Scenarios of groundwater chemical evolution in a region of the Canadian Shield based on multivariate statistical analysis

ContentslistsavailableatScienceDirect

Journal

of

Hydrology:

Regional

Studies

j ou rn a l h o m epa ge : w w w . e l s e v i e r . c o m / l o c a t e / e j r h

Scenarios

of

groundwater

chemical

evolution

in

a

region

of

the

Canadian

Shield

based

on

multivariate

statistical

analysis

Ombeline

Ghesquière

,

Julien

Walter,

Romain

Chesnaux,

Alain

Rouleau

Centred’étudessurlesressourcesminérales,UniversitéduQuébecàChicoutimi,555Boul.del’Université,

Chicoutimi,Québec,CanadaG7H2B1

a

r

t

i

c

l

e

i

n

f

o

Received6February2015 Receivedinrevisedform7June2015 Accepted8June2015

Availableonline21July2015 Keywords:

Hierarchicalclusteranalysis

Factoranalysis

Regionalhydrogeochemistry

CanadianShield

Quaternarysediments

a

b

s

t

r

a

c

t

Studyregion:Thestudyofgroundwaterchemistryofthe Charlevoix/Haute-Côte-Nord(CHCN)regionintheprovinceofQuebecinCanadaispartofaregional hydrogeologicalcharacterizationproject.

Studyfocus:Groundwaterwassampledin113wellsoverthe4500km2_study

areaandanalyzedfor39parametersincludingmajor,minor,traceandinorganic constituents,plusstableisotopes2Hand18O.Twomultivariatestatistical meth-ods,hierarchicalclusteranalysis(HCA)andR-modefactoranalysis(RFA)were combinedwithgraphicmethodstoclassifythesamplesaccordingtoplausible levelsofgroundwaterevolutioninthatregion.

Newhydrologicalinsightsfortheregion:Foursampleclusterswereidentified. Cluster1iscomposedoflow-salinityCa-HCO3groundwatercorrespondingto

recentlyinfiltratedwaterinsurfacegranularaquifersinrechargeareas.Cluster 4Na-(HCO3-Cl)groundwaterismoresalineandcorrespondstomoreevolved

groundwaterprobablyfromconfinedbedrockaquifers.Cluster2andCluster3 (Ca-Na)-HCO3andCa-HCO3 groundwater,respectively,correspondtomixed

orintermediatewaterbetweenCluster1andCluster4frompossibly inter-connectedgranularandbedrockaquifers.Thisstudyidentifiesgroundwater recharge,water–rockinteractions,ionexchange,solutediffusionfrommarine clayaquitards,saltwaterintrusionandalsohydraulicconnectionsbetweenthe CanadianShieldandthegranulardeposits,asthemainprocessesaffectingthe hydrogeochemicalevolutionofgroundwaterintheCHCNregion.

©2015TheAuthors.PublishedbyElsevierB.V.Thisisanopenaccessarticle undertheCCBY-NC-NDlicense(http://creativecommons.org/licenses/ by-nc-nd/4.0/).

∗ Correspondingauthor.Tel.:+14188158671.

E-mailaddresses:ombeline.ghesquiere1@uqac.ca(O.Ghesquière),julienwalter@uqac.ca(J.Walter),

romainchesnaux@uqac.ca(R.Chesnaux),alainrouleau@uqac.ca(A.Rouleau).

http://dx.doi.org/10.1016/j.ejrh.2015.06.004

2214-5818/©2015TheAuthors.PublishedbyElsevierB.V.ThisisanopenaccessarticleundertheCCBY-NC-NDlicense

1. Introduction

ThechemistryofgroundwaterintheCanadianShieldanditsevolutionwithdepthorwith dis-tancealongaflowpathhavebeeninvestigatedbynumerousauthors,namelyGascoyneandKamineni (1994).Recentandshallowgroundwaterchemistryiscontrolledbythecompositionofthelocalrock, wheredissolutionreactionsdominate,whileitsisotopiccompositionreflectstheprecipitation.In con-trast,thechemistryofdeepergroundwateristheresultofextensive,long-terminteractionswiththe bedrock(Frapeetal.,1984).Anumberofstudies(e.g.MelloulandCollin,1992;GülerandThyne,2004; Silva-Filhoetal.,2009)haveshownthatthehydrogeologicalcontext,combinedwith hydrogeochem-icalandisotopiccharacterizationofanaquifercanhelptoidentifydifferenttypesofgroundwater (Ca-HCO3,Na-HCO3andNa-Cltypes)aswellasthemainfactorsthatinfluencethechemical compo-sitionofgroundwater.Otherstudies(Cloutieretal.,2008;Beaudry,2013;Montcoudioletal.,2014) havedemonstratedasignificantcorrelationbetweenthehydrogeologicalcontextandthe groundwa-terchemistryinregionsoftheCanadianShield.Characterizingthehydrogeologicalcontextinparallel withthehydrogeochemicalandisotopicstudyofgroundwaterallowsabettercharacterizationof groundwaterflowandoftheevolutionofitschemicalcomposition.

Güleretal.(2002)showedthatthecombinationofgraphicalandmultivariatestatisticaltechniques providesaconsistentandobjectivemeansofclassifyinglargenumbersofsampleswhilestill preserv-ingtheeaseofclassicgraphicalrepresentations.Cloutieretal.(2008),Yidana(2010)andMontcoudiol etal.(2014)usedmultivariatestatisticalanalysistosupplementgraphicalrepresentationssuchas Schoeller,Stiff,DurovandPiperdiagrams.Usingastatisticalapproach,theysuccessfullyidentified majorgroundwatergroupsandfactorsaffectingthegroundwaterchemistryinanaquifer.

The main objective of this research is to characterize groundwater chemistry and to iden-tify the relationships between the hydrogeological context and groundwater chemistry in the Charlevoix/Haute-Côte-Nord(CHCN)regionbyusingacombinationofmultivariatestatisticalanalysis, graphicalrepresentationsandmaps.“Hierarchicalclusteranalysis”(HCA)and“R-modefactor anal-ysis”(RFA)arecombinedwithgraphicalanalysisusingDurovandStiffdiagramstodevelopabetter understandingofthegroundwaterchemistryanditsevolutionintheCHCNaquifersystemlocatedin theCanadianShield.

2. Studyarea

In 2008, the Government of Quebecimplemented the Programme d’acquisition de connais-sancessurleseauxsouterraines(PACES;GroundwaterKnowledgeAcquisitionProgramme)under theMDDEFP(MinistèreduDéveloppementDurable,del’Environnement,delaForêtetdesParcs),in ordertoimproveknowledgeofthisresource(GovernmentofQuebec,2015a,b).Thisprogramme con-sistsofanumberofregionalhydrogeologicalcharacterizationprojectsaimingtoacquireknowledge ongroundwaterresourcesinthesouthern,moredenselyinhabitedpartsoftheProvinceofQuebec, withtheobjectivesofprotectinggroundwaterandensuringthesustainabilityofitssupply(Chesnaux etal.,2011).

