2 Groundwater geology in the Peshawar Basin……………………56

3.3 Peshawar Basin aquifers...……………………………………….64

3.3.1 Peshawar piedmont aquifer………………………………64

3.3.2 Peshawar lacustrine aquifer……………………………...65

3.3.3 Peshawar floodplain/stream channel aquifer…………….65

4 HYDROCHEMISTRY…………………………………………………..68

4.1 Physico-chemical parameters…………………………………….68

4.1.1 Water surface temperature……………………………….68

4.1.2 pH distribution…………………………………………...77

4.1.3 Conductivity and Total Dissolved Solids………………..77

4.2 Groundwater classification………………………………………82

4.3 Geothermometry…………………………………………………97

5 NUMERICAL SIMULATIONS………………………………………..105

5.1 Groundwater flow in basins under compressive regimes………105

5.2 Abnormal fluid pressures……………………………………….107

5.3 Groundwater Modeling System………………………………...108

5.4 Formulation of FEMWATER…………………………………..110

5.5 Boundary conditions……………………………………………113

iv

5.6 GMS Modeling approach………………………………………117

5.6.1 The conceptual model approach………………………..118

5.6.2 Initial conditions………………………………………..119

5.6.3 Time control parameters………………………………..120

5.7 Application of the model to the Himalayan foreland…………...121

5.8 Model parameters……………………………………………….124

5.8.1 Running the model……………………………………...127

5.8.2 Computed vs. observed values………………………….128

5.8.3 Error vs. time step……………………………………....128

5.8.4 Parameter sensitivity……………………………………139

5.8.5 Calibration targets………………………………………141

5.9 Modeling results………………………………………………...143

6 DISCUSSION AND CONCLUSIONS………………………………...149

6.1 Discussion………………………………………………………149

6.2 Conclusions……………………………………………………..154

6.3 Future work……………………………………………………..155

REFERENCES…………………………………………………………………………157

APPENDIX A………………………………………………………………………….170

APPENDIX B…………………………………………………………………………..179

v LIST OF FIGURES

Figure Page 1.1: Index map of showing the location of the study area………………...... 3

1.2: Map showing location of deep water wells and drainage system in southern part of the study area…………………....……………………………….7

1.3: Map of the major faults and sampling sites in the Peshawar Basin and environs superimposed on shaded relief map of the study area…..……9

1.4: Determination of physico-chemical characteristics of groundwater in the field……………………………………………….……………………….17

1.5: Calibration curves obtained for major ions analyzed in groundwater samples by ICP ………………………………….………………………………18

1.6: Calibration curves obtained for trace elements analyzed in groundwater samples by ICP ………………………………...……………………………...... 19

1.7: Calibration curve and relevant data for DIONEX Ion Chromatograph………….20

1.8: Calibration curve and relevant data for the TOC Analyzer……………………...21

2.1: Structural map of the study area showing major thrust zones.…………………..24

2.2: Geologic map of the study area showing prominent lithologies…………………28

2.3: Columnar sections of the sedimentary sequences in the ……………29

2.4: Dissolved evaporites of Bahadur Khel Salt as seen on this river bed in the vicinity of , south of Peshawar Basin……..……………………30

2.5: Generalized stratigraphy of the Kohat-Potwar area………..…………………….32

2.6: Red sandstones and clays of the Siwalik Group in the Kohat-Potwar plateau of north Pakistan…………...………………………………..……….. …34

vi

2.7: Precambrian metasedimentary series (Salkhalas) exposed on the northern edge of Peshawar basin…………………………………………………………..35

2.8: The Precambrian metamorphic series intruded by post-collisional granites (Malakand area)…...……………………………………………………………..36

2.9: Late Paleozoic metasedimentary rocks of the Eurasian Mass north of the MKT, showing spectacular minor folding...……………………………………..37

2.10: Late to Early Paleozoic metamorphic sequence exposed on the southern margin of the Peshawar Basin...………………………………………..40

2.11: Cross section A-A', extending from the Peshawar basin to the western Salt Range………………………………. ………………………………………41

3.1: Water table elevation (in meters) varies considerably in the area……………….43

3.2: The only dug well in area, located at Mastuj Fort…...…………………..44

3.3: Large sediment load, carried by Chitral River because of high discharge and steep gradients……………………………………………..………………...46

3.4: A small spring in the Early Paleozoic rocks (limestone) in the Attock-Cherat Ranges on the southern margin of Peshawar basin………………47

3.5: Seepage appearing in the Khyber Slate series along the eastern margin of Peshawar basin, just south of Pakistan- border…………………..48

3.6: Spring appearing in alluvium along the Main Swat Road, north of Mingora…………………………………………………………………49

3.7: Largest spring in the study area, located just north of Chitral, which provides most of the drinking water to the city…..……………………………...50

3.8: A small spring appearing in alluvium along the Booni-Chitral road……………51

3.9: The surface expression of this spring is in a glacial till in the town of Mastuj….52

3.10: This spring appears in the Permian Slate series of the Eurasian mass along the Chitral-Garam Chashma road……..…………………………………..53

3.11: This spring appears in the Garam Chashma granodiorite. …………..54

vii

3.12: Hot springs at Garam Chashma, yielding a surface temperature of 70 °C………55

3.13a: Drilled wells known as tube wells and used extensively for irrigation purposes……………………………………………………………….57

3.13b: An operational tube well in the Tarbela area…………………………………….58

3.14: Dug wells, which are most commonly used for domestic purposes and are very susceptible to contamination..…………………………………………..59

3.15: Topographic map of Peshawar basin showing major localities and rivers (contour values given in meters)……….……………………………..61

3.16: Fence diagram constructed from borehole data in the Peshawar Basin……………………………..……………………………………63

3.17: Confluence of Kabul and Indus Rivers at the eastern margin of Peshawar Basin……………………………………………………………………………..67

4.1: Index map of the sampling sites………………………………………………….69

4.2: Distribution of groundwater temperature recorded at the surface (°C).…………70

4.3: Mean annual air temperature based on data from 19 recording stations (°C)…...71

4.4: Distribution of the difference between water surface temperature and mean annual air temperature (∆T °C)………………………………………………….72

4.5: Distribution of pH values in the study area…...…………………………………74

4.6: Distribution of electrical conductivity (EC) values in the study area (micro S/cm)……………………………………………………………………………..76

4.7: Total Dissolved Solids (TDS) distribution in the area (mg/l)……………………77

4.8: Piper (1944) diagram for spring water samples………...………………………..79

4.9: Piper (1944) diagram for shallow well water samples…………………….….….80

4.10: Piper (1944) diagram for deep well water samples………………… …….…....81

4.11: Hounslow (1995) brine differentiation plot, superimposed by data points for deep well water samples…………………………………………….…….….82

viii

4.12: Hounslow (1995) brine differentiation plot superimposed by data points for shallow well water samples..…...... 83

4.13: Hounslow (1995) brine differentiation plot superimposed by data points for spring water samples…………………………………………… …….……..84

4.14: Map of SiO2 concentrations (in mg/L)………………...…………………………86

4.15: Map of boron concentrations (in mg/L)……………..…………………………...87

4.16: Map of strontium concentrations (in mg/L)………….…………………………..88

4.17: Source reservoir temperature of groundwater calculated from chalcedony geothermometry……………………………………………………………….....91

4.18: Source reservoir temperature of groundwater calculated from Mg-corrected Na-K-Ca geothermometry……………………………………………………....92

4.19: Relationship between temperature anomaly and silica concentration in spring water……………………………………………………………..…….93

4.20: Relationship between temperature anomaly and boron concentration in spring water……………………………………………………………………93

4.21: Relationship between temperature anomaly and Sr concentration in spring water………………………………………………………………………94

4.22 Relationship between temperature anomaly and Li concentration in spring water………………………………………………………………………94

4.23: Relationship between spring water temperature and cation-predicted temperature………………………………………………………………………95

4.24: Relationship between spring water temperature and Chalcedony-predicted temperature………………………………………………………………………95

4.25: Relationship between spring water temperature and Mg-Li-predicted temperature………………………………………………………………………96

5.1: Conceptualized model of a generic foreland basin and adjacent fold and thrust belt …………………………….………..……………………………….123

5.2: Boundary conditions and production wells in the study area ….………...…….125

ix

5.3: 2-D mesh generated for the study area, ultimately converted to a 3-D mesh (mesh has been refined around the wells)………...……………………...130

5.4: 3-D representation of the model layers……………………….………………...131

5.5: Input data parameters for modeling deep and shallow wells in the basin……...132

5.6: Initial conditions (IC) have been specified using the Generate IC button….…..133

5.7: Iteration parameters for the flow simulations……………….………………….134

5.8: Dialog showing material properties…………………………………………….135

5.9: Dialog showing progress of the simulation…………………………………….136

5.10: Plot showing computed vs. observed values for the pressure head…………….137

5.11: Plot showing error vs. time step for the transient simulation………….…..…...138

5.12: Sensitivity analysis for various input parameters in FEMWATER modeling of the Peshawar Basin………………..………………………………140

5.13: Components of the Calibration Target………………………………………….142

5.14: Total heads (m) as obtained from the transient simulation, shown on the iso-surface…..…………………………………………………………………..146

5.15: Results of the transient simulation at the last stress period shown as regional pressure heads……..……………………………………………………………147

5.16: Study area shown in map view. Calibration targets for the pressure head simulations indicate errors within the target……………………………………148

x LIST OF TABLES

Table Page 4.1: Physico-chemical characteristics of groundwater samples taken from deep wells………………………………………………………………………..97

4.2: Physico-chemical characteristics of groundwater samples taken from shallow wells…………………………………………………………………….98

4.3: Physico-chemical characteristics of groundwater samples taken from springs……………………………………………………………………………99

4.4: Hydrochemical data for groundwater samples from drilled wells (ionic concentrations in mg/L)………………………………………………….101

4.5: Hydrochemical data for groundwater samples from dug wells (ionic concentrations in mg/L)………………………………………………….102

4.6: Hydrochemical data for spring water samples (ionic concentrations in mg/L)………………………………………………….103

5.1: Input parameters for the model…………………………………………………129

5.2: Recharge and discharge data for the basin……………………………………..129

5.3: Pressure head values (m) and the amount of residuals for the production and observation wells………………………………………………145

xi ACKNOWLEDGEMENTS

I would like to thank my Co-Advisor, Dr. Yoram Eckstein, for giving me the opportunity to pursue my Ph.D. research at Kent State University. His gentle guidance and steady support are much appreciated. I could ask for no better mentor in this pursuit of science. Dr. Eckstein proved to be a great teacher, mentor, and friend. I am also thankful to my Co-Advisor, Dr. Peter S. Dahl, for his guidance and support throughout this research. His critical comments proved to be a valuable asset, and I greatly appreciate his cooperation, particularly during the last stages of this dissertation. Without

the overwhelming support of my advisors, this dissertation would not have been written.

I also wish to thank the committee members: Dr. Mandy Munro-Stasiuk, Dr. Eugene, C.

Gartland and Dr. Neil Wells for reviewing this manuscript and for all they have taught

me. I especially thank Dr. Neil Wells for providing insights into the statistical aspects of

the data analysis. Other mentors I wish to mention here are Dr. Donald Palmer and Dr.

Richard Heimlich.

I would also like to acknowledge the wonderful support of Dr. Ksenija Dejanovic in the analytical phases of the research in Kent, and I owe a great deal of thanks to Mr.

Ghaffar Khan for his hospitality and support during my field work in Pakistan. In addition, I gratefully acknowledge generous financial support from the Geological

Society of America and from Sigma Xi for the field work associated with this research project. Also, I appreciate the Department for supporting the analytical and

xii

computational phases of this project, and for providing me with four years of stipend and tuition waivers.

Finally, I would also like to express my gratitude to my family members, whose sustained support over the years has been of absolute importance to me. I only wish that my deceased brothers, Sajjad and Amir, and my deceased father could have seen me reaching this milestone.

xiii CHAPTER 1

INTRODUCTION

1.1 Objectives of the Study

This research was undertaken to characterize the hydrochemistry and flow paths

of groundwater in the Peshawar Basin and environs, NW Pakistan (Figure 1.1), and to develop a simulation model for groundwater flow in this part of the Himalayan foreland fold-and-thrust belt. Although the Himalayan foreland basin is considered to be under abnormal hydrostatic pressure (Law et al., 1998) the basin simulation model is intended to test this assumption by establishing the presence (or absence) of anomalous hydraulic heads that cannot be explained by topography- or density-driven fluid flow alone. Such anomalies, if present and particularly if coincident with any physical or hydrochemical anomalies, would then be interpreted as having been caused by the only other factor potentially contributing to groundwater flow, namely, the regional tectonic stress regime.

The specific objectives of this research project are:

1. To test the existence of abnormal hydrostatic pressures in the Himalayan foreland

basin.

1 2

2. To test the hypothesis that abnormal pressure may be caused by compaction under

tectonic stresses.

3. To evaluate the role of compressional tectonics in driving deep groundwater in

part of the Himalayan foreland basin.

The research program consists of two major tasks: 1) examination of the

hydrochemical characteristics of a part of the Himalayan groundwater as related to the

regional geology and tectonics; and 2) hydrodynamic modeling of the regional

groundwater flow. Collectively, the two tasks, once completed, will provide tests of the hypothesis, while also quantifying the tectonically-driven overpressure only postulated thus far in theoretical treatment of the subject from topography-driven head (e.g., Oliver,

1986; Ge and Garven, 1994; Bitzer et al., 1996; Neuzil, 1995; McPherson and Garven,

1999 etc.). Most importantly, aside from the local significance, the results of this research will provide an insight into the general relationship between the tectonic stress and fluid migration in a foreland basin under compressive tectonic regime. 3

Gilgit

AFGHANISTAN Peshawar Islamabad

INDIA Quetta

N PAKISTAN

A

R

I N

Karachi 0 400 km INDIAN OCEAN

Figure 1.1: Index map of Pakistan, with boxed area showing the location of the study area. 4

1.2 Significance of the research

This research represents a first attempt to identify the effects of tectonic stress on the groundwater flow patterns in the field, which thus far have only been postulated in theoretical treatments of the subject (e.g., Oliver, 1986; Ge and Garven, 1992; Bitzer et al., 1996; etc.). If successful, this research will contribute to regional understanding of the hydrotectonic processes operating in the Himalayan foreland fold-and-thrust belt, which in turn may prove useful for delineating the paths of petroleum migration and ore mineralization. Within the Peshawar Basin per se, the research is also expected to benefit ongoing efforts to identify and quantify the local water resources that are potentially available to the inhabitants of the Indus Valley.

Foreland basins characterized by stratigraphic continuity, such as the Himalayan foredeep, typically host the largest groundwater flow systems. Because groundwater flow is the dominant mechanism for transporting chemical mass in sedimentary basins, knowledge of the hydrodynamics and geochemistry of flow and transport is a fundamental prerequisite to understanding geologic processes (Garven, 1995). These sedimentary basins are being explored extensively for ore deposits, fossil fuels, and water resources. The Himalayan foreland basin in Pakistan is known to host several trillion cubic feet of gas, and extensive oil and coal deposits (Kazmi and Jan, 1997). The current daily production rates are 60,000 barrels of oil and 2 billion cubic feet of gas in Pakistan

(World Bank Report, 2003). Ore deposits are also being mined economically throughout the region, such as the lead-zinc ores from the Besham area (Kazmi et al., 2000; see

Figure 4.1). Elsewhere, voluminous field data have been obtained that document large- 5

scale groundwater flow. For example, Oliver (1986) postulated for the Appalachian orogen that under the load of thrust sheets, fluids are expelled from continental margins and move towards the foreland basin in the continental interior. Moreover, such tectonically-driven fluids play an important role in geological processes such as faulting, magmatic activity, migration of hydrocarbons, mineral transport, metamorphism, and establishment of paleomagnetic signatures (Oliver, 1986). Indeed, abnormal pore-fluid pressures are known to contribute to overthrusting in the active fold-and-thrust belt of

Taiwan (Suppe and Wittke, 1977). Further, analysis of groundwater hydrodynamics in active thrust belts has proven useful for understanding flow regimes in ancient thrust belts (e.g., the Valley and Ridge, Canadian Rockies, etc.) in that active thrust belts reveal important information not available in ancient belts. Such information includes gravity, seismicity and heat flow data relevant to the timeframe of thrusting (Lillie et al., 1987).

As indicated above, the specific objective of this research is to gain understanding

of the hydrotectonic processes operating in the Himalayan foreland fold-and-thrust belt,

by field-testing the hypothesis that tectonic compression generates abnormally high

hydrostatic pressures in an intermontane sedimentary basin. If this hypothesis is

supported, then the research will have provided new insight regarding the role of

tectonics in delineating the paths of petroleum migration and ore mineralization.

1.3 The Study Area

The study site covers Peshawar Basin and environs in the Himalayan foreland fold-and-thrust belt of northwest Pakistan. The area, located between the latitudes 32-37° 6

N and longitudes 70-74° E, is characterized by steep topography with U-shaped glaciated

valleys in the north, which drain into the River Indus entering from Kashmir and the

River Kabul entering from Afghanistan (Figure 1.2). This basin was chosen for several

reasons. Firstly, it is one of the best-known regions under an unquestionable compressive tectonic regime, where three great mountain ranges (Himalaya, Karakoram, and

Hindukush) join one another (Figure 1.2). Secondly, the Pakistani Himalayan foreland basin exposes rocks, ranging in age from Precambrian to , which are host to enormous oil and gas deposits. Finally, these rocks are arranged in well-characterized thrust sheets and piggy-back basins, thereby providing an excellent opportunity to study the effects of these structural features and related tectonic activity on regional groundwater movement.

The most important mountain ranges in the study area are the ,

Hindukush, and Karakoram (Figure 1.2). Cold winters and warm, dry summers

characterize the climate. June through August are the hot months, during which the mean

maximum air temperature is about 40 °C. The mean annual potential evaporation ranges

from 85 cm in the north of the study area to 130 cm in the Peshawar basin. Snowfall

occurs in the mountainous north during the cold months of December to February when

minimum temperature is several degrees Celsius below the freezing point (Ahmad et al.,

2002).

7

Figure 1.2: Map showing locations of deep water wells and the drainage system in the southern part of the study area. Source: Water and Power Development Authority (WAPDA), 1998 hydrogeological map. 8

1.4 The Himalayan Foreland Basin

Foreland basins are formed by large-scale overthrusting. For example, the

Alberta Basin, Canada, is adjacent to the Rocky Mountains and dips down towards them.

Thus, the overthrusting accommodates compressive stress by horizontal movement of rocks in the basin, whereas the more significant vertical deflection is the result of tectonic loading. In foreland basins, thermal effects on the rocks are insignificant and the rate of subsidence may be very irregular, depending on the way the overthrust loads have evolved (Allen and Allen, 1990).

The Himalayas were formed in conjunction with an arc-trench system, indicating significant horizontal tectonic compression. At present, the Indian craton is moving north-northeast at a rate of 44-61 mm/yr relative to Eurasia/Siberia (Bilham et al., 1997).

