E&EG Journal Volume XXVIII, Number 4

Environmental & Engineering Geoscience

THE JOINT PUBLICATION OF THE ASSOCIATION OF ENVIRONMENTAL AND ENGINEERING GEOLOGISTS AND THE GEOLOGICAL SOCIETY OF AMERICA

SERVING PROFESSIONALS IN ENGINEERING GEOLOGY, ENVIRONMENTAL GEOLOGY, AND HYDROGEOLOGY

Volume28,Number4,November2022

TableofContents

335ACenturyofLandslidesinSeattle,Washington:CoalescingandDigitizingtheCity’sHistoricLandslide Inventories

ElizabethJ.Davis,SusanChang,SteveHou,TammyTeal,KevinCowell,andSandraGarcia-Arceo

347SimpleShearStrengthAnalysisofInherentAnisotropyforaTropicalAlluvialSoil

AlsidqiHasan,NisaIsmail,LeeLinJye,andKhalidAlshibli

361UnearthingUndergroundMining-InducedStrataDisturbancebyElectricalResistivityTomography Interpretation

AmarPrakash,AbhayKumarBharti,andAniketVerma

371InvestigationofPhysicochemicalChangesofSoftClayaroundDeepGeopolymerColumns MajidBagheriniaandNes¸eIs¸ik

387WaterQualityMonitoringofFiveKarstSpringswithinaPasturelandinSouthwestPolkCounty,Missouri RamonaG ´ omezandM ´ elidaGuti ´ errez

397AssociationbetweenCOVID-19andHeavyMetalPollutioninIraqiCitiesDeterminedfromHierarchical Prediction AramMohammedRaheem

OpenAccessArticle

ACenturyofLandslidesinSeattle,Washington:

CoalescingandDigitizingtheCity’sHistoricLandslide Inventories

ELIZABETHJ.DAVIS*

DepartmentofEarthandSpaceSciences,UniversityofWashington,JohnsonHall Rm070,400015thAvenueNE,Seattle,WA98195

SUSANCHANG

SeattleDepartmentofConstructionandInspections,P.O.Box34019,Seattle, WA98124

STEVEHOU

SeattleDepartmentofTransportation,P.O.Box34996,Seattle,WA98124

TAMMYTEAL

JacobsEngineeringGroup,Inc.,1110112thAvenueNE,Bellevue,WA98004

KEVINCOWELL

Shannon&Wilson,Inc.,3990CollinsWay,Suite100,LakeOswego,OR97035

SANDRAGARCIA-ARCEO

1212144thStreetSW,Lynnwood,WA98087

KeyTerms: Landslides,GeologicHazardsMaps,GeologicHazards,LandUse,UrbanGeology,UrbanPlanning,EngineeringGeology,PublicPolicy

ABSTRACT

Landslideshaveimpactedthebuiltenvironmentofthe cityofSeattleforoveracentury.WepresentanewhistoriclandslideinventoryforSeattlebuiltfromover100 yearsoflandsliderecords.Seattlehastrackedlandslide occurrencesincethe1890sandhascommissionedvariousstudiestoexaminewhereandwhylandslidesoccur.Duringthistenure,methodsforcollection,display, anddisseminationoflandslidedatahavevaried,resultinginacomplex,non-uniform,andrichdataset.For thenewdatabasecompletedin2019,multipleinventoriesandthousandsofhistoricdocumentswerecombinedtomeettheCityofSeattle’sobjectivesofkeeping landslideareasprecisewithrespecttopropertyboundaries.Comparedwithpriormaps,thenewmapprovidesmoreinformationfromthehistoricalrecord,maps landslideextentmoreaccurately,andtagsfewerpri-

*Correspondingauthoremail:edav@uw.edu

vatepropertieswithlandslidefeaturesthanpriormaps. Inaddition,digitizedhistoricdocumentsarenowattachedtolandslidefeaturesintheCityofSeattle’s publicgeographicinformationsystem(GIS)map.The historicinventoryiscomplementarytoalightdetectionandranging(LiDAR)inventorycoveringthesame area.Thiscasestudyshowshowhistoricdatacanbe usedtorecordlandslidesinurbanareaswheregeomorphologicalsignaturesmayberemovedbydevelopment. InSeattle,accesstoinformationabouthistoriclandslideswillstreamlineworkflowsforpublicandprivate engineersandgeologistsandwillservepropertyownersandthegeneralpublic.Themapiscurrentlyavailableathttps://www.arcgis.com/apps/webappviewer/ index.html?id = f822b2c6498c4163b0cf908e2241e9c2.

INTRODUCTION

Landslidemapsarecriticaltohazardplanning worldwide,andcountlesscommunitieshaveconstructedsuchmapsasapreliminarysteptoward landslidehazardassessments.Variousmethodsfor constructinglandslidemapshavebeenused,including geomorphicmappinginthefield,visualmapping onaerialphotos,orondigitalelevationmodels

Environmental&EngineeringGeoscience,Vol.XXVIII,No.4,November2022,pp.335–346

Figure1.IndexmapshowingSeattlecitylimits(1A),andlocation inWashingtonState(1B).Labelledaretwoexamplelandslideareas,PerkinsLaneinMagnolianeighborhoodandSunsetAvenuein WestSeattleneighborhood.

constructedfromthelightdetectionandranging (LiDAR)remotesensingmethod(e.g.,Haugerud etal.,2003;Mickelsonetal.,2019),andautomated approaches(e.g.,McKeanandRoering,2003;Booth etal.,2009).Whilethesetechniquesmaybeveryeffectiveinundevelopedandevenvegetatedareas(Guzzetti etal.,2012),alloftheseapproacheshavelimiteduse inurbansettingswheregeologicandgeomorphic indicatorsforslopeinstabilitymaybesubstantially alteredbydevelopment.Historicrecordsfillthisgap, providinginformationaboutpriorlandslideswhere theirgeomorphologicalcluesnolongerexist.Such recordshavebeenconstructedinregionswithlong writtenrecordsworldwide,likethenearly1,000-year recordinUmbria,Italy(Salvatietal.,2009).Inthe presentinvestigation,weaddressedthechallengesof historicmapproductionandintegrationtolandslide hazardassessmentswithacasestudyfromSeattle, Washington(Figure1).Inparticular,wepresenteda newhistoriclandslidemaprecordinglandslidesfrom overacentury,compareditwithaLiDAR-based inventory,anddemonstrateditsinfluenceontheCity ofSeattle’sassessmentoflandslidehazards.

BACKGROUND

ThemostrecentphaseofinterestinSeattlelandslidesbeganNewYear’sEve,1996,whenhundredsof landslidesoccurredfollowingprolongedheavyrainfall,amajorsnowstorm,thenmoreheavyrain,which rapidlymeltedaboutafootofaccumulatedsnow (Baumetal.,1998).Marginallystableslopesall aroundthecityweresaturated,triggeringhundredsof landslides.Thetwogeotechnicalengineersonstaffat theCityofSeattle,aswellasmanyothermunicipalem-

Figure2.HydraulicsluicingofahillsideduringtheJacksonStreet re-gradeofSeptember1909.Manyhomeownersreportedlandslides anddamagetotheirpropertiesfollowingthere-grades,whichremovedentirehillsinsomeplacesandcutlevelroadwaysinothers. Thesereports,includingclaimsfordamages,photos,andotherdocuments,areretainedinthelandslidefiles.Thisphotocanbefound infileSEDJ-1-B.PhotobyLewisandWiley,Inc.

ployees,workedaroundtheclockresponding,fielding andcatalogingreportsoflandslides,assessingdamages,andinspectingbuildings(D.Griswold,Cityof SeattleDepartmentofConstructionandInspections, Seattle,WA,unpub.data,2019).

This1996–97stormeventwasfarfromthefirst landslidewinterinSeattle’shistory(Laprade,1986; Miller,1991).Cityrecordsnotesimilareventsover wintersof1933–34,1971–72,1985–86,and1995–96 (e.g.,SEDA-2-31933,SED25-D1972,SED47-D 1986,SEDP-21996,CityofSeattleDepartmentof Transportation,Seattle,WA,unpub.data,2019).A riseingroundwaterlevelthataccompanieswetSeattlewintersheightenslandslideriskinsomeareasof thecitybutisnottheonlycauseortrigger(Laprade etal.,2000).Localgeologymakestheregionparticularlysusceptibletoslopefailures,whichmaybetriggeredbynaturalprocessesorhumanactivity(Figure2) (Baumetal.,2005).Geologistshavemappedancient landslidecomplexesaroundmanyofthecity’sslopes (e.g.,Tubbs,1974;Troostetal.,2005;Mickelsonetal., 2019).Thefrequencyandhazardoflandslidesresulted inSeattledepartmentskeepingrecordsoflandslides since1890.

Inanefforttoreducetheharmcausedbylandslides, theCityofSeattleregulatesdevelopmentonpropertiesinlandslide-proneareas(2015;SeattleMunicipal Code[SMC]25.09.012A.3and4).Landslide-proneareasincludelocaleswherelandslidesareknowntohave occurred,definedinSMC25.09.012A.3:

Knownlandslidesareasidentifiedbydocumented history,orareasthathaveshownsignificantmovement duringthelast10,000yearsorareunderlainbymass wastagedebrisdepositedduringthisperiod.

Toaddressthefirstpoint,landslidesidentifiedby documentedhistory,theCityofSeattlemaintains mapsshowinglocationswherelandslideshaveoccurred.Variationinrecordingmethodsandfilingpracticesoverthepast100yearsledtoarichanddiversecollectionofinformationretainedwithintheCity ofSeattle’slandslidefiles.Whilethesefilesarepublicrecords,priortotheprojectdescribedinthisstudy, publicaccessinvolvedseveralsteps,aspecificrequest, andusuallyanin-personvisit.Previousiterationsof thehistoriclandslidedatabasealsousedinconsistent waysofvisualizinghistoriclandslides.

Thenewmappresentedasaresultofthisresearch includesinformationfrommultiplelandslideinventories,standardizingtheformatforthemapandmakingallhistoricdocumentsavailableonline.Dataare presentedconsistentlyandwithincreasedeaseofuse, enablingcityplanners,consultants,andthepublicto evaluateavailablehistoricinformationaboutknown landslidesatindividualproperties.

DATASOURCES

TheCityofSeattlehasmaintainedextensivepaper recordsregardinglandslidesforoveracentury.The earliestrecordsoflandslides,datingfrom1890,were collectedandmaintainedbytheSeattleEngineering Department(SED),whichlaterseparatedintoseveral departments,includingtheSeattleDepartmentof Transportation(SDOT),SeattlePublicUtilities,and SeattleDepartmentofConstructionandLandUse (DCLU).SDOTbecameresponsibleformanaging landslidefiles,butin1985,DCLUbegancompiling landslidereportsindependently,particularlythose whichimpactedprivatepropertiesthatwereoutside ofSDOTjurisdiction.Theserecordsconsistofreportsmadebyresidents(manyofwhomsoughtrelief fromtheCityofSeattlethroughlegalorothermeans); notes,reports,andsketchesmadebycityengineers,geologists,andinspectors;correspondencebetweenand amongcityemployeesandthepublic;andplans,legal documents,photos,andexternalgeotechnicalreports (Figure3).Cityengineersbeganplottinglandslide locationsmanuallyonlargeMylarmaps.Landslides werefrequentlymappedascirclesratherthanactual extent.Otherdocumentssometimescontainedmore information,includinglandslideextentorphotos.In ordertoaccessthesedocuments,engineersorothers madeanappointmentwithanSDOTengineerto checkoutfiles.

In1990,pursuanttothepassingofSeattle’sInterim EnvironmentallyCriticalAreasRegulations,thelocationsoflandslidesdocumentedbybothDCLUand theSDOTwerecollatedintheEnvironmentallyCriticalAreas(ECA)folios(CityofSeattle,1990).These folioswereupdatedwithnewlandslideswhenthe regulationsbecameeffectiveOctober31,1992.Some landslideswereplottedaspoints,othersasdetailed outlines.

Duetothedevastatinglandslideseasonduringthe winterof1996–97,theSeattleCityCouncilcreated alandslidetaskforce,whichgeneratedrecommendationstomitigatethelandslidehazardthroughoutthe city.ThisresultedinthespotdrainageprogrammanagedbySeattlePublicUtilities,publicoutreach,educationonlandslideprevention,andtheSeattleLandslideStudycompiledbyconsultingfirmShannon& Wilson,Inc.,firstpublishedin2000(Lapradeetal., 2000)andlaterupdatedin2003(Shannon&Wilson, Inc.,2003).

TheSeattleLandslideStudy(Lapradeetal.,2000; ShannonandWilson,Inc.,2003)reviewedcityrecords andcreatedanewinventorymapplottinglocationsof landslideinitiationaspoints.Theresultingmapwas adoptedinageographicinformationsystem(GIS)as anupdatedKnownLandslideAreaslayerin2001, inaccordancewithDirector’sRule15-2001(Cityof Seattle,2001).Lapradeetal.(2000)andShannon& Wilson,Inc.(2003)systematicallyassembledinformationforeachlandslide,includingslidestyle,date,and estimatedtriggermechanisms,andverifiedwithfield observationsthelocationsofmanyhistoriclandslides.

Duringthelastdecade,theSeattleEmergencyOperationsCenter(EOC)institutedtheuseofanew program,WebEOC(Juvare,2007),whichincludesa wayforcitydepartmentstodocumentresponsesto landslides.TheSeattleDepartmentofConstruction andInspections,SeattleDepartmentofTransportation,SeattlePublicUtilities,andSeattleParksand RecreationtypicallydocumenttheirinspectionsofreportedslidesinWebEOC.Someoftheserecordswere addedtotheKnownLandslidelayerinGISasasinglepointinthecenteroftheparcelwheretheslide originated.

THENEWMAP

ThegoalofthenewmapwastoincreasetheaccuracyandresolutionofSeattle’shistoriclandslide databaseandtodisseminatelandslidedetailsandsupportinghistoricdocumentstothepublic.Seattle’s historiclandslideinventoryhasdevelopmentconsequencesforprivateandpubliclandowners.Propertiesthatoverlapamappedlandslideareregulatedas EnvironmentallyCriticalAreas(ECA,asdefinedin

SMCChapter25.09)andsubjecttoenhancedgeotechnicalreviewcomparedtothoseoutsideofmapped ECAs.Therefore,accurate,consistentmappingandaccessibledocumentationbenefitspropertyowners,city engineers,andtheexternalgeotechnicalcommunity alike.

In2016,webegananewefforttocollate,modernize,andcentralizelandslideinformationforthe

CityofSeattle.Attheproject’sstart,thecity’slandslidedatabaseconsistedofredundantdatafromseveralsources:landslideinitiationpointscreatedbythe 2000and2003datafromtheSeattleLandslideStudy (Lapradeetal.,2000;Shannon&Wilson,Inc.,2003), digitizedlandslidepolygonsfromprioranalogmaps (includinglargecircularartifactsintroducedbydigitizinglow-resolutioncopiesofthefirstMylarmaps),and

Figure4.Clickingonalandslidefeatureintheonlineviewerdisplaysthelandslide’sdateofoccurrence,abriefdescriptionoftheevent,and historicdocumentsavailablefordownload.ThisexampleshowsapartiallandslideoutlinedescribedinfileSEDJ-1-E1933.Thelandslide occurredin1933;thatslopewasremovedwhenU.S.Interstate5wasconstructed.

pointsautomaticallydroppedontoimpactedpropertiesbytheWebEOCmanagementsoftware.

ScopeandPriorities

Wereviewedtheoriginaldatasourcesandeveryfeatureontheformerlandslidemap,adoptedconsistent mappingstandards,adjustedfeatureswhereevidence warranted,addedrecentevents,anddigitizedthehistoricpaperfiles.Thenewmapispublishedasalayerin theCityofSeattle’sonlineGISdatabase,wherelandslidefeaturescontainbriefdescriptionsoftheevents andarelinkedtothedocumentsthatsupportthem (Figure4).

Landslidesweremappedaccordingtoavailableevidence,withparticularcaretowherelandslidefeatures fellwithrespecttopropertyboundaries.Noparcelwas taggedwithoutexplicitdocumentation;thereforethe newmapismoreaccuratethanpriorversions.The updatedKnownLandslidesECAlayerpresentlyincludescityrecordsofreportedeventsthroughJuly15, 2019.

METHODS

Wereadthousandsoflandslidefilesandevaluated theexistingGISmapwhereitintersectedeverypropertyinSeattle.Wherefilesevidencedlandslidesona property,weadjustedexistingGISfeaturesoradded newfeaturestorepresenteachlandslideevent.We wrotebriefdescriptionsofeacheventintheattributes ofeachGISfeature.Wherefeaturesexistedonpropertiesunsupportedbyhistoricallandslidedocumentation,weremovedoradjustedfeaturesaccordingly.We recordedchangesandjustificationsinaspreadsheet whichisavailabletothepublicviarequestfromthe SeattleDepartmentofConstructionandInspections (SDCI)geotechnicalgroup.Allfileswerescannedor digitizedanduploadedtotheGISlayerasattachments tothefeaturestheydescribe.

WhatCountsasaLandslide?

Cityrecordsdescribeavarietyofgeotechnicaland engineeringquandaries,fromroofscollapsingunder snowtoreportsofmysteriousholesthatappearedin

yards.Itwasnotalwaysstraightforwardtoassumethat agivenreportrepresentedalandslide.

Wedefinedknownlandslidesasthefollowing:

Mudflows,debrisflows,rotationallandslides, slumps,erosion

Groundcracking,scarps,settlement,andset-downs Retainingwallfailure,whenaccompaniedby groundmovement

Slopefailuresfollowingsewerorwaterpipebreaks Landslidedebrisandleaningorfallentreesonsite Landsliderunout

Groundmovementfollowingexcavationorgrading.

Generally,thefollowingwerenotinterpretedasknown landslides:

Retainingwallfailurenotaccompaniedbyground movement

Structuralfailurenotapparentlyrelatedtoground movement

Earthquakedamage,exceptwhentriggeringslope movement

Unexplainedsinkholes.

ComplicationsofaCentury-LongMunicipalRecord

SystematicattentiongiventolandslidesinSeattle hasvariedthroughthepastcentury.Fromperiods whencityworkersprioritizedmeticulousrecordkeeping,manyaccountsoflandslidesremain.Other periodslacksubstantialrecords,despitealikely continuationofsliding.Furthermore,decadesof municipalreconfigurationshavecomplicatedrecord keeping.Departmentsresponsiblefordocumentinglandslides,organizationoffiles,andfilenaming schemeshaveevolved.Today,thenamesoflandslide filesreflecttheirhistoricprovenance.Table1describes currentvariationsinfilenamesandtheirorigins.

Ascityprioritieshavechangedthroughtime,variouseffortstocollatethelandslidehistoryhaveresulted innumerousscalesofinformation,fromfinescale(e.g., surveyedoutlinesofindividuallandslides)tocoarse (e.g.,abriefreportofslopefailureonacertainblock). Theupdatedescribedinthisresearchwasthelatest inalonglineofdatabaseupdatesthatservedanew need—specifically,adaptationforaddedGIScapabilities(e.g.,fileattachmentsanddownloadsfromnon–CityofSeattlecomputers).

MuchhaschangedinSeattleoverthepast100years, includingsomestreetnames.Inmanycases,wereviewedavarietyofhistoricalmapsandsewercards toidentifythecorrectboundariesoflandslideswhere streetshadbeenre-namedorpropertyboundarieshad changed.

VariedMapExpressionDependingonInformation TypeandQuality

Weapproachedthesechallengesbyconsideringeach slideareaonanindividualbasisatthescaleofafew cityblocks,drawingGISfeaturesasneededtoprovidethemostinformationfortheindividualslidearea. Landslideeventsarerepresentedintheupdatedlayer aseitheroutlinesoflandslidesderivedfromhistoric maps,rectangularpolygonsonareasknowntohave beenimpacted,linesthatrepresentmappedlandslide headscarps,and/orpointsthatrepresentsingleevents.

Evidencefromhistoricfileswasrequiredforalandslidefeaturetooverlapaprivateparcel.WhereinitiationpointsmappedbyShannon&Wilson,Inc.,were present,weleftthoseinplace,thoughamodestnumber(fewerthan10%)weremodifiedbasedonadditionalinformationfoundinthecurrentrecords(City ofSeattleDepartmentofConstructionandInspections,Seattle,WA,unpub.data,2019).

Thiscase-by-caseapproachsimplifiedthedatabase forusersevaluatinganeighborhood’slandslidehistory butintroducedlimitationsforuseofthedatabaseto evaluatecity-widestatisticaltrends.Noteverylandslideismarkedbyapointorapolygon,andsome landslidesaremarkedbybothpointsandpolygons (Table2).Forexample,landslideoccurrencerates basedonlyonmappedpointswouldexcludesome largerandbetter-documentedslopefailures,whilearea statisticsbuiltaroundpolygonswouldomitthose slidesdocumentedonlybypoints.Themapbestserves detailedevaluationofhistoriclandslidesatspecific properties.

CASESTUDIES

MagnoliaNeighborhood,PerkinsLane

PerkinsLane,aresidentialroadbelowthescarpof MagnoliaBluff(Figure5),isconstructedonanancient landslidebench.MagnoliaBluffconsistsprimarilyof glacialtill.Ancientlandslideshavedepositedthethick layerofcolluviumuponwhichPerkinsLaneisconstructed.Landslidesherehavetroubledresidentsand thecityfordecades,andcityrecordsofPerkinsLane landslidesareabundantandcomplicated.Thefirst sliderecordsretainedbythecityarefromthewinterof 1933–34,andmanyseriouseventshaveoccurredsince then.In1996,newtensioncracksformedatthetopof thebluff,abovePerkinsLane.Thesesymptomsindicatedmovementofadeep-seatedrotationallandslide thatwouldintensifyafterthe1996–97winterstorm (SEDP-21997,CityofSeattleDepartmentofTransportation,Seattle,WA,unpub.data,2019).By1998,at leastsixhomesweredestroyedbycontinuedsliding.

Table1. Historicfilenumbersandsources.

EraFileSource,2017 FilenameFormat ExamplesExplanation

1890topresentCityofSeattle Engineering Department (SED),(now maintainedby SDOT)

SEDA-1;SEDA-1 1933;SEATRAN

1985–99?DCLU(nowSDCI)DCLUJ121; DCLUA121; 1512WTaylor St.

SEDfilesdatebackto1890.Theletterornumberrefersto thestreetname,andthefollowingnumbersandletters refertoanindexmovingalongthestreet.Ayearafterthe filenumberreferstotheyearoftheevent,assignedduring the2016–17updateoftheCityofSeattleLandslide Database.Olderfilesfrequentlycontainother informationaboutstreetprojects.

DCLUfilesdateto1986.DCLUJ#filesoccurredin January1986.DCLUA#representlandslidesthat apparentlyoccurredbetween1988and1991,butfor whichnodetailedinformationremains.Filesmayalsobe namedonlybytheaddressoftheevent.

January,1997DCLU96–97StormAdevastatinglandslideseasonoverthewinterof1996–97 ledtodocumentationofhundredsoflandslidesina concentratedeffort.Whenincludedinlargerdatabases, alloftheselandslideswerereferredtowiththeidentifier “96–97Storm.”

2000and2003Shannon&Wilson,

TheSeattleLandslideStudywaspublishedbyShannon& Wilson,Inc.,in2000(Lapradeetal.,2000).Eachslide wasgivenauniquenumber(SW_ID,whichisseparate fromtheslide’sfilename)andwasrepresentedbyasingle pointinthegeodatabase.Iftheeventoccurredduringthe 1996–97storm(Dec.31toJan.1),thefilenumberislisted assuch.IftheslidewasdocumentedinShannon& Wilson’sprofessionalfiles,filenumbersarelistedaseither “S+W,”“MP##”forrailroadmilepostnumbers,or “j-##.”SlidesaddedtotheSeattleLandslideStudyfrom CityofSeattledocumentswerelistedwiththeirCityof Seattlefilenumber.

EOC#Duringthelastdecade,theSeattleEOCinstitutedtheuseof theprogram,WebEOC(Juvare2007),whichincludes,as oneofitsfeatures,awayforcitydepartmentsto documentresponsestolandslides.TheSeattle DepartmentofConstructionandInspections,Seattle DepartmentofTransportation,SeattlePublicUtilities, andSeattleParksandRecreationtypicallydocument theirinspectionsofreportedslidesinWebEOC.Priorto thisupdate,theserecordswereoccasionallyaddedtothe KnownLandslidelayerinGISasasinglepointinthe centeroftheparcelwheretheslideoriginated.