A regional hydrogeologicalcharacterization project, conducted by the Centre d’études sur les ressourcesminérales(CERM)atUniversitéduQuébecàChicoutimi(UQAC),startedin2012intheCHCN regionaspartofthePACESprogramme.Eventhoughongoingindustrialandagriculturaldevelopment presentsariskforgroundwatercontaminationinthisregion,noregionalhydrogeological charac-terizationprojecthadyetbeencarriedout.Thissituationcallsforapropercharacterizationofthe naturalgeochemicalpropertiesofgroundwaterandabetterunderstandingofthenaturalgeochemical processesthataffectthegroundwaterchemistryduringitsevolutionintheaquifersystems.

TheCHCNregionislocatedonthenorthshoreoftheSaint-LawrenceRivertothenortheastof Quebeccity(Fig.1).ThestudyregionformsanNEelongatedstretchoflandextendingover236km, approximately20kmwide,foratotalareaof4500km2_{.Theclimateoftheregionischaracterizedby} longandcoldwinters,followedbyshort,warmandhumidsummers.Precipitationiswelldistributed throughouttheyear,mostlyinsnowfromNovembertoApril,andtotallingaround900mmperyear (GovernmentofQuebec,2015a,b).Thevegetationismainlycomposedofdeciduousandmixedtree stands.Mostoftheterritoryisforested;partsofitareexploitedbytheforestryindustry.

Fig.1.LocationandprincipalstructuralfeaturesoftheCHCNregion,Quebec,Canada.

AnimportantphysiographicfeatureistheWNW-trendingSaguenayFjordthatseparatesthestudy areaintwoparts:theCharlevoixsubregiontothesouth-westandtheHaute-Côte-Nordsubregionto thenorth-east(Cousineauetal.,2014).ThetopographyoftheCharlevoixsubregionischaracterizedby ameteoricimpactcraterdatedat372–335Ma,calledthe“Charlevoixmeteorcrater”(Rondot,1968). TheMontdesÉboulementscentraluplift,relatedtothemeteorcrater,isboundedbynormalfaultsand surroundedbyannularliftsanddepressions,suchasthevalleysofBaieSt.PaulandLaMalbaie,where thetopographyflattensandelevationsdecreasetosealevel(Rondot,1998).TheCharlevoixsubregion liesalongtheSt.Lawrenceriftsystemandisaseismicallyactivezone.TheCHCNregionismarkedby numerousnormalfaultswhichwereinitiatedorreactivatedduringvarioustectonicevents.Manyof thesenormalfaultsareconsideredtobestillactive(Fig.1).

3. Geologicalandhydrogeologicalfeatures

TheCHCNregionislocatedattheboundarybetweenthreegeologicalprovincesofeasternCanada; itisconstitutedof:(i)crystallinerocksoftheGrenvilleProvinceoftheCanadianShield,(ii)alower PaleozoicsedimentarysuccessionoftheSt.LawrencePlatform,and(iii)unitsofdeformedand trans-portedrocksoftheAppalachianorogentothesoutheast.ThebasementiscomprisedofProterozoic rockssuchasintrusiveigneousrocksandhigh-grademetamorphicrocks.TheGrenvillianrocksofthe Charlevoixareaaremainlycomposedofhigh-gradeorthogneissesandparagneisses,charnockites, andanorthositicandgraniticintrusions(Lemieuxetal.,2003).IntheHaute-Côte-Nord,Grenvillian rocksincludemigmatiteandgabbro.TheGrenvillebasementisoverlainbyLowerPaleozoic siliciclas-ticrocksoftheSt.LawrencePlatformjuxtaposedagainstaccretedunitsoftheAppalachianorogene (Lemieuxetal.,2000).

ThesedimentaryrockunitsofthestudyareaarerarelyexposedbecauseoftheQuaternary sedi-mentsthatoverlaythem.Quaternarysurfacesedimentsmainlyconsistofatilllayer,butglaciomarine, glaciofluvial,lacustrineandalluvialsedimentsarealsopresent.Tilldepositscanreachathicknessof 10mandlieunconformablyonrock.IntheHaute-Côte-Nord,thereisalargerproportionofcoastal glaciomarinesedimentsthaninCharlevoix,duetothelargecoastalareaandthegreatextentofthe deltaicsystems.Thinglaciomarinesedimentssuchassilty andclay-richdepositscanreachmore than100minthickness,whilecoastalanddeltaicsilty-sandorsanddepositsvaryfrom1to20min thickness(Cousineauetal.,2014).

BedrockaquifersprovidemostofthedrinkingwaterintheCharlevoixsubregion,whiletheresource ismostlypumpedfromsuperficialgranularaquifersintheHaute-Côte-Nordsubregion.A predomi-nanceofunconfinedaquiferscanbeidentifiedintheCharlevoixsubregion.TheChamplainSeainvasion thatoccurred10,000yearsagointhesoutheasternpartoftheCanadianShieldisstillaffecting ground-waterqualityinaquiferslocatedinareasthatwerecoveredbythatsea(Cloutieretal.,2008;Walter, 2010;Beaudry,2013;Montcoudiolet al.,2014).Silicateweathering,carbonatedissolution,Ca/Na cationexchangeandmixinghavebeenidentifiedasthemainprocessescontrollingthechemical evo-lutionofgroundwaterinthisarea(Cloutieretal.,2008;Walter,2010;Beaudry,2013;Montcoudiol etal.,2014).

4. Methodology

4.1. Hydrogeochemicaldataset

Atotalof113wells(Fig.2),distributedovertheentirestudiedareaandatamaximumdepthof approximately170m,weresampledusingasamplingprotocoldescribedinCERM-PACES(2013).The typeofaquiferintersectedbyeachsampledwell,i.e.,eitherbedrock(n=60)orQuaternarydeposits (n=53),andthewelldepthweredeterminedusingdatafromdrillingreports.Insitufield measure-mentswereconductedfor severalparameters suchastemperature(T),pH,redox potential(Eh), dissolvedoxygen(DO)andtotaldissolvedsolids(TDS).Groundwatersampleswereanalyzedfor39 parameters(Table1)includingmajor,minor,sometraceandinorganicconstituents,plusthestable isotopesdeuterium2_Hand 18_{O.Theion-balanceerrorwascalculated inordertoverifythe} elec-troneutralityofthesamples.Basedonthisdata,105samplesoutofthe113samplescollectedwere selectedforstatisticalanalysis(8sampleswererejectedastheypresentedanion-balanceerrorabove ±10%).

4.2. Graphicalanalysis

Twographicalmethodsareusedtosortgroundwatergeochemistrysamplesintogroups:theDurov diagram(Durov,1948)andtheStiffdiagram(Stiff,1951),usingthesoftwareAquachem5.0(Waterloo HydrogeologicInc.,2005).

TheDurovdiagramdisplaystherelativeconcentrationsofthemajorcationsandanionsontwo separatetrilinearplotstogetherwithacentralsquareplotwherethepointsfromthetwotrilinear

Fig.2.Locationofthesamplingsitesindicatingtheaquifertypeintersectedbythesampledwells.

plotsareprojected.Mostofthe105groundwatersamples(Fig.3;Table2)areCa-HCO3watertype (n=80).TheremaininggroundwatersamplesareNa-HCO3 (n=13),Na-Cl(n=11)andCa-Cl(n=1) watertypes.

