HYDROGEOCHEMISTRY AND HYDROLOGY OF A BASALT … · HYDROGEOCHEMISTRY AND HYDROLOGY OF A BASALT...

HYDROGEOCHEMISTRY AND HYDROLOGY OF A BASALT AQUIFER

SYSTEM, THE ATHERTON TABLELANDS, NORTH QUEENSLAND

Katrina Louise Locsey

Bachelor of Applied Science

(Queensland University of Technology)

Master of Applied Science

(Queensland University of Technology)

School of Natural Resource Sciences

A thesis submitted for the Degree of Doctor of Philosophy of the

Queensland University of Technology

2004

STATEMENT OF ORIGINAL AUTHORSHIP

The work contained in this thesis has not been previously submitted for a degree ordiploma at any other higher education institution. To the best of my knowledge andbelief, the thesis contains no material previously published or written by anotherperson except where due reference is made.

Signed ………………………………

Katrina Locsey

Date ………………………………

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ABSTRACT

The Atherton Tablelands basalt aquifer is a major source of groundwater supply forirrigation and other agricultural use. The Tertiary to Quaternary age basaltic aquifercan be regarded as a generally unconfined, layered system, comprising numerousbasalt flows separated by palaeo-weathering surfaces and minor alluvial gravels ofpalaeo-drainage channels. Layers of massive basalt and clay-rich weathered zonesact as local aquitards, with some local perched aquifers also present. The aquifer isregarded as a system in which several factors interact to produce the overallcharacteristics of the hydrogeochemistry of the groundwaters. They include themineralogical composition of both the basalt aquifer and the thick overlyingweathered zone, the porosity and permeability of the basalt aquifer, its thickness,bedrock composition, and climate and topography.

The hydrogeochemical processes operating in this aquifer system have beeninvestigated though the analysis of 90 groundwater samples collected from October1998 to October 1999, groundwater chemistry data provided by the QueenslandDepartment of Natural Resources & Mines for more than 800 groundwater samples,rain water samples collected during 1999 by CSIRO, stream chemistry data providedby CSIRO and James Cook University, and mineralogical and whole rockgeochemistry data of drill chip samples.

The methods used in this research study include the assessment of groundwatermajor ion chemistry data and field physico-chemical parameters usinghydrochemical facies and statistical approaches, investigation of the mineralogicalcomposition of the aquifer, assessment of concentrations and activities of the ions insolution, the degree of saturation with respect to both primary and secondaryminerals, and hydrogeochemical modelling to determine the likely controls on thechemical evolution of these groundwaters.

The basaltic groundwaters are mostly Mg-Ca-Na, HCO3 type waters, with electricalconductivities generally less than 250 µS/cm and pH values from 6.5 to 8.5.Dissolved silica (H4SiO4) comprises a large proportion of the total dissolved load,with average concentrations of around 140 mg/L. Concentrations of potassium,chloride and sulphate are low, that is, generally less than 3 mg/L, 15 mg/L and10 mg/L, respectively. Despite the very low salinity of the Atherton Tablelandsbasalt groundwaters, the relative concentrations of the major ions are comparable togroundwaters from other basaltic regions, and are consistent with expected water-rock interactions.

A variety of multivariate statistical techniques may be used to aid in the analysis ofhydrochemical data, including for example, principal component analysis, factoranalysis and cluster analysis. Principal component factor analyses undertaken usingthe hydrochemical data for the Atherton groundwaters has enabled the differentiationof groundwaters from various lithological formations, the underlying geochemicalprocesses controlling groundwater composition in the basalt aquifer to be inferred,relative groundwater residence and flow directions to be inferred and mapping of theestimated thickness of the basalt aquifer.

The limitations of multivariate statistical methods have been examined, withemphasis on the issues pertinent to hydrochemical data, that is, data that are

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compositional and typically, non-normally distributed. The need to validate,normalize and standardize hydrochemical data prior to the application of multivariatestatistical methods is demonstrated.

Assessment of the saturation states of the Atherton basalt groundwaters with respectto some of the primary minerals present indicate that the groundwaters are mostly atequilibrium or saturated with respect to K-feldspar, and approach equilibrium withrespect to the plagioclase feldspars (albite and anorthite) with increasing pH. Thesegroundwaters are at equilibrium or saturated with respect to the major secondaryminerals, kaolinite, smectite (Ca-montmorillonite) and gibbsite. They also tend to besaturated with respect to the oxidation products, goethite and hematite, commonaccessory minerals in the Atherton Tablelands basalt sequence.

Silicate mineral weathering processes are the predominant influence on thecomposition of these basalt groundwaters. These weathering processes include theweathering of pyroxenes, feldspars and other primary minerals to clays, aluminiumand iron oxides, amorphous or crystalline silica, carbonates and zeolites, releasingions to solution. The contribution of substantial organic carbon dioxide to thegroundwater is an important factor in the extent to which silicate mineral weatheringoccurs in this aquifer system. Evaporative enrichment of recharging waters,oxidation and ion-exchange reactions and the uptake of ions from, anddecomposition of, organic matter, are processes that have a minor influence on thecomposition of the basalt groundwaters.

The relationships observed between mineralogical compositions, basalt character andgroundwater occurrence in the Atherton Tablelands region improved theunderstanding how groundwater is stored and transmitted in this basalt aquifersystem. Groundwater is mostly stored in vesicular basalt that may be fresh to highlyweathered, and movement of this water is facilitated by pathways through bothvesicular and fractured basalt.

Related work undertaken as part of this research project showed that the groundwaterflow patterns defined by the hydrogeochemical interpretations correspond well withthe spatial trends in water level fluctuations, and response to recharge events inparticular. Groundwater baseflow to streams and discharge to topographic lows inthe Atherton Tablelands region is indicated by the relationships between the majorcations and anions in the stream waters. Fracture zones are likely to be preferredpathways of groundwater movement. Recharge estimates, based on a chloride massbalance, range from 310 mm/yr in the north-western part of the study area (north ofAtherton) to 600 mm/yr in the wetter southern and eastern parts of the study area.These recharge estimates should be treated with caution however, due to the lowgroundwater chloride concentrations and the high variability in rainfall chlorideconcentrations.

The findings of this research project have improved the understanding of thehydrogeochemical processes controlling the composition of the low salinity basaltgroundwaters in the Atherton Tablelands region, and are applicable to other basaltgroundwater systems, particularly those in high rainfall environments.

Key words: Hydrogeochemistry · Basalt aquifer · Mineralogy · Multivariate statistical analysis

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ACKNOWLEDGEMENTS

I would like to acknowledge the support and encouragement of my principalsupervisor Dr Malcolm Cox, who has been particularly helpful over many years,both during and prior to this PhD research. His establishment of the QUT researchprojects in the Atherton Tablelands region, his guidance in directing this research,provision of the equipment necessary to undertake the research, and maintenance ofscholarship and travel funds, is gratefully acknowledged. My associate supervisorDr Micaela Preda has also contributed considerable time in reviewing manuscriptsand assisting with X-ray diffraction analyses, and has held many helpful discussionswith me during the course of this research.

This research project was funded by the Land and Water Resources Research andDevelopment Corporation and the Queensland Department of Natural Resources andMines (QDNR&M). Without the assistance of these organisations, this researchwould not have been possible. Mr Bruce Pearce, Mr Graham Herbert, Mr AndrewDurick and Mr John Bean (QDNR&M) have provided much advice, data andassistance, particularly in the early stages of this research program. I wouldparticularly like to thank Bruce Pearce, who organised and co-ordinated much of thehydrogeological work undertaken in the Atherton Tablelands region in recent years.

I am also grateful for the data and samples provided by Dr Peter Cook, Dr AndrewHerczeg and Ms Kerryn McEwan from CSIRO Land and Water, and staff at JamesCook University, who have also undertaken work on the Atherton Tablelands.Helpful information and data has also been provided by the QUT Honours students,Ms Lindsey Buck, Ms Michelle Sheldrick and Mr Martin Moloney. Laboratoryassistance was provided by Ms Sharyn Price and Mr Tony Raftery (QUT). Theassistance of Dr Deidre Stuart (QUT) with calculations presented in Appendix VI isgratefully acknowledged.

Travel grants from the QUT Office of Research and the School of Natural ResourceSciences enabled the attendance of conferences in South Africa, Townsville andDarwin, which has been very beneficial to my research and professionaldevelopment. I would also like to thank staff of the School of Natural ResourceSciences, particularly the administrative and computing staff who helped in manyways over the past few years. I also appreciate the encouragement of my fellowpostgraduate students, in particular Mr John Harbison, who reviewed manydocuments for me and shared in many interesting and helpful discussions about ourwork over these past few years.

I would like to thank my friends and family in Brisbane and Melbourne, who havegiven me much encouragement during the course of this research. My thanks to mydear friend Leisl, my sister Michelle and brother-in-law Stewart for their help andencouragement, and to their angels Madeleine, Lauren and Benjamin who alwaysmake my time away from study so enjoyable. Finally and most importantly, I wouldlike to thank my parents Valerie and Robert Locsey for their support over the pastfew years, and for their work and the many sacrifices they have made to provide theirdaughters with the best possible education.

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PUBLICATIONS BY CANDIDATE FROM PhD STUDY

Refereed papers (International journals)Published

PAPER 2:

LOCSEY K.L. & COX M.E. 2002. Statistical and hydrochemical methods to comparebasalt and basement rock hosted groundwaters: Atherton Tablelands, north-eastern Australia. Environmental Geology, 43 (6), pp. 698-713. Paper andsupplementary material published online 10th October 2002 – EnvironmentalGeology, © Springer-Verlag, DOI 10.1007/s00254-002-0667-z.

Manuscript prepared for Hydrogeology Journal

PAPER 3:

LOCSEY K.L., PREDA M. & COX M.E. 2002. Water – rock interactions: aninvestigation of the relationships between mineralogy and groundwatercomposition and flow in a subtropical basalt aquifer.

International conference publicationsReviewed and published papers

PAPER 1A:

LOCSEY K.L. & COX M.E. 2000. Chemical character of groundwater in a basaltaquifer, North Queensland, Australia. In Sililo O. et al. eds. Groundwater:Past achievements and future challenges. Proceedings of the XXXth

International Congress of the International Association of Hydrogeologists,Cape Town, pp. 555-560. A.A.Balkema, Rotterdam.

PAPER 1B:

LOCSEY K.L. & COX M.E. 2001. A hydrochemical classification scheme for abasaltic aquifer as an indicator of groundwater flow position. In Seiler K.P.and Wohnlich S. eds. New approaches to characterising groundwater flow.Proceedings of the XXX1st International Congress of the InternationalAssociation of Hydrogeologists, Munich, pp. 1217-1221. A.A.Balkema, Swets& Zeitlinger B.V., Lisse.

APPENDIX IV:

LOCSEY K.L. & COX M.E. 2002. Hydrochemical variability as a tool for defininggroundwater movement in a basalt aquifer: The Atherton Tablelands, NorthQueensland. In Proceedings of the International Association ofHydrogeologists International Groundwater Conference: Balancing theGroundwater Budget, Darwin, 12-17 May 2002.

Abstract and Poster

APPENDIX I:

LOCSEY K.L. & COX M.E. 2001. Climatic, mineralogical and weathering controls onthe geochemical character of groundwater – the Atherton Tablelands basaltaquifer, North Queensland. In Proceedings of the 4th International Conferenceon Environmental Chemistry and Geochemistry in the Tropics (GEOTROP2001), Townsville, 7-11 May 2001.

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TABLE OF CONTENTS Page

Abstract…………………………………………………...…………………………………...………..i

Acknowledgements……………………………………..…………………………………………….iii

Publications by candidate from PhD study………...…………………….………………….……...iv

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

LITERATURE REVIEW………………………………………………………….……..…6Introduction……………………………………………………………………………………...….…6

Previous work in the Atherton Tablelands region……………………………………...…………...6

Basalt aquifer systems………………………………………………...…...…………………………..9Background…………...………….…………………………………………….……………...9Columbia River Plateau………….………………………………….……………………….11Deccan Basalts…………………………….………………………………………….…...…12Other basalt aquifers...…..……………………………………………….…………………..12Basaltic oceanic islands……….……………………………...………………………….…..13Australian basalt aquifer systems...………………………………………….……………….14

Processes controlling groundwater composition………………………..…………………...……..15Background…………...………….…………………………………….…………………….15Carbon dioxide in water………….………………………………………………….……….16Silicate mineral dissolution and weathering………………………………………….…...…17Oxidation and reduction……………………………………………………….……………..24Ion-exchange…………….…….…………………………….………………...……………..25Evaporation…………………….…………………………………….………………………26Organic matter……………………………………………………………………….………27Other factors influencing groundwater composition…...……………………….……...……28

Mineralogical and hydrochemical methods for modelling hydrogeochemicalprocesses……………………………………………….…………………..………………………….30

Rock chemistry and mineralogy....…………………………………….…………………….30Mineral dissolution and solubility.…………………………………………………….…….30Mass balance approach……………………………………………….…………………...…33Hydrogeochemical modelling……...………………………………………………….……..34

Related hydrogeochemical studies and scope for further research.……………………….....…...36

Statistical methods for hydrochemical data assessment………..……………………...……..……41Background…………...………….………………………………………….……………….41Data distribution and validation…..………………………………….………………………41Transformation and standardization methods………………………………………….…….43Multivariate data assessment…………………………………………………….……….….45

Graphical methods...…………………………………….………………….…………...…46Principal component analysis…………………………………….………………….…...47Factor analysis………………………………………………………………….………..…48Principal component factor analysis…………………………….…………………....…50Limitations of factor analysis………………………………………………….…..…...…53Cluster analysis…………………………………………………………….…………….…54Alternative multivariate statistical methods…….………………….………………...…55

Application of some multivariate statistical methods to hydrological and hydrochemical studiesand scope for further work………….……………………………………………………….....……58

Background…………...………….………………………………………………….……….58Hydrochemical processes………....…………………………………………….……………58Differentiation by source………………………...………………………….……………….61Other studies and scope for further work……..………………………….…………………..62

Conclusions…………………………………………….………………………………………..……64

References…………………………………………….……….……………..…………………...…..65

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PAPER 1A

CHEMICAL CHARACTER OF GROUNDWATER IN A BASALT AQUIFER, NORTH QUEENSLAND,AUSTRALIA………………………………………………………………………...….……..96

PAPER 1B

A HYDROCHEMICAL CLASSIFICATION SCHEME OF A BASALTIC AQUIFER AS AN INDICATOR OFGROUNDWATER FLOW POSITION……………………………………..……………………..110

PAPER 2

STATISTICAL AND HYDROCHEMICAL METHODS TO COMPARE BASALT- AND BASEMENTROCK-HOSTED GROUNDWATERS: ATHERTON TABLELANDS, NORTH-EASTERNAUSTRALIA…………………………………………………………………………………123

PAPER 3

WATER – ROCK INTERACTIONS: AN INVESTIGATION OF THE RELATIONSHIPS BETWEENMINERALOGY AND GROUNDWATER COMPOSITION AND FLOW IN A SUBTROPICAL BASALTAQUIFER…………………………………………………………………………….………157

GENERAL CONCLUSIONS…………..……………………….………………………..197

APPENDICESAPPENDIX I

Climatic, mineralogical and weathering controls on the geochemical character of groundwater – theAtherton Tablelands basalt aquifer, North Queensland…….………………………………………..200

APPENDIX II

Extracts from Locsey and Cox (unpubl.), a report submitted to QDNR&M and LWRRDC, andadditional related work

Hydrogeochemical cross-sections: inferring relationships between hydrochemistry and groundwatermovement.……………………….……………………………………………………………...……202

APPENDIX III


Groundwater–stream interaction: the Atherton Tablelands, NorthQueensland…………………………………………………………………………………...………212

APPENDIX IV

Hydrochemical variability as a tool for defining groundwater movement in a basalt aquifer: theAtherton Tablelands………………………………………………………………………...……..…218

APPENDIX V

Supportive approaches and applications of work presented in PAPER 2

Multivariate data analysis of the Atherton Tablelands groundwaters: Approaches

Thickness of the basalt aquifer

Groundwater flow directions inferred from the principal component factor analysis...……………..240

APPENDIX VI


Groundwater recharge: a chloride mass balance approach

Reliability of the chloride mass balance approach: consideration of additional input sources ofchloride……………………………………………………………………………………………….245

APPENDIX VII

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Chemical analysis of natural waters……………………………………………………………..…...254

APPENDIX VIII

Mineralogical analysis - X-ray diffraction…………………………………………………………...262

APPENDIX IX

Field and laboratory data: groundwater and rain water samples……………………………..………265

APPENDIX X

Mineralogical data……………………………………………………………………………..……..276

APPENDIX XI

Groundwater data sourced from the Queensland Department of Natural Resources and Mines...…..279

INTRODUCTION

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INTRODUCTION

Hydrogeochemical processes are important in defining groundwater hydrology incomplex, layered basalt aquifers, particularly where groundwaters are of very lowsalinity. An assessment of fresh groundwaters, that may show subtle variations inchemical character, requires an understanding of the hydrogeochemical processescontrolling groundwater composition. The relationships between groundwatercomposition, hydrogeochemical processes and groundwater hydrology haveparticular relevance to basalt aquifer systems, as they commonly contain relativelyfresh groundwaters. They also tend to have complex groundwater flow patterns, dueto their geological structure, that may be defined using hydrogeochemicalinterpretations.

This research project tests the hypothesis that hydrogeochemical processes, andsilicate mineral weathering processes in particular, are the most significant influenceon the chemical character of very low salinity groundwaters in a basalt aquifersystem in a subtropical environment, and that an understanding of such processes canbe used to define groundwater hydrology. This research explores the relationshipsbetween groundwater composition, hydrogeochemical processes and groundwaterhydrology; it aims to determine the controls on groundwater composition and thenature of groundwater storage and movement in a subtropical basalt aquifer system.The groundwater resources contained within the basalt and basement rock aquifers ofthe Atherton Tablelands, North Queensland, Australia (Figure 1), provide an idealsetting for such an investigation.

Figure 1. Location map of the study area: the Atherton Tablelands, NorthQueensland, Australia.

145º 22'

-17º 8'145º 46'

-17º 8'

145º 46'

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Queensland

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-17º 8'

145º 46'

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-17º 31'


# CairnsAtherton Tablelands

Queensland


#

0 500 1000 Kilome te rs0 500 1000 Kilome te rs

## CairnsAtherton Tablelands

Queensland

Queensland

Australia

Queensland

Australia

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%

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0 5 10 15 20 Kilometers

LakeTinaroo

MazlinCreek

Barr

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North Johnstone River

Millaa Millaa

MalandaUpperBarron

Atherton

Walkamin

KairiTolga

Basalt

Roads (Major and Minor)

Rivers

N

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The research described in this thesis forms a component of a major programinvestigating the aquifer systems of the Atherton Tablelands. This program wasfunded by the Queensland Department of Natural Resources and Mines (QDNR&M)and the Land and Water Resources Research and Development Corporation(LWRRDC). The project has involved collaboration between QDNR&M, CSIROLand and Water and the Queensland University of Technology (QUT). QDNR&Mhave undertaken extensive assessment and monitoring of the groundwater resource,developed conceptual and numerical groundwater flow models of the north-easternpart of the region, and developed a groundwater management plan for this area. Thecontribution by CSIRO focused on determining groundwater ages and recharge ratesusing isotope hydrology, and identifying groundwater flow zones and base flows tostreams using radium-tracing techniques.

The QUT component of the research program comprised three Honours projectsundertaken in the School of Natural Resource Sciences, as well as this PhD researchproject. The Honours projects involved an assessment of the physical features ofvolcanism in the Atherton Tablelands region (Buck 1999), stratigraphicinterpretation of the lava field using petrogenetic modelling (Sheldrick 1999) and ageophysical study assessing the use of magnetic surveys in the identification ofphysical features of the basalt pile (Maloney 1999). A concurrent Masters degreestudy by Bean (1999) addressed the hydrogeology and groundwater resourcepotential of the northern part of the region.

The hydrochemistry of groundwaters from these aquifers has been assessed in thiscurrent investigation using several approaches, including descriptive statisticalapproaches, multivariate data assessment using principal component factor analysis,and a classification scheme approach. The hydrogeochemistry has also beenassessed using a hydrochemical facies approach, and by examining the processes thatinfluence groundwater composition. These processes include enrichment byevaporation and transpiration, interaction with primary and secondary minerals in thesoils and the weathered and fresh rock layers, ion-exchange effects, and leaching ofions from organic matter. The mixing of waters sourced from different aquifers isalso a factor that is addressed.

The associations between aquifer rock mineral phases and their relative quantities,and groundwater occurrence and composition, have enabled an understanding of thenature of groundwater migration and the controls on groundwater composition.

The methods utilized here have more commonly been applied to regional aquifersystems in arid, semi-arid and temperate climates, where groundwaters havesubstantially higher concentrations of ions and are considerably older. Theapplication of these methods to a study of a very low salinity groundwater system ina subtropical basalt environment, however, is unique and has shown the usefulness ofthese approaches in such a setting. The importance of aquifer systems in tropical andsubtropical environments is being increasingly recognized, particularly in developingcountries in southern Asia and sub-Saharan Africa, where communities are oftenstrongly reliant on locally recharged, non-sedimentary aquifer systems.

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In addition, the methods used in this research project rely predominantly on majorion chemistry and field measurements, and demonstrate the depth of information thatcan be gained from basic hydrochemical data. This aspect of the research project isparticularly relevant to hydrogeological studies undertaken in remote environmentsor in locations where the use of more expensive analytical techniques, such asisotope chemistry, are either impractical or prohibitive due to cost. Facilities for thegeochemical analysis of waters in many countries in Africa for example, are limitedto major and minor ions (Edmunds 1996). Methods used in this study are thereforeanticipated to be widely applicable.

The research aims are accomplished through a literature review, and a series ofresearch papers and associated work; each paper demonstrates the applicability ofparticular methods to improving the understanding of a subtropical basalt aquifersystem.

PAPER 1 is comprised of two related papers (1A and 1B). PAPER 1A entitled“Chemical character of groundwater in a basalt aquifer, North Queensland,Australia” examines the variations in hydrochemical composition in the aquifer andproposes that the aquifer may be divided into hydrochemical zones, depending on thegroundwater composition. These zones range from areas where the groundwatercomposition is predominantly controlled by rainfall composition, to a mixed watertype, to more evolved water that shows the effects of silicate mineral weatheringprocesses.

The hydrochemical relationships between the major ions in the groundwaters of theAtherton Tablelands are further examined in PAPER 1B “A hydrochemicalclassification scheme for a basaltic aquifer as an indicator of groundwater flowposition”. Five key indicators of the chemical evolution of these groundwaters (i.e.Mg2+/Cl-, HCO3

- + CO32-/Sum Cations, HCO3

-/Cl-, H4SiO4 concentration and thepercentage of HCO3

- + CO32- of major anions) were used in a rating-based

classification scheme to identify the relative positions of groundwaters along inferredflow paths, and enabled the identification of areas of preferred recharge. Theconcept of classification schemes is used in other fields in hydrogeology, such as invulnerability and risk mapping studies, and has been applied here to classifygroundwaters based on their chemical compositions. This work is also presented as aconference abstract and poster in APPENDIX I.

The cross-sections and accompanying data presented in APPENDIX II demonstratehow such a classification scheme can be applied to infer relationships betweenhydrochemistry and groundwater movement. One of the key indicators ofhydrochemical evolution (i.e. Mg2+/Cl-) has also been useful in determining thenature of groundwater and stream-water interaction on the Atherton Tablelands.This work is presented in APPENDIX III.

The classification scheme presented in PAPER 1B was refined and modified toexamine only those groundwaters of a ‘basaltic’ hydrochemical composition inAPPENDIX IV “Hydrochemical variability as a tool for defining groundwatermovement in a basalt aquifer: The Atherton Tablelands, North Queensland”.

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APPENDIX IV also further demonstrates the effects of evaporative enrichment andsilicate mineral weathering processes on the compositions of these groundwaters.

Multivariate data analysis, specifically principal component factor analysis, as wellas standard descriptive statistical and hydrochemical methods are demonstrated inPAPER 2 “Statistical and hydrochemical methods to compare basalt- and basementrock-hosted groundwaters: Atherton Tablelands, north-eastern Australia”. This studymakes use of a large set of hydrochemical data from QDNR&M as well as samplescollected and analysed by the author during the course of study. An early applicationof principal component factor analysis to these data provided a qualitativeassessment of the likely host rocks of groundwater from unidentified lithologicalunits and is presented in APPENDIX V.

The methods used in PAPER 2, particularly the principal component factor analysis,show that the hydrochemical variability can be used to distinguish basalt- andbasement rock-hosted groundwaters, and thus enable the definition of the likely hostrocks of groundwaters from unidentified lithological units. This approach resulted inan improved understanding of the thickness of the basalt aquifer and, thereby, theextent of the resource (APPENDIX V). The principal component factor analysis ofthe basaltic hydrochemistry also enabled the interpretation of the likelyhydrogeochemical processes controlling the composition of these waters. Where aparticular process controlling groundwater composition can be related togroundwater residence, flow directions may be inferred (APPENDIX V).

Consideration needs to be given to the use of multivariate statistical methods inanalysing compositional and non-normally distributed data. Transformation andstandardization methods are discussed in PAPER 2, as are the numerous optionsinvolved in applying a principal component factor analysis and the need to assess therobustness and interpretability of the results.

A combination of hydrochemical and mineralogical approaches to characterizinggroundwater evolution and movement in a subtropical basalt aquifer are presented inPAPER 3 “Water – rock interactions: an investigation of the relationships betweenmineralogy and groundwater composition and flow in a subtropical basalt aquifer”.Mineral phases present at various depths in the basalt aquifer were identified andquantified. The relationships between the basalt mineralogy, and groundwateroccurrence and composition, due to water – rock interaction, have improved theunderstanding of groundwater storage and transport in this aquifer system. Massbalance calculations and hydrochemical modelling, when used in conjunction with anunderstanding of the aquifer mineralogy, enabled a more accurate identification ofthe hydrochemical processes influencing this aquifer system.

Related hydrogeochemical work within this study, that is, groundwater rechargecalculations based on a chloride mass balance, is presented in APPENDIX VI. Thiswork has not previously been prepared for publication. The recharge estimates are,however, quoted by Pearce and Durick (2002), who support the estimates byindependent recharge calculations, based on a soil moisture model and groundwaterusage estimates. Methods used to analyse water and rock samples are presented inAPPENDICES VII and VIII, respectively. Results of the groundwater analyses for

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samples collected by the author during the course of study, as well as results of rainsample analyses (samples obtained by CSIRO and analysed by the author), arepresented in APPENDIX IX. Mineralogical data for rock samples analysed arepresented in APPENDIX X and reference to QDNR&M groundwater data used inthis study is made in APPENDIX XI.

The research findings demonstrate that if the hydrochemical variables examinedinclude those expected to differentiate groundwaters by source and by process, thenmultivariate statistical analysis, mineralogical and hydrochemical assessments, andinterpretation of hydrogeochemical processes, can be useful methods for theexamination of a subtropical basalt aquifer system. Limitations of these methods andthe need for verification of the processes inferred are particularly relevant whendealing with groundwaters with low concentrations of ions, because interpretationsare often based on subtle variations in groundwater composition.

References

BEAN J.A. 1999. A conceptual model of groundwater behaviour in the AthertonBasalt Province, Atherton Tablelands, Far North Queensland. MAppSc thesis,Queensland University of Technology, Brisbane (unpubl.), pp. 159.

BUCK L.J. 1999. Physical features of volcanism and their relationship togroundwater, Atherton Basalt Province, North Queensland. BAppSc(Hons)thesis, Queensland University of Technology, Brisbane (unpubl.), pp. 178.

EDMUNDS W.M. 1996. Geochemical framework for water quality studies in sub-Saharan Africa. Journal of African Earth Sciences 22 (4), 385-389.

MOLONEY M. 1999. The magnetic method applied within a Quaternary volcanicplateau – Atherton, North Queensland. BAppSc(Hons) thesis, QueenslandUniversity of Technology, Brisbane (unpubl.), pp. 81.

PEARCE B.R. & DURICK A.M. 2002. Assessment and management of basalt aquiferson the Atherton Tablelands, North Queensland, Australia. In Proceedings ofthe International Association of Hydrogeologists International GroundwaterConference: Balancing the Groundwater Budget, Darwin, 12-17 May 2002.

SHELDRICK M.K.M. 1999. Stratigraphic interpretation of a lava field usingpetrogenetic modelling. BAppSc(Hons) thesis, Queensland University ofTechnology, Brisbane (unpubl.), pp. 57.

LITERATURE REVIEW

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LITERATURE REVIEW

Introduction

This research is based on the basalt aquifers of the Atherton Tablelands, NorthQueensland. The approach to this study is to consider the basalt pile as an aquifersystem in which several natural processes operate to define the chemicalcharacteristics of the groundwater.

The literature review outlines:

previous work undertaken in the Atherton Tablelands region,

the nature of groundwater occurrence in various types of basalt aquifers,

processes controlling groundwater composition, particularly in basaltaquifers,

mineralogical and hydrochemical methods for assessing the influences ofthese processes,

related hydrogeochemical studies and scope for further research,

statistical methods for hydrochemical data assessment, and

the application of multivariate statistical methods to hydrological andhydrochemical studies, and discusses the scope for further application ofsome of these methods to the assessment of very low salinity groundwaters.

This review considers both publised literature on relevant subjects, as well astechnical reports and unpublished material specific to the Atherton Tablelandsregion.

Previous work in the Atherton Tablelands region

The study area is located within the basaltic lava field of the Atherton BasaltProvince, a high rainfall, subtropical elevated plateau with a substantial depth ofweathering. The Atherton Basalt Province forms part of the Eastern AustralianVolcanic Zone, and is an example of an intraplate continental basalt field(Stephenson 1989). The province is characterized by a variety of volcanic featuresthat include shield volcanoes, composite cones, maars, cinder cones and onediatreme (Stephenson et al. 1980). The basalts overlie Devonian metamorphic rocksof the Hodgkinson Formation, various Permo-Carboniferous granites and felsicCarboniferous volcanics (Donchak & Bultitude 1994).

Detailed cross-sectional mapping by Pearce (2002), which is based on drill logs,shows evidence of up to 22 possible phases of volcanism and indicates that the basaltaquifers comprise a complex series of multi-layered flow events, interspersed with

7

highly weathered soil profiles. Pearce (2002) also identified major fault zones withinthe profile, and has proposed that the basalt pile behaves as an unconfined aquifer.Hydraulic conductivity values for the basalt aquifer system vary from 0.1 – 104m/day and specific yields from 1 – 20 %, with an average specific yield of 6.4 %(Pearce & Durick 2002).

The first detailed examination of the groundwater resources in the region wasundertaken by Leach (1986), who examined the Atherton basalt aquifer systemwithin the Atherton Shire. Leach (1986) observed that the basalt is up to 120 mthick, and characterized the aquifer system into two aquifer zones, a highlyweathered, vesicular upper aquifer, and an older, denser, unweathered to slightlyweathered underlying basalt aquifer. Transmissivity and storativity values werecalculated by Leach (1986), as well as an average storage volume for the basaltswithin the Atherton Shire.

An assessment of the physical features of volcanism in the Atherton Basalt Provincein relation to groundwater occurrence was undertaken by Buck (1999). Thisincluded an examination of the general geology and volcanology of the area,examination of the geomorphological structures within the region and mapping of thebase of the volcanic pile. Based on a lineation analysis, surface and basementgeomorphological investigations, geophysical observations, borehole investigationsand field mapping, Buck (1999) proposed that volcanism in the area is structurallycontrolled and, based on the tectonic setting and the type and style of volcanicactivity, that a comparable basalt field is the South Auckland Volcanic Field, NewZealand (Briggs et al. 1994).

Based on laboratory geochemical work and petrographic microscope analyses,Sheldrick (1999) observed that the volcanic rocks of the Atherton region arepredominantly olivine tholeiites, alkali olivine basalts and basanites. The textures ofthe basaltic rocks range from highly porphyritic to aphyric; they generally show anintergranular texture characterized by small pyroxene and opaque minerals, andassociated olivine coexisting with plagioclase in the groundmass. Pyroclasticdeposits are found throughout the study area, and are classified as crystal-rich ashes,and ultramafic xenoliths found in scoria deposits are harzburgites (Sheldrick 1999).

Using aeromagnetic, ground magnetic and magnetic susceptibility methods, Moloney(1999) inferred that the volcanic activity in the area appears to have been localized,and influenced by pre-existing basement faults. Ground magnetic data was used todefine the aerial extent of the volcanic formations in the region, and magneticsusceptibility measurements used to identify paleo-weathering surfaces within thevolcanic pile (Moloney 1999).

The hydrogeology of the northern part of the Atherton Basalt Province was examinedby Bean (1999), with the aim of developing a conceptual hydrogeological model forthe basalt aquifers in the main irrigation area. The study was based on water levels,pump tests, borelogs and physico-chemical data. Bean (1999) proposes that therewere at least three phases of volcanism, with the end of each phase being defined bya weathering surface, and that re-activation of pre-existing basement structures hasresulted in hydraulic connection throughout the basalt pile. Bean (1999) observed

8

that the basalt thickness in the northern irrigation area is generally between 70 and90 m (with a maximum of 130 m), that the basalt aquifers are heterogeneous andanisotropic in character and recharged locally, and that the piezometric surfacereflects the surface topography. Bean (1999) also proposes that field pH and EC canbe used to distinguish between basalt- and basement-derived groundwaters, and thatratios of aqueous HCO3

- / Cl- can be used to confirm hydraulic flow paths whereminimal water level data is available.

The age of the Atherton Tablelands groundwaters have been estimated by Cook et al.(2001) to range from 5 to 30 years based on a CFC-11 (chloroflurocarbon) datingmethod, and recharge across the Tablelands has been estimated using a chloride massbalance approach. Radon concentrations in the groundwaters indicate that flow ratesdecrease with depth, and that there is an active upper flow zone of approximately30 m thickness (Cook et al. 2001). Stable isotope and chloride concentrations ofstream waters in the area are similar to concentrations in the groundwaters, indicatingthat most of the river flow is from groundwater inflows, rather than surface runoff;thus, groundwater extraction, particularly during the dry season, has the potential toimpact on ecosystems dependant on these stream waters (Cook et al. 2001).Groundwater ages for the Atherton Tablelands have also been estimated by Herczeg(2001) based on HCO3

- concentrations using a model based on weathering rates,porosity and mean grain size; residence times were calculated to be between 5 to 120years.

Earlier studies of the Atherton Tablelands include assessments of Cainozoicvolcanism in the region, geological and soil mapping and some investigations ofgroundwater resources.

A review of Cainozoic volcanism in north-eastern Australia (Stephenson et al. 1980)covered 12 volcanic provinces in the region, including the Atherton Tablelands area.The review includes some useful information on basaltic petrology and rockgeochemistry, age determination, vent distribution and structural relationships for thearea. Petrological and geochemical descriptions of some basaltic rocks from theAtherton Tablelands were also provided by Morgan (1968). The regional geologywas summarised by Best (1960, 1962), and a review of available information on theAtherton basalts completed by Bedford (1983). A summary account of the AthertonVolcanic Province and possible courses for some lava flows in the region weresketched by De Keyser and Lucas (1968), Blake (1972) and Stephenson and Griffin(1976). The development of maars and the morphology of Lakes Eacham andBarrine are discussed by Timms (1976).

The general nature of soils developed in the Atherton Tablelands region has beenoutlined by Isbell et al. (1968), and the red and brown basaltic soils that occur in theregion described in some detail by Isbell et al. (1976, 1977). Soil mapping,including references to source rock, has been conducted in the region (Malcolm &Nagel 1997) as well as a soils and agricultural land suitability assessment (Malcolmet al. 1999). An assessment of the mineralogy of the soils on basalt in NorthQueensland by Simonett and Bauleke (1963) found that weathering intensityincreased with increasing rainfall. Poorly crystalline kaolinite is the dominant claymineral in these soils; halloysite may be present in high rainfall areas; gibbsite

9

content increases with increasing rainfall; the content of iron oxides such as hematiteand goethite also increase modestly with increasing rainfall; magnetite, ilmenite andtitanomagnetite may also be present (Simonett & Bauleke 1963).

Some assessments of groundwater resources in the Atherton Tablelands area havebeen undertaken by the Queensland Water Resources Commission (formerly theIrrigation and Water Supply Commission, and now QDNR&M). A description ofthe geology of the area and summary of the history and other details of existing wellswere provided by Gloe (1949), following an apparent decline in well water levelsduring 1947 and 1948. Results of a groundwater drilling program in the early 1950’sare outlined by O’Shea (1954). A broad outline of the groundwater resources inNorth Queensland, including a brief mention of the basalts in the Atherton region, isprovided by McEniery (1980). A groundwater investigation in the adjoiningMulgrave River region (Muller 1978) provides some information on groundwateryields for other rock units also present in the study area. An investigation of thegroundwater occurrence and chemistry of the Hodgkinson Formation(metamorphics) in the Cattle Creek catchment, north-west of the Atherton study areawas completed by Lait (1998).

Basalt aquifer systems

BACKGROUND

Basalt is an igneous rock formed by the solidification of molten material (magma) atthe earth’s surface. The minerals comprising basalt are predominantly the silicate(Al-Si) group of minerals, composed of combinations of silica tetrahedra in, forexample, linear forms (e.g. pyroxene) and individual tetrahedra (e.g. olivine)(Deutsch 1997). The feldspars, such as albite (NaAlSi3O8) and anorthite(CaAl2Si2O8) plagioclase feldspars, which form a solid solution subdivided into sixmineral species, are tektosilicates composed of a three-dimensional network of silicatetrahedra (Faure 1998). Non-crystalline solids such as glass may also be present inbasalt. A compilation of the chemical compositions of igneous rocks by Turekianand Wedepohl (1961) and Vinogradov (1962), presented by Faure (1998), showsbasalt composition (including both volcanic and plutonic rocks of basalticcomposition) as 23.5 % Si, 8.6 % Fe, 8.28 % Al, 7.2 % Ca, 4.55 % Mg, 1.87 % Naand 0.83 % K. Average concentrations of some other elements include 11 400 ppmTi, 1750 ppm Mn, 1130 ppm P, 452 ppm Sr, 385 ppm F, 315 ppm Ba and 300 ppm S(Faure 1998).

A common mode of occurrence of basalt aquifer systems is as lava flows interbeddedwith weathered and pyroclastic material and sediments. The main features of suchaquifer systems are vesicles, fractures and interflow sediments (Singhal & Gupta1999). Basalt aquifers are, as a result, commonly described as having dual porosity.The porosity, permeability and groundwater flow characteristics of fractured rocks ispoorly understood (Singhal & Gupta 1999). The porosity of unfractured volcanicrock varies from less than 1 % in dense basalt to more than 85 % in pumice(Schoeller 1962). Typically, dense basalt will have 1 – 10 % porosity and vesicularbasalt 10 – 50 % porosity (Davis & DeWiest 1991). The main flow paths in basalt,

10

however, are largely a function of other primary and secondary features, such asjoints, fractures, shear zones, faults and other discontinuities (Ecker 1976; Davis &DeWiest 1991; Barnes & Worden 1998; Singhal & Gupta 1999). Auto-brecciationof top and bottom surfaces of lava flows, for example, produces blocky tops andbases to lava flows, providing permeable pathways for groundwater flow (Davis1969; Uhl 1979; Mazor 1997; Singhal & Gupta 1999).

Volcanic rocks are generally highly susceptible to weathering, particularly in tropicaland subtropical environments (Singhal & Gupta 1999). Weathering developssecondary porosity, opening pre-existing fractures and producing pathways that aremore pervious to fluid flow (Davis 1969; Domenico & Schwartz 1998). Forexample, the Columbia River Basalts of the U.S.A. consist of numerous basalt flows,with occasional interbedded sand and gravel units (Domenico & Schwartz 1998).Each basalt layer was affected by weathering processes, which were terminated bythe emplacement of subsequent lava flows. Weathered profiles at he top of lavaflows constitute major pathways for groundwater movement (e.g. Druecker & Fan1976; Freeze & Cherry 1979 Jalludin & Razack 1994) in addition to cooling joints,fractures and vesicles (Hearn et al. 1985). Weathering features, such as highlyweathered basalt, palaeosols, as well as silty to gravelly sediments, have also beenobserved between lava flows in the Tertiary intraplate continental basaltic field of theAtherton Basalt Province (Bean 1999; Buck 1999), within which the study area islocated.

Groundwater in basalt aquifer systems can occur under perched, unconfined andconfined conditions. Localized perched aquifers, for example, are present in theAtherton Tablelands region, due to the occurrence of impervious formations, such asash beds and dense basalt flows above the regional aquifer. On a regional scale,however, hydraulic connection throughout the basalt pile, which may have developeddue to re-activation of pre-existing basement structures, and localized rechargeacross the area, has resulted in regionally unconfined aquifer conditions (Bean 1999).Confined conditions can also be created where vesicular or fractured basalt is locatedbetween massive basalt units (e.g. Singhal 1973).

The features that impart porosity and permeability to basaltic rocks are outlined byStearns (1942), Davis (1969), Davis and DeWiest (1991) and Singhal and Gupta(1999). They include scoriae, breccia zones between flows as discussed above,cavities between pahoehoe lava flows, shrinkage cracks, gas vesicles, lava tubes, treemoulds, and fractures and lineaments. Several of these features have been observedin the basaltic rocks of the Atherton Tablelands region, as discussed by Buck (1999).Dykes and sills can be barriers to groundwater flow, particularly if they are morethan several metres thick (Davis & DeWiest 1991; Bromley et al. 1994; Singhal &Gupta 1999); however, sills and dykes are not significant features of the AthertonTablelands. On a large scale the permeability of basalt is very anisotropic (Freeze &Cherry 1979). Horizontal hydraulic conductivity is generally several times greaterthan vertical hydraulic conductivity, due to the presence of interflow spaces andhorizontal fractures (Peterson 1972; Davis & DeWiest 1991; Singhal & Gupta 1999).Groundwater flow in the Atherton Tablelands region, for example, is stronglyanisotropic in the direction of groundwater flow, with the vertical component of flowconsiderably less than the horizontal component (Buck 1999).

11

Infilling of vesicles and fractures by secondary minerals, such as zeolites, calcite,secondary silica and clays, can lead to decreasing porosity and hydraulicconductivity of basaltic rocks with geological age or degree of weathering (Davis1974; Ecker 1976; Singhal & Gupta 1999). A lower permeability of weatheredvolcanic rocks compared to unweathered rocks on the island of Oahu in Hawaii, forexample, was reported by Oki et al. (1998), although weathered basalts can also formefficient aquifers (e.g. Deolankar 1980). Infilling of vesicles with zeolites and clayshas been observed in basalt chips taken from bores in the Atherton – Tolga – Kairiarea, and in basalt boulders across the Atherton Tablelands, by the author and byBean (1999) and Buck (1999). Singhal and Gupta (1999) also note that recharge tovolcanic aquifers is generally higher in younger volcanics, as the weathering effectsand lower permeability of older volcanics results in high runoff.

The landforms and drainage patterns typical of volcanic terrain are discussed bySinghal and Gupta (1999), and by Buck (1999) specifically in relation to the studyarea. Some examples of basalt aquifer systems are discussed below.

COLUMBIA RIVER PLATEAU

Plateau basalts, also known as continental flood basalts, usually consist of a numberof flows of varying thickness superimposed on each other; the thickness of individuallayers ranges from less than 1 m to 30 m, most being 10 to 30 m (Singhal & Gupta1999). The Columbia River and Snake River basalts in the north-western part of theUnited States are examples of plateau basalts; they occupy an area of more than200 000 km2 covering the states of Washington, Oregon and Idaho. The generallyflat-lying and dense basalt sequence (composed of between 120 to 150 individualflows), is of Miocene to Quaternary age (17.5 – 6 Ma), reaches a maximum thicknessof 1500 m in the central part of the basin and has an average total thickness of about550 m, with extensive river – deposited sediments between many of the basalt flows(Freeze & Cherry 1979; Shelton 1983; Hearn et al. 1990; Singhal & Gupta 1999). Asummary of the formation of the Columbia River basalts is given by Hooper (1982).The basalt aquifers of the Columbia Plateau are an important source of water foragricultural, domestic and municipal uses (Hearn et al. 1985).

The Columbia River Basalt Group lavas are classified as tholeiites and consistpredominantly of plagioclase feldspar, pyroxene and opaque metal oxides, withaccessory minerals such as apatite, olivine and Fe- and Ti-oxides (Deutsch et al.1982). Secondary minerals formed at relatively low temperatures (< 100 °C), suchas smectite (primarily nontronite), the zeolite clinoptilolite, iron oxide and variousforms of silica, are found in the fractured and vesicular zones of the basalt flows,which are the major paths of groundwater flow (Hearn et al. 1985). Groundwaterflow through the basalt tends to parallel the flow units because the most permeableparts of the lava flows are generally along the fractured contact zones between thelava flows (Deutsch et al. 1982). The composition of groundwaters from theColumbia Plateau basalts is discussed by Newcomb (1972), and by Deutsch et al.(1982) for the eastern Washington area, with an emphasis on the solubility controlson the water composition.

12

DECCAN BASALTS

The Deccan Traps of India, of Upper Cretaceous to Eocene age (65 – 60 Ma), whichhave a maximum thickness of about 1500 m, are also an example of a major plateaubasalt province (Singhal & Gupta 1999). The Deccan Volcanic Province comprisesgenerally flat-lying basaltic flows (from a few metres to 50 m thick) in a multiaquifersystem separated by thin impervious tuffaceous layers referred to as “red beds”(Pawar & Shaikh 1995; Singhal & Gupta 1999). The Deccan basalts of western andcentral India cover an area of over 500 000 km2 and form an important source ofwater supply (Kulkarni & Deolankar 1993). The Deccan basalts tend to be eithervesicular – amygdaloidal type basalts or finer grained dense basalts (Athavale et al.1983; Kulkarni & Deolankar 1993). The occurrence of groundwater in the basaltaquifers is controlled by the degree of weathering and jointing, the presence ofvesicles, interconnection between vesicles by fissures and cracks, and intertrappeans(interflow sedimentary deposits) (Pawar 1993; Singhal & Gupta 1999). Thehydrogeology of the Deccan basalts is described by Lunkad and Raymahashay(1978), Athavale et al. (1983), Uhl and Joshi (1986), Kulkarni and Deolankar (1993)and Narayanpethkar et al. (1994).

The basaltic rocks of the Deccan Plateau consist of predominantly augite and calcicplagioclase feldspars, with minor olivine. The weathering products arepredominantly kaolinite, bauxite or laterite under extreme leaching conditions, andmontmorillonite and minor kaolinite and illite under more moderate leachingconditions (Ratha & Sahu 1993). Groundwater in parts of the Deccan basalts, whichis heavily exploited, is affected by agricultural pollution. The impact of irrigationand fertilizers on the quality of groundwater in a small watershed of the Deccan TrapHydrologic Province is discussed by Pawar and Shaikh (1995).

Other examples of plateau basalts include the extensive Early Jurassic (190 Ma)basalts of the Karoo Province, South Africa, which cover an area of around3 × 106 km2, the Middle Paleozoic to Mesozoic basalts of the Siberian Traps, Russia,which cover an area of around 1.5 × 106 km2, and the Lower Cretaceous (140 –120 Ma) Parana Volcanics of Brazil (900 000 km2) (Singhal & Gupta 1999).