Figure5.AerialphotoofPerkinsLaneandMagnoliaBluffpriortothe1997–98landslides.Photolooksnortheast.Glacialtillofthenearly verticalMangoliaBluffisvisiblethroughvegetation.PerkinsLane,whichextendedtotherightedgeofthephoto,wasconstructedona colluvialbench.FromfileSEDP-2photos,p.4.Unknownphotographeranddate.

Figure6showsthenewlandslidemap(right),in comparisonwiththeoldermap(left).Theoldermap lackedanoutlineforthecatastrophic1997event,as wellasoutlinesforpriorevents.Thenewmapincludes

severaladditionalslideoutlinesmappedinengineering documentsandgeotechnicalreports.Thisincludedthe landslideoutlineforthecatastrophic1996–97failure ofthesoutheasternendoftheroad.

Figure6.SeattlecitylandslidemapatPerkinsLane,before(6A)andafter(6B)theupdate.Landslidesarerepresentedaspolygonsorpoints. Thenewmapincludesmanymorelandslideoutlinesandremovespolygonsthatwerenotsupportedbythehistoricrecord.Thecircular artifactinthe“before”panel(6A)waslikelyintroducedduringdigitizationofalower-resolutionMylarlandslidemap,inwhichdotswere plottedinthelocationsoflandslides.

WestSeattleNeighborhood,SunsetAvenue

AnotherexamplefromtheWestSeattleneighborhoodshowslandslidesthatwerecomplicatedbyinfrastructure(Figure7).OnFebruary10,1916,thefailureofawoodenbulkheadatSunsetAvenueandthe breakageoftheJerseyStreetsewer,whichranthrough theravinebetweenSunsetandAlkiAvenues,resulted inamudslidethatremovedpartofSunsetAvenueat 45thStreet(SEDP-61916,CityofSeattleDepartment ofTransportation,Seattle,WA,unpub.data,2019).

Propertiesonthe1300blockofSunsetAvenuewere damaged,andwater,sewage,andmudflowedinto atleastsevenofthehomesbelow.Thissamesewer mayhavebrokentheyearprior,in1915.TheJersey Streetsewerbrokeagain33yearslater,inassociation withanotherlandslide,damagingmanyofthesame downslopeproperties.

Ournewlandslidedatabasemapseachofthese events(Figure8).Thoughphotosweretakenfollowingthe1916slide,thefiledidnotcontainenoughin-

formationtodrawalandslideoutline.Thestraightsidedpolygonsufficestocovereverypropertythatwas namedasaffectedinthefile.Latereventsin1983and 1996–97arewelldescribedbygeotechnicalreports, whichincludeslideoutlines.

DISCUSSION

Thenewmapisaccuratewithrespecttothehistoricalrecordandoffersmanynewbenefitstoproperty owners,engineers,andcityemployees.Thenewmap tags12%fewerparcelsthantheoldmap(Table3). Propertiesaremoreaccuratelytagged,aseveryfeatureissupportedbyhistoricaldocuments,andfewer propertyownerswillberequiredtoprovidegeotechnicalanalysestodeveloptheirpropertiesduetomappingofknownlandslides.Thisupdatewillalsobenefitgeologistsandengineers,whowillhavefasterand morestreamlinedaccesstoinformationaboutspecificparcels.Whereasthelandslidefilesformerlywere onlyaccessiblethroughanin-personvisittoSDOT’s

Environmental&EngineeringGeoscience,Vol.XXVIII,No.4,November2022,pp.335–346

Figure7.Photosof1916landslidebelowSunsetAvenue,WestSeattle,fromfileSEDP-6,February11,1916.(A)Lookingupatthelandslide scarp.(B)WorkersstandinginadrainbelowSunsetAvenueslide.(C)Runoutbelowfailure.

Figure8.LandslidefeaturesinthenewmaparoundSunsetAvenueinWestSeattle.Landslideeventsaredenotedbyredboxes,polygons,or dots.Therewaslessinformationavailableabouttheoldereventin1916(representedbyabox)thanthosein1983and1996–97(represented bylandslideoutlines).SeveralothereventsoccurredandaremarkedwithlandslideinitiationpointsplacedbyShannon&Wilson,Inc.,in 2000.

engineeringoffice,nowindividualfilescanbedownloadeddirectlyfromthewebviewer.Cityemployees alsohaveeasieraccesstotheinformation,facilitating informeddecisions.

Comparedwithlandslidemapsproducedby othermethods,thehistoricalrecordprovidesmore metadata—forexample,informationaboutlandslide timing,triggers,andconsequences.Ofparticularinterestinthisinventoryareco-seismiclandslides,such asthosethatfollowedthe2001Nisquallyearthquake (e.g.,SED19-A,CityofSeattleDepartmentofTransportation,Seattle,WA,unpub.data,2019).Historic co-seismiclandslidescanbedifficulttoidentifyconfidentlyinothertypesoflandslidemaps,likethose producedthroughfieldmappingorLiDAR.Therefore, thishistoricaldatasetoffersnewopportunitiesforregionalresearchonmultihazards.

Completenessofthehistoricdatasetisdifficultto evaluatebecausetherealnumberoflandslideswithin

Table3. Numberofparcelsandtotalareacoveredbylandslidefeaturesinboththenewandoldmaps.Thenewmap,whichrepresents thebestinformationavailable,tagsfewerpropertiesandlessoverall areathantheoldmap.

OldNew%Reduction

Numberofparcels3,0502,65712.9 Totalarea(sq.ft)127,827,197.30116,580,425.298.8

thecitylimitsisunknown.Thehistoricalrecordonly representsasubsetofalllandslidestohaveoccurred duringthistimeperiod.Onlylandslidesreportedto orinvestigatedbytheCityofSeattlearedescribedin thedataset,solandslidesareunder-representedfrom less-populatedareas,newerneighborhoods,orneighborhoodslesslikelytoreportlandslides.Thehistoric datasetalsomissesprehistoricdormantlandslidesas mappedbypublishedgeologicmaps(e.g.,Troostand Booth,2008)ortheWashingtonGeologicalSurvey LiDARdatabaseasdescribedbelowin“Comparison withaLiDARLandslideInventory”(Mickelsonetal., 2019).

Theconsistencyofrecordkeepingoverthepasthundredyearshasbeencomplicatedbyturnoverincity employeesresponsibleforthedataset,avarietyoftechnologicaldevelopments,andseveralmunicipalreorganizations.Oversomeperiods,landsliderecordswere meticulouslymaintained.Duringothers,therewere fewerupdates.Becauseofthisincompleteness,care shouldbetakenwhenusingthedatabasetoevaluate spatiotemporaltrendsinlandslidesacrossSeattle.

ComparisonWithaLiDARLandslideInventory

In2019,WashingtonGeologicalSurvey(WGS) publishedaLiDAR-basedlandslideinventoryofwesternKingCounty,includingSeattle(Mickelsonetal., 2019).Comparedwiththehistoricdataset,theLiDAR

inventorycoversmoregroundandcaptureslandslides indifferentareas.ToproducetheLiDARinventory forSeattle,geologistsatWGSvisuallyidentified ∼800 landslidefeatureswithinSeattlecitylimitsusingLiDARimagesflownin2016with3-footgridresolution (Mickelsonetal.,2019).Landslidedeposits(N = 252), scarps(N = 286),flanks(N = 256),andfans(N = 11)weredigitizedbyhand.Theentiredatabasewasreviewedbyalicensedgeologist.Fortheinventory,37% ofslideswerefieldcheckedandslidefeatureswereassignedaconfidencelevelofhigh(49%oftotalslide areainSeattle),medium(36%),orlow(15%).

Comparedwiththehistoricdataset,LiDARmappedlandslidestagged7,070parcelsinSeattle, 4,413parcelsmorethanthenewhistoricdatabase (LiDAR-mappedslidestouched166%moreparcels thanhistoriclandslides).ManyofthelandslidesidentifiedinLiDARarelocatedinparksorgreenbelts wherelandslideswereless-frequentlyreported,orin largeswathsofhummockyterrainthatmayrepresentancientlandslidesnotdepictedinthehistoric record.Conversely,theLiDARinventorymissedlandslidesmappedinthehistoricdatabase,particularly indevelopedareas(e.g.,downtownSeattle)andon slopeswhereshallowsurficialslideswerethedominantslidemechanism(e.g.,alongsteepshoresofLake Washington).

WhencomparedwithallofSeattle’sECAs,which includeareasofsteepslopesandpotentiallandslide areasgivengeologicconditions,theLiDARinventory touchesonly3%moreparcelsthanexistingECAs,suggestingasimilarextentofhazardsasassessedbyboth methods.Consideredinconcert,theLiDARandhistoricinventoriesarecomplementary—LiDARlocates landslidefeaturesinless-disturbedareas,whilehistoric datamapslandslidesinmodifiedareasandprovides preciseagesfortheseevents.

CONCLUSION

ThiscasestudyfromSeattle,Washington,produced anurbanlandslideinventorywithhighaccuracywith respecttopropertyboundariesandpreciselandslide ages.Whileincomplete,thehistoricmaplikelyhas highergeographicalandthematiccorrectnessthan geomorphic-basedmapsfordevelopedsettings.When combinedwithotherhazardmapslikeaLiDAR landslideinventoryorareasofpotentiallandslides, thehistoricmapcontributestoacomprehensiveunderstandingoflandslidehazardwithinandoutsideof developedareas.Theinteractivehistoricmapandthe datausedtoproduceitareavailablethroughaGIS webviewer.ForusersinSeattle,thenewdatasetis moreaccurateandthepublicGISdisseminatesinformationmoreefficientlyandlikelymoreeffectivelythan

priormethods.Regionally,thenewmap,whichisunusualinitstemporalresolution,historicalreach,and inthequantityofinformationavailableforeachslide, willprovideacomparisonwithotherregionallandslideinventories,andmayfacilitateongoingstudies aboutcascadinghazardsintheregion,includingcoseismiclandslides.Onabroaderscale,thisdatasetadds totheglobalcatalogofhistoricallyrecordedlandslides andprovidesanexampleforothersengagedinsimilar efforts.

ACKNOWLEDGMENTS

ThisworkwasfundedprimarilybytheCityofSeattleDepartmentofConstructionandInspections.AdditionalfundingwasprovidedbytheCityofSeattleDepartmentofTransportation.DeanGriswoldof SDCIwasinstrumentaltothisprojectprovidingstories,historicperspective,andmappingassistance.We thankothergeotechnicalstaffatSDCIandSDOTfor theirreviews,carefulqualitycontrolchecks,andhumor.CityofSeattleemployeesscannedallofthedocumentsdescribedinthisstudy,andCityofSeattleGIS staffKenMarandChristinaThomasdevelopedthe toolsthatmadethisprojectpossible.Themanuscriptis improvedbyreviewsbyRobMcIntosh,JulietCrider, KelsayStanton,ErichHerzig,andthreeanonymous reviewers.

REFERENCES

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Baum,R.L.;Coe,J.A.;Godt,J.W.;Harp,E.L.;Reid,M.E.; Savage,W.Z.;Schulz,W.H.;Brien,D.L.;Chleborad,A.F.; McKenna,J.P.;andMichael,J.A.,2005, RegionallandslidehazardassessmentforSeattle,Washington,USA:Landslides, Vol.2,No.4,pp.266–279.

Booth,A.M.;Roering,J.J.;Perron,J.T.,2009,Automated landslidemappingusingspectralanalysisandhigh-resolution topographicdata:PugetSoundlowlands,Washington,and PortlandHills, Oregon:Geomorphology,Vol.109,No.3–4,pp. 132–147.

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CityofSeattle,WA,2015,MunicipalCode25.09.012, DesignationandDefinitionsofEnvironmentallyCriticalAreas: Electronicdocument,availableathttps://library.municode. com/wa/seattle/codes/municipal_code?nodeId=TIT25ENP RHIPR_CH25.09REENCRAR_25.09.012DEDEENCRAR

Guzzetti,F.;Mondini,A.C.;Cardinali,M.;andFiorucci,F., 2012,Landslideinventorymaps:Newtoolsforanoldproblem: Earth-ScienceReviews,Vol.112,No.1–2,pp.42–66.

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McKean,J.andRoering,J.,2003,Objectivelandslidedetection andsurfacemorphologymappingusinghigh-resolutionairbornelaseraltimetry: Geomorphology,Vol.57,No.3–4,pp. 331–351.

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SimpleShearStrengthAnalysisofInherentAnisotropy foraTropicalAlluvialSoil

ALSIDQIHASAN* NISAISMAIL

DepartmentofCivilEngineering,UniversitiMalaysiaSarawak,UNIMASWest Campus,94300KotaSamarahan,Sarawak,Malaysia

LEELINJYE

GeotechnicalandSlopeEngineeringUnit,SarawakPublicWorksDepartment,Wisma Saberkas,JalanTunAbangHajiOpeng,93582Kuching,SarawakMalaysia

KHALIDALSHIBLI

DepartmentofCivilandEnvironmentalEngineering,325JohnD.TickleEngineering Building,851NeylandDrive,TheUniversityofTennessee,Knoxville,TN37916

KeyTerms: AlluvialSoil,OrganicMaterial,Scanning ElectronMicroscopy,SimpleShear,Anisotropy

ABSTRACT

Tropicalalluvialsoilshaveunusualengineeringpropertiesandtheirbehaviorisnottypicaloffine-grained soils.Theliteratureregardingstrengthpropertiesof alluvialsoilsislimited.Thisstudypresentsanexperimentalevaluationofinherentanisotropyofundisturbed tropicalalluvialsoilsamplesbycomparingthedirect simpleshear(DSS)testresultsof52specimenscut inhorizontalandverticalorientations.Thetestswere carriedoutunderconsolidatedundrainedconstantvolumewithexcessporewaterpressuremeasurements. Thepeakshearstrength,effectivestresspaths,and secantshearmodulusanalysesshowedthatthedifferenceinpropertiesbetweenhorizontallyandvertically cutspecimenswasnegligible.Nonetheless,theresults forverticallycutspecimenspresentedahigherrandom errorcomparedtotheresultsforhorizontalspecimensin allaspects.Agoodrelationshipbetweentheundrained shearstrengthandover-consolidationratiowasfound butwasnotcomparabletopastDSSresultsfornatural clays.Scanningelectronmicroscopyimagesrevealed flocculatededge-to-edgeandedge-to-faceparticleassociations.Directionalityanalysisofmicrofabricshowed thatthealluvialsoilshadlowpreferredorientationof particles.Thegeneralnotionthatallalluvialsoilsare highlyanisotropicwasnotevident,basedontheexperimentsreportedinthisstudy.Thefindingshereinare usefulforgeotechnicalengineerstobetterunderstand thestrengthbehavioroftropicalalluvialsoils.

*Correspondingauthoremail:halsidqi@unimas.my

INTRODUCTION

Tropicalalluvialsoilsexhibitunusualphysicalcharacteristicsandengineeringpropertieswhencompared tocommonsedimentarysoils(Zhangetal.,2004). Theirparticlesoriginatefromprofilesthataredeeply andcontinuallyweathered;theyareexposedtoa highernumberofweatheringcyclesthanalluvialsoils insubtropicalortemperateregions(Edelmanand vanderVoorde,1963;Buringh,1979).Suchweatheringprocessesinfluencemicrofabricpropertiessuch asgrainsize,composition,arrangement,andparticleshape,whichsignificantlyaffecttheirengineeringproperties(MitchellandSoga,2005;Alshibli andHasan,2008;HasanandAlshibli,2010).Fabric anisotropy,alsoknownasinherentanisotropy,isassociatedwiththesedimentationprocessthatusually leadstodifferentmechanicalresponses(Yimsiriand Soga,2000;LeungandNg,2004).Todate,theeffect ofinherentanisotropyonthemechanicalbehaviorof tropicalalluvialsoilshasnotbeenthoroughlystudied usingundisturbedsamples.

Thenecessityforexpansionofinfrastructuredevelopmentintotropicalalluvialsoilschallengesengineers todesigntheproperfoundationsystemstosupport heavystructures.Thesoft,deepnatureofthesoiloften requiresfrictionpilefoundationstobeusedtosupport structures.Thisrequiresathoroughunderstandingof themechanismsthatgovernthesoil–pileinteraction, whichcanbeapproximatedusingthedirectsimple shear(DSS)test,widelyusedtocharacterizestaticor cyclicstrengthpropertiesofsoilswithvarioustypes ofDSSapparatus(e.g.,BjerrumandLandva,1966; RandolphandWroth,1981;Budhu,1984).Initsapplications,theDSStesthasbeenprimarilyusedtocharacterizemarineclaysandoffshoresoils(e.g.,Talesnick

andFrydman,1991;Lanzoetal.,2009).Comparedto thedirectshearboxtest,theDSStestnotonlyrepresentstheclosestapproximationtotherealshearingmechanismwithinthesoil,butalsooffersbetter stressuniformityandmoreconservativestrengthproperties(Hanzawaetal.,2007).ThelackofsoilcharacterizationassociatedwithusingtheDSStestisdue tothelimitedavailabilityofsuchtestapparatusand thevariabilityofcomplexanalysesinvolved.Studies tocharacterizestrengthpropertiesofalluvialsoilshave beencarriedoutonlybyusing in-situ tests,directshear boxtest,ortriaxialtests(YilmazandKaracan,1997; Mlynareketal.,2012).

Theobjectiveofthisstudywastopresentexperimentaldatafromsimpleshearstrengthtestsofa tropicalalluvialsoilfocusingonthesoil’sinherent anisotropy,whichwasevaluatedbycomparingthetest resultsandanalysesof52undisturbedspecimensthat weresampledintwoorthogonalcuttingorientations (i.e.,horizontalandvertical).Thestudyexaminesthe generalbeliefthatalluvialsoilparticlesarealwaysdepositednaturallyviaacertainangleduringthesedimentationprocessandtherefore,thestrengthcharacteristicsofthesoildependonthespecimenorientation. Theimportanceofthisexaminationcanbedirectlyappliedinanalyzingtheshearingmechanismofsoiladjacenttopilesduringthepileinstallationdriving.

SAMPLEACQUISITIONAND CHARACTERIZATION

Thestudyareacoveredthreedifferentsitesnearthe estuariesofRajangRiverintheSarawakregionof northernBorneo,Malaysia:MuaraLassa(location1, 2°26 48 N.,111°31 24 E.),BatangPaloh(location 2,2°22 4 N.,111°25 47 E.),andBatangRajang(location3,2°11 22 N.,111°33 50 E.).TheSarawak regionreceiveshighratesofrainfallanddenudation (VijithandDodge-Wan,2020).TheRajangBasinis oneofthetwomajorcatchmentsystemsthatbring sedimentfromthehighlandstothecoastalregion, whichismostlyunderlainbyriveralluviumsoilsthat weregeneratedduringthePleistoceneEpoch(Jabatan MineraldanGeosains[JMG],2020).Theselocations layinthecenterofthealluvialregion,wherenumerousbridgeandwharffailureshaveoccurreddueto soilconditions(Leeetal.,2013).Currently,thereare threeoutoftenlongbridgesbeingconstructedinthese locationsaspartofacoastalroadnetworkproject (SarawakCoastalRoadNetwork,2021).

Inallthreestudylocations,undisturbedsoilsampleswereextractedfromboreholesusingathin-walled sampler(Shelbytube)thatconformedtoindustrial standardpracticeBS-5930(BritishStandards[BS], 1999).Thesamplerusedwasastainlesssteeltubewith

anouterdiameterof63.5mm,awallthicknessof1.0 mm,alengthof600mm,andacuttingedgeofabout 60° withrespecttothelong-axis;thiswasgreaterthan the5° suggestedbyHightandLeroueil(2003).Acuttingshoeandcorecatcherwerenotused.Theinside clearanceratiowas0percent;thatis,thewallwasflush (straight)fromedgetoedge,lowerthanthe1percent recommendedbyBS-5930(BS,1999).Theratiobetweentheouterdiameterandthewallthicknesswas 63.5,greaterthanminimumrecommendedratioof45 byLaddandDeGroot(2003).Thesecriteriawould yieldthebestqualityundisturbedsamples(Clayton etal.,1998;LaddandDeGroot,2003;Lowetal., 2011).Alltheundisturbedsamplesinthethin-walled samplerwereplacedincushionedboxesandcarefully transportedtothelaboratorytoensureminimumdisturbancetothesoil.Therecoveryratioinallsampling wassuccessfullyobtainedintherangeof75100percent.Priortoeachtest,anadequatesoilsamplewas takenfromthethin-walledsamplerusingahydraulic extruder.

Someofthesampleswereusedforindexproperty teststoevaluatethephysicalpropertiesofthesoils (Table1).Thesampleshadabout8–10percentorganic material(matter)thatcausedaslightlylowerspecific gravityofsolidsvalueswhencomparedtoinorganic soils.However,theorganicfiberwasnotapparent.The organicmatterwasidentifiedonlybythepatchydark colorwithinthesamplesandthedarkcolorsuspensioninthewaterduringspecificgravityandhydrometertests.Theextrudedsampleshadanaturalwater contentslightlylowerthantheirliquidlimits.Toqualifyfororganicclassification,ASTM-D2487(American SocietyforTestingandMaterials[ASTM],2017a)requiredtheliquidlimittobeperformedonbothovendriedandnot-driedspecimens.Figure1showstheparticlesizedistribution(bymass)ofthesoilsamples determinedbyusingthehydrometertestprocedure (ASTM-D422;ASTM,2007).Itshowsthatallsampleparticleswereprimarilywithinthesiltsizerange. Thesampleswereclassifiedassandyorganicsilt(OH) accordingtotheUnifiedSoilClassificationSystem (ASTM-D2487;ASTM,2017a).TheelementalcompositionbypercentofmassusingenergydispersiveXrayspectrometerislistedinTable2.

DIRECTSIMPLESHEAR(DSS)EXPERIMENTS

DSSApparatus

DSSexperimentswereconductedusinganelectromechanicalsimpleshearapparatus,ElectromechanicalDynamicCyclicSimpleShearDevice(EMDCSS;GDSInstruments,Hampshire,U.K.;Figure2). Themaincomponentsoftheapparatusweretwo

Table1. Indexpropertiesofthetropicalalluvialsoilsamples.

LiquidLimit(%)2 PlasticLimit(%)2 PlasticityIndex,PI2

Location SpecificGravity ofSolids(Gs )1 Non–OvenDried OvenDried Non–OvenDried OvenDried Non–OvenDried OvenDried Organic Matter(%)3 Moisture Content(%)4 12.507254433327218.058.7 22.428057443237258.157.7 32.4972474423282410.658.1

1 ASTM-D854;ATSM,2014.

2 ASTM-D4318;ATSM,2017b.

3 ASTM-D2974;ATSM,2020.

4 ASTM-D2216;ATSM,2005.

ASTM = AmericanSocietyforTestingandMaterials.

Figure1.Particlesizedistributions.

loadingactuators,twodisplacementmeasuringsensors,twoforcemeasuringsensors,ahydraulic pressure-volumecontrollersystem,andalateralconfinementdevice.Thetwoloadingactuatorsapplied vertical(axialornormal)loadtothespecimentop capandhorizontalorshearloadtothespecimenbase pedestal.Duringshearing,theverticalactuatorcould befixedviapassiveheightcontrolwithnorotation whilethehorizontalactuatorappliedshearloadvia astrain-controlledloadingmode.Built-inencoders withintheactuatorsmaintainedtheirprecisestrain rateduringloading.Thedisplacementmeasuringdevicesincludedaverticalandahorizontallinearvariabledifferentialtransformercapableofmeasuringdisplacementwithanaccuracygreaterthan99.9percent full-scaleoutput.Theforce-measuringsensorsconsistedofverticalandhorizontal10-kNcapacity“pancaketype”loadcells“in-line”withtheactuators.The hydraulicpressure-volumecontrollerappliedandmeasuredporewaterpressure(backpressure)withinthe specimen(Figure2a).Thelateralconfinementdevice

consistedofastackofTeflon-coatedringsthatencircledthecylindricalsoilspecimen.Theinnerdiameter, outerdiameter,andthicknessoftheringswere51,6.5, and1mm,respectively.Alldeviceswereconnectedtoa dataacquisitionsystemtocontrolaswellastoregister themeasurementsinacomputersystem.TheEMDCSSdevicecouldbesetandruninafullyautomatic modefromtheconsolidationstageuntiltheendofthe shearingstage.

Specimens

Thespecimenswerecylindrical,measuring50mm indiameterand20mminheight,whichconformed toASTM-D6528(ASTM,2017c).Theyweretrimmed fromextrudedShelbytubesamplesusingaspecial ring-shapedcutterwithasharpedgetominimizedisturbanceduringspecimencutting(Figure3aandb). Thespecimenswerecuthorizontallyandvertically.Table3listsallspecimensusedintheDSStestsandtheir cuttingorientations.Samplesfromlocation1weredividedintosixgroups(group1to6):threegroupswere cuthorizontally;theotherthreewerecutvertically. Thesamplesfromlocations2and3wereeachdivided intotwogroups(group7to10):onegroupwascuthorizontally,theothervertically.Eachgroupconsistedof threetosixspecimens.Thetotalnumberofgroupsand specimenswere10and52,respectively.The insitu verticalstress(σ v 0 )ofthespecimenswascalculatedfrom thesaturatedunitweight(γsat )andthedepthofthe samples.