TheStiffdiagramisapolygoncreatedfromthreeparallelhorizontalaxesextendingoneitherside ofaverticalzeroaxis.Cationsareplottedtotheleftoftheaxisandanionstotheright,inunitsof milliequivalentsperlitre(meq/L)(Güleretal.,2002).TheStiffdiagramallowsavisualcomparisonof waterswithdifferentcharacteristics.Sincethepatterntendstomaintainitsshapeuponconcentration ordilution,theStiffdiagramalsoallowsthetracingofflowpaths(Güleretal.,2002).TheStiffdiagram isparticularlyusefulforcomparingresultsfrommanysamplesincombinationwithamultivariate statisticalanalysis,aspresentedbelow.

Table1

Chemicalparametersanalyzedinthelaboratory.

Isotopes ␦2_{H ␦}18_O

Dissolvedmetals

Aluminium(Al) Magnesium(Mg)

Antimony(Sb) Manganese(Mn)

Silver(Ag) Molybdenum(Mo)

Arsenic(As) Nickel(Ni)

Barium(Ba) Lead(Pb)

Beryllium(Be) Potassium(K)

Bismuth(Bi) Selenium(Se)

Boron(B) Silicon(Si)

Cadmium(Cd) Strontium(Sr)

Calcium(Ca) Sodium(Na)

Chromium(Cr) Uranium(U)

Cobalt(Co) Tin(Sn)

Copper(Cu) Titanium(Ti)

Iron(Fe) Vanadium(V)

Lithium(Li) Zinc(Zn)

Anions Bromine_Chlorine(Br)_(Cl) Nitrites_Sulphateand_(SOnitrates(N)

4) Others

Ammoniacalnitrogen(N-NH3) Sulphur(S)

Inorganicphosphorus Totalalkalinity

Fluorine(F)

Fig.3. Durovdiagramofthe105groundwatersampleslabelledaccordingtotheaquifertype.Thecentralsquareplotofthe Durovdiagramisdividedintofoursquarestoidentifythemaingroundwatertypes.

Table2

Numberofgroundwatersamplesfrombedrockaquifersandfromgranularaquifersforeachwatertype.

Ca-HCO3 Na-HCO3 Ca-Cl Na-Cl

R 48 8 1 5

G 32 5 0 6

Table3

Parametersexcludedforthemultivariatestatisticalanalysis.

Parametersexcluded Reasonfortheexclusion

EC,TDS,pH,Eh Parameterswithadditivecharacteristics

Temperature Physicalparameter

DO,␦2_H,␦18_{O Parameterswithlowregionalvariations}

Totalalkalinity ParameterlinkedtoHCO3−concentration

Al,Sb,Ag,As,Ba,Be,Bi,B,Cd,Cr,Co,Cu,Sn,Fe,Li,Mn, Mo,Ni,Pb,Se,U,Ti,V,Zn,N-NH3,Br,F,N,P

Parameterswithmorethan15%ofthesamplesbelow thedetectionlimit

Table4

Descriptivestatisticsforthe105groundwatersamples(concentrationsinmg/L).

Parameter Mean(x) Median Minimum Maximum Standarddeviation(s) Skewness

Ca2+ _{18.673 16.000 1.700 110.000 17.276 2.712} Mg2+ _{3.165 2.100 0.200 25.000 3.698 3.839} K+ _{1.676 0.850 0.055 13.000 2.074 2.916} Si4+ _{6.494 5.900 0.220 16.000 2.446 1.188} Sr2+ _{0.190 0.095 0.013 2.600 0.383 5.076} Na+ _{23.815 5.200 1.000 540.000 63.322 5.961} HCO3− 81.786 62.220 3.660 634.400 85.622 3.712 Cl− 25.418 2.700 0.300 550.000 73.658 4.887 SO4− 8.037 5.000 0.275 150.000 15.322 7.925

4.3. Datapreparationforthemultivariatestatisticalanalysis

Themultivariatestatisticalanalysisisanapproachtogroundwaterclassificationthatallowsthe definitionofdistinctgroupsofgroundwatersamples,aswellascorrelationsbetweenchemical param-etersandgroundwatersamples(Cloutieretal.,2008).Thehierarchicalclusteranalysis(HCA)and theR-modefactoranalysisinprincipalcomponents(RFA)areappliedhereusingthesoftware Sta-tisticaversion12(StatsoftInc.,2013).Thedatapreparationformultivariatestatisticalanalysisis based ontheapproach usedby Cloutieretal.(2008); severalparameterswere excludedforthe analysis,asexplainedinTable3(Sanfordetal.,1993).Themultivariatestatisticalanalysisisthus appliedtoasubgroupofthecompletehydrogeochemicaldataset.Thedatasetusedinthisanalysis constitutesadatamatrixof105samplingsites(observations)byninechemicalparameters (vari-ables).ThenineselectedparametersincludethemajorconstituentsCa2+_,Mg2+_,Na+_,K+_,HCO

3−,Cl−, SO42−andtheminorconstituentsSr2+andSi4+.Forthemultivariatestatisticalanalysis, concentra-tionvalueslowerthanthedetectionlimitweresetat0.55timesthedetectionlimit(Güleretal., 2002).

Allthe parameters except Si4+ _{are highly positivelyskewed and theirfrequency distribution} inmg/Ldoesnotfollow anormaldistribution(Table4).Thus, eachchemicalparameterwas log-transformed exceptSi4+_{.Allthevariables were thenstandardized totheir standardscores Zias} follows:

Zi= (xi−x)

s (1)

whereZ=standardscoreofthesamplei,xi=valueofsamplei,x=meanands=standarddeviation (Davis,1986).Thestandardizationisappliedtoensurethateachvariablehasequalweightinthe statisticalanalyses.

4.4. Hierarchicalclusteranalysis

Hierarchicalclusteranalysis(HCA)isthemostwidelyappliedclusteringtechniqueinEarth Sci-encesandisoftenusedfortheclassificationofhydrogeochemicaldata(Cloutieretal.,2008).The

agglomerativeprocedurestartswithasmanyclustersasobjects(orindividuals).Theclustersare thensuccessivelymerged,accordingtotheirsimilarity,untilonlyoneremains(Templetal.,2008). Thisagglomerativeprocedureallowstoclassifylargeamountsofhydrogeochemicaldataintoseveral groups basedonspecificcharacteristics(Lambrakisetal.,2004).In thisstudy,theEuclidean dis-tancewaschosenasthedistanceorsimilaritymeasurebetweensamplingsites,incombinationwith Ward’smethod(Ward,1963)asthelinkagerule,whichmergesclusterswithaminimum informa-tionlosscriteriabasedonsumsofsquares(Templetal.,2008).Güleretal.(2002)havesuggested thatusingEuclideandistanceasthesimilaritymeasure,togetherwithWard’smethodasthelinkage rule,producesthemostdistinctivegroups.AnumberofotherstudieshavealsousedWard’smethod asthelinkagerule(Lambrakisetal.,2004;Cloutieretal.,2008;Templetal.,2008).Thelevelsof similarityatwhichobservationsarejoinedareusedtoconstructatreediagram,oradendrogram (Davis,1986).Avisualobservationofthedendrogramallowsthegroupingofsamplesintoclusters. Thecharacteristicsofeachclustercanbedeterminedusingdescriptivestatisticsandgraphical meth-ods.Therelationsbetweentheclusterscanbeinterpretedincorrelationwiththehydrogeologicaland geologicalcontexts.