Mandal et al. (2000) reported active shortening accommodated by thrust faults and folds and coeval strike slip faulting along the Jhelum and Kalabagh faults. The active faults within the Himalaya are the Main Boundary Thrust (MBT) and Main Central Thrust

(MCT; Figure 1.3; Lave and Avouac, 2000). Recent tectonism continues to be compressional in nature, resulting in active seismicity. A clearly identifiable ~50-km wide zone of predominately moderate earthquakes (M 5-6), termed the Main Himalayan

Seismic Zone, is located between the MCT and MBT (Kayal, 1996; Figure 1.3).

Instrumentally recorded seismicity of moderate magnitude is concentrated beneath the

MCT at depths between about 10 and 20 km. Active deformation along the MCT is expressed by scarps, uplift, and folding of late Quaternary and Holocene deposits. The 9

38° N

RF

MKT

36° N

MMT

Kabul River

34° N MCT Peshawar

MBT Islamabad

Bannu SRT JF

KF 0 100 km 32° N 70° E 72° E 74° E

Figure 1.3: Map of the major faults and sampling sites (white dots) in the Peshawar Basin and environs superimposed on the shaded relief map of the study area. Salt Range Thrust (SRT); Main Boundary Thrust (MBT); Kalabagh Fault (KF); Main Central Thrust (MCT); Main Mantle Thrust (MMT); Jhelum Fault (JF); Main Karakoram Thrust (MKT); Islamabad (Id); Peshawar (Pr); Indus River (IR); Kabul River (KR); Bannu (Bn). 10

continuing northward drift of has resulted in the underthrusting of Indian lithosphere beneath the and Pamir, causing the most seismically active zone of intracontinental, intermediate-depth earthquakes known on Earth (e.g., Billington et al., 1977; Burtman and Molnar, 1993).

The earthquake focal mechanism solutions (Lisa et al., 1997) and moment-tensor solutions point to a dominant compressive stress regime of about 90 MPa resulting from the India-Eurasia collision (Mandal et al., 2000). A compressive stress of this magnitude has the potential to have caused abnormal fluid pressures in the Himalayan region. Specifically, gravitational loading and tectonic forces increase stress on the sediment, thereby compressing the pore fluid and generating abnormal pressures in low- permeability media (Palciauskas and Domenico, 1989). Indeed, abnormal pressures were reported by some very early workers from the Himalayan region (e.g., Anderson, 1927;

Keep and Ward, 1934). Subsequently, Law et al. (1998) identified two distinct abnormal pressure regimes from the Potwar Basin in north Pakistan (Figure 1.2) – one in rocks and another in pre-Neogene rocks. These workers documented pore pressures in

Neogene rocks equivalent to lithostatic pressures and as high as 0.5-0.7 psi/ft (11.3-15.8 kPa/m) in the pre-Neogene rocks. The abnormally high pressures created major problems for drilling operations in the Potwar Basin. Based on evaluation of thermal maturity, temperature, clay mineral transformations, sediment deposition rates, and structural aspects, Law et al. (1998) concluded that the abnormal pressures resulted from tectonic compression and undercompaction associated with high sedimentation rates.

Abnormal pore pressures in the pre-Neogene rocks were attributed to a combination of 11

hydrocarbon generation and tectonic compression. Presence of biogenic or

thermocatalytic gas has not been reported from the Potwar Basin, thus excluding the

possibility of aquathermal pressuring being a mechanism responsible for abnormal

pressures (Kadri, 1991).

1.5 Literature Review

Fluid flow evolution in thrust belts has been investigated by several workers.

Hubbert and Rubey (1959) and Gretener (1972) postulated that the development of overpressures might affect the evolution of thrust belts. Bear and Corapcioglu (1981) presented a series of four papers analyzing water flow in deformable porous media. They analyzed centrifugal filtration and drained a porous sample under enhanced drainage conditions to determine its properties and dewatering processes. They also presented a model for regional land subsidence due to pumpage from a confined aquifer. Oliver

(1986) hypothesized that along zones of convergence, associated with the Appalachian mountain belt, fluids were expelled from the margin sediments and traveled into the foreland basin and continental interior. In essence, he proposed that the thrust sheet acts like a great squeegee, driving fluids in the upward direction resulting in widespread geologic consequences. Ge and Garven (1989) explored the coupled effects of 2D deformation-driven flow in generic models of foreland basins. They developed 2D numerical models to quantify the role of compressional tectonics in driving regional fluid

flow in the later stages of thrusting in a foreland basin. Deming et al. (1990) studied the

thermal effects of compaction-driven flow with finite difference modeling of a generic 12

basin and found that focusing of flow lines was a necessary requirement for local

elevation of heat flow. Foster and Evans (1991) conducted laboratory and numerical

studies to characterize the permeability structure of thrust zones and to predict regional

groundwater flow patterns in a generic thrust sheet as driven strictly by present-day

topography alone. Ge and Garven (1992) further discussed the general features of

tectonically-driven flow in a sensitivity study that considered effects of permeability, fault and stratigraphic heterogeneity, loading magnitude, and variations in rock

compressibility. They found that tectonically-generated flow rates of centimeters per

year would dissipate over periods of thousands of years. Garven (1995) presented an

overview of the flow systems on a continental scale. He discussed and compared large

hydrogeologic systems that extend laterally for several hundred kilometers, most

commonly across continental landmasses. He also presented an overview of the oil

migration and ore deposits in the context of groundwater flow. Bitzer et al. (1996)

developed a finite element model for the southern Pyrenean foreland basin of Ainsa to

describe fluid flow evolution during the emplacement of thrust sheets. They compared

petrological and geochemical data in the Ainsa basin host rocks and veins to provide

independent support for their model. Garven and Freeze (1984), Oliver (1986), and

Bethke and Marshak (1990) − among others − suggested an association between regional

fluid migration in ancient basins, ore mineralization, and deformation of orogenic belts.

Indeed, these workers have postulated that tectonically-driven fluids may transport heat

and dissolved mass, thereby playing a role in a variety of geochemical processes. The

mechanisms responsible for evolution of excess pore pressures in a ramping thrust sheet 13

were investigated by Smith and Wiltschko (1996). They numerically solved the coupled

pore pressure and temperature equations in two dimensions using a generalized 2-D

hydrostratigraphy of the North American thrust belts. Toth and Almasi (2001) recently

studied the fluid flow patterns in the Pannonian basin of the Hungarian Great Plain. They constructed pressure-elevation profiles and recognized two principal pore pressure zones.

On this basis they divided the Pannonian basin into an upper, gravity-driven unconfined zone and a lower, overpressured confined zone. They concluded that faults and fracture zones act as preferential pathways for pressure diffusion, and thus fluid flow, upwards.

Several workers have studied the nature of groundwater flow in extensional environments. Eckstein and Maurath (1995) developed heat flow models for the Dead

Sea region and concluded that the pattern of terrestrial heat flow density is a product of deep crustal convection being transferred through a thick sedimentary sequence. Hurwitz et al. (2000) worked on the transient groundwater-lake interactions in the Sea of Galilee,

Israel. These workers discussed numerical simulations solving the coupled equations of fluid flow and solute and heat transport. Specifically, they examined the feasibility of the hypothesis that the previously intruded brine had been flushed backward towards the sea.

Odero and Peloso (2000) studied in detail the hydrogeology of the rift valley of Kenya.

Gvirtzman and Bitzer (2000) discussed buoyancy-driven flow associated with salinity variations for the Dead Sea Rift. They proposed buoyancy-driven flow as the principal driving force causing large-scale migration of brine and hydrocarbons in the Dead Sea.

Lampe et al. (2001) developed mathematical models for episodic fluid flow in the

Rhinegraben. Cole et al. (2001) developed a groundwater model for middle Rio Grande 14

Basin. They assembled a 3D geologic framework model using subsurface data from

geophysical logs, detailed surface geologic mapping, and basin wide interpretations of

gravity and magnetic data. McKenzie et al. (2001) presented geochemistry of spring

water from the main Ethiopian rift. The groundwater resources of the southern Arava rift

valley (Israel and Jordan) were quantified by Bein et al. (2001). They used a 3D

calibrated model to explore the quantitative aspects of the water resources of the area.

Heat transport by groundwater flow during the Baikal Rift evolution was studied by Poort and De Batist (2002), who produced a two-dimensional model to study sedimentation, fluid flow, and heat flow in the rift basin.

As implied in the above summary, much more research has been done in

extensional terrains as compared to compressional terrains, in terms of hydrogeological

modeling and field-based hydrochemical and geothermal investigations. However, as

with extensional settings, the hydrogeological regimes of compressional settings have

enormous economical potential in terms of concentrating metallic ores and hydrocarbons.

Studying such regimes is becoming an active research area (Van Balen and Cloetingh,

1993), for which there is a pressing need. Accordingly, this study investigates

groundwater flow in the compressional setting represented by the Himalayan foreland

basin, northwest Pakistan.

1.6 Field and analytical procedures

Two sets of 71 water samples (100 ml untreated, and 100 ml treated with nitric

acid) were collected from water wells, springs, and seepages throughout the study area 15

during July-August 2003. The body of sampling sites included 34 springs, 21 deep wells,

and 16 shallow wells. More water samples were collected along the fault zones and from

Peshawar Basin than from the rest of the study area. Each sampling site was mapped

with a Garmin GPS V, with a position accuracy of less than ±3 m. General physico-

chemical parameters such as temperature, pH, total dissolved solids (TDS), and electrical

conductivity (EC) were determined in the field using Technika Water Quality Meter

850081 with dedicated sensor probes (Figure 1.4). All water samples were filtered in the

lab with a 0.45 µm pore diameter filter.

Water samples were analyzed for major and trace elements at the Department of

Geology, Kent State University. Concentrations of cations (Ca, Mg, Na, K, Sr, B, Li, Si) were analyzed using Perkin Elmer Optima 3300 DV ICPES equipped with an AS90 Plus autosampler. Multi-element solutions prepared from a 20 µg/mL stock solution were used as calibration standards for trace elements, whereas for major elements single- element 1000 mg/L stock solutions were used to make the calibration standards.

Examples of elemental calibration curves obtained on the ICP are shown in Figures 1.5 and 1.6. Overall precision errors of analyses were less than ±6% for trace elements and less than ±3% for the major cations (95% confidence). Concentrations of anions (Cl,

NO3, SO4) were determined using a DIONEX DX 120 Ion Chromatograph with an AS50

autosampler. Anion standard solutions consisted of 1 mg/L, single-element solutions, and the calibration curve for the DIONEX is shown in Figure 1.7. Precision errors of the

- analyses were less than ±5% for all anions (95% confidence). Bicarbonate ion (HCO3 ) was indirectly derived from total carbon as analyzed by SHIMADZU TOC 5000 16

instrument, with precision error less than ±2% (95% confidence), and its calibration

curve is shown in Figure 1.8. The so-called reaction error (cations-

anions/cations+anions) was less than ±5% for all the samples.

For all instruments used, the overall errors in analytical precision quoted above

were estimated from the combination of sampling, instrumental, and replication errors.

Sampling errors (Es) were estimated for all samples from analysis of several sets of

duplicate samples collected from several sampling sites. Instrument errors (Ei) were determined by repeatedly analyzing given standards at specific time intervals.

Replication errors (Er) inherent in the DIONEX phase were evaluated by analyzing three

separate injections from each water sample. Each error component was calculated from

the average reading (x) and standard deviation (s) as:

E = x * s

and overall error (E) is given as the sum of the three error components:

E = Σ (Es + Ei + Er)

17

Figure 1.4: Determination of physico-chemical characteristics of groundwater in the field using Technika Water Quality Meter 850081. 18

Figure 1.5: Calibration curves obtained for major ions analyzed in groundwater samples by ICP. Ion emission is given in counts per sec (cps). 19

Figure 1.6: Calibration curves obtained for trace elements analyzed in groundwater samples by ICP. Ion emission is given in counts per sec (cps). 20

Std 4 1.0 Sample Name: Std 1.0 Injection Volume: 25.0 Vial Number: 5 Channel: ECD_1 Sample Type: standard Wavelength: n.a. Control Program: ANIONS Bandwidth: n.a. Quantif. Method: Anion Dilution Factor: 1.0000 11/14/2003 Recording Time: Sample Weight: 1.0000 13:53 Run Time (min): 15.00 Sample Amount: 1.0000

No. Ret.Time Peak Name Height Area Rel.Area Amount Type min nS nS*min % uM 1 1.79 F 64759.44 6035.04 16.75 1.001 BM 2 2.17 Cl 104539.77 8464.94 23.49 1.003 M 3 3.01 NO3 70414.12 8037.83 22.30 1.002 M 4 3.68 SO4 64091.07 8296.29 23.02 1.003 MB 5 9.39 PO4 6753.75 5205.37 14.44 1.003 BMB^ Total: 310558.16 36039.46 100.00 5.011

120,000 111403 MA #4 [modified by malaclypse, 1 peak manually assigned] ECD_1 nS

Cl 100,000

80,000 NO3 F SO4 60,000

40,000

20,000

PO4 0

-20,000 min 0.0 2.0 4.0 6.0 8.0 10.0 12.0 15.0

Figure 1.7: Calibration curve and relevant data for DIONEX Ion Chromatograph. 21

Figure 1.8: Calibration curve and relevant data for the TOC Analyzer. CHAPTER 2

TECTONICS AND STRATIGRAPHY

2.1 Tectonic Framework

The study area contains three main tectonic elements: the Indo-Pakistan shield and its northern sedimentary cover (Indian Mass), the strata deposited on the southern part of the Eurasian Mass, and the Kohistan Island Arc Sequence (Powell, 1979). From

Archean times, the Indo-Pakistan sub-continent was part of Gondwanaland, which consisted of the continents of South America, Africa, Antarctica, Australia, and India. A vast stretch of the Tethys Sea existed between the Indo-Australian part of Gondwanaland

and Eurasia. From Permian through Middle Jurassic time, the was entirely

located in the Southern Hemisphere. About 130 million years ago, the Indian plate broke

away from Gondwanaland and started drifting towards Eurasia, with the simultaneous

consumption of the intervening Tethys Sea (Khan et al., 1987). In the Upper

(84 Ma), the Indian plate began its very rapid northward drift at an average speed of 16

cm/year, covering a distance of about 6000 km, until the collision of the northwestern

part of the Indian passive margin with Eurasia in the lower (48-52 Ma). All told, the collision of India with Eurasia has accommodated 2000 to 3000 km of convergence since Eocene time (Molnar and Tapponnier, 1977).

22 23

Plate motion models and recent Global Positioning System (GPS) measurements

indicate that convergence between the Indian and Eurasian plates is about 40 to 50 mm/year (De Mets et al., 1994; Paul et al., 2001). At least 17 km of shortening of the

sedimentary section has resulted from movement along the current thrust front,

represented as the Salt Range Thrust (SRT) in Pakistan. Deformation was episodic and

concentrated on the SRT between 10 and 5 Ma and since 1.9 Ma (Sylvain et al., 2002).

The absence of large earthquakes in the Potwar plateau and Salt Range has been

explained by the presence of salt at the décollement level (Yeats and Lillie, 1991). Lillie

et al. (1987) incorporated surface geology, well log, seismic reflection, and gravity data

into studies of thrusting and basin development in the Himalayan foreland of north

Pakistan. They postulated that Indian continental crust of normal thickness underthrusts

a wedge of Phanerozoic sedimentary rocks that thickens to 9 km beneath the northern

Potwar plateau and that extends for over 100 km onto the Indian craton (Figure 2.1).

Gravity and other subsurface data indicate a relatively thin elastic plate

underthrusting the Himalaya in Pakistan (Lillie et al., 1987). The folds and thrusts ride

on a cushion of salt and do not involve the basement (Yeats and Lillie, 1991). The

basement is well imaged on seismic profiles beneath the Salt Range and Potwar Basin,

where it gently dips to the north at 1° and 3-4°, respectively (Lillie et al., 1987). Focal

mechanism solutions indicate that the earthquakes in this region are mainly thrust-type

events, whereas those in Tibet are mainly normal fault-events with associated small

subsets of strike-slip events in both regions (Baranowski et al., 1984). 24

Figure 2.1: Structural map of the study area showing major thrust zones (with teeth on upthrown blocks). Lowlands and Quaternary deposits are shown by stippled pattern. A-A' is the line of the geological cross section in Figure 2.11 (From McDougall et al., 1993). 25

The ongoing northward convergence of the Indian plate with greater Asia has resulted in the formation of four major south-verging thrust faults striking the length of the Himalayan arc (Figure 2.1). The northernmost of these thrusts is Main Karakoram

Thrust (MKT), which separates Asian plate metasedimentary rocks from the Kohistan island arc (KIA). The Main Central Thrust (MCT) emerges along the southern edge of the High Himalaya. It has not been observed to break Quaternary deposits and is therefore considered inactive (Nakata, 1989). The Main Mantle Thrust (MMT) separates the KIA from rocks of the Indian continental margin. The Main Boundary Thrust

(MBT), marking the southern edge of the Lesser Himalaya, is expressed in bedrock along the arc, and is locally observed to displace Quaternary deposits. The southernmost thrust is the Salt Range Thrust (SRT), which separates rocks of the Indian continental shelf from the Quaternary alluvium of the Indus plain (Pivnik and Sercombe, 1993). It is considered to be the most active of the four thrusts and delineates the northern limit of the exposed Indian Plate.

Deformation related to collision of India and Eurasia began in Late Cretaceous or

Early time (Beck et al., 1995; Klootwijk et al., 1991, 1994). Beck et al.,

(1995) mapped a succession of marine sediments, including upper Paleocene strata containing foraminifera, that were considered to be overlapping the suture between the

Indian plate and Asian terranes. Their biostratigraphy was calibrated radiometrically to give an absolute age of 57 ± 1 Ma. It is believed that the onset of collision predates these biostratigraphic marker beds (Butler, 1995). The cessation of marine sedimentation in the middle Eocene marks the southward encroachment of deformation on the northern 26

Indian continental margin (Pivnik and Wells, 1996). Sercombe et al. (1994) concluded

that -Pleistocene deformation of the Pakistan foreland is characterized to a large degree by high-angle, oblique-reverse faults, as opposed to low-angle thrust faults as believed by some previous workers (e.g., Abassi and McElroy, 1992; Baker et al., 1988;

Lillie et al., 1987; McDougall and Hussain, 1991; Pennock et al., 1989).

The sedimentary record of closure of the southern Asian Tethys Sea and collision of India and Eurasia is preserved in Paleocene-Pleistocene sedimentary sequences exposed in the deformed foreland of northern Pakistan, India, and (e.g., Pivnik and

Wells, 1996). Whereas Paleocene-Early Eocene sedimentary rocks form a pre-orogenic complex assemblage of limestone, shale, evaporite, sandstone, and conglomerate (e.g.,

Meissner et al., 1974), the late-synorogenic upper Siwalik group of Pliocene-Pleistocene age records the full imprint of convergent Himalayan tectonics in the proximal foreland of northwest Pakistan (Burbank and Raynolds, 1988). During this latter time period the foreland basin was internally partitioned by Himalayan deformation, giving rise to piggy- back basins such as the Peshawar and Campbellpore Basins (Pivnik and Johnson, 1995).