OTHER BASALT AQUIFERS.

Other basalt aquifer systems include the Middle Tertiary basalts, which form part ofan extensively exploited aquifer system within the Basin of Mexico, and belong tothe Mexican Trans-volcanic Belt (Edmunds et al. 2002). Groundwater from thegranular and fractured volcanic units supplies about 70 % of the total water suppliesof Mexico City (Edmunds et al. 2002). Due to the declining water levels andsubsequent land subsidence, as well as the potential for contamination, the hydrologyand hydrochemistry of the aquifers have been investigated by several workers(e.g. Mazari & Mackay 1993; Birkle et al. 1998).

Some other examples of basalt aquifer systems include the Gedaref basin in easternSudan, which is in part filled with Tertiary basalt lava flows and supplies water to anagricultural centre of grain production (Hussein & Adam 1995), basalts of the

13

Ethiopian Rift Valley (McKenzie et al. 2001), plateau basalts in north-eastern Jordan(Lloyd 1965; Abu-Jaber 20001) which store predominantly Na-HCO3 type watersthat are probably transmitted through fracture zones, highly vesicular zones andinter-flow alluvium (Lloyd 1965), the lavas and pyroclastic deposits of theKumamota Plains, located on the west side of Mount Aso Volcano, southern Japan(Mahara & Igarashi 1993), and the basalts of the Blackburn Hills volcanic field ofwestern Alaska (Moll-Stalcup & Arth 1991).

BASALTIC OCEANIC ISLANDS

The basaltic oceanic islands are associated with both intraplate and plate marginvolcanism and are generally comprised of large, gently-dipping shield volcanoes.Basaltic oceanic islands include both high islands (e.g. Hawaiian Islands) and lowislands (e.g. Cook Islands). Basalt flows are usually thin (6 m or less), and their highpermeability is mostly due to clinker zones in the aa type flows, lava tubes and gasvesicles in the pahoehoe flows, columnar joints and irregular openings (Peterson1984). Ash beds can form confining layers (Singhal & Gupta 1999).

Young basaltic lavas, such as those found typically in the Hawaiian Islands, FrenchPolynesia, and parts of Samoa, are extremely permeable; older lavas that containmore pyroclastic material, such as on the islands of Yap, Truk and Pohnpei in PacificMicronesia are poorly permeable and the most productive aquifers are sedimentaryalluvial deposits and weathered lavas (Peterson 1993). Examples of oceanic islandbasalt aquifer systems also include, for example, the basaltic rocks of the volcanicmassifs of the island of Réunion in the western Indian Ocean, east of Madagascar(Join et al. 1997; Louvat & Allègre 1997) and the fractured volcanic aquifers onTenerife, the largest of the Canary Islands in the Atlantic Ocean (Ecker 1976).Development of groundwater resources on these islands is commonly hampered bysalt-water intrusion. The hydrogeology of volcanic ocean islands is described byPeterson (1972, 1993).

The intraplate Hawaiian Islands consist of six major populated islands and numerousother small islands, formed by extrusion of basaltic lavas as the Pacific Plate movedover the Hawaiian hotspot (Peterson 1993). The largest of the islands, Hawaii,comprises five major shield volcanoes, Kohala, Mauna Kea, Hualalai, Mauna Loaand Kilauea. The basaltic lavas are very permeable due to their young age and thethinness of individual flows (Peterson 1993). The chemical quality of groundwateron five of the Hawaiian islands is described by Swain (1973). The hydrogeology andhydrochemistry of the Puna District, located on the east and south-east slopes ofKilauea Volcano and on the east slope of Mauna Loa Volcano, are described byDruecker and Fan (1976). The groundwater in the Puna District occurs as perched,dyke or basal water and is of Na,Ca-HCO3 or Na,Mg-HCO3 type, and in coastalareas, influenced by seawater intrusion (Druecker & Fan 1976). The hydrogeologyof the basalt aquifer systems on the island of Oahu is described by Visher and Mink(1964), Takasaki and Valenciano (1969), Rosenau et al. (1971) and Oki et al. (1998).

14

AUSTRALIAN BASALT AQUIFER SYSTEMS

During the Cainozoic there was widespread basaltic igneous activity in easternAustralia along and adjacent to the Eastern Highlands, that resulted in the formationof more than fifty recognized igneous provinces (Wellman & McDougall 1974).Price et al. (1997) notes that since the time of continental break-up and extendingover an interval of at least 60 Ma, the south-eastern Australian margin has been thesite of intermittent intraplate volcanism (the Atherton Basalt Province being anexample of this as discussed above). The magmas that formed the igneous provincesof eastern Australia are thought to originate from a magma source or sources, with alimited latitudinal extent, within the asthenosphere; migration is considered to berelated to the movement of the Indian (Australian) lithospheric plate relative to theunderlying asthenosphere (Wellman & McDougall 1974). Various models for thegeneration of the eastern Australian basalts are also discussed by McDonough et al.(1985), Ashley et al. (1995), Price et al. (1997), Stephenson et al. (1998) andSutherland (1998).

The Newer Volcanics Province of western Victoria and south-eastern SouthAustralia comprises Late Tertiary to Quaternary basalts (dominated by tholeiitic andtransitional basalts with alkalic rock types and basaltic icelandites (SiO2 > 52 %)being less common), which were emplaced as extensive lava flows, scoria cones,small shield volcanoes and maar deposits over an area of 15 000 km2 (Price et al.1997). Fractures in the basalt constitute the primary pathways for groundwater flowin the Newer Volcanics basalts. Groundwater from these basalts is used for stockwatering, irrigation and domestic purposes, and contributes to water supplies for thetowns of Penshurst, Dunkeld, Caramut, Mortlake, Streatham and Skipton (Kiernan etal. 2002). The hydrogeology and the hydrochemistry of these basalts are described,for example, by Riha and Kenley (1978) and Finegan (1994). The chemicalevolution of the groundwaters in the Tertiary basalts of Victoria has also beenstudied by Komarower and Wall (1981). The groundwaters in this temperate climate(annual rainfall ~ 800 mm) are more saline than those of the Atherton Tablelandsregion, with total dissolved solids in the range 1000 – 10 000 mg/L; theircompositions are attributed to the weathering of feldspars to beidellite clays(Komarower and Wall 1981).

Tertiary olivine basalt at one time covered large areas in east-central Queensland andis extensively preserved near Clermont, Emerald, Springsure and Rolleston in aregion known as the Central Highlands (Gunn 1974). The prolonged volcanicactivity during the middle Tertiary also resulted in several basaltic occurrences insouth-eastern Queensland. The greatest area and thickness of material accumulatedin the McPherson Ranges, eastern Darling Downs and Bunya Mountains; smallerareas of basalt are found at Tamborine Mountain, Bundamba, Cooper’s Plain,Archerfield, Redland Bay, Burleigh, Buderim, Black Mountain, Cooran andPinbarren (Ferguson 1954a). The composition of groundwaters contained within theTertiary basalts at Ormiston, south-east of Brisbane, is described by Barclay (1997)in relation to weathering and recharge processes and surface and salt-water mixing.

15

Processes controlling groundwater composition

BACKGROUND

The primary controls on the dissolved constituents in groundwater are the originalchemical character and temperature of the water as it enters the zone of saturation,the distribution, solubility and exchange capacity of the rock minerals, the porosityand permeability of the aquifer, and the flow path of the water (Back & Hanshaw1965; Freeze & Cherry 1979; Appelo & Postma 1996; Mazor 1997). Theseprocesses by which groundwater attains its chemical character have beeninvestigated for the basalt aquifer system of the Atherton Tablelands, NorthQueensland.

The concentration of dissolved and undersaturated ions in groundwater is generallyconsidered proportional to the length of the flow path and the residence time of thegroundwater. Rapidly moving groundwater is likely to have lower concentrations ofions than slowly flowing groundwater over an equivalent distance through anequivalent aquifer matrix (e.g. Chebotarev 1955; Back 1966; Back & Hanshaw 1970;Palmer & Cherry 1984; Tóth 1984; Herczeg et al. 1991).

The chemical character of groundwater is related to the time of contact betweengroundwater and the type and solubility of aquifer minerals as well as other factors,such as the amount of dissolved carbon dioxide present, the amount of aquifersurface area in contact with the hydraulically effective pore volume, the temperateand the reaction rate (Claassen & White 1979). Groundwater chemically evolvessystematically along flow paths in the subsurface given sufficient water residencetime (Paces 1976; Wallick & Tóth 1976; Tóth 1984; Veeger 1996; Jankowski &Acworth 1997). The spatial distribution of chemical species may therefore be usedto infer the direction of groundwater movement (e.g. Love et al. 1993; Schreiber etal. 1999; Stuyfzand 1999).

A hydrochemical classification scheme was developed by Szczukariew andPriklonski in 1955, in which groundwater types are classified based on theconcentrations of the major ions constituting greater than 20 % of the total anionsand cations (Alekin 1970). The concept of ‘hydrochemical facies’ was laterdeveloped by Back (1960, 1961, 1966), Morgan and Winner (1962) and Seaber(1962) to describe cation and anion concentrations within defined compositioncategories (Freeze & Cherry 1979). The trilinear or Piper diagram (Piper 1944) canbe used to define hydrochemical facies, as proposed by Back (1961) and Back andHanshaw (1965). Hydrochemical facies reflect the effects of chemical processes inthe lithological environment and the prevailing groundwater flow patterns (Back &Hanshaw 1965). It should be noted, however, that the classical hydrochemicalevolution proposed by Chebotarev (1955) has limited relevance to silicate rockaquifer systems, as chloride and sulfate ions are not significant constituents in silicaterocks, and therefore, there is no development towards chloride and sulfatehydrochemical facies in these rocks (Freeze & Cherry 1979).

16

Among rocks of volcanic origin, basalts are particularly sensitive to chemicalweathering (Berner & Berner 1996). Chemical processes controlling thecomposition of groundwater, such as dissolution, hydration, hydrolysis, oxidation –reduction reactions, direct attack by acids on the rocks, chemical precipitation ofminerals, ion-exchange reactions and concentration by evaporation and transpiration,are discussed by Hem (1985) and Tóth (1984, 1999).

The natural processes that influence the composition of groundwaters in basaltaquifers include production of carbonic acid, mineral dissolution and weathering,oxidation and reduction reactions, ion-exchange and sorption, and evaporation.Decay of organic matter is also an important process particularly with respect to theproduction of carbon dioxide. The selective uptake of ions and / or leaching of ionsfrom vegetation may also influence groundwater composition. These aspects arediscussed with respect to the general concept, and in relation to the study area.

CARBON DIOXIDE IN WATER

The chemical evolution of groundwater begins when rain water infiltrates the soil.Carbon dioxide present in the atmosphere dissolves in rain water and forms aqueousCO2, which associates with water molecules to form carbonic acid, H2CO3, as shownin Equation 1. Carbonic acid, a weak acid, tends to dissociate into hydrogen,bicarbonate and carbonate ions (Johnson et al. 1977; García et al. 2001) in two steps(Equations 2 and 3), releasing one proton in each step (Appelo & Postma 1996;Deutsch 1997; Domenico & Schwartz 1998).

3222(aq) COHOHCO →+ (1)

6.31

332

10

HCOHCOH−

−+

=

+→

K(2)

10.32

233

10

COHHCO−

−+−

=

+→

K(3)

In the absence of other acids or bases, equilibration with atmospheric CO2 results inslightly acidic conditions in open systems (García et al. 2001). Based on the present-day atmosphere CO2 pressure of 10-3.5 atm, unpolluted rain water is slightly acidicwith a pH value of 5.6 (Appelo & Postma 1996). The distribution of CO2 species inwater as a function of pH is described by Appelo and Postma (1996). At differentpH values, different species of CO2 are dominant according to the dissociationconstants, K, noted above. Carbonic acid is dominant at pH < 6.3, CO3

2- becomesdominant at pH > 10.3, and at intermediate pH values HCO3

- is the major CO2

species in water (Appelo & Postma 1996).

The decay of organic matter, an oxidation reaction that may occur in soil and alsowithin aquifers where fossil organic matter may be present, and the respiration ofplant roots, also produce CO2 (Witkamp & Frank 1969; Mazor 1976; Freeze &

17

Cherry 1979; Buyanovsky & Wagner 1983; Solomon & Cerling 1987; Herczeg &Payne 1992; Appelo & Postma 1996; Mazor 1997; Andrésdóttir & Arnórsson 1999;Berner 1999), as shown in Equation 4:

2(g)222 COOHOOCH +→+ , (4)

where a carbohydrate, CH2O, is used as a simplification for organic matter.

In general, the waters that enter igneous rocks from the soil zone have a CO2 content10 to 100 times higher than that expected from equilibrium with the earth’satmosphere (Feth et al. 1964), that is, the pressure of CO2 in soils is commonly 10-1.5

to 10-2.5 atm (Appelo & Postma 1996). Temperature increases CO2 production in soil(Harmon et al. 1975; Drake & Wigley 1975; Brook et al. 1977; Drake 1983).Moisture conditions, microbial activity, availability of organic matter and soilstructure are also important factors controlling biological activity, and therefore theproduction of CO2 (Freeze & Cherry 1979). A map of world CO2 pressure in soil(Brook et al. 1983) indicates that some of the highest soil CO2 pressures are found inNorth Queensland.

Production of CO2 can also occur in subsoil vadose zones and shallow saturatedzones (e.g. Thorstensen et al. 1983; Wood & Petraitis 1984; Keller 1991). Thegeneration of CO2 in the subsurface has been attributed to organic substrates(e.g. Chapelle & Knobel 1985; McMahon et al. 1990) and microbiologicalcommunities (e.g. Chapelle et al. 1987; Ghiorse & Wilson 1988; Bennett & Rogers2000).

The production of CO2 and H2CO3, and the release of H+ ions to solution areimportant initial processes for water – rock interaction (Paces 1972; Berner 1999).The rain water that infiltrates the soil and bedrock is low in dissolved solids, slightlyacidic and is undersaturated with most, if not all, common minerals (Arnórsson1999). Weathering processes then release ions to solution. Weathering processes arecommonly grouped into three broad categories: physical (or mechanical), chemicaland biological. While these processes are active in all climatic environments,physical weathering tends to be dominant in cold and arid climates, and chemicalweathering is dominant in warm and humid climates (Larsson 1984). Chemicalweathering processes are considered to be the most significant natural processescontrolling the composition of the Atherton Tablelands groundwaters; they arediscussed below.

SILICATE MINERAL DISSOLUTION AND WEATHERING

The effect of silicate mineral weathering on groundwater chemistry tends to be lessapparent than the dissolution of carbonate minerals, for example, due to the generallyslow weathering rate of silicate minerals (Appelo & Postma 1996; Tóth 1999). Theweathering of silicate minerals, however, is estimated to contribute about 45 % of thetotal dissolved load of the world’s rivers (Stumm & Wieland 1990; Stumm &Wollast 1990), and Appelo and Postma (1996) note that silicate mineral weatheringis an important buffer mechanism against acidification of soil and groundwater. On

18

a geological time scale, silicate mineral weathering is one of the most importantsinks for atmospheric CO2 (Berner et al. 1983; Stumm & Wieland 1990; Taylor et al.1999). The amount of CO2 consumption during weathering also varies depending onthe type of siliceous rock. Taylor et al. (1999), for example, estimate that basaltweathers twice as fast as granite, and that CO2 consumption resulting from basaltweathering is almost three times greater than during the weathering of granite, due tothe higher Ca2+ and Mg2+ concentrations in basalt.

Igneous rocks such as basalt contain appreciable amounts of aluminosilicateminerals, which form at temperatures far above those near the land surface. Theseminerals are therefore thermodynamically unstable, and dissolve, or weather to claysand oxides when in contact with water (Freeze & Cherry 1979; Deutsch 1997). Thedistribution of primary silicate minerals during weathering was observed by Goldich(1938), who showed that the susceptibilities of silicate minerals to weathering couldbe related to their position in Bowen’s (1928) reaction series shown in Figure 1.Olivine is considered the most easily weathered silicate mineral, and quartz as themineral most resistant to weathering (Goldich 1938). In a chemical weathering studyof basalts and andesites, Colman (1982) similarly found the susceptibility of variousminerals to weathering in the sequence: glass > olivine > pyroxene > amphibole >plagioclase > K-feldspar, but with some variability, which is consistent with thedissolution susceptibility calculated by Aiuppa et al. (2000) for the Mount Etnabasalts. In a study of the weathering of some eastern Australian basalts, Eggleton etal. (1987) observed the susceptibility series: glass ~ olivine > plagioclase > pyroxene> opaque minerals. The order of plagioclase and pyroxene susceptibility found in thework of Eggleton et al. (1987) is the reverse of that commonly described(e.g. Loughnan 1969). Eggleton et al. (1987) note that although plagioclase began toalter earlier than pyroxene, once started, pyroxene weathered relatively quickly, andwas completely altered before plagioclase; consequently, plagioclase started toweather earlier than pyroxene, but persisted longer.

Figure 1. The Goldich (1938) weathering sequence.

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Secondary minerals, such as clays (e.g. kaolinite and montmorillonite) and Al- andFe-oxides (e.g. gibbsite, goethite and hematite), are formed during silicate mineralweathering processes (e.g. Carr et al. 1980). These clays and oxides form byincongruent dissolution of aluminosilicate minerals, whereby the ratio of theelements that appears in solution is different to that in the dissolving mineral(Loughnan 1969; Freeze & Cherry 1979; White & Claassen 1979; Holdren & Speyer1986; Appelo & Postma 1996; Aiuppa et al. 2000; Négrel & Lachassagne 2000).The removal of dissolved constituents by the precipitation of secondary mineralsensures that the water remains undersaturated with respect to the primary minerals;the primary minerals, therefore, continue to dissolve and secondary mineralsprecipitate (Arnórsson 1999). A general reaction (Garrels & Mackenzie 1967;Bricker et al. 1968; Sarin et al. 1989; Singh & Hasnain 1999; Négrel & Lachassagne2000; Das & Kaur 2001) for the weathering of silicate rocks with carbonic acid isshown in Equation 5:

productssolidKMgCaNaHCOSiOHCOHsilicateK)Mg,Ca,(Na, 34432 ++++++→+ (5)

In silicate weathering reactions, sodium is mainly derived from Na-feldspars such asalbite (NaAlSi3O8), or any member of the plagioclase solid solution series betweenalbite and anorthite (i.e. the Ca-feldspar, CaAl2Si2O8) (Appelo & Postma 1996;Négrel & Lachassagne 2000). Clay minerals may also release exchangeable sodium(Renick 1924). Calcium is released during plagioclase weathering, and calcium andmagnesium from the weathering of pyroxenes such as augite ([Ca1.5MgAl0.3Si1.7]O6).Magnesium is also released to solution by the dissolution of olivine, as shown inEquation 6, and can also be derived from the weathering of biotite and amphiboles.Potassium concentrations in basalt groundwaters are typically low due to the verysmall percentage of potassium in the composition of basaltic rock (Wood & Low1986).

−

++→++ +34422242 HCO4SiOHMg2OH4CO4SiOMg (6)

Weathering reactions for some primary minerals commonly found in basalt arepresented in Equations 7 – 9, with the clay mineral kaolinite as the weatheringproduct. Kaolinite is commonly the dominant alteration product of aggressive waterattack on silicate minerals (Garrels 1967).

Albite → Kaolinite

−

+++→++ +34445222283 HCO2SiOH4Na2)OH(OSiAlOH11CO2ONaAlSi2 (7)

Anorthite → Kaolinite

−

++→++ +3

2452222822 HCO2Ca)OH(OSiAlOH3CO2OSiCaAl (8)

20

Augite → Kaolinite

[ ] →++ OH5.4CO4.3OSiAlCaMg 2267.16.07.0

−++ ++++ 34422

4522 3.4HCOSiO1.1H0.7MgCa(OH)OSi0.3Al (9)

Other minerals, such as montmorillonite and gibbsite, can also form as silicateweathering products, as shown in Equations 10 and 11 for the weathering of the Na-feldspar albite:

Albite → Na–montmorillonite

4421045.05.15.022

83 SiOHNa2)OH(OSiMgAlNa2OH4MgONaAlSi3 ++→++ ++ (10)

Albite → Gibbsite

−+ +++→++ 34432283 HCOSiOH3NaAl(OH)O8HCOONaAlSi (11)

In the case of montmorillonite, magnesium is assumed to be derived from theweathering of pyroxenes such as augite, as shown in Equation 9. As can be seen inEquations 7 – 11, aluminium remains conserved in the solid phase, and the maineffects of silicate mineral weathering on groundwater composition are an increase incations, silica and bicarbonate, and a decrease in hydrogen ion concentrations. As allsilicate mineral weathering reactions consume acid, there is a pH buffering effect(Appelo & Postma 1996). The increase in cation concentration, accompanied byincreases in pH and bicarbonate concentration, can lead to the precipitation ofcarbonate minerals, such as calcite and dolomite, in igneous rocks (Garrels 1967;Gunn 1974; Uhl & Joshi 1986; Wood & Low 1986; Appelo & Postma 1996;Houston & Smith 1997; Arnórsson 1999) as discussed in PAPER 3. Folk and Land(1975) and Faure (1998) note, however, that although an aqueous solution may besupersaturated with respect to dolomite, precipitation of this mineral requiresparticular conditions in terms of the salinity and the Mg2+ / Ca2+ ratio of the solution.

The highest concentrations of silica in groundwater tend to be found in volcanicrocks, such as basalt, which contain more reactive minerals than rocks such asgranite or schists (Garrels 1976; Appelo & Postma 1996; Langmuir 1997). Thischaracteristic was noted in a comparison of the groundwater compositions frombasalt and basement rock aquifers in the study area (PAPER 2). In a study ofadjacent basalt and granite drainage systems in Idaho, U.S.A., Taylor et al. (1999)similarly found that silicon fluxes from the basalt basins were more than doublethose from the granite. A high silica content is also found in the groundwaters of theKaroo sandstone aquifer and overlying basalt in western Zimbabwe, and is attributedto the weathering of mafic minerals in the basalt (Larsen et al. 2002).

Silica is most likely present as monomeric silicic acid (or monosilicic acid), H4SiO4,in the normal temperature and pH ranges of natural water (Krauskopf 1956; Davis &DeWiest 1991; Faure 1998), as shown in Equations 6 and 7 and Equations 9 – 13. If

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the solution becomes saturated, silica tends to polymerise as a colloid (Krauskopf1956; Klein 1971). This amorphous silica may settle as a gelatinous precipitate(Krauskopf 1956; Iler 1979), which may later form opal A and opal CT (naturallyoccurring amorphous silica) as intermediate phases (Kastner et al. 1977) beforecrystallizing as chalcedony, a cryptocrystalline variety of quartz (Faure 1998).Microcrystalline silica is observed to have precipitated in vesicles of basalt rocks ofthe eastern Snake River Plain, for example, and is attributed to the addition ofH4SiO4 from the weathering of volcanic glass and silicate minerals (Wood & Low1986).

The source of bicarbonate ions in basalt aquifer systems is from CO2, as discussedabove, from silicate weathering reactions as shown for example in Equations 6 – 9,and low concentrations from carbonate rocks that may be present as weatheringproducts (Deutsch 1997). As sulfur is only a minor constituent of igneous rocks,sulfate concentrations in basalt are generally low, and are largely recycled from theatmosphere (Junge 1963; Wood & Low 1986; Davis & DeWiest 1991).

The total dissolved concentrations in groundwaters in silicate rocks are generallylow. Mazor (1997), for example, notes that basalt groundwaters are generally of lowsalinity with concentrations of total dissolved solids less than 400 mg/L. This maybe attributed to the slow dissolution kinetics of most silicate minerals. In addition, inthe case of massive igneous rocks, groundwater flow along fractures restrictseffective flushing of the rock (Appelo & Postma 1996), which therefore limits thedegree of water – rock interaction.

The weathering products found in a particular setting (e.g. kaolinite, montmorilloniteor gibbsite) are generally interpreted as a reflection of the leaching intensity, whichdepends on the hydrological conditions as well as the rate of mineral weathering(Ferguson 1954a; Barshad 1966; Yaalon et al. 1966; Garrels 1967; Appelo & Postma1996; Drever 1997). Many authors (e.g. Simonett & Bauleke 1963; Berner 1971;Appelo & Postma 1996) note that montmorillonite tends to form preferentially in lowrainfall, dry climates, and gibbsite and other Al-hydroxides, such as bauxite, inintense rainfall, tropical climates. Reactions of clay species, such as the weatheringof Na-, Ca- or Mg–montmorillonite to kaolinite, and the weathering of kaolinite tothe aluminium oxide gibbsite, require substantial amounts of water, as shown inEquations 12 and 13:

Ca–montmorillonite → Kaolinite

442

452224207.334.670.33 SiOH8Ca(OH)OSi7Al2HO23H(OH)OSiAl3Ca ++→++ ++ (12)

Kaolinite → Gibbsite

44324522 SiOH22Al(OH)O5H(OH)OSiAl +→+ (13)

It has been proposed, however, that the type of weathering products formed is relatedto the degree of chemical weathering relative to physical weathering (Nesbitt &

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Wilson 1992). This is supported by the work of Bluth and Kump (1994), who foundin a comparison of rivers draining basaltic terrain that, while a tropical climate andthe presence of abundant vegetation favour chemical dissolution, an excess of soilformation (e.g. low rates of physical weathering) will greatly reduce chemicalweathering; that is, the balance between chemical weathering and physical removalis a factor controlling the rate of weathering and the type of products formed.

The differing rates of silicate mineral weathering were recognized by Goldich (1938)as discussed above. Later studies (e.g. Wollast 1967; Helgeson 1971; Luce et al.1972; Paces 1973; Busenberg & Clemency 1976) aimed to gain a quantitativeunderstanding of the dissolution kinetics of primary silicate minerals. Processes thatcommonly control the rates of dissolution or growth of solid phases in inorganicgeochemistry are discussed, for example, by Petrovic et al. (1976), White andClaassen (1979) and Drever (1997). These processes include reaction at the surfaceof a mineral grain, transport of ions or molecules in solution to or from the grainsurface, and diffusion of ions or molecules through a layer of solid reaction productsor partially altered primary mineral (Drever 1997).

While some studies (e.g. Wollast 1967; Helgeson 1971; Luce et al. 1972; Stumm &Wollast 1990) indicated that diffusion of solutes through a leached or precipitatedlayer on the surface of mineral grains was the rate-controlling step in silicatedissolution, with the reaction rates being parabolic, studies by Berner and Holdren(1979), Holdren and Berner (1979), Schott and Berner (1985) and Grandstaff (1986),for example, have shown that dissolution rates are linear (when crystals have beencorrectly pre-treated) at constant temperature and pH, which is compatible with amechanism whereby surface reaction controls the reaction rate, rather than diffusion,or the transport of weathering products to and from the mineral surface (Appelo &Postma 1996). Holdren and Berner (1979) found that non-linear rates of dissolutionobserved at the initial stage of experiments were due to the dissolution of ultrafine(« 1 μm diameter) particles, which are produced during grinding of the sample.Subsequent work (e.g. Schott et al. 1981; Schott & Berner 1983; Casey et al.1989a,b; Casey & Bunker 1990) has shown the existence of thin altered layers on thesurfaces of dissolving feldspars, although the general view is that while diffusiondoes occur, it is not the major control on the dissolution rates of most silicateminerals (Grandstaff 1986; Drever 1997). The dissolution of volcanic glass,however, may be controlled by diffusion through a partially leached surface layer(White 1983).

Calculations of mean lifetimes of a 1 mm crystal, based on weathering rates at 25 °Cand pH 5 from various studies, were determined by Lasaga (1984) and updated byLasaga et al. (1994); a selection of these is shown in Table 1. They are comparableto the Goldich weathering sequence shown in Figure 1. Reviews of laboratorydissolution rates are also provided by Schnoor (1990), Stumm and Wieland (1990)and Sverdrup (1990).

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Table 1. The mean lifetime in years of 1 mmcrystals of some silicate minerals at 25 °Cand pH 5 (Lasaga et al. 1994).

An important study of dissolution kinetics is that by Chou and Wollast (1985), whoshowed that the albite dissolution rate is strongly pH dependent, and is alsoinfluenced by the dissolved aluminium concentration, which inhibits the dissolutionof albite. The effects of aqueous pH on silicate reaction rates have also observed, forexample, by Wollast (1967), Luce et al. (1972), White and Claassen (1979) andHoldren and Speyer (1986). The dissolution of feldpars is also affected by the partialpressure of CO2 (Sverdrup 1990; Appelo & Postma 1996). In a recent study of thestandard Gibbs free energy of H4SiO4, Gunnarsson and Arnórsson (1999) proposedthat new data indicate that all silicate minerals are more soluble at low temperaturesthan has generally been accepted, due to the higher solubility of quartz. Theydemonstrated this proposal with respect to albite, and showed higher solubility foralbite at temperatures below 100 °C, and in particular, below 30 °C (Gunnarsson &Arnórsson 1999).

Another important consideration with regard to silicate dissolution kinetics is thatdissolution rates measured in field studies are generally several orders of magnitudelower than those predicted in laboratory studies (Paces 1983, 1984; Velbel 1985;Schnoor 1990; Brantley 1992; Anbeek 1993). This is considered to be due to theeffects of temperature, differences in the ratio of effective surface area to totalsurface area, the precipitation of secondary minerals on the surfaces of primaryminerals, which isolates fresh mineral surfaces from the surrounding solution, andhydraulic effects such as preferential flow, rapid flow of water in the aerated zoneand fluctuations in the water table which reduce the active mineral surface areaexposed to weathering in field situations (Spears 1976; Paces 1983, 1984; Velbel1990; Swoboda-Colberg & Drever 1993; Drever & Clow 1995; Drever 1997). Inaddition, anthropogenic processes, such as agricultural and industrial practices,which acidify the groundwater, may also affect field derived rate constants (Paces1983). The study of silicate mineral weathering rates is a complex one. It is outsidethe scope of this research project to determine the weathering rates of minerals foundin the study area.

Minor silicate minerals that occur in basalt can also contribute to the concentrationsof ions in groundwater. Minerals such as apatite and sodalite can release calcium,sodium, phosphorus and chloride ions during weathering. The weathering of apatite,for example, can occur under mildly acidic conditions, given its decreased stability insuch environments (Singer 1999). Chloride may also be found in natural glass andfluid inclusions in basalt (Davis & DeWiest 1991).

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Zeolites are hydrated aluminosilicates of alkali and alkaline earth metals, and aretektosilicates with a more open lattice than other tecktosilicates such as feldspars.They have a high exchange capacity and may therefore participate in ion-exchangereactions (Lloyd & Heathcote 1985). A range of zeolite minerals may precipitate inthe vesicles and along fractures of basaltic rocks (Chalmers 1967; Gottardi & Galli1985; Tschernich 1992). They include chabazite, clinoptilolite, thomsonite,phillipsite, mesolite, scolecite, mordenite, heulandite, stilbite and laumontite.Analcime is a primary constituent in some basalts where it is typically restricted tothe groundmass (Coombs et al. 1959; Deer et al. 1966), although it can also occur asphenocrysts in some volcanic rocks (Liou 1971). Analcime is also a commonsecondary mineral in basalt at low temperatures (< 50 °C) (White et al. 1980;Arnórsson 1999). The presence of these minerals is influenced by pore fluidcomposition, the partial pressure of CO2, volcanic glass content, depth below surface,time and temperature (Hay 1966; Iijima 1980). Studies of zeolite facies in basaltinclude those by Hoover (1968) and Fridriksson et al. (1999). Other secondaryminerals that may precipitate in basalt, in addition to clays, amorphous andcrystallized silica and zeolites as noted above, include pyrite, calcite, aragonite,dolomite, siderite, sepiolite, goethite, hematite and maghemite (Craig & Loughnan1964; Carr et al. 1980; Pawar 1993; Arnórsson 1999; Fridriksson et al. 1999; Aiuppaet al. 2000).

The relationships between secondary mineral phases and fluid compositions arediscussed by Andrésdóttir and Arnórsson (1999) and Fridriksson et al. (1999). In astudy of basalts in eastern Iceland, for example, Fridriksson et al. (1999) note thatiron and magnesium necessary for the precipitation of a mixed layer chlorite /smectite clay is provided by the rapid hydrolysis of olivine and glass, alteration ofchlorite / smectite to zeolites results from an increase in the concentration of Ca2+

relative to Mg2+ and Fe2+ in the fluids, and albitization of plagioclase releases Ca2+ tosolution, leading to saturation with Ca-zeolites such as scolecite, heulandite andstilbite. In a study of both thermal and non-thermal groundwaters from basalt innorthern Iceland, Andrésdóttir and Arnórsson (1999) showed that the low calciumand magnesium concentrations are controlled by the solubility of calcite andamorphous magnesium-silicate, respectively.

OXIDATION AND REDUCTION

Oxidation and reduction (or redox) reactions may generally be regarded in solutionchemistry as reactions involving the transfer of electrons from one atom to another(Drever 1997; Tóth 1999). Oxidation – reduction processes are described by Freezeand Cherry (1979), Appelo and Postma (1996), Deutsch (1997), Faure (1998) andothers.

The solubility of some elements will depend on their oxidation state, which isdetermined by the redox potential or oxidation – reduction potential (Eh) of theenvironment (Davis & DeWiest 1991). The Eh is a measure of the energy needed toremove electrons from ions in a given chemical environment. The thermodynamicrelationship between Eh and the concentrations of dissolved constituents of thesolution, assuming that the species participating in the redox reactions are atequilibrium, is based on the Nernst equation. This can be generalized for any redox

25

reaction at 25 °C (Equation 14) (Back & Hanshaw 1965; Appelo & Postma 1996;Deutsch 1997; Drever 1997):

+=speciesreducedofproductactivity

speciesoxidizedofproductactivitylog

059.0E

nEh (14)

where E is the standard or reference electrode potential and n is the number oftransferred electrons.

High positive values for Eh indicate oxidizing conditions, and low negative valuesreducing conditions. A decline in groundwater Eh values from an oxidizing state inrecharge areas to a reducing state in discharge areas indicates the occurrence ofoxidation – reduction reactions in the aquifer (Champ et al. 1979; Fetter 1994).

The electron activity should be regarded as the tendency for an atom to release oraccept electrons. The parameter pe is defined in Equation 15:

−= e10log-pe (15)

where αe- is the activity of the electrons.

As for Eh, high positive values of pe indicate oxidizing conditions and low negativevalues reducing conditions (Appelo & Postma 1996). The activity of electrons insolution (and therefore its redox level) can thus be expressed in units of volts (Eh) orin units of electron activity (αe- or pe) (Drever 1997). Eh and pe are related byEquation 16 (Appelo & Postma 1996; Drever 1997):

eF

RTh p2.303

E = (16)

where F is Faraday’s constant (96.484 kJ per volt gram equivalent), R is the gasconstant (8.314 × 10-3 kJ/K.mol), T is the temperature in kelvins, and 2.303 is theconversion from natural to base 10 logarithms. At 25 °C, Eh = 0.059pe.

Values for pe have been calculated from Eh readings and used in mineral / solutionsequilibria calculations for the Atherton groundwaters (PAPER 3). As many redoxreactions are influenced by pH, redox diagrams can be used to express the stability ofspecies as a function of pe (or Eh) and pH. A diagram showing the stability of waterand the ranges of pe and pH conditions in natural environments presented by Drever(1997) and Faure (1998) after Garrels and Christ (1965), for example, is a useful wayof identifying waters that are either in contact with or isolated from the atmosphere.

ION-EXCHANGE

Ion-exchange involves a replacement of one chemical for another at the solid surface.Ion-exchange reactions are controlled by the exchange capacity of the solid (Appelo

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& Postma 1996) and can be important in determining the composition of naturalwaters (Fetter 1994).

Ion-exchange sites are found primarily on clays and organic materials (Mitchell1932; Frizado 1979), zeolites and colloidal oxyhydroxides (Drever 1997), and bothcation exchange and anion exchange reactions can occur (Fetter 1994). Ion-exchange capacity is a function of mineralogy, particle size, availability of exchangesites, strength of bonding of the exchangeable ions, temperature, pH, Eh, soilmoisture and activity of the ions in solution (Hitchon et al. 1971; Barrow & Shaw1975; Vijayachandran & Harter 1975; Fetter 1994), and can be measured andexpressed as a cation exchange capacity (CEC) or anion exchange capacity of a soil(usually as meq / 100 g). Alternatively, an empirical formula can be used to relatethe CEC to the percentage of clay and organic carbon (Breeuwsma et al. 1986;Appelo & Postma 1996). The smectite group of clays, including the montmorillonitespecies, for example, are well known for having a high ion-exchange capacity due totheir interlayer charge (Freeze & Cherry 1979; Kittrick 1979; Appelo & Postma1996; Deutsch 1997; Drever 1997). The cations in the interlayer space of these clayminerals can move into solution to be exchanged for other ions (Appelo & Postma1996).

The classic case of cation exchange as an indicator of salinization is described byMagaritz and Luzier (1985), Xue et al. (1993) and Appelo and Postma (1996), whereseawater intrudes a fresh water aquifer. However, fresh water dominated by Ca2+

and HCO3- ions, can also undergo cation exchange, with Ca2+ taken up by the

exchanger and Na+ released to solution (e.g. Back 1966; Schwartz & Gallup 1978;Chapelle 1983). While the anion exchange capacity of clays is usually negligible atthe pH of most natural material (Deutsch 1997), for more heavily weathered soilswhere conditions are relatively acidic, as is the case for the Atherton Tablelands, theanion exchange capacity can be considerably higher (Sposito 1989).

EVAPORATION

Evaporation leads to increases in concentration, which are proportional to the amountof water that evaporates. Concentration by evaporation operates mainly in the soil-moisture zone and between rainfall events (Tóth 1999). One of the earliest studies ofthe effects of evaporation on the composition of fresh waters was undertaken byJones (1965) on closed-basin brines. The effect of evaporation on the composition ofspring waters from the granitic rocks of the Sierra Nevada Mountains of Californiawas later investigated by Garrels and Mackenzie (1967) and is discussed by Faure(1998). Garrels and Mackenzie (1967) concluded that the compounds most likely toform due to evaporation of the spring waters are calcite, gypsum, sepiolite andamorphous silica, accompanied by depletion of Ca2+, Mg2+, HCO3

-, SO42- and SiO2,

and enrichment of Na+, K+ and Cl-, with a rise in pH (Faure 1998).

The evolution of water, due to progressive evaporation and the precipitation ofcompounds, depends on the operation of several geochemical divides associated withthe precipitation of calcite, gypsum and sepiolite as defined by the Hardie-Eugstermodel described by Drever (1997), and Faure (1998). The principles of evaporativeevolutionary paths in relation to the chemistry of closed-basin brines are described

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by Hardie and Eugster (1970), Eugster and Jones (1979) and Al-Droubi et al. (1980).This approach can be used most effectively to explain the controls on thecomposition of saline waters, such as saline lakes (e.g. Jones et al. 1977; Eugster &Maglione 1979; Spencer et al. 1985 a,b). The concepts can also be used, however, toaid in the understanding of evaporative effects on any natural waters.

ORGANIC MATTER

The effect of vegetation or organic matter on soil mineral weathering processes isdiscussed by Drever (1994). Two types of mechanisms are considered by Drever(1994); the direct influence of plants on the physical and hydrological properties ofsoils that can modify water residence times within the soil and, thus, the contact timebetween minerals and aqueous solutions, and the chemical influence induced by theproduction of organic acids by plant roots, microorganisms, and by microbial decayof plant matter (Oliva et al. 1999).

Natural organic matter in soil is composed of degradable plant debris and roots ofvegetation. The dissolution of organic matter is the major source of dissolvedorganic carbon in soil water and shallow groundwater (Thurman 1985; Domenico &Schwartz 1998). Dissolved organic carbon largely constitutes humic substances,consisting mainly of humic and fulvic acids (Wallis et al. 1981; Domenico &Schwartz 1998), which contain the elements carbon, hydrogen, oxygen, nitrogen andsulfur (Sposito 1989; Finger et al. 1992; Frimmel 1992; Deutsch 1997). The openstructures of these polymeric molecules means that humic and fulvic acids arecapable of having cation exchange sites, and can be excellent ion exchangers, withexchange capacities similar to that of smectites (Rashid 1971; Schnitzer & Khan1972; Frizado 1979). Solid organic matter can also affect the composition ofgroundwater, as it adsorbs dissolved organic carbon as well as metals, and can be animportant control on the mobility of trace metals (Broadbent & Lewis 1961; Deutsch1997). The action of organic acids and compounds on clays and other silicates isexamined experimentally and discussed by Huang and Keller (1971).

The uptake of inorganic nutrients by vegetation from the soil solution, can also affectthe concentrations of ions remaining in the groundwater. In addition, the synthesis ofterrestrial biomass requires more cations than anions, and so protons are produced (inaddition to oxygen) to maintain the charge balance (Schnoor & Stumm 1985),supplying acidity to soil solutions (Drever 1997). The effect of biomass uptake onmass-balance budgets is discussed by Likens et al. (1977), Sverdrup and Warfvinge(1988), Davis and DeWiest (1991) and Appelo and Postma (1996). The relativeeffect of biomass on groundwater composition, however, will be less where the inputfrom weathering is greater, which would be the case where the aquifer material isless resistant to chemical weathering (Drever 1997). The chemical constituents mostaffected by biomass uptake are phosphorus, nitrogen species, potassium and calcium(Drever 1997).

The production of CO2, however, is probably the most important process involvingorganic carbon, as it leads to the production of carbonic acid in water, as discussedabove and shown in Equations 4 and 1, respectively. The effect of plants onweathering has been subject of several studies over recent years (e.g. Drever &

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Zobrist 1992; Berner & Rao 1997; Bormann et al. 1998; Berner 1999; Moulton &Berner 1999). These studies have shown that the presence of trees accelerates therate of calcium and magnesium silicate weathering by a factor of approximately threeto ten (Berner 1999).

While the effects of organic matter on the composition of the groundwaters of theAtherton Tablelands region are not addressed in detail in this research project, theeffects of organic matter on water composition, as discussed above, support one ofthe hypotheses proposed in PAPER 2, that is, that the leaching of ions from organicmatter may affect the concentrations of K+ and to a lesser extent Ca2+ in thesegroundwaters. In addition, the rates of the silicate weathering processes are likely tobe influenced to some extent by the vegetation present in the study area, andconsequently the availability of CO2.

OTHER FACTORS INFLUENCING GROUNDWATER COMPOSITION

Average annual rainfall on the Atherton Tablelands ranges spatially fromapproximately 1300 to 2700 mm. This area is categorized by Davis and DeWiest(1991) as having ‘moderately high precipitation’, that is, in excess of 50 inches(1270 mm) per year. Aquifer systems in areas with abundant rainfall are often fullysaturated, have rapid circulation of groundwater and good quality water for mostpurposes. The abundance of water should, however, result in rapid chemicalleaching of soluble and partly soluble material from these aquifers (Davis & DeWiest1991). A study of the composition of groundwater in this environment, as a meansof understanding hydrogeochemical processes, is therefore likely to be a feasibleapproach.

In addition, the relatively high temperatures in the Atherton Tablelands region mayresult in somewhat elevated mineral weathering rates in this area, with subsequenteffects on the groundwater composition. While Peters (1984) found no conclusiveevidence of the effect of temperature on weathering in studies of river chemistry,Meybeck (1986) found a positive correlation between mean air temperature anddissolved silica concentrations in a study of 232 watersheds throughout France. Apositive correlation between temperature and the chemical weathering rate of silicateminerals is experimentally established for silicate minerals such as feldspars (Blum& Stillings 1995), and has been observed for some large rivers by Gaillardet et al.(1999), and for smaller watersheds by Velbel (1993), White and Blum (1995) andWhite et al. (1999). Millot et al. (1999) also observed that rates of silicateweathering are higher in warmer environments, based on their study of weatheringrates for the Mackenzie River basin in western Canada compared to tributaries of theAmazon River basin. This relationship is expected to hold for groundwater systems.

Nesbitt and Wilson (1992) found that while the minerals exposed near the surface insoils are controlled by climatic conditions, the weathering mechanisms and leachingcharacteristics of basalts are apparently controlled more by the bulk composition andprimary phases of the parent basalts than by climate. As such, climatic conditionsmay be expected to contribute to the chemical weathering mechanisms influencingthe composition of the Atherton groundwaters. However, the predominant influenceis likely to be the composition of the basalt rocks.

29

Other processes such as mixing of waters of different compositions can also be afactor in some groundwater systems. Anthropogenic activities, such as urbanization,agricultural activities and industry, can also significantly affect groundwatercomposition. The application of nitrogen-based fertilizers in the Atherton Tablelandsregion is probably the most significant anthropogenic influence on the compositionof both surface and groundwaters in the region. An additional minor source ofnitrogeneous compounds is from nitric oxides produced by lightening discharges(Davis & DeWiest 1991). As noted above, nitrogen is generally taken up by plants.However, where the input is so high that the vegetation’s ability to take it up isexceeded, nitrate behaves as a mobile anion; this situation is referred to as nitrogensaturation (Drever 1997). The reduction of nitrate by organic matter (denitrification)in soils and aquifers is an important process in the removal of nitrate from solution,leading to volatilisation to nitrogen gas (Appelo & Postma 1996).

These influences on groundwater composition in the Atherton Tablelands region, thatis, non-natural processes, are not considered in detail in this study, and will not befurther addressed in this literature review.

30

Mineralogical and hydrochemical methods for modelling hydrogeochemical

processes

ROCK CHEMISTRY AND MINERALOGY

The mineral compositions of fresh and weathered rocks and soils can be studied, forexample, by means of X-ray powder diffraction or by calculating the abundances ofselected minerals (referred to as normative minerals) from chemical analyses of therocks (Faure 1998). Following the choice of minerals to be included in the norm, theoxides are assigned to the normative minerals, with the primary minerals satisfiedfirst, followed by the secondary weathering products (Faure 1998).

X-ray powder diffraction, as well as other analytical techniques, can be also used totrace mineral alterations and to evaluate these alterations in terms of changes inwhole rock geochemistry during the weathering process (Eggleton et al. 1987).Changes in rock chemistry and mineralogy as a result of chemical weathering aredescribed by Loughnan (1969), Langmuir (1997) and Faure (1998). Some of thechemical reactions and mineralogical transformations that take place during basaltweathering are described by Craig and Loughnan (1964), Carr et al. (1980),Chesworth et al. (1981), Colman (1982), Eggleton et al. (1987), Nesbitt and Wilson(1992), Gíslason et al. (1996), Aiuppa et al. (2000) and Hill et al. (2000), in terms ofthe relative mobilities of elements.

MINERAL DISSOLUTION AND SOLUBILITY

The quantification of relations between minerals and dissolved species is describedby Garrels and Christ (1965), Paces (1976), Freeze and Cherry (1979), Fetter (1994),Appelo and Postma (1996), Faure (1998) and others. Some of the basics of assessingthese relations in terms of a thermodynamic equilibrium approach are outlinedbelow.