TheHCAwascarriedoutusingtheclusteranalysismoduleintheMultivariateExploratory Tech-niquesoftheStatisticasoftwareversion12.0.Theinputfilecontainstherawdataconsistingof105rows (samples)by9columns(chemicalparameters).Theclusteringofcases(rows)wasselectedtocluster thesamples,whiletheclusteringofvariables(columns)wasusedtoclusterchemicalparameters. Joining(treeclustering)wasselectedastheclusteringmethod.

4.5. R-modefactoranalysis(RFA)

TheR-modefactoranalysis(RFA)isamultivariatestatisticaltechniqueusedfordatareduction andfordecipheringpatternswithinlargesetsofdata(Farnhametal.,2003).Oncethepatternof the datasetis determined,it maybe compressedby reducing thenumber of dimensions, with-out losing significant information. With RFA, the data matrix is reduced to factor scores and loadings. Acorrelationmatrix isgenerally usedsothateach variableis normalizedtounit vari-ance and therefore contributes equally tothefactor analysis(Farnham etal., 2003; Chenet al., 2007).

Theextractionoffactorswasconductedonasymmetricalcorrelationmatrixcomputedforthe ninevariables.ThisistheR-modetechnique,usedtoinferrelationshipsbetweenvariables(Davis, 1986).Factorsare thuscalculated sothat theytakeinto accountthecorrelations present inthe originaldata,butareuncorrelated tooneanother.Thefirstfactorexplainsthelargestportionof thevarianceoftheoriginaldata,andeachsubsequentfactorexplainsprogressivelyless(Farnham etal.,2003).Thedatacanbereducedtotwoorthreefactorsexplainingthemajorityofthe vari-ancewithintheoriginaldataset(Farnhametal.,2003;Chenetal.,2007),andarotationfactorcan beappliedtomaximizethevarianceoftheretainedfactors.Inthisstudy,thenumberoffactorsto bekeptwasbasedontheKaisercriterion,whichselectsonlythefactorswitheigenvaluesgreater than1(Cloutieretal.,2008).ThemethodusedwastheVarimaxnormalizedrotation,asinthe anal-ysesconductedbyMelloulandCollin(1992),Cloutieretal.(2008)andMontcoudioletal.(2014). Theloadingswerethenevaluatedtoidentifytheelementsthatareresponsibleforthese correla-tions.Elementswiththegreatestpositiveandnegativeloadingsmakethelargestcontribution.The loadingscanthereforebeexaminedtoprovidefurtherinsightintotheprocessesthatare respon-sibleforthevariation ingroundwatergeochemistry(Farnhametal.,2003).Thefactor scoresfor eachgroundwatersamplecanalsobeplotted andtheplotsinspectedforsimilarities(Chenetal., 2007).

TheRFAwascarriedoutusingtheFactorAnalysismoduleintheMultivariateExploratory Tech-niquesof Statisticaversion12.0. TheinputfiledatasetisthesameasfortheHCA.Theprincipal componentsareselectedbased ontheextractionmethodandtheminimumeigenvalueis setto 1, according to the Kaiser criterion. Varimax normalized is finally selected as the rotation fac-tor.

Fig.4.DendrogramandStiffdiagramsresultingfromtheHCAforthe105groundwatersamples,showingthedistributionof

thesesamplesintofourclusters,eachhavingitsowncharacteristicwatertype.Foreachclusterarealsoshownatthe“Elevated

conc.”linethoseminorandtraceconstituentsforwhichtherewasthehighestmeasuredconcentration.Stiffdiagramsare

constructedbasedonthemedianvaluescalculatedforeachcluster.

5. Results

5.1. Hierarchicalclusteranalysis(HCA)

Theclassificationofthesamplesintoclustersisbasedonavisualinspectionofthedendrogram (Fig.4).Bymovingthepositionofthephenon-lineupordownonthedendrogram,onecandefinea greateroralessernumberofclusters(Güleretal.,2002).Inthisstudy,thephenon-linewasdrawn acrossthedendrogramatalinkagedistanceof15.Sampleswithalinkagedistancelowerthan15 arethusgroupedintothesamecluster.Thisallowsadivisionofthedendrogramintofourclustersof groundwatersamples.

Table5

Geochemicalandphysicalcharacteristicsofeachcluster(medianconcentrationsinmg/L).

Parameters Cluster1 Cluster2 Cluster3 Cluster4

N N=22 N=38 N=24 N=21

ChemicalparametersusedintheHCA

Ca2+ _{4.90 15.50 19.00 29.00} Mg2+ _{1.05 1.75 3.15 6.80} Na+ _{2.20 4.85 4.95 56.00} K+ _{0.60 0.60 1.35 3.20} HCO3− 21.35 54.90 73.81 146.40 Cl− _{0.90 2.55 2.35 52.00} SO42− 1.65 5.00 7.00 10.00 Si4+ _{6.15 5.25 7.15 6.50} Sr2+ _{0.03 0.09 0.16 0.24}

Otherchemicalparameters

Ba2+ _{0.00 0.00 0.00 0.02} B3+ _{0.01 0.01 0.01 0.05} Cu2+ _{0.00 0.00 0.00 0.00} Mn2+ _{0.00 0.00 0.00 0.02} Mo2+ _{0.00 0.00 0.00 0.00} Pb2+ _{0.00 0.00 0.00 0.00} Zn2+ _{0.01 0.00 0.01 0.01} Totalalkalinity 17.50 45.00 60.50 120.00 N-NH3 0.01 0.02 0.03 0.06 F− 0.06 0.20 0.10 0.40 Stableisotopes ␦2_{H(VSMOW) −84.17 −87.24 −90.13 −86.29} ␦18_{O(VSMOW) −12.01 −12.35 −12.77 −12.25} Physicalparameters Temperature(◦_{C) 8.94 7.68 7.35 7.63} pH 6.19 7.63 7.26 7.61 DissolvedO2 8.31 3.65 0.63 0.00 TDS 24.50 61.00 71.50 215.00 Welldepth(m) 2.75 65.00 45.50 54.00

N,numberofsamples;boldvalues:highestvalues;underlinedvalues:lowestvalues.

Thedendrograminspectionprovidessomeindicationofthelevelofsimilaritybetweenthefour clusters(Fig.4).ThelinkagedistancebetweenCluster4andthethreeotherclustersiselevated(61), whichindicatesthatgroundwatersamplesinCluster4areclearlyandgeochemicallydistinctfrom thegroundwatersamplesofthethreeotherclusters.Amongthesethreeclusters,Cluster1istheleast similarwithahighlinkagedistance(43)toCluster2andCluster3.Cluster2andCluster3havethe lowestlinkagedistance(16)ofthefourclustersandhavethegreatestsimilarityamongallclusters.It canthereforebeexpectedthatthegeochemistryofthegroundwatersamplesofCluster2andCluster 3wouldpresentsomesimilarity.