2.2 Stratigraphy

The Himalayan foreland deposits of the Indus Basin occupy the southern part of the study area (Figure 2.2), whereas metasedimentary and igneous rocks occupy the northern portion. Gravity and seismic surveys, coupled with borehole data, indicate that

Precambrian rocks form a gentle westward dipping monocline covered by a sequence of

marine, deltaic, and fluviatile sediments (Kazmi and Jan, 1997). The Himalayan foreland 27

resulted primarily from subsidence driven by thrust loading. Sediment carried into the foreland by hinterland rivers can either be stored within the foreland or can bypass it and be transported by the or Indus Rivers to the sea, where it is stored in the Bengal fan or Indus cone (Brozovic and Burbank, 2000). Ongoing India-Asia convergence has led to flexural downwarping of the overridden Indian plate, forming the Himalayan molasse basin, the world’s largest terrestrial foreland basin (Watts, 1992; Burbank,

1996;). Due to subduction, uplift, and erosion, there is a dearth of preserved and exposed

Paleogene foreland (Bossart and Ottiger, 1989; Critelli and Garzanti, 1994; Najman et al.,

1993). From early time onward, however, there is a well exposed, continuous record of detritus shed from the Himalayan Mountains.

The depositional record in and around the Upper Indus Basin is relatively complete from Late Proterozoic to Holocene time (Shah et al., 1977; Iqbal and Shah,

1980). The sedimentary rocks in the area include siliciclastic, carbonate, and evaporite sequences (Figure 2.2) of Precambrian through Pleistocene age attaining a maximum collective thickness of 9000 m (Law et al., 1998). Oil-impregnated shale, sandstones, and carbonates interbedded with evaporites of the Late Proterozoic and Lower Cambrian

Salt Range Formation overlie the Late Proterozoic metamorphic basement rocks (Figure

2.3). The upper part of the Salt Range consists of thick carbonates overlain by evaporites marking the top of the formation (Shah et al., 1977; Iqbal and Shah, 1980). The thickness of the Salt Range Formation varies from more than 1000 m down to 50 m in places where the sequence is truncated by dissolution of these evaporites (Figure 2.4). 28

Quaternary sediments Neogene sedimentary rocks Paleogene sedimentary rocks Tertiary sedimentary rocks Tertiary intrusive & metamorphic rocks Cretaceous sedimentary rocks Jurassic metamorphic rocks Triassic metamorphic & sedimentary rocks Undivided Paleozoic rocks Carboniferous sedimentary rocks Silurian rocks Cambrian sedimentary & met. rocks Undivided Precambrian rocks

Figure 2.2: Geologic map of the study area showing prominent lithologies (after Wandrey and Law, 1999). 29

Figure 2.3: Columnar sections of the sedimentary sequences in the Salt Range (from Fatmi et al., 1984). 30

Figure 2.4: Dissolved evaporites of Bahadur Khel Salt as seen on this river bed in the vicinity of Kohat, south of Peshawar Basin. 31

Above the Salt Range, evaporites consist of as much as 150 m of marine shales and

massive sandstones representing braided-stream deposits of the Khewra Formation,

which has produced oil at different oil fields (Khan et al., 1986). Paleozoic rocks attain a

total thickness of 1230 m and are composed of conglomerate, sandstone, siltstone, shale, and carbonate sequences deposited in marine and non-marine environments. Erosion at

the base of the Lower Permian and base of the Paleocene sections accounts for most of

the thickness variations in these sequences (Figure 2.3). The Cambrian Khewra and the

Permian Tobra and Wargal Formations have yielded oil and gas at different localities in

the basin (Jaswal et al., 1997). An Early Permian unconformity indicates the onset of

fluvio-glacial to glacio-marine/lacustrine conditions (Quadri and Quadri, 2003).

Mesozoic rocks are as thick as 460 m and consist of sandstone, siltstone, shale, and

carbonate sequences deposited in marine and non-marine environments. Progressive

eastward truncation of Mesozoic rocks at the base of the Tertiary section has resulted in

the absence of Mesozoic rocks in the central and eastern parts of the Potwar Plateau

(Jaswal et al., 1997; Figure 2.5). The Jurassic Datta Formation has produced oil and gas

from three fields in the northwest Potwar Plateau area (Quadri and Quadri, 2003).

The Tertiary section includes Paleocene through Pleistocene conglomerate,

sandstone, siltstone, shale, carbonate, and coal that were deposited in marine and non-

marine environments. Paleogene rocks range in thickness from 240-300 m, and the

Neogene rocks are as thick as 6400 m (Law et al., 1998). Oil or gas production from

eight fields spanning the Potwar Plateau is attributed to the Lockhart, Patala and Margala

Hill Formations (Iqbal and Shah, 1980). The Neogene molasse rocks, including the 32

ERA PERIOD GROUP FORMATION LITHO LOG MAXIMUM THICKNESS (m)

Holocene Lei Conglomerate 900 nary ater

Qu Soan Fm 450 Pleistocene k i l Dokh Patan Fm 1820 Pliocene Siwa Nagri Fm 1500 Chinji Fm 1800

Miocene indi p Kamlial Fm 650 Murree Fm 3030 Rawal IC ZO

NO Eocene y CE

tiar Kohat Fm 170

Ter Kuldana Fm 135 t

a Chorgali Fm 150 Lst. 300

Chhar Nammal Fm 130 Patala Fm 182 Paleocene Lockhhart Fm 260 Hangu Fm 150 Late Kawagarh Fm ------200 Early Lumshiwal Fm 120 Cretace ous

IC Late Chichali Fm 70

ZO Middle Samana Suk Fm 366 Shinawari Fm 400 rassic

u Datta Fm 400 MESO J Early Late Kingriali Fm 106 Middle Tredian Fm 88

iassic Early

Tr Mianwali Fm 187

Chhidhru Fm 64 Late Wargal Fm 183

Zaluch Amb Fm 80 Sardhai Fm 65 n

C Warchha Fm 180 a

OI Dandot Fm 50 ian Z Early m Tobra Fm 133 O E Per Nilawah PAL Late/Middle Baghanwala Fm 116 80 elum rian

Jh Jutana Fm b Early Kussak Fm 70

Cam Khewra Fm 200

Salt Range Fm >>>>>>>>>>>>> ian

br (Base not Exposed) m a Shale Dolomite Limestone Marl eC >>>>>> Gypsum Pr Sandstone Conglomerate

Figure 2.5: Generalized stratigraphy of the Kohat-Potwar area (modified from Quadri and Qaudri, 1996; Kemal, 1992; Iqbal and Shah. 1980; Shah et al., 1977). 33

Miocene Rawalpindi Group and Miocene to Pleistocene Siwalik Group, represent the erosional history of the Himalayas. These two groups are composed of conglomerate, sandstone, siltstone, and shale deposited in fluvial environments in response to the southward-advancing Himalayan thrusting. Sediments derived from the thrust sheets along the northern edge of the plateau were deposited rapidly. Rates of sedimentation in the Siwalik Group have been determined to range from 20-50 cm/1000 yr (Raynolds and

Johnson, 1985). Individual lithologic units within both groups exhibit variable thicknesses and are highly lenticular. The Murree Formation contains the youngest reported oil-producing reservoirs in the Kohat-Potwar geologic province. Pliocene and

Pleistocene Siwalik Group fluvial sandstones and conglomerates (Figure 2.6) mark the top of the stratigraphic column in the area (Shah, 1977). The Siwalik strata traditionally have a tripartite division into the progressively younger Lower, Middle, and Upper

Siwalik Formations (Shah, 1977): these roughly correspond to lithofacies (and have generally been regarded as chronofacies) dominated by siltstone, sandstone, and conglomerate, respectively.

The northern block of the study area consists of a complex sequence of igneous, metamorphic, and subordinate sedimentary rocks. The Kohistan terrain formed as an island arc that was later modified in an Andean-type setting. It consists of Cretaceous and Tertiary igneous (gabbroic to granitic) rocks and subordinate sedimentary rocks. The

Asian plate sequence is comprised of Paleozoic to Mesozoic sedimentary and metasedimentary rocks (Pivnik and Johnson, 1995; Figures 2.7, 2.8). The rocks of the

Eurasian Mass north of the MKT (Figure 2.9) are late-Paleozoic metasedimentary 34

Figure 2.6: Red sandstones and clays of the Siwalik Group in the Kohat-Potwar plateau of north Pakistan, which represent the lithologic signature of Himalayan erosion.

35

Figure 2.7: Precambrian metasedimentary series (Salkhalas) exposed on the northern edge of Peshawar basin. 36

Figure 2.8: The Precambrian metamorphic series, intruded by post-collisional granites (Malakand area). 37

Figure 2.9: Late Paleozoic metasedimentary rocks of the Eurasian Mass north of the MKT, showing spectacular minor folding.

38

rocks, mainly flysch (limestone- and shale-dominant), which are considered deep-sea sediments deposited by turbidity currents along the Eurasian plate margin in the Northern

Tethys geosyncline (Khan et al., 1987).

2.3 The Peshawar intermontane basin

The transitional block between MBT and MMT contains Proterozoic to Mesozoic strata of the Indian plate that include abundant intrusive rocks and which experienced

Late Cretaceous-Paleogene greenschist- to amphibolite-facies metamorphism (Figure

2.10) (Maluski and Matte, 1984). All these rocks border the intermontane Peshawar

Basin, which is a broad, oval shaped depression comprising a thick sequence of lacustrine, deltaic, and fluvial sediments overlain by loess and alluvial deposits. These deposits have been dated at 2.8 to 0.6 Ma (Burbank and Tahirkheli, 1985) (Figures 2.1 and 2.11). The basin lies to the north of the Attock-Cherat Range and contains rocks transitional between the sedimentary fold-thrust belt to the south and a metamorphic terrane to the north (Hussain et al., 1998). This basin is superimposed on the Himalayan fold-and-thrust belt in northwest Pakistan, giving rise to a piggy-back basin. Exposure of

Mesozoic and older strata is limited to small inliers of bedrock within the basin and to ranges north and east of the basin fill. The basin sediments are tilted, folded, and faulted along ENE trending faults with north sides upthrown (Hussain et al., 1998).

Evidence for late Quaternary tectonics has been found in four left stepping, en echelon pressure ridges formed within the basin parallel to its southern margin (Hussain et al., 1998). The deformation in the basin is marked by a zone of instrumental seismicity 39

(Seeber et al., 1981). The linear fault traces and instrumental seismicity suggest that the active faults of the basin cut down to the basement rocks. The southward migrating wave of thrusting reached the MBT during the time of deposition of Peshawar and

Campbellpore basin sediments (Hussain et al., 1998; Figure 2.11). South-verging imbricate thrusting in the Murree Formation (mid-Tertiary) was followed by deep erosion and subsequent deposition of lacustrine, fluvial, and alluvial fan deposits in the Peshawar and Campbellpore basins (see Figure 2.1). This deposition was synchronous with the

Attock-Cherat and Kala Chitta ranges being elevated on the back of the MBT (Yeats and

Hussain, 1989). 40

Figure 2.10: Late Proterozoic to Early Paleozoic metamorphic sequence exposed on the southern margin of the Peshawar basin. 41

Pz: Paleozoic strata; Mz: Mesozoic strata; Te: Lower Tertiary strata; M: thrust sheet directly below the MBT.

Figure 2.11: Cross section A-A', extending from the Peshawar basin to the western Salt Range (from McDougall et al., 1993).

CHAPTER 3

HYDROGEOLOGY

3.1 General hydrogeology

The study area can be divided into two hydrogeological provinces. These provinces are described separately below.

The northern portion of the area is mountainous and the water table varies in depth in different intermontane valleys, suggesting the existence of hydraulic discontinuities within the province. In fact, water table elevation varies considerably within the area (Figure 3.1), ranging from less than 100 m in the southern portion to more than 2400 m in the mountainous north (in relation to mean sea level). Abundant springs

(normal and high temperature) are present in this part of the study area, and locally

constitute an important source of drinking water. The outflow from these springs ranges

from less than one L/sec to more than 2000 L/sec. These springs have their surface

expressions in a variety of rocks and unconsolidated sediments. There are no drilled or

dug (shallow) wells in this portion of the study area except for one at Mastuj Fort (Figure

3.2; location D6 in Figure 4.1). The Chitral River drains this area and enters into

Afghanistan with a heavy sediment load. Very small hydroelectric power projects have

been constructed on this river (Figure 3.3). My field investigations indicate that most of

the springs have good quality water, and, according to local authorities, there are

42 43

2500

2300 36°N

2100

1900

1700

1500

1300

1100 34°N Peshawar Islamabad 900

700

500

300

32°N 71°E 73°E

Figure 3.1: Water table elevation (in meters), which varies considerably within the study area. 44

Figure 3.2: The only dug (shallow) well in Chitral area, located at the Mastuj Fort (Sample D6).

45

no water-borne diseases in these areas. Most of the springs flow from unconsolidated or

semi-consolidated fluvial deposits or talus surrounded by various types of hard rocks

(Figures 3.4-3.11). The main rock types in the northern portion of the study area are

slates, phyllites, various types of schists, paragneisses, sandstones, and quartzitic

crystalline conglomerates, which are intruded by basic-to-acidic igneous rocks. The

igneous rocks, constituting the Kohistan Island Arc (KIA) sequence, consist of a thick

series of calc-alkaline plutonic, volcanic and volcano- sedimentary rocks, Jurassic-

Cretaceous in age (Todaka et al., 1988). There are a number of hot springs in this region, most of which are located in relatively inaccessible areas. The ones most accessible are present in the town of Garam Chashma, which means “hot spring”. These springs are located 45 km north of the District Headquarters of Chitral and are famous for their curing properties. The dissolved minerals have been deposited where these springs appear on the surface. The Garam Chashma Hot Springs (Figure. 3.12; Sample S16 on

Figure 4.1) appear in the post-collisional Garam Chashma leucogranites, which yield K-

Ar (biotite) age of 20-18 Ma in the Hindukush Range (Hildebrand et al., 1998; Zafar et al., 2000). It is the westernmost manifestation of the Himalayan Geothermal Belt (HGB), between the MBT and MKT. The HGB has been described in great detail by Tong and

Zhang (1981), Hochstein and Regenauer-Lieb (1988), and Hochstein and Yang (1995).

The source of elevated heat flow within the HGB has been attributed to “advective sweeps of infiltrated meteoric water from the hot brittle, upper crust” (Hochstein and

Regenauer-Lieb, 1988). 46

Figure 3.3: Large sediment load carried by Chitral River, because of high discharge and steep gradients. The Chitral River enters Afghanistan and re-enters Pakistan as the Kabul River at the eastern edge of the Peshawar basin. 47

Figure 3.4: A small spring (Sample S24) in the Early Paleozoic limestone in the Attock- Cherat Ranges, on the southern margin of the Peshawar basin. 48

Figure 3.5: A seepage (Sample S23) in the Khyber Slate series along the eastern margin of the Peshawar basin, just south of Pakistan-Afghanistan border.

49

Figure 3.6: A spring (Sample S28) occurring in alluvium along the Main Swat Road, north of Mingora.

50

Figure 3.7: The largest spring (Sample S15) in the study area, located just north of Chitral, which provides most of drinking water to the city. The discharge is estimated at > 2000 L/sec.

51

Figure 3.8: A small spring (Sample S7) appearing in alluvium along the Booni-Chitral road.

52

Figure 3.9: A spring (Sample S9) occurring in a glacial till, in the town of Mastuj. 53

Figure 3.10: A spring (Sample S17) occurring within the Permian Slate series of the Eurasian mass, along the Chitral-Garam Chashma road.

54

Figure 3.11: A spring (Sample S15) occurring in the Paleogene Garam Chashma granodiorite.

55

Figure 3.12: The hot springs (Sample S16) at Garam Chashma, which yielded a surface temperature of 70 °C. 56

The southern part of the study area consists of the Indus platform and the

foredeep, which are covered by unconsolidated Quaternary deposits that attain a

maximum thickness of 500 m (Gazdar, 1987). This part can be divided into isolated

basins including the Peshawar, Bannu, and Campbellpore Basins, which are variously

bordered by mountains on one side or on all sides. The main sources of recharge to the

aquifer are precipitation, seepage from rivers, surface storage reservoirs, and irrigation

networks. A large number of drilled wells and dug wells are present in the area. They

are extensively used for irrigation, industrial, and domestic, purposes. Drilled wells

(Figure 3. 13a and b) range in depth from 50 to 150 m, whereas the maximum depth of

the dug wells (Figure 3.14) is 20 m.

3.2 Groundwater geology in the Peshawar Basin

The Peshawar intermontane basin is filled with thick sequences of Quaternary

sediments, a large portion of which were deposited by break-out floods generated by breaching of glacial dams along upper and middle Indus Valley. The presence of horizontally bedded, fining-upward sequences of sands, silts, and clays throughout the basin has previously been ascribed to Pleistocene lakes within the basin (Said and Majid,

1977). It has been suggested that these sediments, however, show sedimentological properties that are more characteristic of deposits of periodic break-out flood deposits and not lacustrine deposits. Various deposits of these sediments show evidence of subaerial exposure (mudcracks and bioturbation zones), lateral continuity, and fracture sets

(Cornwell, 1998). Evidence of ice-dams and lakes in the Indus drainage system is 57

Figure 3.13a: Drilled wells known as Tube wells, which are extensively used for irrigation purposes.

58

Figure 3.13b: An operational tube well in the Tarbela area. 59

Figure 3.14: A typical dug well, which are most commonly used for domestic purposes and are very susceptible to contamination.

60

abundant. Cross-valley moraines and lacustrine deposits that stretch many kilometers upstream are visible in the middle Indus valley. Limited thermoluminescence (TL) analyses of the youngest set of graded sediments in the basin suggest an age of at least

130,000 years BP. This timeframe correlates to the Yunz stage of glaciation along the middle Indus valley which spans from the middle to late Pleistocene to about 130,000

years BP (Cornwell, 1998).

The basin sediments form productive aquifers both north and south of Peshawar

valley. However, in the central part, the coarse sediments are interbedded with clay, silt,

and sandy silt attaining its maximum thickness and providing semi-confinement for a

number of aquifers. Khyber, Attock-Cherat, and Lower Swat-Bunner piedmont aquifers

occur on the periphery of the basin, whereas flood plain and lacustrine aquifers occupy the central part. Depth to the water table is less than 5 m, except on the margins of the basin and in the southeast where it ranges from 5 to more than 30 m. Hydraulic conductivity ranges from 30-60 m/day and the average specific yield is 12%; these values

indicate a potentially high-yielding aquifer with substantial storage capacity (Rathur,

1987). There is a general groundwater flow from the margins of the basin towards the

center, with an average gradient of 0.004 (Bundschuh and Balke, 1991). Robberts (1988)

estimated that the total recharge to the basin is 923 Mm3/yr over a 6270 km2 area. The main contributors to this recharge are precipitation (151 Mm3/yr), surface water irrigation

(734 Mm3/yr), groundwater-based irrigation (15 Mm3/yr), and runoff water (23 Mm3/yr).