The Law of Mass Action states that the rate of reaction is proportional to theconcentrations of the reactants as shown in Equations 17 and 18:

dDcCbBaA +↔+ (17)

where the chemical constituents are denoted by capitals, and a, b, c and d are thenumber of moles of these constituents, and

[ ] [ ][ ] [ ]ba

dcK

BA

DC= (18)

where K is the coefficient known as the equilibrium constant or stability constant,and bracketed quantities denote the activities of the constituents. Derivation of theLaw of Mass Action based on the first and second laws of thermodynamics is givenby Faure (1998).

31

Activities, or ‘effective concentrations’, reflect the chance that the ions will react andform a precipitate (Appelo & Postma 1996) and are calculated based on the ionicstrength of the solution (Deutsch 1997). The chemical activity of an ion is equal tothe molal concentration multiplied by a factor known as the activity coefficient.Some equations used to derive activity coefficients, such as the Debije-Hückel andthe Davies equations, are presented by Lewis and Randall (1961), Back andHanshaw (1965), Stumm and Morgan (1981), Appelo and Postma (1996), Drever(1997) and Domenico and Schwartz (1998).

To determine the saturation state of a solution with respect to a mineral, the solubilityproduct (K) is compared to the ion activity product (IAP) of the solution. Where themineral C is being dissolved according to Equation 19:

yYxXcC +↔ , Kiap is given by (19)

( ) ( )yYxXiap =K (20)

where α denotes the chemical activity of the ions.

It is essentially a comparison of the activities in the water sample (represented by theIAP) to the activities at equilibrium (K). The ratio between the IAP and K can beused to express the saturation conditions, as shown in Equation 21:

)/log(SI KIAP= (21)

where SI is the saturation index.

The saturation index reflects the direction of the reaction. A negative SI indicatesthat the solution is undersaturated and that dissolution is expected, while a positiveSI indicates that the solution is supersaturated and that precipitation should occur(Nordstrom & Munoz 1994). Because of inherent uncertainties in the calculation ofsaturation indices, a range of values near zero, such as SI = 0 ± 0.5, are considered tobe within equilibrium (Paces 1976; Deutsch 1997).

Some of the theory behind mass transfer calculations, including the computation ofmolalities, activity coefficients, activities of species in solution, and equilibrium (orsaturation) states is given by Helgeson et al. (1970). The calculation of ion activitiesand saturation states can be undertaken using computer-based hydrochemical modelssuch as PHREEQC (Parkhurst 1995) and WATEQ4F (Truesdell & Jones 1974; Ball& Nordstrom 1991).

Interpretation of saturation indices should be undertaken in conjunction withmineralogical data (e.g. PAPER 3). It should be noted, however, that possiblereactive minerals might not be identified in the solid phase because they are atconcentrations below the detection limits of the analytical method, or because theymay be weathering products, which may form a very small percentage of the wholerock (Deutsch 1997).

32

One of the drawbacks of the saturation state approach, particularly with respect tosilicate minerals, as noted by Appelo and Postma (1996) and Drever (1997), is thatthe aluminium concentration in groundwater is often below the detection limit.Mineral stability diagrams (a type of activity diagram) may therefore be used todisplay such data, and are based on the assumption that all the aluminium ispreserved in the weathering product. Such diagrams facilitate prediction andinterpretation of the chemical environments in which mineral assemblages form(Helgeson et al. 1969). A stability diagram for the Na-silicates, for example, isshown in Figure 2. It contains stability fields for the Na-feldspar albite and itspossible weathering products, Na-montmorillonite, kaolinite and gibbsite, expressedas a function of log [Na+]/[H+] and log [H4SiO4]. The cation / proton activity ratiosare a useful measure of evolution of a water body towards equilibrium in a particulargeological environment, since progressive water – rock interaction involvessimultaneous increase in aqueous cation concentrations from the minerals anddecrease in hydrogen ion concentrations (Arnórsson 1999). The lines on stabilitydiagrams represent the alteration of one mineral to another, based on thermodynamicdata. A good discussion of the construction of mineral stability diagrams is providedby Faure (1998).

Tardy (1971), Freeze and Cherry (1979) and Appelo and Postma (1996) note thatconsideration of pure end-member minerals is a simplification of real situations,where solid solutions are more abundant than pure minerals, and due to the slowreaction kinetics of most silicate minerals, it is uncertain whether true equilibrium isever attained. Silicate stability diagrams can, however, give an understanding of thelikely stability relations between minerals and water (Garrels 1976; Appelo &Postma 1996).

The methods described above to assess groundwater solutions in terms of mineralsolubility have been widely adopted. For example, Tardy (1971) examined thecomposition of surface waters from crystalline massifs in Europe and Africa usingsilicate stability diagrams, and Rogers (1989) used stability diagrams to presentgroundwater chemistry data from silicate and carbonate rocks from areas of NewEngland, New York and Pennsylvania, U.S.A. In a hydrogeochemical study of asandstone and carbonaceous claystone aquifer system in the Lethakend –Bothapatlou area at the fringe of the semi-arid Botswana Kalahari, Beekman andSalaolo (1994) also used methods such as assessment of activity ratios. In that study,WATEQ4F (Ball & Nordstrom 1991) was used to calculate mineral saturation statesalong a flow path, and compared with the mineral composition (using XRD analysis)of end-of-flow-path claystone samples.

Calcium, sodium and magnesium aluminosilicate stability diagrams and saturationindices for some primary silicate minerals, as well as some secondary minerals, havebeen used to describe the controls on the composition of the Atherton basaltgroundwaters in PAPER 3 and APPENDIX IV.

33

Figure 2. Na2O-Al2O3-SiO2-H2O system at 25 °C and 1 atm. [ ] denotes acivity

MASS BALANCE APPROACH

The incongruent dissolution of some silicate minerals (whereby the ratio of theelements which appear in solution differs from that in the dissolving mineral) hasmade the use of mass balance calculations, which relate changes in water chemistryto the dissolution or precipitation of minerals, particularly useful (e.g. Plummer &Back 1980; Velbel 1986; Wood & Low 1986). The solution of mass balancecalculations is based on the general reaction shown in Equation 22. For a rockconsisting of a mixture of minerals, the contributions of different weatheringreactions to the water composition may be determined (Appelo & Postma 1996).

initial solution + reactant minerals → final solution + weathering residue (22)

In an important study relating groundwater chemistry to silicate weathering reactionsin a granitic area of Sierra Nevada, U.S.A., Garrels and Mackenzie (1967) used amass balance calculation approach. This is considered a ‘classic’ study using themass balance approach to an investigation of mineral – water interactions and isdiscussed, for example, by Garrels (1976), Freeze and Cherry (1979), Appelo andPostma (1996), Drever (1997) and Faure (1998). Using the compositions of snowand ephemeral spring waters, Garrels and Mackenzie (1967) calculated the ‘rockweathering’ component of the major ion concentrations of the spring waters. Basedon the average composition of the minerals found in the area, they accounted for theNa+, Ca2+, Mg2+, K+, HCO3

- and the bulk of the SiO2 concentrations through thestepwise reaction of plagioclase, biotite and K-feldspar to kaolinite. Other examplesof the mass balance approach to investigating natural water systems are presented byPlummer and Back (1980).

0

2

4

6

8

10

-5.0 -4.5 -4.0 -3.5 -3.0 -2.5

Kaolinite

Gib

bsit

e

Am

orph

ous

Silic

a

Qua

rtz

Albite

Na-

Montmorillonite

Log [H4SiO4]

Log

[N

a+]/

[H+]

0

2

4

6

8

10

-5.0 -4.5 -4.0 -3.5 -3.0 -2.5

Kaolinite

Gib

bsit

e

Am

orph

ous

Silic

a

Qua

rtz

Albite

Na-

Montmorillonite

Log [H4SiO4]

Log

[N

a+]/

[H+]

34

The mass balance approach to the investigation of groundwater has a number oflimitations that should be considered, as outlined by Appelo and Postma (1996).They are summarised below:

the solution of mass balance equations is not necessarily unique, andtherefore, a mass balance calculation does not prove that particular reactionstake place, although through a series of elimination processes, there oftenremains a single reaction model that is consistent with the observed data(Plummer & Back 1980; Plummer et al. 1983; Wood & Low 1986),

there are no thermodynamic constraints on the calculations, and thecalculations do not consider what is kinetically consistent,

mass balance calculations assume steady state conditions. Variations ingroundwater composition along a flow path are assumed to be due toreactions with minerals and not, for example, due to temporal variations inrecharge water composition, and

a homogeneous reaction between the points of analysis is assumed.

Careful interpretation of the mass balance calculations and consideration ofalternative reaction schemes is therefore required. In addition, for a thoroughexamination of the controls on groundwater composition, factors other than mineralweathering should be taken into consideration. These include evaporation, ion-exchange and redox reactions, input from dry deposition and possible biomass inputand uptake.

The mass balance approach to describing the controls on groundwater composition isan inverse method of modelling aquifer geochemical interactions (Deutsch 1997);both inverse and forward modelling methods are discussed in the following section.A mass balance approach has been applied to this study to define the likely mineralweathering processes controlling the composition of the basalt groundwaters(PAPER 3). Hydrochemical models such as BALANCE (Parkhurst et al. 1982),NETPATH (Plummer et al. 1994) and PHREEQC (Parkhurst 1995) can be used formass balance calculations. PHREEQC (version 2) has been utilised in this capacityin the study of basaltic water – rock interaction processes (PAPER 3).

HYDROGEOCHEMICAL MODELLING

In addition to the calculations described above, which can be computed withhydrogeochemical models, computer programs such as PHREEQC (an improvementon the PHREEQE hydrogeochemical model developed by Parkhurst et al. (1980))can be used to calculate how a water composition changes in response to reactionsand to test hypotheses. Hydrogeochemical models can also be used to compare fieldor laboratory data with geochemical model calculations, and to validate numericalprocedures and reaction schemes (Appelo & Postma 1996).

The types of chemical reactions that can be modelled include gas exchange, ionspeciation, ion complexation, oxidation and reduction, mineral dissolution and

35

precipitation, and adsorption and desorption reactions (Deutsch 1997). Data (orcomponents) used to model a particular aquifer setting may include pH, Eh (or pe),temperature, solution composition and aquifer mineralogy.

The modelling of aquifer geochemical interaction can be considered in terms ofinverse or forward approaches. Where there is sufficient data to define agroundwater flow path and changes in groundwater composition along the flow path,then an inverse method (mass balance approach) can be used to account for thechange in solution composition based on the dissolution or precipitation of reactivephases (Deutsch 1997). With the inverse approach the phases and solute constraintsnecessary to produce the observed changes are specified (e.g. Fryar et al. 2001).Mass balance computer codes that can be used for inverse modelling includeBALANCE (Parkhurst et al. 1982), its successor NETPATH (Plummer et al. 1994),and PHREEQC (Parkhurst 1995).

The forward method of geochemical modelling can be used to predict thecomposition at a down gradient location based on natural geochemical processesalong a flow path, or to determine how an aquifer system will respond to the additionof a reactant or some change in conditions (Deutsch 1997). In the forward method,reactants are added to a starting solution, which may be open to gas exchange (e.g. inthe vadose zone) or closed to gas exchange (in the saturated zone) (e.g. Fryar et al.2001). The most commonly used computer codes for forward-reaction modelling arePHREEQC and MINTEQ (Felmy et al. 1984).

Descriptions and comparisons of forward and inverse methods of geochemicalmodelling are given by Plummer (1984, 1992), Parkhurst and Plummer (1993) andNordstrom and Munoz (1994). The capabilities of the modelling codes noted above,as well as other programs, are described by Nordstrom and Munoz (1994), Appeloand Postma (1996) and Deutsch (1997). Reviews of aqueous geochemical models,including transport models, include those by Nordstrom et al. (1979), Grove andStollenwerk (1987), Engesgaard and Christensen (1988), Mangold and Tsang (1991),Plummer (1992) and Parkhurst and Plummer (1993). The program used for thisresearch investigation, that is, PHREEQC (version 2), is a computer program writtenin the C programming language, and is designed for low – temperature aqueousgeochemical calculations of speciation, phase distribution, and reaction paths(Nordstrom & Munoz 1994; Parkhurst & Appelo 1999).

Recent examples of hydrogeochemical modelling approaches to the assessment ofthe controls on groundwater composition in various lithological settings includethose by Frengstad and Banks (2000), Pereira and Almeida (2000) and Martínez andBocanegra (2001).

36

Related hydrogeochemical studies and scope for further research

One of the earliest examinations of hydrogeochemical processes was undertaken byLeGrand (1958), in an assessment of the chemical character of water in the igneousand metamorphic rocks of North Carolina. In a study of two suites of rocksapproximating granite and diorite in composition, LeGrand (1958) showed thatlithological determinations based on the chemical character of groundwater aregenerally reliable in regions of similar climate and topography. Further, anomaliesin dissolved mineral constituents that are not due to differences in rock type, climate,or topography may indicate either abnormal structural conditions, or the presence ofconcentrated mineral deposits. With respect to geological structure, it has beenproposed that groundwater is not chemically affected by the type of openings, butrather by the chemical character of the rock and by the length of time it is in contactwith the rock (LeGrand 1958). Accordingly, only those structures that cause thecirculation of water to be greatly accelerated or retarded might be detected by anappraisal of the chemical character of the water.

A correlation was similarly shown to exist between the physical and chemicalcharacteristics of groundwater and lithology in a study in São Paulo, Brazil (Szikszayet al. 1981). Differences in hydrochemical type were attributed to lithologicalvariations in the four main rock types, comprising granitic rocks, sediments,volcanics, and sandstone interbedded with basalt. This study may have beensignificantly enhanced through a more comprehensive examination of water – rockinteraction processes. Szikszay et al. (1981) were able, however, to show thathydrochemical anomalies in the shallow aquifer in São Paulo can be used as anindicator of the presence of ascending deep water through fractures of fault zones.

Water – rock interaction processes have been widely investigated throughhydrochemical studies in a range of lithological settings, including for example,sedimentary rocks and metabasalts in the Catoctin Mountains, Maryland (Katz et al.1985; Katz 1989), schist in the Piedmont Province of Maryland (Bricker et al. 1968),granite and other felsic rocks in the Bohemian massif of the former Czechoslovakia(Paces 1972), and granitic rocks in Stripa, Sweden (Nordstrom et al. 1989; Grimaudet al. 1990; Waber & Nordstrom 1992), Vedée, France (Beaucaire et al. 1995),Cornwall, England (Edmunds et al. 1984; Smedley 1989), the Taejon area, Korea(Jeong 2001a) and the Loch Vale Watershed of Colorado (Mast & Drever 1990).Such investigations in basaltic provinces, however, are limited (e.g. Deutsch et al.1982; Wood & Low 1986; Davis et al. 1989; Benedetti et al. 1992, 1994, 1999) andthere is considerable scope for further research into the role of basaltic water – rockinteraction on the control of groundwater composition, and the use of this knowledgein identifying the nature of groundwater occurrence, flow directions, and rechargeand discharge areas.

The interaction of meteoric waters with basalts has received far less attention than ingranitic, rhyolitic, metamorphic and mixed terrains (Gíslason & Eugster 1987b).Geothermal waters of meteoric origin associated with basaltic rocks have beenstudied by Ellis and Mahon (1964, 1977), Arnason (1977), Ármannsson et al. (1982),Arnórsson et al. (1983a,b), Olafsson and Kristmannsdóttir (1989), Cox and Browne(1998), and Andrésdóttir and Arnórsson (1999). The alteration of basalt by seawater

37

has been studied by Bischoff and Dickson (1975), Mottl and Holland (1978),Seyfried and Mottl (1982) and Chandrasekharam et al. (1989).

Dilute meteoric waters, however, respond more readily than seawater to dissolutionand precipitation reactions and, thus, they can be used as geochemical probes todefine the nature of such reactions (Gíslason & Eugster 1987b; Benedetti et al. 1994,1999). Laboratory studies have been conducted to define the rates of dissolution ofbasaltic rocks and their dependence on temperature, solution composition and oncrystallinity (e.g. Gíslason & Eugster 1987a; Gíslason et al. 1993). These laboratorystudies were undertaken in conditions duplicating weathering conditions in north-eastIceland. A field study in north-east Iceland (Gíslason & Eugster 1987b) involvedsampling and analysis of rain, snow, melt water, cold springs, hot springs andgeothermal fluids, derived from meteoric inflow. Processes of solute acquisition,saturation states of the waters with respect to primary and alteration minerals,reaction paths, reaction progress and mass transfer were defined. Equations werederived which relate residence time to active surface area, characteristic rock particleradii, characteristic crack widths and hydraulic conductivities of aquifers (Gíslason &Eugster 1987b).

A study of mineral-solution equilibrium conditions in basaltic groundwater systemsin Iceland has also been undertaken by Arnórsson (1999), who notes that the sparsevegetation, and therefore, minimal dissolved CO2 from organic sources, means thatlimited reaction is required with the reactive basaltic minerals to saturate the waterwith secondary minerals, such as calcite and epidote at low and high temperatures,respectively, that subsequently precipitate from the water. In those groundwaters,equilibrium is closely approached with the secondary minerals at temperatures as lowas 40 °C (Arnórsson et al. 1983a) and in extreme cases at 10 – 20 °C (Arnórsson1999). Gíslason and Eugster (1987b) also note that in north-east Iceland, after initialsaturation with atmospheric CO2, dissolution and precipitation reactions in the waterstake place sealed off from the atmosphere and without significant CO2 contributionsfrom soils.

Significant differences in field conditions between north-east Iceland and the studyarea of the Atherton Tablelands, North Queensland, may contribute to substantialdifferences in basalt dissolution rates, groundwater saturation states with respect toprimary and alteration minerals and reaction paths. These differences in fieldconditions include climatic variation (particularly temperature) and differences inweathered zone and soil profile development. The weathered zone in the AthertonTablelands region is commonly up to 30 m deep and soil profiles are well developed.There is also dense vegetation in some areas of the Tablelands, and CO2

contributions from the soils may be substantial.

A conceptual model for the chemical evolution of groundwaters of the ColumbiaRiver Plateau is described by Hearn et al. (1990), in terms of the progressive changesin groundwater chemistry with increasing residence time, and the composition ofsecondary mineral phases. Hearn et al. (1990) propose that the evolution of thesegroundwaters is determined primarily by the hydrolysis of volcanic glass andpyroxene, and the stoichiometry of secondary alteration products.

38

In humid tropical climates, soil profiles develop rapidly on basalt, due to the higherreactivity of basalt minerals compared to other siliceous rocks. In the AthertonTablelands region, where deep weathering profiles are common, the groundwatercomposition may be significantly influenced by the mineralogy of alteration productsin the weathered zone.

In an assessment of groundwater quality in the weathered Deccan basalt of theMalwa Plateau, India, a relationship between the thermodynamic stability of the soilminerals and groundwater composition was identified (Lunkad & Raymahashay1978). This work was based on the general conclusion that basalt weathers tokaolinitic red soils under good drainage conditions and weathers to montmorillonite–rich black soils where drainage is poor. Lunkad and Raymahashay (1978) usedmethods developed by Garrels (1967) and Garrels and Mackenzie (1967, 1971) whoshowed that formation of montmorillonite by CO2 leaching of plagioclase results in agroundwater HCO3

-/SiO2 mole ratio of more than three, compared with values lessthan three for kaolinization. Kaolinization of an ideal augite similarly results in aHCO3

-/SiO2 mole ratio equal to six.

An investigation of the hydrochemistry and weathering products of Vietnam ShelfIslands, including the basalts of Re Island, indicated that groundwater is inequilibrium with weathering products and is not in equilibrium with primaryaluminosilicates of the parent rocks (Shvartsev 1978; Korotky et al. 1995). Thegroundwater compositions reflect rapid water circulation and drainage on steepslopes and the nature of stable minerals in basement rocks.

A general qualitative summary of the genesis of groundwaters from igneous rockswas given by Garrels (1967), which included an assessment of the correlationbetween silicate mineral compositions, and water compositions and alterationproducts. Several useful diagrams showing the relationships between watercompositions (using mole ratios and concentrations) and theoretical mineralweathering reactions are presented by Garrels (1967); some of these diagrams wereapplied to this research project (PAPER 3). Garrels (1976) again later emphasizedthe importance of the determination of the chemical composition of waters andcorrelation with the compositions of water-bearing rocks. As discussed above,however, such studies of meteoric waters in basaltic terrain are limited, particularlyin tropical and subtropical environments.

A study of the aqueous geochemistry and diagenesis of the basalt aquifer system ofthe eastern Snake River Plain, Idaho, was undertaken by Wood and Low (1986). Thelow-temperature aqueous geochemical approach applied to this study provided auseful basis for the study of the Atherton Tablelands basalt aquifer system. Theaquifer system of the eastern Snake River Plain is comprised of olivine basalt and isin a semi-arid environment (average precipitation of approximately 300 mm / yr)with an average annual temperature of approximately 8 °C, which is markedlydifferent to the climatic setting of the Atherton Tablelands. In addition, thepredominant clay mineral in the eastern Snake River Plain basalts is a calcium-smectite (Wood & Low 1986), in comparison to the dominant kaolinite presentlyforming in the Atherton region. Wood and Low (1986) used a mass-balanceapproach to determine the amount of solutes generated and precipitated in the

39

aquifer, and thermodynamic arguments to identify specific solute sources and sinks.They were able to identify and quantify the reactions controlling soluteconcentrations in the groundwaters and showed that the aquifer is not inert, but isundergoing active diagenesis and is both a source and sink for solutes (Wood & Low1986).

A study of the mobility and fluxes of major, minor and trace metals during basaltweathering and groundwater transport at the Mount Etna volcano, Sicily, wasundertaken by Aiuppa et al. (2000). The mineralogy and chemistry of theweathering profiles were studied to assess the geochemical mobility of elementsduring basalt weathering, in the manner similarly undertaken by Carr et al. (1980)and Nesbitt and Wilson (1992). The low temperature, meteoric groundwaters of thebasaltic Etnean aquifer are strongly affected by the input of magma-derived CO2, andthe subsequent dissolution of the primary minerals olivine, clinopyroxene andplagioclase (Aiuppa et al. 2000).

The effects of basalt weathering have also been examined by Hill et al. (2000) in astudy of the Tertiary basalts overlying the Ulster White Limestone Formation ofNorthern Ireland; the changes in whole rock chemistry and mineralogy from basaltthrough to laterite and iron-rich crust were examined. Hill et al. (2000) observed thatprimary olivine, plagioclase feldspar, and augite were successively weathered andreplaced by a mineral assemblage consisting of hematite, gibbsite, goethite, anatase,meta-halloysite and kaolinite. All of the elements for which the mass balance couldbe calculated were depleted in the iron crust, with enrichment of only Al, LOI, Cr,Cu and V in the laterite horizon (Hill et al. 2000). The groundwater chemistry of theTertiary olivine basalts in Northern Ireland was examined by Barnes and Worden(1998), who proposed that the chemical breakdown of feldspars, releasing Na+ andadsorbing Mg2+ following the formation of smectite, and cation exchange of Na+ forMg2+ at exchange sites on clay, are possible influences on the evolution of thebasaltic groundwaters.

Benedetti et al. (1994) notes that studies of water – rock interactions under tropicalhumid conditions are rare. Benedetti et al. (1994) examined solute acquisition bymeteoric waters in the basaltic area of Ribeirão Preto (Paraná, Brazil) to quantify thewater-basalt interaction, to address the impact of biomass on weathering and toestimate the age of the weathering processes affecting the basalts under humidtropical conditions. Studies of basalt weathering processes have also beenundertaken in a humid tropical environment by Benedetti et al. (1999) and Gérard etal. (1999). These studies examined the effects of the early stage of weathering onsoils, streams and spring waters around the active volcano, Mount Cameroon, Africa.In an approach somewhat similar to that taken in this research project, Benedetti etal. (1999) observed relationships between alkalinity and altitude, alkalinity anddissolved silica, and the sum of the cations and alkalinity; they used theserelationships to infer the time of interaction between water and basalt, and alsoproposed that the aqueous major element concentrations are controlled by weatheringreactions. Benedetti et al. (1999) concluded that the aqueous Si4+ and Al3+

concentrations in that area are controlled by amorphous mineral phases, mostlyamorphous Fe-hydroxides and Al-rich allophanes. Gérard et al. (1999) proposed thatthese secondary phases are related to the weathering of glass, which represents a

40

significant proportion of the tephra materials in the Mount Cameroon area. Theweathering of glass, characterized by the release of Si4+, Mg2+, Ca2+, Na+ and K+ tosolution, is the major control on the stream and spring water compositions aroundMount Cameroon (Benedetti et al. 1999; Gérard et al. 1999).

Climates with ‘moderately high precipitation’, defined by Davis and DeWiest (1991)as in excess of 50 inches (1270 mm) / yr, such as parts of North Queensland,southern India, north-eastern South America, and parts of eastern central, central andwestern Africa, usually have marked wet and dry seasons. These areas can thereforebe affected by shortages of water for domestic and agricultural purposes duringsevere dry seasons (Davis & DeWiest 1991). Studies of groundwater systems aretherefore important for sustainable management of groundwater resources in theseenvironments. There is scope for further research into the controls on groundwatercomposition as a means of improving the understanding of groundwater occurrenceand movement in aquifer systems in subtropical and tropical environments.

41

Statistical methods for hydrochemical data assessment

BACKGROUND

Variations in water chemistry variables are often the result of complex interactions asdiscussed above. It is therefore useful to examine the relationships between two ormore variables to gain an understanding of the processes affecting a groundwatersystem (Steinhorst & Williams 1985). An understanding of the chemistry of naturalwaters may be approached through an investigation of statistical associationsbetween dissolved constituents and environmental parameters (such as lithology),enabling a deduction of cause-and-effect relationships (Drever 1997). The mostwidely used statistical technique in geochemistry is R-mode factor analysis(discussed below), which is recommended, for example, for identifyinggroundwaters sourced from different lithological formations based on variations inchemical composition (Drever 1997).

Some descriptive statistical approaches for examining water chemistry data, andseveral methods of multivariate data analysis useful in hydrology andhydrochemistry are discussed below. In addition, methods of data validation anddata preparation, such as transformation (to normalise) and standardizationprocedures are addressed.

DATA DISTRUBUTION AND VALIDATION

Some summary measures of the distribution of data (e.g. the arithmetic mean,median, mode and harmonic mean) and the dispersion of data (e.g. the variance,standard deviation and range) are described by McBean and Rovers (1998). Anotheruseful summary measure is the coefficient of variation, which is used to describe therelative amount of variation in a population. The sample estimate of the coefficientof variation (COV) is defined in Equation 23 as:

xS

COV = (23)

where S is the standard deviation and x is the mean.

Most statistical methods of data analysis require some conformity of distribution,usually the normal distribution (Jöreskog et al. 1976; Reimann and Filzmoser 2000),and some methods also assume multivariate as well as univariate normality.Multivariate normality is the assumption that all variables and all combinations ofvariables are normally distributed. Multivariate normality also implies that therelationships between the variables are linear. The correlation coefficient, which iscentral to R-mode factor analysis, for example, will be adversely affected if thevariables have highly skewed distributions.

The normal (or Gaussian) distribution is based on the Central Limit Theorem, that is,any variable that can be regarded as the sum of a large number of small independent

42

contributions is likely to follow the normal distribution (Rock 1988; McBean &Rovers 1998). The normal distribution is symmetrical about its mean, with tails thatextend to both positive and negative infinity, and the bell shaped algorithm can bedefined by two parameters, the mean and the standard deviation. There are manyother statistical distributions found in water chemistry and environmental studies. Asummary of the normal, lognormal, bimodal, Poisson, exponential and Paretodistributions, as well as several other distributions, is provided by McNeil (2002).

Most variables in the earth and natural sciences have an asymmetric distribution(Reyment 1971; Rock 1988; Goovaerts 1997). The lognormal distribution, forexample, is common for many types of hydrological and chemical data, that is, thedata are positively skewed with no negative values (McBean & Rovers 1998). Thelognormal distribution for geochemical data was proposed by Ahrens (1953, 1954a,1954b, 1957), although this idea was criticized, for example, by Aubrey (1954,1956), Chayes (1954), Miller and Goldberg (1955) and Vistelius (1960). The normaland lognormal distributions in geochemistry are discussed by Reimann andFilzmoser (2000), who propose that distributions are rarely normal or lognormal.While the logarithmic transformation is commonly applied to hydrological data, asdiscussed below, a careful examination of the data should always be undertaken todetermine the distribution type and appropriate transformation method.

To assess for normality, an examination of skewness and kurtosis as well as thecoefficient of variation is usually undertaken (Rummel 1970). Skewness is related tothe symmetry of the data distribution and kurtosis to the peakedness of thedistribution. McBean and Rovers (1998) state that the normal distribution has askewness of zero, a kurtosis coefficient value of three and a COV less than 0.5 or1.0, with a COV exceeding 1.0 strongly indicating that the data are not normallydistributed.

Other tests for normality include “goodness-of-fit” tests, such as the chi-square, theShapiro-Wilk for small sample sizes (< 50) and the Shapiro-Francia andKolmogorov-Smirnov tests for larger sample sizes (> 50). These tests for normalityare described by McBean and Rovers (1998) and in many other texts dealing with thestatistical treatment of data. Histograms and probability tests can also be used toconfirm normality.

Univariate and multivariate outliers also need to be removed from data, due to theirstrong influence on the calculation of correlation coefficients, which in turninfluences, for example, the calculation of components or factors in principalcomponent analysis or factor analysis. In addition, tests for linearity, such asgraphical analyses of pairs of variables should be undertaken prior to most statisticalprocedures (Jöreskog et al. 1976). Thorough explanations of methods for detectingoutliers and procedures for validating data are provided by McNeil (2002).

Another important measure is the correlation coefficient, a measure of the strength ofassociation between two variables measured on a number of individuals (Jöreskog etal. 1976; Rollinson 1993). The parametric Pearson product-moment coefficient oflinear correlation makes considerable assumptions about the nature of the dataassessed, that is, that the units of measurement are equidistant for both variables,

43

there is a linear relationship between the variables, and both variables are normallydistributed (Rollinson 1993). In some circumstances, therefore, a non-parametricapproach such as the Spearman rank correlation coefficient is more appropriate.

Most of the statistical methods discussed in this literature review are parametric,assuming that the data are normally distributed. This is generally not the case in theearth and natural sciences, as has been discussed. Rock (1988) notes, however, thatparametric tests are robust, that is, not too seriously affected by departures fromnormality. Alternative non-parametric tests include the Runs test, the Wilcoxon test,the Mann-Whitney test, the Kruskal-Wallis test and the Spearman rank correlationcoefficient. A discussion of some non-parametric tests, for use specifically withwater quality data, is provided by Lettenmaier (1976). An example of ahydrogeochemical study in which non-parametric methods, such as the Wilcoxonand the Mann-Whitney tests, have been used is that by Korkka-Niemi (2001).

TRANSFORMATION AND STANDARDIZATION METHODS

Transformations are used to normalise data, to reduce the influence of extremevalues or outliers (Goovaerts 1997), and to remedy failures of linearity andhomoscedasticity (the variability of one variable for a given value of another)(Rummel 1970).

A transformation of data should not be considered as a stratagem to make the data fitsome preconceived notion. Logarithms of amounts, for example, are no lessreasonable than amounts expressed in mg/L or ppm, and experience indicates thatlogarithmic values more closely reflect natural distributions of variables (Jöreskog etal. 1976). In addition, the logarithmic (as well as the square root) transformation ismonotonic, and so therefore preserves the rank of the original data in the cumulativedistribution (Goovaerts 1997).

Two transformations, the logarithmic (natural or Briggsian) and the square root, arecommonly applied to skewed distributions, which pull in the tail of the distributionby reducing the arithmetic size of the intervals as the values increase (Jöreskog et al.1976). Other transformations include the reciprocal, squared, exponential, rank andarcsine. Descriptions and uses of these and other transformation methods, as well asexamples from published literature, are provided by McNeil (2002). An analysis ofthe use of transformation was undertaken by Bartlett (1947) and good discussions ofdistribution types and transformation methods are provided by Rummel (1970) andHirsch et al. (1991).

The logarithmic transformation is widely considered as the most appropriatetransformation method in studies in hydrology (e.g. Leopold 1962; Wallis 1965;Reeder et al. 1972; Miller & Drever 1977; Symader & Thomas 1978; Williams1982). Wallis (1965) does point out, however, that each data set should be carefullyanalysed to determine the most appropriate transformation method. In addition, theeffect of the transformation of the data should also be examined and should not beassumed to have the effect of normalizing the data. Reyment (1971), for example,found that a logarithmic transformation of some natural data resulted in improved

44

univariate kurtosis, but in greater skewness of the data. In a factor analysis of somehydrochemical data, Ruiz et al. (1990) found that if the logarithms of concentrationsare used instead of the actual values, the communalities calculated are much lower,indicating that the correlation is not improved by the transformation of those data.Rummel (1970) also recommends that the adequacy of a transformation be assessed,a procedure that has been undertaken for this study (PAPER 2).

The transformation method found to be the most appropriate for this study(PAPER 2) was the natural logarithm ln (x + 1). This method has also been used byHitchon et al. (1971) and Steinhorst and Williams (1985) to normalisehydrochemical data.

The simplest procedure to achieve multivariate normality is to transform eachvariable using the appropriate univariate technique as discussed above, and althoughthis approach does not guarantee multivariate normality, it does increase thelikelihood (Jobson 1992). Another approach for detecting multivariate outliers, thatis, the Mahalanobis distance measure, is discussed by Dillon and Goldstein (1984)and Jobson (1992). Important references on multivariate normality include Mardia(1970) and Reyment (1971).

Many types of geological and natural resources data are also problematic in that theyare compositional. That is, the data are expressed, for example, as %, ‰ or ppm,which sum to a constant value (Jolliffe 1986; Reyment & Jöreskog 1996). This typeof data is termed closed (Rock 1988) as it forms a closed array (Rollinson 1993).The principal consequence of ‘closure’ (or the ‘constant sum effect’) is thatcorrelations can produce misleading results (Rollinson 1993). The ‘constant sumeffect’ is addressed by Aitchison (1982, 1983, 1984) in a series of detailed papers.Aitchison (1986) proposes that log-ratios of the variables should be calculated to freeclosed data from their restricted space (or ‘simplex’), with the preferredtransformation being the centred log-ratio, where the divisor is the geometric meanof each variable. This method is discussed and supported by Jolliffe (1986) andReyment and Jöreskog (1996), although an example of a principal componentanalysis using both raw and centred log-ratio transformed data provided by Jolliffe(1986), shows that there were little differences between the two sets of results. Theapplicability of the centred log-ratio transformation to the hydrochemical data usedin this study was examined in PAPER 2.

The implications of ignoring the distribution of data prior to using statisticalanalytical methods requiring normality should not be underestimated. For example,in an assessment of a study by Salman and Abu Ruka’h (1999), Szava-Kovats (2000)proposed that a log-ratio transformation should have been applied to that data, toeliminate the effects of closure and negative correlation between variables. A lack ofconsideration of issues pertinent to compositional data and of the requirement offactor analysis for univariate and multivariate normality by Salman and Abu Ruka’h(1999) resulted in spurious interpretation of the factor analysis results (Szava-Kovats2000).

45

Standardization refers to converting original data to standard normal deviates or zscores by centring them about their mean ( )x and rescaling them by the reciprocal oftheir standard deviation ( )S (Steele & Matalas 1971; Jöreskog et al. 1976; Steinhorst& Williams 1985; Rock 1988; Auf der Heyde 1990; Briz-Kishore & Murali 1992;Hussein & Adam 1995; Join et al. 1997) as shown in Equation 24, where

S

xx −=z (24)

Standardizing combines the effects of column normalization and column centring,and is appropriate in studies where the variables are measured on different scales andin different units (Steinhorst & Williams 1985; Schot & van der Wal 1992; Reyment& Jöreskog 1996), as is the case in this study (PAPER 2).

MULTIVARIATE DATA ASSESSMENT

Multivariate data analysis is concerned with analyzing multiple measurements onone or several samples (Cooley & Lohnes 1971). Graphical methods (such as Piper,Stiff and Schoeller diagrams), principal component analysis and factor analysis arewidely used methods of multivariate data analysis in hydrochemical studies. In bothprincipal component analysis and factor analysis, the main aim is to replace theoriginal variables with a smaller number of underlying variables, that is, to reducethe dimensionality of a variable set (Dunteman 1989). Principal component analysisconsists in finding an orthogonal transformation of the original variables to a new setof uncorrelated variables, called principal components (Chatfield & Collins 1980).That is, principal component analysis reduces the number of variables to a smallernumber of principal components that are linear combinations of the originalvariables. Factor analysis has similar aims to principal component analysis, but isbased on a linear statistical model, which specifies a number of underlying variablescalled factors (Chatfield & Collins 1980).

Many modern multivariate studies of water chemistry data use a variety of methods.A combination of multivariate methods have been used by van Tonder and Hodgson(1986), including cluster analysis, principal component analysis and discriminantanalysis, to define hydrochemical facies in groundwater. It has also been noted byMcNeil (2002) that whichever multivariate technique is selected as the primaryanalytical tool, it is advisable to support it with another method for verification. Inthis study (PAPER 2 and APPENDIX V) principal component factor analysis hasbeen used to identify the likely hydrochemical processes controlling groundwatercomposition in the Atherton Tablelands region. Principal component factor analysishas also been used as a form of discrimination, as defined by Kendall and Stuart(1966), to allocate unknown samples to defined groups (PAPER 2 andAPPENDIX V), and cluster analysis has been applied to the results to confirmgroupings (PAPER 2).

Some graphical methods for multivariate data analysis, principal componentanalysis, factor analysis, principal component factor analysis and cluster analysisare discussed below and examples of applications of these methods provided.

46

Particular emphasis is placed on the application of these methods to hydrological andhydrochemical studies and avenues for further application of these methods areidentified. Some limitations of factor analytical procedures are also discussed, andsome additional multivariate data analysis methods, that is, multiple regressionanalysis, discriminant analysis, canonical correlation analysis, common principalcomponent analysis, correspondence analysis and classification schemes are brieflyaddressed.

Graphical methods

Hydrochemical data are commonly displayed in graphical form. Many graphicalforms have been proposed, including X-Y scatter plots, bar graphs (e.g. Collins1923), pie diagrams and nomographs (Freeze & Cherry 1979; Hem 1985; Davis &DeWiest 1991; Domenico & Schwartz 1998). The use of graphical methods tointerpret water chemistry data is discussed by Zaporozec (1972). Several of themethods described below have been used in this study.

The most widely used graphical method of displaying hydrochemical facies is thePiper diagram (Piper 1944), similar to that developed by Hill (1940), which is aneffective tool for segregating analytical data, with respect to sources of dissolvedconstituents, modifications in the character of water along a flow path, and relatedgeochemical problems. The procedure is based on a multiple trilinear diagram,commonly displaying the percent concentrations of the major dissolved constituents(i.e. Ca2+, Mg2+, Na+, K+, HCO3

-, CO32-, SO4

2- and Cl-). Recent examples of theapplication of the Piper diagram to hydrochemical studies include those byMcKenzie et al. (2001), Naik et al. (2001) and Umar et al. (2001).

The Durov (Durov 1948) and the Expanded Durov (Lloyd 1965; Lloyd & Heathcote1985) diagrams are also widely used forms of trilinear graphical representation forhydrochemical data (e.g. Lawrence et al. 1976). The Durov diagram can be used toclassify water into types (or facies), to determine the concentration of chemicalconstituents and total dissolved solids, to study the origin of the chemicalcomposition of water and for correlating chemical analyses (Abdulaziz et al. 1997).

The Stiff (1951) pattern is also used to present chemical analyses, and is useful inmaking a rapid visual comparison between water from different sources. The Stiffpattern is based on a polygonal shape created from four parallel horizontal axesextending from either side of a vertical zero axis. Cations are plotted inmilliequivalents per litre on the left of the zero axis and anions are plotted on theright (Fetter 1994).

Other diagrams used to present hydrochemial data include the Langelier-Ludwig(1942) diagram and the Schoeller (1956) diagram. Cross-sections are also used todisplay hydrochemical data and interpretations in two, or even three dimensions,which are sometimes referred to as ‘fence diagrams’ (e.g. Back 1961; Amadi et al.1989; Stein & Schwartz 1990; Schreiber et al. 1999; Stuyfzand 1999; Tóth 1999).

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Principal component analysis

The technique of principal component analysis was first described by Pearson (1901)in his mathematical methodology of fitting planes by orthogonal least squares, andwas later independently developed by Hotelling (1933, 1936a) for analyzingcorrelation structures. These papers can be found among a collection of papersedited by Bryant and Atchley (1975). A precursor to principal component analysis,however, was the reduction of a square matrix into its singular components(Sylvester 1889). The historical development of principal component analysis, albeitwith an emphasis on meteorological applications, is provided by Preisendorfer(1988).

A thorough explanation of principal component analysis, including examples, can befound in Jolliffe (1986), and Rao (1964) provides ideas for uses, interpretations andextensions of principal component analysis. The following quotation by Rollinson(1993) describes the principal component extraction method:

The method defines a new set of orthogonal axes called eigenvectors or latent roots. Forinstance, the first eigenvector is the direction of maximum spread of the data in terms ofn-dimensional space. It is a ‘best fit’ line in n-dimensional space and the original data canbe projected onto this vector using the first set of principal component coordinates. Thevariance of these coordinates is the first eigenvalue or latent root, and is a measure of thespread in the direction of the first eigenvector. For example, eigenvector 1 may beexpressed as

.......OAlxTiOxSiOx1rEigenvecto 3232221 ++= (25)

where 321 xxx ++ etc., define the principal component coordinates.

The method then defines a second eigenvector, which has the maximum spread at rightangles to the first eigenvector, and so on. The eigenvalues are used to measure theproportion of data used in each eigenvector. By definition, the first eigenvector willcontain the most information and succeeding eigenvectors will contain progressively lessinformation. Thus it is often the case that the majority of information is contained in thefirst two or three eigenvectors. Eigenvectors and eigenvalues may be calculated eitherfrom a covariance matrix (where the variables are measured in the same units, such as wt%or ppm) or from a correlation matrix where the variables are expressed in different units.

Principal component analysis is a mathematical technique, which does not require anunderlying statistical model to explain the error structure (Chatfield & Collins 1980).Principal component analysis makes no assumptions about the underlying structureof the variables, and requires no a priori estimates of the communalities (Seyhan1985). The percent variance of each variable explained by the components or factorsis termed the communality; communalities may be interpreted as indicators of thereliability of the components.

There are numerous computer packages available for principal component analysis.Brief descriptions of some of these packages, that is, the BMDP suite of programs,GENSTAT, MINITAB, SAS and SPSS, are provided by Jolliffe (1986).

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Factor analysis

Factor analysis is the most commonly used multivariate statistical method inhydrology (Seyhan & Hope 1983). The primary objective of factor analysis is torepresent a group of variables (or cases) in terms of several factors (Hotelling 1933,1936a; Rummel 1970; Harman 1976; Morrison 1990). The specific objectives offactor analysis, as outlined by Seyhan (1985) are:

to study the intercorrelation of a large number of variables (or cases),

to interpret each factor according to the intercorrelated variables (or cases)grouped under that factor, and

to use the factors to omit non-significant variables (or cases).

A variant of factor analysis, that is, principal component factor analysis, has beenused to meet such objectives in a hydrogeochemical study of the Atherton Tablelandsaquifer systems (PAPER 2).

Like principal component analysis, factor analysis accounts for the variation in anumber of variables using a smaller number of factors. However, in factor analysiseach variable is expressed as a linear combination of factors, plus a residual term thatreflects the independence of the variable (Rummel 1970; Mulaik 1972; Manly 1986).That is, any observed variable is assumed to be influenced by some factors which arecommon to all the variables and by some unique factors; the unique factors being theresidual variance that is not explained by the common factors (Seyhan 1985;Morrison 1990).

In principal component analysis the components account for the maximum varianceof all the variables, whereas in factor analysis, the factors are defined to accountmaximally for the intercorrelations of the variables. That is, principal componentanalysis is variance-oriented; factor analysis is correlation-oriented. The residualterms are assumed to be small in principal component analysis, and a large part ofthe total variance of a variable is assumed to be in common with other variables.Factor analysis, however, allows uniqueness to be present in the data and utilizesonly that part of a variable that is in correlation with other variables (Reyment &Jöreskog 1996). Communalities are therefore estimated before applying a factoranalysis.

The concept of latent factors was first proposed by Galton (1888). The earlydevelopment of factor analysis may, however, be attributed to Charles Spearman,who observed that correlations between test scores could be accounted for by asimple model (Spearman 1904). Spearman (1927) developed a model for twofactors, which was later extended to include multiple factors (Thurstone 1935). Theterm factor analysis was first introduced by Thurstone (1931). The history of factoranalysis has been described by Mulaik (1972, 1986).

Equation 26 is a general factor analysis model reproduced after Manly (1986):

49

imimiii eFaFaFaX ++++= ........2211 (26)

where iX is the ith test score with mean zero and unit variance; imii aaa ,........,, 21 are the

factor loadings for the ith test; mFFF ,........,, 21 are m uncorrelated common factors, each

with mean zero and unit variance; and ie is a factor specific only to the ith test, which is

uncorrelated with any of the common factors and has mean zero. With this model

( ) ( ) ( ) ( ) ( )imimiii eFaFaFaX varvar........varvar1var 22

221

21 ++++== (27)

( )iimii eaaa var........ 222

21 ++++= (28)

where 222

21 ........ imii aaa +++= is called the communality of iX (the part of its variance

that is related to the common factors) while ( )ievar is called the specificity of iX (the

part of its variance that is unrelated to the common factors).

Factor analysis may be used to explore the underlying dimensions of the data and asa means of data reduction in what is known as exploratory factor analysis, or as ameans of testing specific hypotheses about factor loading patterns in confirmatoryfactor analysis (Dunteman 1989). The division of these uses, however, may notalways be clear (Lewis-Beck 1994). There are many types of factor analysismethods as noted by Seyhan (1985). They differ by the procedural steps in:

the input data matrix (i.e. R-mode analysis of variables or Q-mode analysis ofcases),

the extraction of the factor loadings (methods of initial factor extractioninclude principal components, principal factors, centroid, least-squares,maximum-likelihood, minres etc.), and

the type of rotation of the determined factors, such as orthogonal rotation(e.g. varimax, quartimax or equimax methods) or oblique rotation (e.g.promax, oblimax, oblimin or quartimin methods).

It is outside the scope of this literature review to describe each of these methods.Factor analytical methods are well described by Horst (1965), Cooley and Lohnes(1971), Lawley and Maxwell (1971), Mulaik (1972), Rummel (1970), Harman(1976), Davis (1986), Morrison (1990), Briz-Kishore and Murali (1992), Lewis-Beck(1994), Hair et al. (1995), Reyment and Jöreskog (1996) and Rollinson (1993), thelatter specifically in terms of geochemical data. In addition, the main factoranalytical procedures, notably the effectiveness of extraction and rotation methods,are discussed by Cattell and Jaspers (1967) based on their investigations using afactor plasmode (a set of measurements which fit a particular form or structure).

More detailed discussion of theoretical methods here is limited to those applied inthis study (PAPER 2), that is, R-mode analysis of variables using a principalcomponent factor extraction method, the varimax rotation method, as well as the

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various criteria for selecting the number of factors to be extracted and methods forcalculating factor scores.