Afterbeingtrimmed,eachspecimen(withthecutter)waspre-saturatedbybeingsubmergedintapwater for3days.Pre-saturationwasfoundtobeveryuseful

forexpeditingthesaturationstageduringtesting. Nospecimensexhibitedswellingafterpre-saturation. Thepreparationbeforethetestwasaccordingtothe followingsequence:(1)Thespecimenwasremoved fromthecutter;(2)specimenwasplacedonthebase pedestal;(3)specimenwasenclosedinalatexmembraneusingaspecialmoldwithasuctionhose;(4) thelatexmembrane(0.5mmthick)wassealedusing arubberO-ringatthebottom(Figure3c);(5)the specimenwasenclosedwithinalateralconfinement deviceconsistingofastackofTeflon-coatedrings (Figure3d),madeslightlylongerthanthespecimen toproperlyinsertthetopcap;(6)thetopcapwas lowereduntilittouchedthesurfaceofthespecimen; and(7)thelatexmembranewasstretchedaround thetopcapandsealedwithtworubberO-rings (Figure3e).

Notethatthelatexmembranewasusedtodirectly measuretheexcessporewaterpressure(e.g.,Ishihara andYamazaki,1980;MengandChu,2011;Lietal., 2017).Thediameterofthemembranewasslightly lessthan50mmtoprovidesubstantialliningbetweenthespecimenandrings.Theinitialmembrane resistance(hoopstress)wasverysmall,andmembraneresistancecorrectionduringverticalloadingwas notneededsincethespecimenwasrestrictedbythe rings(Greeuwetal.,2001).Theringsmaintaineda constantdiameterofthespecimenthroughoutthe testwithminimalfriction.Afterthetest,thespecimendeformedfollowinganobliquecylindershape (Figure3f).

TheDSSexperimentswereconductedaccordingto ASTM-D6528(ASTM,2017c)standardexceptforthe drainagecondition,wherespecimenswerecompletely

Figure2.GDSEMDCSS(GlobalDigitalSystems,ElectromechanicalDynamicCyclicSimpleShearDevice)directsimpleshearapparatus. (a)Thepictureoftheapparatusand(b)theschematicdiagram.

Table3. Specimendetails.

Location Group NumberGroupName

Numberof Specimensin EachGroup

Depthfrom GroundLevel (m)

SaturatedUnit Weight, γsat (kN/m3 )

Insitu Vertical EffectiveStress, σ v 0 (kPa) Cutting Orientation 11M1-H612.515.874.8Horizontal 2M2-H66.516.342.0 3M3-H621.516.3140.4 4M1-V69.015.047.3Vertical 5M2-V512.515.874.5 6M3-V413.516.286.5 27P-H412.515.874.5Horizontal 8P-V64.515.626.0Vertical 39R-H615.516.4102.5Horizontal 10R-V34.516.229.0Vertical

H = horizontal;V = vertical.

sealed(undrained)throughouttheshearingphaseof thetestandporewaterpressurewasmeasured.Once apre-saturatedspecimenwasfullypreparedinthe DSSapparatus(withtopcapinplaceandsealed),the testcommencedfirstwithamanualsaturationcheck. Backpressurewasincreasedwhilethetopcap(verticalactuator)wasfixedandseatingpressurewasmaintainednearlyconstantforafewminutes.Backpressurewasthenstoppedandthespecimenwasslightly compressed.Ifporewaterpressureincreasedrapidly (<15seconds),itwasassumedthespecimenwasfully saturated.Notethatthesaturationcheckfolloweda proceduresimilartothecontrolled-strainloadingconsolidationtest,ASTM-D4186(ASTM,2012).

Thenextstepwastoconsolidatethespecimenaccordingtothetargetconsolidationpressure(σ z 0 ), between20kPaand640kPa(Table4).Theoverconsolidationclassificationwascalculatedbasedon insitu verticalstress(σ v 0 ).Thenumberofoverconsolidated(OC)andnormallyconsolidated(NC) specimenswere18and34,respectively.Duringconsolidation,porewaterwasallowedtodrainfromthe

specimenintothehydraulicpressure-volumecontrolleruntilexcessporewaterpressuredissipated(Figure3g).Sincethesoilwasmainlysilt,theconsolidation phasewasachievedrelativelyquickly;forexample,in 640kPaconsolidationpressure(σ z 0 ),theconsolidationterminatedwithin0.5hours.Oncetheconsolidationphasewascompleted,theverticalactuator waslockedinpositiontomaintainaconstantsample height.Thehorizontalactuatorappliedtheshearload bymovingthebasepedestalwithaconstanthorizontaldisplacementrateof5mm/hour.Duringshearing, porewaterdrainagewasalwaysclosed(undrained), andexcessporewaterpressure( u)wasmonitored. Sincewaterisnearlyincompressible,aconstantvolumecouldbeassumed(Figure3h).

Thevertical(normal)load, Fz (kN);horizontal (shear)load, Fh (kN);horizontal(shear)displacement, x (mm);andtheexcessporewaterpressure, u (kPa) wererecordedevery5seconds.Fromthesedata,vertical(normal)stress, σz (kPa);shearstress, τzx (kPa);and shearstrain, γzx (percent)werecomputed.Theshearingwasterminatedatabout14mmhorizontal(shear)

M1-H674.820(OC),40(OC),80(NC),160(NC),320(NC),640(NC) M2-H64220(OC),40(OC),80(NC),160(NC),320(NC),640(NC)

M3-H6140.420(OC),40(OC),80(OC),160(NC),320(NC),640(NC) M1-V647.320(OC),40(OC),80(NC),160(NC),320(NC),640(NC)

M2-V574.520(OC),40(OC),80(NC),160(NC),320(NC)

M3-V486.540(OC),80(OC),160(NC),320(NC) P-H474.540(OC),80(NC),160(NC),320(NC)

P-V62620(OC),40(NC),80(NC),160(NC),320(NC),640(NC)

R-H6102.520(OC),40(OC),80(OC),160(NC),320(NC),640(NC)

R-V32940(NC),80(NC),160(NC)

H = horizontal;V = vertical;OC = over-consolidated;NC = normallyconsolidated.

Figure4.Voidratioversusnormalizedconsolidationpressure.

travelofthebasepedestal,whichwasequivalentto ashearstrain(γzx )of70percentorashearangleof 35° withrespecttotheverticalaxis.Aftershearing,the horizontalactuatorwasretractedtoitsinitialposition toeaseindismantlingthespecimen.Watercontentwas measuredandthetestwascompleted.

RESULTS

ConsolidationPhase

Figure4showscompressibilityplotsofthevoidratio(e)andlogofnormalizedconsolidationpressure withrespectto insitu verticalstress(σ z 0 /σ v 0 )forall specimens.Eachdatapointrepresentstheresultofone test.Forfullysaturatedspecimens,thevoidratio(e)is calculatedasfollows: e = w Gs (1) where Gs isthespecificgravityofsolidsand w iswatercontentofthespecimen.Thecurvesindicatethat asnormalizedconsolidationpressureincreases,void ratiodecreasescorrespondingtotheamountofpore waterpressuredissipationfromthespecimens.The curvesslightlyturnatnormalizedconsolidationpressureequaltounity,whichdemonstratesthatthespecimensarenormallyconsolidated.Thisconclusionisin agreementwiththefactthattherewasnorecordofany structures,hills,orfillontopofthesoildepositinthe past.

ShearingPhase

Figure5showstherelationshipofshearstress, τzx (kPa);excessporewaterpressure, u (kPa);andtotal verticalstress, σz (kPa),versusshearstrain, γz (percent)forM1-Hspecimens.Theresultsofallother specimensaregiveninAppendixA(seeSupplemental

Material,AppendixA).Overall,shearstressincreased asshearstrainincreaseduntilitreachedthepeak shearstressstate,afterwhichitgraduallyplateaued. Thepeakshearstressstateexisted(obviouslyvisible)forthespecimenswithconsolidationpressuresof 160kPaandhigherthatwereattainedbefore20percentofshearstrain.Afterthepeak,mostcurves reachedresidualstates(well-plateauedcurve)except forspecimenswith640kPaconsolidationpressure. Thecurveslopeanglebeforethepeakstateindicated thattheshearmoduluscorrespondedtoconsolidation pressure,whichwasaresultofreducingvoidratio(increasingindensity)asevidencedinFigure4.

Excessporewaterpressurechangeswerebetween2 and 4kPa,whichisquiteinsignificantcomparedto changesinverticalstress.Hence,therewasnoequalitybetweenchangeinverticalstresswithchangein porewaterpressure,whichdisagreeswiththeassertion fromBjerrumandLandva(1966).Theyconducted aconstant-volumedraintestbutasserted(strongly predicted)theequivalencybetweenchangeinvertical stressandchangeinporewaterpressure(inaconstantvolumeundrainedtest).Forthemostpart,theexcess porewaterpressurecurvestendedtodecreaseasshear strainincreased.Thechangeintheexcessporewaterpressuremighthavebeenduetothedistribution ratewithinthespecimenduringshearing,whichcorrelatedwiththeuseddisplacementrate.Thetotalverticalstresscurvesdecreasedasshearstrainincreased andgraduallydiminishedtoapproximatelyaconstant (plateau)valueafter20percentofshearstrain.The specimenswithhigherconsolidationpressureshowed amoresignificantdecrease.Fromvisualobservation, therewasnoevidenceofslippagebetweenthetopcap orbasepedestalandthespecimenduringshearingin anyspecimen.Thetopcapandbasepedestalhadcorrugatedsurfacesthathelpedpreventslippageevenat thelowestconsolidationpressureof20kPa.Afterbeingsheared,thespecimensformedanobliquecylinder shape,andthesideswereinclined.

ANALYSESANDDISCUSSIONS

PeakStrength

Figure6aandbshowplotsofthepeakshear strength(τzx, max )andcorrespondingverticalstress(totalandeffective)forOCspecimens.Theresultsof NCandthecombinationofOCandNCspecimens aregiveninAppendixB(seeSupplementalMaterial,AppendixB).Notethatpeakshearstrengthis equaltomaximumshearstrengthduringshearing. However,ifthepeakisnotreachedbefore20percent ofshearstrain,thentheshearstressat20percentshear strainistakenasthepeak.The20percentshearstrain

Figure5.M1-Hspecimens:results.(a)Shearstressversusshearstrain,(b)excessporewaterpressureversusshearstrain,and(c)totalvertical stressversusshearstrain.

isassociatedwithpracticalserviceabilitylimit,and ASTM-D6528(ASTM,2017c)specifiesamaximum shearstrainof20percentinasimplesheartest.The datawerefittedintotheMohr–Coulombmodelassumingtherelationshipsstartedfromtheoriginofcoordinates.Thisassumptionwasmadebasedonthevisualobservationthattherewasnotruecohesionfound inthesamples;thatis,theunconfinedsamplecouldbe easilybrokenifsubmergedinwater.

TheNCspecimensexhibitedaverygoodfitwiththe Mohr–Coulombmodel.Basedoncoefficientsofdetermination(R2 ),horizontallycutspecimensshowed abetterrandomerrorthanverticallycutspecimens. Similarly,effectiverelationshipswerebetterthantotal stressrelationships.Thecurvefittingshowedslopesof 0.44and0.23foreffectiveandtotalcases,respectively. Therewasnodifferenceintermsofslopebetweenhorizontallyandverticallycutspecimens.Also,thecombinationofOCandNCdidnotchangetheslope.Becausethe y-axisinterceptwaszero,thepeakeffective frictionangle(ϕ dss )andtotalfrictionangle(ϕdss )were calculatedas:

TheOCspecimensshowedapoorerfitforthe Mohr–CoulombmodelwhencomparedtotheNC specimens.However,theslopewasnotsignificantlyaffectedwhenOCdatawerecombinedwithNCdata. TodescribetheeffectofOCtothemaximumshear strength,ageneralizedempiricalfunctionwasadopted

fromLaddetal.(1977): cu σz 0 = C × OCR (4) OCR = σ p σz 0 (5) where cu istheundrainedshearstrength(i.e.,equivalenttomaximumshearstrength[τzx ,max ]), σ z 0 isconsolidationpressure, C and areconstants,OCRis theover-consolidationratio,and σ p ispastmaximum pressureequivalenttothecurrent insitu verticalstress (σ v 0 )inthisexperiment.Theconstant C wasused todeterminetheupperboundorlowerboundlimits. Mayne(1988)collectedDSStestdatafornaturalclays andproposed0.35,0.15,and0.8forupperbound C, lowerbound C,and ,respectively.Figure7shows log-logscaleplotsofnormalizedpeakshearstrength versusOCRforthepresentdata,upperboundand lowerbound(Mayne,1988),anddatafromalluvial claytill(AtkinsonandLau,1991).Theplotsshowthat datapointsscatterwithinandbeyondtheupperbound andlowerboundplotsofnaturalclays.Thepresent datafittingintoEq.4showedasignificantdifference intermsofslopewhen wascomparedtoMayne’s (1988).The forhorizontalandverticalspecimens wasfoundtobe0.46and0.38,respectively.The C valuesforhorizontalandverticalspecimenswere0.25 and0.28,respectively.However,DSSdataofalluvial claytillweresomewhatinagreementwiththepresent data.Thus,theslope( )mightbedependentonsoil type.Despitethesimilarityincurve-fittingcoefficients, thedatapointsfortheverticalspecimenshowedasignificantlyhigherrandomerrorindicatedbyalower R2 valuecomparedtothehorizontalspecimens.

Figure6.Maximumshearstrengthversustotalandeffectiveverticalstressforover-consolidated(OC)specimens.(a)Horizontallycutspecimensand(b)verticallycutspecimens.

DSSEffectiveStressPathontheHorizontalPlane

Figure8aandbdisplaysplotsofeffectivestress pathsonthehorizontalplaneforM1-HandM1-V specimens,respectively.Resultsofallotherspecimens aregiveninAppendixC(seeSupplementalMaterial, AppendixC).Datapointsfromhorizontallycutspecimensandverticallycutspecimensarecomparedside byside.Theeffectivestresspathsareusedtokeeptrack ofshearstress(τzx )aftertheconsolidationstageuntiltheendofshearingstage.Allcurvesinitiatedwith verticaleffectivestressequaltoconsolidationpressure (σ z 0 ),andshearstress(τzx )wereequaltozero.At thispoint,since τzx = 0,the x-axismustbeatthe principalstressplane.Asshearstrengthincreased, τzx and σ z werenolongeraprincipalstressplanesince τzx 0.Thetrajectoryofeffectivestresspathscurves towardstheleft,wheretheverticaleffectivestressreducesgradually.Interestingly,theirshapesaresimilar totheeffectivestresspathsofconsolidatedundrained triaxialtests,althoughtheincreaseofporewaterpres-

sureinthepresentDSStestswasinsignificant;thatis, themeasuredverticalstresswasalmostequaltotheeffectiveverticalstress.Aftershearstrengthreachedits maximumvalue,bothshearstrengthandverticaleffectivestressdecreasedandfinallyterminatedalongthe failurelines.Sincealltestshadbeenshearedtolarge shearstrain,thefailurelinesmustlieonthecritical stateline(CSL).

Recentnumericalstudiesshowedthattheprincipal stressplaneandtheplaneofmaximumstressobliquity (maximum τ/σ z )rotatecontinuouslyasshearstrain increasesandthehorizontalplanebecomestheplane ofmaximumstressobliquityatlargestrains(Doherty andFahey,2011;Wijewickremeetal.,2013).Basedon thisfinding,theCSLshowninFigure8aandbshould beattheplaneofmaximumstressobliquity,thatis, tangenttoMohr’scircle.TheDSScriticalstatefriction angle, ϕ cs,dss iscomputedas: tan ϕcs,dss = τzx σz (6)

Figure7.Log-logscaleplotsofnormalizedpeakshearstrengthversusover-consolidationratio(OCR).

Figure8.Directsimpleshear(DSS)stresspaths;shearstressversusverticalstressdifferentiatingbetweenhorizontalandverticalspecimens. (a)M1-Hspecimensand(b)M1-Vspecimens.

TheCSLsshowedthattheaveragefrictionangles forhorizontalspecimensandverticalspecimenswere 23° and24.2°,respectively.Thehorizontalspecimen’s frictionanglewasslightlylowerthanthepeakeffective frictionangle.

SecantShearModulus(G50 )

Thesecantmodulusparameterisusefulforgeotechnicalengineerstoapplyinfoundationengineering practicetopredicttheelasticdeformationduetoshear. Itistheratiobetweenthechangeofshearstress andshearstrain,whichreducesprogressivelywith theshearstrain(VardanegaandBolton,2013;Dong etal.,2018).Theelasticcomponentinshearstrain canbeapproximatedwiththeratioofshearstressat halfofthepeakandthecorrespondingshearstrain (LambeandWhitman,1969).Itisusefultofindthe relationshipsbetweenmodulusandlevelsofapplied stressratherthannormalizingwithundrainedshear strength(Caseyetal.,2016).Figure9showsplotsof elasticshearmodulus, G50 ,forhorizontalandverticalspecimensagainsttheverticaleffectivestress(σ z ). Therangeofshearmoduluswasbetween95kPaand 14,000kPa,withintherangeoftypicalvaluesreported intheliterature.

TheNCspecimens(forbothhorizontalandvertical) showedagoodfitwithapowerfunction.Thefitting forhorizontalspecimensshowedahighercoefficientof determinationcomparedtotheverticalsamples.However,theover-consolidatedspecimens(forbothhorizontalandvertical)showedscattereddatapointsand didnotshowgoodrelationships.Thismightbedueto thestresshistoryofthespecimens,andadetailedinvestigationisrecommendedforfutureworks.

DirectionalityofMicrofabric

Theinherentanisotropyofthesoilswasquantified bymeasuringthemicrofabricdirectionality(orientation)inscanningelectronmicroscopy(SEM)imagesof averysmall,thinfractionofdriedsamples(Figure10). TopreparetheSEMsamples,undisturbedsamples fromdepthsof6.5m(location1),4.5m(location2), and4.5m(location3)wereovendried.Whencompletelydry,thesamplesweremanuallysplitinaverticalorientation.Athinsliceofuntouchedexposed surfacewascarefullycutandplacedintotheSEM sampleholder(note:theuntouchedsurfacefacedupward).TheSEMimageswerecroppedintosquare images(900 × 900pixels)toremoveimagelegend andscalebar.Thesesquareimages,whichrepresented 44 μm × 44 μmofactualsize,areshowninFigure 10atoc,left,forlocations1,2,and3,respectively.The SEMimageswereprocessedandanalyzedusingFiji

Figure9.Secantshearmoduli. G50 comparisonbetweenhorizontal andverticalspecimens.

software,basedonImageJsoftwarethatprovidedan open-sourceplatform,processingtools,andpluginsto conductimageanalyses(Schindelinetal.,2012).

TheSEMimagesrevealedflocculatededge-to-edge andedge-to-faceparticleassociations.ThemicrofabricintheSEMimageswasdominatedbyflake-shaped clayparticles(inadditiontoroundsiltparticles);their direction(orientation)couldbedeterminedfromthe orientationoftheiredges.Theedgesweredetected withtheFijiprocessingtoolFindEdge,whichusesthe Sobeledgedetectorandhighlightsthesharpchanges inlocalintensity.Theresultsoftheedgedetectionare showninFigure10atoc,middle,asscribble(random)linesrepresentedbywhitepixels.TheorientationsoftheselineswerequantifiedviatheDirectionalityplugin(Liu,1991;Deravietal.,2017;Sensinietal., 2018).ThepluginusedFouriercomponentsanalysisthattransformedtheimageintoFourierpower spectra.Thespectrawereusedtocalculatespatial

Figure10.Directionalityofmicrofabricofspecimens:(a)location1,vertical;(b)location2,vertical;(c)location3,vertical;(d)location1, horizontal;(e)location2,horizontal;and(f)location3,horizontal.

frequencieswithinanimageinagivensetofradialdirections.Figure10atoc,right,arepolarbarcharts withabinsizeof2° orientedina0° to360° orientation.Eachbinrepresentsanormalizedamountof linesinagivendirection.Thehighestpeaksofthebar chartswerefittedbyGaussianfunctiontodetermine theorientationsandthegoodnessoffit.Theanalysis showedparticleorientationsof15.9° , 1.6°,and18.3° withrespecttohorizontalandgoodnessoffitof0.51, 0.54,and0.65(in0–1range)forsamplesinlocations 1,2,and3,respectively.Theaveragegoodnessoffitof 0.57indicatedpoorpreferentialdirection.Therefore,it wasconcludedthatthetropicalalluvialsoilsfromthe threelocationshadlowpreferredorientationofparticles,asinlowinherentanisotropy.Suchbehaviorwas similartosoftmarineandbrackish-waterilliticclays (MitchellandSoga,2005).Forthepurposesofcomparison,directionalityanalysiswasalsoconductedfor thinslicestakenfromhorizontallysplitsamples(at thesamedepths).Thesameprocedureswereapplied asthosefortheverticallysplitsamples.Theimages areshowninFigure10dtofforlocations1,2,and 3,respectively.Theanalysisforsamplesinlocations1, 2,3showedparticleorientationsof 5.1° , 53°,and 96° withrespecttohorizontalandgoodnessoffit of0.52,0.17,0.46,respectively.Theaveragegoodness

offitof0.38indicatedpoorpreferentialinhorizontal direction.

CONCLUSIONS

DSStestingandanalysesofatotalof52specimens wereconductedforundisturbedtropicalalluvialsoils ofnorthernBorneo.Theanalysescomparedtheinherentfabricanisotropyeffecttothestrengthcharacteristicsofthesoilsbygroupingspecimensintotwo cuttingorientations,horizontalandvertical.Itisconcludedthattherewasnosignificantdifferencebetween thestrengthcharacteristicsofhorizontallyandverticallycutspecimensduetolowpreferredorientation ofparticles.However,datashowedthatthevertically cutspecimenshadasignificantlyhigheroccurrence ofrandomerrorscomparedtohorizontallycutspecimens.Thefollowingarethemainconclusionsfrom thisstudy:

1.Peakstrengthanalysisshowednodifferencebetweenhorizontallycutandverticallycutspecimens. UsingMohr–Coulombmodelfitting,horizontal andverticalspecimentypeshadpeakeffectiveand totalfrictionanglesof23° and13°,respectively. However,theresultsoftheverticallycutspecimen

showedalowercoefficientofdetermination, R2 , whencomparedtothehorizontalspecimens.

2.Therelationshipbetweennormalizedshearstress andOCRhadagoodfitwithexponentialsfunction usingadifferent valuefromDSStestresultsof compilednaturalclays.Thepresentresultsgave valuesof0.46and0.38forhorizontalandvertical specimens,respectively.

3.Effectivestresspathsshowedthatthetrajectory endedatCSLs.TheslopeanglesoftheCSLswere 23° and24.2° forhorizontalandverticalspecimens, respectively.

4.Goodrelationshipswerefoundforbothhorizontal andverticalspecimensforanormallyconsolidated case.

5.QualitativeandquantitativeanalysesofSEMimagesshowedthatthealluvialsoilshadlowpreferred orientationofparticles.

SUPPLEMENTALMATERIAL

SupplementalMaterialassociatedwiththisarticle canbefoundonlineathttps://www.aegweb.org/e-egsupplements.

ACKNOWLEDGMENTS

TheauthorswouldliketoacknowledgethefinancialsupportfromindustrialresearchgrantIG/ F02/SSMC/2019:GeotechnicalCharacterizationof SarawakSoftMarineClay,fundedbySarawakPublic WorksDepartment,Sarawak,Malaysia,incollaborationwithUNIMASHoldingSdnBhd.