The discharge of the groundwater takes place mainly along the downstream part of the

Kabul River and its tributaries (Figure. 3.15). Additional discharge occurs through 61

34.5°N

Mardan

Kabul River Swabi 34°N Peshawar

Indus River

33.5°N 71.5°E 72°E N 72.5°E 0 50 km

Figure 3.15: Topographic map of the Peshawar basin showing major localities and rivers. Elevations of contours are given in meters. 62

subsurface outflow into the basin, pumping for irrigation, drainage, and water consumption for domestic and industrial purposes. The total estimated discharge from the basin is 891 Mm3/yr, of which base flow constitutes 713 Mm3/yr (Robberts, 1988).

Information on subsurface geology of the basin has been derived from the lithological logs of boreholes drilled by WAPDA, Pakistan, and made available through various Information Releases. These data indicate that the Quaternary sediments vary in thickness from few meters to more than 150 m. However, the total thickness of

Quaternary sediments is not known because none of the boreholes penetrates the bedrock

(Figure 3.16). The coarseness of these sediments increases from north to south in the basin (Tariq and Hamidullah, 2003). In the central part of the basin the alluvial sediments consist of a relatively large proportion of fine-grained material, where the sandy silt is interbedded with discontinuous alluvial sand and thin gravel layers of various thicknesses.

Figure 3.16 shows that coarse-grained layers occur only as lenses and are not interconnected. However, the absence of significant changes in the groundwater level over short distance is an indication of hydraulic continuity between the gravel strata

(Kruesman and Naqavi, 1994). It may be assumed that the gravel and sand strata are hydraulically interconnected and form a large regional aquifer. Semi-confined aquifer conditions predominate over most part of the basin, where the topographic gradient is steep. Artesian conditions occur where the transmissivity of the deep aquifers rapidly decreases due to a decrease in average grain size. As a consequence, many boreholes in the western part of the basin are free-flowing wells (Kruesman and Naqavi, 1994). 63

Figure 3.16: Fence diagram constructed from borehole data in the Peshawar basin. Borehole data were taken from WAPDA, Hydrogeology Directorate, Peshawar and are indicated here with different borehole numbers.

64

3.3 Peshawar Basin Aquifers

Lack of available borehole data is a hindrance in classifying the aquifers of the

Peshawar Basin. On the basis of three main lithologies of the area (piedmont, break-out flooding, and the flood plain deposits), various types of aquifers can be classified in this basin.

3.3.1 Peshawar Piedmont Aquifer

The Peshawar Piedmont Aquifer is further divided into Khyber, Attock-Cherat and Lower Swat piedmont aquifers. The Khyber Mountain Range piedmont aquifer occupies the west and northwest of the basin. The aquifer is generally composed of fluvial sediments occurring in the form of alluvial fans. These sediments consist mainly of interbedded gravel, sand, and clay layers. Calcium carbonate concretions (irregularly shaped and very well sorted) are associated with fine- to coarse-grained sand. These fluvial sediments form a vast unconfined aquifer, which is intervened occasionally by thin clay layers. The Attock-Cherat Range piedmont aquifer is generally composed of

Paleozoic rocks and is considered as the catchment area for the southern part of the basin.

The fluvial deposits consist of clastic material derived from the bordering hills, except

along the main streams where flood plain deposits are found. The aquifer in this area is

characterized by both floodplain and piedmont deposits, which consist mainly of clastic

material, coarse sand, gravel, and interbedded clay layers. The Lower Swat Range

piedmont aquifer is found in the northeastern margin of Peshawar Basin. The alluvial

deposits at the base of this range form unconfined and confined aquifers. Locally, the 65

confined conditions are developed due to the presence of clay lenses. The unconfined

aquifer is of low permeability and consists of silt, clay, and (rarely) fine sand strata,

whereas the confined aquifer is highly permeable and generally composed of sand and

gravel strata from a depth of 30 to 150 m. Dug wells in this area confirm the low permeability conditions. However, these wells are used only for domestic purposes

(Kruesman and Naqavi, 1994).

3.3.2 Peshawar Lacustrine Aquifer

This aquifer is classified on the basis of lacustrine deposits now believed to have been deposited by break-out flooding during the Pleistocene (Cornwell, 1998). These deposits occupy the central portion of the basin in the Nowshera, Mardan, and Swabi areas (Figure. 3.15). The alluvial sediments of the central part of the basin contain a large proportion of fine sand, silt, and clay interbedded with discontinuous alluvial sand and thin gravel layers of various thicknesses. Coarse-grained deposits of sand and gravel are present in the western part of the basin and along the river channels. The fine-grained strata provide semi-confined aquifers over most of the central part of the basin.

3.3.3 Peshawar Floodplain/Stream Channel aquifer

The current and past channel deposits of the Kabul and Swat rivers are classified as the Floodplain/Stream Channel aquifer. This type of aquifer is local in extent and relatively shallow in depth as compared to the Pleistocene flood deposits in the basin.

The Kabul River drains almost the entire basin and discharges into the Indus River at the 66

eastern edge of the basin (Figure. 3.17). The Kabul River divides the basin into northern and southern portions and carries large amount of sediments during the summer season.

67

Figure 3.17: Confluence of Kabul and Indus Rivers at the eastern margin of Peshawar basin. Muddy water on the left is from Kabul River, whereas clear water on the right comes from the Indus River.

CHAPTER 4

HYDROCHEMISTRY

4.1 Physico-chemical Parameters

Temperature, pH, Total Dissolved Solids (TDS), and Electrical Conductivity (EC) were measured as part of the hydrochemical field work (field and analytical methods have been described in Chapter 1). The physico-chemical data for springs and deep and shallow water-wells are presented in Tables 4.1-4.3 and an index map of the sampling sites is shown in Figure 4.1.

4.1.1. Water surface temperature

Temperature ranges from 14 to 29.5 °C for the well waters and from 8 to 68 °C for the spring waters (Figure 4.2). Groundwater temperature generally equilibrates itself

with the mean annual air temperature for a particular locality. The mean annual air

temperatures range from 13 to 25 °C and are given in Figure 4.3 (NASA-GISS, 2005).

The regional distribution of differences between the water surface temperature and mean

annual air temperature, designated here as ∆T, is mapped in Figure 4.4. It is seen in

Figure 4.4 that most groundwaters show some surplus over the mean annual air

temperature. The hot spring at Garam Chashma shows the maximum surplus over the

mean annual air temperature. Specifically, with its orifice temperature of 68 °C it is ~52

68 69

AFGHANISTAN S18 Asian Plate S7 S5 RF MKT S4

S8 S6 S9 S10 Kohistan Island S15 D6 Spring S17 S11 Arc sequence Deep (drilled) well S16 S13 S14 S3 Shallow (dug) well S21 N S19 A S20 S28 N T S I 0 50 km S34 Besham K S12 S33 A 35° N S32 MMT S30 P S27 S31 D16 S29 D15 S26 W20 INDIA Indian PlateS25 D14 W21 S23 D7 D13 D3 W15 D5 D8 W16 D4 MCT S22 D12 S24 D11 W14 W17 W13 D10 MBT W1 W12 S1 W11 W2

Transitional Zone W3 D9 W4 W18 W19 D2 33° N W5 W7 D1 S2 W8 RT W9 S W10 W6 Himalayan Foreland

71° E 73° E

Figure 4.1: Index map of the sampling sites. Salt Range Thrust (SRT); Main Boundary Thrust (MBT); Main Central Thrust (MCT); Main Mantle Thrust (MMT); Reshun Fault (RF). 70

RF MKT 56

36°N 50

44

38

MMT 32

34°N MCT 26

MBT 20

14 SRT 8

32°N 71°E 73°E

Figure 4.2: Distribution of groundwater temperature recorded at the surface (°C). Fault representations are as identified in Figures 1.3 and 4.1. 71

38°N

26

25

24

36°N Chitral 23

Drosh 22

21 Dir 20

19 Chakdara Battal Balakot 18 Kakul Landikotal Risalpur 17 Peshawar Haripur 34°N Murree Cherat 16 Kohat Rawalpindi 15

14 Bannu Jhelum 13

Mianwali

DIKhan 32°N 70°E 72°E 74°E

Figure 4.3: Mean annual air temperatures based on data from 19 recording stations (°C). The data were taken from NASA’s Goddard Institute for Space Studies, 2005 (website). 72

RF MKT 52

36° N 46

40

34

28

22 MMT 16

34° N MCT 10

MBT 4

-2

SRT -8

32° N 71° E 73° E

Figure 4.4: Distribution of the difference between water surface temperature and mean annual air temperature (∆T °C). Fault representations are as identified in Figures 1.3 and 4.1 73

°C warmer than the local mean annual temperature (Figure 4.4). Significantly, the only two springs (samples S8 and S11, Figure 4.1) with temperature considerably below local mean annual air temperature are located relatively far from the fault lines, whereas sampling sites with positive thermal anomalies (i.e., where water sample temperature significantly exceeds local mean annual air temperature) are either very close to or virtually straddling a fault line (Figure 4.4).

4.1.2 pH distribution

The values of pH exhibit a rather narrow distribution in the study area, as shown in Figure 4.5. In particular, the well waters range in pH from 7.1 to 8.6, whereas pH values of the spring waters range from 6.7 to 8.7. Moreover, the groundwater tends to be more acidic away from most major fault zones (except the MCT and MBT) and more alkaline groundwater in the vicinity of these fault zones. Also, higher values of pH are noticed in the center of Peshawar basin (> 7.8) as compared to the low values on its margins (< 7.6).

4.1.3 Conductivity and Total Dissolved Solids

Conductivity, which is also known as electrical conductivity (EC), specific conductivity, or conductance, is the reciprocal of the resistance in ohms between the opposite faces of a one-cm cube of an aqueous solution at 25 °C. The International Unit for conductivity is the siemens, which is numerically equivalent to the mhos (Hounslow,

1995). The EC values indicate a general impression of the chemical behavior and chemical quality of the groundwater in an area and are linked to the quantity of salts 74

RF MKT 8.5

36°N 8.3

8.1

7.9

7.7 MMT

7.5 34°N MCT 7.3 MBT 7.1

SRT 6.9

32°N 71°E 73°E

Figure 4.5: Distribution of pH values in the study area. Fault representations are as identified in Figures 1.3 and 4.1. 75

dissolved in the groundwater (Bundschuh, 1992). A usual rule for drinkable water is 10

mhos or 1000 micro Siemens per cm (µS/cm). Figure 4.6 shows the distribution of EC

values in the study area. The EC values range from 150 to more than 8000 µS/cm in the

well waters, and from 40 to 1500 µS/cm in the spring waters with the exception of one

sample (S2) which shows an EC value of 3000 µS/cm. The highest values of EC are

clustered around two centers in the Kohat-Potwar basin (Figure 4.6). Groundwater in the vicinity of these centers is salty in taste and may cause longterm health problems.

Generally, the distribution of EC values corresponds to the depth of groundwater levels;

that is, the shallower the groundwater, the higher the conductivity (Bundschuh and Balke,

1991). No such correlation was observed in the groundwater of the studied area,

however. The use of highly mineralized groundwater for irrigation purposes in some

parts of the area may lead to an increasing salt content of both the soil and groundwater

(Bundschuh and Balke, 1991). Total Dissolved Solids (TDS) is calculated by adding the

mass of ions plus that of SiO2. TDS ranges from 100 to more than 5500 mg/l in the well

waters and from 25 to 1900 mg/l in the spring waters (Figure 4.7). 76

RF MKT

7500 36°N 6750

6000

5250

4500

3750 MMT

3000 34°N MCT 2250

MBT 1500

750

SRT 0

32°N 71°E 73°E

Figure 4.6: Distribution of electrical conductivity (EC) values in the study area (micro S/cm). Fault representations are as identified in Figures 1.3 and 4.1. 77

RF MKT 2700 36°N 2400

2100

1800

1500

MMT 1200

900 34°N MCT 600 MBT 300

0 SRT

32°N 71°E 73°E

Figure 4.7: Total Dissolved Solids (TDS) distribution in the area (mg/L). Fault representations are as identified in Figures 1.3 and 4.1. 78

4.2 Groundwater Classification

Regional abundances of major and trace elements in the groundwater samples are

presented in Tables 4.4-4.6, and the analyses are plotted on Piper (1944) discriminant

diagrams in Figures 4.8-4.10, and Hounslow (1995) (Figures 4.11-4.13). Piper diagrams

are a combination of anion and cation triangles that lie on a common baseline. Adjacent

sides of the two triangles are then 60° apart. Conclusions can be drawn from Piper

diagrams regarding water type, precipitation or solution, mixing, and ion exchange

(Hounslow, 1995). The diamond part of the diagram may be used to characterize

different water types. Most of the spring water is typically characterized by elemental

abundance in the sequence Ca>Mg>(Na+K), with bicarbonate as the dominant anion,

suggesting young and fresh recharge. However, two samples (S2 and S16) exhibit

(Na+K)>Ca>Mg, with sulfate for the dominant anion (Figure 4.8), and both samples also

show anomalous temperatures (Figure 4.4). That is, sample S2 is 6 °C over the mean

annual ground surface temperature and sample S16 is the hot spring of Garam Chashma

showing a surplus of 52°C over the mean annual ground surface temperature. The linear

trend on the Piper diagram for spring water- taken together with high TDS values-

indicate dissolution of Ca2+ and sulfate (Figure 4.8). The linear trend stretches all along the left axis of the plot, indicating mixing of two types of waters.

79

- C l a 2 C + - + 2 +

4 M O g 2 S +

2+ 2- Mg SO4

2+ + + 2- - - Ca Na + K CO3 + HCO3 Cl

Figure 4.8: Piper (1944) diagram for spring water samples. Open and filled squares represent groundwater equilibration with different rock suites.

80

- l C a 2 C + - + 2 +

4 M O g 2 S +

2+ 2- Mg SO4

2+ + + 2- - - Ca Na + K CO + HCO Cl 3 3

Figure 4.9: Piper (1944) diagram for shallow well water samples. 81

- l C a 2 C + - + 2 +

4 M O g 2 S +

2+ 2- Mg SO4

2+ + + 2- - - Ca Na + K CO + HCO Cl 3 3

Figure 4.10: Piper (1944) diagram for deep well water samples. Open and filled circles represent groundwater equilibration with different rock suites.

82

1 Oil-field Brines W17 W1 W15 ] 4 O [S

]+ Evaporites

a 0.5 C [ / ] a

[C Sea water

Alkali lakes 0 00.51 [Na]/[Na]+[Cl]

Figure 4.11: Hounslow (1995) brine differentiation plot, superimposed by data points for deep well water samples. 83

1 Oil-field Brines

D16 ] 4 O [S

]+ Evaporites

a 0.5 C [ / ] a

[C Sea water

Alkali Lakes 0 00.51 [Na]/[Na]+[Cl]

Figure 4.12: Hounslow (1995) brine differentiation plot superimposed by data points for shallow well water samples. Sample D16 lies along a major fault zone. 84

1 Oil-field Brines ] 4 O [S

]+ Evaporites

a 0.5 C [ / ] a S2 [C Sea water S16

Alkali Lakes 0 00.51 [Na]/[Na]+[Cl]

Figure 4.13: Hounslow (1995) brine differentiation plot superimposed by data points for spring water samples. Samples S2 and S16 show a very high surplus over the mean annual temperature (∆T). 85

Most of the samples from shallow-dug wells tend toward Ca-bicarbonatic, with a

few exceptions (Figure 4.9). A large group of samples from deep wells is also dominated

by (Na+K)>Ca>Mg, with sulfate occurring as the dominant anion (Figure 4.10). The

trends for both the shallow and deep water samples exhibit ion exchange in which

calcium and magnesium in solution are being replaced by sodium. The trends start

parallel to constant magnesium and then curve towards the sodium apex, suggesting that

more calcium is being exchanged than magnesium (Hounslow, 1995). Most

significantly, water samples from one shallow well and three deep wells, all located in an

immediate vicinity of the major thrust zones (MBT and MMT), demonstrate clear

imprints of admixture of oil-brines (Figures 4.11 and 4.12). All of these samples also

show a significant surplus temperature over the local mean annual ground surface

temperature (Tables 1-2), and the map of the surplus temperature over the local mean

annual ground surface temperature (Figure 4.4) shows several positive anomalies. One

such anomaly, located along the MKT, is represented by the samples S15-17, S6, S4 and

S7, and another is located along MCT and MBT is represented by the samples W17,

D10-11 and W11-13 (cf. Figures 4.1 and 4.4). All of these samples exhibit temperatures of at least 6oC above the local mean annual temperature (Tables 1-3). Furthermore, all

samples with such significant excess temperature over the local mean annual air

temperature also have anomalously high concentrations of SiO2 (Figure 4.14), whereas those along the MKT are also characterized by anomalously high concentrations of boron and strontium (Figures 4.15-16). 86

RF MKT

48 36° N 44

40

36

32

28

MMT 24

20 34° N MCT 16

12 MBT 8

4

SRT 0

32° N 71° E 73° E

Figure 4.14: Map of SiO2 concentrations (in mg/L). Fault representations are as identified in Figures 1.3 and 4.1 87

RF MKT

1.00 36° N 0.90

0.80

0.70

0.60

0.50 MMT 0.40

34° N MCT 0.30

0.20 MBT 0.10

0.00 SRT

32° N 71° E 73° E

Figure 4.15: Map of boron concentrations (in mg/L). Faults representations are as shown in Figures 1.3 and 4.1. 88

RF MKT

2 36° N 1.8

1.6

1.4

1.2

MMT 1

0.8 34° N MCT 0.6

MBT 0.4

0.2

SRT 0

32° N 71° E 73° E

Figure 4.16: Map of strontium concentrations (in mg/L). Fault representations are as shown in Figures 1.3 and 4.1. 89

4.3 Geothermometry

One of the major tasks in the exploration of geothermal resources is to estimate subsurface temperatures in the reservoir from the geochemical and isotopic compositions of thermal springs. During the last several decades, various geochemical and isotope geothermometers have been developed, which are applicable under different conditions

(e.g., Fournier and Truesdell, 1973; Truesdell and Fournier, 1977; Fournier, 1977;

Fournier and Potter, 1979; Arnorsson, 1983; Fouillac and Michard, 1981; Giggenbach,

1988; Giggenbach and Goguel, 1989; Kharaka and Mariner, 1989). In the present study,

chemical geothermometers (based on silica and cation abundances) were used to

determine the source-reservoir temperatures for water samples from 34 springs (Table

4.6). The silica geothermometry is based on water equilibration with quartz (no steam

loss and maximum steam loss) and chalcedony equilibration. The cation

geothermometers include Na-K, Na-K-Ca, Mg-corrected Na-K-Ca, Mg-Li, and Na-Li

calibrations. All of these geothermometers rely upon several assumptions, including

equilibration with the subsurface environment and no re-equilibration of the water on its

way to the surface environment. It is also assumed that the hot water did not mix with

colder surface water.

The hot spring from Garam Chashma yielded very high concentrations of SiO2, B, and Li, indicating origin from deeper groundwater circulation (Table 4.6). The surface temperature of this hot spring is 67 °C whereas source reservoir temperatures of 128 °C and 84 °C were estimated using the Mg-Li and Mg-corrected Na-K-Ca geothermometers, respectively. Source reservoir temperatures for the groundwater samples were calculated 90

using the Mg-corrected Na-K-Ca and chalcedony geothermometers (Figures 4.17-4.18).