Some examples of factor analytical techniques applied to the natural sciences areoutlined by Reyment and Jöreskog (1996) and include those in the fields of:

Sedimentary petrology – Osborne (1967, 1969) used factor analysis to groupOrdovician limestones on the basis on characteristics determined in thinsection, and inferred the paleoecological significances of the factors.

Stratigraphy – McElroy and Kaesler (1965) interpreted factors from ananalysis of sandstone groundwaters in Kansas in terms of subsidence duringdeposition of the sandstone, regional distribution patterns, and periods ofuplift or non-subsidence.

Geochemistry – Armands (1972) used principal component and factoranalysis of the geochemistry of uranium, molybdenum and vanadium inSwedish alum shale to determine the paragenesis of these elements. Thecategories established were detrital, authigenic, carbonate, sulfide andorganic.

Other examples include those by Auf der Heyde (1990) who applied factor analysisto a hypothetical chemical data set, Ratha and Sahu (1993) who investigated soilgeochemical variables in an industrial area of Bombay, India, using R-mode factoranalysis and Lin (2002) who used factor analysis to relate industrial waste plants andirrigation systems to heavy metal concentrations in soils in Taiwan.

Principal component factor analysis

Principal component factor analysis is one of several models of factor analysis.Alternative approaches include, for example, maximum likelihood factor analysis(Lawley & Maxwell 1971). Reyment (1991) notes, however, that as practised in thenatural sciences, factor analysis is essentially a variant of principal componentanalysis, with some of the features appertaining to classical factor analysis. Thisvariant was termed principal component factor analysis by Jöreskog et al. (1976).

Following the initial steps in preparing the input data matrix (i.e. selection of R-modeversus Q-mode analysis and transformation and standardization of data if required), asimilarity matrix is computed to examine the interrelationships among the variablesor cases. This similarity matrix is usually a correlation or a variance-covariancematrix. The use of standardized variables and the correlation matrix ( R ) is advisableif the variables have different units (Morrison 1990) and recommended forhydrological studies (Seyhan 1985). Also, while Q-mode analysis is often used insedimentology, for example, R-mode analysis is most commonly used in studies ofwater chemistry (Drever 1997).

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The principal component factor analysis (with iteration) method in SPSS (v.10.0.5)refers to the estimation of factor loadings and transformation of the correlationmatrix in order to determine whether some smaller number of factors will explainmost of the variance in the original data (Seyhan 1985). The procedureautomatically replaces the main diagonal elements of R with communality estimates,with the iteration procedure improving these estimates (Foster 1998).

Transformation of the factor matrix produces a new pattern of factor loadings that aremore easily interpreted. The objective of transformation is to simplify the structureof the factor matrix, as only those factors for which the variables have a simplestructure are meaningful (Thurstone 1947). The principal of simple structureproposed by Thurstone (1947) is that a variable should not depend on all commonfactors but only a few, and that each factor should only be associated with a smallportion of the variables (Reyment & Jöreskog 1996). Thurstone (1947) provided anumber of rules for the determination of simple structure. These are outlined byMulaik (1972) and in many texts on factor analysis.

Transformation may be achieved by orthogonal axes rotation, resulting inuncorrelated factors. Seyhan (1985) notes that it is generally considered thatprincipal component factor analysis differs from classical factor analysis mainlybecause the rotations made with classical factor analysis are not necessarilyorthogonal (Blackith & Reyment 1971).

Early analytical solutions for factor rotation, including those by Carroll (1953),Saunders (1953), Ferguson (1954b) and Neuhaus and Wrigley (1954), enabled thereduction of Thurstone’s (1947) simple structure concepts to mathematical functions(Seyhan 1985), based on the quartimax criterion. Other orthogonal rotation methodsdeveloped by Kaiser (1956, 1958, 1959) known as the raw varimax criterion and thenormal varimax (or merely the varimax) have become the most widely used rotationtechniques in multivariate statistical research (Jöreskog et al. 1976; Seyhan 1985;Dunteman 1989). The raw varimax maximises the variance of the squared loadingswithin each column of the rotated factor matrix. Kaiser later modified this approachwith the normal varimax (1958), which takes into account the magnitude of thecommunalities by normalizing the factor loadings. The factor loadings are dividedby their corresponding communality value, and following rotation, each factorloading is multiplied by the square root of the respective communality. An outlineand examples of varimax rotation are given by Harman (1976). The varimax rotationwas quickly applied to studies in hydrology, by Wong (1963) and Wallis (1965), forexample, and remains popular in water chemistry studies (e.g. Suk & Lee 1999;Jeong 2001b, Meng & Maynard 2001).

In a principal component factor analysis with orthogonal rotation, factor loadings areequivalent to correlations between factors and variables (Lewis-Beck 1994).Loadings of the same sign on a factor are positively correlated variables; loadings ofopposite signs are negatively correlated variables (Drever 1997).

The number of factors calculated for a particular data set is based on the experienceand professional judgment of the hydrogeologist, who must then evaluate theimplications of the groupings (Riley et al. 1990). Various criteria may be used to

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determine the number of factors that should be extracted; reviews of the ‘number offactors’ problem have been made by Browne (1968), Linn (1968), Tucker et al.(1969), Hakstian and Muller (1973), Hakstian et al. (1982), and Zwick and Velicer(1982, 1986).

The Guttman (1954) selection rule, supported by Kaiser (1960), proposes that theleast number of factors to be retained is that number for which all eigenvalues greaterthan or equal to one are kept. An eigenvalue of one means that factor has as muchvariation as one variable. Other methods include the Cattell (1966) scree test, basedon the observation that the factor variance levels off when the factors are largelymeasuring random error, and the LEV rule (Craddock & Flood 1969; Farmer, 1971),an alternative to the scree test, popular in fields such as meteorology (Jolliffe 1986;Preisendorfer 1988; DeGaetano 1996). Jolliffe (1972) proposes that factors witheigenvalues less than 0.7 should be dropped, while some researchers keep enoughfactors to account for 90 % of the variance in the data.

It is recommended by Seyhan (1985) that several criteria be applied and resultscompared, to determine the final number of significant factors. As a general rule,extracting too many factors is preferred to extracting too few factors, asunderfactoring can distort the factor structure (Rummel 1970; Reyment & Jöreskog1996). While the above rules of thumb should be applied to extract the ‘right’number of factors, it is worth keeping in mind that the extensive practical experienceof Cattell (1952) and the empirical studies of Mosier (1939) consistently indicate thatoverfactoring results in better interpretations than underfactoring. For example,although Reyment and Jöreskog (1996) recommend that the number of factors shouldbe limited to those with at least three significant loadings, the need forinterpretability may require more factors than this to be retained. Hitchon et al.(1971), for example, have included several unique factors in their R-mode analysis ofsubsurface brines, as those factors (such as membrane filtration, solution of halite,chlorite formation and cation exchange) represent important processes controlling thegeochemistry of those waters.

In terms of a principal component or factor analysis of chemical data, in addition tothe considerations noted above, the number of factors extracted must be less than thenumber of variables. Steele and Matalas (1974) note that if the ionic species weremutually independent, then the number of principal components m, would equal thenumber of ionic species (variables) n. However, the ionic species cannot be mutuallyindependent because the cations and anions are in balance, and therefore due to co-linearity among the variables, 1−≤ nm .

In R-mode analysis a factor may be regarded as a function of the original variables.By calculating factor scores, the ‘amount’ of these new factors may be determinedand examined (Jöreskog et al. 1976). Factor scores are simply calculated for aprincipal component factor analysis, as outlined by Lawley and Maxwell (1971),Seyhan (1985), Rock (1988) and Buccianti (1997), and for example by Lee (1969) ina principal component analysis of connate waters in northern Taiwan. Known asexact factor scores, they are linear combinations of the variables (Rummel 1970).Factor scores, therefore, express the degree to which each case represents theproperty or process that the factor defines. Dekkers et al. (1989) also note that an

53

analysis (such as cluster analysis) of component or factor scores, rather than of theraw data, enables an interpretation of hydrogeochemical processes that are describedby more than one variable.

The calculation of factor scores for classical factor analysis is more complex.Methods include regression estimates, estimates based on ideal variables (‘leastsquares’ criterion), the Bartlett (1937) method of minimizing the error variance, andestimates with orthogonality constraints such as the Anderson-Rubin criterion(Anderson & Rubin 1956). These methods are explained by Rummel (1970),Lawley and Maxwell (1971), Harman (1976), Lewis-Beck (1994) and Reyment andJöreskog (1996). It is worth noting, however, that some authors (e.g. Schönemann &Wang 1972; Velicer 1976) consider that there is little practical difference betweentrue (or exact) factor scores and factor score estimates.

Limitations of factor analysis

Multivariate methods of data analysis are complex, in both their theoretical structureand in their operational methodology. Care must therefore be taken to adhere to theassumptions in these methods, so that the results may be accurately and practicallyinterpreted (Davis 1986).

Limitations on the use of classical and principal component factor analyses areoutlined by Ehrenberg (1962), Matalas and Reiher (1967), Wallis (1968), Seyhan(1985) and others. Some of these limitations include:

factor analysis was originally developed for psychological data.Hydrological data, however, are different in that they are rarely a largerandom sample taken from a homogeneous population (Wallis 1968),

the meaning of factors can be vague, as factors are non-observable(Ehrenberg 1962),

factor analyses are linear functions; non-linear functions may lead to betterresults,

an orthogonal rotation may not be appropriate for all hydrological processes,and

the variables must be selected carefully, otherwise analyses may bemisinterpreted. Also, any new variable added to or dropped from the analysismay result in a different grouping of factors (Steele & Matalas 1974).

Anderson (1957) also recommends prior evaluation of issues such as:

the types of relationships that exist among the variables (such as, are therelationships linear, and if not, can the variables be transformed to form linearrelationships?),

the number and type of factors to be extracted, and

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the variables to be considered for analysis.

In the case of a hydrogeochemical study, the number and type of hydrogeochemicalprocesses expected should be considered. In addition, the variables studied shouldbe consistent with the factors expected (Cattell 1952; Reyment & Jöreskog 1996).For example, in a study of formation waters in Alberta, Canada, Hitchon et al. (1971)chose variables that were relevant to the hypothesis that there is a relationshipbetween particular elements and filtration of groundwater though shale membranes.

Some of the prior considerations and limitations of the principal component factoranalysis method as applied to the Atherton Tablelands data have been examined anddiscussed in PAPER 2, and an assessment of the robustness or sensitivity of theanalysis undertaken.

Cluster analysis

Like factor analysis, cluster analysis was first developed by psychologists in the1930’s and 1940’s, and can also be applied to R-mode (variable oriented) or Q-mode(sample oriented) problems (Seyhan 1985). As an exploratory technique, clusteranalysis does not require many of the assumptions that other statistical methods do,except that the data be heterogeneous. Cluster analysis provides an easily understoodgraphic display (dendrogram) and is a method used frequently in the geologicalsciences to group samples or variables of a data set (Alther 1979; Pacheco 1998;Meng & Maynard 2001).

Useful texts on cluster analysis include those by Tyron and Bailey (1970), Anderberg(1973), Everitt (1980) and Hartigan (1975), the latter including algorithms andcomputer programs. Davis (1986) discusses cluster analysis with applications forearth sciences and Gong and Richman (1995) provide a review of cluster analysisprocedures.

Cluster analysis groups a set of observations into clusters in such a way that mostpairs of observations in the same group are more similar to each other than are pairsof observations in two different groups (Jolliffe 1986). Similarity may be expressedthrough a set of distances between pairs of objects. One such measure of similarityis the Euclidean distance, which is essentially a straight-line distance between thevectors corresponding to the cases (Hartigan 1975). The Euclidean distance betweentwo points is the length of the distance vector and is found by Pythagoras’s theoremfrom the square root of the minor product moment of the difference vector (Reyment& Jöreskog 1996). The Euclidean distance function is most frequently used forquantitative variables, which are usually standardized prior to calculation, to ensurethey contribute equally to the determination of distance (Manly 1986).

Hierarchical methods of cluster analysis produce a dendrogram in which groups areformed by agglomeration or division. In an agglomerative hierarchical method,individuals begin alone in groups of one, and groups that are close together aremerged, whereas a divisive method starts with a complete data set and successivelydivides it (Manly 1986; Rock 1988). There are numerous linkage methods to define

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closeness, including single (or nearest neighbour) linkage, furthest neighbour (orcomplete linkage), group average linkage, centroid sorting, Ward’s and weightedgroup average methods (Chatfield & Collins 1980; Manly 1986).

Examples of the application of cluster analysis to studies in the natural sciencesinclude those by Campbell et al. (1970) in a classification of some Australian soilprofiles, Auf der Heyde (1990) in an analysis of chemical data, Gong and Richman(1995) in an assessment of some North American rainfall data, and DeGaetano(1996) who used both principal component analysis and cluster analysis to delineateclimatically similar zones in the north-eastern United States. Cluster analysis wasalso found to be a useful tool in the detection of temporal and spatial patterns ofwater chemistry in Lake George, north-eastern New York (Momen et al. 1996) andin the discrimination of groundwaters from different geological units in the Gedarefbasin in eastern Sudan, based on their chemical compositions (Hussein & Adam1995).

Alternative multivariate statistical methods

There are many other types of multivariate statistical methods that may be applied tostudies in hydrology and hydrochemistry, although the methods described above, thatis, principal component analysis, factor analysis and cluster analysis and theirvariants, are the methods most commonly used.

Multiple regression analysis is based on the concept that an observed variable can bedefined as a function of other variables measured at the same time, although notconsidered by Davis (1986) as a true method of multivariate analysis, as the varianceof only one variable is considered. It has been applied, for example, in a studycalculating runoff from catchment physiography in South Africa (Seyhan & Hope1983). One of the major problems of multiple regression with the usual least squaresestimators, however, is the problem of multicollinearity, which occurs when there arenear-constant linear functions of two or more of the predictor (regressor) variables,that can lead to unstable and misleading estimates of the regression equation (Jolliffe1986).

Discriminant analysis may be applied to data in which each observation comes fromone of several well-defined groups or populations. Assumptions are made about thestructure of the populations, and the main objective is to construct rules for assigningfuture observations to one of the populations (Jolliffe 1986). Discriminant analysishas been used by Villagra et al. (1990), for example, in a comparison of surfacewaters and hydrothermal springs. Davis (1986) notes that while discriminantanalysis is reasonably robust with departures from normality, it is highly sensitive tooutliers in the original data. Because of this, and assumptions in the method, McNeil(2002) proposes that discriminant analysis is not suited to the exploratory analysis oflarge irregular data collections, and may be more suitable to follow-up analyses inwhich samples are placed in groups established by classification procedures such ascluster analysis.

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Discriminant analysis may be regarded as a special type of factor analysis thatextracts orthogonal factors to show the differences among several groups (Seyhan &Hope 1983). It has been successfully used by Seyhan and Hope (1983) to determinethat two catchments in environmentally different regions of South Africa arestatistically different in terms of physiography and hydromorphometry. In a mannersimilar to this approach, the use of a principal component factor analysis todiscriminate between basalt- and basement rock-hosted groundwaters in the AthertonTablelands region, and the establishment of a rule to allocate unknown samples toone of these two groups (PAPER 2), may in fact be regarded as a form ofdiscriminant analysis.

Canonical correlation analysis involves the division of variables into two groups andan examination of the relationships between these groups (Manly 1986). Originallydeveloped by Hotelling (1935, 1936b), the canonical correlation is the maximumcorrelation between linear functions of the two vector variables (Cooley & Lohnes1971). The objective is to successively find pairs of linear functions called canonicalvariates, such that the correlation between them is maximized, while each new pair isorthogonal to all previously derived linear combinations (Cooley & Lohnes 1971;Jolliffe 1986).

An example of an application of canonical correlation analysis is provided by Jeffers(1978) in a study from the north-west of England. Variables of two types wereexamined; variables measuring chemical or physical properties of sand or mudsamples, and variables measuring the abundance of invertebrate species in thesamples. Canonical correlation analysis was used to examine the relationshipsbetween the two groups of variables describing environment and species. Althoughnot a method applicable to this particular study, one can envisage where canonicalcorrelation analysis could be applied to a hydrochemical study where, for example,the relationships between variables measuring water quality parameters and variablesmeasuring different types of land use are of interest.

Common principal component analysis is one of the newer methods of multivariateanalysis, currently mainly applied in the fields of palaeontology, palaeoecology andevolutionary studies (Reyment 1997). Common principal component analysis is aprocedure for the simultaneous principal component analysis of several groups. Themethod is described by Flury (1984, 1988), Krzanowski (1984) and Jolliffe (1986).The concept of common principal components may be applied where it is suspectedthat the same components underlie the covariance matrices of each group, but thatthey have different weights in each group (Jolliffe 1986). Bookstein (1991) notesthat this method has an advantage over canonical variate analysis, which has alogical insufficiency if group differences are established a posteriori by someclustering technique (Reyment 1997).

The common principal component analysis may not prove likely to be applicable to agreat number of situations, however, mainly because data that meet the strictrequirements of this method are relatively rare (Reyment 1997). This method hassome attraction for the field of hydrochemistry where, for example, the sameprocesses may effect the composition of waters from different geological formations,but to varying extents. Reyment (1997) states that compositional data can be made to

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fit the common principal component model by the appropriate log-ratio covariancematrix. Reyment (1997) recommends, however, that currently it would be wise torestrict common principal component analysis to multivariate Gaussian (normal)datasets, as the methods for assessing the stability of common principal componentlatent vectors still needs to be examined. Common principal component analysismay, however, prove to be useful in some hydrochemical studies in the future.

In a statistical analysis of hydrogeochemical data from the alluvial aquifer of AltoGuadalentín, south-east Spain, Cerón et al. (2000) used both principal componentanalysis and another multivariate statistical method, correspondence analysis, toassess sources of and processes affecting groundwater. Correspondence analysisproved to be more useful than principal component analysis in that study, asprincipal component analysis was unable to distinguish the three sources of water,due to the influence of extreme values (Cerón et al. 2000).

Although not strictly a statistical method, another multivariate approach to analyzingdata is through the use of classification schemes. Classification schemes arecommonly used in hydrogeology such as, for example, matrix and rating systems ingroundwater vulnerability and risk mapping studies (e.g. LeGrand 1964; Foster1987; Adams & Foster 1992). They can also be developed to assess hydrochemicaldata. An example of a classification scheme approach to assessing hydrochemicaldata and application of the results are presented for this study (PAPER 1B andAPPENDIX IV).

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Application of some multivariate statistical methods to hydrological and

hydrochemical studies and scope for further work

BACKGROUND

Studies in hydrology and hydrochemistry include problems involving complexinteractions of many variables and processes. In early hydrological studies(e.g. Anderson 1957; Fritts 1962) these problems were approached using multipleregression analysis. However, multiple regression analysis tends to confoundindependent effects and to build models that are hard to interpret (Wallis 1965;Eiselstein 1967). Comparative results of multiple regression analysis andmultivariate analysis are presented by Snyder (1962) for three applications inhydrology. Snyder (1962) and Rice (1967) propose that multivariate analyses, suchas principal component analysis and factor analysis, as well as discriminant andcanonical correlation analyses are applicable to a variety of hydrological studies.Statistical methods, such as principal component and factor analyses, were later usedin hydrological studies upon the general availability of computing facilities(e.g. Wong 1963; Wallis 1965; Dawdy & Feth 1967; Eiselstein 1967; Diaz et al.1968; Egleson & Querio 1969; Knisel 1970). A recent evaluation of graphical andmultivariate statistical methods for the classification of water chemistry data frompart of the arid Basin and Range Province of the south-western U.S.A. is presentedby Güler et al. (2002).

In multiple factor hydrological problems, Wallis (1965) recommends a principalcomponent analysis with varimax rotation of the factor matrix, and where manyobservations are available, followed by an object analysis based on cluster groupings.This approach is essentially an initial principal component factor analysis, followedby cluster analysis of the factor scores. A similar approach has been used in a studyof the hydrochemistry of the Atherton Tablelands groundwaters (PAPER 2).

The application of multivariate statistical methods to hydrology and hydrochemistryis generally undertaken with the aim of inferring processes controlling watercomposition and / or identifying different sources of water. Several examples fromthe literature grouped into these two broad aims are outlined below, and scope forfurther work is discussed.

HYDROCHEMICAL PROCESSES

Multivariate statistical methods, and factor analysis in particular, are useful forinterpreting routinely-collected groundwater chemistry data and relating those data tospecific hydrogeological processes (Lawrence & Upchurch 1982). R-mode factoranalysis, for example, has been used to discriminate chemical variables that reflectrecharge processes from those strictly related to the dissolution of aquifer materialsin the karstic Floridan Aquifer in part of north central Florida (Lawrence &Upchurch 1982). Hitchon et al. (1971) have inferred possible chemical and physicalreactions that affect the geochemistry of brines using factor analysis of compositionaldata in the western Canada sedimentary basin. Several other examples where

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multivariate statistical methods have been used to in infer hydrogeological orhydrochemical processes are given below.

A useful early application of factor analysis to the study of groundwater chemistrydata was undertaken by Dawdy and Feth (1967) who studied the chemical analysesof more than 100 groundwater samples from the Upper and Middle Mojave RiverValley, San Bernardino County, California. They inferred that the variance in thedata was due to sources of sodium chloride, the carbonate-bicarbonate system andother factors. Dawdy and Feth (1967) note that where there is a lack of negativecorrelations in the factor matrix, that is, an absence of mutually exclusivecomponents, this is an indication that there is no reaction path by which one set ofchemical products replaces another set. For example, none of the components orfactors is strictly controlled by equilibrium with minerals in the aquifers. This isrelevant to the study of the Atherton Tablelands groundwaters, where the factoranalysis results for the basaltic groundwaters show few negative correlations(PAPER 2), and therefore indicate that the Atherton basalt groundwaters are not inequilibrium with the dominant mineral phases. The work presented inAPPENDIX IV supports this interpretation, with the calculated saturation indicesindicating that some of the groundwaters are in equilibrium with the clays, but thatnone of the groundwaters have yet reached equilibrium with respect to the primarysilicate minerals. Dawdy and Feth (1967) also caution that the sources of the majorconstituents must be inferred from information other than just the statisticalassociations in the data.

Factor analysis and cluster analysis have been used by Suk and Lee (1999) toidentify the hydrochemical processes controlling groundwater composition in gneiss,granite and alluvium aquifers in a small residential and industrial area of Incheon,Korea. The major controlling factors identified were oceanic rain and wet season,leaked fuel oils and associated degradation products, the partially confiningconditions and anthropogenic sources. Factor analysis has also been used by Jeong(2001a) to distinguish between the influence of natural chemical weathering ofgranitic rocks and anthropogenic inputs in the Taejon area, Korea.

Factor analysis has been used to help infer the main processes influencinggroundwater chemistry in the fractured rocks (Permian sandstones and mudstones,and Jurassic dolerite dykes and sills) around Sutherland in the Western Karoo regionof South Africa (Adams et al. 2001). These processes are salinization, mineralprecipitation and dissolution, cation exchange and human activity.

Processes such as the dissolution of alkali-feldspar minerals, calcite dissolution andinter-aquifer leakage, have been interpreted by Meng and Maynard (2001) ascontrolling groundwater composition in the Botucatu Sandstone aquifer in part of theParaná Basin, Brazil, using cluster analysis and factor analysis.

Factor analysis has also been applied to hydrochemical data by Jeong (2001b) toinfer mineral-water reaction processes controlling the composition of groundwaterstored within Pre-Cambrian granitic gneiss in the abandoned Samkwang mine area inKorea, a research site for radioactive waste disposal. The processes inferred were the

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dissolution of calcite, chlorite, albite and sulfides, and the precipitation of clay andoxide minerals.

Lawrence and Upchurch (1976) also showed that factor analysis is useful ininterpreting water chemistry data and relating those data to hydrogeologicalprocesses in an area around Lake City, Florida. Using R-mode factor analysis,Lawrence and Upchurch (1976) showed that particular variables are related tospecific processes, those being contact with limestone and dolomite of the FloridanAquifer, percolation through clastics overlying the Floridan Aquifer, and directconnection with the surface via sinkhole lakes.

Factor analysis and another type of multivariate analysis, that is, correspondenceanalysis have been used by Usunoff and Guzmán-Guzmán (1989) to definehydrochemical processes controlling groundwater composition in the interbeddedsandstones and shales of the Milk River aquifer, Alberta, Canada. These processesare sulfate reduction, mixing of waters of different ages, ion-filtration and ion-exchange on clays (Usunoff & Guzmán-Guzmán 1989).

Factor analysis has been used to relate trace element data to processes such asenrichment related to groundwater acidity, evaporative concentration, and release ofions from clays, organic solids or Fe- or Mn-oxides, in groundwaters from LakeTyrrell, Victoria (Giblin & Dickson 1992). Principal component analysis has beenused by Kundu et al. (2001) in a geochemical appraisal of fluoride contamination ofgroundwater from high-grade metamorphic rocks in the Nayagarh District of Orissa,India; they showed that the fluorine-rich groundwater was produced due to mixing ofhot spring water with the surrounding groundwater.

R-mode factor analysis and Q-mode cluster analysis have been applied togroundwater analyses from fluvial sands and gravels from the Gooi and Vechtstreekarea in the Netherlands, to determine the factors controlling groundwatercomposition (Schot & van der Wal 1992). The processes identified were dissolutionof carbonates, decomposition of organic matter, pollution, recharge of surface wateraffected by Vecht River water, and mixing of fresh and brackish groundwater (Schot& van der Wal 1992).

Principal component analysis and Q-mode cluster analysis have been carried out ongroundwater data from two rock types, that is, granite and its contact aureole (schist),in the Nisa region of central Portugal, to determine governing hydrogeochemicalprocesses by Dekkers et al. (1989). The processes identified for the granitegroundwaters were evapotranspiration, relation to faults and fracture zones, fertilizerapplication and oxidation – reduction processes; for the schist groundwaters,evapotranspiration, water – rock interaction and a surface versus depth dipole(Dekkers et al. 1986; Dekkers et al. 1989).

Korkka-Niemi (2001) used principal component analysis to assess groundwaterchemistry from igneous and metamorphic rocks (granitoids, gneisses, migmatites anda greenstone belt composed of metavolcanic and metasedimentary rocks) in Finland.Five factors were inferred from the analysis, those being salinity, humus-redox, pH,

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pollution, and contamination factors. Korkka-Niemi (2001) concluded that thedominant salinity factor for the bedrock groundwaters could be used as an indicatorof the residence time of the water.

DIFFERENTIATION BY SOURCE

Examples of the application of multivariate statistical methods to differentiate watersby source are less commonly found in the literature in comparison to ‘process’studies, although some useful examples are provided below.

A study by Riley et al. (1990) is an example of the use of statistical procedures as aquantitative means for differentiating groundwaters according to hydrochemistry.Riley et al. (1990) used multivariate cluster analysis, MANOVA, canonical analysisand discriminant analysis to investigate the directions of groundwater movement inthe Saddle Mountains, Wanapum, and the Grande Ronde basalt formations in thevicinity of the Hanford Reservation. Washington. The statistical analyses indicatethat the hydrochemistry of the groundwaters in those basalt formations is distinctlydifferent on each side of the Columbia River where the river passes through theHanford Reservation, and indicate that the river is a groundwater divide or that theriver is roughly coincident with a hydrogeological barrier boundary (Riley et al.1990). Riley et al. (1990) also found that some of the hydrochemical differencescould be related to stratigraphic positions of the basalt flows.

Seyhan et al. (1985) used multivariate statistical analysis (i.e. R-mode and Q-modefactor analysis as well as cluster analysis) of hydrochemical and environmentalisotope data to differentiate groundwater of different hydrogeological origins withinthe Sasso Lungo dolomitic reef aquifer, northern Italy. The groundwaters wereidentified as sourced from either the Upper Triassic Sciliar dolomite or from theLower Permian volcanic deposits (tuffs and tuffaceous-calcareous shales), or wereidentified as a mixed water from these two sources (Seyhan et al. 1985).

Cluster analysis of groundwater chemistry data, has been used by Hussein and Adam(1995) to separate sandstone and basalt groundwaters from the Gedaref Basin ineastern Sudan. The basalt groundwaters, which have total dissolved solidsconcentrations between 250 and 2730 ppm, could be separated from the sandstonegroundwaters using a cluster analysis of major ion concentrations.

Cluster analysis and canonical analysis have been used by Williams (1982) to test thehypothesis that it is possible to utilize a statistical analysis of water quality data toidentify pathways of preferential hydraulic connection between groundwaterdischarge points on the surface of Mount Emmons, Colorado, and pyrite-rich,mineralised zones in the core of the mountain. Cluster analysis and canonicalanalysis of the water quality data delineated those discharge points that containgroundwater emanating from a mineralised pyrite-rich source; these analyses, alongwith fault-vein maps were used to identify those springs most likely to be affected bymining in the core of Mount Emmons (Williams 1982).

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In a related study, Steinhorst and Williams (1985) also used cluster analysis,MANOVA, canonical analysis and discriminant analysis to identify distinctgroundwater sources using hydrochemical data. Water samples taken from adiversity of sources from a proposed molydbenum mine site in western Coloradowere assessed to determine which sources were affected by the ore body and pyriteassociated with it. Steinhorst and Williams (1985) also used these multivariatestatistical methods to determine whether water taken from different formations, thatis, basalt flows and sedimentary interbeds in south central Washington, arechemically distinguishable.

Q-mode factor analysis has been used to study the groundwaters in the San PedroRiver basin in Arizona, and enabled the hydrochemical segregation of waters fromconfined Miocene – Pliocene sedimentary rocks and unconfined Pleistocenesediments (Usunoff & Guzmán-Guzmán 1989).

Another study, a factor analysis of hydrochemical data from over 2500 analyses ofbrines by Kramer (1969), showed that the factor groupings are very similarregardless of rock type (limestone, sandstone, dolomite, granite wash, evaporite andshale). This was interpreted by Kramer (1969) as indicating that most of the rocksystems studied are open and that a trend towards some equilibrium state occurs.

OTHER STUDIES AND SCOPE FOR FURTHER WORK

Other studies using multivariate statistical methods to assess the chemistry of surfaceand groundwaters include those by Collins (1967), Lee (1969), Miller and Drever(1977), Ashley and Lloyd (1978), Dalton and Upchurch (1978), Symader andThomas (1978), Stallard and Edmond (1983), van Tonder and Hodgson (1986),Zielinski et al. (1987), Nölte (1988), Faillat and Blavoux (1989), Ruiz et al. (1990),Christophersen and Hooper (1992), Melloul and Collin (1992), Laaksoharju et al.(1999), Bedbur et al. (2001), López-Chicano et al. (2001) and Reghunath et al.(2002).

Examples in the literature of the specific application of principal component or factoranalysis to distinguish processes controlling groundwater composition or differinglithological sources of groundwater for data sets in which there are very lowconcentrations of ions, are very limited. Join et al. (1997) used principal componentanalysis to assess the relationship between ionic concentration and geological settingfor fresh spring waters on the tropical island of Réunion in the western Indian Ocean.Join et al. (1997) inferred two main factor from the analysis; the first is associatedwith deep volcanic formations (basal aquifers) and is characterized by the chemicalcomponents K+, pH, Ca2+ and Na+, the second is associated with the superficiallayers of the volcanoes (superficial and perched aquifers) and is characterized by Cl-

and NO3-.

A recent study using multivariate statistical methods (Q- and R-mode factor andcluster analysis) to assess groundwater composition in a tropical climate wasundertaken by Reghunath et al. (2002) in the Nethravathi river basin of southernIndia. The analyses indicate that exchange between river water and groundwater in

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these Precambrian crystalline formations plays a dominant role in the hydrochemicalevolution of the Nethravathi river basin groundwaters (Reghunath et al. 2002).

An example of the use of a multivariate statistical method for data with low ionconcentrations is a principal component and factor analysis by Bridgman (1992), inwhich the sources of contamination were established for a rainwater chemistry dataset containing near-background ion levels. Bridgman (1992) inferred that soil,fertilizer and industrial emission factors influenced rainwater quality in the Hunterregion of New South Wales. Reeder et al. (1972) used Q-mode and R-mode factoranalyses to assess the chemical and physical properties of over 100 surface waters ofthe Mackenzie River drainage basin, Canada, and identified the likely factorsinfluencing the composition of those waters.

There is considerable scope for further application of multivariate statistical methodsto hydrogeochemical studies, particularly for subtropical aquifer systems with freshgroundwaters, which have received less attention than aquifer systems in temperate,semi-arid and arid climates where the groundwaters are more hydrochemically‘evolved’. In addition, examples of the application of multivariate statisticalmethods, particularly principal component factor analysis, to the assessment ofbasalt aquifer systems are very limited. The study by Join et al. (1997) in a tropicalbasalt island setting, discussed above, is the only known example in the publishedliterature of the application of a principal component analysis method to assesshydrochemical processes in a basalt aquifer in a tropical climate. The aquifers of theAtherton Tablelands region are, therefore, a useful system for the investigation ofhydrogeochemical processes and groundwater sources using statistical methods ofdata analysis.

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Conclusions

A primary aim of this study is to demonstrate that hydrogeochemical processes, andsilicate mineral weathering processes in particular, are a significant influence on thecomposition of basaltic groundwaters.

It is evident from this literature review, that there are a wide variety ofhydrogeochemical and statistical methods that may be applied to the study of abasaltic aquifer system. They include the assessment of mineral dissolution andweathering processes through the use of aqueous elemental ratios in relation to thestoichiometry of possible reactions, investigation of whole rock geochemistry andmineralogy, including changes in these as a result of weathering, quantification ofrelations between minerals and dissolved species through the calculation of aqueousion activities and mineral saturation states, and the use of mineral stability diagrams,as well as hydrogeochemical modelling approaches. Assessment of other naturalprocesses that may influence the composition of basaltic groundwaters, such as theacquisition of carbon dioxide, ion-exchange and sorption mechanisms, oxidation –reduction reactions, evaporation and the effects of organic matter should also beconsidered.

The review of the literature clearly demonstrates that it is essential to validate,normalise and standardize hydrochemical data sets before they can be subjected tomultivariate analytical techniques. Multivariate statistical analyses provide a rangeof techniques that may be used in hydrogeochemical studies, with the choice ofmethod dependent on the aims of the investigation. Multivariate statistical analysesinclude, for example, graphical methods, principal component analysis, factoranalysis (and variants of these) and cluster analysis.

Few investigations of low-temperature meteoric water – rock interactions in basalticterrain have been reported, and this is particularly so in tropical and subtropicalenvironments. In addition, the application of principal component or factor analysismethods to distinguish hydrogeochemical processes controlling groundwatercomposition or differing lithological sources of fresh groundwaters, are very limited.There is considerable scope for further research into the hydrogeochemical processescontrolling the composition of fresh basaltic groundwaters in tropical and subtropicalenvironments, and the use of multivariate statistical methods in such an investigation.

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References

ABDULAZIZ A-B.M., HUSSEIN A.S. & JOMAAH A-A. A. 1997. DurovPlot: a computerprogram for processing and plotting hydrochemical data. Ground Water 35

(2), 362-367.ABU-JABER N. 2001. Geochemical evolution and recharge of the shallow aquifers at

Tulul al Ashaqif, NE Jordan. Environmental Geology 41, 372-383.ADAMS B. & FOSTER S.S.D. 1992. Land-surface zoning for groundwater protection.

Journal of the Institution of Water and Environmental Management 6, 312-320.

ADAMS S., TITUS R., PIETERSEN K., TREDOUX G. & HARRIS C. 2001. Hydrochemicalcharacteristics of aquifers near Sutherland in the Western Karoo, South Africa.Journal of Hydrology 241, 91-103.

AHRENS L.H. 1953. A fundamental law of geochemistry. Nature 172, 1148.AHRENS L.H. 1954a. The lognormal distribution of the elements (a fundamental law

of geochemistry and its subsidiary). Geochimica et Cosmochimica Acta 5, 49-73.

AHRENS L.H. 1954b. The lognormal distribution of the elements II. Geochimica etCosmochimica Acta 6, 121-131.

AHRENS L.H. 1957. Lognormal-type distributions III. Geochimica et CosmochimicaActa 11, 205-212.

AITCHISON J. 1982. The statistical analysis of compositional data (with discussion).Journal of the Royal Statistical Society B 44, 139-177.

AITCHISON J. 1983. Principal component analysis of compositional data. Biometrika70, 57-65.

AITCHISON J. 1984. Reducing the dimensionality of compositional data sets.Mathematical Geology 16, 617-635.

AITCHISON J. 1986. The Statistical Analysis of Compositional Data. Monographs ofStatistics and Applied Probability. Chapman and Hall, London, pp. 416.

AIUPPA A., ALLARD P., D’ALESSANDRO W., MICHEL A., PARELLO F., TREUIL M. &VALENZA M. 2000. Mobility and fluxes of major, minor and trace metalsduring basalt weathering and groundwater transport at Mt. Etna volcano(Sicily). Geochimica et Cosmochimica Acta 64, 1827-1841.

AL-DROUBI A., FRITZ B., GAC J.-Y. & TARDY Y. 1980. Generalized residualalkalinity concept; application to prediction of the chemical evolution ofnatural waters by evaporation. American Journal of Science 280, 560-572.

ALEKIN O.A. 1970. Osnovy Hydrokhimii (Principles of Hydrochemistry).Hydrometeorologicheskoe Isdat., Leningrad, pp. 443.

ALTHER G.A. 1979. A simplified statistical sequence applied to routine water qualityanalysis: a case history. Ground Water 17 (6), 556-561.

AMADI P.A., OFOEGBU C.O. & MORRISON T. 1989. Hydrogeochemical assessmentof groundwater quality in parts of the Niger Delta, Nigeria. EnvironmentalGeology and Water Science 14 (3), 195-202.

ANBEEK C. 1993. The effect of natural weathering on dissolution rates. Geochimicaet Cosmochimica Acta 57, 4963-4975.

ANDERBERG M.R. 1973. Cluster Analysis for Applications. Academic Press, NewYork, pp. 359.

ANDERSON T.W. 1957. Relating sediment yield to watershed variables.Transactions of the American Geophysical Union 38, 921-924.

66

ANDERSON T.W. & RUBIN H. 1956. Statistical inference in factor analysis.Proceedings of the Third Berkeley Symposium on Mathematical Statistics andProbability, Vol. 5, pp.111-150. University of California Press, Berkeley.

ANDRÉSDÓTTIR A. & ARNÓRSSON S. 1999. Processes controlling Ca and Mgmobility in natural waters in Skagafjördur, N-Iceland. In Ármannsson H. ed.Geochemistry of the Earth’s Surface, pp. 361-364. A.A.Balkema, Rotterdam.

APPELO C.A.J. & POSTMA D. 1996. Geochemistry, Groundwater and Pollution.A.A.Balkema, Rotterdam, pp. 536.

ARMANDS G. 1972. Geochemical studies of uranium, molybdnnum and vanadium ina Swedish alum shale. Stockholm Contributions in Geology 27, 1-148.

ÁRMANNSSON H., GÍSLASON G. & HAUKSSON T. 1982. Magmatic gases in wellfluids aid the mapping of the flow pattern in a geothermal system. Geochimicaet Cosmochimica Acta 46, 167-177.

ARNASON B. 1977. Hydrothermal systems in Iceland traced by deuterium.Geothermics 5, 125-151.

ARNÓRSSON S. 1999. Invited lecture: Progressive water-rock interaction andmineral-solution equilibria in groundwater systems. In Ármannsson H. ed.Geochemistry of the Earth’s Surface, pp. 471-474. A.A.Balkema, Rotterdam.

ARNÓRSSON S., GUNNLAUGSSON E. & SVAVARSSON H. 1983a. The chemistry ofgeothermal waters in Iceland: II. Mineral equilibria and independent variablescontrolling water compositions. Geochimica et Cosmochimica Acta 47, 547-566.

ARNÓRSSON S., GUNNLAUGSSON E. & SVAVARSSON H. 1983b. The chemistry ofgeothermal waters in Iceland: III. Chemical geothermometry in geothermalinvestigations. Geochimica et Cosmochimica Acta 47, 567-577.

ASHLEY P.M., DUNCAN R.A. & FEEBREY C.A. 1995. Ebor Volcano and CrescentComplex, northeastern New South Wales: age and geological development.Australian Journal of Earth Sciences 42, 471-480.

ASHLEY R.P. & LLOYD J.W. 1978. An example of the use of factor analysis andcluster analysis in groundwater chemistry interpretation. Journal of Hydrology39, 355-364.

ATHAVALE R.N., CHAND R. & RANGARAJAN R. 1983. Groundwater rechargeestimates for two basins in the Deccan Trap basalt formation. HydrologicalSciences Journal 28 (4), 525-538.

AUBREY K.V. 1954. Frequency distribution of the concentrations of elements inrocks. Nature 174, 141-142.

AUBREY K.V. 1956. Frequency distribution of elements in igneous rocks.Geochimica et Cosmochimica Acta 9, 83-89.

AUF DER HEYDE T.P.E. 1990. Analyzing chemical data in more than twodimensions. Journal of Chemical Education 67 (6), 461-469.

BACK W. 1960. Origin of hydrochemical facies of ground water in the AtlanticCoastal Plain. In Back W. and Freeze R.A. eds., 1983. Benchmark Papers inGeology, Vol. 73: Chemical Hydrogeology, 79-87. Hutchinson RossPublishing Company, Stroudsburg, Pennsylvania.

BACK W. 1961. Techniques for mapping of hydrochemical facies. In Short Papersin the Geologic and Hydrologic Sciences, United States Geological SurveyProfessional Paper 424-D, 380-382.

BACK W. 1966. Hydrochemical facies and ground-water flow patterns in thenorthern part of the Atlantic Coastal Plain. United States Geological SurveyProfessional Paper 498-A, 1-2.

67

BACK W. & HANSHAW, B.B. 1965. Chemical geohydrology. In Chow .V.T. ed.Advances in Hydroscience 2, 49-109. Academic Press, New York.

BACK W. & HANSHAW, B.B. 1970. Comparison of chemical hydrology of thecarbonate peninsula of Florida and Yucatan. Journal of Hydrology 10, 330-368.

BALL J.W. & NORDSTROM D.K. 1991. WATEQ4F User’s manual with revisedthermodynamic data base and test cases for calculating speciation of major,trace and redox elements in natural waters. United States Geological SurveyOpen-File Report 91-183, pp. 189.

BARCLAY D. 1997. Groundwater occurrence and geochemistry within a basalticaquifer, Ormiston, S.E. Queensland. BAppSc(Hons) thesis, QueenslandUniversity of Technology, Brisbane (unpubl.), pp. 57.

BARNES S. & WORDEN R.H. 1998. Understanding groundwater sources andmovement using water chemistry and tracers in a low matrix permeabilityterrain: the Cretaceous (Chalk) Ulster White Limestone Formation, NorthernIreland. Applied Geochemistry 13, 143-153.

BARROW N.J. & SHAW T.C. 1975. The slow reactions between soil and anions: 3.The effects of time and temperature on the decrease in isotopicallyexchangeable phosphate. Soil Science 119, 190-197.

BARSHAD I. 1966. The effect of a variation in precipitation on the nature of claymineral formation in soils from acid and basic igneous rocks. In Heller L. andWeiss A. eds. Proceedings of the International Clay Conference, 1, pp. 167-173. Israel Program for Scientific Translations, Jerusalem.

BARTLETT M.S. 1937. The statistical conception of mental factors. British Journalof Psychology 28, 97-104.

BARTLETT M.S. 1947. The use of transformations. Biometrics 3, 39-52.BEAN J.A. 1999. A conceptual model of groundwater behaviour in the Atherton

Basalt Province, Atherton Tablelands, Far North Queensland. MAppSc thesis,Queensland University of Technology, Brisbane (unpubl.), pp. 159.

BEAUCAIRE C., GASSAMA N., TRESONNE N. & LOUVAT D. 1995. Geochemicalevolution of saline waters in crystalline rocks: Chardon mine (France) - Part I:Behaviour of main ions. In Kharaka Y.K. and Chudaev O.V. eds. Water –Rock Interaction WRI-8, pp. 433-436. A.A.Balkema, Rotterdam.

BEDBUR E., PETERSEN M., BIALLAS H., WOLLSCHLÄGER U. & SCHMIDT S. 2001.Chemical evolution of ground waters in W-Iceland (Snæfellsnes). In Cidu R.ed. Water – Rock Interaction WRI-10, pp. 461-464. A.A.Balkema, Lisse.

BEDFORD K. 1983. The Atherton Basalts. Queensland Water ResourcesCommission. Internal report (unpubl.).

BEEKMAN H.E. & SALAOLO E.T. 1994. Long term average recharge of a shallowgroundwater system in Botswana – a hydrochemical and isotope approach.Proceedings of the 25th Congress of The International Association ofHydrogeologists / International Hydrology and Water Resources Symposium ofThe Institution of Engineers, Australia (National Conference Publication No.94/14), pp. 157-162. The Institution of Engineers, Australia.

BENEDETTI M., MENARD O. & NOACK Y. 1992. Geochemistry of water and chemicalweathering rates under a humid tropical climate. In Kharaka Y.K. and MaestA.S. eds. Water – Rock Interaction WRI-7, pp. 545-548. A.A.Balkema,Rotterdam.

68

BENEDETTI M.F., MENARD O., NOACK Y., CARVALHO A. & NAHON D. 1994. Water-rock interactions in tropical catchments: field rates of weathering and biomassimpact. Chemical Geology 118, 203-220.

BENEDETTI M.F., BOULEGUE J., DIA A., BULOURDE M., CHAUVEL C., CHABAUX F.,RIOTTE J., FRITZ B., GÉRARD M., BERTAUX J., ETAME J., DERUELLE B. &ILDEFONSE PH. 1999. The weathering of Mount Cameroon: 2. Watergeochemistry. In Ármannsson H. ed. Geochemistry of the Earth’s Surface, pp.365-367. A.A.Balkema, Rotterdam.

BENNETT P.C. & ROGERS J.R. 2000. The mineralogy of microbial ecology. In SililoO. et al. eds. Groundwater: Past achievements and future challenges.Proceedings of the XXXth International Congress of the InternationalAssociation of Hydrogeologists, Cape Town, pp. 3-6. A.A.Balkema,Rotterdam.

BERNER E.K. & BERNER R.A. 1996. Global Environment: Water, Air andGeochemical Cycles. Prentice Hall, Englewood Cliffs, New Jersey, pp. 376.

BERNER R.A. 1971. Principles of Chemical Sedimentology. McGraw-Hill, NewYork, pp. 240.

BERNER R.A. 1999. Invited lecture: Plants, weathering and the evolution ofatmospheric CO2. In Ármannsson H. ed. Geochemistry of the Earth’s Surface,pp. 3-5. A.A.Balkema, Rotterdam.

BERNER R.A. & HOLDREN G.R. 1979. Mechanism of feldspar weathering–II.Observations of feldspars from soils. Geochimica et Cosmochimica Acta 43,1173-1186.

BERNER R.A., LASAGA A.C. & GARRELS R.M. 1983. The carbonate – silicategeochemical cycle and its effects on atmospheric carbon dioxide over the past100 million years. American Journal of Science 283, 641-683.

BERNER R.A. & RAO J-L. 1997. Alkalinity buildup during silicate weathering undera snow cover. Aquatic Geochemistry 2, 301-312.