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DisturbancebyElectricalResistivityTomography Interpretation

AMARPRAKASH* ABHAYKUMARBHARTI ANIKETVERMA

MineSubsidenceandSurveying,CentralInstituteofMining&FuelResearch, Dhanbad,India826015

KeyTerms: Pole-Dipole,Wenner-Schlumberger,MineSubsidence,Topography,Resistivity

ABSTRACT

Thefocusofthestudywastoevaluatetherockstrata transformationaboveanundergroundminepanelduring pre-and-postminingbasedonanelectricalresistivitytomography(ERT)geophysicaltechnique.Thedatawere acquiredusingtwoelectrodearrays(i.e.,pole-dipoleand Wenner-Schlumberger[WS])withelectrodespacingof 6mupto570minlength.Theresistivitydatawere digitallyprocessedthroughRES2DINVsoftware.The formationoffracturedrockintheoverburdencaused byundergroundminingoperationswasclearlydistinguishedbyresistivityanomaliesobservedusingthepoledipolearray.Variationinthehydrogeologicalcondition inthestratawasalsoassessedduringthepre-and-post miningconditions.Theimpactofcompressionandtensiongeneratedinthestrataasaresultofextractionof coalandsubsidenceintheoverburdenrockwasobserved throughprominentresistivityvariationsobservedinan inversionmodellingoftheWStrueresistivityprofile. Theinfluenceofsurfacetopographyinthenearsurface topweatheredrockwasalsodistinctlyoutlinedbythe resistivitymeasurements.ERTisastrongtoolcapable ofprovidingvaluableinformationregardingstratadeformationcausedbymining.

INTRODUCTION

Subsidenceatthegroundsurfaceisoneoftheimpactsofundergroundcoalminingandisakeyenvironmentalconcern(Holla,2000).Extractionofcoal byundergroundminingleadstosurfacetransformationintwoforms:potholeformationandtroughsubsidence(Lokhandeetal.,2005).Thelatterleadsto depressionofthegroundsurface,resultingindisturbanceof insitu strata.Theseverityinthedisturbances

*Correspondingauthoremail:amar_cmri@yahoo.co.in

ofstrataishighundermulti-seamminingconditions. Evaluationoftheextentofstratadamageisvitalfrom theperspectiveofstabilityoftheground,seepageof surfacewaterintotheunderground,etc.Geophysical electricalresistivitytomography(ERT)isasuitable techniqueforthedeterminationofstratadisturbance andhasbeenusedfordetectionofgroundsubsidence (DobeckiandUpchurch,2006).UsingtheERTtechnique,thepossibilityofgroundsurfacecollapsecan bedetermineddependingonthetypeofsurfacesubsidence(Lietal.,2011).Theuseofresistivitymeasurementsisapplicableforlargeareasofinvestigation becausethesemeasurementsprovidecontinuousprofilesectionsoverabroadarea(Oyedeleetal.,2015). Thetrueresistivityofthesubsurfacecanbeestimated fromthesurfacewithanelectricalresistivitysurvey (Loke,2011).Thestudydescribedinthisarticlewas conductedovertheactivepanelatJamadobamine,locatedintheJhariacoalfield,India.ERTdatawereacquiredtodepictthestatusofstrataabovetheexcavated areatostudytheimpactofminingontherocks.

SITEDESCRIPTION

Thestudywascarriedoutoverthe2Spanelofthe XVseamatJamadoba2Pitmine,locatedintheeasternlimboftheJhariacoalfield(Figure1).Coalwas extractedusingtheBordandPillarmethodofmininginconjunctionwithhydraulicsandstowingwith 60percentextraction.Theaveragedepthofthepanel was166m,andtheheightofextractionwas3.4m.The XVIseamlocatedabovethepanelhadbeenminedin thepast.Thelithologyoftheoverburdencomprises sandstone,shale,shalysandstone,andcoalseams. Sandstoneandshalearethedominantrocktypesin theoverburden(Figure2).Thecoalseamslieinthe BarakarFormationofLowerGondwana.

ELECTRICALRESISTIVITYTOMOGRAPHY

Theresistivityofamaterialisdefinedastheresistance(inohms)betweenoppositefacesofaunitcube

ofthematerial.Thistechniqueiscommonlyapplied indifferentfieldsbecauseoftheadvantageofquantitativeinterpretationofsubsurfaceanomaliesbasedon resistivitymodels.

ParametersInfluencingResistivity

Dissimilaritiesintheresistivityofdifferentrock typesprimarilydependonlithology,claycontent,fluid content,porosity,andthedegreeofwatersaturation intherock.Thestructureofthebedrockhadbeen identifiedwithgeophysicaltechniquesbydifferentresearchers(Hsuetal.,2010;Chambersetal.,2012).Intactrock,fracturedrock,andgeologicallydisturbed rocksalongwiththeinfluenceofwatercontentarethe keyparametersforinterpretationofERTdata.Inthe presenceofwater,resistivityincreaseswithadecrease intheporosityoftherockformation.Accordingto Andersonetal.(2006),intensivelyfracturedrockscorrespondtoresistivitiesofbetween100and400ohm-m. Air-filledcavitiescorrespondtomuchhigherresistivityvalues(>10,000ohm-m).Therangeofresistivity ofdifferentrocktypesisshowninTable1.

Foursubsurfacematerialswereusedtointerpretthe ERTdatausingtheirtypicalresistivityvalues:moist

clay,moistsoils,highlyfracturedrocks,andair-filled cavities(Muchaidze,2008).Acavityimageappearsas alateralanomalyinahomogeneousmedium.Awelldefinedstructurewitheitherhighresistivity(i.e.,filled withair)orlowresistivity(i.e.,filledwithwater)surroundedwithalowerorhigherresistivitysuggeststhe presenceofasubsurfacecavity(Satarugsaetal.,2004).

Methodology

Pole-dipoleandWenner-Schlumberger(WS)arrays wereadoptedforinvestigationofthestratadeformationcausedbyundergroundmining.Themain strengthsofthepole-dipolemethodareitssensitivity tosubsurfaceinhomogeneitiesanditsdepthofpenetration(Ward,1990).Thisarrayisparticularlyuseful formulti-electroderesistivitymetersystemswitharelativelysmallnumberofnodesbecauseithasgoodhorizontalcoverage.Withthismethod,thetransmitterremoteelectrode(C2)isplacedfarawayfromthesurvey sothattheinstrumentdoesnotsensetheeffectofthe poleelectrode(Figure3).Theothercurrentelectrode isplacedinthevicinityoftwopotentialelectrodes.The geometricfactorofpole-dipoleisexpressedasfollows: k = 2πn (n + 1 ) x, (1)

Figure1.Locationofthestudysite.

Table1. Resistivityrangeofrocktypes(KellerandFrischknecht,1966).

SubsurfacematerialDescriptionResistivity(Ohm-m)

MoistclaysVerylowresistivityandvariesbasedonitsdegreeofsaturation, porosity,andlayerthickness <100

Moistsoilsandintensely fracturedrock Moderateresistivityandcouldbebasedonitsdegreeof saturation,porosity,andlayerthickness 100—00

RelativelyintactrockSlightlyhigherresistivityandcouldvarybasedonitsdegreeof saturation,porosity,andlayerthickness >400

Air-filledcavitiesVeryhighresistivityandcouldvarydependingontheconductivity ofsurroundingstrataanddepth,size,andshapeofvoid

Usually >10,000

Figure2.SectionofboreholeNo.J3ofJamadoba2Pit.

where k = geometricfactor, n = numberoftimes,and x = distancebetweenelectrodes.Thisgeometryreduces thedistortionofequipotentialsurfaces.Thismethodologywasadoptedfortheobjectiveofapplyingpoledipoletoevaluatethestatusofstratadeepwithinthe crosssectionofearth.

Thesignalstrengthofthepole-dipolearrayislower incomparisontothatoftheWSarrayandwasmeasuredduringpost-miningforbetterevaluationand interpretationoftheconditionofthestrata.“WS,” hybridarraysofWennerandSchlumberger,isone ofthecommonarraysusedinresistivityimaging (Samouelianetal.,2005;Loke,2010).Itissensitiveto bothhorizontalandverticalstructuresandoffersbetterhorizontalcoverageandlessdatapointlossata deeperlevel(Loke,1999).AccordingtoAlwan(2013), WSisthesuitablearrayforshallowsubsurfacedetectionofstructure.AtypicalarrayofWSisshownin Figure4,andthegeometryfactorisexpressedas k = πn (n + 1 ) x. (2)

Layout

Thegeophysicalsurveywasconductedduringtwo phasesofminingalongthesameprofile:duringtheinitialphaseofthedepillaringoperationandaftercompletionofmining.AnERTtraverse(A-A )of570-m lengthencompassing96electrodesspacedat6-mintervalswasorientedalongthelengthofthepanel(face advance),asshowninFigure1.Thisalsorunsalong thesubsidenceprofileofA-Line(Figure5).Thekey

Figure3.Arrayofpole-dipole.

Figure4.ArrayofWS.

notionwastocoverthedepthof200muptoundergroundworking.Thelengthofthe570-mprofile crossedtheundulatingsurfaceoverthepanel.

SUBSIDENCEINVESTIGATION

Methodology

Monitoringstationswerefixedonthegroundasper thedesignlayoutatregularintervalscoveringtheentireareaofinterest.Subsidencemeasurementswere carriedoutfromareferencestationorbenchmark fixedbeyondtheinfluenceofgroundmovement.Atotalstationwasusedformeasuringreducedlevel(RL) ofsubsidencemonitoringstationsandhorizontaldistancebetweentheadjacentmonitoringstationsinthe field.Thisdesignaidsincomputingsubsidence(verticaldisplacement),strain(horizontaldisplacement), andslopeofthesubsidence.TheMissingLineMeasurementmodewasadoptedforthesubsidenceinvestigationbecauseitcalculatesthehorizontaldistance, slopedistance,anddifferenceinelevationbetweentwo targetprisms,asillustratedinFigure6.

Figure6.ConceptofMissingLineMeasurementmode.

Subsidence

Thelayoutofthemonitoringstationsoverthe2S paneloftheXVseamwithoverlyinggoafatJamadoba 2PitmineisshowninFigure1.Amaximumsubsidenceof108mmwasobservedalongtheA-Line,as showninFigure7.Thestrataabovetheworkingpanel weredisturbedbecauseoftheextractionofcoalfrom theoverlyingXVIseam.Theresettlementofthefragmentedstratacontributestotheaugmentationofthe subsidencevalue.Theprofileofthesubsidenceevidentlyindicatedtheinfluenceofoverlyingoldworking.Thesurfaceprofilewasundulating,withRLvariationfrom90to100mRL.

DATAINTERPRETATION

TheERTdatawasprocessedbyRES2DINV software(GeomatrixEarthScienceLtd.,Leighton Buzzard,UnitedKingdom)togeneratethetwodimensionalresistivityimageafterremovingthebad points.Theruggedtopographyandoverburdenatthe sitecausedimpropergroundingofseveralelectrodes, resultinginunusabledatapoints.Theapparentresistivitymeasuredintheminewastransformedintotrue resistivitybytheinversionprocess.Theinversionroutinesarebasedonthesmoothness-constrainedleast squaresmethod(Sasaki,1992;LokeandBarker,1996). Themeasurementswerestackedthreetosixtimesfor eachpointalongtheprofileinordertoacquirebetter dataquality.

Pre-Mining

Thegeo-electricalsectionofprofileA-A generatedbypole-dipolearray,asperthemeasurement conductedduringthewinterseason,isshownin Figure8.Theabsoluteerrorwasfoundtobe14.2 percentaftersixiterations.Duringthisperiod,the panelwaspartlyextracted,andnosubsidencewasobservedatthesurface.Resistanceinhorizontallaminationallalongtheprofilewasobservedandwasfound

Figure5.LayoutofERTtraverseandsubsidencepillaralong A-Line.

toenhancegraduallywithdepth.Themeasurement bypole-dipoleshowedverylowresistivityimmediately belowthesurface(i.e.,inthetopweatheredrock)becauseofthepercolationofalargequantityofmoisture (winterseason),asshowninFigure8.Therewasconsistentlylowresistanceuptoanaveragedepthof40m. TheexistenceoftheoverlyingcavedpanelintheXVI seamatadepthof40mmostlikelyledtodisturbance

ofoverlyingstrata,andthemoistconditioncropped uptheconductivity.Hence,influenceofoldoverlying workingonstratacanbeinterpretedbythisresistivity imagingsystem.Theresistivityremarkablyincreased belowtheXVIseam,indicatinganintactrockcondition.Thus,theimpactofworkingintheXVseamwas notobserved,inferringthatnostratadisturbanceoccurredduringtheinitialphaseofmining.

Figure7.SurfaceandsubsidenceprofilealongA-Line.

Figure8.Two-dimensionalERTsectionalongprofileA-A bypole-dipolearrayduringinitialminingphase.

Post-Mining

Thesecondsetofmeasurementswasconductedaftercompletionofminingalongthesameprofileduringtherainyseasontolookintotheimpactofminingofthe2SpaneloftheXVseam.Themeasurement wasdonebothbypole-dipoleandWSarraystoincreasetheconfidenceininterpretation.Accordingto thepole-dipoleprofile,thetrendofresistivity,especiallyfrom0to288malongtheprofile,wasfound tovaryindepthfrominitialmeasurement,showing lessresistivity.Byandlargeitprovidedanindication ofdisturbedstrataundermoistconditions,depictedas “A”inFigure9.Asdepillaringofcoaldidnotreach belowlocation“B”(i.e.,beyond380m),theresistivity characteristicwassimilartotheinitialmeasurement. Hence,theangleofdrawcanapproximatelybeprojectedbasedontheresistivityvariationfromtheinitialmeasurement.Thesubsidencephenomenonleads todevelopmentoftensileandcompressivezonesin theoverburden.AccordingtoBrinckerhoff(2015),increasedpermeabilityandreducedpermeabilityshould

existinthetensionzoneandcompressionzone,respectively(Figure10).Thischaracteristicwasobservedin resistivityanomalies.

IrregularityinresistivityalongthelateralandverticalprofilewasprominentlyobservedintheWSarray. Variationintheresistivityinthenearsurfacelayerwas distinctduringtherainyseason.Lowresistivitywas observeduptoashallowdepthof10minthetensile zoneatthepaneledgeonbothsides,becauseunder tensionthenaturalcracksandjointsopenupandfill withwater,leadingtohigherconductivitywithrespect tothesurroundings(Figure11).Thestratabetween theXVIandXVseamswasfoundtobemoredisturbedincomparisontoshallowdepth.Thisoutcome correlateswiththedevelopmentofzonesofmovement intheoverburdencausedbysubsidence.Thecombinedheightoffracturedandcavedzonesgenerally extendsupto20to30timestheheightofextraction(Peng,1992).TheoverburdenbetweentheXVI andXVseamswasexpectedtobeunderfractured andcavedzones,likelyduetowideopenfracturesin therockmassfilledwithwater,whichledtoverylow

Figure10.Zonesofdisturbance(Brinckerhoff,2015).

Figure9.Two-dimensionalERTsectionalongprofileA-A bypole-dipolearrayaftermining.

resistivityonthedipsideofthemineworking.The sourceofwaterwasanticipatedbytheseepageofsurfacewaterbelowadrainagepathatthesurfaceof thesite.Thereappearedtobeaconnectivityoffracturedrockbelowthedrainagepathlocatedatatraverselengthof380m(Figure11).Suchacharacteristic wasnotobservedontherisesideoftheworking,indicatingdryconditions.Theresistivitywashighinthe compressionzone(betweentheXVIandXVseams;

i.e.,inthemiddleoftheextractedportion),inferring thepossibilityofair-filledcompressedfractures.

TopographicalInfluence

Thattheresistivityofthenearsurfacelayerof weatheredrockisdominatedbythetopographyofthe land(hence,itscorrelation)isvitaltothisstudy.The surfacelandwasbarrenwithundulatingtopography

Figure12.Isometricviewofthestudyarea. Environmental&EngineeringGeoscience,Vol.XXVIII,No.4,November2022,pp.361–369

Figure11.Interpretationbasedontwo-dimensionalERTbyWSarrayaftermining.

duetoanolddump,presentlybeingcoveredbygreen forest.Thethree-dimensionalviewofthestudyarea isshowninFigure12.Thelow-lyinglandeitherremainedpartlywater-filledorwetduringtherainyseason.Thischaracteristiccouldbeeasilycorrelatedand demarcatedbythedisruptionsofresistivityofnear surfacerocksmeasuredbythepole-dipolearray(Figure13).Thedrainagepathshowedlowresistivitydue topresenceofwater.At300mand380m,theabrupt enhancedresistivityatthesurfacecanbeinterpretedas solidexposedrock.Accordingtophysicalobservation, randomlylocatedoutcropsofrocksinthesurrounding areasverifiedthenatureofthenearsurfacerockheterogeneity.Anoldsettleddumpexistsbeyond450m. Thiscanbeclearlyinterpretedbythehighconductivityduringrainyreasons.

CONCLUSIONS

Thedisturbancesinrockstratacausedbydeepminingcanbeassessedbyageophysicaltechniquewith lesstimeandeffortandalsowithoutanydevelopment ofboreholes,etc.Uniformpenetrationofmoisture contactwasobservedduringwinter.Thewater-filled fracturedstrataoverthepost-miningzoneconstituted anindicationofthedisturbanceof insitu ground,as interpretedbyformationofanomalouslylowresistivityoverthepanel.Theextentofdeformationinrock masscanalsobebroadlyprojected.Theconductivity variationwasduetothepresenceofwaterormoisture.

Thedampnessofgroundatthelow-profiletopographyshowedverylowresistivity.Theimpactofsurface waterduringrainyseasoncanalsobeprominently observedandclearlydemarcatedbasedonresistivity disruptions.Seepageofwaterinthestratahelpedin evaluatingtheheightofthefracturedzonecausedby thedepillaringoperation.Thus,ERTcanbeavaluabletoolforthestudyofstratadeformationcausedby miningoperations.

ACKNOWLEDGMENTS

WeacknowledgethesupportandfacilityuseprovidedbytheminemanagementofTataSteel,which aidedinfieldinvestigationsandgenerationofdata. TheauthorsthanktheDirectoroftheCSIR–Central InstituteofMiningandFuelResearch,Dhanbad,for permittingthepublishingofthisarticle.Theviewsexpressedinthisarticlearethoseoftheauthorsandnot necessarilyoftheorganizationtheyrepresent.

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InvestigationofPhysicochemicalChangesofSoftClay aroundDeepGeopolymerColumns

MAJIDBAGHERINIA* NE¸SEI¸SIK

DepartmentofCivilEngineering,UniversityofAtaturk,Erzurum25240,Turkey

KeyTerms: DeepMixing,Geopolymer,SoftClays, Full-ScaleTests,GroundImprovement

ABSTRACT

Geopolymersshowgoodpromiseforsoftclaystabilization.Thispaperaimedtoimprovesoftclaywith geopolymerandevaluatetheeffectsofgeopolymerstabilizedcolumnsonthemechanicalandchemicalbehaviorofthesurroundingclay.Rangesoftestswere conductedonbothstabilizedandunstabilizedspecimenstodeterminetheimpactsofgeopolymeronthe claystructure.Theresultsshowedthatincreasingthe bindercontentandcuringtimesignificantlyincreased theunconfinedcompressivestrengthofstabilizedsamples.Microstructureandmineralogyanalysesrevealed thathardenedmaterialswereformedwithinthegeopolymermatrixfromtheamorphousclayphases.Inaddition,theformationoftheeffectiveareaaroundthe geopolymer-stabilizedcolumnsresultedinthewater contentofsoftclaydecreasingwhiletheundrainedshear strength,pH,andelectricconductivityvaluesincreased. Furthermore,thebearingcapacityofsoftclaydramaticallyincreased(30-fold)duetoanincreaseincolumn area.

INTRODUCTION

Softsoilsareamajorconcerningeotechnicalengineeringbecauseoftheirlowshearstrengthand largedeformationunderlightloads(Cristeloetal., 2013;Yaghoubietal.,2020).Inground-improvement projects,thedeepmixing(DM)methodisanalternativetotheusualground-improvementtechniquesin softground,suchasstonecolumnsandsandcompactionpiles.InDM,bindersinadryorwetform areinjectedintothegroundwithahollowaugerand mixedbytherotationofcuttingtools.Asaresult,the groundparticlesareultimatelyblended,andstabilized columnarelementsareformed(BruceandBruce,2003; KitazumeandTerashi,2013).Thestabilizedareahas

*Correspondingauthoremail:majid.bagherinia13@ogr.atauni.edu.tr

highstrengthandstiffness,lowpermeability,andlow settlement(KitazumeandTerashi,2013;Jamsawanga etal.,2017).Thismethodissuitableforproviding anappropriatebearingcapacityforlighttomedium loadsandissuperiortoothermethods,botheconomicallyandpractically(Bruceetal.,2013;Kitazumeand Terashi,2013).

Limeandcementarecommonlyusedastraditional bindersinDM,andtheystabilizeweaksoilswitha bindercontentofupto30percentbyweightrelative tothesoil(Rogersetal.,2000;Shenetal.,2003a; Horpibulsuketal.,2011;PakbazandAlipour,2012; andBruceetal.,2013).Thesebinders,especiallyPortlandcement(PC),haveanegativeimpactontheatmosphereandcauseseriousenvironmentalproblemsdue totheemissionofcarbondioxide(CO2 )duringcombustionandchemicalcalcination(Zhangetal.,2013; Duetal.,2016;andYaghoubietal.,2018).Inaddition,thedurabilityofcementisunacceptable,resultinginexcessivecostandtimerequiredforre-fixation. Duetothesechallenges,researchintonewmaterialsisessential.Therefore,thisstudyaimedtoinvestigateanalternativematerialtoPCforuseintheDM application.

Geopolymersareinorganicmaterialsthathave recentlyreceivedspecialattentionfromresearchers.In additiontothemechanicalperformanceofgeopolymers,comparedtotraditionalbinders,theirenvironmentaladvantagesmakethemanattractivealternative (Yaghoubietal.,2019).Previousstudieshavereported thatgeopolymersareanalternativetoPCduetotheir preferablecompressiveandflexuralstrength,higher ductility,lowershrinkage,andsuperiordurability (suchasfireandacidresistance)(Gaoetal.,2013; Zhangetal.,2013;Phoo-Ngernkhametal.,2015, 2016;Duetal.,2016,2017;NathandSarker,2017; andRiosetal.,2017).

Ageopolymerisatypeofinorganicmaterialthat appearsasananalogofthermosetorganiccrosslinkingagents(Sukmaketal.,2013b).Geopolymerization(alkalineactivation)occurswhenaluminosilicateandalkalinematerialsreactwitheach other.Duringthereaction,silicaandaluminaunits blendinconjunctionandconnecttheoxygenions; thisisknownasthepolycondensationreaction

(Davidovits,1991;Gaoetal.,2013;andPourakbar etal.,2016).Davidovits(2013)concludedthatkaolinite(withahighcontentofsilicaandalumina)ispolymerizedbyalkalistoformahard,concrete-likematerial.Intheliterature,differenttypesofwastematerials (e.g.,flyash,blastfurnaceslag,andvolcanicash)have beenactivatedwithvariousalkalies(e.g.,sodiumoxide,sodiumhydroxide,sodiumsilicate,potassiumhydroxide,andcalciumhydroxide)toimprovesoftclay soils(Cristeloetal.,2013;Sargentetal.,2013;and Miaoetal.,2017).Theresultsindicatethatthecompressivestrengthofthestabilizedsoftclayincreased significantly,whiletheswellingpotentialandplasticityindexdecreased.Otherresearchersindicatedthat soiltype,bindertypeandratio,andmixingproperties areimportantfactorsaffectingtheperformanceofstabilizedsoils(Huseienetal.,2016;OliviaandNikraz, 2012;Pacheco-Torgaletal.,2008;Phoo-Ngernkham etal.,2015,2016;NathandSarker,2017;andWu etal.,2019).Geopolymerscanbeusedingeotechnicalapplicationssuchassoilstabilizationingroundimprovement(Phetchuayetal.,2016;Pourakbaretal., 2016;Singhietal.,2016;Duetal.,2017;andYaghoubi etal.,2018)andDMprojects(Arulrajahetal.,2018; Mohammadiniaetal.,2019).

AftertheinstallationofDMcolumns,themechanicalandchemicalpropertiesofthesurroundingsoft clayareaffectedbyionmigration.Manystudieshave alreadyreportedthemigrationofionsfromlimeor lime-cementcolumnsintosoftclay,andtheireffects ontheadjacentgroundhavebeeninvestigated.Nevertheless,knowledgeofionmigrationrelatedtothe behaviorofgeopolymericcompoundsandtheireffect onsoilproperties,suchasundrainedshearstrength, bearingcapacity,settlement,etc.,islimited.Inarecentstudy,BagheriniaandZaimo ˘ glu(2021)installed DMcolumnswithpotassiumhydroxideasabinder andfoundthatthepropertiesofsoftclayimproveddue toionmigration.

Thispaperpresentsanexperimentalstudyonthe stabilizationofsoftclaywithgeopolymers.Rangesof testswereconductedonbothstabilizedandunstabilizedspecimenstoevaluatetheeffectsofbindercontent,curingtime,andconditionduringthegeopolymerizationprocess,includingunconfinedcompressive strength(UCS),X-raydiffractionpattern(XRD),and scanningelectronmicroscopy(SEM)analyses.The mainobjectivewastoincreasethebearingcapacityof softclayandreducesettlementbyinstallinggeopolymerDMcolumns.Todeterminetheeffectivearea aroundthecolumnsduetoionmigrationandthe distanceofthisareafromthecolumn,experiments wereperformedtodeterminepH,electricconductivity(EC),watercontent,andundrainedshearstrength (St)inthesurroundingclay.