The two independent geothermometers are showing similar results in that the source

reservoir temperatures of groundwater are elevated in the vicinity of the fault zones.

Geochemical data for spring water samples were tested for normality using

skewness, kurtosis, Chi-square, Kolmogorov-Smirnov, and Z-score plot tests. The data

indicate a non-Gaussian distribution and, therefore, the Spearman’s non-parametric R2 values were used on all the plots, omitting data from the Garam Chashma hot spring

(based on personal communication from N. A. Wells). Bivariate plots of chemical constituents (SiO2, B, Sr, Li) show positive correlations with the difference between

spring orifice temperature and the local mean annual air temperature (∆T °C; Figures

4.19-4.22). The most pronounced positive correlation is obtained for SiO2 and Li, indicating that high-temperature water dissolved more of these constituents while circulating in the deeper formations (Figures 4.19, 4.22). Temperatures estimated from both the silica and cation geothermometers are positively correlated with the surface temperature of the spring water (Figures 4.23-25). The trends on all these plots are consistent and geologically significant. The fact that the relationship is not 1:1 (i.e., the trend lines are not at 45 degrees) suggests that a significant dilution by colder water

accompanied the hot water on its way from the “hot reservoir” to the ground surface.

These trends are expected because the high porosity and permeability of the top aquifers

allow mixing of deep and shallow circulation regimes. Thus, the actual reservoir

temperatures may be even higher than the calculated estimates given in Table 4.6. 91

RF MKT

70

36° N 65

60

55

50

45

40

MMT 35 30

25 34° N MCT 20

15 MBT 10

5 SRT 0

32° N 71° E 73° E

Figure 4.17: Source reservoir temperature of groundwater calculated from chalcedony geothermometry. 92

RF MKT

95 36° N

85

75

65

55 MMT 45

34° N MCT 35

MBT 25

15

SRT 5

32° N 71° E 73° E

Figure 4.18: Source reservoir temperature of groundwater calculated from Mg-corrected Na-K-Ca geothermometry. 93

60

50 S 16 40

30

20 y = 0.16x - 0.97 T °C R2 = 0.39 ∆ 10

0

-10

-20 0 102030405060 [SiO ] mg/L 2

Figure 4.19: Relationship between temperature anomaly and silica concentration in spring water. The linear trendline omits value from S16, which is the hot spring from Garam Chashma.

60

50 S16 40

30

20 y = 7.02x + 0.61 T °C 2 ∆ R = 0.21 10

0

-10

-20 0.0 0.2 0.4 0.6 0.8 [B] mg/L

Figure 4.20: Relationship between temperature anomaly and boron concentration in spring water. The linear trendline omits value from S16, which is the hot spring from Garam Chashma. 94

60

S16 40

y = 3.81x - 0.50 C 20 R2 = 0.347 T ° ∆

0

-20 0.0 0.5 1.0 1.5 2.0 [Sr] mg/L

Figure 4.21: Relationship between temperature anomaly and Sr concentration in spring water. The linear trendline omits value from S16, which is the hot spring from Garam Chashma.

60 S16 50 y = 23.78x + 0.40 R2 = 0.24 40

30 C 20 T ° ∆ 10

0

-10

-20 0.0 0.5 1.0 1.5 2.0 2.5 [Li] mg/L

Figure 4.22: Relationship between temperature anomaly and Li concentration in spring water. The linear trendline omits value from S16, which is the hot spring from Garam Chashma. 95

80

70 S16 60

50 y = 0.107x - 1.70

temperature °C 40 R2 = 0.24 ter

a 30

ing w 20

Spr 10

0 0 102030405060708090

TNa-K-Ca-Mg °C

Figure 4.23: Relationship between spring water temperature and cation-predicted temperature. The linear trendline omits value from S16, which is the hot spring from Garam Chashma.

80

70

°C S16 e

r 60 u t a r

e 50 p y = 0.14x + 15.89 m

e 40 R2 = 0.37 r t te 30 wa

ng 20 ri

Sp 10

0 0 1020304050607080 T °C Chalcedony

Figure 4.24: Relationship between spring water temperature and Chalcedony-predicted temperature. The linear trendline omits value from S16, which is the hot spring from Garam Chashma. 96

80

70 C S16 e ° 60 atur 50

mper 40 te

ter y = 0.08x + 15.00 a 30 R2 = 0.01 ng w

i 20 r p S 10

0 0 20406080100120140 T °C Mg-Li

Figure 4.25: Relationship between spring water temperature and Mg-Li-predicted temperature. The linear trendline omits value from S16, which is the hot spring from Garam Chashma.

97

Table 4.1: Physico-chemical characteristics of groundwater samples taken from deep wells. S/cm) °C pH µ (m) screen Latitude Latitude Bottom of Longitude Sample ID EC( TDS (mg/L) General area Temperature Specific area Depth to WT Elevation (m) W1 Kohat Donga Timar Khel 71° 31' 17" 33° 43' 47" 585 40 110 7.34 1210 810 29.5 W2 Kohat 71° 31' 09" 33° 32' 51" 469 37 102 7.46 1015 681 26.6 W3 Kohat 71° 30' 22" 33° 13' 24" 459 39 98 8.25 8280 5527 27.0 W4 Kohat Shakardara 71° 30' 22" 33° 12' 49" 607 41 95 7.75 1150 764 28.0 W5 Potohar Kalabagh 71° 31' 41" 32° 57' 12" 612 29 88 7.67 391 259 21.0 W6 Potohar Mianwali 71° 47' 37" 32° 42' 00" 338 34 110 7.91 2640 1760 28.0 W7 Potohar Chakwal 72° 34' 59" 32° 56' 39" 425 32 105 7.87 938 625 26.0 W8 Potohar Chakwal 73° 00' 38" 32° 46' 00" 425 28 90 8.60 4760 3173 29.0 W9 Potohar Pinddadan Khan 73° 02' 46" 32° 35' 25" 213 29 92 7.94 254 192 28.5 W10 Potohar Khewra 73° 02' 41" 32° 36' 00" 215 32 89 7.96 1736 1158 27.5 W11 Potohar Rawalpindi 72° 55' 58" 33° 38' 01" 558 28 95 7.66 621 413 28.5 W12 Potohar Margalla Hills 72° 49' 48" 33° 41' 58" 549 43 120 7.53 962 641 27.5 W13 Potohar Tarbela 72° 32' 37" 33° 52' 50" 342 33 94 7.70 380 254 29.5 W14 Peshawar Hayatabad 71° 26' 05" 33° 56' 48" 359 47 120 7.59 632 423 29.4 W15 Peshawar Shekhmalkhel 71° 10' 50" 34° 06' 46" 1117 24 79 7.35 680 453 25.3 W16 Peshawar Badrashi 72° 01' 25" 33° 58' 10" 390 36 112 7.48 530 353 26.5 W17 Peshawar Nizam Pur 72° 06' 00" 33° 50' 15" 288 24.5 93 7.47 801 534 27.0 W18 Karak Karak 71° 08' 00" 33° 07' 03" 244 39 115 7.34 1137 753 26.5 W19 Bannu Bannu 70° 36' 08" 33° 01' 05" 253 38 125 7.67 856 571 27.3 W20 Swat Aboha 72° 12' 18" 34° 40' 34" 793 25.6 90 7.47 426 284 25.1 W21 Mardan Jalala 71° 54' 32" 34° 19' 51" 347 34.5 102 7.68 498 333 26.9 98

Table 4.2: Physico-chemical characteristics of groundwater samples taken from shallow wells. °C S/cm) pH µ (m) Latitude Latitude Longitude Sample ID EC( TDS (mg/L) General area Specific area Depth to WT Elevation (m) Temperature D1 Potohar Mianwali 71° 34' 29" 32° 47' 11" 198 16 8.05 896 595 28.0 D2 Potohar Chakwal 72° 17' 02" 32° 55' 09" 445 10 7.74 1495 997 29.0 D3 Swabi Hemlet 72° 37' 58" 34° 03' 57" 337 11 7.63 431 441 28.0 D4 Swabi Shahmansur 72° 27' 22" 34° 04' 45" 327 9 7.92 328 218 28.5 D5 Swabi Dobian 72° 13' 29" 34° 08' 58" 317 3 7.69 297 198 27.5 D6 Chitral Mastuj 72° 30' 47" 36° 16' 40" 2412 12 7.13 665 445 14.2 D7 Peshawar Warsak 71° 26' 22" 34° 07' 37" 333 3 7.48 885 601 21.6 D8 Peshawar Taru Jabba 71° 43' 33" 34° 00' 54" 302 9 7.62 1061 709 23.0 D9 Peshawar Kund 72° 13' 38" 33° 56' 07" 283 10.2 7.27 892 595 28.6 D10 Peshawar Hisartang 72° 10' 10" 33° 50' 48" 425 3 7.41 504 335 26.0 D11 Peshawar Nizam Pur 72° 06' 00" 33° 50' 15" 288 10 8.08 151 101 27.5 D12 Peshawar Charsadda 71° 43' 06" 34° 09' 07" 294 20 7.38 561 374 28.4 D13 Peshawar Charsadda 71° 45' 03" 34° 12' 56" 308 21 7.99 463 308 28.6 D14 Swat Chakdara 72° 35' 03" 34° 01' 56" 540 2.3 7.66 522 345 26.9 D15 Swat Chakdara 72° 35' 07" 34° 02' 16" 545 3.1 7.45 408 272 27.3 D16 Swat Qambar 72° 19' 08" 34° 45' 38" 902 17.4 7.27 1148 765 26.2

99

Table 4.3: Physico-chemical characteristics of groundwater samples taken from springs.

S/cm) °C pH µ Latitude Latitude Longitude Sample ID EC( TDS (mg/L) General area Temperature Specific area Elevation (m) S1 Kohat Main Bazar 71° 26' 23" 33° 35' 33" 490 7.41 718 482 22.6 S2 Potohar Pinddadan Khan 72° 58' 56" 32° 47' 09" 529 7.36 2940 1953 30.5 S3 Chitral Greenlusht 72° 04' 50" 36° 08' 18" 1991 8.70 350 230 19.6 S4 Chitral Shah Der 72° 05' 51" 36° 08' 58" 1958 8.15 479 270 20.7 S5 Chitral Reshun 72° 05' 53" 36° 08' 56" 1955 7.45 1184 793 15.2 S6 Chitral Awi Lasht 72° 13' 37" 36° 16' 35" 2083 7.62 625 420 21.0 S7 Chitral Parwak Center 72° 24' 05" 36° 17' 00" 2286 8.51 1520 1030 26.2 S8 Chitral Sarghuz 72° 27' 19" 36° 16' 29" 2320 7.39 98 65 7.9 S9 Chitral Mastuj 72° 30' 57" 36° 16' 45" 2410 7.40 936 621 14.4 S10 Chitral Parwak Bala 72° 25' 13" 36° 16' 28" 2237 7.80 907 610 14.5 S11 Chitral Snowghar 72° 24' 28" 36° 16' 05" 2351 7.90 97 65 7.8 S12 Chitral Sirangdoori 72° 05' 58" 36° 09' 37" 1849 7.16 623 417 13.6 S13 Chitral Golain 71° 57' 00" 35° 57' 32" 1861 8.03 430 286 15.6 S14 Chitral Ragh 71° 52' 42" 35° 55' 53" 1881 8.10 242 160 13.8 S15 Chitral Mough 71° 40' 15" 36° 00' 39" 1974 7.90 57 38 9.9 S16 Chitral Garam Chishma 71° 33' 36" 35° 59' 43" 2257 7.30 885 600 67.5 S17 Chitral Shoghor 71° 45' 58" 36° 01' 32" 1901 7.72 436 292 12.5 S18 Chitral Shasha 71° 47' 34" 37° 00' 07" 1704 7.01 639 426 17.5 S19 Chitral Bamboret (Pehlawandeh) 71° 42' 21" 35° 42' 49" 1900 7.45 357 240 13.4 S20 Chitral Bamboret (Brun) 71° 41' 28" 35° 42' 00" 1950 7.54 405 271 13.4 S21 Chitral Daneen 71° 47' 36" 35° 51' 06" 1567 8.18 182 121 13.7 100

Table 4.3: Physico-chemical characteristics of groundwater samples taken from springs (continued).

S/cm) °C pH µ Latitude Latitude Longitude Sample ID EC( TDS (mg/L) General area Temperature Specific area Elevation (m) S22 Peshawar Ali masjid 71° 15' 10" 34° 02' 38" 655 7.25 527 351 27.0 S23 Peshawar Haidari Kandao 71° 12' 13" 34° 07' 09" 1113 7.59 1475 982 25.0 S24 Peshawar Hisartang 72° 10' 10" 33° 50' 48" 425 7.78 467 311 21.2 S25 Swat Malakand 71° 53' 59" 34° 33' 03" 637 7.58 559 372 22.0 S26 Swat Fizagat 72° 23' 19" 34° 47' 31" 944 8.06 382 255 19.4 S27 Swat Ghwara Masti 72° 24' 00" 34° 47' 42" 964 7.34 584 389 20.1 S28 Swat Gul Maira 72° 27' 33" 34° 48' 57" 1003 7.35 402 266 18.9 S29 Swat Khamba 72° 32' 18" 34° 50' 21" 1433 7.25 457 303 21.3 S30 Swat Malam Jabba 72° 34' 28" 34° 57' 36" 2472 7.46 41 27 20.2 S31 Swat Landal 72° 26' 39" 34° 54' 45" 1265 7.82 396 264 20.4 S32 Swat Tangi (Madyan Rd) 72° 28' 08" 35° 00' 44" 1234 6.74 182 124 16.9 S33 Swat Pya Khwar (Madyan Rd) 72° 30' 50" 35° 06' 33" 1329 7.16 227 152 16.5 S34 Swat Behrain 72° 33' 01" 35° 12' 34" 1420 8.13 40 27 17.4

101

Table 4.4: Hydrochemical data for groundwater samples from drilled wells (concentrations in mg/L).

Sample TNaCaK TChaledony TMg-Li ∆T ID Ca Mg Na K Cl NO3 SO4 HCO3 SiO2 Sr B Li °C °C °C °C W1 127.8 42.5 54.4 3.3 147.1 168.5 148.6 198.3 21.3 1.355 0.471 0.02 25 34 33 6.3 W2 92.7 47.7 83.2 5.1 51.9 39.9 299.4 331.1 19.2 1.348 0.361 0.11 44 30 38 3.4 W3 59.4 115.4 1934.7 34.2 1168.9 463.6 1760.7 1855.9 26.2 0.412 0.131 0.02 45 42 48 3.8 W4 38.4 49.5 170.9 10.8 35.2 14.5 202.0 580.9 24.4 0.986 0.200 0.03 55 40 38 4.8 W5 45.0 17.1 18.7 9.6 12.5 4.9 66.5 181.3 12.3 0.626 0.054 0.02 38 14 46 5.1 W6 75.7 71.3 375.4 12.8 422.4 30.0 578.8 343.5 18.3 1.973 0.993 0.11 96 44 47 5.7 W7 23.7 38.2 137.6 4.8 52.8 85.7 78.6 395.3 27.5 0.131 0.130 0.03 41 24 39 3.1 W8 6.9 5.1 1162.9 19.4 738.9 123.5 1020.5 1025.5 10.1 0.254 0.862 0.07 31 7 71 6.1 W9 32.3 10.4 63.7 8.5 11.9 6.1 57.9 165.1 11.8 0.288 0.442 0.01 31 12 40 3.9 W10 71.7 68.1 187.5 13.1 270.7 71.9 202.0 373.9 22.2 0.908 0.553 0.05 81 21 39 2.9 W11 43.7 15.5 30.4 2.2 21.6 22.6 31.4 196.9 19.9 0.409 0.442 0.01 48 31 40 6.9 W12 78.0 42.3 63.5 6.4 71.9 119.8 73.0 335.4 24.5 0.113 0.333 0.13 67 40 35 5.9 W13 41.4 11.8 20.2 2.7 6.6 27.4 11.6 210.0 32.1 0.156 0.322 0.01 61 51 34 6.6 W14 57.6 27.1 37.6 4.8 48.6 36.0 85.0 225.1 17.1 0.804 0.000 0.03 39 26 44 7.3 W15 65.9 21.3 40.8 2.4 72.4 97.4 63.3 161.9 16.9 0.611 0.000 0.01 35 25 34 6.2 W16 38.1 16.2 56.3 4.3 14.2 16.0 32.3 285.4 25.8 0.446 0.000 0.02 53 42 45 4.4 W17 106.6 19.2 33.7 3.3 62.3 114.0 81.6 163.2 32.5 0.809 0.000 0.04 69 52 50 7.6 W18 75.8 51.8 84.8 3.3 111.2 36.1 228.7 280.3 23.7 1.880 0.060 0.10 47 38 35 4.8 W19 68.2 53.6 32.7 7.6 16.5 12.9 187.5 338.5 18.0 1.351 0.000 0.03 49 27 37 4.9 W20 66.9 7.7 11.5 4.4 5.5 12.7 44.7 221.3 18.0 0.301 0.000 0.01 55 40 39 6 W21 23.1 15.5 71.5 3.4 19.1 10.0 113.6 201.6 15.3 0.225 0.000 0.01 48 21 37 5.7

TNaCaK °C: Source reservoir temperature determined by the cation geothermometer (Mg-corrected NaCaK) TChaledony °C: Source reservoir temperature determined by the chalcedony geothermometer TMg-Li °C: Source reservoir temperature determined by the Mg-Li geothermometer ∆T °C: Difference between water surface temperature and mean annual air temperature

102

Table 4.5: Hydrochemical data for groundwater samples from dug wells (concentrations in mg/L). Sample T T T ∆T ID NaCaK Chaledony Mg-Li Ca Mg Na K Cl NO3 SO4 HCO3 SiO2 Sr B Li °C °C °C °C D1 45.0 33.0 124.8 11.1 70.0 3.1 395.8 140.6 15.1 0.988 0.224 0.02 32 37 21 3.4 D2 74.0 89.7 89.1 13.7 205.2 110.9 295.6 261.8 21.6 0.421 0.066 0.03 55 33 35 6.1 D3 79.6 24.3 25.7 4.2 25.9 53.4 121.3 195.6 22.8 0.327 0.030 0.01 33 38 37 5.1 D4 29.0 11.9 26.4 4.8 8.5 14.3 13.8 183.0 24.0 0.266 0.000 0.01 54 41 39 5.7 D5 18.3 10.3 27.6 5.7 11.2 10.2 15.2 152.3 20.2 0.258 0.000 0.01 47 41 32 4.7 D6 79.3 21.4 8.0 4.7 2.3 3.5 155.1 167.0 14.0 0.477 0.000 0.04 26 50 18 1.7 D7 86.8 52.7 54.5 11.1 66.0 6.0 253.0 261.9 18.1 0.602 0.000 0.05 55 43 28 1.2 D8 57.2 63.5 110.6 13.8 25.9 6.7 429.2 360.6 19.5 1.298 0.146 0.04 47 37 31 1.3 D9 87.6 31.7 50.4 5.0 29.8 49.7 138.3 309.6 24.9 0.779 0.000 0.05 61 48 40 5.8 D10 54.0 23.7 20.6 2.5 15.1 17.9 87.4 202.9 17.5 0.343 0.000 0.02 44 40 36 6.6 D11 23.6 3.4 6.3 3.2 5.5 4.3 38.4 56.1 3.8 0.116 0.000 0.01 34 52 12 8.1 D12 63.1 15.3 19.6 3.6 23.5 4.6 42.0 221.9 21.3 0.291 0.000 0.00 41 30 34 5.5 D13 14.8 21.6 55.0 5.4 9.6 9.2 29.8 283.4 15.3 0.414 0.000 0.01 51 30 21 5.7 D14 81.6 10.3 9.3 2.4 11.1 8.2 11.1 225.3 21.7 0.323 0.000 0.00 29 33 35 6.4 D15 67.9 10.9 4.3 2.1 4.6 5.0 33.3 208.4 12.8 0.226 0.000 0.00 5 34 15 6.8 D16 139.3 26.7 35.5 2.5 101.8 104.4 110.7 238.7 20.9 0.805 0.000 0.01 41 32 33 6.6

TNaCaK °C: Source reservoir temperature determined by the cation geothermometer (Mg-corrected NaCaK) TChaledony °C: Source reservoir temperature determined by the chalcedony geothermometer TMg-Li °C: Source reservoir temperature determined by the Mg-Li geothermometer ∆T °C: Difference between water surface temperature and mean annual air temperature 103

Table 4.6: Hydrochemical data for spring water samples (concentrations in mg/L).