BEST J.G. 1960. Some Cainozoic basaltic volcanoes in North Queensland. Bureauof Mineral Resources Australia Record 1960/78. In De Keyser F. 1964.1:250000 Innisfail Sheet (SE/55-6) – Explanatory notes. Bureau of MineralResources Geology and Geophysics, Canberra, pp. 30.

BEST J.G. 1962. Atherton, Queensland – 1:250 000 Geological Series Sheet SE/55-5. Explanatory Notes Bureau Mineral Resources Geology and Geophysics,Australia.

BIRKLE P., TORRÉS ROGRÍGUEZ V. & GONZÁLEZ PERTIDA E. 1998. The waterbalance for the Basin of the Valley of Mexico and implications for future waterconsumption. Hydrogeology Journal 6 (4), 500-517.

BISCHOFF J.L. & DICKSON F.W. 1975. Seawater – basalt interaction at 200 °C and500 bars: implications for origin of sea-floor heavy-metal deposits andregulation of seawater chemistry. Earth Planetary Science Letters 25, 285-297.

BLACKITH R.E. & REYMENT R.A. 1971. Multivariate Morphometrics. AcademicPress, London, pp. 412.

BLAKE D. 1972. Regional and economic geology of the Herberton / Mount Garnetarea – Herberton tinfield, North Queensland. Bulletin of the Bureau of MineralResources Geology and Geophysics Australia, 124.

BLUM A.E. & STILLINGS L.L. 1995. Feldspar dissolution kinetics. In White A.F. andBrantley S.L. eds. Chemical Weathering Rates of Silicate Minerals 31, pp.291-351. Mineralogical Society of America, Washington, D.C.

69

BLUTH G.J.S. & KUMP L.R. 1994. Lithologic and climatologic controls of riverchemistry. Geochimica et Cosmochimica Acta 58, 2341-2359.

BOOKSTEIN F.L. 1991. Morphometric Tools for Landmark Data: Geometry andBiology. Cambridge University Press, New York, pp. 435.

BORMANN B.T., WANG D., BORMANN F.H., BENOIT G., APRIL R. & SNYDER M.C.1998. Rapid plant induced weathering in an aggrading experimentalecosystem. Biogeochemistry 43, 129-155.

BOWEN N.L. 1928. The Evolution of the Igneous Rocks. Princeton University Press,Princeton, New Jersey, pp. 334.

BRANTLEY S.L. 1992. Kinetics of dissolution and precipitation – Experimental andfield results. In Kharaka Y.K. and Maest A.S. eds. Water – Rock InteractionWRI-7, pp. 3-6. A.A.Balkema, Rotterdam.

BREEUWSMA A., WÖSTEN J.H.M., VLEESHOUWER J.J., VAN SLOBBE A.M. & BOUMA

J. 1986. Derivation of land qualities to assess environmental problems fromsoil surveys. Journal of the Soil Science Society of America 50, 186-190.

BRICKER O.P., GODFREY A.E. & CLEAVES E.T. 1968. Mineral-water interactionduring the chemical weathering of silicates. In Gould R.F. ed. TraceInorganics in Water, Advances in Chemistry Series, pp. 128-142. AmericanChemical Society, Washington, D.C.

BRIDGMAN H.A. 1992. Evaluating rainwater contamination and sources in south-eastAustralia using factor analysis. Atmospheric Environment 26A (13), 2401-2412.

BRIGGS R., ODADA T., ITAYA T., SHIBUYA H. & SMITH I. 1994. K-Ar ages,palaeomagnetism, and geochemistry of the South Auckland volcanic field,North Island, New Zealand. New Zealand Journal of Geology and Geophysics37, 143-153.

BRIZ-KISHORE B.H. & MURALI G. 1992. Factor analysis for revealinghydrochemical characteristics of a watershed. Environmental Geology andWater Science 19 (1), 3-9.

BROADBENT F. & LEWIS T. 1961. Soil organic matter – metal complexes; 4. Natureand properties of exchange sites. Soil Science 91, 393-399.

BROMLEY J., MANNSTROM B., NISCA D. & JAMTLID A. 1994. Airborne geophysics:application to a groundwater study in Botswana. Ground Water 32 (1), 79-90.

BROOK G.A., COWELL D.W. & FORD D.C. 1977. Comment on ‘RegionalHydrochemistry of North American Carbonate Terrains’ by Russell S.Harmon, William B. White, John J. Drake, and John W. Hess and ‘The Effectof Climate on the Chemistry of Carbonate Groundwater’ by John J. Drake andT.M.L. Wigley. Water Resources Research 13 (5), 856-858.

BROOK G.A., FOLKOFF M.E. & BOX E.O. 1983. A world model of soil carbondioxide. Earth Surface Processes and Landforms 8, 79-88

BROWNE M.W. 1968. A comparison of factor analytic techniques. Psychometrika33, 267-334.

BRYANT E.H & ATCHLEY W.R. 1975. Multivariate Statistical Methods: Within-group Covariation. Halsted Press, Stroudsberg, pp. 436.

BUCCIANTI A. 1997. Multivariate analysis to investigate Cl distribution in rocksfrom different settings. Mathematical Geology 29 (3), 349-359.


70

BUSENBERG E. & CLEMENCY C.V. 1976. The dissolution kinetics of feldspars at25 °C and 1 atm CO2 partial pressure. Geochimica et Cosmochimica Acta 40,41-49.

BUYANOVSKY G.A. & WAGNER G.H. 1983. Annual cycles of carbon dioxide level insoil air. Journal of the Soil Science Society of America 47, 1139-1145.

CAMPBELL N.A., MULCAHY M.J & MCARTHUR W.M. 1970. Numericalclassification of soil profiles on the basis of field morphological properties.Australian Journal of Soil Research 8, 43-58.

CARR R.G., RODGERS K.A. & BLACK P.M. 1980. The chemical and mineralogicalchanges accompanying the laterization of basalt at Kerikeri, North Auckland.Journal of the Royal Society of New Zealand 10 (3), 247-258.

CARROLL J.B. 1953. An analytic solution for approximating simple structure infactor analysis. Psychometrika 18, 23-38.

CASEY W.H., WESTRICH H.R., ARNOLD G.W. & BANFIELD J.F. 1989a. The surfacechemistry of dissolving labradorite feldspar. Geochimica et CosmochimicaActa 53, 821-832.

CASEY W.H., WESTRICH H.R., MASSIS T., BANFIELD J.F. & ARNOLD G.W. 1989b.The surface of labradorite feldspar after acid hydrolysis. Chemical Geology78, 205-218.

CASEY W.H. & BUNKER B. 1990. Leaching of mineral and glass surfaces duringdissolution. In Hochella M.F. and White A.F. eds. Mineral-Water InterfaceGeochemistry, Reviews in Mineralogy 23, 397-426.

CATTELL R.B. 1952. Factor Analysis: An Introduction and Manual for thePsychologist and Social Scientist. Harper and Row, New York, pp. 462.

CATTELL R.B. 1966. The scree test for the number of factors. MultivariateBehavioral Research 1, 245-276.

CATTELL R.B. & JASPERS J. 1967. A general plasmode (No. 30-10-5-2) for factoranalytic exercises and research. Multivariate Behavioral ResearchMonographs 67-3. Society of Multivariate Experimental Psychology, FortWorth, Texas, pp. 211.

CERÓN J.C., JIMÉNEZ-ESPINOSA R. & PULIDO-BOSCH A. 2000. Numerical analysis ofhydrogeochemical data: a case study (Alto Guadalentín, south-east Spain).Applied Geochemistry 15, 1053-1067.

CHALMERS R.O. 1967. Australian Rocks, Minerals and Gemstones. Angus &Robertson, Sydney, pp. 398.

CHANDRASEKHARAM D., RAMESH R. & BALASUBRAMANIAN J. 1989. Geochemistry,oxygen and hydrogen isotope ratios of thermal springs, western continentalmargin of India – field and experimental results. In Miles D.L. ed. Water –Rock Interaction WRI-6, pp. 149-154. A.A.Balkema, Rotterdam.

CHAMP D.R., GULENS J. & JACKSON R.E. 1979. Oxidation – reduction sequences inground water flow systems. Canadian Journal of Earth Science 16, 12-23.

CHAPELLE F.H. 1983. Groundwater geochemistry and calcite cementation of theAquia aquifer in Southern Maryland. Water Resources Research 19 (2), 545-558.

CHAPELLE F.H. & KNOBEL L.L. 1985. Stable carbon isotopes of HCO3 in the Aquiaaquifer, Maryland: evidence for an isotopically heavy source of CO2. GroundWater 23 (5), 592-599.

CHAPELLE F.H., ZELIBOR J.L., GRIMES D.J. & KNOBEL L.L. 1987. Bacteria in deepcoastal plain sediments of Maryland: a possible source of CO2 to groundwater.Water Resources Research 23 (8), 1625-1632.

71

CHATFIELD C. & COLLINS A.J. 1980. Introduction to Multivariate Analysis.Chapman and Hall, London, pp. 246.

CHAYES F. 1954. The lognormal distribution of the elements: a discussion.Geochimica et Cosmochimica Acta 6, 119-120.

CHEBOTAREV I.I. 1955. Metamorphism of natural waters in the crust of weathering –1. Geochimica et Cosmochimica Acta 8, 22-48.

CHESWORTH W., DEJOU J. & LARROQUE P. 1981. The weathering of basalt andrelative mobilities of the major elements at Belbex, France. Geochimica etCosmochimica Acta 45, 1235-1243.

CHOU L. & WOLLAST R. 1985. Steady – state kinetics and dissolution mechanismsof albite. American Journal of Science 285, 963-993.

CHRISTOPHERSEN N. & HOOPER R.P. 1992. Multivariate analysis of stream waterchemical data: the use of principal components analysis for the end-membermixing problem. Water Resources Research 28 (1), 99-107.

CLAASSEN H.C. & WHITE A.F. 1979. Application of geochemical kinetic data togroundwater systems – A tuffaceous-rock system in Southern Nevada. InJenne E.A. ed. Chemical Modeling in Aqueous Systems: Speciation, Sorption,Solubility and Kinetics, pp. 771-793. American Chemical Society SymposiumSeries 93. American Chemical Society, Washington, D.C.

COLLINS A.G. 1967. Geochemistry of some Tertiary and Cretaceous age oil-bearingformation waters. Environmental Science and Technology 1 (9), 725-730.

COLLINS W.D. 1923. Graphical representation of water analyses. Industrial andEngineering Chemistry 15, 394.

COLMAN S.M. 1982. Chemical weathering of basalts and andesites: evidence fromweathering rinds. United States Geological Survey Professional Paper 1246,pp. 51.

COOK P.G., HERCZEG A.L. & MCEWAN K.L. 2001. Groundwater recharge andstream baseflow, Atherton Tablelands, Queensland. CSIRO Land and WaterTechnical Report 08/01, pp. 84.

COOLEY W.W. & LOHNES P.R. 1971. Multivariate Data Analysis. John Wiley andSons, New York, pp. 364.

COOMBS D.S., ELLIS A.J., FYFE W.S. & TAYLOR A.M. 1959. The zeolite facies, withcomments on the interpretation of hydrothermal syntheses. Geochimica etCosmochimica Acta 17, 53-107.

COX M.E. & BROWNE P. 1998. Hydrothermal alteration mineralogy as an indicatorof hydrology at the Ngawha geothermal field, New Zealand. Geothermics 27

(3), 259-270.CRADDOCK J.M. & FLOOD C.R. 1969. Eigenvectors for representing the 500 mb

geopotenial surface over the Northern Hemisphere. Quarterly Journal of theRoyal Meteorological Society 95, 576-593.

CRAIG D.C. & LOUGHNAN F.C. 1964. Chemical and mineralogical transformationaccompanying the weathering of basic volcanic rocks from New South Wales:Australia. Australian Journal of Soil Research 2, 218-234.

DALTON M.G. & UPCHURCH S.B. 1978. Interpretation of hydrochemical facies byfactor analysis. Ground Water 16 (4), 228-233.

DAS B.K. & KAUR P. 2001. Major ion chemistry of Renuka Lake and weatheringprocesses, Sirmaur District, Himachal Pradesh, India. Environmental Geology40, 908-917.

DAVIS J.C. 1986. Statistics and Data Analysis in Geology. John Wiley and Sons,Toronto, pp. 646.

72

DAVIS S.N. 1969. Porosity and permeability of natural materials. In DeWiest R.J.M.ed. Flow Through Porous Media, pp. 53-89. Academic Press, New York.

DAVIS S.N. 1974. Changes of porosity and permeability with geological time. InProceedings of an International Symposium on the Hydrology of VolcanicRocks, pp. 32. Unesco.

DAVIS S.N., CUSTODIO E., VEEGER A. & JIMÉNEZ J. 1989. A comparison of thechemistry of water from La Palma, Canary Islands, with water from otherbasaltic aquifers. The 28th International Geological Congress, Washington,D.C., Abstracts 1, 372-373.

DAVIS S.N. & DEWIEST R.J.M. 1991. Hydrogeology. Krieger Publishing Company,Malaber, Florida, pp. 463.

DAWDY D.R. & FETH J.H. 1967. Applications of factor analysis in study ofchemistry of groundwater quality, Mojave River Valley, California. WaterResources Research 3 (2), 505-510.

DEER W.A., HOWIE R.A. & ZUSSMAN J. 1966. An Introduction to the Rock FormingMinerals. Longman Group, London, pp. 528.

DEGAETANO A.T. 1996. Delineation of mesoscale climate zones in the north-easternUnites States using a novel approach to cluster analysis. Journal of Climate 9

(8), 1765-1982.DE KEYSER F. & LUCAS K.G. 1968. Geology of the Hodgkinson and Laura Basins,

North Queensland. Bureau Mineral Resources Geology and Geophysics,Australia 84.

DEKKERS M.J., VRIEND S.P., VAN DER WEIJDEN C.H. & VAN DIEST PH. 1986. TheSão Pedro do Sul granite, Portugal: hydrogeochemistry related to theexploration of uranium. Uranium 2, 261-277.

DEKKERS M.J., VRIEND S.P., VAN DER WEIJDEN C.H. & VAN GAANS P.F.M. 1989.Uranium anomaly evaluation in groundwaters: a hydrogeochemical study inthe Nisa region, Portugal. Applied Geochemistry 4, 375-394.

DEOLANKAR S.B. 1980. The Deccan Basalts of Maharashtra, India – their potentialas aquifers. Ground Water 18 (5), 434-437.

DEUTSCH W.J. 1997. Groundwater Geochemistry – Fundamentals and Applicationsto Contamination. Lewis Publishers, Boca Raton, pp. 221.

DEUTSCH W.A., JENNE E.A. & KRUPKA K.M. 1982. Solubility equilibria in basaltaquifers: The Columbia Plateau, eastern Washington, U.S.A. ChemicalGeology 36, 15-34.

DIAZ G., SEWELL J.I. & SHELTON C.H. 1968. An application of principal componentanalysis and factor analysis in the study of water yield. Water ResourcesResearch 4 (2), 299-306.

DILLON W.R. & GOLDSTEIN M. 1984. Multvariate Analysis: Methods andApplications. John Wiley and Sons, New York, pp. 587.

DOMENICO P.A. & SCHWARTZ F.W. 1998. Physical and Chemical Hydrogeology.John Wiley and Sons, New York, pp. 506.

DONCHAK P. & BULTITUDE R. 1994. Geology of the Atherton 1:250 000 Sheet Area.Queensland Geological Record 1994/5.

DRAKE J.J. 1983. The effects of geomorphology and seasonality on the chemistry ofcarbonate groundwater. Journal of Hydrology 61, 223-236.

DRAKE J.J. & WIGLEY T.M.L. 1975. The effect of climate on the chemistry ofcarbonate groundwater. Water Resources Research 11 (6), 958-962.

DREVER J.I. 1994. The effect of land plants on weathering rates of silicate minerals.Geochimica et Cosmochimica Acta 58, 2325-2332.

73

DREVER J.I. 1997. The Geochemistry of Natural Waters. Surface and GroundwaterEnvironments. Prentice Hall, Upper Saddle River, New Jersey, pp. 436.

DREVER J.I. & ZOBRIST J. 1992. Chemical weathering of silicate rocks as a functionof elevation in the southern Swiss Alps. Geochimica et Cosmochimica Acta56, 3209-3216.

DREVER J.I. & CLOW D.W. 1995. Weathering rates in catchments. In White A.F.and Brantley S.L. eds. Chemical Weathering Rates of Silicate Minerals, pp.463-483. Mineralogical Society of America, Washington, D.C.

DRUECKER M. & FAN P. 1976. Hydrology and chemistry of ground water in Puna,Hawaii. Ground Water 14 (5), 328-338.

DUNTEMAN G.H. 1989. Principal Components Analysis. Sage Publications,Newbury Park, California, pp. 96.

DUROV S.A. 1948. Natural waters and graphic representation of their composition.Doklady Akademii Nauk SSSR 59, 87-90.

ECKER A. 1976. Groundwater behaviour in Tenerife, volcanic island (CanaryIslands, Spain). Journal of Hydrology 28, 73-86.

EDMUNDS W.M., ANDREWS J.N., BURGESS W.G., KAY R.L.F. & LEE D.J. 1984. Theevolution of saline and thermal groundwaters in the Carnmenellis granite.Mineralogical Magazine 48, 407-424.

EDMUNDS W.M., CARRILLO-RIVERA J.J. & CARDONA A. 2002. Geochemicalevolution of groundwater beneath Mexico City. Journal of Hydrology 258, 1-24.

EGGLETON R.A., FOUDOULIS C. & VARKEVISSER D. 1987. Weathering of basalt:changes in rock chemistry and mineralogy. Clays and Clay Minerals 35 (3),161-169.

EGLESON G.C. & QUERIO C.W. 1969. Variation in the composition of brine from theSylvania Formation near Midland, Michigan. Environmental Science andTechnology 3 (4), 367-371.

EHRENBERG A.S.C. 1962. Some questions about factor analysis. The Statistician 12

(3), 191-208.EISELSTEIN L.M. 1967. A principal component analysis of surface runoff data from a

New Zealand alpine watershed. In Proceedings of the International HydrologySymposium, pp. 479-489. International Association of Scientific Hydrology,Fort Collins.

ELLIS A.J. & MAHON W.A.J. 1964. Natural hydrothermal systems and experimentalhot water – rock interactions: I. Geochimica et Cosmochimica Acta 28, 1323-1357.

ELLIS A.J. & MAHON W.A.J. 1977. Geochemistry and Geothermal Systems.Academic Press, New York, pp. 392.

ENGESGAARD P. & CHRISTENSEN T. 1988. A review of chemical solute transportmodels. Nordic Hydrology 19, 183-216.

EUGSTER H.P. & JONES B.F. 1979. Behavior of major solutes during closed-basinbrine evolution. American Journal of Science 279, 609-631.

EUGSTER H.P. & MAGLIONE G. 1979. Brines and evaporates of the Lake Chad basin,Africa. Geochimica et Cosmochimica Acta 43, 973-982.

EVERITT B.S. 1980. Cluster Analysis. Heinemann Educational Books, London, pp.136.

FAILLAT J.P. & BLAVOUX B. 1989. Caractères hydrochimiques des nappes desroches endogènes fissures en zone tropicale humid: l’example de la Côted’Ivoire. Journal of African Earth Sciences 9 (1), 31-40.

74

FARMER S.A. 1971. An investigation into the results of a principal componentanalysis of data derived from random errors. The Statistician 20, 63-72.

FAURE G. 1998. Principles and Applications of Geochemistry. Prentice Hall, UpperSaddle River, New Jersey, pp. 600.

FELMY A.R., GIRVIN, D.C. & JENNE E.A. 1984. MINTEQ – a computer program forcalculating aqueous geochemical equilibria. United States EnvironmentalProtection Agency, Environmental Research Laboratory, Athens, GA, EPA-

600/3-84-032.FERGUSON J.A. 1954a. Transformations of clay minerals in black earths and red

loams of basaltic origin. Australian Journal of Agricultural Research 5, 98-108.

FERGUSON G.A. 1954b. The concept of parsimony in factor analysis. Psychometrika19, 281-290.

FETH J.H., ROBERSON C.E. & POLZER W.L. 1964. Sources of mineral constituents inwater from granitic rocks, Sierra Nevada, California and Nevada. UnitedStates Geological Survey Water-Supply Paper 1535-I, 1-170.

FETTER C.W. 1994. Applied Hydrogeology. Macmillan Publishing Company, NewYork, pp. 691.

FINEGAN J.M. 1994. Groundwater contamination in a basalt aquifer – transport andattenuation of pollutants. In Water Down-Under, Proceedings of the 25th

Congress of the International Association of Hydrogeologists / InternationalHydrology and Water Resources Symposium of the Institution of Engineers,Australia, 661-667. The Institution of Engineers, Australia (NationalConference Publication No. 94/14).

FINGER W., POST B. & KLAMBERG H. 1992. Isolation and characterization of soilhumic matter. In Matthess G., Frimmel F., Hirsch P., Schulz H.D. andUsdowski H.-E. eds. Progress in Hydrogeochemistry, pp. 13-19. Springer-Verlag, Berlin.

FLURY B. 1984. Common principal components in k groups. Journal of theAmerican Statistical Association 79, 892-898.

FLURY B. 1988. Common Principal Components and Related Multivariate Models.John Wiley and Sons, New York, pp. 258.

FOLK R.L. & LAND L.S. 1975. Mg/Ca ratio and salinity: two controls overcrystallization of dolomite. The American Association of Petroleum GeologistsBulletin 59 (1), 60-68.

FOSTER J.J. 1998. Data Analysis Using SPSS for Windows: A Beginner’s Guide.Sage Publications, London, pp. 224.

FOSTER S.S.D. 1987. Fundamental concepts in aquifer vulnerability, pollution riskand protection strategy. In van Duijvenbooden W. and van Waegeningh H.G.eds. Vulnerability of Soil and Groundwater to Pollutants, Proceedings andInformation 38, 69-86. TNO Committee on Hydrological Research, TheHague.

FREEZE R.A. & CHERRY J.A. 1979. Groundwater. Prentice Hall, Englewood Cliffs,New Jersey, pp. 604.

FRENGSTAD B. & BANKS D. 2000. Evolution of high-pH Na-HCO3 groundwaters inanorthosites: silicate weathering or cation exchange? In Sililo O. et al. eds.Groundwater: Past achievements and future challenges. Proceedings of theXXXth International Congress of the International Association ofHydrogeologists, Cape Town, pp. 493-498. A.A.Balkema, Rotterdam.

75

FRIDRIKSSON TH., NEUHOFF P.S., BIRD D.K. & ARNÓRSSON S. 1999. Clays andzeolites record alteration history at Teigarhorn, eastern Iceland. InÁrmannsson H. ed. Geochemistry of the Earth’s Surface, pp. 377-380.A.A.Balkema, Rotterdam.

FRIMMEL F.H. 1992. Isolation and general characterization of organic acids frompore water. In Matthess G., Frimmel F., Hirsch P., Schulz H.D. and UsdowskiH.-E. eds. Progress in Hydrogeochemistry, pp. 9-13. Springer-Verlag, Berlin.

FRITTS H.C. 1962. An approach to dendroclimatology – screening by means ofmultiple regression techniques. Journal of Geophysical Research 67 (4), 1413-1420.

FRIZADO J.P. 1979. Ion exchange on humic materials – a regular solution approach.In Jenne E.A. ed. Chemical Modeling in Aqueous Systems: Speciation,Sorption, Solubility and Kinetics, pp. 133-145. American Chemical SocietySymposium Series 93. American Chemical Society, Washington, D.C.

FRYAR A.E., MULLICAN III W.F. & MACKO S.A. 2001. Groundwater recharge andchemical evolution in the southern High Plains of Texas, USA. HydrogeologyJournal 9 (6), 522-542.

GAILLARDET J., ALLÈGRE C.J. & DUPRÉ B. 1999. Invited lecture: Intensities andfluxes of global silicate weathering deduced from large river study. InÁrmannsson H. ed. Geochemistry of the Earth’s Surface, pp. 75-77.A.A.Balkema, Rotterdam.

GALTON F. 1888. Co-relations and their measurement, chiefly from anthropometricdata. Proceedings of the Royal Society 45, 135-140.

GARCÍA M.G., HIDALGO M DEL V. & BLESA M.A. 2001. Geochemistry ofgroundwater in the alluvial plain of Tucumán province, Argentina.Hydrogeology Journal 9 (6), 597-610.

GARRELS R.M. 1967. Genesis of some ground waters from igneous rocks. InAbelson P.H. ed. Researches in Geochemistry 2, pp. 405-420. John Wiley andSons Inc., New York.

GARRELS R.M. 1976. A survey of low temperature mineral-water relations. InInterpretation of Environmental Isotope and Hydrochemical Data inGroundwater Hydrology, pp. 65-84. International Atomic Energy Association,Vienna.

GARRELS R.M. & CHRIST C.L. 1965. Solutions, Minerals, and Equilibria. Harperand Row, New York, pp. 450.

GARRELS R.M. & MACKENZIE F.T. 1967. Origin of the chemical compositions ofsome springs and lakes. In Stumm W. ed. Equilibrium Concepts in NaturalWater Systems: A Symposium, Advances in Chemistry Series 67, pp. 222-242.American Chemical Society, Washington, D.C.

GARRELS R.M. & MACKENZIE F.T. 1971. Evolution of Sedimentary Rocks. Norton,New York, pp. 397.

GÉRARD M., BERTAUX J., ILDEFONSE PH., BULOURDE M., CHAUVEL C., DIA A..BENEDETTI M., BOULÈGUE J., CHABAUX F., FRITZ B., ETAME J., NGOUNOUNO

I., DERUELLE B. 1999. Weathering of Mount Cameroon: 1. Mineralogy andgeochemistry. In Ármannsson H. ed. Geochemistry of the Earth’s Surface, pp.381-384. A.A.Balkema, Rotterdam.

GHIORSE W.C. & WILSON J.T. 1988. Microbial ecology of the terrestrial subsurface.Advances in Applied Microbiology, 33, 107-172.

76

GIBLIN A.M. & DICKSON B.L. 1992. Source, distribution and economic significanceof trace elements in groundwaters from Lake Tyrrell, Victoria, Australia.Chemical Geology 96, 133-149.

GÍSLASON S.R. & EUGSTER H.P. 1987a. Meteoric water – basalt interactions: I. Alaboratory study. Geochimica et Cosmochimica Acta 51, 2827-2840.

GÍSLASON S.R. & EUGSTER H.P. 1987b. Meteoric water – basalt interactions: II. Afield study in north-eastern Iceland. Geochimica et Cosmochimica Acta 51,2841-2855.

GÍSLASON S.R., VEBLEN D.R. & LIVI K.J.T. 1993. Experimental meteoric water –basalt interactions: characterization and interpretation of alteration products.Geochimica et Cosmochimica Acta 57, 1459-1471.

GÍSLASON S.R., ARNÓRSSON S. & ÁRMANNSSON H. 1996. Chemical weathering ofbasalt in southwest Iceland: effects of runoff, age of rocks andvegetative/glacial cover. American Journal of Science 296, 837-907.

GLOE G. 1949. Report on the underground water resources of the AthertonTableland. Irrigation and Water Supply Commission, Queensland (unpubl.).

GOLDICH S.S. 1938. A study in rock-weathering. Journal of Geology 46, 17-58.GONG X. & RICHMAN M.B. 1995. On the application of cluster analysis to growing

season precipitation data in North America east of the Rockies. Journal ofClimate 8, 897-931.

GOOVAERTS P. 1997. Geostatistics for Natural Resources Evaluation. OxfordUniversity Press, Oxford, pp. 483.

GOTTARDI G. & GALLI E. 1985. Natural Zeolites. Springer-Verlag, New York, pp.390.

GRANDSTAFF D.E. 1986. The dissolution rate of forsteritic olivine from Hawaiianbeach sand. In Colman S.M. and Dethier D.P. eds. Rates of ChemicalWeathering of Rocks and Minerals, pp. 41-59. Academic Press, Orlando,Florida.

GRIMAUD D., BEAUCAIRE C. & MICHARD G. 1990. Modelling of the evolution ofgroundwaters in a granitic system at low temperature evolution: the Stripagroundwaters, Sweden. Applied Geochemistry 5, 525-535.

GROVE D.B. & STOLLENWERK K.G. 1987. Chemical reactions simulated by ground-water-quality models. Water Resources Bulletin 23 (4), 601-615.

GÜLER C., THYNE G.D., MCCRAY J.E. & TURNER A.K. 2002. Evaluation ofgraphical and multivariate statistical methods for classification of waterchemistry data. Hydrogeology Journal 10 (4), 455-474.

GUNN R.H. 1974. A soil catena on weathered basalt in Queensland. AustralianJournal of Soil Research 12, 1-14.

GUNNARSSON I. & ARNÓRSSON S. 1999. New data on the standard Gibbs energy ofH4SiO4 and its effect on silicate solubility. In Ármannsson H. ed.Geochemistry of the Earth’s Surface, pp. 449-452. A.A.Balkema, Rotterdam.

GUTTMAN L. 1954. Some necessary conditions for common-factor analysis.Psychometrika 19, 149-161.

HAIR J.F., ANDERSON R.E., TATHAM R.L. & BLACK W.C. 1995. Multivariate DataAnalysis: with Readings. Prentice Hall, Englewood Cliffs, New Jersey, pp.745.

HAKSTIAN A.R. & MULLER V.J. 1973. Some notes on the number of factorsproblem. Multivariate Behavioral Research 8, 461-475.

77

HAKSTIAN A.R. ROGERS W.T. & CATTELL R.B. 1982. The behavoir of number-of-factors rule with simulated data. Multivariate Behavioral Research 17, 193-219.

HARDIE L.A. & EUGSTER H.P. 1970. The evolution of closed-basin brines.Mineralogical Society of America Special Paper 3, 273-290.

HARMAN H.H. 1976. Modern Factor Analysis. The University of Chicago Press,Chicago, pp. 487.

HARMON R.S., WHITE W.B., DRAKE J.J. & HESS J.W. 1975. Regionalhydrochemistry of North American carbonate terrains. Water ResourcesResearch 11 (6), 963-967.

HARTIGAN J.H. 1975. Clustering Algorithms. John Wiley and Sons, New York, pp.351.

HAY R.L. 1966. Zeolites and Zeolitic Reactions in Sedimentary Rocks. TheGeological Society of America Special Papers 85, The Geological Society ofAmerica, New York, pp. 130.

HEARN P.P., STEINKAMPF W.C., BORTLESON G.C. & DROST B.W. 1985.Geochemical controls on dissolved sodium in basalt aquifers of the ColumbiaPlateau, Washington. United States Geological Survey Water-ResourcesInvestigations Report 84-4304, pp. 38.

HEARN P.P., STEINKAMPF W.C., WHITE L.D. & EVANS J.R. 1990. Geochemistry ofrock-water reactions in basalt aquifers of the Columbia River Plateau. In DoeB.R. ed. Proceedings of a U.S. Geological Survey Workshop onEnvironmental Geochemistry, United States Geological Survey Circular 1033,63-68.

HELGESON H.C. 1971. Kinetics of mass transfer among silicates and aqueoussolutions. Geochimica et Cosmochimica Acta 35, 421-469.

HELGESON H.C., BROWN T.H., & LEEPER R.H. 1969. Handbook of TheoreticalActivity Diagrams depicting Chemical Equilibria in Geologic Systemsinvolving an Aqueous Phase at one Atm and 0 to 30 °C. Freeman, Cooper, SanFrancisco, pp. 253.

HELGESON H.C., BROWN T.H., NIGRINI A. & JONES T.A. 1970. Calculation of masstransfer in geochemical proceses involving aqueous solutions. Geochimica etCosmochimica Acta 34, 569-592.

HEM J.D. 1985. Study and interpretation of the chemical characteristics of naturalwater. United States Geological Survey Water-Supply Paper 2254. UnitedStates Government Printing Office, Washington, D.C., pp. 264.

HERCZEG A.L. 2001. Can major ion chemistry be used to estimate groundwaterresidence time in basaltic aquifers? In Cidu R. ed. Water – Rock InteractionWRI-10, pp. 529-532. A.A.Balkema, Lisse.

HERCZEG A.L., TORGERSEN T., CHIVAS A.R. & HABERMEHL M.A. 1991.Geochemistry of groundwaters from the Great Artesian Basin, Australia.Journal of Hydrology 126, 225-245.

HERCZEG A.L. & PAYNE T.E. 1992. Recharge and weathering processes in fracturedrock aquifers in Northern Australia. In Kharaka Y.K. and Maest A.S. eds.Water – Rock Interaction WRI-7, pp. 561-564. A.A.Balkema, Rotterdam.

HILL I.G., WORDEN R.H. & MEIGHAN I.G. 2000. Geochemical evolution of apalaeolaterite: the Interbasaltic Formation, Northern Ireland. ChemicalGeology 166, 65-84.

HILL R.A. 1940. Geochemical patterns in Coachella Valley, California.Transactions of the American Geophysical Union 21, 46-53.

78

HIRSCH R.M., ALEXANDER R.B. & SMITH R.A. 1991. Selection of methods for thedetection and estimation of trends in water quality. Water Resources Research27 (5), 803-813.

HITCHON B., BILLINGS G.K. & KLOVAN J.E. 1971. Geochemistry and origin offormation waters in the western Canada sedimentary basin III. Factorscontrolling chemical composition. Geochimica et Cosmochimica Acta 35, 567-598.

HOLDREN G.R. & BERNER R.A. 1979. Mechanism of feldspar weathering–I.Experimental studies. Geochimica et Cosmochimica Acta 43, 1161-1171.

HOLDREN G.R. & SPEYER P.M. 1986. Stoichiometry of alkali feldspar dissolution atroom temperature and various pH values. In Colman S.M. and Dethier D.P.eds. Rates of Chemical Weathering of Rocks and Minerals, pp. 61-81.Academic Press, Orlando, Florida.

HOOPER P.R. 1982. The Columbia River basalts. Science 215 (4539), 1463-1468.HOOVER D.L. 1968. Genesis of zeolites, Nevada test site. In Eckel E.B. ed. Nevada

Test Site, 275-284. Memoir 110, The Geological Society of America, Boulder,Colorado.

HORST P. 1965. Factor Analysis of Data Matrices. Holt, Rinehart and Winston,New York, pp. 730.

HOTELLING H. 1933. Analysis of a complex of statistical variables into principalcomponents. Journal of Educational Psychology 24, 417-441; 498-520.

HOTELLING H. 1935. The most predictable criterion. Journal of EducationalPsychology 26, 139-142.

HOTELLING H. 1936a. Simplified calculation of principal components.Psychometrika 1, 27-35.

HOTELLING H. 1936b. Relations between two sets of variates. Biometrika 28, 321-377.

HOUSTON E.C. & SMITH J.V. 1997. Assessment of rock quality variability due tosmectitic alteration in basalt using X-ray diffraction analysis. EngineeringGeology 46, 19-32.

HUANG W.H. & KELLER W.D. 1971. Dissolution of clay minerals in dilute organicacids at room temperature. The American Mineralogist 56, 1082-1095.

HUSSEIN M.T. & ADAM E.G. 1995. Water quality in the Gedaref basin, Sudan.Hydrological Sciences Journal 40 (2), 205-216.

IIJIMA A. 1980. Geology of natural zeolites and zeolitic rocks. In Rees L.V.C. ed.Proceedings of the Fifth International Conference on Zeolites, 103-118.Heyden, London.

ILER R.K. 1979. The Chemistry of Silica. John Wiley and Sons, New York, pp. 866.ISBELL R.F., WEBB A.A. & MURTHA G.G. 1968. Atlas of Australian Soils.

Explanatory Data for Sheet 7, North Queensland. CSIRO Australia andMelbourne University Press, Melbourne.

ISBELL R.F., STEPHENSON P.J., MURTHA G.G. & GILLMAN G.P. 1976. Red basalticsoils in North Queensland. Technical Paper, Division of Soils, CSIROAustralia, 28.

ISBELL R.F., GILLMAN G.P., MURTHA G.G. & JONES P.N. 1977. Brown basaltic soilsin North Queensland. Technical Paper, Division of Soils, CSIRO Australia, 34.

JALLUDIN M. & RAZACK M. 1994. Analysis of pumping tests, with regard totectonics, hydrothermal effects and weathering, for fractured Dalha andstratiform basalts, Republic of Djibouti. Journal of Hydrology 155, 237-250.

79

JANKOWSKI J. & ACWORTH R.I. 1997. Impact of debris-flow deposits onhydrogeochemical processes and the development of dryland salinity in theYass River catchment, New South Wales, Australia. Hydrogeology Journal 5

(4), 71-88.JEFFERS J.N.R. 1978. An Introduction to Systems Analysis: with Ecological

Applications. Edward Arnold, London, pp. 198.JEONG C-H. 2001a. Effect of land use and urbanization on hydrochemistry and

contamination of groundwater from Taejon area, Korea. Journal of Hydrology253, 194-210.

JEONG C-H. 2001b. Mineral-water interaction and hydrogeochemistry in theSamkwang mine area, Korea. Geochemical Journal 35, 1-12.

JOBSON J.D. 1992. Applied Multivariate Data Analysis, Vol. II, Categorical andMultivariate Methods. Springer-Verlag, New York, pp. 731.

JOHNSON D.W., COLE D.W., GESSEL S.P., SINGER M.J. & MINDEN R.V. 1977.Carbonic acid leaching in a tropical, temperate, subalpine, and northern forestsoil. Artic and Alpine Research 9, 329-343.

JOIN J-L., COUDRAY J. & LONGWORTH K. 1997. Using principal componentsanalysis and Na/Cl ratios to trace groundwater circulation in a volcanic island:the example of Reunion. Journal of Hydrology 190, 1-18.

JOLLIFFE I.T. 1972. Discarding varaiables in a principal component analysis, I:Artificial data. Applied Statistics 21, 160-173.

JOLLIFFE I.T. 1986. Principal Component Analysis. Springer-Verlag, New York, pp.271.

JONES B.F. 1965. The hydrology and mineralogy of Deep Springs Lake, InyoCounty, California. United States Geological Survey Professional Paper 502-

A, pp. 53.JONES B.F., EUGSTER H.P. & RETTIG S.L. 1977. Hydrogeochemistry of the Lake

Magadi basin, Kenya. Geochimica et Cosmochimica Acta 41, 53-72.JÖRESKOG K.G., KLOVAN J.E. & REYMENT R.A. 1976. Geological Factor Analysis.

Elsevier Scientific Publishing Company, Amsterdam, pp. 178.JUNGE C.E. 1963. Air, Chemistry and Radioactivity. Academic Press, New York,

pp. 382.KAISER H.F. 1956. The varimax method of factor analysis. PhD thesis, University

of California, Berkeley (unpubl.).KAISER H.F. 1958. The varimax criterion for analytic rotation in factor analysis.

Psychometrika 23, 187-200.KAISER H.F. 1959. Computer program for varimax rotation in factor analysis.

Educational and Psychological Measurement 19, 413-420.KAISER H.F. 1960. The application of electronic computers to factor analysis.

Educational and Psychological Measurement 20, 141-151.KASTNER M., KEENE J.B. & GIESKES J.M. 1977. Diagenesis of siliceous oozes–I.

Chemical controls on the rate of opal A and opal CT transformation: anexperimental study. Geochimica et Cosmochimica Acta 41, 1041-1060.

KATZ B.G. 1989. Influence of mineral weathering on the chemical composition ofsoil water, springs, and ground water, Catoctin Mountains, Maryland.Hydrological Processes 3, 185-202.

KATZ B.G., BRICKER O.P. & KENNEDY M.M. 1985. Geochemical mass-balancerelationships for selected ions in precipitation and stream water, CatoctinMountains, Maryland. American Journal of Science 285, 931–962.

80

KELLER C.K. 1991. Hydrogeochemistry of a clayey till 2. Sources of CO2. WaterResources Research 27 (10), 2555-2564.

KENDALL M.G. & STUART A. 1966. The Advanced Theory of Statistics, Vol. 3,Design and Analysis, and Time Series. Charles Griffin, London, pp. 552.

KIERNAN K., WOOD C. & MIDDLETON G. 2002. Aquifer structure and contaminationrick in lava flows: insights from Iceland and Australia. EnvironmentalGeology DOI 10.1007/s00254-002-0707-8, Published Online 29th October2002.

KITTRICK J.A. 1979. Ion exchange and mineral stability: are the reactions linked orseparate? In Jenne E.A. ed. Chemical Modeling in Aqueous Systems:Speciation, Sorption, Solubility and Kinetics, pp. 401-412. American ChemicalSociety Symposium Series 93. American Chemical Society, Washington, D.C.

KLEIN J.M. 1971. Geochemical behavior of silica in the artesian ground water of theclosed basin area, San Luis Valley, Colorado. MSc thesis, Colorado School ofMines, Golden, Colorado (unpubl.), pp. 121.

KNISEL W.G. 1970. A factor analysis of reservoir losses. Water Resources Research6 (2), 491-498.

KOMAROWER P.M. & WALL V.J. 1981. The chemical evolution of the groundwatersin the Tertiary basalts of Victoria. In Lawrence C.R. & Hughes R.J. eds.Proceedings of the Groundwater Pollution Conference, Perth, 19-23 February1979, pp. 290-307. Australian Government Publishing Service, Canberra.

KORKKA-NIEMI K. 2001. Cumulative geological, regional and site-specific factorsaffecting groundwater quality in domestic wells in Finland. Monographs of theBoreal Environment Research No 20, pp. 98.

KOROTKY A.M., RAZJIGAEVA N.G., GANZEY L.A. & BAZAROVA V.B. 1995.Hydrochemistry and weathering products of Vietnam Shelf Islands. InKharaka Y.K. and Chudaev O.V. eds. Water – Rock Interaction WRI-8, pp.355-359. A.A.Balkema, Rotterdam.

KRAMER J.R. 1969. Subsurface brines and mineral equilibria. Chemical Geology 4,37-50.

KRAUSKOPF K.B. 1956. Dissolution and precipitation of silica at low temperatures.Geochimica et Cosmochimica Acta 10, 1-26.

KRZANOWSKI W.J. 1984. Principal component analysis in the presence of groupstructure. Applied Statistics 33, 164-168.

KULKARNI H. & DEOLANKAR S.B. 1993. Ground water abstraction from shallowunconfined Deccan basaltic aquifers of Maharashtra, India. In Sakura Y. ed.International Association of Hydrogeologists Selected Papers onEnvironmental Hydrogeology, Vol. 4, pp. 107-120. Verlag Heinz Heise,Hannover.

KUNDU N., PANIGRAHI M.K., TRIPATHY S., MUNSHI S., POWELL M.A. & HART B.R.2001. Geochemical appraisal of fluoride contamination of groundwater in theNayagarh District of Orissa, India. Environmental Geology 41, 451-460.

LAAKSOHARJU M., SKÅRMAN C. & SKÅRMAN E. 1999. Multivariate mixing andmass balance (M3) calculations, a new tool for decoding hydrogeochemicalinformation. Applied Geochemistry 14, 861-871.

LAIT R. 1998. Groundwater occurrence and chemistry in the Cattle CreekCatchment, North Queensland. MAppSc thesis, Queensland University ofTechnology, Brisbane (unpubl.), pp. 174.

81

LANGELIER W.F. & LUDWIG H.F. 1942. Graphical methods for indicating themineral character of natural waters. Journal of the American Water WorksAssociation 34, 335-352.

LANGMUIR D. 1997. Aqueous Environmental Geochemistry. Prentice Hall, UpperSaddle River, New Jersey, pp. 600.

LARSEN F., OWEN R., DAHLIN T., MANGEYA P. & BARMEN G. 2002. A preliminaryanalysis of the groundwater recharge to the Karoo formations, mid-Zambezibasin, Zimbabwe. Physics and Chemistry of the Earth 27, 765-772.

LARSSON I. 1984. Ground Water in Hard Rocks: Project 8.6 of the InternationalHydrological Programme. Unesco, Paris, pp. 228.

LASAGA A.C. 1984. Chemical kinetics of water – rock interaction. Journal ofGeophysical Research 89, 4009-4025.

LASAGA A.C., SOLER J.M., GANOR J., BURCH T.E. & NAGY K.L. 1994. Chemicalweathering rate laws and global geochemical cycles. Geochimica etCosmochimica Acta 58, 2361-2386.

LAWLEY D.N. & MAXWELL A.E. 1971. Factor Analysis as a Statistical Method.Butterworth and Co., London, pp. 153.

LAWRENCE A.R., LLOYD J.W. & MARSH J.M. 1976. Hydrochemistry and ground-water mixing in part of Lincolnshire Limestone Aquifer, England. GroundWater 14 (5), 320-327.

LAWRENCE F.W. & UPCHURCH S.B. 1976. Identification of geochemical patterns ingroundwater by numerical analysis. In Saleem Z.A. ed. Advances inGroundwater Hydrology, pp. 199-214. American Water ResourcesAssociation, Minneapolis.

LAWRENCE F.W. & UPCHURCH S.B. 1982. Identification of recharge areas usinggeochemical factor analysis. Ground Water 20 (6), 680-687.

LEACH L.M. 1986. Groundwater resources of the Atherton basalt, Atherton Shire.Queensland Water Resources Commission, Mareeba (unpubl.).

LEE P.J. 1969. Principal component analysis on the connate water of gas and oilfields in northern Taiwan. Proceedings of the Geological Society of China 12,121-128.

LEGRAND H.E. 1958. Chemical character of water in the igneous and metamorphicrocks of North Carolina. Journal of Economic Geology 53, 178-189.

LEGRAND H.E. 1964. System for evaluating the contamination potential of somewaste sites. Journal of the American Water Works Association 56 (8), 959-974.

LEOPOLD L.B. 1962. Rivers. American Scientist 50 (4), 511-537.LETTERMAIER D.P. 1976. Detection of trends in water quality data from records with

dependent observations. Water Resources Research 12 (5), 1037-1046.LEWIS G.N. & RANDALL M. 1961. Thermodynamics. McGraw-Hill, New York, pp.

566.LEWIS-BECK M.S. 1994. Factor Analysis and Related Techniques. Sage

Publications Toppan Publishing, London, pp. 424.LIKENS G.E., BORMANN F.H., PIERCE R.S., EATON J.S. & JOHNSON N.M. 1977.

Biogeochemistry of a Forested Ecosystem. Springer-Verlag, New York, pp.146.

LIN Y-P. 2002. Multivariate geostatistical methods to identify and map spatialvariations of soil heavy metals. Environmental Geology 42 (1), 1-10.

LINN R. 1968. A Monte Carlo approach to the number of factors problem.Psychometrika 33, 37-71.

82

LIOU J.G. 1971. Analcime equilibria. Lithos 4, 389-402.LLOYD J.W. 1965. The hydrochemistry of the aquifers of north-eastern Jordan.

Journal of Hydrology 3, 319-330.LLOYD J.W. & HEATHCOTE J.A. 1985. Natural Inorganic Hydrochemistry in

Relation to Groundwater: An Introduction. Clarendon Press, Oxford, pp. 296.LÓPEZ-CHICANO M., BOUAMAMA M., VALLEJOS A. & PULIDO-BOSCH A. 2001.

Factors which determine the hydrogeochemical behaviour of karstic springs. Acase study from the Betic Cordilleras, Spain. Applied Geochemistry 16, 1179-1192.

LOUGHNAN F.C. 1969. Chemical Weathering of the Silicate Minerals. AmericanElsevier Publishing Company, New York, pp. 154.