Table1. Indexpropertiesofclay.

PropertyClay

Claycontent, <0.002mm(%)17 Finercontent, <0.075mm(%)80 Specificgravity,Gs2.65 Liquidlimit,LL(%)44 Plasticlimit,PL(%)26 Plasticityindex,PI(%)18 Optimumwatercontent(%)16 Maximumdryunitweight, γdmax (kN/m3 )18.5 Hydraulicconductivity, k (cm/s)6.980 × 10 7

MATERIALSANDMETHOD

Materials

Claysoilwascollectedfromthefield(asitein Kır¸sehir,Turkey),fromabout3.5mbelowtheground surface,anddriedinanovenat105°Cfor1day;it wasthenpulverizedandpassedthrougha1mmsieve. Thesoiltypeselectedforthestudywasalluvialsoil, whichisclassifiedaslow-plasticityclayaccordingto theUnifiedSoilClassificationSystem(USCS).DifferentpropertiesofclayareshowninTable1.The XRDandX-rayfluorescence(XRF)patternsofthe clayillustratedthepresenceofkaolinite(46.65percent),quartz(27.14percent),aluminumoxidesilicate (5.24percent),nacrite(7.6percent),andalunite(4.39 percent)ascommonmineralsinthissoil.Theremainingminerals(8.98percent)wereamorphousinnature.Thesoilalsocontainedalumina(Al2 O3 = 26percent)andsilica(SiO2 = 69percent),whichconveyed geopolymericpropertiesontheclay(Gaoetal.,2013; Pourakbar,2016).

Sodiumhydroxide(NaOH)intheformofbeads (purity:97percent)wasobtainedfromlocalsuppliersinTurkey.WhiteNaOHbeads,withapHof12, wereusedintheexperimentsasanalkalineadditive thatissolubleinwater,ethanol,andmethanol.Other characteristicsofNaOHareshowninTable2.NaOH solutionwithhighermolaritiesisdangeroustoworkersbecauseofitscorrosivenature(Phoo-Ngernkham etal.,2015;Phetchuayetal.,2016;andSubektietal.,

Table3. Summaryofexperimentalprogram.

Materials(%)

SampleNameClayat44%WaterContentNaOHTotalCuringTime(days)NumberofSamples

Stage1:Unconfinedcompressionstrengthtest(38mm × 76mm)

S1100—1007,14,28,56,11215 S29911007,14,28,56,11215 S39731007,14,28,56,11215 S49551007,14,28,56,11215

S59371007,14,28,56,11215

S6*9191007,14,28,56,11215

S789111007,14,28,56,11215

Total = 105

Stage2:Small-scalemodeltest(watercontent,pH,EC,andSt)

SC1100—1007,14,28,56,1125 SC29911007,14,28,56,1125 SC39731007,14,28,56,1125 SC49551007,14,28,56,1125

SC59371007,14,28,56,1125 SC69191007,14,28,56,1125

Total = 30

Stage3:Large-scalemodeltest(load-bearingcapacity)

LS919100561,3,and7columns

*S6isthesampleusedforXRDandSEManalysesat28,56,and112days.

2017).Therefore,itwasusedindryformintheexperimentstoreduceitsharmfuleffects.

SamplePreparationandTesting

Thelaboratorytestingprogramwasplannedinthree stages:(1)UCStest,(2)small-scaletest,and(3)largescaletest(Table3).Anoptimumbindercontentof20 to25percent(Horpibulsuketal.,2011;Bushraand Robinson,2013)upto30percent(Bruceetal.,2013; KitazumeandTerashi,2013)hasbeensuggestedfor thestabilizationofclayeysoilsusingtheDMmethod. Intheexperiments,theNaOHcontentwasselectedas 1,3,5,7,9,and11percent(bymassofsoil),whichis verylowcomparedtotheliteraturevalues.

Previousstudies(LorenzoandBergado,2004;Horpibulsuketal.,2011;Cristeloetal.,2013;Phetchuay etal.,2016;andArulrajahetal.,2018)indicatedthat theoptimumwatercontentfortheimprovementof clayeysoilswithhighwatercontentis1.0liquidlimit (LL)ofthesoil.Thesamevaluewaschosenforthis study.Thenaturalwatercontentandliquidlimitof the insitu claywas38to51percentand44percent, respectively.

FortheUCStest,thedriedclayandwaterwere placedinamechanicalstirrerandmixedforapproximately5minutes.Themixturewaspouredintoaplasticbagandkeptfor1daytobehomogenized.Then, theNaOHbeadswereaddedtothemixture,andthe mixingprocesswasrepeatedat150rpm.Themixture

wascollectedfromthemechanicalstirrer,andthree layerswerepouredintoacylindricalmetalmoldwith alengthof76mmandadiameterof38mm.Theinnersurfacesofthemoldswerelubricatedwithathin layer(Greaseoil)tofacilitatetheextrusionofthetest specimens.Theedgeofthemoldwaslightlytapped byhandtoreduceairbubbles.Thepreparedspecimenswerekeptinacuringroomat20 ± 3°Cambienttemperatureand90 ± 5percenthumidityfor 7,14,28,56,and112days.Alkali-stabilizedsamplesneedtobecuredatahightemperature(butbelow100°C)tocompletethegeopolymerizationprocess(Davidovits,2017).Sincecuringathightemperaturesisnotpossibleinthefield,acuringtemperature suitableforfieldconditionswaschosen.Therefore,the ambienttemperaturewasselectedtodetecttheformationofthegeopolymericproductsintheclaystructure.ThepreparationofthespecimensandthecuringconditionswereperformedaccordingtoJapanese GeotechnicalSociety(2000),EuroSoilStab(2002), andArasanetal.(2017).Attheendofthecuringperiod,theUCStestwasconductedonthespecimensaccordingtoASTMD2166/D2166M(2016)(Figure1). Thetestingloadwasappliedatarateof1.0mm/min. ForeachNaOHratioandcuringtime,threespecimens wereprepared,andtheUCSvaluesweredetermined byaveragingthreemeasurements.

FollowingtheUCStest,sampleS6wasevaluated usingXRDandSEManalysestoassesssoftclay stabilization.TheXRDpatternswererecordedwith

Figure1.Unconfinedcompressivestrengthtestafter(a)7,(b)14,(c)28,(d)56,and(e)112days.

anEMPYREANdiffractometerandanalyzedwith thePANalyticalmeasurementprogram.Themeasurementswereconductedontreatedanduntreatedclay soilat λ = 1.54060ÅwavelengthfromtheCu-Ku source,atascanningrangeof5° to75°,ascanning speedof2degrees/min,andascreeningstepof0.0260 degrees(BagheriniaandZaimo ˘ glu,2021).

TheSEMimagesweretakenofthesamplestoevaluatetheinteractionsbetweenNaOHandclayminerals. Thesampleinthepowderedformwasputonthesampleplatewithacarbonbandadheredandcoatedwith gold(5nminthickness),andvacuumtreatmentwas carriedoutfor3minutes.Finally,itwasplacedinthe sampleholderandanalyzedusingaZeissSigma300 (BagheriniaandZaimo ˘ glu,2021).

InstallationofDMColumns(Small-ScaleTest)

Atthisstage,theend-bearinggeopolymerDM columnswereinstalledintotheclaytoinvestigatethe effectsofionmigrationonthemechanicalandchemicalpropertiesofthesurroundingsoftclay.

Aclaymixturewithoptimummoisturecontent(and LL = 44percent)waspreparedinthesameway asthatdonefortheUCStest.Acylindricalmold madeofpolyvinylchloride(PVC),withaheightof 110mmandadiameterof100mm,wasusedtoprepareclaybeds.Theclaymixturewasfilledintothe moldandcompactedintothreelayersusingawooden tamper(MalarvizhiandIlamparuthi,2004;¸Sengör, 2011;Demiretal.,2013;andMalekpoorandPoorebrahim,2014).Then,thecolumnswereinstalledusing adrymixmethodforDM(Figure2).Thedrymix methodreferstothestateofthebinderasitisdistributedinthemixerandthesoilasadrypowder.The

NaOHpowderwascastintothesoftclayasfollows, toinstallcolumnswith30mmdiameterand110mm height.

Atubewithaninnerdiameterof30mmwasverticallypushedintothesoftclay.Anothertubewith aninnerdiameterof10mmwasthenplacedinside arodwithanouterdiameterof30mm,andtherod waspluggedatoneend.Thesmallertubeandtherod werethenplacedwithinthelargertubeanddrivenverticallydowntothedesireddepth.Therod,pluggedat theend,wasthenremoved.Thesmallertube(inner diameterof10mm)wasfilledwithapre-determined amountofNaOH.Afterawhile,the10mmtubewas pulledout,andtheNaOHremainedintheclay.A mixingtoolwithashaft-tippedblade,25mmindiameter,wasrotatedandinsertedthroughthesoftclay, downtotheintendeddepthandwithdrawnatarateof 2m/minandrotationalvelocityof320rpm(Larsson etal.,2009;BagheriniaandZaimo ˘ glu,2021).Themix-

Figure2.Imagesofinstallationofsmall-scalegeopolymerDMcolumn:(a)planviewand(b)cross-sectionview.

Figure3.SchematicviewofinstallationofDMcolumninsoftclay.

ingprocesswasrepeatedintriplicateforeverycolumn. Finally,the30-mm-diametertubewaspulledout.A schematicviewoftheinstallationoftheDMcolumn isdisplayedinFigure3.ThePVCmoldsweresealed withaplasticcovertopreventthelossoftheclay’s watercontent.Thesampleswerekeptinthecuring roomat20 ± 3°Cambienttemperatureand90 ± 5percenthumidityfor7,14,28,56,and112days. Attheendofthecuringtimes,watercontent,pH, EC,andSttestswereconductedat5,10,15,20,and 25mmdistancesfromthecolumnedgeand20mm depthfromthesurface,accordingtothefollowing experiments.

Watercontenttest:Thesamplesweretakenfrom thespecifiedintervalsanddepthsusingaverythin metalruler,andthetestswereconductedaccording toASTMD2216(2019).

pHandECtest:Thesamplingprocedurewasperformedasinthewatercontenttest.Subsequently, air-driedsoilpassingthroughano.10sievewas collectedandplacedinaglasscontainer,followed bydistilledwater,andthemixturewasstirredevery10minutesfor1hour.Then,thepHandECof themixturewerereadbyapHandECmeter,respectively.Theratioofdistilledwaterwas1:1and 1:2.5forthepHandECtests,respectively.ThepH andECtestswereperformedaccordingtoASTM D4972(2019)andRaymentandHigginson(1992), respectively.

Sttest:TheSttestwasperformedaroundthe columnsaccordingtoISO/TS17892-6:(CSNEN ISO17892-6,2004)todeterminethestrengthdevelopmentofthesoftclay.Thistestmeasuresthe conepenetrationdepth,whichiscorrelatedwiththe

undrainedshearstrength.TheStvalueswereevaluatedaccordingtoEq.1(Hansbo,1957).

St = Cg m i 2 . (1)

Stisundrainedshearstrength(kPa), C isaconstant determinedbytheanglebetweenthegroundandthe cone(C = 0.8at30°C), g istheaccelerationdueto gravity(9.81cm/s2 ), m isthemassofthecone(g),and i istheconepenetrationdistance(mm).

InstallationofDMColumns(Large-ScaleTest)

Alarge-scalemodeltestwasperformedtoinvestigatetheload-settlementbehavioroftheDMcolumns inthesoftclayandsimulatetheirbehaviorinpractice. Moreover,asinglecolumnwasproducedtoexamine loadcapacityduringsettlementinthesoftclay,and theresultwascomparedtotheclaybedcontaining nocolumn(untreatedsoil).Tomeasuretheeffectof columngroupsontheload-settlementbehaviorofthe softclay,twodifferentareareplacementratios(triple columns,as = 0.0748,andsevencolumns,as = 0.1745) wereusedinthisstudy.

Intheexperiment,acylindricalmetaltank(1,000 mmindiameter,400mminheight,and20mmin thickness)wasusedtoinstalltheend-bearingcolumns (30mmindiameterand200mminheight).Accordingly,theclaybedandcolumnswerepreparedasdescribedinthesmall-scalemodeltestusinga300-mmlongauger(Fig.4a).Thetankwasthensealedwitha plasticcoverfor56daysat20 ± 3°Ctocontrolhumidity(90 ± 5percent).Itshouldbenotedthatthehighest compressivestrengthvalueobtainedintheUCStest waswith9percentNaOH,sothisamountwasused

Figure4.Large-scalemodeltest:(a)preparationofclaybedandinstallationofgeopolymerDMcolumns,(b)attachmentLVDTs,and(c) testingcolumns.

inthecolumninstallation,andthespacingbetween columnsinthecolumngroupswaschosenbasedon themosteffectiveareafromthesmall-scaletestresults (distancecolumnperiphery = 25mm).

Attheendofthecuringperiod,thecolumnswere subjectedtoverticalloadingataconstantstrainrateof 1.0mm/minusingaloadingframe.Theverticalload wasappliedtothecolumnsviaarigidcircularplate withadiameterof80mmand190mmforthesingle andcolumngroups,respectively.Allplateshadathicknessof20mm.AnLVDT(linearvariabledifferential transformer)wasattachedtomeasurethesettlement oftheplateduringloading(Figure4bandc).

RESULTSANDDISCUSSION

UCSTestResults

TheeffectsoftheNaOHratioandcuringtimeon theUCSofthesamplesarepresentedbelow.The UCSresultsofthestabilizedspecimenswerecompared

withuntreatedspecimensandotherstudiesfromthe literature.

Figure5showstherelationshipbetweentheNaOH ratioandtheUCSvalueatdifferentcuringages.Generally,thestrengthofalltreatedspecimensincreased withtheincreaseofNaOHratiofrom1percent

Figure5.RelationshipbetweentheUCS-NaOHratioandcuring timeoftreatedanduntreatedsoftclay.

to9percent.Between1percentand3percent,there wasanegligibleincreaseinUCSvalues,indicatingthatthelowbindercontentdidnotsufficiently completegeopolymerizationinthesoil.TheUCS valuesincreasedsteadilyat7percentandthenincreaseddramaticallywhentheNaOHcontentreached 9percent.Previousstudieshavealsoreporteda significantstrengthimprovementformixturespreparedwithNaOH(NematollahiandSanjayan,2014; Phoo-Ngernkhametal.,2015;andYaghoubietal., 2018).Moreover,NaOHhasanoticeablepotential forstrengthdevelopmentinthesoftclaycomparedto KOH(BagheriniaandZaimo ˘ glu,2021).Thisimplies apossibledifferenceinionicdiameterbetweensodium andpotassium.

BasedonFigure5,theUCSvaluesdramaticallydecreasedwhenmorethan9percentNaOHwasadded tothesoil.Thiscouldhavebeenduetotheexcessive NaOHcontent,which,whenitpenetratestheclaylayers,separatestheminsteadofstickingtogether.Similarresultswerenotedbyotherauthorswhoshowed thatthecompressivestrengthofthespecimensdecreasedwhenthebindercontentwasabove10percent (Consolietal.,2009;Sabetetal.,2013;andValipour etal.,2014).

Inaddition,increasingthecuringperiodhadnomajoreffectontheUCSvaluesofsamplesS2(1percent), S3(3percent),andS4(5percent).TheUCSvalues ofsampleS5(7percent)showedagradualincrease after14daysbutremainunchangeduntil112days. Otherwise,thecuringagesweremoreeffectiveforS6 (9percent).Here,UCSvaluessuddenlyincreasedafter 7days,andadramaticincreasewasobservedupto112 days,indicatingthecriticalroleoftheNaOHratioin geopolymerizationatearlystagesandthereafter.The highestUCSvaluewasreachedusing9percentNaOH after56curingdays.TheUCSvaluesofthespecimens atthisratioforthecuringperiodsof7,14,28,56,and 112dayswere923,1,421,2,345,3,120,and3,115kPa, respectively.ThehighestUCSvalue(9percentNaOH and3,120kPa)ofthetreatedsamplewas680percent higherthanthatoftheuntreatedspecimens(0percent NaOHand400kPa)forthesamecuringtime.Nevertheless,thelowestUCSvalueobtainedfromthe9 percentNaOHresultswashigherthanthelowerUCS limitforcohesivesoil(200kPa)fortheDMmethod (Bruceetal.,1998;BruceandBruce,2003).ThisresultindicatesthatNaOHisanacceptablebinderinthe DMapplication.

Thecuringstateofthespecimensstabilizedwithalkalinematerialsiscrucialingeopolymerization;low temperaturesleadtolowstrength,whilehightemperaturesleadtohighstrength(Abdeldjouadetal.,2019). Theresultsdemonstratedthatsoftclaywithhighaluminaandsilicacontentscanbegeopolymerizedat

Figure6.XRDanalysisof(a)untreatedclay,(b)clay + 9percent NaOHafter28days,(c)clay + 9percentNaOHafter56days,and (d)clay + 9percentNaOHafter112days.

roomtemperature(20 ± 3°C),andthestrengthvalues ofthestabilizedsamplesareacceptable,accordingto theliterature.

ItisworthmentioningthattheUCSvaluesofthe samplespreparedwith7percentand9percentNaOH slightlydecreasein112dayscomparedtothatat56 days.Thiswasprobablyrelatedtothetimerequiredfor theformationofthenucleationphase.Thesameresult waspreviouslyobservedforsoilstabilizationwithlime (Cristeloetal.,2009)andalkalinematerials(Cristelo etal.,2013).

XRDResults

TheXRDanalysisfocusedonthespecimensthatexhibitedthehighestcompressivestrengthfromtheUCS test.TheeffectofthecuringperiodontheXRDof thetreatedspecimenswasinvestigated,andtheresults werecomparedwiththoseoftheuntreatedclay.

Figure6displaystheXRDresultsoftheuntreated clayandthestabilizedspecimensofS6after28,56, and112days.Theuntreatedclaywascomposedof amorphoustosignificantlycrystallinematerials.The peakcrystallinephaseswerereducedbetween28and 56daysbytheadditionof9percentNaOHandremainedunchangeduntil112days.Thereductionin XRDpeaksaftersoftclaytreatmentshouldincrease thestrengthofthesamples(Villaetal.,2010;Cristelo etal.,2013;andPhoo-Ngernkhametal.,2015).After28days,newamorphousphaseswerefound,some ofwhichoverlappedwiththemainpeaks.Theseobservationssuggestthatcompoundssuchassodium aluminosilicatehydrate(NASH),sodiumhydrogen aluminosilicate,andhydrogensodiumaluminosilicate formedbythereactionofNaOHandclayminerals (silicaandalumina)inthepresenceofwater.Onthe otherhand,anadditionalsemi-crystallinepeakofhydrosodalite(θ = 14°)andNASH(θ = 32.5°)increased after28and56days,respectively.Thealumina-silicate

inthekaolinitemineralreactswithNaOHtoformhydrosodalite(Marshetal.,2018).Hydrosodalitecauses somegeopolymerization,whichleadstoanincreasein strength(Somnaetal.,2011;Phoo-Ngernkhametal., 2015),andsotheformationofNASHgelsinthesystemmayhaveenhancedthestrengthofthesamples (Ismailetal.,2014;Phoo-Ngernkhametal.,2015;and Phetchuayetal.,2016).

SEMResults

SEMimagesprovideusefulinformationformonitoringstructuralchangesinclayasaresultofchemical reactions.Figure7showstheSEMmicrographsofuntreatedclay,NaOH,andS6after28,56,and112days ofcuring.TheSEMofclayillustratesaporoustexturewithwidelyspacedplatesandlooseandscattered layers(Figure7aandb).NaOHhasanangularand filledstructure.TheparticlesizeofNaOHisgenerally smallerthanthatofclay(Figure7candd).InFigure7eandf,softclaystabilizedwith9percentNaOH showsgeopolymerizationandbondingbetweenlayersafter28days,withstrengthincreasingwithtime (from400kPato2,345kPa);however,somemicroporesarestillpresentbetweenclaylayers.Atthisage, tinyparticlesoflessthan0.1 μmaredetectedinthe compactedmass(Figure7f),indicatinggeopolymerizedparticles(Sukmaketal.,2013a;Miaoetal.,2017). Figure7gandhshowsthatthegeopolymerizedcompoundsadheretomostclayparticlesafter56daysand, subsequently,causesignificantagglomerationinthe soilstructure,enhancingthestrengthbydecreasingthe microporevolume(3,120kPa).TheformationofhydrosodaliteandNASHgelswithintheclaystructure significantlyincreasedthestrengthofsoftclayover time(Somnaetal.,2011;Ismailetal.,2014;PhooNgernkhametal.,2015;andPhetchuayetal.,2016). ThiscanbeattributedtoanincreaseintheSi/Alratio inthesystem.Similarconclusionsweredrawninpreviousstudies,whenNaOHwasusedasanalkalitopreparethegeopolymericproducts,andthemechanical improvementwasobserved via microstructureanalysis (Wangetal.,2005;Komljenovi ´ cetal.,2010;Cristelo etal.,2013;Singhietal.,2016;andYaghoubietal., 2018).Inaddition,theSEManalysisresultsdisplayed thegeopolymerizationofsoftclayatroomtemperature,whichwasalsosupportedbytheXRDandUCS testresults.

Small-ScaleTestResults

Todeterminethemigrationofgeopolymersintothe surroundingsoftclay,testswereperformedforwatercontent(percent),pH,electricalconductivity(EC), andundrainedshearstrength(St)fromthedistance

columnperiphery(DCP).Thenegligibleresultofthe DMcolumnpreparationwith1percentNaOHisnot includedinthetestresults.AfterDCP = 25mm(0.83d, d = columndiameter),thevaluesoftheaforementionedtestsdroppeddrastically(similartothesoftclay values)andwere,therefore,excludedfromtheresults.

WaterContentTestResults

Figure8displaystheresultsofthechangesin watercontentaroundthegeopolymer-stabilizedDM columnsatdifferentpointsofDCPandcuringage. Foralladditiveratios,thewatercontentofsoftclay decreasednearthecolumnandincreasedfarfromthe columnedge(athighDCP).Thisdemonstratesthatinteractionbetweenthegeopolymercolumnandtheclay particlesismoreeffectivenearthecolumnthanfarther away.Inotherwords,ionmigrationishighnearthe column.

Furthermore,thewatercontent,especiallynearthe columns,decreasedslightlywithincreasingNaOHratio,andthiscanbeattributedtothemigrationofthe hydroxylgroups(BagheriniaandZaimo ˘ glu,2021)and sodiumions.Thesereductionswereevenmorepronouncedwithincreasingagingtime(upto56days) andthenreachedaplateauwithin112days.Asimilar trendwasobservedfortheimprovementofsoftclay soilswithlimecolumns(Tonozetal.,2003).Theminimumwatercontent(42.7percent)wasobtainedfor SC6in56days,whichwas3.0percentlowerthanthe initialvalue(untreatedclay = 44percent).

pHTestResults

ThepHtestwasperformedonthesoftclayaround thegeopolymerDMcolumnstodeterminethechanges inthealkalinityofthesoil,whichisanimportantfactorinstabilizingclaysoils.AsshowninFigure9,the pHsimultaneouslyincreasednearthecolumnwhen theNaOHratioincreased,anditdecreasedwithdistancefromthecolumn.ItisexpectedthatthepHof thesoilnearthecolumnswillbehighduetotheintenseiontransfer;hydroxylionscanmigratewithinthe clayandcausehighlyalkalineconditions(Diamond andKinter,1966;BagheriniaandZaimo ˘ glu,2021).In theclay-watersystem,ahighalkalinestatusindicatesa highpH,whichleadstoeffectivegroundstabilization (Vural,2012;Ghobadietal.,2014;andBagheriniaand Zaimo ˘ glu,2021).Accordingly,thehighestpHvalueillustratesstiffandfirmground,whilethelowestvalue describesweakandlooseground.Accordingtotheresultsandliteraturereview,theincreasedpHofsoft claynearthecolumnindicatesimprovedclayproperties(Shenetal.,2003a,2003b,2008;Tonozetal.,2003; Larssonetal.,2009).

Figure8.WatercontentvaluesaroundthegeopolymerDMcolumns.

Moreover,thepHvaluesshowedanupwardtrend withgreateragingtime.ForallNaOHratios,soilpH increasedfrom7to56daysandremainedconstantuntil112days.ThemaximumpHof8.78wasreachedat DCP = 5mm,9percentNaOH(SC6),andacuring periodof56days.Thisvalueis35percenthigherthan thatforrawclay(6.5).