Sample T T T ∆T ID NaCaK Chaledony Mg-Li Ca Mg Na K Cl NO3 SO4 HCO3 SiO2 Sr B Li °C °C °C °C S1 71.0 32.4 36.5 5.6 25.9 15.3 182.1 218.7 14.0 0.84 0.15 0.18 45 18 41 1.4 S2 138.1 95.8 439.3 5.2 342.4 79.7 972.0 353.1 18.1 1.92 0.39 0.17 53 28 39 5.9 S3 26.1 34.3 9.5 2.2 0.5 5.3 49.4 218.4 11.3 0.15 0.00 0.04 27 11 43 4.1 S4 39.1 58.4 22.5 3.6 1.3 6.3 183.3 271.4 12.2 1.05 0.46 0.06 56 13 44 5.2 S5 195.9 95.8 14.6 3.9 1.5 2.4 798.9 96.5 12.5 0.22 0.00 0.08 19 14 41 -0.3 S6 100.2 56.4 29.1 11.7 1.2 4.5 475.6 107.5 14.7 1.99 0.12 0.07 50 20 45 5.5 S7 147.5 147.4 86.9 10.9 7.5 3.9 971.6 275.7 20.6 2.00 0.45 0.16 58 33 43 10.7 S8 22.5 4.6 3.5 1.5 0.1 1.7 54.9 28.3 1.9 0.11 0.00 0.00 12 6 39 -7.6 S9 125.1 47.7 29.3 7.4 11.6 4.0 429.7 194.0 15.6 0.80 0.12 0.13 40 22 53 0.6 S10 93.1 81.4 29.1 9.5 0.7 6.7 425.0 307.5 10.5 1.04 0.00 0.05 52 8 38 0.7 S11 20.4 4.3 3.6 2.0 0.2 1.8 71.4 15.9 4.9 0.10 0.00 0.00 21 5 44 -7.7 S12 68.0 25.7 7.8 2.5 2.8 8.7 129.8 164.3 10.9 0.17 0.00 0.03 14 10 45 0.2 S13 38.6 9.0 44.9 4.6 47.7 3.3 116.0 80.2 8.9 0.27 0.00 0.03 52 3 54 0.1 S14 49.5 5.4 4.3 1.4 2.7 3.3 97.7 77.0 12.0 0.06 0.00 0.00 1 13 36 0 S15 11.6 1.2 3.1 1.2 0.5 2.6 12.9 29.0 5.0 0.04 0.00 0.00 18 4 51 -5.6 S16 39.4 2.1 170.9 8.5 25.1 3.5 366.1 128.3 53.5 0.53 0.69 1.94 84 75 128 52 S17 51.2 29.9 7.3 2.4 0.9 6.5 122.2 182.6 8.3 0.21 0.00 0.04 17 1 47 0.3 S18 66.7 20.6 20.2 5.2 25.7 5.2 102.9 164.7 8.9 0.32 0.49 0.21 39 3 67 2 S19 50.8 15.9 5.5 2.6 1.9 9.1 22.6 196.7 8.8 0.20 0.00 0.01 16 2 36 0.4 S20 54.6 26.7 5.2 2.6 1.9 7.6 64.5 200.8 7.9 0.25 0.00 0.01 15 3 35 0.3 S21 29.2 7.1 9.0 3.5 0.4 5.4 23.7 127.9 10.6 0.14 0.00 0.01 35 9 43 0.5 S22 59.3 23.5 15.8 1.8 17.3 36.2 74.1 219.4 15.7 0.44 0.00 0.01 3 22 30 7.7 S23 266.7 55.0 58.4 11.5 12.4 4.8 962.0 145.8 29.3 1.90 0.00 0.03 45 47 36 5.7 S24 52.0 18.6 26.4 2.3 6.8 12.5 114.9 184.7 18.6 0.23 0.00 0.02 26 29 42 1.9 S25 95.4 29.1 14.8 3.4 8.5 7.8 252.1 178.3 20.9 0.73 0.00 0.02 20 33 40 2 S26 56.8 15.6 6.6 1.3 3.7 4.2 29.1 195.9 9.1 0.58 0.39 0.01 32 4 39 0.5 S27 82.5 15.8 13.7 4.7 18.3 52.6 56.1 208.3 49.6 0.33 0.44 0.02 41 72 46 1.2 S28 55.6 12.4 8.6 2.7 10.1 14.4 27.9 211.8 15.3 0.11 0.00 0.01 20 21 35 0.7 104

Table 4.6: Hydrochemical data for spring water samples (concentrations in mg/L) (Continued).

S29 72.6 3.1 4.5 0.5 6.2 11.2 5.4 156.6 18.3 0.18 0.44 0.05 26 28 48 3.7 S30 6.1 0.3 4.1 1.0 1.4 7.4 4.2 4.4 8.8 0.04 0.00 0.00 33 3 70 2.8 S31 42.2 24.5 6.9 1.1 3.1 16.7 9.5 249.5 31.8 0.25 0.00 0.00 21 51 23 2.6 S32 27.8 6.1 6.2 1.4 6.6 4.8 13.0 89.1 23.3 0.13 0.55 0.00 21 38 36 1.1 S33 30.4 9.8 7.8 2.2 6.3 17.3 12.5 113.3 24.5 0.14 0.00 0.00 23 40 31 1 S34 10.2 0.9 2.9 1.4 3.3 4.0 4.6 292.3 4.5 0.10 0.00 0.00 27 3 62 0.6

TNaCaK °C: Source reservoir temperature determined by the cation geothermometer (Mg-corrected NaCaK) TChaledony °C: Source reservoir temperature determined by the chalcedony geothermometer TMg-Li °C: Source reservoir temperature determined by the Mg-Li geothermometer ∆T °C: Difference between water surface temperature and mean annual air temperature

CHAPTER 5

NUMERICAL SIMULATIONS

The regional groundwater flow in the study area was numerically simulated using

Department of Defense commercial software “Groundwater Modeling System (GMS)”.

Peshawar Basin and its surroundings are experiencing a very high compressive stress which is affecting the regional groundwater flow and is leading to abnormal pressure heads. Traditionally, fluid flow and deformation have been modeled using generic codes and, therefore, this study is considered to be the first attempt to model fluid flow and deformation using a commercial software.

5.1 Groundwater flow in basins under compressive regimes

Basins under compressive regimes exhibit complex groundwater flow patterns

that are controlled by the tectonic evolution of the basin and involve active thrust sheets

and strong lateral deformation. With respect to its hydrodynamic evolution, a compressive basin can be separated into a more or less stationary part that does not undergo geometrical changes apart from sedimentation and/or erosion, and another part, which in itself is either part of, or is loaded by the weight of the advancing thrust sheets.

The load of thrust sheets involves compaction fluid flow from underlying strata and is generally directed toward the foreland (Bitzer et al., 1996). As such, fluid flow

105 106

associated with compression of foreland basins potentially influences patterns of

petroleum migration and formation of sediment-hosted ore deposits (Ge and Garven,

1989). Deep groundwater flow can be driven by several mechanisms in sedimentary

basins. In the case of evolving foreland basins, large-scale compression and thrusting

potentially causes abnormally high pressures in the foreland sag that may initiate

transient fluid flow (Ge and Garven, 1992). Groundwater flow systems also evolve continuously during the development of a sedimentary basin. That is, transient hydraulic and thermal states can develop in response to spatio-temporal changes in climate, thermal conditions, landscape erosion, sediment compaction, continental uplift, tectonic stress and ongoing diagenesis.

Accretionary wedges and continental margins are compressed by large horizontal forces, which originate from collisional plate tectonics during the early stages of foreland basin formation. Continued compression and collision eventually produce thrust and fold belts that form mountain ranges adjacent to the margin and cause the crustal basement to further subside (Davis et al., 1983). Erosional unloading of the fold and thrust belts will cause uplift of the foreland platform to reestablish isostatic balance. Additional compression, advancing of thrust sheets, and sediment compaction provide new triggers and locations for further sedimentation, and these processes may be repeated as the basin is subjected to successive episodes of compression in subsequent events over a time period of tens of millions of years. In addition to setting up both stress-induced and topographically-driven fluid migration systems, compression of the foreland also results in the development of the fracture networks that propagate along planes normal to the 107

least principal stress, which serve to increase the regional permeability of basin strata

(Bell and Babcock, 1986).

In summary, it has become increasingly evident that large-scale groundwater flow

systems are dynamically coupled to the tectonic evolution of the crust (Oliver, 1986;

Bethke and Marshak, 1990). Finally, to expand upon a point introduced above,

understanding the transient history of subsurface flow in a deforming foreland basin is

fundamentally important for elucidating the role of deep groundwater in tectonic and

related processes such as overthrusting, diagenesis, hydrothermal ore genesis, petroleum

migration, and metasomatism (Bredehoeft and Norton, 1990).

5.2 Abnormal fluid pressures

Abnormal pressures may occur as over- or under-pressures, both of which

represent departures from normal hydrostatic conditions for a given depth. These

occurrences are natural phenomena for topography-driven, osmotic, and density-driven

flow systems. Several factors contribute to the origin and preservation of abnormal

pressure, including disequilibrium compaction (vertical loading stress), tectonic forces

(lateral compressive stress), aquathermal expansion, dehydration reactions, hydrocarbon

generation, osmosis, and buoyancy due to density contrasts (Swarbrick and Osborne,

1998). Indeed, compaction and deformation are probably the most important factors with respect to over-pressure development (McPherson and Garven, 1999). On a geologic time scale, an under-pressured formation may become normally- or over-pressured because of transient flow induced by vertical geologic movements (Jiao and Zheng, 108

1998). Overpressure may be defined as pore fluid pressure that significantly exceeds

hydrostatic pressure. This condition may arise because the pore fluids largely bear the

weight of the overburden. Environments with low permeability and conditions that

reduce available pore space or increase fluid volumes are necessary for the generation of

overpressures (McPherson and Garven, 1999). Overpressures develop in the thrusted

sediments, and a decrease of overpressure can often be observed with increasing distance

from a thrust front (e.g., Canadian Rocky Mountains and Arkoma Basin). Neuzil (1995)

summarized two distinct conceptual approaches to abnormal pressures, namely the static and hydrodynamic phenomena. Bradley (1975) and Powley (1990) described abnormal pressure regimes as static, which occur where the subsurface is compartmentalized by impermeable barriers to fluid flow. The hydrodynamic phenomenon (Bredehoeft and

Hanshaw, 1968; Toth and Miller, 1983; Bethke and Corbet, 1988) characterized abnormal pressures as generally dynamic, representing a balance between ongoing geologic processes that perturb the pressure and fluid fluxes that tend to dissipate the perturbations. McPherson and Garven (1999) concluded that tectonic compression is the likely cause for overpressure mechanism in the Sacramento Basin.

5.3 Groundwater Modeling System

The Department of Defense Groundwater Modeling System (GMS) provides a

comprehensive graphical environment for groundwater modeling, including tools for site

characterization, model conceptualization, mesh and grid generation, and geostatistics, as well as sophisticated tools for graphical visualization of the modeled phenomena. 109

Several types of numerical codes are supported by GMS. The current version of GMS

provides a complete interface for the codes MODFLOW (grid based flow model), MT3D

(a contaminant transport model), MODPATH (a particle tracking code), SEAM3D (a

reactive transport model), SEEP2D (a code for cross-sectional flow), UTCHEM

(surfactant enhanced flushing code), and FEMWATER (a finite element flow and

transport model).

GMS includes a graphical interface to the groundwater flow model, included as

part of FEMWATER. FEMWATER is a three-dimensional finite-element computer program for modeling density-dependent groundwater flow and transport in variably-

saturated media. FEMWATER represents a combination of two older models,

3DFEMWATER (flow) (Yeh, 1987b) and 3DLEWASTE (transport) (Yeh, 1990), which

provides a single, powerful model for coupled flow and transport. The improvements

embodied in the combined FEMWATER code are numerous. First, the entire program

structure was changed to allow its integration into the Department of Defense

Groundwater Modeling System (GMS), which contains a state-of-the-art graphical user

environment that allows efficient model setup and visualization (Engineering Computer

Graphics Laboratory; ECGL, 1996). Second, the flow and transport algorithms in

FEMWATER can be coupled to simulate density dependent problems such as salinity

intrusion. Third, the finite-element algorithm used by FEMWATER permits actual

boundaries, wells, and stratigraphic units to be modeled precisely, without relying upon

regularly spaced nodes to approximate them and their characteristics. Fourth, because

FEMWATER simulates flow in the unsaturated zone, the entire aquifer is modeled and 110

sources and sinks can be directly represented in the mesh and boundary conditions, unlike

the conductance approach in MODFLOW, which requires external sources and sinks.

The disadvantages of FEMWATER are that it is memory intensive, its solutions can be

time-consuming, and model convergence is more difficult. However, these limitations

have not proven to be an impediment in hydrodynamic modeling of the Peshawar Basin

and its environs.

5.4 Formulation of FEMWATER

FEMWATER is designed to solve the following system of governing equations

which, combined with user-specified initial and boundary conditions, describe flow and

transport through saturated-unsaturated porous media. The governing equation for flow

is essentially the modified Richards equation (Eq. 1) (Yeh, 1992). Derivation of the

Richards equation is given in Appendix A.

and

where

F = storage coefficient (dimensionless) 111

h = pressure head (L)

t = time (T)

2 K = hydraulic conductivity tensor (L /T) z = potential head (L)

3 3 q = source and/or sink [(L /T)/L ]

3 ρ = water density at chemical concentration C (M/L )

3 ρo = referenced water density at zero chemical concentration (M/L )

3 ρ* = density of either the injection fluid or the withdrawn water (M/L )

θ = moisture content (dimensionless)

2 α′ = modified compressibility of the medium (M /kg)

2 β′ = modified compressibility of the water (M /kg))

3 3 n = porosity of the medium (L /L )

S = degree of saturation (dimensionless)

The hydraulic conductivity K is given by:

where

µ = dynamic viscosity of water at chemical concentration C (M/LT)

µo = referenced dynamic viscosity at zero chemical concentration (M/LT) 112

2 k = permeability tensor (L )

2 ks = saturated permeability tensor (L )

2 kr = relative permeability or relative hydraulic conductivity (L )

2 Kso = referenced saturated hydraulic conductivity tensor (L /T)

The referenced value is usually taken at zero chemical concentration. The density and dynamic viscosity of water are functions of chemical concentration and are assumed to take the following respective form:

and

3 where C is the chemical concentration (M/L ) and a1, a2, ..., a7, a8 are the parameters

3 (L /M) that are used to describe the concentration dependence of water density and dynamic viscosity. The Darcy velocity is calculated as follows:

113

The initial conditions for the flow equation are given by the following Equation:

where R is the region of interest and hi is the prescribed initial condition for hydraulic

head, which can be obtained by either field measurements or by solving the steady state

version of Equation (1). In this study, the initial conditions were obtained by field

measurements and final head distribution was numerically simulated.

5.5 Boundary conditions

The specification of boundary conditions is probably the most critical and complex task in groundwater flow modeling. As explained by Yeh (1987b), the boundary conditions of the region of interest can be examined from a dynamic, physical, or mathematical point of view. From a dynamic standpoint, a boundary segment can be considered either as impermeable or flow-through. On the other hand, from a physical point of view, such a segment could be classified as a soil-soil interface, soil-air interface, or soil-water interface. Lastly, from a mathematical point of view, the boundary segment can be classified as one of four types of boundary conditions, namely as (a) Dirichlet, (b) gradient flux, (c) flux, or (d) variable boundary conditions.

The Dirichlet boundary condition is usually applied to soil-water interfaces, such as streams, artificial impoundments, and coastal lines, and involves prescribing the functional value on the boundary. The gradient-flux boundary condition, on the other hand, involves prescribing the gradient of the function on the boundary and does not 114

occur very often in real-world problems. This condition, however, can be encountered at the base of the media where natural drainage occurs. The third type of boundary condition, the flux boundary condition, involves prescribing the total normal flux due to the gradient on the boundary. Usually surface water bodies with known infiltration rates through the bottom layers of their sediments or liners into the subsurface media are assigned this boundary condition. If a soil-air interface exists in the region of interest, a variable boundary condition is employed. In such a case, either Dirichlet or flux boundary conditions dominate, mainly depending on the potential evaporation, the conductivity of the media, and the availability of water such as rainfall (Yeh 1987a).

From this discussion, four types of boundary conditions can be specified for the flow equations depending on the physical location of the boundaries:

a. Dirichlet boundary conditions:

(8)

b. Gradient flux boundary conditions:

(9)

115

c. Flux boundary conditions:

(10)

d. Variable boundary conditions - during precipitation period:

(11)

or

(12)

e. Variable boundary conditions - during non-precipitation period:

(13)

or

(14)

or

(15)

116

f. River boundary conditions:

(16)

where

n = outward unit vector normal to the boundary

(xb, yb, zb) = spatial coordinate on the boundary

hd = Dirichlet functional value

qh = Gradient flux value

qc = Flux value

Bd = Dirichlet boundary

Bn = Gradient flux boundary

Bc = Flux boundary

Bv = variable boundary

hp = ponding depth on the variable boundary

qp = throughfall of precipitation on the variable boundary 117

hm = minimum pressure on the variable boundary

qe = evaporation rate (potential evaporation) on the variable boundary

KR = hydraulic conductivity of the river bottom sediment layer

bR = thickness of the river bottom sediment layer

hR = depth of the river bottom measured from the river surface.