Toevaluatethecharacteristicsofeachclusterofgroundwatersamples,Table5presentsthemedian valuesofgeochemicalandphysicaldata,includingthe9chemicalparametersusedintheHCA,aswell as10minorandtraceconstituents,stableisotopes␦2_Hand␦18_{O,temperature,pH,dissolvedoxygen,} TDSandwelldepth.Only10ofthe30otherminorandtraceconstituentsanalyzedinthelaboratoryare includedinthistablebecausethemedianconcentrationsoftheremainingconstituentsareidentical foreachclusterofsamplesand,therefore,appearirrelevanttoourstudy.Minorandtraceconstituents withelevatedmedianconcentrationsareindicatedinFig.4.Stiffdiagramsforeachclusterbasedon themedianvaluescalculatedforeachclusterarealsopresentedinFig.4.StiffdiagramsforCluster1, Cluster2andCluster3haveasimilarshapewithCa2+_andHCO

3−asthedominantions,whereasthe StiffdiagramforCluster4showsadistinctiveshape,withNa+_,HCO

3−andCl−asthedominantions. Table6presentsthenumberofCa-HCO3,Na-HCO3,Ca-ClandNa-Clwatertypesamplesfrombedrock aquifersandfromgranularaquifersforeachcluster,basedonthepreviousinspectionoftheDurov diagram.

Table6

NumberofgroundwatersamplesineachclusterofCa-HCO3,Na-HCO3,Ca-Cl,andNa-Clwatertypes,frombedrockaquifersand

fromgranularaquifers.

Cluster1 Cluster2 Cluster3 Cluster4

R G R G R G R G Ca-HCO3 1 16 22 8 16 7 9 1 Na-HCO3 0 3 3 2 0 1 2 2 Ca-Cl 0 0 1 0 0 0 0 0 Na-Cl 0 2 0 2 0 0 5 2 Total 1 21 26 12 16 8 16 5

R,bedrockaquifer;G,granularaquifer. Table7

FactorloadingsandexplainedvarianceforthethreefactorswithVarimaxnormalizedrotation.

Parameters Factor1 Factor2 Factor3

Ca2+ _{0.90 0.06 0.15} Mg2+ _{0.67 0.45 0.42} K+ _{0.17 0.85 0.14} Si4+ _{0.10 0.04 0.96} Sr2+ _{0.86 0.23 0.09} Na+ _{0.29 0.90 -0.03} HCO3− 0.76 0.39 0.08 Cl− _{0.28 0.88 0.02} SO42− 0.68 0.39 -0.20 Explainedvariance 3.23 2.86 1.20 Explainedvariance(%) 0.36 0.32 0.13 Cumulative%ofvariance 0.36 0.68 0.81

Boldvalues:loadings>0.67.

TheCluster1samples(n=22)aremainlyoftheCa-HCO3 watertypeandarecharacterizedby elevatedconcentrationsofPb2+_,Zn2+_{anddissolvedoxygen.TheCluster1samplesalsohavethelowest} pHandthelowestTDSvaluesofallclusters.TheCluster2samples(n=38)aremainlyofthe (Ca-Na)-HCO3 watertypeandarecharacterizedbyelevatedconcentrationsofCu2+,andbythelowest concentrationsofSi4+_{ofallclusters.TheCluster3samples(n=24)areoftheCa-HCO}

3watertypeand arecharacterizedbythehighestconcentrationsofSi4+_{ofalltheclusters.TheCluster2andCluster3} samplesshowanumberofsimilarities,includingtheTDSmedianvalue,buttheCluster3sampleshave higherconcentrationsofMg2+_,K+_,HCO

32−,andSr2−thanCluster2samples.TheCluster4samples (n=21)areoftheNa-(HCO3-Cl)watertypeandarecharacterizedbyelevatedconcentrationsofBa2+, B3+_,Mn2+_,Mo2+_,N-NH

3andF−,aswellasthelowestconcentrationsofCu2+anddissolvedoxygenof allclusters,andthehighestTDSvaluesofallclusters.Ninety-fivepercentofCluster1groundwater samplesarefromshallowgranularaquifers,whereas76%ofCluster4groundwatersamplesarefrom deeperbedrockaquifers.TheCluster2andCluster3samplescontaingroundwaterfrombothshallow anddeep,granularandbedrockaquifers.

5.2. R-modefactoranalysis(RFA)

TheRFAallowedtheextractionofninefactors.Onlythefirstthreefactorshaveeigenvaluesgreater than1;aVarimaxnormalizedfactorrotationwasappliedinordertomaximizethevariance.The firstthreefactorsaccountfor81%ofthetotalvarianceinthedataset.Thefactorloadingsforthefirst threefactorsandtheirrespectiveexplainedvariancearepresentedinTable7.Thefirsttwofactors, respectively,explain35.9%and31.8%ofthevariance,andthereforeexplainmostofthevariancein thedataset,whilefactor3explains13.3%ofthevarianceinthedataset.

Fig.5showsthepositionoftheloadingsofchemicalparametersinaplanedefinedbytheaxesof Factors1and2(a),andinaplanedefinedbytheaxesofFactors1and3(b).Theseplotshelptoidentify whichchemicalparametersareassociatedwitheachfactor.Factor1explainsthegreatestamountof

Fig.5. PlotoftheloadingsforFactor1andFactor2(a)andforFactor1andFactor3(b)withVarimaxnormalizedrotation.

PlotofthefactorscoresforFactor1andFactor2(c)andforFactor1andFactor3(d)withthegroundwatersampleslabelled

accordingtotheirrespectiveclusters.

thevariance,andischaracterizedbyhighlypositiveloadingsinCa2+_,Sr2+_andHCO

3−.Theloadingis alsohighforSO42−andMg2+(Fig.5a).BecauseoftheassociationofCa2+andMg2+,Factor1isdefined asthe«hardness»factor(Cloutieretal.,2008).Factor2ischaracterizedbyhighlypositiveloadingsin Na+_,Cl−_andK+_{(Fig.5a).Factor2isthusdefinedasthe«salinity»factor.Factor3ischaracterizedbya} veryhighlypositiveloadinginSi4+_(Fig.5b).

RFAresultsareconsistentwiththeHCAresults,asillustratedinFig.5.Thefactorscoresrepresent theinfluenceofthefactoronthegroundwatersamples(Cloutieretal.,2008).Thedistinctionbetween clustersofsamplesisclearwhenplottingscoresforFactor1versusFactor2(Fig.5c).Cluster1samples arelocatedonthemiddle-leftsideoftheplot,whereasCluster4samplesarelocatedontheupperright side.Cluster2andCluster3samplesarelocatedinthemiddleoftheplotandcannotbedifferentiated accordingtothesefactors.ThedistinctionofCluster2andCluster3samplesishoweverpossible whenplottingscoresforFactor1versusFactor3(Fig.5d).Cluster1samplesarecharacterizedby mediumtohighnegativescoresforFactor1,lownegativescoresforFactor2,andmediumnegativeto highpositivescoresforFactor3.MostCluster2samplesarecharacterizedbylowpositivescoresfor

Fig.6. Plotof␦18_{OVSMOWversus␦}2_{HVSMOW,withthegroundwatersampleslabelledaccordingtotheirrespectivecluster.}

TheGlobalMeteoricWaterLineandtheisotopiccompositionofseawaterareindicated.