LOUVAT P. & ALLÈGRE C.J. 1997. Present dunudation rates on the island of Réuniondetermined by river geochemistry: basalt weathering and mass budget betweenchemical and mechanical erosions. Geochimica et Cosmochimica Acta 61,3645-3669.

LOVE A.J., HERCZEG A.L., ARMSTRONG D., STADTER F. & MAZOR E. 1993.Groundwater flow regime within the Gambier Embayment of the Otway Basin,Australia: evidence from hydraulics and hydrochemistry. Journal ofHydrology 143, 297-338.

LUCE R.W., BARTLETT R.W. & PARKS G.A. 1972. Dissolution kinetics ofmagnesium silicates. Geochimica et Cosmochimica Acta 36, 35-50.

LUNKAD S.K. & RAYMAHASHAY B.C. 1978. Ground water quality in weatheredDeccan Basalt of Malwa Plateau, India. Quarterly Journal of EngineeringGeology 11, 273-277.

MAGARITZ M & LUZIER J.E. 1985. Water-rock interactions and seawater –freshwater mixing effects in the coastal dune aquifer, Coos Bay, Oregon.Geochimica et Cosmochimica Acta 49, 2515-2525.

MAHARA Y. & IGARASHI T. 1993. Survey of groundwater flow in a volcanic aquiferby the 3H+ 3He dating method. In Sakura Y. ed. International Association ofHydrogeologists Selected Papers on Environmental Hydrogeology, Vol. 4, pp.173-183. Verlag Heinz Heise, Hannover.

MALCOLM D.T. & NAGEL B.K.A. 1997. Soils of the Atherton tablelands 1:50 000.The State of Queensland, Department of Natural Resources.

MALCOLM D.T., NAGEL B.K.A., SINCLAIR I.G. & HEINER I.J. 1999. Soils andagricultural land suitability of the Atherton Tablelands. QueenslandDepartment of Natural Resources, Brisbane, Land Resources BulletinDNRQ980091, pp. 241.

MANGOLD D.C. & TSANG C.-F. 1991. A summary of subsurface hydrological andhydrochemical models. Reviews of Geophysics 29, 51-79.

MANLY B.F.J. 1986. Multivariate Statistical Methods – A Primer. Chapman & Hall,London, pp. 159.

MARDIA K.V. 1970. Measures of multivariate skewness and kurtosis withapplications. Biometrika 57, 519-530.

MARTÍNEZ D.E. & BOCANEGRA E.M. 2001. Hydrogeochemistry of the coastal duneaquifer in the province of Buenos Aires, Argentina. In Seiler K.P. andWohnlich S. eds. New approaches to characterising groundwater flow.Proceedings of the XXX1st International Congress of the InternationalAssociation of Hydrogeologists, Munich, pp. 1223-1226. A.A.Balkema, Swets& Zeitlinger B.V., Lisse.

83

MAST M.A. & DREVER J.I. 1990. Chemical weathering in the Loch Vale Watershed,Rocky Mountain National Park, Colorado. Water Resources Research 26 (12),2971-2978.

MATALAS N.C. & REIHER B.J. 1967. Some comments on the use of factor analysis.Water Resources Research 3 (1), 213-223.

MAZARI M. & MACKAY D.M. 1993. Potential for groundwater contamination inMexico City. Environmental Science and Technology 27 (5), 794-801.

MAZOR E. 1976. Multitracing and multisampling in hydrological studies. InInterpretation of Environmental Isotope and Hydrochemical Data inGroundwater Hydrology, pp. 7-36. International Atomic Energy Association,Vienna.

MAZOR E. 1997. Chemical and Isotopic Groundwater Hydrology – The AppliedApproach. Marcel Dekker, New York, pp. 413.

MCBEAN E.A. & ROVERS F.A. 1998. Statistical Procedures for Analysis ofEnvironmental Monitoring Data and Risk Assessment. Prentice Hall, UpperSaddle River, New Jersey, pp. 313.

MCDONOUGH W.F., MCCULLOCH M.T. & SUN S.S. 1985. Isotopic and geochemicalsystematics in Tertiary-Recent basalts from southeasten Australia andimplications for the evolution of the sub-continental lithosphere. Geochimicaet Cosmochimica Acta 49, 2051-2067.

MCELROY M.N. & KAESLER R.L. 1965. Application of factor analysis to the UpperCambrian Reagan Sandstone of central and north-west Kansas. Compass ofSigma Gamma Epsilon 42, 188-201.

MCENIERY M.B. 1980. Groundwater resources – North Queensland. In HendersonR.A. and Stephenson P.J. eds. The Geology and Geophysics of NortheasternAustralia, pp. 435-445. Geological Society of Australia, Queensland Division,Brisbane.

MCKENZIE J.M., SIEGEL D.I., PATTERSON W. & MCKENZIE D.J. 2001. Ageochemical survey of spring water from the main Ethiopian rift valley,southern Ethiopia: implications for well-head protection. HydrogeologyJournal 9 (3), 265-272.

MCMAHON P.B., WILLIAMS D.F. & MORRIS J.T. 1990. Production and carbonisotopic composition of bacterial CO2 in deep coastal plain sediments of SouthCarolina. Ground Water 28 (5), 693-702.

MCNEIL V.H. 2002. Assessment methodologies for very large, irregularly collectedwater quality data sets with special reference to the natural waters ofQueensland. PhD thesis, Queensland University of Technology, Brisbane(unpubl.), pp. 166.

MELLOUL A. & COLLIN M. 1992. The ‘principal components’ statistical-method as acomplementary approach to geochemical methods in water quality factoridentification; application to the Coastal Plain aquifer of Israel. Journal ofHydrology 140, 49-73.

MENG S.X. & MAYNARD J.B. 2001. Use of statistical analysis to formulateconceptual models of geochemical behavior: water chemical data from theBotucatu aquifer in São Paulo state, Brazil. Journal of Hydrology 250, 78-97.

MEYBECK M. 1986. Composition chimique naturelle des ruisseaux non pollués deFrance. Science Géologie Bulletin 39 (1), 3-77.

MILLER R.L. & GOLDBERH E.D. 1955. The normal distribution in geochemistry.Geochimica et Cosmochimica Acta 8, 53-62.

84

MILLER W.R. & DREVER J.I. 1977. Water chemistry of a stream following a stormfollowing a storm, Absaroka Mountains, Wyoming. Geological Society ofAmerica Bulletin 88, 286-290.

MILLOT R., GAILLARDET J., ALLÈGRE C.J. & DUPRÉ B. 1999. Silicate weatheringrates in the Mackenzie river basin, North-West Territories, Canada. InÁrmannsson H. ed. Geochemistry of the Earth’s Surface, pp. 115-118.A.A.Balkema, Rotterdam.

MITCHELL J. 1932. The origin, nature and importance of soil organic constituentshaving base exchange properties. Journal of American Society of Agronomy24, 256-275.

MOLL-STALCUP E.J. & ARTH J.G. 1991. Isotopic and chemical constraints on thepetrogenesis of Blackburn Hills volcanic field, western Alaska. Geochimica etCosmochimica Acta 55, 3753-3776.

MOLONEY M. 1999. The magnetic method applied within a Quaternary volcanicplateau – Atherton, North Queensland. BAppSc(Hons) thesis, QueenslandUniversity of Technology, Brisbane (unpubl.), pp. 81.

MOMEN B., EICHLER L.W., BOYLEN C.W. & ZEHR J.P. 1996. Application ofmultivariate statistics in detecting temporal and spatial patterns of waterchemistry in Lake George, New York. Ecological Modelling 91, 183-192.

MORRISON D.F. 1990. Multivariate Statistical Methods. McGraw-Hill, New York,pp. 495.

MORGAN C.O. & WINNER, JR M.D. 1962. Hydrochemical facies in the 400 foot and600 foot sands of the Baton Rouge Area, Louisiana. United States GeologicalSurvey Professional Paper 450-B, 120-121.

MORGAN W.R. 1968. The petrology of some Cainozoic basalt rocks from theAtherton Tableland and Einasleigh-Mount Garnet areas, North Queensland.Proceedings of the Royal Society of Queensland 80, 1-12.

MOSIER C.I. 1939. Determining a simple structure when loadings for certain tests areknown. Psychometrika 4, 149-162.

MOTTL M.J. & HOLLAND H.D. 1978. Chemical exchange during hydrothermalalteration of basalt by seawater: I. Experimental results for major and minorcomponents of seawater. Geochimica et Cosmochimica Acta 42, 1103-1117.

MOULTON K.L & BERNER R.A. 1999. Quantitative effects of plants on weathering:forest sinks for carbon. In Ármannsson H. ed. Geochemistry of the Earth’sSurface, pp. 57-60. A.A.Balkema, Rotterdam.

MULAIK S.A. 1972. The Foundations of Factor Analysis. McGraw-Hill, New York,pp. 453.

MULAIK S.A. 1986. Factor analysis and psychometrika: major developments.Psychometrika 51, 23-33.

MULLER P.J. 1978. Mulgrave River groundwater investigations. Hydrogeology ofthe Mulgrave River alluvial valley. Geological Survey of Queensland Record1978/6 (unpubl.).

NAIK P.K., AWASTHI A.K., ANAND A.V.S.S. & MOHAN P.C. 2001. Hydrogeologicframework of the Deccan terrain of the Koyna River basin, India.Hydrogeology Journal 9 (3), 243-264.

NARAYANPETHKAR A.B., GURUNADHA RAO V.V.S. & MALLICK K. 1994. Estimationof groundwater recharge in a basaltic aquifer. Hydrological Processes 8, 211-220.

85

NÉGREL P. & LACHASSAGNE P. 2000. Geochemistry of the Maroni River (FrenchGuiana) during the low water stage: implications for water – rock interactionand groundwater characteristics. Journal of Hydrology 237, 212-233.

NESBITT H.W. & WILSON R.E. 1992. Recent chemical weathering of basalts.American Journal of Science 292, 740-777.

NEUHAUS J.O. & WRIGLEY C. 1954. The quartimax method: an analytical approachto orthogonal simple structure. British Journal of Statistical Psychology 7, 81-91.

NEWCOMB R.C. 1972. Quality of the ground water in basalt of the Columbia RiverGroup, Washington, Oregon, and Idaho. United States Geological SurveyWater-Supply Paper 1999-N, pp. 71.

NÖLTE J. 1988. Pollution source analysis of river water and sewerage sludge.Environmental Technology Letters 9, 857-868.

NORDSTROM D.K., PLUMMER L.N., WIGLEY T.M.L., WOLERY T.J., BALL J.W., JENNE

E.A., BASSETT R.L., CRERAR D.A., FLORENCE T.M., FRITZ B., HOFFMAN M.,HOLDREN JR G.R., LAFON G.M., MATTIGOD S.V., MCDUFF R.E., MOREL F.,REDDY M.M., SPOSITO G. & THRAIKILL J. 1979. A comparison ofcomputerized chemical models for equilibrium calculations in aqueoussystems. In Jenne E.A. ed. Chemical Modeling in Aqueous Systems:Speciation, Sorption, Solubility and Kinetics, pp. 857-892. American ChemicalSociety Symposium Series 93. American Chemical Society, Washington, D.C.

NORDSTROM D.K., BALL J.W. DONAHOE R.J. & WHITTEMORE D. 1989.Groundwater chemistry and water – rock interaction at Stripa. Geochimica etCosmochimica Acta 53, 1727-1740.

NORDSTROM D.K. & MUNOZ J.L. 1994. Geochemical Thermodynamics. BlackwellScientific Publications, Boston, pp. 493.

OKI D.S., SOUZA W.R., BOLKE E.L. & BAUER G.R. 1998. Numerical analysis of thehydrogeologic controls in a layered coastal aquifer system, Oahu, Hawaii,USA. Hydrogeology Journal 6 (2), 243-263.

OLAFSSON M. & KRISTMANNSDÓTTIR H. 1989. The influence of volcanic activity ongroundwater chemistry within the Námafjall geothermal system, North Iceland.In Miles D.L. ed. Water – Rock Interaction WRI-6, pp. 537-540.A.A.Balkema, Rotterdam.

OLIVA P., VIERS J., DUPRÉ B., FORTUNÉ J.P., MARTIN F., BRAUN J.J., NAHON D. &ROBAIN H. 1999. The effect of organic matter on chemical weathering: studyof a small tropical watershed: Nsimi-Zoétélé site, Cameroon. Geochimica etCosmochimica Acta 63, 4013-4035.

OSBORNE R.H. 1967. The American Upper Ordovician standard. VIII. R-modefactor analysis of Cincinnatian limestones. Journal of Sedimentary Petrology37 (2), 649-657.

OSBORNE R.H. 1969. The American Upper Ordovician standard. XI. Multivariateclassification of typical Cincinnatian calcarenites. Journal of SedimentaryPetrology 39 (2), 769-776.

O’SHEA J.A. 1954. Progress report on Atherton Tableland underground waterinvestigation to 30th June 1954. Irrigation and Water Supply Commission,Queensland (unpubl.).

PACES T. 1972. Chemical characteristics and equilibration in natural water-felsicrock-CO2 system. Geochimica et Cosmochimica Acta 36, 217-240.

PACES T. 1973. Steady state kinetics and equilibrium between ground water andgranitic rock. Geochimica et Cosmochimica Acta 37, 2641-2663.

86

PACES T. 1976. Kinetics of natural water systems. In Interpretation ofEnvironmental Isotope and Hydrochemical Data in Groundwater Hydrology,pp. 85-108. International Atomic Energy Association, Vienna.

PACES T. 1983. Rate constants of dissolution derived from the measurements ofmass balance in hydrological catchments. Geochimica et Cosmochimica Acta47, 1855-1863.

PACES T. 1984. Mass-balance approach to the understanding of geochemicalprocesses in aqueous systems. In Eriksson E. ed. Hydrochemcial Balances ofFreshwater Systems, Proceedings International Symposium on HydrochemicalBalances of Freshwater Systems, Uppsala, Sweden, 223-235. InternationalAssociation of Hydrological Sciences, Sallingford.

PACHECO F.A.L. 1998. Finding the number of natural clusters in groundwater datasets using the concept of equivalent class. Computers and Geosciences 14 (1),7-15.

PALMER C.D. & CHERRY J.A. 1984. Geochemical evolution of groundwater insequences of sedimentary rocks. Journal of Hydrology 75, 27-65.

PARKHURST D.L. 1995. User’s Guide to PHREEQC – A computer program forspeciation, reaction-path, advective-transport, and inverse geochemicalcalculations. United States Geological Survey Water-Resources InvestigationsReport 95-4227, pp. 143.

PARKHURST D.L., THORSTENSON D.C. & PLUMMER L.N. 1980. PHREEQE – Acomputer program for geochemical calculations. United States GeologicalSurvey Water-Resources Investigations Report 80-96, pp. 210.

PARKHURST D.L., PLUMMER L.N. & THORSTENSON D.C. 1982. BALANCE – Acomputer program for calculating mass transfer for geochemical reactions ingroundwater. United States Geological Survey Water-Resources InvestigationsReport 82-14, pp. 29.

PARKHURST D.L. & PLUMMER L.N. 1993. Geochemical models. In Alley W.M. ed.Regional Ground-Water Quality, pp. 199-225. Van Nostrand Reinhold, NewYork.

PARKHURST D.L. & APPELO C.A.J. 1999. User’s Guide to PHREEQC (version 2) –A computer program for speciation, batch-reaction, one-dimensional transport,and inverse geochemical calculations. United States Geological Survey Water-Resources Investigations Report 99-4259, pp. 312.

PAWAR N.J. 1993. Geochemistry of carbonate precipitation from the ground watersin basaltic aquifers: an equilibrium thermodynamic approach. Journal of theGeological Society of India 41, 119-131.

PAWAR N.J. & SHAIKH I.J. 1995. Nitrate pollution of ground waters from shallowbasaltic aquifers, Deccan Trap Hydrologic Province, India. EnvironmentalGeology 25, 197-204.

PEARCE B.R. 2002. Report on compilation of a geological conceptual model for theAtherton Tableland Basalts. Queensland Department of Natural Resources andMines, Brisbane (unpubl.).


PEARSON K. 1901. On lines and planes of closest fit to systems of points in space.Philosophical Magazine 2, 559-572.

87

PEREIRA M.R. & ALMEIDA C. 2000. Geochemical evolution of groundwater inmetamorphic rocks of Trás-Os-Montes, Portugal. In Sililo O. et al. eds.Groundwater: Past achievements and future challenges. Proceedings of theXXXth International Congress of the International Association ofHydrogeologists, Cape Town, pp. 587-591. A.A.Balkema, Rotterdam.

PETERS N.E. 1984. Evaluation of environmental factors affecting yields of majordissolved ions of streams in the United States. United States GeologicalSurvey Water-Supply Paper 2228, pp. 39.

PETERSON F.L. 1972. Water development on tropic volcanic islands – type example:Hawaii. Ground Water 10 (5), 18-23.

PETERSON F.L. 1984. Hydrogeology of high oceanic islands. In Water Resources ofSmall Islands, Technical Proceedings of the Regional Workshop on WaterResources of Small Isalnds (Part 2), pp. 431-435. Commonwealth ScienceCouncil, London.

PETERSON F.L. 1993. Hydrogeology of volcanic oceanic islands. In Sakura Y. ed.International Association of Hydrogeologists Selected Papers onEnvironmental Hydrogeology, Vol. 4, pp. 163-171. Verlag Heinz Heise,Hannover.

PETROVIC R., BERNER R.A. & GOLDHABER M.B. 1976. Rate control in dissolution ofalkali feldspars: I. Study of residual feldspar grains by x-ray photoelectronmicroscopy. Geochimica et Cosmochimica Acta 40, 537-548.

PIPER A.M. 1944. A graphic procedure in the geochemical interpretation of wateranalyses. Transactions of the American Geophysical Union 25, 914-923.

PLUMMER L.N. 1984. Geochemical modeling: a comparison of forward and inversemethods. In Hitchon B and Wallick E.I. eds. Proceedings of the FirstCanadian / American Conference on Hydrogeology – Practical Applications ofGround Water Geochemistry, pp. 149-177. National Water Well Association,Worthington, Ohio.

PLUMMER L.N. 1992. Geochemical modeling of water-rock interaction: past,present, future. In Kharaka Y.K. and Maest A.S. eds. Water – Rock InteractionWRI-7, pp. 23-33. A.A.Balkema, Rotterdam.

PLUMMER L.N. & BACK W. 1980. The mass balance approach: application tointerpreting the chemical evolution of hydrologic systems. American Journalof Science 280, 130-142.

PLUMMER L.N., PARKHURST D.L. & THORSTENSON D.C. 1983. Development ofreaction models for ground-water systems. Geochimica et Cosmochimica Acta47, 665-686.

PLUMMER L.N., PRESTEMON E.C. & PARKHURST D.L. 1994. An interactive code(NETPATH) for modeling net geochemical reactions along a flow path,version 2.0, United States Geological Survey Water-Resources InvestigationsReport 94-4169, pp. 130.

PREISENDORFER R.W. 1988. Principal Component Analysis in Meteorology andOceanography. Elsevier Science Publishers B.V., Amsterdam, pp. 425.

PRICE R.C., GRAY C.M. & FREY F.A. 1997. Strontium isotopic and trace elementheterogeneity in the plains basalts of the Newer Volcanic Province, Victoria,Australia. Geochimica et Cosmochimica Acta 61, 171-192.

RAO C.R. 1964. The use and interpretation of principal component analysis inapplied research. Sankhy Serie A 26, 329-358.

88

RASHID M. 1971. Role of humic acids of marine origin and their different molecularweight fractions in complexing di- and tri-valent metals. Soil Science 111,298-306.

RATHA D.S. & SAHU B.K. 1993. Source and distribution of metals in urban soil ofBombay, India, using multivariate statistical techniques. EnvironmentalGeology 22, 276-285.

REEDER S.W., HITCHON B. & LEVINSON A.A. 1972. Hydrogeochemistry of thesurface waters of the Mackenzie River drainage basin, Canada – I. Factorscontrolling inorganic composition. Geochimica et Cosmochimica Acta 36,825-865.

REGHUNATH R., SREEDHARA MURTHY T.R. & RAGHAVAN B.R. 2002. The utility ofmultivariate statistical techniques in hydrogeochemical studies: an examplefrom Karnataka, India. Water Research 36, 2437-2442.

REIMANN C. & FILZMOSER P. 2000. Normal and lognormal data distribution ingeochemistry: death of a myth. Consequences for the statistical treatment ofgeochemical and environmental data. Environmental Geology 39 (9), 1001-1014.

RENICK B.C. 1924. Base exchange in ground water by silicates as illustrated inMontana. United States Geological Survey Water-Supply Paper 520-D, 53-72.

REYMENT R.A 1971. Multivariate normality in morphometric analysis.Mathematical Geology 3 (4), 357-368.

REYMENT R.A 1991. Multidimensional Palaeobiology. Pergamon Press, Oxford, pp.377.

REYMENT R.A 1997. Multiple group principal component analysis. MathematicalGeology 29 (1), 1-16.

REYMENT R.A & JÖRESKOG K.G. 1996. Applied Factor Analysis in the NaturalSciences. Cambridge University Press, Cambridge, pp. 369.

RIHA M. & KENLEY P.R. 1978. Investigation of the hydrogeology and groundwaterpollution in the basalt aquifer system, west of Melbourne. Geological Surveyof Victoria 1978/40 (unpubl.).

RICE R.M. 1967. Multivariate methods useful in hydrology. In Proceedings of theInternational Hydrology Symposium, pp. 471-478. International Association ofScientific Hydrology, Fort Collins.

RILEY J.A., STEINHORST R.K., WINTER G.V. & WILLIAMS R.E. 1990. Statisticalanalysis of the hydrochemistry of groundwater in Columbia River Basalts.Journal of Hydrology 119, 245-262.

ROCK N.M.S. 1988. Numerical Geology. Lecture Notes in Earth Sciences 18.Springer-Verlag, Berlin, pp. 427.

ROGERS R.J. 1989. Geochemical comparison of groundwater in areas of NewEngland, New York, and Pennsylvania. Ground Water 27, 690-712.

ROLLINSON H.R. 1993. Using Geochemical Data: Evaluation, Presentation,Interpretation. Longman Group, Harlow, pp. 352.

ROSENAU J.C., LUBKE E.R. & NAKAHARA R.H. 1971. Water resources of north-central Oahu, Hawaii. United States Geological Survey Water-Supply Paper1899-D, pp. 39.

RUIZ F., GOMIS V. & BLASCO P. 1990. Application of factor analysis to thehydrogeochemical study of a coastal aquifer. Journal of Hydrology 119, 169-177.

RUMMEL R.J. 1970. Applied Factor Analysis. Northwestern University Press,Evanston, pp. 619.

89

SALMAN A.R. & ABU RUKA’H Y.H. 1999. Multivariate and principal componentstatistical analysis of contamination in urban and agricultural soils from NorthJordan. Environmental Geology 38 (3), 265-270.

SARIN M.M., KRISHNASWAMI S., DILLI K., SOMAYAJULU B.L. & MOORE W.S. 1989.Major ion chemistry of the Ganga – Brahmaputra river system: weatheringprocesses and fluxes to the Bay of Bengal. Geochimica et Cosmochimica Acta53, 997-1009.

SAUNDERS D.R. 1953. An analytic method for rotation to orthogonal simplestructure. Research Bulletin 53-10. Educational Testing Service, Princeton.

SCHNITZER M. & KHAN S. 1972. Humic Substances in the Environment. MarcelDekker, New York, pp. 327.

SCHNOOR J.L. 1990. Kinetics of chemical weathering: a comparison of laboratoryand field weathering rates. In Stumm W. ed. Aquatic Chemical Kinetics:Reaction Rates of Processes in Natural Waters, pp, 475-504 John Wiley andSons, New York.

SCHNOOR J.L. & STUMM W. 1985. Acidification of aquatic and terrestrial systems.In Stumm W. ed. Chemical Processes in Lakes, pp. 311-338. Wiley-Interscience, New York.

SCHOELLER H. 1956. Géochimie des Eaux Souterraines: application aux eaux degisements de pétrole. Technip, Paris, pp.213.

SCHOELLER H. 1962. Les Eaux Souterraines. Massio et Cie, Paris, pp.642.SCHÖNEMANN P.H. & WANG M-M. 1972. Some new results on factor

indeterminancy. Psychometrika 37, 61-91.SCHOT P.P. & VAN DER WAL J. 1992. Human impact on regional groundwater

composition through intervention in natural flow patterns and changes in landuse. Journal of Hydrology 134, 297-313.

SCHOTT J., BERNER R.A. & SJOBERG E.L. 1981. Mechanism of pyroxene andamphibole weathering. I. Experimental studies of iron-free minerals.Geochimica et Cosmochimica Acta 45, 2123-2135.

SCHOTT J. & BERNER R.A. 1983. X-ray photoelectron studies of the mechanism ofiron silicate dissolution during weathering. Geochimica et Cosmochimica Acta47, 2233-2240.

SCHOTT J. & BERNER R.A. 1985. Dissolution mechanisms of pyroxenes and olivinesduring weathering. In Drever J.I. ed. The Chemistry of Weathering, pp. 35-53.D. Reidel Publishing Company, Dordrecht.

SCHREIBER M.E., MOLINE G.R. & BAHR J.M. 1999. Using hydrochemical facies todelineate ground water flowpaths in fractured shale. Ground WaterMonitoring and Remediation 19 (1), 95-109.

SCHWARTZ F.W. & GALLUP D. 1978. Some factors controlling the major ionchemistry of small lakes: examples from the Prairie Parkland of Canada.Hydrobiologia 58 (1), 65-81.

SEABER P.R. 1962. Cation hydrochemical facies of groundwater in the EnglishtownFormation, New Jersey. United States Geological Survey Professional Paper450-B, 124-126.

SEYFRIED W.E. & MOTTL M.J. 1982. Hydrothermal alteration of basalt by seawaterunder seawater dominated conditions. Geochimica et Cosmochimica Acta 40,777-789.

SEYHAN E. 1985. Introduction to Multivariate Statistical Analysis in Hydrology.Free University, Amsterdam.

90

SEYHAN E. & HOPE A.S. 1983. Calculating runoff from catchment physiography inSouth Africa. Water South Africa 9 (4), 131-139.

SEYHAN E., VAN DE GRIEND A.A. & ENGELEN G.B. 1985. Multivariate analysis andinterpretation of the hydrochemistry of a dolomitic reef aquifer, northern Italy.Water Resources Research 21 (7), 1010-1024.

SHELDRICK M.K.M. 1999. Stratigraphic interpretation of a lava field usingpetrogenetic modelling. BAppSc(Hons) thesis, Queensland University ofTechnology, Brisbane (unpubl.), pp. 57.

SHELTON M.L. 1983. Basalts and groundwater management in the Deschutes RiverBasin, Oregon. The Environmental Professional 5, 33-45.

SHVARTSEV S.L. 1978. Hydrogeochemistry of Hypergenic Zone: 287. Nedra,Moscow.

SIMONETT D.S. & BAULEKE M.P. 1963. Mineralogy of soils on basalt in NorthQueensland. Proceedings of the Soil Society of America 27, 205-212.

SINGER A. 1999. Weathering of basic magmatic rocks under Mediterraneanconditions. In Ármannsson H. ed. Geochemistry of the Earth’s Surface, pp.403-405. A.A.Balkema, Rotterdam.

SINGH A.K. & HASNAIN S.I. 1999. Environmental geochemistry of Domodar Riverbasin, east coast of India. Environmental Geology 37, 124-136.

SINGHAL B.B.S. 1973. Some observations on the occurrence, utilisation andmanagement of groundwater in the Deccan Trap areas of Central Maharashtra,India. In Proceedings International Symposium on Development ofGroundwater Resources, Madras, India, Vol. 3, pp. V75-81.

SINGHAL B.B.S. & GUPTA R.P. 1999. Applied Hydrogeology of Fractured Rocks.Kluwer Academic Publishers, Dordrecht, The Netherlands, pp. 400.

SMEDLEY P.L. 1989. Alkali metal enrichments in groundwaters from theCarnmenellis area, Cornwall. In Miles D.L. ed. Water – Rock InteractionWRI-6, pp. 647-650. A.A.Balkema, Rotterdam.

SNYDER W.M. 1962. Some possibilities for multivariate analysis in hydrologicstudies. Journal of Geophysical Research 67 (2), 721-729.

SOLOMON D.K. & CERLING T.E. 1987. The annual carbon dioxide cycle in amontane soil: observations, modeling, and implications for weathering. WaterResources Research 23 (12), 2257-2265.

SPEARMAN C. 1904. ‘General intelligence’, objectively determined and measured.American Journal of Psychology 15, 201-293.

SPEARMAN C. 1927. The Abilities of Man: Their Nature and Measurement.Macmillan, London, pp. 415.

SPEARS D.A. 1976. Information on groundwater composition obtained from alaboratory study of sediment-water interaction. Quarterly Journal ofEngineering Geology 9, 25-36.

SPENCER R.J., EUGSTER H.P., JONES B.F. & RETTIG S.L. 1985a. Geochemistry ofGreat Salt Lake, Utah I. Hydrochemistry since 1850. Geochimica etCosmochimica Acta 49, 727-738.

SPENCER R.J., EUGSTER H.P. & JONES B.F. 1985b. Geochemistry of Great Salt Lake,Utah II. Pleistocene-Holocene evolution. Geochimica et Cosmochimica Acta49, 739-748.

SPOSITO G. 1989. The Chemistry of Soils. Oxford University Press, New York, pp.277.

91

STALLARD R.F. & EDMOND J.M. 1983. Geochemistry of the Amazon 2. Theinfluence of geology and weathering environment on the dissolved load.Journal of Geophysical Research 88 (C14), 9671-9688.

STEARNS H.T. 1942. Hydrology of volcanic terrains. In Meinzer O.E. ed.Hydrology, pp. 678-703. Dover Publications, New York.

STEELE T.D. & MATALAS N.C. 1974. Principal-component analysis of streamflowchemical quality data. In Proceedings of an International Symposium onMathematical Models in Hydrology in Warsaw, Poland 1971, pp. 355-363.International Association of Hydrological Sciences, Paris.

STEIN R. & SCHWARTZ F.W. 1990. On the origin of saline soils at BlackspringRidge, Alberta, Canada. Journal of Hydrology 117, 99-131.

STEINHORST R.K. & WILLIAMS R.E. 1985. Discrimination of groundwater sourcesusing cluster analysis, MANOVA, canonical analysis and discriminantanalysis. Water Resources Research 21 (8), 1149-1156.

STEPHENSON P.J. 1989. Northern Queensland. In Johnson R.W. ed. IntraplateVolcanism in Eastern Australia and New Zealand, pp. 89-97. CambridgeUniversity Press, Cambridge.

STEPHENSON P.J. & GRIFFIN T.J. 1976. Cainozoic volcanicity North Queensland.Proceedings of the 25th International Geological Congress, Sydney, ExcursionGuide 7A.

STEPHENSON P.J., GRIFFIN T.J. & SUTHERLAND F.L. 1980. Cainozoic volcanism innortheastern Australia. In Henderson R.A. and Stephenson P.J. eds. TheGeology and Geophysics of Northeastern Australia, pp. 349-374. GeologicalSociety of Australia, Queensland Division, Brisbane.

STEPHENSON P.J., BURCH-JOHNSTON A.T., STANTON D. & WHITEHEAD P.W. 1998.Three long lava flows in north Queensland. Journal of Geophysical Research103 (B11), 27359-27370.

STIFF H.A. 1951. The interpretation of chemical water analysis by means of patterns.Journal of Petroleum Technology 3, 15-17.

STUMM W. & MORGAN J.J. 1981. Aquatic Chemistry. John Wiley and Sons, NewYork, pp. 780.

STUMM W. & WIELAND E. 1990. Dissolution of oxide and silicate minerals: ratesdepend on surface speciation. In Stumm W. ed. Aquatic Chemical Kinetics:Reaction Rates of Processes in Natural Waters, pp, 367-400 John Wiley andSons, New York.

STUMM W. & WOLLAST R. 1990. Coordination chemistry of weathering. Reviews ofGeophysics 28, 53-69.

STUYFZAND P.J. 1999. Patterns in groundwater chemistry resulting fromgroundwater flow. Hydrogeology Journal 7 (1), 15-27.

SUK H. & LEE K-K. 1999. Characterization of a ground water hydrochemical systemthrough multivariate analysis: clustering into ground water zones. GroundWater 37 (3), 358-366.

SUTHERLAND F.L. 1998. Origin of north Queensland Cenozoic volcanism:relationships to long lava flow basaltic fields, Australia. Journal ofGeophysical Research 103 (B11), 27347-27358.

SVERDRUP H.U. 1990. The Kinetics of Base Cation Release due to ChemicalWeathering. Lund University Press, Lund, pp. 246.

SVERDRUP H. & WARFVINGE P. 1988. Weathering of primary silicate minerals in thenatural soil environment in relation to a chemical weathering model. Water,Air, and Soil Pollution 38, 387-408.

92

SWAIN L.A. 1973. Chemical quality of ground water on Hawaii. United StatesGeological Survey and Department of Land and Natural Resources Report

R48, State of Hawaii, Honolulu.SWOBODA-COLBERG N.G. & DREVER J.I. 1993. Mineral dissolution rates in plot-

scale field and laboratory experiments. Chemical Geology 105, 51-69.SYLVESTER J.J. 1889. On the reduction of a bilinear quantic of the nth order to the

form of a sum of n products by a double orthogonal substitution. Messenger ofMathematics 19, 42-46.

SYMADER W. & THOMAS W. 1978. Interpretation of average heavy metal pollutionin flowing waters and sediment by means of hierarchical grouping analysisusing two different error indices. Catena 5, 131-144.

SZAVA-KOVATS R.C. 2000. Comment on “Multivariate and principal componentstatistical analysis of contamination in urban and agricultural soils from NorthJordan”. Environmental Geology 39 (11), 1309-1310.

SZIKSZAY M., TEISSEDRE J.-M., BARNER U. & MATSUI E. 1981. Geochemical andisotopic characteristics of spring and groundwater in the State of São Paulo,Brazil. Journal of Hydrology 54, 23-32.

TAKASAKI K.J. & VALENCIANO S. 1969. Water in the Kahuku area, Oahu, Hawaii.United States Geological Survey Water-Supply Paper 1874, pp. 59.

TARDY Y. 1971. Characterisation of principal weathering types by the geochemistryof waters from some European and African crystalline massifs. ChemicalGeology 7, 252-271.

TAYLOR A.S., LASAGA A.C. & BLUM J.D. 1999. Effect of lithology on silicateweathering rates. In Ármannsson H. ed. Geochemistry of the Earth’s Surface,pp. 127-128. A.A.Balkema, Rotterdam.

THORSTENSON D.C., WEEKS E.P., HAAS H. & FISHER D.W. 1983. Distribution ofgaseous 12CO2,

13CO2 and 14CO2 in the subsoil unsaturated zone of the westernGreat Plains of the U.S. Radiocarbon 25 (2), 315-346.

THURMAN E.M. 1985. Organic Geochemistry of Natural Waters. Martinus Nijhoff /Dr W. Junk Publishers, Dordrecht, The Netherlands, pp. 497.

THURSTONE L.L. 1931. Multiple factor analysis. Psychological Review 38, 406-427.THURSTONE L.L. 1935. The Vectors of the Mind. University of Chicago Press,

Chicago, pp. 266.THURSTONE L.L. 1947. Multiple-factor Analysis: A Development and Expansion of

‘The Vectors of the Mind’. University of Chicago Press, Chicago, pp. 535.TIMMS B.V. 1976. Morphology of Lakes Barrine, Eacham and Euramoo, Atherton

Tableland, North Queensland. Proceedings of the Royal Society of Queensland87, 81-84.

TÓTH J. 1984. The role of regional gravity flow in the chemical and thermalevolution of ground water . In Hitchon B. and Wallick E.I. eds. Proceedingsof the First Canadian / American Conference on Hydrogeology – PracticalApplications of Ground Water Geochemistry, pp. 3-39. National Water WellAssociation, Worthington, Ohio.

TÓTH J. 1999. Groundwater as a geologic agent: an overview of the causes,processes, and manifestations. Hydrogeology Journal 7 (1), 1-14.

TRUESDELL A.H. & JONES B.F. 1974. WATEQ – A computer program forcalculating chemical equilibria of natural waters. Journal of Research, UnitedStates Geological Survey 2 (2), 233-274.

TSCHERNICH R.W. 1992. Zeolites of the World. Geoscience Pres Inc., Phoenix, pp.563.

93

TUCKER L.R., KOOPMAN R.F. & LINN R.L. 1969. Evaluation of factor analyticresearch procedures by means of simulated correlation matrices.Psychometrika 34, 421-459.

TUREKIAN K.K. & WEDEPOHL K.H. 1961. Distribution of the elements in somemajor units of the Earth’s crust. Geological Society of America Bulletin 72,175-192.

TYRON R.C. & BAILEY R.C. 1970. Cluster Analysis. McGraw-Hill, New York, pp.347.

UHL V.W. 1979. Occurrence of groundwater in the Satpura Hills region of centralIndia. Journal of Hydrology 41, 123-141.

UHL V.W. & JOSHI V.G. 1986. Results of pumping tests in the Deccan Trap Basaltsof central India. Journal of Hydrology 86, 147-168.

UMAR A., UMAR R. & AHMAD M.S. 2001. Hydrogeological and hydrochemicalframework of regional aquifer system in Kali-Ganga sub-basin, India.Environmental Geology 40 (4-5), 602-611

USUNOFF E.J. & GUZMÁN-GUZMÁN A. 1989. Multivariate analysis inhydrochemistry: an example of the use of factor and correspondence analyses.Ground Water 27 (1), 27-34.

VAN TONDER G.J. & HODGSON F.D.I. 1986. Interpretation of hydrogeochemicalfacies by multivariate statistical methods. Water South Africa 12 (1), 1-6.

VEEGER A.I. 1996. Using hydrogeochemical methods to evaluate complexquaternary subsurface stratigraphy Block Island, Rhode Island, USA.Hydrogeology Journal 4 (4), 69-82.

VELBEL M.A. 1985. Geochemical mass balances and weathering rates in forestedwatersheds of the southern Blue Ridge. American Journal of Science 285, 904-930.

VELBEL M.A. 1986. The mathematical basis for determining rates of geochemicaland geomorphic processes in small forested watersheds by mass balance:examples and implications. In Colman S.M. and Delthier D.P. eds. Rates ofChemical Weathering of Rocks and Minerals, pp. 439-451. Academic Press,Orlando, Florida.

VELBEL M.A. 1990. Influence of temperature and mineral surface characteristics onfeldspar weathering rates in natural and artificial systems: a firstapproximation. Water Resources Research 26 (12), 3049-3053.

VELBEL M.C. 1993. Temperature dependence of silicate weathering in nature: howstrong a feedback on long-term accumulation of atmospheric CO2 and globalgreenhouse warming. Geology 21, 1059-1062.

VELICER W.F. 1976. The relation between factor score estimates, image scores, andprincipal component scores. Educational and Psychological Measurement 36,149-159.

VIJAYACHANDRAN P.K. & HARTER R.D. 1975. Evaluation of phosphorus adsorptionby a cross section of soil types. Soil Science 119, 119-126.

VILLAGRA M.J., GOMEZ G., ROMERO F. & CRUZ-SANJULIAN J. 1990. Hydrochemicalapplications of the analysis of repeated measurements. Water South Africa 16

(2), 109-114.VINOGRADOV A.P. 1962. Average contents of chemical elements in the principal

types of igneous rocks of the Earth’s crust. Geochemistry 1962 (7), 641-664.VISHER F.N. & MINK J.F. 1964. Ground-water resources in southern Oahu, Hawaii.

United States Geological Survey Water-Supply Paper 1778, pp. 133.

94

VISTELIUS A.B. 1960. The skew frequency distributions and the fundamental law ofthe geochemical processes. Journal of Geology 68, 1-22.

WABER N. & NORSTROM D.K. 1992. Geochemical modeling of granitic groundwaters at the Stripa site (Sweden) using a mass balance approach. In KharakaY.K. and Maest A.S. eds. Water – Rock Interaction WRI-7, pp. 243-246.A.A.Balkema, Rotterdam.

WALLICK E.I. & TÓTH J. 1976. Methods of regional groundwater flow analysis withsuggestions for the use of environmental isotopes. In Interpretation ofEnvironmental Isotope and Hydrochemical Data in Groundwater Hydrology,pp. 37-64. International Atomic Energy Association, Vienna.

WALLIS J.R. 1965. Multivariate statistical methods in hydrology – a comparisonusing data of known functional relationship. Water Resources Research 1 (4),447-461.

WALLIS J.R. 1968. Factor analysis in hydrology – an agnostic view. WaterResources Research 4 (3), 521-527.

WALLIS P.M., HYNES H.B.N. & TERLANG S.A. 1981. The importance ofgroundwater in the transportation of allochthonous dissolved organic matter tothe streams draining a small mountain basin. Hydrobiologia 79, 77-90.

WELLMAN P. & MCDOUGALL I. 1974. Cainozoic igneous activity in easternAustralia. Tectonophysics 23, 49-65.

WHITE A.F. 1983. Surface chemistry and dissolution kinetics of glassy rocks at25 °C. Geochimica et Cosmochimica Acta 47, 805-816.

WHITE A.F. & CLAASSEN H.C. 1979. Dissolution kinetics of silicate rocks –application to solute modeling. In Jenne E.A. ed. Chemical Modeling inAqueous Systems: Speciation, Sorption, Solubility and Kinetics, pp. 447-473.American Chemical Society Symposium Series 93. American ChemicalSociety, Washington, D.C.

WHITE A.F., CLAASSEN H.C. & BENSON L.V. 1980. The effect of dissolution ofvolcanic glass on the water chemistry in a tuffaceous aquifer, Rainier Mesa,Nevada. United States Geological Survey Water-Supply Paper 1535-Q. UnitedStates Government Printing Office, Washington, D.C., pp. 34.

WHITE A.F. & BLUM A.E. 1995. Effects of climate on chemical weathering rates inwatersheds. Geochimica et Cosmochimica Acta 59, 1729-1747.

WHITE A.F., BULLEN T.D., VIVIT D.V., SCHULZ M.S. & BLUM A.E. 1999. Invitedlecture: The effect of climate on chemical weathering of silicate rocks. InÁrmannsson H. ed. Geochemistry of the Earth’s Surface, pp. 79-82.A.A.Balkema, Rotterdam.

WILLIAMS R.E. 1982. Statistical identification of hydraulic connections between thesurface of a mountain and internal mineralised sources. Ground Water 20 (4),466-478.

WITKAMP M. & FRANK M.L. 1969. Evolution of CO2 from litter, humus, and subsoilof a pine stand. Pedobiologia 9, 358-365.

WOLLAST R. 1967. Kinetics of the alteration of K-feldspar in buffered solutions atlow temperature. Geochimica et Cosmochimica Acta 31, 635-648.

WONG S.T. 1963. A multivariate statistical model for predicting mean annual floodin New England. Annals of the Association of American Geographers 53 (3),298-311.

WOOD W.W. & PETRAITIS M.J. 1984. Origin and distribution of carbon dioxide inthe unsaturated zone of the Southern High Plains of Texas. Water ResourcesResearch 20 (9), 1193-1208.

95

WOOD W.W. & LOW W.H. 1986. Aqueous geochemistry and diagenesis in theeastern Snake River Plain aquifer system, Idaho. Geological Society ofAmerica Bulletin 97, 1456-1466.

XUE Y., WU J., LIU P. & WANG J. 1993. Sea-water intrusion in the coastal area ofLaizhou Bay, China. I. Distribution of sea-water intrusion and itshydrochemical characteristics. Ground Water 31 (4), 532-537.

YAALON D.H., NATHAN Y., KOYUMDJISKY H. & DAN J. 1966. Weathering andcatenary differentiation of clay minerals in soils on various parent materials inIsrael. In Heller L. and Weiss A. eds. Proceedings of the International ClayConference, 1, pp. 187-198. Israel Program for Scientific Translations,Jerusalem.

ZAPOROZEC A. 1972. Graphical interpretation of water-quality data. Ground Water10 (2), 32-43.

ZIELINSKI R.A., OTTON J.K., WANTY R.B. & PIERSON C.T. 1987. The geochemistryof water near a surficial organic-rich uranium deposit, north-easternWashington State, U.S.A. Chemical Geology 62, 263-289.

ZWICK W.R. & VELICER W.F. 1982. Factors influencing four rules for determiningthe number of components to retain. Multivariate Behavioral Research 17,253-269.

ZWICK W.R. & VELICER W.F. 1986. Comparison of five rules for determining thenumber of components to retain. Psychological Bulletin 99, 432-442.

96

PAPER 1A

CHEMICAL CHARACTER OF GROUNDWATER IN A BASALT AQUIFER,

NORTH QUEENSLAND, AUSTRALIA

Katrina L. Locsey and Malcolm E. Cox



In Sililo O. et al. eds. Groundwater: Past achievements and future challenges.Proceedings of the XXXth International Congress of the International Association of

Hydrogeologists, Cape Town, 26 November – 1 December 2000, pp. 555-560.A.A.Balkema, Rotterdam.

97

Statement of original authorship

Locsey K.L. (candidate)

Undertook fieldwork and analysed samples, carried out compilation and analysis ofdata, interpreted and presented results, wrote manuscript.

Cox M.E. (principal supervisor)

Supervised work and reviewed manuscript.

98

Abstract

Due to the increasing demands on the groundwater resources on the AthertonTablelands, North Queensland over the last 15 years, a number of investigations arebeing undertaken to determine the extent and sustainability of the resource. Thegroundwater supplies are predominantly sourced from fresh and weathered basalt,varying from highly vesicular to massive in character, with fracture zones alsopresent. The chemical character of groundwater contained within the basalt can beused to define trends in groundwater movement, based on its chemical evolution.The groundwater chemically evolves from water with no dominant ions to slightlyHCO3

--rich water in areas where direct rainfall infiltration predominates, to a Ca-Mg,HCO3 type water along flow gradient and at discharge zones. Trends in major ionconcentrations and relationships between dissolved constituents indicate thatreactions with clinopyroxene, plagioclase feldspars and olivine are the principalcontrols on the chemical character of these groundwaters.

Key words: Groundwater · Basalt · Chemical character

halla

This article is not available online. Please consult the hardcopy thesis available from the QUT Library

110

PAPER 1B

A HYDROCHEMICAL CLASSIFICATION SCHEME FOR A BASALTIC

AQUIFER AS AN INDICATOR OF GROUNDWATER FLOW POSITION




In Seiler K.P. and. Wohnlich S. eds. New approaches to characterising groundwaterflow. Proceedings of the XXXIst International Congress of the International

Association of Hydrogeologists, Munich, 10-14 September 2001, pp 1217-1221.A.A.Balkema, Swets & Zeitlinger B.V., Lisse.

111






112

Abstract

The hydrochemical relationships between the major ions in the groundwaters of theAtherton Tablelands, North Queensland, Australia, have been used to define therelative positions of samples along inferred flow paths. The five key indicators ofthe chemical evolution of these basalt-hosted groundwaters (i.e. Mg2+/Cl-, HCO3

- +CO3

2-/Sum Cations, HCO3-/Cl-, H4SiO4 concentration and the percentage of HCO3

- +CO3

2- of major anions) have been used in a rating-based classification scheme toidentify “upper-”, “mid-” and “lower-flow” position groundwaters. The results ofthis hydrochemical classification correspond well with water level response times torecharge events. The classification scheme is a useful indicator of groundwater flowdirections for the Atherton Tablelands basalt aquifer, and may also enable theidentification of areas of preferred recharge.