ElectricConductivityTestResults

Theelectricalconductivityoftheclay-watersystem dependsonthetypeandnumberofionsinthemixture.Whenionsontheclaysurfacearedissolvedinto thesolution,theconductivityofthecationunderthe electricfieldandthemovementofthecolloidalparticlesincreasetheconductivityofthesolution.

Figure10displaystherelationshipbetweentheelectricalconductivityoftheclaysoilandthedistance fromtheedgeofthecolumnatdifferentcuringtimes. TheECvaluesofthesurroundingsoftclayincreased withtheincreaseoftheNaOHcontentinthegeopolymerDMcolumns(from3percentto9percent)and thecuringtime.Ontheotherhand,similartothewatercontentandpHtests,theECofthesurrounding clayincreasedsteadily,peakingwithin56days(atall

NaOHratios)andthenremainingconstantordecreasingupto112days.TheincreaseoftheECwasmore efficientnearthecolumns,particularlyat7percent and9percentNaOH,indicatingmigrationofNa+ and OH ionsintothesurroundingsoftclayandincreased colloidalparticleandionconcentrationactivity.The maximumECvalueof1.78mS/cmwasreachedat DCP = 5mm,9percentNaOH,and56daysofcuring,whichisabout88percenthigherthantheoriginal value(untreatedclay = 0.943mS/cm).Itshouldbe notedthattheECvaluedidnotincreaseafter56days. Thesetrendscouldbeduetodecreasediontransfer fromthegeopolymerDMcolumnstothesurrounding softclay,probablyleadingtoNaOHconsumption.As reportedearlier(SalimiandGhorbani,2020),theEC valueofthegeopolymer-stabilizedsamplesdecreased withagingafter56days,whichcouldbeduetolower ionconcentrationandadditiveconsumption.

UndrainedShearStrengthTestResults

Theundrainedshearstrength(St)testwasperformedaroundthecolumnstomeasurethemechanicalimprovementofthesoftclayandtoinvestigatethe effectsofthegeopolymerDMcolumnsontheshear

strengthofthesoil.Theeffectsofcuringtimesand NaOHratiosonthestrengthdevelopmentofthesoft claywereinvestigatedatdifferentDCPs.Theresultsof SttestsareshowninFigure11.

Figure11showsthatthestrengthoftheclaysoilincreasedwithanincreaseinNaOHratiofrom3to9 percent.Duetothehigherionconcentrations,theincreasesweregreaterneartheperipheryofthecolumns thanatgreaterdistancesfromtheedgeofthecolumns.

Atrendsimilartothatdescribedabovewasalsoobservedduringthelongagingprocess.TheStvaluesincreasedwithincreasingcuringtime(7to56days)for allNaOHratiosandthenremainedunchangeduntil112days.Theeffectofcuringtimewasmorepronouncedfor9percentNaOHandclosedistancesfrom thecolumn.Aswiththetestsforwatercontent,pH, andEC,theStofthesurroundingsoftclayremained unchangedafter56days.Asdescribedintheprevious section,suchtrendscouldbeduetodecreasedionmigrationthatresultsinNaOHconsumption.

ThemaximumStvalueof5.68kPawasreached forSC6atDCP = 5mmand56daysofcuring, whichisabouteighttimeshigherthanthevaluefor theuntreatedclay(0.63kPa).AccordingtoBagherinia andZaimo ˘ glu(2021),theundrainedshearstrengthof

softclaycanbeimprovednearDMcolumnsprepared withalkalinematerials.TheyreportedthattheDM columnscontainaneffectiveareaortransitionzone duetothemigrationofpotassiumandhydroxylions, andthatthestabilizationofthesoiloccursduetothe reactionbetweentheclayparticlesandthemigrating ions.Ghobadietal.(2014)reportedthattheundrained shearstrengthoflime-stabilizedspecimensincreased withincreasingpH.Theyindicatedthatalkalinityis afactoraffectingthestabilizationofclaysoils.Other studiesfocusedonionmigrationanditseffectsonthe undrainedshearstrengthofsoftclayaroundlimeor cementcolumns(Shenetal.,2003a,2003b,2008;Larssonetal.,2009).

Large-ScaleTestResults

Figure12showstheload-settlementbehaviorof theclaybed,asinglecolumn,andthree-andsevencolumngroupsofend-bearingcolumnsafter56days. Asshown,thebearingcapacityoftheclaybed withnocolumnincreasedfrom0.05to0.20kNaftertheinstallationofthesinglecolumn.Inother words,thegeopolymerDMcolumnnoticeablyimprovedthebearingcapacityofthesoftclay.Theeffec-

Figure9.ThepHvaluesofsoftclayaroundthegeopolymerDMcolumns.

tivearea(transitionzone)increasedwhenthenumber ofcolumnswasincreased,whichfurtherimprovedthe bearingcapacityofthesoftclay.Thebearingcapacity ofthreeandsevencolumnswas0.6and1.7kN,respectively.

Theultimatebearingcapacityof1,3,and7endbearingcolumnswasapproximately275percent,1,018 percentand2,990percenthigherthantheultimate bearingcapacityoftheclaybedwithnocolumns,respectively.ThesevaluessuggestthattheDMcolumns weresuccessfullyinstalledintothesoftclayandsignificantlyimprovedthemechanicalpropertiesofthesurroundingsoftclaybyincreasingthearearatio(numberofcolumns).Nevertheless,theresultsofthisstudy couldbemorebeneficialthanotherstudiesondeep mixedorstonecolumnsintheliterature(Malarvizhi andIlamparuthi,2004;Alietal.,2010;Malekpoorand Poorebrahim,2014).

CONCLUSIONS

Inthisstudy,seriesofunconfinedcompressivetests andsmall-andlarge-scalemodeltestswereconducted

toinvestigatetheeffectsofgeopolymerDMcolumns onthemechanicalstrengthandchemicalchangesof thesurroundingsoftclay.Thefollowingconclusions andrecommendationscanbedrawnfromthetest results.

ThemaximumUCSvalueobtainedinthisstudywas approximately56percentgreaterthantheaccepted limitvalue(i.e.,2,000kPa)fordeepmixedclaysoils withcementreportedintheliterature.

Claysoilsthatarerichinsilicaandaluminacanbe geopolymerizedwithNaOHbeadsatroomtemperature,whichwasconfirmedbytheXRDandSEM analyses.

Thetransitionzone(DCP = 25mm)formedaround thegeopolymerDMcolumnsduetothemigration ofions.

Thepropertiesofthesoftclaycanvaryinthetransitionzone.Whiletheundrainedshearstrength,pH, andECofthesoftclayincreased,thewatercontent decreased.Thetransitionofionsdependedonthe ratioofadditive,curingtime,anddistancefromthe edgeofthecolumn.

Figure10.TheECvaluesaroundthegeopolymerDMcolumns.

Figure11.TheStvaluesaroundthegeopolymerDMcolumns.

Theend-bearinggeopolymerDMcolumnincreased theload-bearingcapacityofthesoftclay,andincreasingthenumberofcolumnsincreasedtheloadbearingcapacityofthesoftclay.

Theload-bearingcapacityofthesoftclayafterinstallingsevengroupsofend-bearingcolumnswas approximately30timeshigherthanthatofsoftclay withoutanycolumns.

Consideringtheresultsofthisstudyandtheliteraturereview,NaOHcanberecommendedasanew binderforstabilizingsoftclaysoilsusingthedeepmixingmethod.Fieldstudiesareneededtoconfirmthe resultsofthisstudy.

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Environmental&EngineeringGeoscience,Vol.XXVIII,No.4,November2022,pp.371–386

WaterQualityMonitoringofFiveKarstSpringswithina PasturelandinSouthwestPolkCounty,Missouri

RAMONAGÓMEZ MÉLIDAGUTIÉRREZ*

DepartmentofGeography,Geology,andPlanning,MissouriStateUniversity, SpringfieldMO65897

KeyTerms: Nitrate,Chloride,KarstSpring,Water QualityMonitoring,Ozarks

ABSTRACT

Thefracturednatureofkarstterrainmakestheseareashighlysusceptibletocontamination.Besidesaquifer contamination,impairedkarstspringscannegatively impacttheaquatichabitatoftheirreceivingstreams. FivespringsofashallowkarstaquiferinsouthwestPolk County,Missouri,andtheirreceivingstreamwereselectedtoconstructabaselineofwaterqualitydata,usingnitrate(NO3 )asindicator.Themainlanduseinthe studyareaiscattlefarming.Watersampleswerecollectedduringa12-monthperiodandanalyzedforpH, turbidity,Ca,Mg,HCO3 ,Cl,SO4 ,andNO3 .Results showthateachspringhaditsownrangeofvalues.NO3 andClvalueswerebelowcontaminationlevelsandonly inafewinstancesexceededthresholdlevelsreportedfor karstareas(NO3 -N <3mg/L;Cl <13mg/L),implying thatthenumberofcattleperacreismaintainedatasustainablelevelandleakingfromtheSpringfieldPlateau aquifertotheunderlyingOzarkaquiferposesaminor threat.Interestingly,NO3 andCldidnotcorrelatedespitetheircommonsource,suggestingthattheyundergo differentchemicalandmicrobiologicalprocessesalong theirpath.TheyearlynitrateexportfromtheLittleSac Riverwasestimatedas286.8Mg,andthemaximumN loadwasobservedinMarch.Monitoringofspringsand streamsisrecommendedforthisenvironmentallyfragile area.

INTRODUCTION

Karstterrainsformafterdissolutionofbedrock, primarilylimestoneanddolostone.Asdissolutionenlargesthefractures,theresultantsecondaryporosity allowstherocktoholdgroundwater,formingakarst aquifer(Kresic,2013;Maasetal.,2019;andMedici andWest,2021).Karstaquifersareimportantsources ofdrinkingwater,supplyingwatertoabout10%of

*Correspondingauthoremail:mgutierrez@missouristate.edu

theworld’spopulation(Stevanovic,2019).Otherkarst featuresincludesprings,caves,dolines,andsinkholes (GoldscheiderandDrew,2014).

Thefracturednatureofkarstproducesconduits ofpreferentialflow,restrictingbothfiltrationofcontaminantsandadsorptiontosolidsurfaces(Allshorn etal.,2007;TagneandDowling,2020;andVisser etal.,2021).Unconfinedkarstaquifersarethuseasilyimpactedbyactivitiesthattakeplaceonthesurface(Kresic,2013;Knierimetal.,2015).However,the waterflowandthechemicalandbiologicalprocesses occurringwithinakarstsystemarecomplex,aswaterflowsfasterthroughtheseconduitsofpreferential flowandslowerthroughthelesspermeablerockmatrix,creatingzoneswithvariousdegreesofbiological activity(Husicetal.,2020;Visseretal.,2021).

Nitrogenasnitrate(NO3 -N)isacommonindicator ofagriculturalcontaminationbecauseofitsstableand solublenatureandforbeingassociatedwithmineral fertilizers,manure,andseptictankeffluents(Kresic, 2013;Medicietal.,2021;andVisseretal.2021).NO3 Nhasgainednotorietyrecentlyasaleadingcauseof theGulfofMexico’shypoxiczone(Schillingetal., 2019;TagneandDowling,2020).Therefore,NO3 contributionfromagriculturallandscapesrequiresmonitoringoflevels,startingatasmallwatershedlevel (TagneandDowling,2020),inordertodevelopstrategiestomitigatenutrientexportatalargerscale.

IntheUnitedStates,karstisprominentinmany states,includingFlorida,NewYork,andmidwestern statesfromTexastoMichigan(Venietal.,2001;Katz, 2020).Pannoetal.(2006)usedNO3 -Nconcentrations from232karstspringsinIllinoisanddetermined athresholdconcentrationforkarstspringstobe 2.5mg/LNO3 -N.Thethresholdvalueforpresent-day precipitationisreportedtobe0.7mg/LNO3 -N(NationalAtmosphericDepositionProgram,2022)for thestudyarea.Otherstudiesreportingnitrateinkarst springsintheU.S.MidwestincludeMaasetal.(2019) innorthwesternIllinois,TagneandDowling(2020)in theOhioRiverbasin,Schillingetal.(2019)inIowa, andFordetal.(2019)inKentucky.IntheOzarks, waterqualityofkarstspringshasbeenreportedby Adamski(2000),Mugel(2002),Petersonetal.(2002),

Figure1.LocationofPolkCountywithintheOzarkPlateausProvinceandofthesamplinglocations.TheSpringfieldPlateauconsistsof exposedlimestoneandtheSalemPlateauofexposeddolomite(modifiedfromAdamski,1997).

andOwenandPavlowsky(2011).Waterqualityisalso reportedbytheU.S.GeologicalSurvey(USGS)NationalWaterInformationSystem(https://waterdata. usgs.gov/mo/nwis/qw)andtheMissouriDepartment ofNaturalResourcesintheMissouriCleanWater InformationSystems.WefocusedourstudytoapasturelandareainsouthwestPolkCounty,Missouri, locatedontheedgeofthelimestoneplatformknown astheSpringfieldPlateau(Figure1).

Themajorthreattoshallowwaterqualityisthat fromongoingagriculture,animaloperations,andurbanization(Mugel,2002;Gillmanetal.,2008;Katz, 2020;andTagneandDowling,2020).TheSpringfield PlateauaquiferseparatesfromtheunderlyingOzark aquiferbyarelativelythin(asthinas6m)(Mugel, 2002)andfracturedconfininglayer.Whilethereare numerousstudiesfocusingonwaterqualityofsurface waterandthedeeperOzarkaquifer,studiesfocusing onwaterqualityoftheSpringfieldPlateauaquiferare lessabundant.

StudyObjectives

ThewaterqualityoftheSpringfieldPlateauaquifer isrelevantfortwomajorreasons.Oneisthecontaminationthreattothedeeperaquiferasaresultfrom

severalfaultsandtheotheranegativeimpactthatcontaminatedspringdischargemayhaveontheaquatic habitatsofthereceivingstreamsand,inthecaseofnitrate,hypoxiazonesasthewaterreachestheocean.A waterqualitybaselineofthisaquiferisthereforekey totheprotectionofwaterresourcesoftheregion.The objectivesofthisstudywerethefollowing:

CompilewaterqualitydataoffivekarstspringsdischargingintotheLittleSacRiverinsouthwestern PolkCountyMissouri.

Determinethetemporalvariationinwaterquality foreachofthefivestudiedspringsbasedonseason andprecipitationevents.

Identifythespringsandtheconditionsleading tocontaminatedgroundwaterbasedonnitrate content.

RESEARCHMETHODS

StudyArea

ThestudyareaislocatedinsouthwesternPolk Countyandlayswithinthephysiographicprovinceof theOzarkPlateau(Adamski,1997;Haysetal.,2016) (Figure1).Thestudiedspringsclusterinaruralarea

Figure2.StratigraphiccolumnofPolkCounty,Missouri.(Source: MSDISMissouriImagery.)

approximately25kmnorthofSpringfield,Missouri, attheedgeoftheSpringfieldPlateau,wherelimestone bedrockiscoveredbyathinlayerofsoil,thereforereferredtoasmantledkarst.Themaineconomicactivityiscattlefarming,astheabundantprecipitationof theOzarksisconducivetothegrowthofgrasses.Nbasedfertilizerisappliedtopasturelandatarateof 150kg/ha(2–4poundsper1,000ft2 ),commonlyduringthespringofeachyear(Maasetal.,2019).

TheSpringfieldPlateauaquiferiswithinathin(10–20m)layerofhighlyfracturedlimestone(chertyin someplaces)ofMississippianage,whosesurfacecoincideswiththeSpringfieldPlateauphysiographicregionshowninFigure1.TheOzarkconfiningunitseparatestheshallowSpringfieldPlateauaquiferfromthe underlyingOzarkaquifer(Figure2).TheOzarkconfiningunit,composedoflayersofshaleandmudstone, variesinthicknessinthestudyareafrom20to26m, whereastheOzarkaquiferiswithinathick(300–600m)layeroffractureddolostonesandlimestones (Figure2).TheoverlyingMississippianlimestoneand confininglayerareabsentintheSalemPlateau,exposingolder(Ordovician)dolomites.

Thesurfacehydrologyofthestudyareaisshownin Figure3.Springswithinthiswatershedareadrainwaterintosmallspring-fedstreamsandthen,withinafew kilometers,intotheLittleSacRiver.Formanagement

purposes,theLittleSacRiverwatershedisdividedinto upperandlowerwatersheds.TheupperLittleSacwatershedistheprimarysourceofthepublicdrinking waterforthecityofSpringfield,andthereforeitswaterqualityhasbeencloselymonitored,mainlywithrespecttobacteria(Escherichiacoli)loading(Watershed CommitteeoftheOzarks,2010).Oursamplesarelocatedattheboundarybetweenupperandlowerwatersheds,withthreesamplingsitesintheupperandthree inthelowerLittleSacRiverwatershed(Figure3).

Theclimateistemperatehumid,witha106-cmaverageannualprecipitationscatteredthroughouttheyear, slightlymoreintenseinthespringandwinter.Sincethe SpringfieldPlateauaquiferisthinandunconfinedand morelikelytobecontaminated(Adamski,1997),most wellsintheareatapintothedeeperOzarkaquifer (Popeetal.,2009).

Inkarstspringselsewhere,precipitationhasbeenreportedtofirstflushsolutesfromthesoilfollowedby adecreaseinconcentrationasaconsequenceofdilution(Huebschetal.,2014;Schillingetal.,2019;Tobinetal.,2021;andVisseretal.,2021).Thiseffect requiresacontinuousmeasurementprobe(Huebsch etal.,2014).Becauseofthediscontinuoussamplingof ourstudy,moreelevatednitrateconcentrationscould haveeasilybeenoverseen;however,thisprocessmay explainahighconcentrationobservedafterarain eventthatfollowsarelativelylongdryperiod.

LandUse

With56,600cows,PolkCountyhasthesecondlargestnumberofcattleinMissouri(U.S.DepartmentofAgriculture,2020).Manuregeneratedbycattle andpoultrycontainsnutrients(N,P),coliformbacteria,andvariouschemicals(e.g.,antibiotics,pesticides)thatposeathreattolocalkarstaquifersand downstreamwaterways(Adamski,1997;Tagneand Dowling,2020).Confinedanimalfeedingoperations (CAFOs)arelargeanimaloperationsthatkeepfrom 300to >7,000animals(hogs,cattle,andpoultry)confinedinpens.AlthoughtherearenoCAFOswithin thestudyareaandonlyoneinPolkCounty,CAFOs areabundantinotherpartsofMissouri,increasing thelikelihoodofamorewidespreadpresenceinthe OzarkPlateausinthefuture(Mugel,2002;Tagneand Dowling,2020).

SamplingandAnalyses

WeselectedfivespringswithintheSpringfield PlateauinPolkCountybasedontheirlocationand accessibilityandcollectedsamplesduring11months in2021andonein2022.ExceptforLeithSpring,all springsweresmall,andtheirwaterqualityotherthan

pH,temperature,andTDSisseldomreported.The samplinglocationsareshowninFigures1and3and listedinTable1.

Watersampleswerecollectedinclean1-Lplastic containersandkeptcoolduringtransporttothelaboratory,whereturbidity,pH,andalkalinityweremeasuredonarrival.Theremainderofthesamplewasfilteredandkeptrefrigeratedat4°Cforfurtheranalyses, whichwerecompletedwithin3daysofsamplecollection.Thechemicalparametersweredeterminedusing standardmethodology(Clescerietal.,1998).TurbiditywasanalyzedusinganHfScientificDRT-15CEturbiditymeter.Totalalkalinity,chloride,calcium,and magnesiumweredeterminedtitrimetrically,sulfateby thenephelometricmethod,andtotalnitratecolori-

metricallyusingaHachDR3900spectrophotometer asnitrite + nitrate,towhichnitritewassubtracted (mostvalueswerebelowdetectionlimit)andreported asNO3 -N.Ammoniawasprobedusingacommercial kittodetermineifproperdeterminationswerenecessary,butallsamplescamebelowdetectionlimits.Na andKaremostlyreportedasminorcationsandare notdirectlyrelatedtothisstudy;therefore,theywere measuredforthreesamplespersiteandtheirmedian valueusedforpercenterrorbalance(%EB).

Allchemicaldeterminationsfollowedstandard guidelinesforqualitycontrol,whichincludeddaily calibrationofreagentsandinstrumentsandreplicates andblanksevery10thsample.Thepercenterrorofthe electricbalanceforthesampleswasbelow5%formost

Figure3.HydrologyofthestudyareaandlocationofsamplingsiteswithintheLittleSacRiverwatershed(modifiedfromWatershedCommitteeoftheOzarks,2010).

Figure4.Piperdiagramofthewaterfromthefivestudiedsprings andtheLittleSacRiver.

samplesAfewsampleshadEBupto7.5%,whichwe consideredacceptableandkeptinthedatabase.

PearsoncorrelationanalysesusingMicrosoftExcel wereappliedtothedatatodetermineanyassociationamongchemicalparametersthatcouldbeassociatedtoacommonsource.Forexample,bothCl andNO3 arepresentinanimalwastesandseptictank effluents.Correlationcoefficients(r)largerthan0.6 wereconsideredstrong,andtheirsignificancewasdeterminedusingatwo-tailed t-distributionalsousing Excel.

RESULTS

Table2liststhevaluesobtainedforselectedchemicalparametersandFigure4thePiperdiagram.The PiperdiagramshowsallspringsbutEudoraSpring plottingclosetogether.ThewaterisaCa-Mg-HCO3 watertypeforallspringsexceptforEudoraSpring, whichhasaCa-Mg-HCO3 -SO4 watertype.

TheresultsinTable2showmodestvariationsof waterchemistrywithinanyonespringcomparedtoa moreevidentvariationamongsprings.Turbiditywas higherforallspringsontwooccasions,March12and July16,bothtimesbecauseofanintenseprecipitation event.Onthesedates,thevaluesofHCO3 andCain springnos.2and3andEudoraSpringdecreased,suggestingdilution,buttheseeffectswerelessnoticeable inspringno.4andLeithSpring.NO3 -Ndidnotfollowthispatternofdilution.

NaandKconcentrationsweredeterminedfora smallernumberofsamples.Theresultsareshown inTable3.Errorbalancecalculationswere <10.0% forallsamplesexceptfortwosamplesofEudora Spring(10.26%and10.29%EB),whichwerekeptin thedatabaseanddidnotaffectthecorrelationre-

sults,asEudoraSpringsampleswereexcludedfrom thecorrelationcalculationsduetoitsdifferentwater type.

Becauseoftheirdifferentwatertypes,correlation datawereseparatedintotwogroups,onecombining springnos.2,3,4,and6andoneforEudoraSpring. ExceptforthecorrelationbetweenCaandalkalinity (r = 0.63, p < 0.01),waterqualityparametersdidnot correlateinthegroupofcombinedspringnos.2,3,4, and6.CorrelationcoefficientsforEudoraSpringwere notstatisticallysignificant.

DISCUSSION

Amongthesprings,therewasalargevariationin waterchemistryinspiteofbeingallwithina20-km lineardistance,likelytheresultofeachspringhaving aparticularflowpathandchemicaltransformations throughsoilandepikarst.Thespringsmorelikelyto becontaminatedwithanimalwasteorseptictanks wereidentifiedasthosesurpassingthethresholdvaluesof2.5mg/LNO3 -Nand13mg/LCl(Pannoetal., 2006).

Springno.2showedthelargestNO3 concentration, 3.3mg/LNO3 -N,andsurpassedtheNO3 -Nbackgroundvaluein44%ofthesamples.Springno.2was alsotheonlyspringtocompletelydryduringdryspells ofAugust–September2021andremaineddryforseveralmonths.Springno.4surpassedthekarstNO3 -N thresholdlevelsonce(7%ofthesamples).Visualappraisaloftheflowsofspringnos.2and4rankedthem asthesmallestofallsprings,andthislackofdilutionis probablyacontributingfactoroftheirhigherNO3 -N highcontent.

Chlorideconcentrationssurpassedbackgroundvaluesin7%ofthesamplesinspringno.3and47%ofthe samplesinspringno.4.Thehigh(>13mg/LCl)valuesoccurredconcurrentwithlowNO3 -Nvalues;however,thisinverserelationwasweak(r = 0.10)andnot statisticallysignificant.

EudoraSpring(no.5)showedadistinctlydifferent waterchemistrythantheotherfoursprings,withlow chlorideandnitratecontentandalargesulfatecontent.ThelocationofEudoraSpringcoincideswith aPennsylvanianstreamchannelexposure,achannel carvedintotheMississippianlimestonethatiscomprisedofsandstonesandshales.Thedifferentlithology explainsitsdistinctwaterquality.