Only one of the above equations (13)-(16) is utilized at any point on the variable boundary at any time. Boundary conditions for the present research have been specified in section 5.8.

5.6 GMS Modeling Approach

GMS can be used to construct complex FEMWATER models. The conceptual

model approach can be used to simplify mesh generation and parameter/boundary condition assignment. A suite of powerful 3D visualization tools are available for post- processing FEMWATER models including animations, cross-sections, and iso-surface plots. Two basic approaches are provided in GMS for constructing a FEMWATER model: either the model can be completely defined using the tools in the 3D Mesh module (the direct approach), or the model can be defined with the aid of the feature 118

object tools in the Map module (the conceptual model approach). The later approach has been adopted for constructing the simulation model for this study.

5.6.1 The Conceptual Model Approach

The preferred method for setting up a FEMWATER simulation is to use the feature object tools in the Map module to define a FEMWATER conceptual model of a site being studied. The conceptual model is a high-level description of the site including sources/sinks, the boundary of the domain to be modeled, rainfall and seepage zones, and material zones within each of the layers. The conceptual model is defined with feature objects, including points, arcs, and polygons, and is constructed independently of a numerical grid. Once the conceptual model is complete, a mesh is automatically constructed to fit the conceptual model, and the FEMWATER data are converted from the conceptual model to the nodes, elements, and element faces. The dialogs and interactive editing tools in the FEMWATER menu can then be used to edit or review the data if desired. The first step in performing a FEMWATER simulation is to create a 3D finite element mesh. The volumetric domain to be modeled by FEMWATER is idealized and discretized into hexahedra, prisms, tetrahedra, and/or pyramids. Elements are grouped into zones representing hydrostratigraphic units. Each element is assigned a material ID representing the zone to which the element belongs. The FEMWATER conceptual model can be used to automatically build a 2D mesh that matches the model boundaries and is refined around wells. This mesh is then extruded into a 3-D mesh.

119

5.6.2 Initial Conditions

Initial conditions define the initial status of the pressure head and concentration.

Three types of initial conditions are possible for a FEMWATER simulation: cold starts,

hot starts, and flow solutions. Cold starts are used to establish a set of initial values at the beginning of a steady state or transient simulation. Hot starts are used to continue a previous run of FEMWATER without having to start over from the beginning. Flow

solutions are used to define the flow field that is necessary when performing a transport

only simulation (as opposed to coupled flow and transport). Initial conditions are defined using the “Initial Conditions” dialog. Two options are available for designating a pressure head cold start initial condition. One option is to enter a constant value into the field labeled “Total head.” This essentially defines an initial condition corresponding to a

flat water table. FEMWATER reads this value and internally generates an array of

pressure heads by subtracting the nodal elevations from the given total head value. The

“Read from data set file” option can be used to designate that the pressure head varies spatially and that the values will be read from a data set file. The data set file was generated using the interpolation options and then saved using the “Export Data Set”

command. The pressure head initial condition is computed by subtracting the node

elevations from the total heads. The pressure head data set was saved to a GMS data set

file, whereupon the path to the file is automatically written to the IC pressure head field

at the bottom of the “Initial Conditions” dialog. The pressure head cold start can have a

significant influence on the speed of convergence. In some cases, a poorly defined initial

condition may even prevent convergence. Hot starts are used to begin a new simulation 120

starting at a given time step of a solution computed from a previous transient simulation.

FEMWATER reads the specified hot start file and finds the time step corresponding to the specified time. The solution then begins using the data set at that time as the initial condition. When the “Hot start” option is chosen, the names of the files used for the hot start are entered in the fields at the bottom of the “Initial Conditions” dialog.

5.6.3 Time Control Parameters

The “Time Control” dialog is used to enter the data used by FEMWATER to compute the computational time intervals. It is also used to define the reference time.

There are two methods for defining the computational time steps: “Constant” time step and “Variable” time step. With the “Constant” time step method, the first time step is assumed to begin at time 0.0. A constant interval time is entered along with a maximum simulation time. The “Variable” time step option permits variable intervals between time steps. The options at the bottom of the “Time Control” dialog are used to enter the reference time for the FEMWATER simulation. The reference time is the date/time corresponding to the beginning of the simulation (t=0). If a reference time is entered and the “Date/Time” option is selected in the “Time display” section, all time values entered for transient input data (i.e., time series defined in the XY Series Editor) can be entered in a date/time format rather than a scalar time format. Also, when post-processing, the values shown in the time step selector in the “Data Browser” or at the top of the GMS

Window are displayed in the date/time format. Furthermore, any time series curves entered as part of the FEMWATER conceptual model in the Map module that were 121

defined using the date/time format will be automatically converted to the proper time

scale when the conceptual model is converted to mesh-based numerical model.

5.7 Application of the model to the Himalayan foreland

The numerical model is applied to the regional groundwater flow regime

developed in the compressional tectonic environment of the Himalayas. Modeling

regional groundwater flow means developing numerical models of the aquifer system

being studied and using these models to predict the value of hydraulic head at points (and

times) of interest (Istok, 1989).

Figure 5.1 shows a schematic cross section of a foreland basin during a late stage

in its evolution. As the leading thrust develops, horizontal tectonic forces compress the

platform from the left and vertical loads result from the weight of the advancing thrust

sheet. Both horizontal and vertical loads provide the tectonic force for squeezing pore

fluids out of the sheet and buried strata. This load has been represented by using the

compressibility values (β′) in the model using equation (2). Sedimentary rocks in the basin are layered with regionally continuous aquifers interbedded with aquitards. Deep basal aquifers are commonly composed of uncemented sandstones and/or karstic carbonates, whereas aquitards consist typically of fine-grained limestone, mudstone, evaporites, and crystalline basement (Ge and Garven, 1989). A gentle subaerial topographic slope is assumed across the basin, which may have resulted from flexural rebound following an earlier tectonic event. Clastic sedimentation derived from the

mountain belt may also contribute to the existence of the slope. 122

Transient flow fields are commonly associated with abnormal pressure gradients

created through compaction, tectonic dilation, and chemical diagenesis (Neuzil, 1995).

Groundwater flow rates in this environment are not well known, but theoretical calculations suggest maximum velocities in the 0.5 m/yr range for aquifers and these rates would dissipate quickly when the stress relaxes (Garven, 1995). 123

Figure 5.1: Conceptualized model of a generic foreland basin and adjacent fold and thrust belt (after Ge and Garven, 1992).

124

5.8 Model Parameters

The following protocols were adopted in developing the numerical groundwater flow model for the Peshawar Basin: a) identify the type of model that should be used b) identify the location of aquifer boundaries c) determine values for aquifer materials d) determine values and types of boundary and initial conditions, and e) calibrate and verify the model.

A finite element method was chosen for this study because of its flexibility in handling irregular basin geometry and boundary conditions, tensoral properties, and deforming media. Input parameters for the model include recharge, discharge, and bulk compressibility of the media and water. The ramping structures were used to mimic the field conditions and to incorporate lateral tectonic compression and weight of the imposed thrust sheets. The geometry and boundary conditions are as specified in Figure

5.2. The model is bounded on the east by the Indus River flowing from north to south.

This constitutes a constant head (Dirichlet) boundary and nodal values of 1400 and 400 m were assigned to the northern and southern end, respectively. The rest of the model is bounded by no-flow boundaries. A constant flux (Neumann) boundary has been used to enter the recharge and evapotranspiration for the area. The entire model was represented by 9200 nodes.

125

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0 50 km

71ºE 72ºE 73ºE

Figure 5.2: Boundary conditions and production wells in the study area. Deep well (DW), shallow well (SW). The numbers indicate contour interval (m). Lighter contour colors indicate lower elevations and higher elevations are represented by darker shades. 126

For the steady-state conditions, it has been assumed that the emplacement of these

loads occur nearly instantaneously in a geological sense, an assumption which is

physically unrealistic. This assumption maximizes the actual transient pressure effects

(Ge and Garven, 1992). Typical values of compressibility for sedimentary rocks range from 1x10-8 to 1x10-11 Pa (Birch 1966; Palciauskas and Domenico, 1989), with shaly rocks tending to be somewhat more compressible than sandstones and carbonates.

However, because deformation within a thrust belt occurs over periods of tens of millions of years, inelastic deformation undoubtedly takes place. Palciauskas and Domenico

(1989) theoretically treat the irreversible process of pressure solution in a sandstone and determined that the inelastic value of compressibility is 50 times greater than for elastic deformation for a time scale on the order of millions of years. It was assumed for this study that this conclusion is applicable to all rock types and therefore different values were used for different materials of the model. Compressibility values used as input data for the model are given in Table 5.1. The compressibility of water is a function of pressure and temperature (Strauss and Schubert 1977), but it does not vary much for the conditions present in this model; therefore, a constant value of 5x 10-10 Pa was assumed.

The stratigraphic section is highly simplified into hydrostratigraphic units to better understand the general hydraulics of regional flow. The bottom layers consist of continuous aquifers that extend over the entire length of the basin and vary slightly in thickness. A less permeable aquitard sequence overlies the aquifers. No attempt has been made to differentiate individual stratigraphic units within the respective sequences. 127

A few studies have been conducted to investigate the hydrological properties of

faults (e.g., Morrow et al., 1984; and Forster and Evans, 1991). If clay-type gouge is

found in a fault, the fault is likely to be a barrier to fluid flow (Ge and Garven, 1994).

Morrow et al. (1984) found that hydraulic conductivities in faults range from 10-8 to 10-4 m/yr. However, some studies support the argument that the fracture network within the

fault zone would allow for larger permeabilities during deformation (e.g., Sibson, 1981;

1987). The thrust faults in the area are filled with coarse material and contain fractures

and may well be more permeable than the surrounding rocks. These faults may act as

conduits for flow and chemical transport, and therefore, higher values of hydraulic

conductivities have been assigned to them (Table 5.1). The convergence criteria for both

the steady-state and transient simulations were set at 0.01 m. Recharge and discharge

values for the basin are given in Table 5.2. Both deep and shallow wells have been

represented in the model. Observation wells were installed to monitor the pressure heads

and to provide a reliable tool for calibration of the model. Model verification is not

possible at this time, because the record of field measurements is not available for any

previous time. However, any future measurements of the pressure heads can be used to

verify this model.

5.8.1 Running the model

The model was run on a PC with Windows platform, 512 MB Ram, and 2.44 GHz

microprocessor speed. Input data for the model were entered using various dialogs

(Figures 5.5-5.8). The 2-D mesh and Triangulated Irregular Networks (TINs) are shown 128

in Figures 5.3 and 5.4 respectively. The progress of the simulation can be observed in a

separate window showing graph of iterations vs. error (Figure 5.9). When the model

converges, the result of the simulation can be displayed either as contours or as an iso- surface.

5.8.2 Computed vs. Observed values

A “Computed vs. Observed values” plot is used to display how well the entire set of observed values matches a model solution, as shown in Figure 5.10. A 45 degree line is drawn on this plot, which represents a perfect correspondence between observed data and solution values. One symbol is drawn for each observation point at the intersection of the observed and computed values for the point. The plot shows both the trend of the solution values and the observed data (Figure 5.10).

5.8.3 Error vs. Time step

An “Error vs. Time Step” plot is used with transient simulations to display the mean error, mean absolute error, and root mean squared error between a model solution and observed data as a function of time. This plot applies to a single Data Set in a model solution. Transient measurement types will show the average errors at each time step of the data set. This plot shows the average error at the last time step, as shown in

Figure 5.11.

129

Parameter Rock Upper Aquifer Lower Aquifer Confining Layer Conductivity 0.03 3.0 2.0 0.01 X (m/d) Conductivity 0.03 3.0 2.0 0.01 Y (m/d) Conductivity 0.01 1.0 0.75 0.005 Z (m/d) Moisture 0.25-0.31 0.35-0.43 0.35-0.43 0.15-0.20 content Relative 0.15-0.50 0.25-1.0 0.25-1.0 0.11-0.31 conductivity Water capacity 0.0-0.19 0.0-0.03 0.0-0.03 Young’s 4x1010 8x1010 7x1010 1x1010 Modulus (Pa) Poisson’s 0.3 0.3 0.3 0.3 Ratio (Pa) Compressibilit 4.3x10-12 2.1x10-10 1.5x10-10 2.5x10-11 y (m2/kg)

Table 5.1: Input parameters for hydrodynamic modeling of the Peshawar Basin using the FEMWATER code.

Recharge (Mm3/yr) Discharge (Mm3/yr)

Precipitation 151 Baseflow 713

Surface water 734 Groundwater 177 irrigation extraction Groundwater-based 15 Evapotranspiration 1 irrigation Runoff 23 Total 923 891

Table 5.2: Recharge and discharge data for the Peshawar Basin (Robberts, 1988). 130

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0 50 km

71ºE 72ºE 73ºE

Figure 5.3: 2-D mesh generated for the study area, ultimately to be converted to a 3-D mesh. The mesh has been refined around the wells. Lighter contour colors indicate lower elevations and higher elevations are represented by darker shades. 131

MMT

MCT

Figure 5.4: 3-D representation of the model layers. Every layer is bound by a Triangulated Irregular Network (TIN). Main Mantle Thrust (MMT); Main Central Thrust (MCT). 132

Figure 5.5: Input data parameters for modeling deep and shallow wells in the basin. Deep well (DW), shallow well (SW), observation well (OW). 133

Figure 5.6: Initial conditions (IC) have been specified using the Generate IC button. The IC pressure head was generated from a water table surface.

134

Figure 5.7: Iteration parameters for the flow simulations. 135

Figure 5.8: Dialog showing material properties. The Peshawar Basin aquifers were divided into several hydrostratigraphic units and different values were assigned to each unit. 136

Figure 5.9: Dialog box showing progress of the simulation. 137

82

77 ) m

e ( 72 u

val 67 ed t u p 62 m o C 57

52 53 58 63 68 73 78 83 Observed value (m)

Figure 5.10: Plot showing computed vs. observed values for the pressure head. 138

Figure 5.11: Plot showing error vs. time step for the transient simulation. 139

5.8.4 Parameter sensitivity

In a sensitivity analysis, the values of model parameters are varied across the

range of likely values and the effect upon computed head is noted. Sensitivity analysis

was performed on a set of selected input parameters. A “Parameter Sensitivity” plot has

been used to display the sensitivity of the FEMWATER parameters, as shown in Figure

5.12. This plot shows that the model is highly responsive to changes in compressibility whereas the model responses to changes in conductivity, recharge, and discharge values are relatively small. 140

3.5

3

2.5 ) m ( y

t 2 i iv it

s 1.5 n e S 1

0.5

0 y e t e Z Y X g y li g y y r t t t i i a ar ib v v vi h i s i t t c s ch cti s e e uc r u R Di p duc d n n m ond o o o C C C C

Figure 5.12: Sensitivity analysis for various input parameters in FEMWATER modeling of the Peshawar Basin. The vertical axis represents transient heads (m).

141

5.8.5 Calibration Targets

If an observed value has been assigned to an observation point, or if an observed flow has been assigned to an arc or polygon, the calibration error at each object can be plotted using a "calibration target" (Figure 5.13). A set of calibration targets provides useful feedback on the magnitude, direction (high, low), and spatial distribution of the calibration error. The components of a calibration target are illustrated in Figure 5.13.

The center of the target corresponds to the observed value. The top of the target corresponds to the observed value plus the interval and the bottom corresponds to the observed value minus the interval. The colored bar represents the error (not shown on the figure). If the bar lies entirely within the target, the color bar is drawn in green. If the bar is outside the target, but the error is less than 200%, the bar is drawn in yellow. If the error is greater than 200%, the bar is drawn in red. 142

Figure 5.13: Components of the Calibration Target. 143

5.9 Modeling Results

Steady-state and transient simulations were performed for both topography-driven and tectonically-induced fluid flow conditions. Pressure head values in the wells are given in Table 5.3 and values for all the nodes are compiled in Appendix B. Tectonic compression was imposed using the stair-step pattern and compressibility values for different layers. Total heads and pressure heads are shown in Figures 5.14-5.15, and calibration targets are shown in Figure 5.16. The distribution of pressure heads is uneven throughout the study area, but a general slope from north to south is evident in Figure

5.15.

Transient simulations show positive residuals of 0.98-2.90 m over the topography-driven flow (Table 5.3). An attempt was made to minimize these positive residuals by increasing the value of recharge to the model. As is evident from the sensitivity analysis, the model did not respond to higher values of recharge, and even doubling the recharge value did not minimize the positive residuals. It appears (Figure

5.15; Table 5.3) that the remaining positive residuals are aligned parallel to the major fault zones (MMT and MCT). The successive transient simulations indicate that the residual pressure heads originate in the vicinity of these two major thrust zones in deeper horizons and gradually spread out to shallow levels. These residuals were minimized to a maximum of 0.35 m after incorporating the compressibility values (Table 5.1). It is my understanding that these positive residuals can only be caused by an additional force/pressure that cannot be explained by higher recharge or higher recharge- topography. Therefore, it is proposed that the requisite additional force derives from the 144

litho-tectonic stress imposed by the compressional environment of the study area. In other words, results of the transient simulations appear to indicate that tectonic compression is responsible for the anomalous pressure heads observed in the area.

Moreover, it appears that the new pressure heads attain their maximum values in the first two time steps, that is, within ~104-105 years. 145

P.H. P.H. Computed P.H. Residuals Computed P.H. Node measured in before over after Net ID field compressibility Topography compressibility Residuals 4805 70 67.887 2.113 69.898 0.102 6727 65 62.669 2.331 63.903 1.097 5767 59 57.007 1.993 58.13 0.87 3845 54 53.013 0.987 53.358 0.642 3991 59 56.124 2.876 58.263 0.737 5913 76 73.1 2.9 74.667 1.333 4209 73 70.779 2.221 72.65 0.35 6131 62 60.046 1.954 61.17 0.83 4140 63 61.246 1.754 62.346 0.654 6062 57 55.51 1.49 56.38 0.62 4202 67 64.451 2.549 65.571 1.429 6124 77 75.139 1.861 78.519 -1.519 4464 61 58.109 2.891 62.668 -1.668 6386 73 70.216 2.784 71.594 1.406 4568 55 52.897 2.103 55.787 -0.787 6490 76 74.109 1.891 75.072 0.928

Table 5.3: Pressure head (P.H.) values (m) and the amount of residuals for the production and observation wells.

146

Figure 5.14: Total heads (m) as obtained from the transient simulation at the last stress period, shown on the iso-surface. Y-axis indicates the north. Total heads (m) are highest in the northern part and show a steady decrease towards the south. Green bars indicate error within the range. 147

MMT

MCT

Figure 5.15: Results of the transient simulation at the last stress period, shown as regional pressure heads (m). Pressure heads attain maximum values where the two fault zones (MMT, MCT) originate at depth. See also Figure 5.4 for location of the thrust zones. The last stress period is given in days. Y-axis indicates the north.

148

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71ºE 72ºE 73ºE

Figure 5.16: Study area shown in map view. Calibration targets for the pressure head simulations indicate errors within the target (all the targets show green color only). Every target bar represents an observation well.