Factor1,mediumnegativetolowpositivescoresforFactor2andnegativescoresforFactor3.Some end-membersofCluster2havehighnegativescoresforFactor1incontrasttohighpositivescores forFactor2.Cluster3sampleshavepositivescoresforFactor1andlownegativescoresforFactor2 andlownegativetohighpositivescoresforFactor3.MostofCluster4sampleshavemediumtohigh positivescoresforFactor1andFactor2,andmediumnegativetohighpositivescoresforFactor3.

5.3. Stableisotopesı2_Handı18_O

ThedistributionofthesamplesinFig.6followstheGlobalMeteoricWaterLine,ascalculated byCraig (1961),towardsseawaterisotopiccomposition (␦2_{H=−5‰and ␦}18_{O=0‰).Thisreflects} mixingbetweenseawaterandmeteoricwater(Walter,2010),andindicatesthatgroundwaterwas notaffectedbyevaporationprocesses.Nodistinctionofisotopiccompositioncanbeobservedbased ontheclusterizationofthesamples.Becauseofthisalignment,wecanstatethatallgroundwater sampledforthisstudyhasacommonorigin,i.e.,itisrechargewatercommonlyfoundintemperate

tocoldclimates.Thecalculationofthemedianvaluesforstableisotopes(Table5),however,allowsa distinctionsincetheCluster3samplesareslightlyenrichedin␦2_H.

6. Interpretationanddiscussion

HCAallowsgroupingthe105groundwatersamplesintofourclusters.TheTDSvaluesincreasefrom Cluster1toCluster4(Table5)andtheoppositeisobservedregardingtheconcentrationindissolved oxygen.TheCluster1groundwatersampleshaveamoreacidicpHthanthegroundwatersamples ofthethreeotherclusters,andtheirtemperatureisthehighest.Table6indicatesthattheCluster1 samplesaremainlyCa-HCO3watertypeandcomefromshallowgranularaquifers(95%).TheCluster2 samplesaremainly(Ca-Na)-HCO3watertypeandcomefrombothshallowanddeep,granular(31.6%) andbedrockaquifers(68.4%).TheCluster3samplesareCa-HCO3watertypeandalsocomefromboth shallowanddeep,granular(33.3%)andbedrockaquifers(66.7%).TheCluster4samplesareNa-(HCO3 -Cl)watertypeandcomefromdeeperbedrockaquifers(76.2%).Theseobservationsindicatethatthe fourclustersaregeochemicallydistinctgroupsofgroundwatersamples,whichwerecollectedfrom differenthydrogeologicalcontexts,suggestingarelationshipbetweengroundwaterchemistryandthe hydrogeologicalcontext.

AGibbsdiagram(Gibbs,1970)ispresentedinFig.7,plottingtheTDSconcentrationasafunction oftheratiobetweenClandCl+HCO3withthesampleslabelledaccordingtotheirrespectivecluster. SincetheTDSconcentrationincreasesfromCluster1toCluster4,thefourclustersareeasily dis-tinguishable.Allthegroundwatersamplesmainlyfallinthedomaininfluencedbythegeology.The Cluster1samplesfallclosertorainwaterthanthesamplesintheotherclusters,whichisconsistent withthepreviousobservations(Table5).ThegroundwatersamplesofCluster1couldthus corre-spondtolow-salinityandrecentlyinfiltratedwatersinrechargeareas(Frapeetal.,1984;Gascoyne andKamineni,1994).ElevatedconcentrationsinPb2+_andZn2+_{forCluster1samplescomparedtothe} threeotherclustersareunexplained.TheCluster2andCluster3samplesaremoreinfluencedbythe water–rockinteractionsandfresheninghasaffectedsomeoftheCluster2samples.Thesesamples couldcorrespondtomixedorintermediatewatertypesfromgranularandbedrockaquifers(Frape etal.,1984;RajmohanandElango,2004;Subramanietal.,2010).Thislastobservationhighlightsthe possibilityofhydraulicconnectionsbetweentheCanadianShieldbedrockandthegranulardeposits asrecentlydemonstratedbyChesnauxetal.(2012)andRichardetal.(2014).TheCluster4samples wouldthereforecorrespondtomoresalineandprobablymorematurewaterfrombedrockaquifers (Frapeetal.,1984;GascoyneandKamineni,1994).Thesesamplescanbedividedintotwosubgroups: onesubgroupofsamplesinfluencedbythewater–rockinteractionsandonesubgroupofsamples correspondingtomixturesbetweenseawaterandwaterundergoingsomefreshening(Fig.7).These lastsamplesmainlycorrespondtoNa-Clgroundwatertype,whichcouldbetheresultofthe natu-ralevolutionofgroundwateralongitsflowpathandcorrespondingtoancientgroundwater(Frape etal.,1984;GascoyneandKamineni,1994).Thisgroundwatertypecouldalsoresultfromnumerous groundwatersalinizationprocessessuchassolutediffusionfromamarineclayaquitardorsaltwater intrusion(Cloutieretal.,2008;Beaudry,2013;Montcoudioletal.,2014).

Fig.8ashowsHCO3−andCa2+enrichmentfromCluster1toCluster4byplottingHCO3− concentra-tionversusCa2+_{concentrationwiththegroundwatersampleslabelledaccordingtotheirrespective} clusters.Cluster1samplesarecharacterizedbythelowestHCO3−andCa2+concentrations.Cluster2, Cluster3andCluster4samplesarecharacterizedbyenrichmentinCa2+_andHCO

3−.Thedistribution oftheCluster2andCluster3samplesfollowsthetheoreticallineofcalciteandanorthitedissolution (Montcoudioletal.,2014).Ca-richmineraldissolutioncanthusbeproposedastheprimaryprocess ofCa2+_andHCO

32− enrichmentforCluster2andCluster3samples(RajmohanandElango,2004; Subramanietal.,2010;Montcoudioletal.,2014).TheweatheringofCa-richsilicatesandthe cal-citedissolution(Eqs.(2)and(3);AppeloandPostma,2005)arepresentedasaconsistentprocessof Ca2+_andHCO

3−enrichmentofthegroundwater,sincethebasementofthestudyareaismadeupof charnockiticgneiss,graniteandanorthosite,butalsolimestoneintheareasurroundingthemeteor crater(Lemieuxetal.,2003).

Fig.7. GibbsdiagramplottingtheTDSconcentrationasafunctionoftheratiobetweenClandCl+HCO3withthesamples

labelledaccordingtotheirrespectiveclusters.Themainprocessesaffectingeachclusterofgroundwatersamplesaredetermined

accordingtotheClandHCO3ratio.