Key words: Hydrochemical relationships · Chemical evolution · Classificationscheme · Groundwater flow paths

halla


123

PAPER 2

STATISTICAL AND HYDROCHEMICAL METHODS TO COMPARE

BASALT- AND BASEMENT ROCK-HOSTED GROUNDWATERS:

ATHERTON TABLELANDS, NORTH-EASTERN AUSTRALIA




Environmental Geology 43 (6), pp. 698-713

Published online 10th October 2002Environmental Geology© Springer-Verlag 2002

DOI 10.1007/s00254-002-0667-z

124






125

Abstract

Multivariate analysis of physico-chemical and chemical data has enableddifferentiation among groundwaters sourced from different lithological formations inthe Atherton Tablelands region of north-eastern Australia. The main water resourceis stored in basalt, although basement rocks such as granite and metamorphics alsocontain variable amounts of water. Groundwater in the basalt is mostly Mg-Ca-Na,HCO3 type, with electrical conductivities less than 300 μS/cm and pH values from6.5 to 8.5. Some of the other groundwater is quite similar, making the identificationof hydrochemical facies difficult.

Groundwater samples were grouped based on the results of a principal componentfactor analysis of the major dissolved constituents H4SiO4, Na+, Ca2+, Mg2+ andHCO3

-, as well as pH and electrical conductivity. Based on this differentiation it waspossible to identify the likely host rocks of groundwaters from unidentifiedlithological units, define the basalt thickness and provide a better understanding ofthe groundwater resource.

Principal component factor analysis has also been useful in identifying the likelyhydrochemical processes controlling the composition of these groundwaters,including the production of weak acids in the soil layers, silicate mineral weathering,ion-exchange reactions, evapotranspiration and the leaching of ions from organicmatter.

Key words: Atherton Tablelands · Groundwater · Hydrochemistry · Principalcomponent factor analysis · North Queensland

halla


157

PAPER 3

WATER – ROCK INTERACTIONS: AN INVESTIGATION OF THE

RELATIONSHIPS BETWEEN MINERALOGY AND GROUNDWATER

COMPOSITION AND FLOW IN A SUBTROPICAL BASALT AQUIFER

Katrina L. Locsey, Micaela Preda and Malcolm E. Cox



Manuscript prepared for Hydrogeology Journal

158



Undertook fieldwork and analysed aqueous samples, carried out compilation andanalysis of data, interpreted and presented results, wrote manuscript.

Preda M. (associate supervisor)

Undertook XRD analyses, identified and quantified mineral phases, and reviewedmanuscript.



159

Abstract

The composition of the basalt groundwaters of the Atherton Tablelands region areconsidered, to elucidate possible mechanisms for the evolution of these very lowsalinity, silica- and bicarbonate-rich groundwaters. It is proposed thataluminosilicate mineral weathering is the major contributing process to the overallcomposition of the basalt groundwaters.

The groundwaters approach equilibrium with respect to the primary minerals withincreasing pH, and are mostly in equilibrium with the major secondary minerals(kaolinite and smectite), and other secondary phases such as goethite, hematite andgibbsite, which are common accessory minerals in the Atherton basalts.

The mineralogy of the basalt rocks, which has been examined using X-ray diffractionand whole rock geochemistry methods, supports the proposed model for thehydrogeochemical evolution of these groundwaters. The variations in themineralogical content of these basalts also provide insights into the controls ongroundwater storage and movement in this aquifer system. The fresh and weatheredvesicular basalts are considered to be important in terms of zones of groundwateroccurrence, while the fractures in the massive basalt are important pathways forgroundwater movement.

Key words: Basalt aquifer · Aluminosilicate mineral weathering · Mass balance

halla


GENERAL CONCLUSIONS

197

GENERAL CONCLUSIONS

The aims of this research project were to examine the effects of hydrogeochemicalprocesses, in particular, silicate mineral weathering processes, on the composition ofvery low salinity groundwaters in a basalt aquifer system in a subtropical climate. Afocus of this study was to use the hydrochemical observations to better define thegroundwater hydrology, and thereby provide an additional tool for resourcemanagement. Several elements of the system (basalt and basement rocks,groundwaters and steam waters) were investigated using a number of chemical,physical and statistical analytical methods, as well as hydrogeochemical modelling.

The mineralogy of the basaltic rocks of the Atherton Tablelands has been examinedusing X-ray diffraction and whole rock geochemistry techniques. The results showthat there is considerable variation in the relative proportions of the primary andsecondary minerals present, and that the sequence of basalt rocks comprises a veryheterogeneous package of both fresh and weathered material. Vesicular basalt, thatmay be fresh to highly weathered, was identified as important in terms of zones ofgroundwater occurrence, while both fractured and vesicular basalt provide pathwaysfor groundwater movement. Zones between lava flows are also importanthydrologically.

The mineralogy of the basalt rocks ultimately determines the occurrence of chemicalelements in the groundwaters and the speciation of the weathering products. Theconcentrations of the major dissolved constituents in the Atherton Tablelands basaltgroundwaters are influenced by silicate weathering reactions such as the dissociationof olivine, the weathering of pyroxenes and feldspars to kaolinite and smectites, andthe formation of other secondary minerals such as amorphous or crystalline silica,goethite, gibbsite and hematite. Saturation of the groundwaters with respect tocarbonate minerals and zeolites leads to the precipitation of these minerals in vesiclesand along fracture planes in the basalt. The relationships between the stoichiometryof these weathering reactions and the molar ratios of dissolved constituents in thegroundwaters support these proposals. The hypothesis that silicate mineralweathering processes are the predominant influence on the groundwater compositionis well supported by the stability of the basalt groundwater with respect to kaoliniteand smectite clays, as shown on aluminosilicate mineral stability diagrams,saturation indices with respect to both primary and secondary minerals, and inversehydrogeochemical modelling.

It is evident that the effects of mineral weathering processes can be observed on thecomposition of these young (Cook et al. 2001) and very low salinity basaltgroundwaters, which receive substantial recharge and undergo extensive flushingannually. These observations were used to relate the compositions of thegroundwaters to positions along flow lines (i.e. relative residence times wereidentified), and to identify likely recharge and discharge areas. The groundwaterflow patterns defined by the hydrogeochemical interpretations correspond well withthe spatial trends in water level fluctuations, and response to recharge events inparticular.

Other processes that influence the groundwater composition include the availabilityof CO2, oxidation and ion-exchange reactions, and uptake of ions from, anddecomposition of, organic matter. Due to extensive soil development and rapid plant

198

growth in the subtropical monsoonal climate of the study area, substantial CO2, andhence hydrogen ions, are available to circulating water; the extent to which silicateweathering occurs is related to the availability of H+ ions. While some evaporationof recharging waters does occur, the effects of evaporative enrichment on thecomposition of the Atherton basalt groundwaters is limited in comparison to theeffects of silicate mineral weathering processes.

Groundwater baseflow to streams and discharge to topographic lows in the AthertonTablelands region is indicated by the relationships between the major cations andanions in the stream waters, particularly the ratios of Mg2+/Cl- and HCO3

-/Cl-, whichcan be used as indicators of silicate mineral weathering processes. Fracture zonesare likely to be preferred pathways of groundwater movement, enabling discharge tostreams. Longitudinal radon profiles measured at low flow conditions along theBarron and North Johnstone Rivers (Cook et al. 2001) support this finding.Evidence of a groundwater baseflow contribution to streams, showing that thesurface water bodies are an integral part of the groundwater flow system, is animportant finding in terms of management of the water resources contained withinthe groundwater and surface water systems.

Estimates for recharge to the basalt aquifer system of the Atherton Tablelands, basedon a chloride mass balance, range from 310 mm/yr in the north-western part of thestudy area (north of Atherton) to 600 mm/yr in the wetter southern and eastern partsof the study area. Estimating recharge to a groundwater system based on a chloridemass balance approach has limitations, and estimates should be treated with caution,particularly in areas where rainfall chloride concentrations are highly variable (Rosenet al. 1999), and where the groundwaters have very low chloride concentrations (Roe1995), as is the case for the Atherton Tablelands. The recharge estimate for thenorth-western part of the study area is supported, however, by an independentrecharge estimate (based on a soil moisture model and groundwater usage) by Pearceand Durick (2002). The high recharge estimates for the southern and eastern parts ofthe Atherton Tablelands are comparable to estimated recharge to aquifer systems inother high rainfall regions (e.g. Pulawski & Øbro 1976; Wright 1984; Uma &Egboka 1988).

The multivariate statistical approaches used in this study to assess the hydrochemicaldata from the Atherton Tablelands region, and the application of the results are asignificant contribution to this field of work. Principal component analysis of themajor constituents, pH and electrical conductivities of these very low salinitygroundwaters from a subtropical environment, supported by other methods, haveshown that:

groundwaters from different lithological formations, that is, basalt andbasement rocks (comprising granite and metamorphosed sediments), arehydrochemically distinguishable,

the likely sources of groundwater obtained from unidentified lithologicalunits can be defined,

the underlying geochemical processes controlling groundwater composition,particularly in the basalt aquifer, can be inferred, and

199

the results can be applied to indicate relative groundwater residence and flowdirections, and to map the thickness of the basalt aquifer, which thusimproves the understanding of the potential extent of the groundwaterresource.

The interpretative methods applied to this research project relied predominantly onmajor ion chemistry and field measurements, in addition to mineralogical data.Extensive hydrogeochemical information has been gained from these data, and thisresearch demonstrates the potential for basic hydrochemical data to aid in theunderstanding of the controls on groundwater composition, and the application ofthis knowledge in terms of groundwater storage and movement.

References

COOK P.G., HERCZEG A.L. & MCEWAN K.L. 2001. Groundwater recharge andstream baseflow, Atherton Tablelands, Queensland. CSIRO Land and WaterTechnical Report 08/01, pp. 84.


PULAWSKI B. & ØBRO H. 1976. Groundwater study of a volcanic area near Bandung,Java, Indonesia. Journal of Hydrology 28, 53-72.

ROE R.B. 1995. Release of chloride from basalt: Implications for the chloride mass-balance approach to estimating groundwater recharge. M.S. thesis,Washington State University, Washington (unpubl.), pp. 90.

ROSEN M.R., BRIGHT J., CARRAN P., STEWART M.K. & REEVES R. 1999. Estimatingrainfall recharge and soil water residence times in Pukekohe, New Zealand, bycombining geophysical, chemical, and isotopic methods. Ground Water 37 (6),836-844.

UMA K.O. & EGBOKA B.C.E. 1988. Groundwater recharge from three cheap andindependent methods in the small watersheds of the rainforest belt of Nigeria.In Simmers I. ed. Estimation of Natural Groundwater Recharge, pp. 435-447.D.Reidel Publishing Company, Dordrecht, Holland.

WRIGHT E.P. 1984. Drilling for groundwater in the Pacific region. In WaterResources of Small Islands, Technical Proceedings (Part 2) on the RegionalWorkshop on Water Resources of Small Islands, pp. 525-529. CommonwealthScience Council, London.

APPENDICES

200

APPENDIX I

4th International Conference on Environmental Chemistry and Geochemistry in theTropics (GEOTROP 2001) 7 - 11 May 2001, Townsville.

Climatic, mineralogical and weathering controls on the geochemical character

of groundwater – the Atherton Tablelands basalt aquifer, North Queensland.

KATRINA LOCSEY


Queensland University of TechnologyAbstract

Due to the increasing demands on the groundwater resources on the AthertonTablelands, North Queensland over the last 15 years, a number of investigations arebeing undertaken to determine the extent and sustainability of the resource. Thegroundwater supplies are predominantly sourced from fresh and weathered basalt,varying from highly vesicular to massive in character, with fracture zones alsopresent. The chemical character of groundwater contained within the basalt can beused to define trends in groundwater movement, based on its chemical evolution.

Recharge by direct rainfall infiltration occurs throughout the Tablelands. Rechargerates may be expected to reflect the rainfall distribution pattern, with rates decreasingfrom the south-east to the north-west. Recharge has been estimated using a chloridemass balance, assuming that the groundwater chloride concentration ispredominantly due to evaporative enrichment, with some contribution from rockweathering.

The groundwater chemically evolves from water with no dominant ions to slightlyHCO3

--rich water in areas where direct rainfall infiltration predominates, to a Ca-Mg,HCO3 type water along flow gradient and at discharge zones. The increasingconcentrations of HCO3

-, H4SiO4 and cations along flow gradient, and therelationship between cations (e.g. Mg2+) and HCO3

-, indicate that groundwaterchemical composition is influenced by basalt mineralogy. The predominantmineralogy of the Atherton basalts is clinopyroxene, plagioclase feldspars andolivine. Kaolinite and montmorillonite are the dominant clay minerals; minorgibbsite is also present. Where soil development and plant growth are rapid, as is thecase in the subtropical, monsoonal climate of the Atherton Tablelands, substantialCO2, and, hence, hydrogen ions are available to circulating water. The extent towhich reactions with the minerals occurs, is related to the availability of H+. In thesouth-east of the Tablelands, where annual rainfall exceeds 2500 mm and intenseleaching conditions persist, weathering of albite to gibbsite, influences groundwaterchemical composition.

Although these groundwaters have low total dissolved solids, trends in major ionconcentrations and ratios of Na+, Ca2+, Mg2+, HCO3

- and H4SiO4, can be usefulindicators of evolution of the chemical character of the groundwater. This aspect canbe used to determine the nature of groundwater occurrence and movement.

Climatic, mineralogical and weathering controls on

the geochemical character of groundwater

Ms Katrina Locsey and Dr Malcolm CoxSchool of Natural Resource Sciences


GEOTROP 2001

4th International Conference on Environmental

Chemistry and Geochemistry in the TropicsTownsville, 7 - 11 May, 2001

Extent of the Basalt Aquifer and Locations of

Groundwater Bores on the Atherton Tablelands

0.0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

4.0

0.0 0.2 0.4 0.6 0.8 1.0Ca2+ (mmol/L)

HC

O3

-(m

mo

l/L

)

Augite-Kaolinite (1:3.7)

The hydrochemical relationships between the major ions in the groundwaters of

the Atherton Tablelands have been used to define the relative positions of samples

along inferred flow paths. Interpretations are based on more than 900 sets of

groundwater analyses. The five key indicators of the chemical evolution of these 2+ - - 2- - -

basalt-hosted groundwaters (i.e. Mg /Cl , HCO + CO /Sum Cations, HCO /Cl ,3 3 3

- 2-H SiO concentration and the percentage of HCO + CO of major anions) have 4 4 3 3

been used in a rating-based classification scheme to identify “upper-”, “mid-” and

“lower-flow” position groundwaters. The results of this hydrochemical classification

correspond well with water level response times to recharge events. The

classification scheme is a useful indicator of groundwater flow directions for the

Atherton Tablelands basalt aquifer, and may also enable the identification of

areas of preferred recharge.

The rate of evaporative enrichment of recharging groundwaters increases from SE to NW, from

an evaporation factor of 2.5 around Malanda to 3.6 around Atherton.

Interactions between groundwater and the basaltic rocks are believed to be the main

processes responsible for the chemical characteristics of the Atherton groundwaters. The

composition of these groundwaters is primarily attributed to the acidic weathering of primary

aluminosilicate minerals to kaolinite, and other clays and oxides (Locsey and Cox, 2000). The

predominant mineralogy of the Atherton basalts is clinopyroxene (augite), plagioclase feldspars

(probably albite and anorthite) and olivine. Groundwater composition is influenced by the

reactions with these minerals. The dissolution of these minerals is shown with kaolinite and

montmorillonite as the end products (the weathering of albite to montmorillonite assumes the 2+

presence of Mg leached from pyroxenes).

Augite - Kaolinite2+ 2+

[CaMg Al Si ]O + 3.4CO +4.5H O = 0.3Al Si O (OH) + Ca + 0.7Mg + 1.1H SiO +0.7 0.6 1.7 6 2 2 2 2 5 4 4 4

-3.4HCO3

Albite - Kaolinite+ -

2NaAlSi O + 2CO + 11H O = Al Si O (OH) + 2Na + 4H SiO + 2HCO3 8 2 2 2 2 5 4 4 4 3

Anorthite - Kaolinite2+ -

CaAl Si O + 2CO + 3H O = Al Si O (OH) + Ca + 2HCO2 2 8 2 2 2 2 5 4 3

Albite - Montmorillonite2+ +

3NaAlSi O + Mg + 4H O = 2Na Al Mg Si O (OH) + 2Na + H SiO3 8 2 0.5 1.5 0.5 4 10 2 4 4

0.0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

4.0

0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5 4.0Ca2+ + Mg2+ + Na+ (mmol/L)

HC

O3

-(m

mo

l/L

)

(1:1.25)Augite-Kaolinite

Albite-Kaolinite

Anorthite-Kaolinite

Albite-Montmorillonite

(20%)

(80%)

Most samples plot above the augite to kaolinite 2+

weathering reaction line (that is, release of Ca-

and HCO on a 1:3.7 moles basis). Excess of 3

-HCO may be due to olivine dissociation, and 3

weathering of albite or anorthite to kaolinite, -

which also release HCO to solution.3

2+ 2+ +If the release of the ions Ca , Mg , Na and

-HCO is considered in terms of the weathering 3

reactions above, with the weathering of augite,

albite and anorthite accounting for 80% of the

ions released to solution, and the weathering of

albite to montmorillonite accounting for the

remaining 20% of ions, then the ratio of cations to -

HCO would be 1:1.25. This corresponds well with 3

the data for the Atherton groundwaters, indicating

that some combination of these reactions is likely

to be controlling the groundwater composition.

Relationships between the five main chemical indicators 2+ - - 2-

of groundwater evolution (Mg /Cl , HCO + CO /Sum3 3

- -Cations, HCO /Cl , H SiO concentration and the 3 4 4

- 2-percentage of HCO + CO of major anions)3 3

0.0

0.5

1.0

1.5

2.0

0 1 2 3 4 5 6Mg2+/Cl- (meq/L)

(HC

O3

-+

CO

32-

)/S

um

Cat

ion

s

(mm

ol/

L)

0

2

4

6

8

10

12

14

0 1 2 3 4 5 6Mg2+/Cl- (meq/L)

HC

O3

-/

Cl-

(meq

/L)

0

10

20

30

40

50

60

70

80

90

100

0 1 2 3 4 5 6Mg2+/Cl- (meq/L)

HC

O3

-+

CO

32-

of

maj

or

anio

ns

0.1

1.0

10.0

0 1 2 3 4 5 6Mg2+/Cl- (meq/L)

H4S

iO4

(mm

ol/

L)

Hydrochemical

Classification

Mg2+

/Cl-

(meq/L)Rating

<= 0.5 0.25> 0.5 and <= 1 0.75> 1 and <= 1.5 1.25> 1.5 and <= 2 1.75> 2 and <= 2.5 2.25> 2.5 and <= 3 2.75> 3 3

HCO3-+ CO3

2-/Sum Cations

(mmol/L)Rating

<= 0.5 0.5> 0.5 and <= 1 1>1 and <= 1.3 2> 1.3 3

HCO3-/Cl

-

(meq/L)Rating

<= 1 0.5> 1 and <= 3 1> 3 and <= 4 2> 4 and <= 5 2.5> 5 3

H4SiO4

(mmol/L)Rating

<= 0.5 0.5> 0.5 amd <= 1 1> 1 No Rating

HCO3-+ CO3

2-of major anions

(%)Rating

<= 60 0.5> 60 and <= 80 1> 80 and <= 87 2> 87 – 100 3

Mg2+

/Cl-

ratingHCO3

-+CO3

2-

/Sum Cationsrating

HCO3-/Cl

-

ratingH4SiO4

ratingHCO3

-+CO3

2-of

anions rating

MethodA weight

0.25 0.25 0.25 0.125 0.125

MethodB weight

0.28 0.28 0.28 - 0.16

Method A for groundwater samples with a H SiO concentration <= 1 4 4

mmol/L. Method B for groundwater samples with a H SiO4 4

concentration > 1 mmol/L, or if no H SiO data available.4 4

The “Class” equals the sum of the

five weighted ratings within a range

of 0 - 3, with the lower end of this

range representing an “upper-flow”

position and the upper end of this

range representing a “lower-flow”

position, that is, a longer residence.

C l a s s i f i c a t i o n s y s t e m d e f i n e d

b y w e i g h t e d k e y indicators

“Class” Legend

LakeTinaroo

############

#######

########

#####################

#####

11000118

1100006845431

11000066

45783

11000129

11000064

Bar

ron

Riv

er

0 2 4 Kilometers

Atherton

Groundwater boresshowninhydrographs#

X-Section location A-Bdowngroundwater flowgradient

N

A B

The hydrochemical classification corresponds

well with the groundwater contours and flow

lines for the Atherton region

Cross-section A-B, from an upper- to mid- to lower-flow

position, defined by the hydrochemical classification and 2+ - - -

groundwater levels. A = Mg /Cl (meq/L), B = HCO /Cl3

- 2-(meq/L), C = HCO + CO /Sum Cations (mmol/L), D = 3 3

- 2-H SiO (mmol/L) and E = HCO + CO of major anions (%).4 4 3 3

Water level response lags give support to the

hydrochemical classification system. A

recharge water level response lag of three

months between groundwaters classified as

representing an upper-flow position (bores

45783 and 11000066) and groundwaters

classified as representing a mid-flow position

(bores 11000064 and 11000068) is evident.

Interpolated grid using an inverse distance

weighted method, with increasing “Class”

from 0 - 3 shown in blues to reds.

Reference: Locsey, K.L. & M.E. Cox 2000. Chemical character of groundwater in a basalt aquifer, North Queensland,

Australia. In O.Sililo et al. (eds), Groundwater: Past achievements and future challenges; Proc. XXXth International

Congress of the International Association of Hydrogeologists, Cape Town, 26 November - 1 December 2000.

Rotterdam: Balkema.

This work was conducted as part of a research program funded and supported by the Queensland Department

of Natural Resources and the Land and Water Resources Research and Development Corporation.

Groundwater Monitoring Bore

600

650

700

750

800

1 2 3

(met

res)

Surface

SWL

Screened

Interval

45431 11000068 11000118

Class = 1.49

A = 1.7

B = 2.7

C = 1.0

D = 1.7

E = 78%

Class = 1.71

A = 1.64

B = 2.9

C = 1.1

D = 2.1

E = 82%

Class = 2.96

A = 5.94

B = 10.6

C = 1.4

D = 1.6

E = 94%

Groundwater flow direction

600

650

700

750

800

1 2 3

(met

res)

Surface

SWL

Screened

Interval

45431 11000068 11000118

Class = 1.49

A = 1.7

B = 2.7

C = 1.0

D = 1.7

E = 78%

Class = 1.71

A = 1.64

B = 2.9

C = 1.1

D = 2.1

E = 82%

Class = 2.96

A = 5.94

B = 10.6

C = 1.4

D = 1.6

E = 94%

Groundwater flow direction

-50

-40

-30

-20

-10

0

Feb-

89

May-

89

Aug-

89

Nov-

89

Feb-

90

May-

90

Aug-

90

Nov-

90

Feb-

91

May-

91

Sta

nd

ing

wa

ter

lev

el

(m)

45783

11000066

11000064

11000068

Class < 0.79

Class 0.79 - 1.38

Class 1.38 - 2

Class 2 - 2.58

Class 2.58 - 3

202

APPENDIX II

Extracts from Locsey and Cox (unpubl.), a report submitted to QDNR&M and

LWRRDC, and additional related work

HYDROGEOCHEMICAL CROSS-SECTIONS: INFERRING RELATIONSHIPS BETWEEN

HYDROCHEMISTRY AND GROUNDWATER MOVEMENT

.

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212

APPENDIX III



GROUNDWATER – STREAM INTERACTION: THE ATHERTON TABLELANDS, NORTH

QUEENSLAND

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218

APPENDIX IV

HYDROCHEMICAL VARIABILITY AS A TOOL FOR DEFINING

GROUNDWATER MOVEMENT IN A BASALT AQUIFER: THE

ATHERTON TABLELANDS, NORTH QUEENSLAND




In Proceedings of the International Association of Hydrogeologists InternationalGroundwater Conference: Balancing the Groundwater Budget, Darwin, 12-17 May

2002.

219




Cox M.E. (supervisor)


220

Abstract

The hydrochemcical processes affecting the groundwater composition in theAtherton Tablelands basalt aquifers were examined to assess the potential for usingthis understanding to identify trends in groundwater movement. The principalobjectives of the hydrochemical investigation of the basalt aquifers were todetermine whether the effects of silicate weathering and relative residence timescould be observed in basaltic groundwaters in a subtropical environment, withsubstantial recharge and flushing annually, and to use the observed hydrochemicaltrends to infer groundwater flow patterns, and to identify areas of preferred rechargeand discharge.

The groundwater is of very low salinity (generally < 250 mg/L total dissolved ions),typical of groundwaters in tropical environments. Characteristics of the basaltaquifers include a slow rate of weathering of silicate minerals and localized recharge.There is however, an observed evolution of the chemical composition of thegroundwaters due to water – rock interaction that can be reconciled with positions ofgroundwaters along flow paths.

The processes of silicate weathering were determined to be the predominantinfluence on groundwater composition in the region, due to reactions with primaryand secondary minerals releasing ions to solution. It is inferred that the weatheringof augite, albite and anorthite to kaolinite, and albite to montmorillonite, are theprincipal silicate weathering reactions involved in the release of the major ions to thegroundwater. Olivine dissociation and the weathering of albite to gibbsite would beexpected to have a lesser influence on the groundwater composition. Saturation ofthe groundwaters with respect to some secondary minerals and subsequentprecipitation has a limiting influence on the concentration of the major ions insolution.

The hydrochemical relationships observed are subtle, but can be used to classify thebasalt-hosted groundwaters in terms of “residence”, to define trends in groundwatermovement and to identify areas of potential preferred recharge and discharge. Thegroundwater flow patterns defined by the hydrochemical classification correspondwell with the spatial trends in water level fluctuations, in particular, response tosummer recharge. The identification of areas of preferred recharge (e.g. fracturezones) may be facilitated by the interpretation of hydrochemical variations in theaquifer, as fresher, recharge waters tend to show a distinctive chemical composition.The most chemically evolved groundwaters are found to discharge from springs atthe edges of the basalt lava fields, and typically have major ion elemental ratios (e.g.Mg2+/Cl- and HCO3

- +CO32-/Sum Cations) eight times those of recharging waters.

Key words: Hydrochemistry · Basalt aquifers · North Queensland, Australia

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240

APPENDIX V

Supportive approaches and applications of work presented in PAPER 2

MULTIVARIATE DATA ANALYSIS OF THE ATHERTON TABLELANDS GROUNDWATERS:APPROACHES

Multivariate analysis of the hydrochemical data was initially applied by undertakingfour separate principal component factor analyses of groundwaters obtained frombasalt, granite and metamorphic rocks, as well as of groundwaters from unknownlithological sources. The variables significantly contributing to the factors for eachlithological group are shown in Table 1. The principal component factor analysisresults for the unknown group are most similar to those of the basalt-hostedgroundwaters. The variables contributing to factor I for these groups are similar; theinclusion of the variables pH and Na+ in factor I of the unknown group should betreated with some caution, as these variables have lower communalities than usualfor the set of factors defined. In addition, the variables Cl-, H4SiO4 and SO4

2- are thesingle significant variables contributing to three of the factors for both groups. Theoverall set of factors for the unknown group most closely resembles that of thebasalt-hosted groundwaters, indicating that the majority of the groundwater samplescomprising the unknown group are likely to the sourced from basalt.

Table 1. A summary of the variable significantly contributing to the factors for eachlithological group.

Factor Basalt Granite Metamorphic Unknown

I HCO3-

Mg2+

ElectricalConductivity

Ca2+

H4SiO4

Na+

K+

HCO3-

pHElectrical

Conductivity

pHCa2+

HCO3-

HCO3-

Ca2+

Electrical ConductivitypH

Mg2+

Na+

II K+

Na+

pH

SO42-


Mg2+

Na+


Cl-

SO42-

Cl-

III H4SiO4 Cl-

Mg2+K+

Mg2+


Cl-

H4SiO4

IV Cl- Ca2+ H4SiO4

Mg2+

SO42-

SO42-

V SO42- K+

This approach shows that water taken from different formations in the AthertonTablelands region are chemically distinguishable, and provides a qualitativeassessment of the likely predominant host rock of the unknown groundwaters. Itdoes not, however, enable the identification of the unknown samples on an individual

241

basis, a procedure necessary for any further application of the results, such as thedefinition of the thickness of the basalt aquifer.

Kendall and Stuart (1966) discuss the problems of differentiating between two ormore populations on the basis of multivariate measurements. The followingquotation from them shows that there are three distinct classes of problem:

Discrimination: We are given the existence of two populations and a sample ofindividuals from each. The problem is to set up a rule, based onmeasurements from these individuals, which will enable us to allotsome new individual to the correct population when we do not knowfrom which of the two it emanates.

Classification: We are given a sample of individuals, or the whole population, andthe problem is to classify them into groups which shall be as distinctas possible.

Dissection: We are given a sample or population and wish to divide it intogroups, whether the border lines of subdivision are natural or not.

In PAPER 2, principal component factor analysis has been used to classify thesamples into groups in the sense of Kendall and Stuart (1966). The unknownsamples were allotted to the groups, addressing the problem of ‘discrimination’ asdefined by Kendall and Stuart (1966). PAPER 2 presents the results of a principalcomponent factor analysis, applied in such a way that the unknown groundwatersamples could be individually defined, and shows how this information can beapplied.

242

THICKNESS OF THE BASALT AQUIFER

Based on the results of the principal component factor analysis used to define thelikely host rocks of groundwaters from unidentified lithological units, presented inPAPER 2, the thickness of the basalt aquifer could be better defined. For thosesamples defined as being basalt-hosted groundwaters, the depths of the screenedintervals or open-holes were noted, and added to the known depth of basalt in thearea (Buck 1999). A spatial interpolation was undertaken using an inverse distanceweighted method (based on 12 nearest neighbours and a power of 2) in the ArcView(v. 3.1) geographic information system. A map of the interpreted basalt thicknesswith a grid cell size of 500 m is shown in Figure 1, colour coded according to depthranges. This map of the basalt thickness in the Atherton Tablelands region improvesthe understanding of the potential extent of the groundwater resource.

Figure 1. Basalt aquifer thickness – an interpolation based on datacompiled by Buck (1999) and additional unknown bores defined as‘basalt’ from a principal component factor analysis of hydrochemicaldata (PAPER 2).

243

GROUNDWATER FLOW DIRECTIONS INFERRED FROM THE PRINCIPAL COMPONENT

FACTOR ANALYSIS

The principal component factor analysis of the basaltic hydrochemistry also enabledthe interpretation of the likely hydrogeochemical processes controlling thecomposition of the groundwaters in the Atherton Tablelands region (PAPER 2). Theprincipal factor (factor I) controlling the groundwater composition of the basalticgroundwater is dominated by strong loadings of Na+, HCO3

-, Mg2+ and Ca2+, as wellas electrical conductivity, and accounts for almost 39 % of the variance in the data.As discussed in PAPER 2 factor I is interpreted to be controlled by silicateweathering processes.

Factor scores may be used as an indication of the degree to which interpretedprocesses control the groundwater composition; they can therefore be used as anindicator of groundwater residence and flow directions. The results of a spatialinterpolation of the scores for factor I using an inverse distance weighted method inArcView (v. 3.1), are shown in Figure 2, coloured from blues (low factor scores) toreds (high factor scores). Inferred groundwater flow directions are also shown.

Figure 1. Grid of Factor I scores (PAPER 2), based on an inversedistance weighted interpolation, and inferred groundwater flowdirections.

%

%

%

%

%

%

Kairi

Tolga

Malanda

Upper

Barron

Walkamin

Atherton

0 2 4 Kilometers

N

North Johnstone

River

Mazlin Creek

Barro

nRive

r

Factor I ScoresLegend

-3.47 - -2.39

-2.39 - -1.8-1.8 - -1.22

-1.22 - -0.64-0.64 - -0.05

-0.05 - 0.530.53 - 1.121.12 - 1.7

1.7 - 2.282.28 - 2.87

2.87 - 3.453.45 - 4.04

4.04 - 4.624.62 - 8.96

LakeTinaroo

Groundwater flow direction (inferred)

%

%

%

%

%

%

Kairi

Tolga

Malanda

Upper

Barron

Walkamin

Atherton

0 2 4 Kilometers

N

North Johnstone

River

Mazlin Creek

Barro

nRive

r

Factor I ScoresLegend

-3.47 - -2.39

-2.39 - -1.8-1.8 - -1.22

-1.22 - -0.64-0.64 - -0.05

-0.05 - 0.530.53 - 1.121.12 - 1.7

1.7 - 2.282.28 - 2.87

2.87 - 3.453.45 - 4.04

4.04 - 4.624.62 - 8.96

LakeTinaroo

Groundwater flow direction (inferred)

244

References


KENDALL M.G. & STUART A. 1966. The Advanced Theory of Statistics, Vol. 3,Design and Analysis, and Time Series. Charles Griffin, London, pp. 552.

245

APPENDIX VI



GROUNDWATER RECHARGE: A CHLORIDE MASS BALANCE APPROACH

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254

APPENDIX VII

Chemical Analysis of Natural Waters

The physical parameters of the groundwater samples were measured in the field, andincluded the parameters electrical conductivity, pH and Eh (referenced to standardhydrogen electrode). Two water samples were then collected in polyethylene orpolypropylene, acid washed bottles for analysis of chemical parameters in thelaboratory. One of these samples was preserved by storage at 4 °C for anion analysis.The other was preserved by acidifying to < pH 2 with nitric acid for analysis ofcations.

Rain water samples provided by CSIRO Land and Water were analysed for the majorcations using ICP-OES, and for the anions, chloride, sulfate, nitrate, phosphate andbromide by ion chromatography (IC) using a Dionex DX300 ion chromatograph.The analyses were checked by calculating the cation-anion balance for each sample.

Cations in Water by Inductively Coupled Plasma – Optical Emission

Spectroscopy (ICP-OES)

Cations were analysed by a Varian Liberty 200 inductively coupled plasma opticalemission spectrometer (ICP-OES). The instrument was calibrated using syntheticstandards. Major cations analysed were Na, K, Ca, and Mg; minor and trace cationswere Fe, Al, Zn, Cu, Mn, Sr, Ba, Ti, Li and V. Silica, although not in ionic form innatural waters, was also analysed with this suite of cations. The detection limits usedare shown in Table 1.

Table 1. Detection limits.

Element Minimum Detection Limits

Na 0.015 mg/L

K 0.20 mg/L

Mg 0.009 mg/L

Ca 0.06 mg/L

Al 0.015 mg/L

Si 0.18 mg/L

Sr 0.0006 mg/L

Mn 0.003 mg/L

Fe 0.015 mg/L

Zn 0.009 mg/L

Cu 0.02 mg/L

Ba 0.0007 mg/L

Ti 0.009 mg/L

Li 0.006 mg/L

V 0.02 mg/L

255

THEORY OF OPERATION:

The cation concentrations were measured using inductively coupled plasma - opticalemission spectroscopy (ICP-OES). This technique involves the water sample beingaspirated into a plasma. The intensity of characteristic wavelengths emitted by theexcited analyte ions in the plasma are measured by a spectrophotometer. Themeasured intensity is proportional to concentration, thus concentration of ions in thesample can be determined.

SAMPLE PREPARATION:

Little or no sample preparation is required for analysis of aqueous samples by ICP-OES except for highly turbid samples, which must be filtered (0.45 μm membranefilter) before analysis. As all the water samples analysed in this study have electricalconductivities less than 4000 μS/cm, dilution before analysis was not required. Also,concentration of elements determined must be within the detection limits of the ICP-OES for the results to have analytical meaning.

ANALYTICAL ERROR:

Approximate error (based on repeat analyses) of approximately 5 %.

256

Anions in Water by Ion Chromatography (IC)

The following anions, chloride, sulfate, nitrate, phosphate and bromide, have beendetermined by ion chromatography (IC) using a Dionex DX300 ion chromatographwith suppressed conductivity detection. The system utilises Dionex AS14 analyticalcolumn and AG14 guard column. Conductivity suppression was by amicromembrane suppressor, Dionex CMMS-II.

DETECTION LIMITS:

A working range has been given in Table 2. This range is based on a combination ofstandard concentration range and instrument working range.

Table 2. Detection Limits.

Element Working Detection Limits

F- 0.05 – 12 mg/L

Cl- 0.5 – 150 mg/L

SO42- 0.5 – 100 mg/L

Br- 0.05 – 12 mg/L

NO3- 0.05 – 12 mg/L

PO43- 0.05 – 12 mg/L

THEORY OF OPERATION:

ION CHROMATOGRAPHIC PROCESS:

The sample is introduced in the flowing stream and carried into the anion exchangecolumn. Ions interact with the ion exchange sites on the stationary phase in thecolumn. Mobile phase ions (or eluent ions) compete with the sample ions for ionexchange sites on the column. Separation depends upon the different ions havingdifferent affinities for both phases. In the case of anion separations the differingaffinities for stationary and mobile phases are due to the ionic charge and ion size(ionic radius) of each anion species. Once anions are separated the concentration ofeach species present in the sample is measured using a conductivity detector. Achromatogram displays peaks in conductivity at various retention times. Eachanionic species is identified by its retention time which remains constant throughoutsuccessive runs.

STATIONARY PHASE:

The column packing material containing functionalised active sites. For aniondeterminations the Dionex AS14 anion exchange column is used.

257

MOBILE PHASE (OR ELUENT):

The liquid flowing though the column that contains competing ion for the activesites.

SAMPLE PREPARATION:

Little of no sample preparation is required of analysis of aqueous sample by ionchromatography. However highly turbid samples must be filtered before analysis(0.45 μm membrane filter). As all the water samples collected in this study hadelectrical conductivities < 700 μS/cm, dilution before analysis was not required.

REAGENTS:

Eluent: 3.5 mM Na2CO3/1.0 mM NaHCO3. Prepare diluting the 100x concentrate100 fold (i.e. pipette 10 mL of 100x concentrate into a 1000 mL volumetric flask anddilute to the mark with ultra pure water). Fill eluent bottle with this solution andsparge with argon for at least ten minutes before starting eluent pump.

Regenerant solution: Add 2.4 mL of conc H2SO4 to 1000 mL of ultra pure water anddilute further to 2000 mLs. Fill regen bottle with this solution recap and allow topressurise. After several minutes ensure regen solution is flowing throughsuppressor.

RESULTS:

Ion chromatography is an excellent method of anion species determination in watersamples. It has an extremely good precision with a % RSD of < 2 %. However it isimportant that results obtained are not taken on face value but are checked to assuredata is reasonable. This is particularly important as peaks can be misnamed due tosmall shifts in retention time. The retention time can change due to a variety ofreasons most commonly due to problems with the eluent pump, blockages andinaccurate preparation of eluent. Always check with previous days data to determineif retention times have not changed. Also data should be with the working range ofeach species listed above.

258

Alkalinity – Acid titration method

Alkalinity or the acid neutralising capacity is determined by acid titration. Alkalinityis primarily a function of the carbonate (CO3

-), bicarbonate (HCO3-) and hydroxide

(OH-) ion content. The procedure below is based on that of Greenberg et al. (1992).

DETECTION LIMITS:

0.25 ppm Alkalinity (CaCO3) (mg/L water)

HCO3- 0.305 mg/L

CO32- 0.15 mg/L

APPARATUS:

250 mL conical flask, calibrated pH meter and 25 mL burette

SAFETY EQUIPMENT:

Laboratory coat, safety glasses.

REAGENTS:

0.1N Standard HCl: SAFETY: This dilution must be carried out in a fume cupboard.Pipette 10 mLs of conc HCl (10 M) into a 1000 mL volumetric flask and dilute tomark.

Standardisation of 0.1 N HCl:

Weigh 0.7 - 0.8 g of pure sodium tetraborate by difference into a 150 mL conicalflask, dissolve in about 50 mLs of distilled water and add a few drops of methyl redindicator. Titrate the sodium tetraborate solution with the 0.1N HCl as the titrantuntil the colour changes to pink. Record the volume of HCl used. Carry out thisprocedure in triplicate. Use the following equation to calculated the normality of theacid solution.

N HCl = Weight of Na2B4O7 / 190.72 x Vol of Titrant (HCl)

0.02 N Standard HCl: Pipette 200 mLs of standard 0.1N HCl into a 1000 mLvolumetric flask and dilute to the mark.

259

PROCEDURE:

The alkalinity of a sample is due to the presence of hydroxide, carbonate orbicarbonate ions. The concentration of each of these ions in a sample can becalculated once the phenolphthalein and total alkalinity have been determined.

1) DETERMINATION OF PHENOLPHTHALEIN ALKALINITY (P)

Pipette 100 mLs of sample into a 250 mL beaker. Measure the pH of the sample.

If pH is less than 8.3 go on to step 2) as P=0.

If pH is greater than 8.3 then titrate the sample with 0.1N HCl to pH 8.3. Use amagnetic stirrer and leave pH probe in sample while titrating. Record volume of HClused. Calculate alkalinity due to hydroxide, P, by using calculation (a). Go to step 2.

2) DETERMINATION OF TOTAL ALKALINITY (T)

Titrate the sample to the pH 4.7 if the sample alkalinity is unknown. If knownchoose the appropriate total alkalinity equivalence point from the following table.

The pH values shown in Table 3 are suggested equivalence points for thecorresponding alkalinity concentrations.

Table 3. Alkalinity equivalence points.

Alkalinity (mg/L CaCO3) End Point pH: Total

30 4.9

150 4.6

500 4.3

Silicates, phosphates known or suspected 4.5

Industrial waste or complex system 4.5

Record total volume of HCl titrated i.e. include volume of titrant used in step 1

If appropriate, calculate the Total Alkalinity, T, using calculation (b).

If Total Alkalinity, T, is less than 20 mg/L CaCO3 go to step 3.

If Total Alkalinity, T, is greater than 20 mg/L CaCO3 go to step 4.

260

3) Determination of total alkalinity less the 20 mg/L CaCO3

a) Pipette 100 mLs of sample into a 250 mL beaker and titrate using 0.01M HClto an end point in the range of 4.3 to 4.7. Record the volume and the exactpH.

b) Titrate the solution further to reduce the pH exactly 0.30 pH units and record volume. Use calculation (c) to determine Total Alkalinity, T.

4) DETERMINE THE RELATIONSHIP BETWEEN HYDROXIDE, CARBONATE AND

BICARBONATE ALKALINITY USING THE TABLE BELOW

NOTE:As the end point is approached make smaller additions of acid and be surethat pH equilibrium is reached before adding more titrant.

CALCULATIONS:

a) P (Phenolphthalein Alkalinity)

P mg/L CaCO3 = A x N x 50 000 / volume of sample

where A = mL standard acid used

N = normality of standard acid

b) T (Total Alkalinity)

T mg/L CaCO3 = A x N x 50 000 / volume of sample

where A = mL standard acid used

N = normality of standard acid

c) Potentiometric titration of low alkalinity (<20mg/L CaCO3):

T (Total alkalinity),

T mg/L CaCO3 = (2B - C) x N 50 000 / volume of sample

where B = mL of titrant to first recorded pH

C = total mL of titrant of reach pH 0.3 unit lower

N = normality of acid

261

The calculation of hydroxide, carbonate and bicarbonate alkalinities is based on therelationship between phenolphthalein and total alkalinity, as shown in Table 4.

Table 4. Formulas for the calculation of hydroxide, carbonate and bicarbonatealkalinities.

Result of

titration

Hydroxide alkalinity as

CaCO3

Carbonate alkalinity as

CaCO3

Bicarbonate alkalinity as

CaCO3

P = 0 0 0 T

P < 1/2T 0 2P T - 2P

P >=1/2T 0 2P 0

P > 1/2T 2P-T 2(T-P) 0

P=T T 0 0

Where P = phenolphthalein alkalinity

T = total alkalinity

Report total alkalinity as:

"The alkalinity to pH ____ = ____ mg CaCO3/L"

To convert hydroxide, carbonate and bicarbonate expressed as alkalinity toconcentration of their own species to be used in a mass balance multiply by thefollowing factors.

Hydroxide mg/L OH- = mg/l CaCO3 x 0.34

Carbonate mg/L CO32- = mg/L CaCO3 x 0.60

Bicarbonate mg/L HCO3- = mg/L CaCO3 x 1.22

ANALYTICAL ERROR:

Approximate error (based on repeat analyses) of approximately:

Alkalinity 0.6 %

HCO3- 0.6 %

CO32- 1.7 %

References

GREENBERG A.E., CLESCERI L.S. & EASTON A.D. 1992. Standard Methods for theExamination of Water and Waste Water. APHA-AWWA-WEF, Washington,D.C.

262

APPENDIX VIII

Mineralogical Analysis - X-ray Diffraction

GENERAL

XRD is a widely used technique for mineral identification, particularly for fine-grained materials where the grain size is too small to be usefully studied with theoptical microscope. In addition, the XRD analysis can provide information on thedegree of structural disorder, particle size, and the nature of isomorphoussubstitutions.

The method is based on the fact that X-rays are scattered by the electrons aroundatoms, which form the atomic layers in crystals (lattice spacings). A particularcrystalline material has a particular structure or lattice. The scattered X-raysreinforce each other in directions that depend on the lattice repeat distances and thewavelength of the X-rays. The angles of diffraction give an indirect indication of thespacings (d spacings) between atomic layers and therefore can be used for mineralidentification.

The advantages of the method include the fact that:

it is non-destructive,

the samples are reasonably easy to prepare,

the material can be processed even in very small quantities, and

modern computer-linked instruments are quite straightforward to operate andmaintain.

The limitations of the XRD analysis include:

the method is capable of identifying only crystalline materials, and

the components of the same mineral series (i.e. micas, feldspars, amphiboles)which have very similar crystallographic structures are difficult to separatedue to their very similar XRD patterns.

Mineral compositions of the samples were determined using a Philips PW 1050diffractometer equipped with a cobalt anticathode. The identification andquantification of mineral phases was assisted by computer programs such as Jade(search-match program) and Siroquant (quantification program which expresses thecomposition of crystalline material within a sample in percentages of dry weight).An internal standard (10 % corundum) was also added to the samples to enable theestimation of amorphous material.

The program Jade searches a large database of mineral XRD intensity patterns andmatches those ideal patterns with the experimental ones. The limitation of this

263

search-match process is that similar crystallographic structures result in similar XRDpatterns and this can make mineral identification questionable, especially of mineralsbelonging to the same series such as plagioclase or pyroxenes.

The Siroquant program provides quantitative analyses of mineral phases based on theprinciple of “pattern synthesis”; an ideal XRD pattern is synthesised from basiccrystal structure data for each mineral in the sample. These synthesised patterns areadded and fitted by a least squares refinement to the sample pattern. Thequantification of the experimental XRD trace is thus indirectly performed byquantifying the synthesised pattern. There is no perfect fit between a calculated(synthesised) pattern and the observed (experimental) one; this imperfect fit results inerrors in the quantification of each mineral phase. For the current investigation, thereis an error of less than1 % for most mineral phases identified; these errors are mainlybased on the goodness of fit between the synthesised XRD pattern and theexperimental one.