CHAPTER 6

DISCUSSION AND CONCLUSIONS

6.1 Discussion

Results from water chemistry (Tables 4.4-4.6), in conjunction with the measured

spring and water well temperatures and calculated reservoir temperatures for the spring

water samples, combine to indicate that several of the sampling sites contain water with

anomalous composition and temperature. Both characteristics suggest origin of these

waters from deep horizons within the basin. Most of the groundwater samples show a

significant surplus temperature over the local mean annual air temperature (see Tables

4.4-4.6). The difference between water surface temperature and mean annual air

temperature (∆T °C, Figure 4.4) exhibits several positive anomalies. One anomaly occurs along the MKT, as represented by samples S15-17, S6, S4, and S7, whereas the other occurs along the MCT and MBT, as represented by samples W17, D10-11 and

W11-13 (see Figure 4.1). All samples indicate temperatures of at least 6 °C above the local mean annual air temperature. In contrast, the only two springs with temperature considerably below the local mean annual temperature (samples S8 and S11; see Table

4.6), an obvious characteristic for topography-driven head, are located relatively far from the fault lines (see Figure 4.1). As noted above, sampling sites with positive thermal anomalies (i.e. where water temperature significantly exceeds the local mean annual

149

150

temperature) are either very close to or virtually straddling a fault line (see Figure 4.1).

The excess temperatures characteristic of groundwaters sampled along the fault zones

(MKT, MBT, and MCT) indicate that they have gained excess heat compared to those

sampled more distant from the fault zones.

All of the groundwater samples reveal chemical signatures indicating that fresh

recharge has mixed with the relatively old, deeply circulated waters (see Figures 4.8-

4.10). This trend is clearly observed on the Piper (1944) diagram for spring water

samples (Figure 4.8), where groundwater shows a spread among all the end members.

All spring water samples plot in the field for fresh recharge, and two of the samples

located along MKT and SRT (S2 and S16) show anomalous composition and temperature

(Figure 4.13). Most significantly, water samples from one shallow well and three deep

wells, all located in the immediate vicinity of the MBT and MMT, demonstrate clear

imprints of admixture of oil-brines (see Figures 4.11-4.12). Furthermore, all the samples

with significantly high ∆T and anomalous composition have abnormally high

concentrations of SiO2 (see Figure 4.14), and the SiO2 concentration of all the waters sampled along the major fault zones is higher than those sampled more distant from the fault zones. Deviation from this trend can be seen in one anomaly on the eastern margin of the Peshawar basin, between the MBT and MMT (Figure 4.14). The high SiO2 concentration at this location may be the result of a blind fault running along the eastern

margin of the Peshawar basin. The anomalous SiO2 trend described above is supplemented by similar trends involving the anomalously high concentrations of boron and strontium (see Figures 4.15-4.16). In particular, the anomalous boron composition is

151

clearly noticeable along the SRT and MKT, whereas clusters of higher boron

composition are evident along the MMT and MBT (Figure 4.15). Likewise, anomalously

high strontium concentrations occur along all of the fault zones except the MMT, where

high Sr is concentrated at one cluster only (Figure 4.16). The anomalously high Sr

abundance along the proposed blind fault exhibits the same spatial pattern as SiO2

(described above). All of these anomalously high levels of components reflect initial dissolution of rock material by deeply circulating groundwater as it migrates to the shallower horizons sampled in this study.

Boron, strontium, and SiO2 concentrations have been plotted against ∆T for all

the groundwater samples. All of these components indicate a positive correlation with

the difference of water surface temperature and the local mean annual air temperature

(see Figures 4.17-4.19). The most pronounced positive correlation is obtained for SiO2, indicating that high-temperature water dissolved more silica while circulating in the deeper formations (see Figure 4.17). Boron and strontium exhibit the same trends, although they are not as pronounced as the SiO2 trend. Measured orifice temperatures of groundwater from the springs were plotted against temperatures calculated from independent geothermometers. In particular, the source reservoir temperature was calculated using Mg-corrected Na-K-Ca, Mg-Li, and chalcedony (silica) geothermometers. Both the silica and cation geothermometers show positive correlations with the orifice temperature of the spring water (see Figures 4.20-4.22). The trend is clearly noticeable on Na-K-Ca-Mg and chalcedony plots, whereas any trend from the

Mg-Li plot is less clear. All of these plots indicate that groundwater equilibrated at

152

higher temperature in deeper, sub-surface formations. The behavior of the Garam

Chashma hot spring is noteworthy on all these diagrams, in that it plots far above all the other groundwater samples. The Garam Chashma hot spring is also the westernmost manifestation of the > 3000 km-long Himalayan Geothermal Belt (HGB) between the

MBT and MKT. The HGB has been described in great detail by Hochstein and

Regenauer-Lieb (1988) and by Hochstein and Yang (1995). The source of the elevated heat flow within the HGB has been attributed to “advective sweeps of infiltrated meteoric water from the hot brittle, upper crust” (Hochstein and Regenauer-Lieb, 1988). Using the geothermal gradient of 0.026 °C/m, as reported by Hochstein and Yang (1995) from wells to the east from our study area, permits inference of a 2000-m-deep circulation of meteoric water. However, the mapped faults might simply have acted as ascent routes for deeply circulating waters of possible meteoric origin, which become thermal because of contact with relatively hot rocks present at relevant depths, similar to what has been observed in the Alps (Pastorelli et al., 2001). Yet, the presence of a regionally dominant compressional tectonic regime (Molnar and Tapponnier, 1977; De Mets et al., 1994; Paul et al., 2001), combined with intense mylonitization along the thrust faults, raises doubt regarding the feasibility of a simple topography-driven mechanism for such deep

“advective sweeps of infiltrated meteoric water.” The very high orifice temperature and anomalous composition of this hot spring cannot be explained by the simple fact that this water is gaining heat from the felsic plutons in the area. Moreover, these plutons are older than 5 Ma and are therefore considered too cold at present to have contributed any heat to the descending recharge. Thus, the only contributing factor to the higher

153

temperature of this hot spring appears to be the deeper circulation of groundwater and

ascent through the fault zones.

The topography-driven pressure from the highest ridges to the north of the study

area may attain a maximum of 25 MPa as compared to the tectonic stress of 90 MPa.

The question remains open as to which of these factors predominates in driving deep

groundwater circulation. It is proposed here that the higher pressure regime is breaking

the sealed thrusts in the foreland fold-and-thrust belt and adjoining areas. Results of the

numerical simulations point in the same direction. Simulation results show that positive

residuals are obtained when tectonic compression is incorporated as an input parameter.

Results of the transient simulations indicate that topography alone is not sufficient to

induce pressure heads observed in the field (field measurements were conducted during

July/August 2003). The positive residuals of 0.98-2.90 m are reduced to 0.40 m at the

last stress period of the transient simulation, showing that tectonic compression is playing

an important role in driving deep groundwater to the shallow levels observed in the water

wells in the study area. The numeric calculations have shown that tectonic compressions

can create periods of transient flows in foreland basins, with excess flow rates of the

order of 10-4 to 10-3 m/yr for thrust sheet loads from 1 to 10 km thick. Most of the excess

pressure generated by compression appears to dissipate in about 104 to 105 years before a new steady state can be reached in about 104 to 105 years. Ge and Garven (1992) arrived at the same conclusion for the Arkoma basin in central Arkansas and Oklahoma.

Although overthrust faults are usually tightly sealed with cataclastic or mylonitized breccias such as the MMT (Dipietro et al., 2000; Singh, 2003), thus

154

rendering them impervious to groundwater flow, it would seem that the overall tectonic

pressure within the basin is high enough to overcome this obstacle. Moreover, a substantial amount of heat is presumably generated by frictional movement along these faults (Todaka et al., 1988). Finally, the remarkable proximity of all the thermal and hydrochemical anomalies (see Figures 4.2 and 4.14-4.16; Tables 4.4-4.6) supports the hypothesis that waters with anomalous composition and temperatures in the Peshawar basin ascended from greater depths along the major fault lines (MMT, MBT and MKT).

6.2 Conclusions

Conclusions from this research are summarized as follows:

1. The study area has been divided into two hydrogeological provinces. Water

table fluctuates considerably in the mountainous north and normal and high-

temperature springs are its only manifestations on the surface. The southern

part of the study area shows a relatively continuous water table in the deep

and shallow wells.

2. Field measurements exhibit surplus temperature of groundwater over the

mean annual air temperature.

3. Geothermometric data of spring water indicate source reservoir temperatures

of up to 200 ºC and 2000 m deep circulation.

155

4. Anomalous pressure heads are obtained through numerical simulations of the

basin.

5. Topography alone cannot account for the pressure heads measured in the field.

The effect of tectonic compression compensates for some of the anomalous

pressure head distribution.

6. The entire thermal and simulation anomalies lends support to the hypothesis

that groundwater is being squeezed from deeper horizons and appears at

shallow levels in drilled wells and at spring heads.

6.3 Future Work

The Himalayan foredeep (Peshawar basin) has provided an ideal site in which to evaluate the effects of tectonic loading on groundwater flow. Moreover, since the entire basin is currently being exploited for valuable oil and gas deposits, future work in the area may be profitably aimed at determining the extent to which groundwater flow paths determined in this study also delineate patterns of petroleum migration. Also, the

Peshawar basin is experiencing a total stress of 90 MPa (Mandal et al., 2000), which is unrivaled in any other part of the world. However, compressive stress probably varies locally throughout the basin, in which case the effects on local groundwater flow will be variable locally in ways that need to be quantified on smaller scales that considered in this study. Coupled processes should also be taken into consideration to see the extent of

156

heat transport and fluid flow. The origin of the emerging groundwater in springs remains as an open question. However, stable isotope analysis (O and H) of these groundwaters would provide insight into their origin.

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169

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APPENDIX A

DERIVATION OF THE FLOW EQUATION FOR FEMWATER

170 171

The governing equation for flow is essentially the modified Richards equation.

Given the continuity of fluid, continuity of solid, consolidation of the media, and the equation of state (Yeh, 1992), the starting equation for derivation of the modified

Richards equation is:

where

3 ρ = fluid density (M/L )

2 k = intrinsic permeability tensor of the media (L )

µ = dynamic viscosity of the fluid (M/LT)

2 2 p = fluid pressure [(ML/T )/L ]

2 g = acceleration of gravity (L/T )

z = potential head (L)

3 3 n = porosity (L /L )

S = degree of saturation (dimensionless) 172

Vs = velocity of the deformable material due to consolidation (L/T)

3 ρ* = density of the injected fluid (M/L )

3 3 q = internal source/sink [(L /T)/L ]

t = time (T)

Expanding the right hand of Equation (A1) yields:

Expanding Equation (A2) by the chain rule yields:

3 where C is chemical concentration (M/L ). Rearranging Equation (A3) gives:

where the first and second terms represent storativity, the third term describes a density- concentration coupling, and the fourth term characterizes unsaturated media. Substituting

Equation (A4) into Equation (A1) results in: 173

An approximation made possible by neglecting the second-order term:

gives

Compressibility of the fluid is defined as:

2 where β is the compressibility of the fluid (LT /M), and its moisture content is defined as:

174

where θ is the moisture content (dimensionless). Substituting Equations (A8) and (A9) into Equation (A7) and rewriting the result leads to the equation:

Beginning with the continuity statement of incompressible solids, Yeh (1992) defined a compressible skeleton is defined as:

Rearranging Equation (A11) in the following form:

and substituting Equation (A12) into Equation (A10) gives:

175

Because the flux of solid velocity is the divergence of Vs (Yeh, 1992), it follows that:

2 where α is the coefficient of consolidation of the media (LT /M). Substituting Equation

(A14) into Equation (A13) and rewriting yields:

Substituting Equation (A9) into Equation (15) gives:

176

Experimental evidence has shown that the degree of saturation is a function of pressure, namely:

Substitution of Equation (A17) into Equation (A16) gives:

Next, the reference pressure head is defined as:

where h is the reference pressure head (L) and ρo is the reference water density (M/L3).

Substituting Equation (A19) into Equation (A18) gives:

177

Dividing Equation (A20) by ρo and rearranging yields:

Modified compressibilities of the media and water are respectively defined as

where α′ is the modified compressibility of the media (1/L) and β′ is the modified compressibility of the water (1/L). Substituting Equations (A22) and (A23) into Equation

(A21) and rearranging yields:

178

The storage coefficient is defined as:

where F is the storage coefficient. Substituting Equation (A25) into Equation (A24) and neglecting the second term on the right side of Equation (A24), following Frind (1982), leads to the equation:

The hydraulic conductivity tensor K is defined as:

Substituting Equation (A27) into Equation (A26) and rearranging gives the density- dependent flow equation (Richards equation):

APPENDIX B

RESULTS OF THE NUMERICAL SIMULATIONS

179 180

INTEGER INDICATING THE SIMULATION MODES, KMOD . . . . . 10 INTEGER INDICATING THE DIAGNOSTIC OUTPUT, IBUG . . . . 1 INTEGER INDICATING THE RAINFALL NODES BE PRINTED,ICHNG 0

NO. OF ITER. ALLOWED FOR HYDRO-TRANS ITERA, NITFTT. . 10 RELAXATION FACTOR FOR HYDRO-TRANS ITER, OMEFTT . . . . 0.50

*** OPTIONAL PARAMETERS (FLOW/TRANSPORT) *** FLOW STEADY-STATE I.C. CONTROL, KSSF ...... 1 TRANSPORT STEADY-STATE I.C. CONTROL, KSST...... 1 LUMPING INDICATOR, ILUMP ...... 1 MID-DIFFERENCE INDICATOR, IMID ...... 0 POINTWISE ITERATION INDICATOR FOR FLOW, IPNTSF . . . 1 POINTWISE ITERATION INDICATOR FOR TRANSPORT, IPNTST. 1 INDEX OF USING QUADRATURE FOR INTEGRATION, IQUAR . . 11

*** OPTIONAL PARAMETERS (FLOW ONLY) *** GRAVITY CONTROL, KGRAV ...... 1 TIME-INTEGRATION PARAMETER, WF...... 1.000000D+00 ITERATION PARAMETER FOR NONLINEAR EQUATION, OMEF. 1.000000D+00 RELAXATION PARAMETER FOR MATRIX EQ. SOV., OMIF. . 1.000000D+00 MIN. ITERATION PARAMETER FOR NONLIN. EQ., OMEMIN. 1.000000D-02 MAX. ITERATION PARAMETER FOR NONLIN. EQ., OMEMAX. 1.500000D+00 ADD. ITERATION PARAMETER FOR NONLIN. EQ., OMEADD. 5.000000D-03 RED. ITERATION PARAMETER FOR NONLIN. EQ., OMERED. 6.667000D-01 CONSTRAINT ON HYDRAULIC CONDUTIVITY, CNSTKR . . . 1.000000D-05

*** OPTIONAL PARAMETERS (TRANSPORT ONLY) *** SORPTION MODEL CONTROL, KSROP ...... 1 LGRANGIAN INDICATOR, LGRN ...... 1

181

ITERATION PARAMETER FOR NONLINEAR EQUATION, OMET . 1.000000D+00 RELAXATION PARAMETER FOR MATRIX EQUATION, OMIT . . 1.000000D+00

**** ITERATION PARAMETERS (FLOW ONLY) **** NO. OF ITERATIONS PER CYCLE, NITERF...... 100 NO. OF CYCLES PER TIME STEP, NCYLF ...... 1 NO. OF ITERATIONS ALLOWED FOR SOLVING MATRIX EQ . . 1000 STEADY-STATE TOLERANCE, TOLAF ...... 1.000000D-02 TRANSIENT-STATE TOLERANCE, TOLBF...... 1.000000D-02

*** ITERATION PARAMETERS (TRANSPORT ONLY) *** NO. OF ITERATIONS FOR NONLINEAR EQUATION, NITERT . 40 NO. OF ITERATIONS FOR MATRIX EQUATION, NPITERT . . 400 ERROR ALLOWANCE FOR TRANSIENT SOLUTION, TOLBT. . . 1.000000D-02

*** TIME CONTROL PARAMTER *** NUMBER OF TIME INCREMENTS,NTI...... 11

MAXIMUM VALUE OF TIME, TMAX ...... 3.650000D+06

LINE PRINTER OUTPUT CONTROL 1 2 3 PRINTER TIME-STEP CONTROL 1 DSK SAVED TIME-STEP CONTROL 1

TIME INCREMENT, DELT = 3.650000D+05 *** MATERIAL PROPERTIES *** NUMBER OF DIFFERENT MATERIALS, NMAT...... 3 NUMBER OF MATERIAL PROPERTIES PER MATERIAL, NMPPM . 8 NUMBER OF DENSITY AND VISCOSITY FUNCTION COEFFS. . . 8 182

MAT NO. SAT KXX SAT KYY SAT KZZ SAT KXY SAT KXZ SAT KXZ Alpha Porosity ------3 9.0000D-01 9.0000D-01 6.0000D-01 0.0000D+00 0.0000D+00 0.0000D+00 0.0000D+00 4.3000D-01 2 1.2000D+00 1.2000D+00 9.0000D-01 0.0000D+00 0.0000D+00 0.0000D+00 0.0000D+00 4.3000D-01 1 3.0000D-02 3.0000D-02 1.0000D-02 0.0000D+00 0.0000D+00 0.0000D+00 0.0000D+00 4.1000D-01

*** DENSITY AND VISCOSITY FUNCTION COEFF.S *** RHO0 B1 B2 B3 MU0 A1 A2 A3 1.000 0.000 0.000 0.000 1.000 0.000 0.000 0.000

**** SOIL PROPERTY PARAMETERS ****

NUMBER OF SOIL PROPERTY PARAMETERS, NSPPM . . . . . 3 PERMEABILITY INPUT CONTROL, KCP ...... 0 DENSITY OF WATER, RHO ...... 1.000000D+00 ACCELERATION OF GRAVITY, GRAV ...... 7.320625D+10 VISCOSITY OF WATER, VISC...... 0.000000D+00 Compressibility of water...... 4.300000D-11

MAT. NO.KD RHOB AL AT AM TAU LAMADA N OR SMAX Kw Ks ------3 0.00D+00 0.00D+00 0.00D+00 0.00D+00 0.00D+00 1.00D+00 0.00D+00 0.00D+00 0.00D+00 0.00D+00

2 0.00D+00 0.00D+00 0.00D+00 0.00D+00 0.00D+00 1.00D+00 0.00D+00 0.00D+00 0.00D+00 0.00D+00

1 0.00D+00 0.00D+00 0.00D+00 0.00D+00 0.00D+00 1.00D+00 0.00D+00 0.00D+00 0.00D+00 0.00D+00

***** ELEMENT DATA ***** NO. OF ELEMENTS, NEL ...... 16389 ***** NODAL COORDINATE DATA ***** NO. OF NODAL POINTS, NNP ...... 9610 PRESSURE HEADS(m) AT TIME = 3.6500D+06 (DELT = 3.6500D+05),(BAND WIDTH = 102) IT = 10 183

NODE P. HEAD(L) NODE P. HEAD(L) NODE P. HEAD(L) NODE P HEAD(L) NODEP HEAD(L) NODE P HEAD(L)

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