CO2+H2O+CaCO3(calcite) =Ca2++2HCO3− (3)

Thesechemicalreactions(Eqs.(2)and(3))areconsistentwiththeRFAresultswhichshowahigh loadingforsilicaonthethirdfactor,furthersuggestingtheimportanceofsilicateweathering.Thisis alsoconsistentwiththeCluster2andCluster3samplesinfluencedbythewater–rockinteractions basedontheGibbsdiagrams.Inthisstudy,thedissolutionofanorthiteispresentedastheprimary processofCa2+_andHCO

3−enrichmentbecausethissilicatemineraliseasilydissolved(Montcoudiol etal.,2014).InFig.8b,mostofthegroundwatersamplesplotabovethe[Ca2+_]=2[Mg2+_{]line,indicating} thatsilicateweatheringdominatesovercarbonatedissolution(RajmohanandElango,2004).However, someoftheCluster3andCluster4samplesplotbelowthisline,indicatingthatthedissolutionofcalcite couldalsobeaprocessofCa2+_andHCO

3−enrichmentforsomeoftheseclustersamples(Rajmohan andElango,2004;Subramanietal.,2010;Montcoudioletal.,2014).

InFig.8c,thesamplesfromCluster1toCluster4mainlyshowanenrichmentinCa2+_andNa+ concentrationswhichcouldbeexplainedbysilicateweathering(notonlyCa-richminerals)andcalcite dissolution(Montcoudioletal.,2014).SomeoftheCluster2andCluster4samplesshowhighNa+

Fig.8.PlotofHCO3−concentrationversusCa2+concentration(a),Mg2+concentrationversusCa2+concentration(b),Na+

con-centrationversusCa2+_{concentration(c)andNa}+_{concentrationversusCl}−_{concentration(d),withthegroundwatersamples}

labelledaccordingtotheirrespectiveclusters.ThelinearrelationshipbetweenCa2+_andHCO

3−(a)andthecomparisonbetween

Ca2+_andMg2+_{(b)areevidenceofCa-silicateweatheringandcalcitedissolution.IndicationsofCa}2+_/Na+_{ionexchangeare}

pro-videdbyadecreaseinCa2+_{concentration(c)ortoconstantCl}−_{concentrationsandenrichmentinNa}+_{(d)mainlyfortheCluster}

2andCluster4samplescomparedtotheothersamples.EnrichmentinCl−andconstantNa+_{concentrationssuggestamixing}

process(d).

concentrationsassociatedwithalowerCa2+_{concentrationthantheothersamples.Thesesamples} appeartobemixturesinfluencedbyionexchange(Fig.8d).Theprocessofionexchangeisknown toexplainthedeficitofcalciumversussodiumingroundwater(AppeloandPostma,2005).Based ontheRFAresults(Fig.5),thesesamplesarecharacterizedbynegativescoresforhardness(Factor 1)incontrasttopositivescoresforsalinity(Factor2)whichisconsistentwiththeoccurrenceofion exchange.TheCluster1,Cluster3andCluster4samplesmainlyfollowtheseawaterdilutionline buttheCluster2samplesaremorerandomlydistributed, reflectingsignificantion exchangeand mixing(Fig.8d).TheshapeoftheStiffdiagramforCluster4samplesischaracterizedbyhigherNa concentrations(Fig.4).ThiscouldbeexplainedbygroundwaterNa-enrichment(Cloutieretal.,2008;

Fig.9.Regionaldistributionofthe105groundwatersampleswiththesampleslabelledaccordingtotheirrespectiveclusters

andthegeologicalcontext.C1:Cluster1;C2:Cluster2;C3:Cluster3andC4:Cluster4.

Walter,2010;Montcoudioletal.,2014)relatedtocationexchangeofNa+_byCa2+_{accordingtoEq.(4)} (GascoyneandKamineni,1994):

Ca2++2Na-X(s) =2Na++Ca-X(s) (4)

TheCluster2samplesarethusinfluencedbyCa-richsilicateweathering,ionexchangeandmixing whiletheCluster3samplesappeartobemoreaffectedbyCa-richsilicateweatheringandcalcite dissolution.

ThegeographicallocationoftheclustersispresentedinFig.9.TheCluster2samplescollectedfrom granularaquifersarelocatedintheHaute-Côte-Nord,andontheislandIsle-aux-Coudres,whereasthe samplesfrombedrockaquifersaremainlylocatedintheCharlevoixsubregion,intheareasurrounding

Fig.10.Evolutionofgroundwaterhydrogeochemistry.PlotofthefactorscoresforFactor1andFactor2withthesamples

labelledaccordingtotheirrespectiveclusters(a),andStiffdiagramsshowingtherelationshipbetweentheclustersandthe

groundwatergroups’evolution(b).GroundwaterofCluster1correspondstorechargegroundwaterandevolvesalongitsflow

pathintoCluster2andCluster3affectedbypossiblehydraulicconnections.Cluster2andCluster3groundwatersthenevolve

intoCluster4groundwaterpresentindischargeareas.

themeteorcrater.AsimilarobservationcanbemaderegardingtheCluster3samples:thesamples fromgranularaquifersarelocatedintheHaute-Côte-Nordandthesamplesfrombedrockaquifers aremainlylocatedintheCharlevoixsubregion.SincetheCluster4samplesarelocatedalongthe St.LawrenceRiverandtheSaguenaycoastwhereglaciomarinesilty-sandsandclaysweredeposited duringtheGoldthwaitSeaepisode14,000BP(Cousineauetal.,2014),solutediffusionfrommarine clayorsaltwaterintrusioncanalsobeproposedasprocessesofgroundwatersalinization(Cloutier etal.,2008;Beaudry,2013;Montcoudioletal.,2014).AfirstCluster4subgroupisthuscomposedof groundwaterinfluencedbyCa-richsilicateweatheringandcalcitedissolutionwhileasecondCluster 4subgroupiscomposedofamixturebetweenseawaterandwaterundergoingsomefreshening influ-encedbyionexchange.HigherconcentrationsofSr2+_,Ba2+_,B3+_,Mn2+_,Mo2+_,andF−_{intheCluster4} samplessuggestamoreintensivealterationofthebedrockminerals.

Finally,Fig.10presentsaplotofthescoresforthefirsttwofactors,hardnessandsalinity,with thesampleslabelledaccordingtotheirrespectivecluster.Thisplotallowsagoodvisualizationof