SAMPLE PREPARATION

(after Bish & Post 1989; Jenkins & Snyder 1996)

Micronizing

The micronizing vessel consists of a plastic cylinder filled with 48 stacked smallagate or corundum cylinders. The particle size of the sample material to be crushedin this type of mill is to be no larger than 100 microns (i.e. what is obtainable from aswing mill). Approximately 3 g of sample and 10-12 ml of alcohol are placed intothe micronization vessel and then into the arm of the mill. The timer on the mill istypically set to 0.2 (hr) (i.e. 12 minutes). Other settings of the timer can be made.The slurry obtained is homogenous and the particle size is ideally in the range of 1 to5 microns. The mixture of sample/alcohol is placed in a pre-labeled beaker and leftto dry overnight in an oven at 50-60 °C. The sample will require remixing prior itsuse to counteract any segregation of phases during the drying step. The micronizedpowder is used to identify all the mineral phases of the sample providing that thephases are present in sufficient abundance.

Randomly-orientated powder samples

About 1.5-2 g of powder is lightly packed (to avoid as much as practical pressureorientation), into the back side of a circular cavity of an aluminum plate. The frontface of the sample holder rests on a polished metal block. The pressing is done usinga small plastic cylinder and a metal ring for guidance. After the powder is packed,the plastic cylinder and metal ring are removed and the second half of the holder iscarefully clicked on. The entire holder is then lifted, inverted and placed faceupward into the autosample changer carousel. When the entire batch is ready, thecarousel is placed into the autosample changer and the data acquisition task begun.

264

References

JENKINS R. & SNYDER R.L. 1996. Introduction to X-ray Powder Diffractometry.Chemical Analysis, Vol. 138, pp. 231-259, Wiley, New York.

BISH D.L. & POST J.E. 1989. Sample preparation for x-ray diffraction. Reviews inMineralogy 20, 72-99. Mineralogical Society of America, Washington D.C.

265

APPENDIX IX

Field and laboratory data: groundwater and rain water samples

Abbreviations

bd Below detection limit

na Not analysed

np Not present

GROUNDWATERS: FIELD DATA

RN Sampled SWL Field EC Field pH Field Eh Temp. Screened

(m) (μS/cm) (deg. C) Lithology

45431 23/10/98 145.9 6.61 343 22.8 unknown

45675 27/10/98 12.95 99 5.92 355 24.8 unknown

45789 23/10/98 112.6 6.25 372 22 unknown

45807 23/10/98 71 5.46 410 22.4 unknown

45809 23/10/98 143 6.63 370 22.1 unknown

45857 23/10/98 158.9 6.56 339 23 basalt

72094 23/10/98 156.7 6.75 318 23.1 unknown

72145 23/10/98 110.5 6.31 330 22.8 unknown

72153 23/10/98 124.1 6.56 360 23.8 basalt

72918 20/10/98 9.54 205 8.06 252 21.8 basalt

92593 23/10/98 364 6.85 70 23.7 basalt

92678 19/10/98 25.55 64 5.99 452 22.2 unknown

92679 19/10/98 44 5.67 442 22 unknown

92685 19/10/98 16.25 95 5.42 430 20.7 unknown

92689 19/10/98 34.86 56 5.05 454 21.3 unknown

92690 19/10/98 18.76 72 6.14 407 22.2 unknown

92710 19/10/98 55 5.34 461 22.6 unknown

92744 20/10/98 194 7.75 308 22.4 unknown

92753 20/10/98 24.11 251 7.09 300 22.8 basalt

92757 19/10/98 24.3 46 4.44 474 21.7 metamorphics

92760 19/10/98 17.33 84 6.43 367 22.4 unknown

92761 19/10/98 41 5.42 449 22 basalt

109030 20/10/98 15.7 257 8.25 209 22.6 unknown

109031 20/10/98 18.56 58 6.05 415 21.6 metamorphics

109043 20/10/98 47.87 193 6.63 358 21.7 unknown

266



109108 19/10/98 15.41 294 7.78 278 23 unknown

109109 20/10/98 108 6.26 335 22.7 granite

11000055 no sample 39 142.8 6.38 350 22.8 basalt

11000056 24/10/98 13.25 164 6.26 289 24.4 basalt

11000061 27/10/98 26.06 167.8 6.65 362 25.2 basalt

11000062 27/10/98 21.61 193.1 6.9 364 24.6 basalt

11000063 27/10/98 24.72 111.2 6.47 390 24.6 basalt

11000064 24/10/98 41.84 210 6.78 347 25.5 basalt

11000066 26/10/98 17.07 124 6 376 24.8 basalt

11000067 28/10/98 17.69 135.5 6.82 374 23.9 basalt

11000068 28/10/98 45.7 148.5 6.75 357 29.5 basalt

11000115 24/10/98 21.11 225 6.83 370 24.9 basalt

11000116 27/10/98 10.96 367 7.36 235 25 basalt/granite

11000117 28/10/98 39.39 161 6.88 344 25.8 basalt

11000118 25/10/98 15.33 338 7.35 319 25.5 basalt

11000125 24/10/98 22.7 244 7.29 318 25.5 basalt

11000126 24/10/98 50.26 203 9.9 70 24.2 basalt

11000127 24/10/98 14.67 122.2 6.8 355 24.7 basalt

11000128 24/10/98 43.1 259 9.5 125 27.6 basalt

11000129 24/10/98 32.17 266 8.42 220 26.7 basalt

11000130 28/10/98 7.61 181 6.91 358 24.8 basalt

11000132 24/10/98 20.88 132 6.9 315 25.8 basalt

11000133 26/10/98 44.96 278 6.86 300 26.5 basalt

11000134 27/10/98 11.92 67.3 5.57 434 24.9 basalt/meta

Lake Eacham 19/10/98 na na na na

11000061 19/5/99 17.75 147.8 6.55 na 23.9 basalt

11000064 20/5/99 33.64 189.4 6.97 502 25.1 basalt

11000117 15/5/99 32.10 162.0 6.41 438 25.3 basalt

11000119 15/5/99 8.53 123.0 6.43 456 25.1 basalt

11000128 19/5/99 27.13 253.0 8.91 421 25.7 basalt

11000129 19/5/99 20.73 253.0 7.94 na 27 basalt

11000133 20/5/99 36.86 189.9 7.03 na 25.9 basalt

11000136 19/5/99 14.79 288.0 8.51 432 27.8 basalt

11000137 19/5/99 13.17 150.3 6.80 548 24.8 basalt

11000138 16/5/99 17.46 216.0 7.15 484 25.1 granite

11000139 15/5/99 ~18-19 225.0 6.89 443 22.3 granite

11000140 15/5/99 27.30 279.0 8.10 440 25.6 granite

267



11200012 16/5/99 4.06 40.0 5.04 471 25.1 metamorphics

11200018 16/5/99 34.21 264.0 9.25 381 25.9 basalt

11200019 16/5/99 11.21 68.0 6.12 466 23.9 basalt

11000066 16/10/99 13.29 107 6.69 42 24.4 basalt

11000104 15/10/99 25.05 145 5.25 314 25 granite

11000118 16/10/99 13.73 230 7.45 213 24.3 basalt

11000128 15/10/99 33.15 248 8.47 149 23.6 basalt

11000129 15/10/99 23.19 236 8.42 169 22.7 basalt

11000130 16/10/99 3.89 176 7.24 169 23.3 basalt

11000132 16/10/99 14.16 98 7.77 184 24.3 basalt

11000135 16/10/99 39.38 131 7.14 175 24.8 basalt

11000136 16/10/99 15.98 266 8.41 176 25 basalt

11000137 16/10/99 13.74 163 7.71 188 24.1 basalt

11000138 15/10/99 29.04 291 7.9 141 23.7 granite

11000139 15/10/99 20.14 190 7.52 199 20.5 granite

11000140 15/10/99 29.28 272 8.28 146 23.2 granite

11200012 15/10/99 10.16 32 7 131 22.2 metamorphics

11200018 14/10/99 35.03 252 8.24 76 21.7 basalt

11200019 14/10/99 12.18 60 7.4 168 21.8 basalt

11200142 14/10/99 14.33 51 5.36 195 21.5 basalt

11200144 15/10/99 16.77 70 6.52 201 23 metamorphics

11200146 14/10/99 9.47 284 7.72 112 16.5 metamorphics

268

GR

OU

ND

WA

TE

RS: L

AB

OR

AT

OR

Y D

AT

A

RN

Sa

mp

led

Na

KC

aM

gS

iT

ota

l S

Mn

Fe

Al

Sr

Ti

Ba

VZ

nC

uL

i

mg/

Lm

g/L

mg/

Lm

g/L

mg/

Lm

g/L

mg/

Lm

g/L

mg/

Lm

g/L

mg/

Lm

g/L

mg/

Lm

g/L

mg/

Lm

g/L

4543

123

/10/

987.

789

1.91

97.

956

7.37

722

.13

nabd

bdbd

bdbd

0.00

7na

bdbd

na

4567

527

/10/

987.

519

0.92

12.

579

3.94

54.

134

na0.

084

0.52

bdbd

bd0.

03na

1.16

1bd

na

4578

923

/10/

985.

988

1.64

84.

637

5.60

912

.46

nabd

0.08

bdbd

bd0.

035

nabd

bdna

4580

723

/10/

985.

326

0.42

10.

944

1.34

13.

687

na0.

006

0.60

8bd

bdbd

0.02

9na

bdbd

na

4580

923

/10/

987.

661.

405

7.58

67.

925

20.9

9na

0.00

90.

076

bdbd

bd0.

009

na0.

067

bdna

4585

723

/10/

988.

012.

109

7.11

28.

249

18.7

1na

0.13

0.18

70.

042

0.06

9bd

bdna

bdbd

na

7209

423

/10/

988.

923

1.86

68.

724

8.22

916

.48

na0.

187

0.18

bdbd

bd0.

007

na0.

021

bdna

7214

523

/10/

985.

381

0.95

85.

272

5.93

59.

931

nabd

bdbd

bdbd

0.01

6na

bdbd

na

7215

323

/10/

986.

211

1.99

46.

458

7.63

12.0

9na

0.00

91.

946

0.37

3bd

bd0.

015

na0.

109

0.05

4na

7291

820

/10/

9813

.11

2.97

212

.73

6.56

512

.23

na0.

049

bdbd

0.01

9bd

0.00

2na

bdbd

na

9259

323

/10/

9849

.97

3.07

98.

939

6.15

831

.51

na0.

205

2.20

7bd

bdbd

0.05

8na

bdbd

na

9267

819

/10/

984.

564

1.54

33.

106

2.40

511

.01

na0.

016

0.29

3bd

bdbd

0.00

7na

0.13

10.

136

na

9267

919

/10/

984.

060.

509

0.31

41.

018

5.55

4na

bd0.

375

bdbd

bd0.

011

na0.

025

0.04

5na

9268

519

/10/

989.

027

0.76

80.

465

2.57

85.

632

na0.

046

0.01

70.

051

bdbd

0.02

1na

0.03

5bd

na

9268

919

/10/

984.

497

0.37

0.2

1.25

24.

57na

0.11

270.

2564

0.17

bdbd

0.02

1na

0.02

3bd

na

9269

019

/10/

984.

748

0.70

72.

42.

852

8.81

8na

bdbd

bdbd

bd0.

015

na0.

02bd

na

9271

019

/10/

983.

563

bd0.

433

1.40

26.

382

na0.

024

0.02

60.

031

bdbd

0.01

7na

0.01

5bd

na

9274

420

/10/

989.

462

1.49

711

.22

10.3

212

.73

nabd

0.02

4bd

0.07

1bd

0.00

6na

bdbd

na

9275

320

/10/

9813

.38

1.93

59.

1615

.01

22.9

na0.

010.

08bd

0.05

6bd

0.00

3na

0.29

0.02

3na

269

RN

Sa

mp

led

Na

KC

aM

gS

iT

ota

l S

Mn

Fe

Al

Sr

Ti

Ba

VZ

nC

uL

i

mg/

Lm

g/L

mg/

Lm

g/L

mg/

Lm

g/L

mg/

Lm

g/L

mg/

Lm

g/L

mg/

Lm

g/L

mg/

Lm

g/L

mg/

Lm

g/L

9275

719

/10/

982.

179

bd<

0.06

0.86

2.85

na0.

008

0.03

0.29

bdbd

0.01

5na

bdbd

na

9276

019

/10/

984.

373

0.39

53.

73.

573

9.12

8na

bd0.

017

bdbd

bd0.

005

na0.

084

0.06

9na

9276

119

/10/

983.

479

bd0.

288

0.69

53.

143

na0.

004

bdbd

bdbd

0.01

3na

bdbd

na

1090

3020

/10/

9813

.77

1.80

420

.66

11.3

617

.29

na0.

003

bdbd

bdbd

0.00

4na

bdbd

na

1090

3120

/10/

984.

005

0.40

72.

458

2.00

28.

606

nabd

0.39

70.

383

bdbd

0.00

6na

bdbd

na

1090

4320

/10/

989.

537

1.71

310

.87

8.44

28.8

nabd

bdbd

0.04

5bd

0.00

2na

bdbd

na

1091

0819

/10/

9812

.87

2.18

17.5

79.

746

15.9

4na

0.18

10.

036

bd0.

069

bd0.

013

nabd

bdna

1091

0920

/10/

986.

479

0.51

3.77

54.

038

15.1

1na

0.23

32.

575

bdbd

bd0.

172

na0.

005

bdna

1091

0819

/10/

9812

.87

2.18

17.5

79.

746

15.9

4na

0.18

10.

036

bd0.

069

bd0.

013

nabd

bdna

1091

0920

/10/

986.

479

0.51

3.77

54.

038

15.1

1na

0.23

32.

575

bdbd

bd0.

172

na0.

005

bdna

1100

0055

no s

ampl

ena

nana

nana

nana

nana

nana

nana

nana

na

1100

0056

24/1

0/98

10.7

81.

397

7.81

27.

184

23.8

4na

bd0.

037

bdbd

bd0.

003

nabd

bdna

1100

0061

27/1

0/98

8.52

31.

874

9.29

49.

169

18.9

nabd

bdbd

bdbd

0.01

nabd

bdna

1100

0062

27/1

0/98

8.18

83.

489

11.6

11.1

417

.53

nabd

bdbd

bdbd

bdna

bdbd

na

1100

0063

27/1

0/98

7.22

32.

024

4.81

24.

142

16.6

4na

bd0.

019

bd0.

048

bd0.

016

nabd

bdna

1100

0064

24/1

0/98

9.95

42.

141

13.3

311

.11

23.5

1na

bd0.

081

bdbd

bd0.

003

nabd

bdna

1100

0066

26/1

0/98

11.5

61.

069

3.44

83.

427

11.5

nabd

bdbd

0.02

5bd

0.00

7na

bdbd

na

1100

0067

28/1

0/98

6.18

91.

282

5.82

66.

698

11.6

7na

0.08

70.

166

0.01

60.

059

bd0.

006

nabd

bdna

1100

0068

28/1

0/98

7.58

71.

935

6.84

16.

3823

.23

nabd

0.08

6bd

0.06

5bd

0.00

3na

bdbd

na

1100

0115

24/1

0/98

9.94

62.

110

11.5

89.

539

19.2

8na

bd0.

093

0.08

0.10

8bd

0.00

5na

bdbd

na

1100

0116

27/1

0/98

69.1

11.

207

6.16

75.

546

17.6

3na

0.05

90.

122

bdbd

bd0.

003

nabd

bdna

270

RN

Sa

mp

led

Na

KC

aM

gS

iT

ota

l S

Mn

Fe

Al

Sr

Ti

Ba

VZ

nC

uL

i

mg/

Lm

g/L

mg/

Lm

g/L

mg/

Lm

g/L

mg/

Lm

g/L

mg/

Lm

g/L

mg/

Lm

g/L

mg/

Lm

g/L

mg/

Lm

g/L

1100

0117

28/1

0/98

8.42

72.

674

8.43

6.88

119

.98

nabd

bdbd

0.08

9bd

0.00

4na

bdbd

na

1100

0118

25/1

0/98

15.2

81.

349

16.9

221

.56

16.8

2na

bdbd

bd0.

022

bd0.

003

nabd

bdna

1100

0125

24/1

0/98

9.60

32.

363

20.0

210

.43

21.7

1na

bd0.

104

bdbd

bd0.

048

nabd

bdna

1100

0126

24/1

0/98

17.6

63.

627

85.7

916

.28

43.5

9na

nana

na0.

259

bdbd

na0.

225

0.03

5na

1100

0127

24/1

0/98

4.95

1.18

79.

051

4.22

313

.62

na0.

008

0.27

40.

191

bdbd

0.01

5na

bdbd

na

1100

0128

24/1

0/98

20.0

12.

851

18.8

28.

256

13.7

4na

0.03

20.

121

bdbd

bd0.

086

nabd

bdna

1100

0129

24/1

0/98

12.9

42.

217

21.3

110

.713

.46

na0.

003

0.09

8bd

bdbd

0.01

nabd

bdna

1100

0130

28/1

0/98

8.77

51.

899

10.3

69.

2822

.44

nabd

bdbd

0.08

5bd

0.01

7na

bdbd

na

1100

0132

24/1

0/98

5.29

51.

150

6.66

25.

096

20.6

8na

bd0.

536

bdbd

bd0.

005

nabd

bdna

1100

0133

26/1

0/98

9.36

12.

361

12.5

210

.57

24.2

1na

bdbd

bdbd

bd0.

002

nabd

bdna

1100

0134

27/1

0/98

5.66

20.

681

1.24

61.

753

3.96

8na

bdbd

bdbd

bd0.

052

nabd

bdna

Lak

e E

acha

m19

/10/

982.

649

1.00

31.

503

2.49

<0.

18na

bdbd

bdbd

bd0.

004

nabd

bdna

1100

0061

19/5

/99

7.81

11.

759

8.16

38.

243

21.0

80.

505

bdbd

bd0.

089

bd0.

010

bdbd

bd0.

012

1100

0064

20/5

/99

9.00

52.

110

11.6

69.

955

27.6

30.

561

bd0.

024

bd0.

135

bd0.

003

bd0.

019

bd0.

017

1100

0117

15/5

/99

8.14

52.

557

7.23

35.

9325

.33

0.26

1bd

0.02

1bd

0.10

4bd

0.00

30.

0210

bdbd

0.01

7

1100

0119

15/5

/99

28.0

10.

352

0.74

20.

837

10.7

70.

202

bd0.

038

0.04

2bd

bdbd

bdbd

bd0.

020

1100

0128

19/5

/99

21.8

82.

854

17.1

810

.48

15.9

32.

729

bdbd

0.05

10.

122

bd0.

006

bd0.

011

bd0.

015

1100

0129

19/5

/99

11.5

41.

723

20.9

813

.17

20.7

22.

811

bdbd

bd0.

178

bd0.

007

0.04

950.

012

bd0.

019

1100

0133

20/5

/99

8.87

32.

234

12.2

210

.63

27.6

40.

482

bdbd

bd0.

132

bd0.

002

bd0.

022

bd0.

017

1100

0136

19/5

/99

42.6

4.54

89.

621

4.66

39.

786

4.53

00.

180

1.68

51.

781

0.11

00.

013

0.03

70.

0146

0.02

6bd

0.02

1

1100

0137

19/5

/99

6.77

61.

619

10.0

58.

0623

.60.

227

bdbd

bd0.

113

bd0.

006

0.03

130.

014

bd0.

014

271

RN

Sa

mp

led

Na

KC

aM

gS

iT

ota

l S

Mn

Fe

Al

Sr

Ti

Ba

VZ

nC

uL

i

mg/

Lm

g/L

mg/

Lm

g/L

mg/

Lm

g/L

mg/

Lm

g/L

mg/

Lm

g/L

mg/

Lm

g/L

mg/

Lm

g/L

mg/

Lm

g/L

1100

0138

16/5

/99

19.7

61.

204

20.2

93.

648

23.9

42.

133

0.00

60.

021

0.07

80.

170

bd0.

008

bd0.

011

bd0.

018

1100

0139

15/5

/99

29.1

21.

839

9.33

47.

313

20.3

42.

109

0.07

90.

051

0.48

80.

041

bd0.

005

0.02

770.

010

bd0.

014

1100

0140

15/5

/99

25.9

72.

853

22.0

98.

575

18.7

23.

789

0.08

5bd

bd0.

115

bd0.

015

0.03

39bd

bd0.

031

1120

0012

16/5

/99

2.67

00.

225

0.23

81.

092

5.34

70.

939

0.12

10.

187

0.01

5bd

bd0.

022

bd0.

062

0.08

00.

019

1120

0018

16/5

/99

15.4

73.

234

24.4

611

.14

18.9

75.

578

bdbd

0.36

40.

150

bd0.

012

bd0.

009

bd0.

013

1120

0019

16/5

/99

3.26

51.

075

3.32

72.

268

10.7

80.

331

bd0.

038

0.05

60.

019

bd0.

008

bd0.

017

bd0.

014

1100

0066

16/1

0/99

5.67

70.

417

5.00

32.

431

14.8

7na

0.01

30.

468

0.52

1bd

0.08

90.

011

na0.

477

nana

1100

0104

15/1

0/99

1.93

90.

732

1.52

81.

232

7.12

9na

0.06

60.

499

0.48

3bd

0.03

80.

096

na0.

023

nana

1100

0118

16/1

0/99

7.06

51.

091

18.4

111

.68

21.1

9na

bd0.

284

0.22

0bd

0.02

70.

003

nabd

nana

1100

0128

15/1

0/99

15.4

82.

115

28.7

18.

864

14.7

7na

bd5.

000

bdbd

bd0.

014

na0.

718

nana

1100

0129

15/1

0/99

7.64

91.

351

41.3

110

.96

18.1

9na

bd0.

061

0.01

70.

035

bd0.

015

nabd

nana

1100

0130

16/1

0/99

4.99

71.

442

17.3

27.

446

28.2

4na

bd5.

000

bdbd

bd0.

011

na0.

227

nana

1100

0132

16/1

0/99

3.35

1.00

57.

913.

541

21.5

6na

bd0.

193

0.17

2bd

0.02

10.

007

na0.

038

nana

1100

0135

16/1

0/99

4.58

90.

740

9.58

14.

724

19.9

1na

bd0.

062

bdbd

bd0.

01na

0.05

7na

na

1100

0136

16/1

0/99

40.9

3.02

47.

865

2.57

69.

747

nabd

0.98

71.

328

bd0.

055

0.01

4na

0.03

0na

na

1100

0137

16/1

0/99

4.79

41.

494

17.2

26.

482

21.8

1na

bd0.

065

0.01

6bd

bd0.

017

na0.

093

nana

1100

0138

15/1

0/99

6.58

20.

965

28.5

813

.32

26.5

8na

bd0.

039

bdbd

bd0.

014

na0.

044

nana

1100

0139

15/1

0/99

17.7

31.

592

12.2

95.

7518

.62

nabd

0.08

90.

309

bd0.

017

0.01

na0.

065

nana

1100

0140

15/1

0/99

19.9

32.

006

33.0

88.

083

19.5

6na

bd0.

100

0.06

2bd

0.01

70.

029

na0.

347

nana

1120

0012

15/1

0/99

1.17

40.

354

5.41

0.80

55.

832

na0.

067

0.11

60.

093

bdbd

0.02

6na

0.36

3na

na

272

RN

Sa

mp

led

Na

KC

aM

gS

iT

ota

l S

Mn

Fe

Al

Sr

Ti

Ba

VZ

nC

uL

i

mg/

Lm

g/L

mg/

Lm

g/L

mg/

Lm

g/L

mg/

Lm

g/L

mg/

Lm

g/L

mg/

Lm

g/L

mg/

Lm

g/L

mg/

Lm

g/L

1120

0018

14/1

0/99

11.9

32.

625

53.8

46.

708

14.7

1na

bd5.

000

bdbd

bd0.

019

na0.

026

nana

1120

0019

14/1

0/99

1.48

10.

537

8.45

62.

033

12.5

9na

bd0.

555

0.30

1bd

0.04

30.

009

nabd

nana

1120

0142

14/1

0/99

1.24

60.

092

6.05

31.

493

5.05

1na

0.19

00.

100

0.11

3bd

bd0.

027

na0.

039

nana

1120

0144

15/1

0/99

6.71

60.

248

3.48

0.19

6.78

3na

0.07

47.

582

0.38

7bd

0.19

40.

033

na0.

049

nana

1120

0146

14/1

0/99

29.4

91.

098

30.7

3.70

29.

3na

bd0.

285

0.48

1bd

0.07

0.03

2na

bdna

na

273

GROUNDWATERS: LABORATORY DATA (continued)

RN Sampled HCO3 CO3 Cl SO4 F Br NO3 PO4 Ionic Balance

mg/L mg/L mg/L mg/L mg/L mg/L mg/L mg/L %

11000061 19/5/99 64.29 np 11.32 1.33 bd bd 5.46 bd 0.5

11000064 20/5/99 87.13 np 11.39 1.39 bd bd 5.62 bd 0.4

11000117 15/5/99 50.47 np 11.41 0.18 bd bd 5.02 0.21 1.6

11000119 15/5/99 61.63 np 6.22 1.27 bd bd 2.69 bd 3.4

11000128 19/5/99 144.78 0.26 7.69 0.70 bd bd bd bd 2.6

11000129 19/5/99 140.80 np 6.42 0.55 bd bd 3.55 bd 2.5

11000133 20/5/99 92.45 np 13.15 2.55 0.11 0.28 1.98 0.31 1.5

11000136 19/5/99 139.74 np 5.46 3.67 bd bd bd 0.41 10.6

11000137 19/5/99 70.66 np 9.85 1.24 bd bd 2.61 bd 0.2

11000138 16/5/99 118.49 np 8.14 2.37 bd bd bd 0.76 0.6

11000139 15/5/99 126.45 np 6.79 1.31 bd bd 0.15 0.14 3.7

11000140 15/5/99 158.33 np 9.90 3.44 0.41 bd 0.01 bd 0.9

11200012 16/5/99 3.72 np 6.78 1.77 bd bd 0.63 bd 9.5

11200018 16/5/99 126.47 14.63 5.38 4.59 bd bd 0.11 0.30 2.1

11200019 16/5/99 19.65 np 4.89 0.22 bd bd 4.90 bd 0.5

11000066 16/10/99 22.32 np 16.25 2.07 bd 0.08 12.97 0.15 -14.2

11000104 15/10/99 0.80 np 7.69 4.63 bd bd 0.96 bd 3.7

11000118 16/10/99 131.76 np 9.29 0.72 bd 0.1 0.11 0.19 -4

11000128 15/10/99 164.17 np 8.74 1.74 bd bd bd bd 3.3

11000129 15/10/99 176.39 np 7.38 0.88 bd bd 2.09 0.32 2.7

11000130 16/10/99 98.82 np 10.26 1 bd bd 0.97 0.6 1

11000132 16/10/99 53.13 np 4.51 0.13 bd bd 2.91 0.15 -8.4

11000135 16/10/99 53.13 np 8.01 0.42 bd bd 5.57 0.05 -4.7

11000136 16/10/99 159.39 np 5.92 6.6 bd bd bd 0.19 -4.6

11000137 16/10/99 84.48 np 11.41 0.7 bd bd 3.73 0.09 -4

11000138 15/10/99 165.77 np 8.36 2.77 bd bd 0.21 0.43 -3.3

11000139 15/10/99 125.39 np 6.82 2.81 bd bd bd 0.12 -8.7

11000140 15/10/99 175.33 np 9.9 3.13 0.3 0.07 3.38 bd -0.5

11200012 15/10/99 16.47 np 6.36 1.5 bd bd 0.52 bd -7

11200018 14/10/99 188.62 np 9 9.47 0.07 bd 2.01 0.23 6.6

11200019 14/10/99 34.00 np 4.88 1.12 bd bd 2.34 bd -1.5

11200142 14/10/99 0.53 np 4.76 17.55 bd bd 2.82 bd -4.3

11200144 15/10/99 15.94 np 15.29 9.59 bd bd 0.98 bd 2.6

11200146 14/10/99 167.36 np 11.84 7.59 bd 0.08 1.44 bd -0.6

274

RAINWATERS: LABORATORY DATA

Monthly rainfall samples were collected by CSIRO Land and Water from fiverainfall stations between October 1998 and November 1999, and analysed at QUT(all units in mg/L).

Malanda Cl Br NO3 PO4 SO4 Mg Na Ca K

1/10/98 3.23 bd 0.84 bd 1.64 0.221 1.573 0.125 bd

9/11/98 2.40 bd 8.90 0.69 1.41 0.352 1.315 0.309 0.513

9/12/98 1.59 bd 1.75 bd 0.68 0.012 0.624 bd bd

20/01/99 1.44 bd 8.92 bd 0.43 0.106 0.637 0.103 0.507

15/02/99 1.20 bd 0.40 bd 0.37 0.052 0.353 bd bd

3/3/99 1.41 bd 0.30 bd 0.35 0.046 0.272 bd bd

4/5/99 3.40 bd bd bd 0.58 0.181 1.655 bd bd

15/6/99 3.26 bd 0.18 bd 0.84 bd bd bd bd

15/7/99 1.67 bd 0.12 bd 0.51 bd bd bd bd

25/8/99 5.69 bd 0.65 bd 1.38 0.018 bd bd bd

13/9/99 2.46 bd 0.44 bd 0.65 bd bd bd bd

5/11/99 4.08 bd 0.19 bd 0.95 bd bd bd bd

29/11/99 1.09 bd 0.51 bd 0.51 bd bd bd bd

Walkamin Cl Br NO3 PO4 SO4 Mg Na Ca K

9/11/98 2.57 bd 0.89 bd 1.01 0.137 0.840 0.170 bd

9/12/98 0.71 bd bd bd 0.69 0.031 0.112 bd bd

20/01/99 2.89 bd bd 1.48 2.44 0.327 1.077 0.114 2.286

15/02/99 0.23 bd bd 0.14 0.33 bd bd bd bd

3/3/99 1.72 bd 0.17 bd 0.82 bd 0.342 0.664 bd

31/03/99 1.74 bd 0.12 bd 0.80 0.054 0.496 0.145 bd

15/6/99 5.90 bd 57.10 12.80 7.10 1.373 6.298 4.371 5.274

15/7/99 0.63 bd 6.66 2.61 0.89 bd bd bd 0.703

25/8/99 5.50 bd 124.30 9.10 5.00 1.860 8.069 3.956 7.750

05/11/99 6.20 bd 87.90 21.70 12.00 2.095 6.189 3.860 11.270

Atherton Cl Br NO3 PO4 SO4 Mg Na Ca K

9/11/98 2.83 bd bd 0.39 1.37 0.212 0.912 1.124 0.379

9/12/98 3.36 bd bd 0.14 1.05 0.246 1.373 0.923 0.561

20/01/99 2.78 bd 8.20 0.17 0.93 0.272 0.845 0.623 0.515

15/02/99 1.21 bd 2.08 0.33 0.50 bd 0.140 0.081 bd

3/3/99 0.99 bd 0.41 0.89 1.60 0.144 0.053 0.134 1.418

31/03/99 1.33 bd 2.83 0.15 0.71 bd 0.216 0.152 bd

275

Atherton Cl Br NO3 PO4 SO4 Mg Na Ca K

30/04/99 4.38 bd 38.91 0.53 3.60 unreliable unreliable unreliable unreliable

31/05/99 1.11 bd 3.50 0.39 1.59 0.106 0.182 unreliable bd

15/6/99 3.20 0.20 26.20 2.00 3.30 0.456 bd 1.828 1.555

15/7/99 0.62 bd 7.34 0.99 0.49 bd bd 0.154 bd

25/8/99 4.06 bd 11.85 1.32 2.00 0.175 bd 1.549 0.471

13/9/99 1.59 bd 6.39 1.20 0.76 bd bd 0.328 0.887

05/11/99 3.16 bd 19.20 4.73 0.13 0.108 bd 0.543 1.000

29/11/99 0.69 bd 1.78 0.51 0.63 bd bd bd 0.200

Upper Barron Cl Br NO3 PO4 SO4 Mg Na Ca K

1/10/98 3.07 bd 7.62 1.98 1.58 0.384 1.361 0.416 1.030

9/11/98 2.15 bd 2.15 0.58 1.15 0.219 0.875 0.726 0.571

9/12/98 1.34 bd 1.01 0.89 0.66 0.026 0.386 0.089 0.376

20/01/99 1.53 bd 26.45 2.50 2.22 0.376 0.462 0.388 1.510

15/02/99 1.94 bd 16.87 0.17 1.58 0.029 0.123 bd 0.282

3/3/99 1.59 bd 12.03 bd 0.87 0.089 0.334 0.064 0.846

31/03/99 0.83 bd 0.11 0.29 0.21 bd 0.045 bd bd

15/6/99 3.20 bd 16.26 2.77 2.36 0.246 bd bd 1.972

25/8/99 5.65 bd 18.77 2.04 4.50 0.366 4.390 1.030 1.041

13/9/99 3.20 bd 0.34 bd 3.15 0.165 2.330 0.956 bd

05/11/99 4.24 bd 3.02 1.07 1.21 0.383 0.145 0.237 2.189

29/11/99 1.16 bd 7.07 0.46 0.75 bd bd bd 0.411

Millaa Millaa Cl Br NO3 PO4 SO4 Mg Na Ca K

1/10/98 3.16 bd 0.09 bd 0.73 0.522 1.362 0.174 bd

9/11/98 3.83 bd 1.68 bd 0.55 0.207 1.876 0.217 0.515

9/12/98 2.34 bd 0.07 0.12 0.46 bd 0.874 bd bd

20/01/99 1.40 bd bd bd 0.09 bd 0.348 bd bd

15/02/99 1.26 bd 0.06 bd 0.21 0.015 0.152 bd bd

31/03/99 1.47 bd 0.07 bd 0.15 bd 0.090 bd 0.737

4/5/99 2.71 bd bd bd 0.45 0.043 1.077 bd bd

15/6/99 1.58 bd 0.03 bd 0.23 bd bd bd bd

15/7/99 1.61 bd 3.67 1.02 0.62 0.033 bd 0.294 0.491

25/8/99 4.21 bd 0.03 bd 0.34 0.044 0.105 bd bd

13/9/99 3.79 bd 0.04 0.25 0.27 bd 0.156 bd bd

5/11/99 4.54 bd bd bd 0.26 0.053 0.551 bd bd

29/11/99 2.82 bd bd bd 0.39 bd bd bd bd

276

AP

PE

ND

IX X

Min

era

logic

al

data

RE

SU

LT

S O

F Q

UA

NT

ITA

TIV

E A

NA

LY

SE

S O

F M

INE

RA

L P

HA

SE

S U

SIN

G S

IRO

QU

AN

TF

OR

SA

MP

LE

S F

RO

M B

OR

E 1

1000

128.

(res

ults

exp

ress

ed a

s w

t%)

Bo

re/s

am

ple

dep

thP

yro

xen

es1

Pla

gio

cla

seK

-fel

dsp

ar

Ka

oli

nit

eS

mec

tite

Qu

art

zM

usc

ov

ite

Oth

ers2

1100

0128

/ 6m

4.0

4.2

1.7

86.9

1.1

0.9

0.0

1.1(

Gd)

1100

0128

/ 19

m2.

99.

48.

573

.31.

81.

40.

02.

8(H

,Gd,

P)11

0001

28 /

23m

7.9

36.9

14.2

20.4

17.8

0.6

0.0

2.2

(H,G

d)11

0001

28 /

32m

13.1

33.9

10.3

17.8

20.0

0.6

0.0

4.2(

H,G

d,C

,S)

1100

0128

/ 39

m28

.040

.311

.913

.32.

80.

00.

03.

8(G

d,H

,C,S

)11

0001

28 /

43m

36.6

44.0

9.9

2.4

3.1

0.6

0.0

3.4(

H,G

d,S)

1100

0128

/ 50

m30

.651

.211

.32.

70.

70.

60.

02.

9(H

,Gd,

S)11

0001

28 /

52m

30.5

45.4

7.6

2.7

8.7

0.6

0.0

4.6(

H,G

d,G

t,S)

1100

0128

/ 58

m3

67.3

3.7

5.0

6.9

8.5

0.0

0.0

8.0(

Gt,G

b,G

d,H

,S,P

)11

0001

28 /

59m

371

.02.

67.

63.

34.

5tr

aces

0.0

11.2

(Gt,G

b,S,

Gd,

H)

1100

0128

/ 65

m39

.336

.48.

23.

28.

80.

60.

03.

5(G

d,H

,Gt,S

)11

0001

28 /

67m

37.2

44.7

6.8

3.5

4.9

trac

es0.

03.

0(G

d,G

t,H,S

,Gb)

1100

0128

/ 74

m37

.339

.05.

810

.24.

7tr

aces

0.0

3.0(

Gd,

H,G

t,Gb,

S)11

0001

28 /

78m

38.2

39.6

5.5

9.1

3.8

trac

es0.

03.

7(G

d,S,

H)

1100

0128

/ 82

m39

.440

.24.

310

.23.

2tr

aces

0.0

2.7(

Gd,

S,H

)11

0001

28 /

85m

12.2

13.1

2.7

16.8

29.2

26.0

0.0

0.0

1100

0128

/ 89

m0.

028

.811

.12.

30.

447

.010

.30.

0

1 d

iops

ide

and/

or a

ugit

e2 h

emat

ite

(H),

sid

erit

e (S

), g

oeth

ite

(Gt)

, gib

bsit

e (G

b), p

yrit

e (P

) an

d ze

olit

es s

uch

as g

otta

rdii

te/b

oggs

ite

(Gd)

and

cha

bazi

te(C

), li

sted

in o

rder

of

decr

easi

ng a

bund

ance

.3 a

ppro

xim

ate

valu

es a

s sa

mpl

e al

so c

onta

ins

smal

l am

ount

s of

ana

lcim

e, w

hich

is u

nqua

ntif

ied.

277

RE

SU

LT

S O

F Q

UA

NT

ITA

TIV

E A

NA

LY

SE

S O

F M

INE

RA

L P

HA

SE

S U

SIN

G S

IRO

QU

AN

TF

OR

SA

MP

LE

S F

RO

M B

OR

E 1

1000

133.

(res

ults

exp

ress

ed a

s w

t%)

Bo

re/s

am

ple

dep

thP

yro

xen

es1

Pla

gio

cla

seK

-fel

dsp

ar

Ka

oli

nit

eS

mec

tite

Qu

art

zM

usc

ov

ite

Oth

ers2

1100

0133

/ 8m

2.2

1.7

1.2

71.4

0.0

0.0

0.0

23.4

(H,G

b)11

0001

33 /

19m

17.7

27.6

18.5

26.6

1.4

trac

es0.

08.

2(C

,Gd,

H,S

,P)

1100

0133

/ 25

m27

.933

.110

.119

.8tr

aces

trac

es0.

09.

1(C

,H,G

d,P)

1100

0133

/ 32

m15

.952

.213

.612

.72.

1tr

aces

0.0

3.4(

H,G

d,P)

1100

0133

/ 36

m29

.148

.810

.07.

50.

8tr

aces

0.0

3.8(

S,G

d)11

0001

33 /

43m

25.2

52.2

11.1

9.0

0.8

0.0

0.0

1.7(

Gd,

P)11

0001

33 /

49m

29.4

44.1

10.2

11.5

trac

estr

aces

0.0

4.8(

Gd,

C,S

,H,P

)11

0001

33 /

50m

27.8

42.3

11.8

12.7

trac

estr

aces

0.0

5.3(

C,G

d,S,

H,P

)11

0001

33 /

54m

(ze

olite

)4.

522

.74.

955

.65.

31.

30.

05.

7(S,

C,G

d)11

0001

33 /

54m

9.4

47.9

18.2

16.9

5.2

1.1

0.0

1.1(

Gd)

1100

0133

/ 55

m (

zeol

ite)

7.3

327

.711

.540

.06.

21.

50.

05.

7(C

,Gd,

H,P

)11

0001

33 /

56m

6.7

329

.014

.036

.76.

41.

30.

05.

9(H

,C,G

d,P)

1100

0133

/ 58

m6.

229

.915

.035

.710

.2tr

aces

0.0

2.9(

H,G

d,C

,P)

1100

0133

/ 60

m5.

732

.214

.934

.010

.3tr

aces

0.0

2.9(

H,G

d,C

,P)

1 d

iops

ide

and/

or a

ugit

e2 h

emat

ite

(H),

sid

erit

e (S

), g

ibbs

ite

(Gb)

, py

rite

(P

) an

d ze

olit

es s

uch

as g

otta

rdii

te/b

oggs

ite

(Gd)

and

cha

bazi

te (

C),

lis

ted

in o

rder

of

decr

easi

ng a

bund

ance

.3 in

clud

es tr

aces

of

oliv

ine,

mos

t lik

ely

faya

lite

.

Not

e: S

ampl

es 1

1000

133

/ 54

m (

zeol

ite)

and

110

0013

3 /

55m

(ze

olit

e) w

ere

sele

ctiv

ely

sam

pled

to

dete

rmin

e ze

olit

e ph

ases

cle

arly

obse

rvab

le in

han

d sp

ecim

ens.

278

RE

SU

LT

S O

F Q

UA

NT

ITA

TIV

E A

NA

LY

SE

S O

F M

INE

RA

L P

HA

SE

S U

SIN

G S

IRO

QU

AN

TF

OR

SA

MP

LE

S F

RO

M B

OR

E 1

1000

136.

(res

ults

exp

ress

ed a

s w

t%)

Bo

re/s

am

ple

dep

thP

yro

xen

es1

Pla

gio

cla

seK

-fel

dsp

ar

Ka

oli

nit

eS

mec

tite

Qu

art

zM

usc

ov

ite

Oth

ers2

1100

0136

/ 16

m5.

325

.69.

443

.712

.51.

30.

02.

2(G

d,C

,S,P

)11

0001

36 /

19m

10.8

45.2

11.3

27.5

3.1

trac

es0.

02.

1(G

d)11

0001

36 /

29m

10.8

41.4

12.5

23.5

9.6

trac

es0.

02.

1(G

d)11

0001

36 /

33m

0.0

6.1

2.7

61.8

2.6

21.5

0.0

5.4(

H,G

d)11

0001

36 /

42m

2.6

16.1

9.1

30.1

39.5

0.6

0.0

2.0(

Gd)

1100

0136

/ 52

m10

.533

.911

.511

.827

.80.

60.

03.

9(G

d,H

,P)

1100

0136

/ 54

m7.

029

.111

.011

.836

.71.

20.

03.

2(G

d,H

,P)

1100

0136

/ 60

m19

.733

.710

.218

.914

.41.

50.

01.

7(G

d,C

)11

0001

36 /

68m

9.7

9.7

5.8

36.2

33.9

1.5

0.0

3.1(

Gd,

H,S

,C,P

)11

0001

36 /

69m

8.4

10.3

4.9

37.1

34.8

1.2

0.0

3.1(

Gd,

C,S

,H,P

)11

0001

36 /

79m

38.5

40.9

6.9

4.2

2.0

1.7

0.0

5.8(

Gd,

H,S

,P)

1100

0136

/ 86

m22

.419

.13.

323

.57.

15.

918

.80.

011

0001

36 /

91m

0.0

31.0

0.0

8.5

0.2

6.5

47.5

6.3

(Ch)

1 d

iops

ide

and/

or a

ugit

e2 h

emat

ite

(H),

sid

erit

e (S

), g

ibbs

ite

(Gb)

, py

rite

(P

), c

hlor

ite

(Ch)

and

zeo

lite

s su

ch a

s go

ttar

diit

e/bo

ggsi

te (

Gd)

and

cha

bazi

te (

C),

liste

d in

ord

er o

f de

crea

sing

abu

ndan

ce.

279

APPENDIX XI

Groundwater data sourced from the Queensland Department of Natural

Resources and Mines

Groundwater data provided by the Queensland Department of Natural Resources andMines (QDNR&M) has been used in this study, in conjunction with data generatedby the author (APPENDIX IX). Data sourced from QDNR&M has been used inwork presented in PAPERS 1A, 1B and 2, as well as in APPENDICES I, II, IV, Vand VI. Over 800 sets of groundwater chemistry analyses from 1950 to 1999 wereprovided by QDNR&M for the bores listed below. Most of these analyses are forbores sampled since 1990, with 25 % from bores sampled between 1990 and 1997,and 50 % from bores sampled during 1998 and 1999.

The data is publicly available by contacting the Senior Scientist, Resource Conditionand Trend, Resource Sciences and Knowledge, QDNR&M (Tel. (07) 3896 9816).

GROUNDWATER BORE NUMBERS

45004 45412 45542 45769 45835 45928 7818545155 45417 45544 45781 45837 45930 7818645156 45418 45547 45782 45840 45969 7818745159 45420 45549 45783 45841 45970 7818845170 45425 45612 45785 45846 45971 7819045201 45427 45629 45789 45847 45980 7819145365 45428 45645 45790 45852 45981 7819545366 45429 45647 45791 45853 72010 7820345367 45431 45655 45794 45854 72011 7828145368 45433 45656 45795 45855 72020 7830345371 45438 45659 45797 45857 72094 7842545375 45477 45660 45804 45858 72145 7844545380 45509 45661 45807 45859 72153 7875545381 45520 45675 45808 45861 72155 7876045396 45524 45678 45809 45863 72156 7877945397 45525 45679 45818 45865 72393 7879445399 45526 45680 45819 45866 72628 9237945400 45527 45692 45820 45869 72770 9254945403 45529 45693 45821 45870 72918 9259345404 45530 45703 45822 45875 78001 9259345405 45531 45715 45823 45888 78141 9266845406 45532 45717 45825 45889 78156 9267045407 45533 45720 45826 45891 78181 9267145410 45534 45725 45829 45910 78182 9267245411 45535 45726 45831 45916 78183 92673

280

GROUNDWATER BORE NUMBERS (continued)

92675 92739 92790 109053 109108 11000006 1100011892676 92740 92791 109054 109109 11000007 1100011992677 92741 92793 109059 109110 11000008 1100012092678 92742 92794 109061 109112 11000055 1100012592679 92743 92795 109062 109113 11000056 1100012692680 92744 92796 109063 109114 11000057 1100012792681 92746 92797 109064 109115 11000059 1100012892682 92748 92798 109068 109116 11000060 1100012992683 92749 92799 109069 109117 11000061 1100013092684 92750 99076 109073 109119 11000062 1100013192685 92751 109003 109076 109120 11000063 1100013292686 92752 109006 109077 109121 11000064 1100013392687 92753 109008 109078 109122 11000066 1100013492688 92754 109009 109082 109123 11000067 1100013592689 92755 109019 109083 109124 11000068 1100013692690 92757 109022 109085 109125 11000079 1100013792691 92758 109023 109086 109126 11000080 1100013892692 92760 109024 109087 109127 11000081 1100013992710 92761 109030 109088 109128 11000082 1100014092725 92763 109031 109089 109135 11000083 1120001292727 92764 109032 109090 109137 11000103 1120001392728 92765 109033 109093 109141 11000104 1120001892729 92766 109034 109096 109142 11000105 1120001992730 92767 109043 109098 11000001 11000114 1120014292731 92768 109045 109099 11000002 11000115 1120014492736 92776 109048 109102 11000003 11000116 11200145

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