ThelackofcorrelationbetweenNO3 andotherpossiblyrelated(anthropogenic)parameters,suchasCl andSO4 (bothareindicatorsof,e.g.,contamination fromsepticsystems)observedinallsprings,suggests thatnitrogentransformationsaretakingplaceseparatelyandmoreintenselyforNcompoundsthanthose ofClorSO4 .Theseprocessesoccurintheoverlying

Table2. SelectedwaterqualityparametersoftheLittleSacRiver(no.1),threeunnamedsprings(nos.2–4),EudoraSpring(no.5),andLeith Spring(no.6).

Sample No. Date, 2021–2022pH Turbidity (NTU)HCO3 (mg/L)Ca(mg/L)Mg(mg/L)NO3 (mg/L)Cl(mg/L)SO4 (mg/L) 1Feb.57.963.0114.769.69.71.6813.59.2 Feb.267.9914.0109.8NDND1.0016.07.0 Mar.127.9322.9107.462.41.20.8521.312.0 Mar.197.9122.1100.469.210.21.3613.56.1 Apr.28.176.4117.169.68.71.077.17.2 Apr.308.028.3100.060.07.80.7217.09.6 May148.197.6119.669.66.81.119.27.6 Jun.118.286.5119.673.66.30.7611.37.7 Jul.168.0417.685.455.217.00.7728.47.0 Aug.288.019.2112.263.214,10.5026.611.8 Sep.268.054.1112.263.89.70.1722.113.0 Oct.318.022.2129.376.310.71.736.712.2 Nov.308.031.0124.464.012.20.8624.813.4 Dec.308.071.1107.467.212.60.1625.115.3 Jan.318.011.3131.864.012.20.5027.715.6 2Feb.57.472.4167.187.28.33.025.34.0 Feb.267.963.3163.587.29.73.327.66.1 Mar.127.5842.1114.777.60.51.906.76.1 Mar.197.280.8134.275.28.32.7211.45.1 Apr.27.360.4131.886.41.52.551.14.3 Apr.307.360.3131.885.66.32.4312.44.0 May147.440.7131.881.65.42.400.75.4 Jun.117.340.3126.984.03.92.013.54.0 Jul.167.191.4117.274.47.82.236.44.3 ———Dry————

3Feb.57.612.2128.171.26.30.995.317.6 Feb.267.642.2109.870.47.30.607.417.0 Mar.127.5520.659.853.60.50.816.416.4 Mar.197.685.373.248.81.51.057.810.2 Apr.27.691.6126.981.69.70.805.316.2 Apr.307.612.1129.380.08.80.5820.219.6 May147.801.5136.680.06.80.7710.015.2 Jun.117.342.1102.548.816.50.1311.711.2 Jul.167.1913.678.136.811.20.116.87.0 Aug.287.574.7134.259.221.40.0512.49.1 Sep.267.562.6131.857.622.30.014.610.4 Oct.317.390.8144.076.86.83.116.75.2 Nov.307.731.4153.788.812.20.2712.124.8 Dec.307.830.9153.087.212.60.2311.323.0 Jan.317.880.8153.788.012.20.2610.623.6 4Feb.57.573.3104.964.06.32.158.53.8 Feb.267.484.1104.961.67.82.079.96.9 Mar.127.459.3109.873.61.01.9418.86.3 Mar.197.413.278.056.00.51.934.63.0 Apr.27.371.5102.568.05.82.213.94.4 Apr.307.381.5102.567.24.41.6014.54.9 May147.581.6100.461.63.91.726.45.2 Jun.117.331.4100.067.26.81.9811.75.1 Jul.167.186.290.357.64.41.6810.93.6 Aug.287.3810.9117.176.09.71.7015.64.8 Sep.267.322.2120.076.08.81.669.65.0 Oct.317.272.1124.479.22.41.7015.27.1 Nov.307.421.4129.380.09.21.7719.17.6 Dec.307.511.3119.680.010.21.8519.07.0 Jan.317.891.2119.679.09.01.8418.96.5 5Feb.56.423.139.035.611.10.06 <0.0252.0 Feb.266.452.536.632.010.20.05 <0.0252.5 Mar.126.3121.531.739.22.90.140.0740.0 Mar.196.5516.028.728.03.90.13 <0.0226.8

Table2. Continued.

Sample No. Date, 2021–2022pH Turbidity (NTU)HCO3 (mg/L)Ca(mg/L)Mg(mg/L)NO3 (mg/L)Cl(mg/L)SO4 (mg/L) Apr.26.635.936.639.23.90.041.0660.4 Apr.306.185.830.528.811.7 <0.013.5056.0 May146.568.524.430.48.3 <0.01 <0.0256.8 Jun.116.140.534.233.69.7 <0.011.162.8 Jul.165.9831.314.614.43.40.161.820.8 Aug.286.223.436.639.211.20.0611.357.6 Sep.266.2319.934.232.88.8 <0.019.657.6 Oct.316.1211.439.035.27.3 <0.012.166.0 Nov.306.1018.731.728.810.7 <0.01 <0.0262.8 Dec.306.3013.229.328.013.6 <0.011.157.6 Jan.316.463.431.728.213.0 <0.01 <0.0259.2 6Feb.58.191.3125.169.47.31.4810.67.2 Feb.268.101.1129.378.48.81.075.39.1 Mar.128.067.7109.880.27.80.8912.18.8 Mar.198.064.4112.276.02.41.063.23.6 Apr.28.190.7141.583.26.81.262.08.2 Apr.308.181.1139.189.68.70.6110.37.5 May148.361.4148.890.43.90.972.86.1 Jun.118.041.1112.271.26.31.225.35.5 Jul.168.024.2126.984.06.80.645.75.2 Aug.288.040.4122.071.23.91.3513.15.5 Sep.268.080.2109.872.011.70.467.46.1 Oct.317.880.4153.760.010.70.5012.79.6 Nov.307.910.1141.572.014.60.758.49.6 Dec.308.060.6141.588.012.60.547.411.2 Jan.3180.10.3136.684.013.00.748.211.6

ND = notdetermined;— = dry.

soilandepikarstzoneandincludenitrification,denitrification,plantuptake,andseveralsoilandwatermicrobiologicalprocesses(Visseretal.,2021).

Figure5showsNO3 -Nconcentrationvariationsfor eachspringandtheirrelationshiptoprecipitation(cumulativeprecipitationof3dayspriortosamplingdate) andthedischargeoftheLittleSacRiveronthedayof sampling).Duringthesamplingperiod,thedischarge oftheLittleSacRivervariedbetween0.3and140m3/ s (historicalminimaandmaximaare0.06and782m3 /s, respectively),meaningthatbothrainyanddryweather

wererepresented.NO3 -Nvaluesvariedoverarelativesmallrangeofvaluesandhadaquickresponseto precipitationeventsasdescribedbyMugel(2002)and Huebschetal.(2014),respectively.

SpringswithaquickerresponseofNO3 -Ntoaprecipitationeventwerenos.2and3,EudoraSpring,and theLittleSacRiver,whereasLeithSpringandspring no.4showedadelayedresponse.Apossibleexplanationforthedelayresponseisalongerflowpath, smallerwaterconduits,orboth.AngelandPeterson (2015)usedNO3 -NandClasparametersofconcern

LittleSacRiverSpringNo.2SpringNo.3SpringNo.4EudoraSpringLeithSpring

Environmental&EngineeringGeoscience,Vol.XXVIII,No.4,November2022,pp.387–396

Figure5.NitrateconcentrationforeachofthefivespringsandtheLittleSacRiver.Barsrepresentriverdischarge,inm3 /s,and3-day cumulativeprecipitation(mm).

andfoundminimallyimpactedkarstspringsinKentucky,withvaluesupto1.5mg/LNO3 -N,whereas Schillingetal.(2019)reportedvaluesupto22mg/L NO3 -NforspringsinIowa.Precipitationseemedto impactturbidity;however,thisvisualeffectonceusingturbiditymeasurementsproducedanonsignificant correlationwithprecipitation.

Sincechlorideisaconservativeelementandacontaminantpresumedtosharethesamesourceoforigin asNO3 ,agraphshowingClvariationsforeachspring wasconstructedandisshowninFigure6.

Thedailyexportofnitratefromthisrelativelysmall (614km2 )watershedwasestimatedas0.786Mg/d (286.75Mg/yr)basedonthemedianvalueofthe15

consecutivenitrateloadsoftheLittleSacRiverat theUSGS06918740LittleSacRivernearMorrisville, showninTable4.

Althoughthevaluesforpotentialcontaminantsnitrateandchloridearerelativelylowinthefivestudied springs,thefactsthatsomewereabovebackground levelsandthatmostofthemrespondedtoprecipitationeventswereconsideredsignsofconcernwithrespecttotheamountofNO3 potentiallydischarged intothestream.Theresultsprovidebackgroundvalues thatcouldbeusefultofuturestudies,suchastopredictimpactduetopotentialchangesineitherweather patterns(e.g.,globalclimatechange)orlanduse(e.g., landdevelopmentandCAFOs).

Figure6.ChlorideconcentrationsforeachoffivespringsandtheLittleSacRiver.Barsrepresentriverdischarge,inm3 /s,and3-daycumulative precipitation(mm).

Table4. NitrateloadattheU.S.GeologicalSurvey06918740Little SacRiverneartheMorrisville,Missouri,location.

Date, 2021–2022 NO3 (mg/L) Discharge (m3 /s) NO3 -Nload (Mg/d) Feb.51.688.471.229 Feb.261.685.520.802 Mar.120.8514.301.054 Mar.191.3645.595.357 Apr.21.078.100.749 Apr.300.7212.630.786 May141.1114.361.377 Jun.110.767.620.500 Jul.160.7725.801.716 Aug.280.500.510.022 Sep.260.170.370.005 Oct.311.737.221.079 Nov.300.861.420.105 Dec.300.161.440.020 Jan.310.501.340.058

CONCLUSIONS

Water–rockinteractionandprecipitationwere,in thisorder,thecontrollingfactorsofwaterquality offivekarstspringsoutflowingfromtheSpringfield PlateauinPolkCounty,Missouri.Thechemistrywas uniqueforeachspringandmostlybelowthresholdconcentrationsreportedforotherkarstsprings (2.5mg/LNO3 -Nand13mg/LCl),whichindicates thatthenumberofcattleinthepasturelandiskeptat asustainablelevelandtheirwasteisnotsignificantly impactingthewaterqualityoftheSpringfieldPlateau aquifer.Springnos.2and4hadNO3 -Nvaluesabove karstthresholdlevelsin44%and7%ofthesamples, respectively.Bothofthesespringscorrespondedtothe smallestflows,andthisisprobablyacontributingfactorfortheirhigherNO3 -Ncontent.Inallcases,NO3 Ndidnotcorrelatewithotherpotentialhuman-related parameters,eitherClorSO4 ,suggestingthateachof thesecompoundsundergoesdifferenttransformations alongtheirflowpath.

Cattlefarmingisthemaineconomicactivityofthe studyareaandcouldexpandinfollowingyearsif farmerswererequiredtoincreasetheirproduction.A waterqualitydatabasefortheunconfinedSpringfield aquiferiskeyforcomparisonpurposesifchangesin landuse(e.g.,CAFOandurbanization)andmoreintenseweatherpatternsweretooccur.Specifically,the databasewouldhelppredicttheextentandperiodicityofcontaminationandtheeffectofrainevents oncontaminantlevels.TheNexportfromthewatershedisimportantforwaterbodiesdownstream andthusfortheconservationofwaterresources.The presentexportofNbythiswatershedwasestimated as287Mgofnitrogenperyear.Monitoringnutrientsatsmall-scalewatershedsisimportanttoidentify

thespringsandtheconditionsthatfavortheirrelease. Thedatacanthenbeusedtodevisewaystoprotecttheaquiferfromcontaminationandtomitigate Nexport.

ACKNOWLEDGMENTS

WearegratefultotheMissouriLouisStokesAlliancesforMinorityParticipationProgramforpartialfundingofthisstudyandtotheNationalScience Foundation1828069CHEgrantAcquisitionofan Inductively-CoupledPlasmaMassSpectrometerSystemawardedtoMissouriStateUniversity.

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AssociationbetweenCOVID-19andHeavyMetal PollutioninIraqiCitiesDeterminedfromHierarchical Prediction

ARAMMOHAMMEDRAHEEM*

DepartmentofCivilEngineering,UniversityofKirkuk,Al-SayadaStreet,Kirkuk, Iraq,36001

KeyTerms: COVID-19,ConfirmedCases,Heavy Metal,Contamination,DistinctiveIraqiCities,StandardLimits,HierarchicalPredictionApproach

ABSTRACT

Thisstudyassessestherelationshipbetweencoronavirus(COVID-19)andthespreadofvariousheavy metalcontaminantsacrossIraq.Thestudycollectsall confirmed,recovered,anddeathcasesoftheCOVID19virusatitsonsetinIraquntilMay2,2020,comparingIraqwiththetopthreeinfectedcountriesinthe world(theUnitedStatesSpain,andItaly).Inaddition,numerousheavymetalcontaminationindifferent Iraqicitieshavebeensummarizedandassociatedwith theallowableupperandlowerworldwidestandardlimits.Furthermore,thestudyintroducesahierarchicalpredictiveapproachfortherelationshipbetweenconfirmed infectedcasesanddeathsduetotheCOVID-19virus andheavymetalcontaminationinvariousIraqicities.It isconcludedthatallthestudiedIraqicitieshaveheavy metalcontaminationfordifferentchemicalelementsexceedingtheallowablestandardlimits.Extremecontentsofcopper,nickel,lead,andzincareconcentrated inAl-Qadisiyah,Al-Sulaimaniyah,Erbil,andBaghdad withlimitsof160 µg/g,240.9 µg/g,378 µg/g,and 1,080 µg/g,respectively.Basedonthehierarchicalpredictionapproach,alinearpositiverelationshipbetween bothconfirmedcasesanddeathsduetoCOVID-19with differentheavymetalcontaminationwasobtainedwith amaximumcoefficientofdetermination(R2 )of0.97.

INTRODUCTION

Coronavirus(COVID-19)startedinWuhan,Hubei Province,China,andeventuallyreachedtheentire world(Malayetal.,2020a;Tosepuetal.,2020).CoronavirusesarepartoftheCoronaviridaegroupand aresingle-strandedenvelopedviruseswitharibonucleicacid(RNA)genomeofapproximately26–32kb

*Correspondingauthoremail:engaram@yahoo.com, aram_raheem@uokirkuk.edu.iq

involume(Clementetal.,2020).COVID-19couldbe aresultofevolvingorre-evolvingdiseases,defecatinganimalsorhumans,orboth(El-SayedandKamel, 2020;Malayetal.,2020b).OnMay2,2020,Iraqi officialshadreported2,153confirmedcasesofthe COVID-19virussincethebeginningofthepandemic. InIraq,thetopthreecitieswithconfirmedaccumulativecasesofCOVID-19wereBaghdad,Al-Najaf,and Al-Basrah,citieswith384,303,and281cases,respectively.NormalindicationsfortheCOVID-19virusincludesignsofseverebreathingcomplaints,includinga hightemperatureaccompaniedbycoughing.Theperiodofsicknessrangesfrom5to14days,wheresevere casescreatecriticalbreathingdifficulties,pneumonia, kidneybreakdown,anddeath.Preliminaryclinicalindicationshaveshownthatmanycasesincludefever, whileafewcasesincludebreathingproblemswithmassivepneumoniainfiltrationinbothlungs(Holshue etal.,2020;LorikaandStefan,2020;andPerlman, 2020).ThemedicalsignsofsuchharshanddangerousCOVID-19diseasearereasonablysimilartoMiddleEastrespiratorysyndromeandsevereacuterespiratorysyndrome(Wangetal.,2020a).Earlierstudies showedthatseveralfactors,suchasa2-week-longcriticalwindspeedbeforethespreadoftheCOVID-19 virusanddailytemperature,havestronginfluences onpopulations(Bashiretal.,2020;¸Sahin,2020).In addition,anautoregressiveintegratedmovingaveragemodelhasbeenusedtopredictthefuturetime evolutionofCOVID-19casesindifferentcountries (Ceylan,2020).InIraq,nostudieshavetriedtoinvestigatetheenvironmentalissuesandtheirassociation withthespreadofCOVID-19.

Toxicheavymetalsandradionuclidepollutionhave beenamajorhealthandpoliticalproblem(Guoetal., 2016).Inrecentyears,theproblemsofenvironmentalpollutioninIraqhaveincreased,especiallyheavy metalpollution(Al-Janabietal.,2019).Suchmetals havebeenreleasedintotheecosystemathighratesand areseverecontaminantsbecauseoftheirtoxicity,firmness,andbioaccumulativeharm(Saharetal.,2020). Massivemetalconcentrationsarehazardousandmay persistinthesystemforalongtime,despitethefact

thatmostoftheseheavymetalsarephysicalelements oftheearth’sshell(Volpeetal.,2020).However,heavy metalsinvolvedinrockweatheringaredissolvedinwater(Mokhtaretal.,2015;Khanetal.,2020a,2021a, 2021b,2021c;andLuoetal.,2020).

Thecontaminationcausedbyheavymetalsin bothagriculturalandurbansoilsorwaterarises fromsourcessuchasmanufacturing,mining,paints, pesticides,batteries,automobiles,anddomesticand industrialsludge(TawfiqandGhazi,2017;Umaetal., 2020;andWangetal.,2020b).Itwasshownthatusing asedimentationtankmethodcouldremoveheavy metalsby70%;however,thesemethodsbuildupheavy metalsintraps,ponds,andtanks,generatingatoxic wasteproductthatisdifficulttoeliminate(Cairns etal.,2020).Soilscancontainheavymetalseither fromnaturalgeologicalsourcesorfromhuman-made sources,suchasfertilizers,industrialwaste,deposits, andirrigation(Liuetal.,2020).Sourcessuchasenergy production,humananthropogenicactions,removalof wastes,manufacturingreleases,andvehicledischarges wouldaccumulatedepositsofheavymetalsonany urbansurface.Naturalsoilsfromdifferentplaces, includingurbanareas,landfills,andgasandoillocations,mightinfluencehumanhealthsincesuchsoils couldincludeanthropogeniccontamination(Steffan etal.,2018).Anothercrucialsoilpollutionfactoris crudeoilobtainedfromprocessingoilproductionand wastes.Severalvitalmetalsrepresentedbycadmium (Cd),copper(Cu),iron(Fe),lead(Pb),manganese (Mn),nickel(Ni),andzinc(Zn)arethemajorheavy metalpollutantsinthewater.Levelsofheavymetals andaccumulatedsedimentsinrivershaveincreasedbecauseoftheincreaseinthereleaseofmassiveamounts ofindustrialanddomesticwasteintothesystem.

TheCu(II)ionisanecessaryconstituentinboth chemistryandbiochemistry.However,itsconcentrationinwastewatercancauseharmtohumans,plants, andanimals(Awualetal.,2019).ExtremeCu(II)ion canaltertheredoxstateoftheintracellularenvironment,spoilthestructuralperformanceofcells,and destroycells.Moreover,exposuretoahugeamount ofCu(II)mightcausehealthproblemsrangingfrom stomachdistresstobraindamage.Themaximumacceptablelimitisaccuratelyadjusted,asthepermissible Cu(II)ionindrinkingwateris0.05mg/L.

Humantoxicitymighthaveresultedfromthe sourcesofthesoilsupplies,asthesoilhasagreatimpactonhumanhealth.Dependingonsoilconditions, thesoilcanaffecthumanlifepositivelyornegatively. Aswithanynecessaryelementforhumanhealth,there isanideallimitthatthebodyrequires,andhaving anyconcentrationabovesuchalimitcancausetoxicity(Greenetal.,2016).Ascontaminatedsoilisirrigatedtocropplantsandfoods,suchobtainedfruitsor

vegetablesareconsideredriskstohumanhealth (Jankaite,2009).Justassoilcanprovidehumanswith miscellaneousnutrients,itcanalsodeliverdangerousingredientstothebodythroughfoodconsumed (OliverandGregory,2015).Thus,thehealthofhumanscanbeaffectedbychemicallycontaminatedsoil.

Heavymetalscanbereleasedfromthesurficialsedimentsofwatertotheupperwaterenvironmentand thuscanbeusedintentionallyforirrigationprocesses accompaniedbyharmfulimpactstofishinthewater (Yinetal.,2020).Thefoodcharacteristicsaccompaniedbytherisktohumanhealthareaffectedmainly bythetypeofagriculturalproducts,wherethequalityofsuchproductsiscontrolledbythetypeofsoil anditsmetalcontaminationlevel(HadiaandAhmed, 2018).Heavymetalsareharmfulmaterials,astheyaccumulateinthetissuesofthehumanbody(Kirchmann etal.,2017).

Also,theexistenceofmanganeseions(Mn+2 )iningestingwaterclogssupplypipesbecauseoftheoxidationofMn+2 toMnO2 ,resultinginablackcoloranda metallictasteinthewateranddiscolorationinhouseholdandwashingfixtures(Asirietal.,2018).ContinuedexposuretoahighconcentrationofMn+2 is hazardousandcanhurthumanhealth,causingmood swingsanddepression.

Ingeneral,heavymetalsaremetallicchemicalelementswithhighatomicmassesanddensities.Someof themareessentialtothehumanbodyatlowlevelsbut cancausepoisoningathigherlevels.Frequently,adensityofatleast5gm/cm3 isusedtodescribeaheavy metal.Moreover,heavymetalsinvolveanatomicmass greaterthan23oranatomicnumberhigherthan20. Investigatingtheperiodictableofchemicalelements, heavymetalsdominatecolumns3–16ofperiods4–6, includingthetransitionmetals,post-transitionmetals,andlanthanides(Duffus,2002).Therearemore than50constituentsofheavymetals,whereonly17 ofthemareclassifiedastoxicelements(Canoetal., 2013;Khanetal.,2020b).PbandCdaretwoofthe mostdangerouselementstohumanhealth,andsuch constituentscancausecoughing,headache,vomiting, anddeadlychestpain.

Pbisoneofthemostwidespreadsoilcontaminants theworldover;itssourcesincludelead-basedpaints, leadedgasoline,variousindustrialactivities,andlead smeltingandmining(Balabanovaetal.,2017).Urban soilcontaminatedwithPbisamajorsourceofhealth problemsforchildren(Lietal.,2015).Fertilization combinedwithsewage,slurry,orindustrialactivities arethemainsourcesofCdcontaminationinthesoil (Nordbergetal.,2014),andChinesesoiliscontaminatedmostlywithCd.Cd-contaminatedsoilcaused theitai-itaidiseaseeruptioninJapaninthefirstpart ofthe20thcentury(Nordbergetal.,2014).

Asnitrogenisnecessaryforplantsinthesoil,its overuseorinappropriateusecancausealeachingof excessnitrateintothesurfaceorgroundwater,leadingtoseveretoxicityduetotheformationofnitrites(Zhangetal.,2015).Nitritetendstoreactwith hemoglobinandformmethemoglobin,whichprevents oxygenfrombeingtransportedtotheentirebody.Fe shortageleadstoanemiasinceitisavitalelementof hemoglobin.Around2billionpeopletheworldover strugglewithadeficiencyofFe.Inaddition,toomuch Fecancausemetabolicandgeneticdiseases(Fraga, 2005).Zndeficiencyinitiatesnegativeeffectsonseveralofthebody’sabilities,suchastheimmunesystemresponse,thehealingofwounds,andtheability tobothsmellandtaste(Fraga,2005).Basedoncation exchangecapacity,silvernanoparticleshavebeenused toremoveheavymetalionsofPbfromwater(Khan etal.,2013).

Inrecentyears,worldadvancementhascausedenvironmentalpollution,asconcentrationsofheavymetalsinurbanareashavepassedtheiroriginalacceptable standards(Duanetal.,2018).Cd,Cu,andZnhavealteredthenatureofthesoilfromuncontaminatedconditionstotolerablycontaminatedconditions.Itwasreportedthatthespeciesoftheinhabitantplantstendto betreatedbyphytoremediationofsoilscontaminated byCd,chromium(Cr),Cu,andPb.However,other studieshavedemonstratedenvironmentalbiological toxicitywithsubstantialheavymetalsrepresentedby arsenic(As),Cr,Cu,Ni,tin,andZn(LiuandChen, 2018).Moreover,currentstudieshaveshownthatairpollutedcountriesaremorevulnerabletosuffering fromtheCOVID-19virus,whichimpliesapositiverelationshipbetweencontaminationandtheCOVID-19 virusinfectionrate(Albuquerqueetal.,2020).Itis worthwhiletomentionthatanionshavemanypositive effectsonhumanhealth,suchasbindingredblood cellsandincreasingoxygenintake,decreasingblood pressure,increasingthebloodpressurerate,andforcingthecontractionoftheheart(Imetal.,2018).Thus, itisbelievedthatanionsshouldhavenonegativeimpactsonhumanhealthandnopossiblerelationswith COVID-19.