thevariousgroundwatertypesfoundintheregionofCharlevoixandHaute-Côte-Nord,aswellas insightintothegeochemicalprocessesresponsibleforthesevariations.Thefourclusterscanbe clas-sifiedintoplausiblelevelsofgroundwaterevolutionintheCharlevoixandHaute-Côte-Nordregion. Cluster1representslow-salinityCa-HCO3groundwaterthatcorrespondstorecentlyinfiltratedwater fromsurfacegranularaquifersinrechargeareas.Cluster4Na-(HCO3-Cl)groundwaterismoresaline andcorrespondstomoreevolvedgroundwater.Thisgroundwaterplausiblyoriginatesfromconfined bedrockaquifers,sincetheCluster 4samplesaredistributedalongtheSt.LawrenceRiver,where glaciomarineandmarinesedimentsweredeposited,forminganaquitard.Hardness(Factor1)and salinity(Factor2)haveastrongpositiveinfluenceonmoresalinegroundwatersamplesfrom frac-turedrockaquifersofCluster4.Onthecontrary,thesetwofactorshaveanegativeinfluenceonpoorly mineralizedwatersfromgranularaquifersofCluster1.Asmentionedpreviously,hardness(Factor1) couldbeassociatedwiththeweatheringofanorthiteorwiththedissolutionofcalciteofthesilicate bedrock,butalsowiththegroundwaterrechargeprocess.Salinity(Factor2)couldbeassociatedwith Na+_{enrichmentprocessessuchasCa}2+_/Na+_{ionexchangeandwithnumerousprocessesof} ground-watersalinizationsuchassolutediffusionfrommarineclayaquitardsorsaltwaterintrusion(Cloutier etal.,2008;Beaudry,2013;Montcoudioletal.,2014).TheCluster2andCluster3intermediateor mixedgroundwatersamplesarelessstronglyinfluencedbythetwofirstfactorsthantheother clus-tersamples.TheCluster2andCluster3(Ca-Na)-HCO3groundwaterscouldcorrespondtomixedor intermediategroundwaterbetweenCluster1andCluster4frompossiblyinterconnectedgranularand bedrockaquifers(Chesnauxetal.,2012;Richardetal.,2014).TheCluster3samplesaremore influ-encedbyFactor3(Si4+_{).Thisthirdfactorcouldalsobeassociatedwithsilicateweathering,sincethe} studyareaisunderlainbysilicaterocks,asmentionedpreviously.ThisisconsistentwiththeCluster3 sampleshavingthehighestconcentrationsinSi4+_{ofallclusters.Thefactthatthehydrogeochemical} evolutionofgroundwatercanberepresentedintheplaneofFactors1and2confirmstheimportance ofthesetwofactorsdefinedasthe«hardness»andthe«salinity»inthehydrogeochemistryofthe Charlevoix/Haute-Côte-Nordaquifersystem.

7. Conclusion

ThegroundwaterchemistryoftheCharlevoix/Haute-Côte-Nordregionwasstudiedaspartofa regionalhydrogeologicalcharacterizationproject.Groundwatersampleswerecollectedat113sites distributedoverthewholestudyarea,eitherinthebedrock(60sites)orinthesurficialdeposits(53 sites).Anion-balancecalculationledtotheselectionof105samplesfortheanalysis.

Theanalysisofthestableisotopes␦2_Hand␦18_{Osuggeststhatsampledgroundwaterhasacommon} origin:rechargewatersinatemperatetocoldclimate.Thisshowsthatthereismixingbetween seawa-terandmeteoricwater.Thehierarchicalclusteranalysisallowedthesortingofthe105samplesinto fourclustersandtodefineaspatialgeochemicalzonationoftheaquifersystem.Thefourclustersare geochemicallydistinctgroupsofgroundwatersamples,andthereappearstobearelationshipbetween thegroundwaterclustersandthehydrogeologicalcontext.TheR-modefactoranalysisallowedthe extractionofninefactors.Thethreefirstfactorsaccountfor81%ofthetotalvarianceinthedataset. Factor1explains35.9%ofthevarianceandischaracterizedbyhighlypositiveloadingsinCa2+_,Sr2+_, HCO3−,SO42−,andMg2+.Factor2explains31.8%ofthevarianceandischaracterizedbyhighly pos-itiveloadingsinNa+_,Cl−_andK+_{.Factors1and2weredefinedas“hardness”and“salinity”factors,} respectively.Hardness(Factor1)couldbeassociatedwiththeweatheringofCa-richsilicatesorthe dissolutionofcalcitecontainedinthesilicatebedrock.Salinity(Factor2)couldbeassociatedwith Ca2+_/Na+_{ionexchangeandwithnumerousprocessesofgroundwatersalinizationsuchassolute} dif-fusionfrommarineclayaquitardsorsaltwaterintrusion.Factor3explains13.3%ofthevarianceand ischaracterizedbyaveryhighlypositiveloadinginSi4+_{andcouldalsobeassociatedwiththeCa-rich} silicateweathering.

TheintegrationofHCA,RFAandgraphicalanalysisresultsallowedtheclassificationofthefour clustersintoplausiblelevelsofgroundwaterevolutionintheCharlevoixandHaute-Côte-Nordregion. Cluster1low-salinityCa-HCO3groundwatercorrespondstorecentlyinfiltratedwaterfromsurface granularaquifersin rechargeareas.Cluster4 Na-(HCO3-Cl)groundwaterismore salineand cor-respondstomoreevolvedgroundwater.Thisgroundwaterplausiblycomesfromconfinedbedrock

aquifers.Cluster2andCluster3(Ca-Na)-HCO3groundwatercouldcorrespondtomixedor intermedi-ategroundwaterbetweenCluster1andCluster4,frompossiblyinterconnectedgranularandbedrock aquifers.

Thisstudyidentifiedthemainprocessesaffectingthehydrogeochemicalevolutionofgroundwater intheCHCNregionasthefollowing:groundwaterrecharge,water–rockinteractions,ionexchange, solutediffusionfrommarineclayaquitardsorsaltwaterintrusion,butalsohydraulicconnections betweentheCanadianShieldandthegranulardeposits.

TheseresultsareconsistentwithotherstudiescarriedoutinotherregionsoftheCanadianShield, where geological and hydrogeologicalcharacteristics and geologicalhistory, including the latest glaciationandseawaterinvasion,werefoundtobetheprimaryfactorsinfluencingtheevolution ofgroundwatergeochemistry(Cloutieretal.,2008;Beaudry,2013;Montcoudioletal.,2014). How-ever,abetterknowledgeofthehydrogeologicalconditionswouldallowabettercharacterizationof groundwaterchemistryinrelationtothehydrogeologicalcontextandabetteridentificationofthe geochemicalprocessesinfluencingtheevolutionofgroundwaterchemistry.Furtherinvestigations, includingmoredetailedstudiesofthelithologyofthestratigraphicunitsoftheCHCNaquifer sys-temandtheinterpretationofpumpingtestsinordertoidentifyhydraulicconnections,couldsupport therelationshipsbetweengroundwaterchemistryandthehydrogeologicalcontextdiscussedinthis study.Alocalinvestigationandagreateramountofgeochemicalandhydrogeologicaldatacouldallow amappingofgroundwaterrechargeareas.

Conflictofinterest

Theauthorsdeclarethatthereisnoconflictofinterest.

Acknowledgements

ThisprojectwasfundedbytheProgrammed’acquisitiondeconnaissancessurleseaux souter-rainesofQuebec(PACES),withcontributionfromtheQuebecMinistèreduDéveloppementdurable, del’Environnement,delaFauneetdesParcs(MDDEFP),andthethreeregionalmunicipalitiesofthe CHCNregion.Theauthorswouldliketoacknowledgethecontributionstothisreportfromteam mem-bersofthePACES-CHCNproject.Theworkofallstudentsinvolvedintheprojectasfieldassistants, andthecollaborationofthepopulationoftheCHCNregionwerealsogreatlyappreciated.

AppendixA. Supplementarydata

Supplementary data associated with this article can be found, in the online version, at doi:10.1016/j.ejrh.2015.06.004.

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