DifferentcitiesinIraqareunderthethreatofheavy metalpollutionintheabsenceofstandardenvironmentalrulesandregulations,especiallycitieswitha highpopulation.Forexample,Baghdadhasthehighestpopulation,estimatedatalmost7millionin2011, andsuchalargepopulationisareasonfortheintensivelypooranthropogenicactivity(Demographia, 2014).Inaddition,attentiontocrudeoilwasteis requiredafterthegrowthofthepetroleumsubdivisioninthenorthernregionofIraq(Ahmedand Gulser,2019).IntheseIraqienvironments,constructionworkers,farmers,andminersareintouchwith

suchsoils,andtheirhealthisexposedtoriskatdifferentrates.Hence,theprocessofheavymetalassessment playsacrucialroleinIraqienvironmentalpollution studies.

Particulatematter(PM)isdefinedasasetofparticlesdiffusedintheairforalongenoughtimetobedispersedandtransferred.PMconsistsofinhalablecorpusclesthatproducedistinctivedestructiontohuman healthduetotheirsmallsize.ThetoxicityofPMis amplifiedsinceitcanabsorbotherconstituents,such aspolycyclicaromatichydrocarbonsandheavymetals. Hydrocarbonsareobtainedfromoilandarehighestin concentrationduringthewinterseason.Heavymetals areordinarycomponentsoftheEarth’scrust.Mostof theheavymetals(As,Cd,Cr,Pb,mercury,anduranium)aretoxic.Cardiovasculareffectsarecausedby PMandareassociatedwiththedepositionofparticlesinthelungs,wheretheirtranslocationsintothe air–bloodbarriercancausesystemicinflammation. Thus,heavymetalscanhaveastrongassociationwith COVID-19,wherebothcaninducedrasticharmtothe lungsandthreatenhumanlife.

Destroyingthehealthofhumansisthetarget forbothCOVID-19andheavymetalcontamination, wherebothworkindividuallyortogethertomaintaintheirgoal.Ininvestigatingtheconsequencesof COVID-19andheavymetalcontamination,itisobviousthatbothharmthesameordifferentportions ofthehumanbody.Mathematically,thetarget(human health)isaffectedbytheindividualorcombinedvariationofthevariables(COVID-19andheavymetalcontamination).Moreover,theeffectofincreasingoneof thevariables(COVID-19orheavymetalcontamination)andtheirimpactsonthetarget(humanhealth) canhelptheothervariableindefeatingthetarget faster.ThecomplicatedconnectionsofhumanlifeassociatedwithboththeCOVID-19virusandcontaminationcausedbydifferentheavymetalshavecreated thefocusforthisinvestigation.Inaddition,nopreviousstudieshavetriedtoexaminesuchanassessmentin Iraq.Thenoveltyofthisworkcanbeachievedbyprovidingamathematicalrelationshipbetweenconfirmed deathcasesofCOVID-19andtheindividualdistributionofheavymetalsinIraq.Themathematicalcorrelationthatisusedisderivedfromacomprehensive surveyofheavymetaldistributionsinvariousIraqi citiesintermsofconfirmeddeathcasesofCOVID-19 recordedoveraspecifictime.Hence,themainobjectiveofthisstudywastoinspecttheparalleldistributionforboththeCOVID-19virusandheavymetal contaminationinIraqicitiesdependingonavailable data.Specifically,thestudyhastriedtotesttherelationshipbetweentheCOVID-19virusandheavymetal contaminationindifferentIraqicitiesusingahierarchicalpredictiveapproach.

Table1. Allowablelimitforheavymetalconcentrationinsoil(μg/g) (EuropeanCommissionDirectorGeneralEnvironment,2010).

ElementGermanyNetherlandsSwedenUnitedStatesIreland

Cd1.00.50.41.91.0 Cr60.030.060.0150.0— Cu40.040.040.075.050.0 Hg0.50.50.30.851.0 Ni50.015.030.021.030.0 Pb70.040.040.015.050.0 Zn150.0100.0100–150140.0150.0

METHODS

StudyArea

IraqoccupiestheheartoftheMiddleEast,where Baghdadisthecapitalcitywiththehighestpopulation.Baghdadliesat33.312805latitudeand44.361488 longitude.ThetotalareaofIraqis437,072km2 and consistsof18provinces.Basedonthedataof2018, thetotalpopulationinIraqis38.43millionwithan annualgrowthrateof2.3percent.

DataCollection

Usingofficialonlinereports,thenumbersof COVID-19casesinIraqhavebeencollectedfromthe firstcaseuptoMay2,2020.Inaddition,thedetailsof confirmedcases,casespermillionforeachcity,recoveredcases,anddeathshavebeenassembled.Theprocessofheavymetalcontaminationhasincludedseveral worldwidestandards,asshowninTable1.Moreover, thedetailsofheavymetalcontaminationinallIraqi citiesaresummarizedinTable2.

RESULTSANDDISCUSSION

COVID-19Cases

TotalconfirmedCOVID-19casesfortheentirepopulationinIraquptoMay2,2020,comparedwith thetopthreecountriesintheworldareshownin Figure1a.ItisclearlyshownthatIraqhadarateof 0.004percentforthetotalconfirmedcasesperpopulation,whereasSpainhadthehighestrateof0.461 percentforthetotalconfirmedcasesperpopulation. However,boththeUnitedStatesandItalyhadalmost thesamerateofthetotalconfirmedcasesperpopulationupto0.344percent.Figure1bshowsthetotaldeathsfromCOVID-19casesintheentirepopulationinIraquptoMay2,2020,comparedwiththe topthreecountriesintheworld.ItisrevealedthatIraq hadthelowestrateoftotaldeathcasesperpopulation of0.0002percentcomparedwiththetopthreecountries.Spainhadthehighestrateofdeathsperpopulationcasesof(0.0534percent),followedbyItalyandthe

Figure1.ComparisonbetweenIraqandthetopthreecountriesin worldfor(a)confirmedcasespertotalpopulationofCOVID-19 virus,(b)deathcasespertotalpopulationofCOVID-19virus,and (c)recoverycasespertotalpopulationofCOVID-19virus.

Table2. DatacollectionfordifferentchemicalelementsoverallofIraq.

ReferenceElement Concertation (μg/g)Remarks

Al-JaberiandAl-Dabbas (2014)

Co17.7City:Al-Basrah Cu41No.ofsamples:23

Ni119Location:sedimentsofcoastline

Pb18Methodoftesting:inductivelycoupledplasma-atomicemissionspectrometry Zn127Placeoftesting:UppsalaUniversity,Sweden

Concentration:maximumtestedvalues

Almayahietal.(2014)Cd0.88City:Al-Najaf

Co1.31No.ofsamples:12

Cr1.37Location:differentplacesinthecity

Pb3.35Methodoftesting:flameatomicabsorptionspectrophotometry

Placeoftesting:UniversityofKufa,Iraq

Concentration:maximumtestedvalues.

Benni(2014)Co39City:ThiQar. Cr418No.ofsamples:436

Cu144Location:alloverthecity

Ni494Methodoftesting:atomicabsorptionanalysis

Pb54Placeoftesting:chemicallaboratories,IraqGeologicalSurvey U2.66Concentration:maximumtestedvalues

Zn310

Othmanetal.(2014)Cd10.4City:Mosul Cu135No.ofsamples:20

Fe455.4Location:crowdedstreetsandneargenerators Mn)229.6Methodoftesting:atomicabsorptionanalysis Pb289.6Placeoftesting:MosulUniversity,Iraq Si21.8Concentration:maximumtestedvalues

Al-Hamdanietal.(2016)Cd0.54City:Kirkuk Co14.426No.ofsamples:99

Cr128.64Location:alloverthecity(onesample/km2 )

Cu76.45Methodoftesting:inductivelycoupledmassspectrometry Ni120.37Placeoftesting:LaboratoryofSoilMechanics,KirkukConstructionLab,Iraq Pb341.44Concentration:maximumtestedvalues Zn229.48

Mohammedand Abdullah(2016)

Cd4.31City:Baghdad

Cr123No.ofsamples:24

Cu82Location:variousplaces,nearnorthofeastBaghdadoilfield Ni196.5Methodoftesting:inductivelycoupledplasma-massSpectrometry

Pb31Placeoftesting:ALSGroupLabs,Spain

Zn1,080Concentration:maximumtestedvalues

Yousif(2016)Cd56.52City:Dohuk

Co56.52No.ofsamples:120

Ni82.7Location:placesnearthepavementedgesoffivedifferentzones Pb85.15Methodoftesting:Shimadzudevice,model6401F,Japan

Zn83.79Placeoftesting:ZakhoUniversity,Iraq

Concentration:maximumtestedvalues

Abood(2017)Cr93City:Diyala

Cu38No.ofsamples:28

Fe16,650Location:Differentplacesalloverthecity Ni121Methodoftesting:X-rayfluorescence

Pb93PlaceofTesting:UniversityofDiyala,Iraq

Zn240Concentration:maximumtestedvalues

TawfiqandGhazi(2017)Cd1.10City:Misan

Cr86.8No.ofsamples:28

Ni90.1Location:residential,industrial,commercial,andagriculturalzonesinthecity Pb78.7Methodoftesting:inductivelycoupledplasma-massspectrometry

Placeoftesting:UniversityofBaghdad,Iraq

Concentration:maximumtestedvalues

Al-Dabbasetal.(2018)Co18City:Al-Qadisiyah

Cu160No.ofsamples:12

Ni200Location:westernandeasternzonesinthecity

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Table2. Continued.

ReferenceElement Concertation (μg/g)Remarks

Pb110Methodoftesting:X-raydiffractionandX-rayfluorescence Zn190Placeoftesting:UniversityofBaghdad,Iraq Concentration:maximumtestedvalues

Sürücüetal.(2018)Cd5.01City:Al-Sulaimaniyah Co10.21No.ofsamples:120

Cr300.6Location:threesectionsofmainroadsconnectingthecity Pb245Methodoftesting:atomicabsorptionspectrometry,PerkinElmer8800 Ni240.9Placeoftesting:UniversityofSulaimania,Iraq

Concentration:maximumtestedvalues

Ahmedand Abd-Alhameed(2019)

Cr74City:Erbil Cu85.2No.ofsamples:41

Fe6,700Location:differentlocationssurroundingthesteelcompanyinthecity Ni10.2Methodoftesting:X-rayfluorescence Pb378Placeoftesting:SalahaddinUniversity-Erbil,Iraq Zn220.4Concentration:maximumtestedvalues

Hmoodetal.(2019)Cd0.211City:Karbala Pb11.712No.ofsamples:12

Location:selectedschoolsinthecity Methodoftesting:atomicabsorptionSpectrometry Placeoftesting:UniversityofKerbala,Kerbala,Iraq Concentration:maximumtestedvalues

Khazaaletal.(2019)Cd0.201City:Al-Anbar Cr0.132No.ofsamples:100

Fe0.423Location:alongthecenterofLakeAl-Habbaniyyahinthecity Ni0.095Methodoftesting:atomicabsorptionspectrometry Pb0.602Placeoftesting:NationalResearchCouncilCanada Concentration:maximumtestedvalues

Maneaetal.(2019)As8.20City:Babil Cd11.5No.ofsamples:13

Co43Location:bothsoilandriversedimentsinthecity Cr31.6Methodoftesting:atomicabsorptionspectrometry Cu102Placeoftesting:UniversityofBaghdad,Iraq Fe3,120Concentration:maximumtestedvalues Mn74 Ni68

Pb76.5 Zn131

Al-DabbasandAbdullah (2020)

Co32.5City:SalahAl-Din Cu55.1No.ofsamples:10

Pb19.8Location:agriculturalareainthecity Zn140.8Methodoftesting:X-rayfluorescence

Placeoftesting:UniversityofBrighton,UnitedKingdom,andUniversityof Baghdad,Iraq

Concentration:maximumtestedvalues

AlSharaaetal.(2020)Cr47City:Al-Muthanna Cu42No.ofsamples:300

Ni49Location:Achemicalweaponsstoragefacilityinthecity Pb34Methodoftesting:noinformation

Zn407Placeoftesting:UniversityofTechnology,Baghdad,Iraq

Concentration:maximumtestedvalues

Issaetal.(2020)Cd2City:Wasit Co25.4No.ofsamples:18

Cr425.2Location:sedimentscoveringTigrisRiverinthecity Cu56.2Methodoftesting:X-raydiffractionandX-rayfluorescence Mn1,069Placeoftesting:UniversityofBaghdad,Iraq Mo15.8Concentration:maximumtestedvalues Ni226.6 Pb35.2 Zn190.3

Environmental&EngineeringGeoscience,Vol.XXVIII,No.4,November2022,pp.397–413

Table2. Continued.

ReferenceElementConcertation(μg/g)Remarks

RemarksVariouschemical contaminants

MinimumelementcontentisNi(0.095)in Al-Anbar,whereasmaximumelement contentisFe(16500)inDiyala

City:allIraqicities

No.ofsamples:range(10–436)

Location:variouslocations,suchasresidential,industrial, commercial,agricultural,andriversediments

Methodoftesting:mainlyatomicabsorptionspectrometryand rarelyX-raydiffractionandX-rayfluorescencemethods Concentration:maximumtestedvalues

UnitedStates(0.0467percentand0.0199percent,respectively).TotalrecoveryfromCOVID-19casesinthe entirepopulationofIraquptoMay2,2020,compared withthetopthreecountriesintheworldisshownin Figure1c.AspresentedinFigure1c,Iraqhadthe lowestrecoverycasesperpopulationof0.003percent incontrasttoSpain,whichhadthehighestrecovery casesperpopulationof0.249percent.Inaddition,it isworthwhiletopointoutthattherecoverycasesper populationwere0.129percentand0.0431percentin ItalyandtheUnitedStates,respectively.

TotalconfirmedCOVID-19casesinallIraqicities uptoMay2,2020,areshowninFigure2a.Baghdad hadthehighestnumberofconfirmedcasesfollowed byAl-Najaf,Al-Basrah,Erbil,andAl-Sulaymaniyah. ConfirmedcasesinthetopIraqicitiesrangefrom384 inBaghdadto138inAl-Sulaymaniyah.Thisismainly becausethesefivecitieshaveinternationalairportsthat facilitatedtheentranceoftheviruswithlimitedhealth monitoringsystemsinsuchairports.Figure2bshows thetotalconfirmedCOVID-19casespermillionofthe citypopulationinallIraqicitiesuptoMay2,2020. ThehighestrateforthetotalconfirmedCOVID-19 casespermillionofthecitypopulationwasinAlNajaf(upto216),whereasthelowestratewasrecorded inAl-Anbar.Inaddition,DohukandAl-Basrahare thetwocitieswithnoreportednumbersforthetotalconfirmedCOVID-19casespermillionofthecity population.ItissignificanttorecognizethatAl-Najaf isacrowdedplacesinceitholdsanimportantIslamic shrine.Figure2creportsthetotalrecoveredCOVID19casesinallIraqicitiesuptoMay2,2020.AlNajafhadthehighestnumberofrecoveredcases(270), whileSalahal-Dinhadthelowest(1).Totaldeathsof COVID-19casesinallIraqicitiesduringthestudyperiodarereportedinFigured.Baghdadhadthehighest numberdeaths(30),followedbyAl-Basrah,Al-Najaf, andKarbala(17,6,and6,respectively).

HeavyMetalContamination

Forheavymetalrepresentation,theobtaineddata fromTable2havebeendrawnfromalloverthe

country.ThedistributionofCdindifferentIraqicities isshowninFigure3a.Basedonthecollecteddata,DohukhasthehighestCdcontentwithaconcentrationof 56.52 µg/g(61percentofthetotalCdconcentrationin allIraqicities).ThemainreasonforthehighCdconcentrationinDohukisattributedtotherecentworkof oilcompanieswithinadequateobligationstoenvironmentalrules.TheaveragereportedCdconcentration foranareawithcoalpowerplantsis0.06 µg/g,which ismuchlowerthanthatformostIraqicities(Okedeyi etal.,2014).Thus,morelimitationsandregulations shouldbeappliedtominimizetheincreaseofCdconcentrationinIraqicities.

Similarly,thedistributionsofCrandCuarereportedinFigure3bandc,respectively.ItcanbenoticedthatWasit,ThiQar,andAl-Sulaimaniyahare thetopthreeIraqicities,withCrconcentrationsof 425.2 µg/g,418 µg/g,and300.6 µg/g,respectively. TheconsecutiveCrconcentrationsinWasit,ThiQar, andAl-Sulaimaniyahrepresent25percent,24percent, and17percentofthetotalCrconcentrationinall Iraqicities.Inaddition,itcanbeobservedthatAlQadisiyah,ThiQar,andMosularethetopthreeIraqi cities,withCuconcentrationsof160 µg/g,144 µg/g, and135 µg/g,respectively.TheconsecutiveCuconcentrationsinAl-Qadisiyah,ThiQar,andMosulrepresent16percent,14percent,and13percentofthetotalCuconcentrationinallIraqicities.TheaveragereportedCrandCuconcentrationsforanareawithcoal powerplantsare63.27 µg/gand56.15 µg/g,respectively(Okedeyietal.,2014).Also,therecordedCrand CuconcentrationsinIraqicitiesarehigherthanthe reportedvalues.Hence,topreventanyupcomingenvironmentalcatastrophe,IraqiauthoritiesshouldcontroltheincreaseofbothCrandCuconcentrations.

ThedistributionsofNi,Pb,andZnareshownin Figure4a,b,andc,respectively.Itcanbeseenthat Al-Sulaimaniyah,Wasit,andAl-Qadisiyaharethetop threeIraqicities,withaNiconcentrationsof240.9 µg/g,226.6 µg/g,and200 µg/g,respectively.TheconsecutiveNiconcentrationsinAl-Sulaimaniyah,Wasit,andAl-Qadisiyahrepresent12percent,11percent, and10percentofthetotalNiconcentrationinall

Figure2.Mapdistributionof(a)confirmedCOVID-19casesinallIraqicities,(b)confirmedCOVID-19casespermillionofcitypopulation inallIraqicities,(c)recoveredCOVID-19casesinallIraqicities,and(d)deathcasesofCOVID-19inallIraqicities.

Figure3.Mapdistributionofvariouschemicalelements(μg/g)in differentIraqicities:(a)Cd,(b)Cr,and(c)Cu.

Figure4.Mapdistributionofvariouschemicalelements(μg/g)in differentIraqicities:(a)Ni,(b)Pb,and(c)Zn.

Environmental&EngineeringGeoscience,Vol.XXVIII,No.4,November2022,pp.397–413

Iraqicities.Inaddition,itcanbeobservedthatErbil, Kirkuk,andMosularethetopthreeIraqicities,witha Pbconcentrationof378 µg/g,341.44 µg/g,and289.6 µg/g,respectively.TheconsecutivePbconcentrations inErbil,Kirkuk,andMosulrepresent20percent,18 percent,and15percentofthetotalPbconcentration inallIraqicities.Moreover,Baghdad,Al-Muthanna, andThiQararethetopthreeIraqicities,withZnconcentrationsof1,080 µg/g,407 µg/g,and310 µg/g,respectively.TheconsecutiveZnconcentrationsinBaghdad,Al-Muthanna,andThiQarrepresent32percent, 12percent,and9percentofthetotalZnconcentration inallIraqicities.TheaveragereportedNi,Pb,andZn concentrationsforanareawithcoalpowerplantsare 31.79 µg/g,52.05 µg/g,and86.49 µg/g,respectively (Okedeyietal.,2014).Inaddition,therecordedNi,Pb, andZnconcentrationsinIraqicitiesarehigherthan thereportedvalues.ThecurrentNi,Pb,andZnconcentrationsportendanupcomingenvironmentaldisasterinIraq.

Acomparisonbetweentheheavymetaldistributionwithupperandlowerallowablestandardlimits hasbeeninvestigated.ThevariationofCddistribution comparedwithstandardallowablelimitsisshownin Figure5a.ItisclearlyshownthatplacessuchasDohuk,Babil,andMosulhaveCdconcentrationshigher thantheallowableupperlimit.TheCdconcentration ratehasexceededtheallowableupperlimitby30,6, and5timesinDohuk,Babil,andMosul,respectively.

Similarly,thevariationofCrdistributioncompared withstandardallowablelimitsisshowninFigure5b. ItisindicatedthatcitiessuchasWasit,ThiQar,and Al-SulaimaniyahhaveCrconcentrationshigherthan theallowableupperlimit.TheCdconcentrationrate hasexceededtheallowableupperlimitbyalmost3,3, and2timesinWasit,ThiQar,andAl-Sulaimaniyah, respectively.

ThevariationofCudistributioncomparedwith standardallowablelimitsisshowninFigure5c.SeveralIraqicitieshaveexceededtheallowableupper limit,suchasThiQar,Mosul,Kirkuk,Baghdad,AlQadisiyah,Erbil,andBabil.ItisnoticeablethatAlQadisiyah,ThiQar,andMosulhavethehighestCu concentrationscomparedtootherIraqicities.TheCu concentrationratehasexceededtheallowableupper limitbyalmost2,1.9,and1.8timesinAl-Qadisiyah, ThiQar,andMosul,respectively.

ThevariationofNidistributioncomparedwith standardallowablelimitsisreportedinFigure5d. MostofthecitieshaveNiconcentrationshigherthan theupperallowablelimit,whereThiQarhadthehighestNiconcentrationexceedingtheupperallowable limitby9.9times.Inaddition,Al-Sulaimaniyahand WasithaveexceededtheNiallowableupperlimitby 4.8and4.5times,respectively.

ThevariationofPbdistributioncomparedwith standardallowablelimitsisshowninFigure5e.Allthe IraqicitieshaveaPbconcentrationwithdifferentrates, wherenineofthecitieshavePbconcentrationshigher thantheallowableupperlimit.ItcanbeseenthatErbil,Kirkuk,andMosularethetopthreeIraqicities thatexceededthePballowableupperlimitbyalmost 5.4,4.9,and4.1times,respectively.

ThevariationofZndistributioncomparedwith standardallowablelimitsisshowninFigure5f.Eight IraqicitieshaveaZnconcentrationhigherthanthe allowableupperlimit.ItcanbeseenthatBaghdad,Al-Muthanna,andThiQararethetopthree IraqicitiesthatexceededtheZnallowableupper limit.TheZnconcentrationratehasexceededthe allowableupperlimitbyalmost7.2,2.7,and2.1 timesinBaghdad,Al-Muthanna,andThiQarcities, respectively.

Asanoverallassessment,differentIraqicitieshave variouslevelsofheavymetalcontamination.Itis worthwhiletomentionthatDiyalahadthehighestFe concentrationof16,650 µg/g,anditisclearlysummarizedinTable2.

RelationbetweenCOVID-19andHeavyMetal Contamination

Basedonthereportedinformationregardingboth COVID-19andheavymetaldistribution,asuitablehierarchicalpredictivestatisticalmodelhasbeenproposed.Thismodelisbasedonthefactthattheincreaseinheavymetalcontaminationcanincreasethe rateofdeathresultingfromreducedhumanbodyresistance.Similarly,COVID-19exhibitsthesametrendin termsofweakeningthehumanbody’sresistance.The target(humanhealth)ismathematicallyaffectedby theindividualorcombinedvariationofthevariables (COVID-19andheavymetalcontamination).Furthermore,increasingoneofthevariables(COVID-19or heavymetalcontamination)anditsimpactonthetarget(humanhealth)canaidtheothervariableindefeatingthetargetmorequickly.Hence,alinearaccumulativehierarchicalstatisticalmodelhasbeenproposed assumingthattheaccumulativeconfirmedordeath COVID-19casesarelinearlyproportionedtotheaccumulativeheavymetalconcentration.Theproposed modelhasthefollowingform: (Conf Cases )i (Conf Cases ) (% ) = A + B

(HeavyMetalConcentration )i (HeavyMetalConcentration ) (% ) (1) where (Conf. Cases)i istheaccumulativesumof confirmedcasesofCOVID-19, (Conf. Cases)isthe

totalsumofconfirmedcasesofCOVID19, A and B are arbitraryconstants, (HeavyMetalConcentration)i istheaccumulativesumofaspecificheavymetalconcentration,and (HeavyMetalConcentration)isthe totalsumofaspecificheavymetalconcentration.

Asimilarproposedstatisticalmodelcanbeapplied fordeathcasesofCOVID-19.Thestatisticalmodelfor

Table3. Statisticalmodelparameters(Eqs.1–3).

ConfirmedCasesCOVID-19(Eq.1)DeathCasesofCOVID-19(Eq.2)

HeavyMetalTypeABR2 ABR2

Cd32.50.650.8415.130.800.83 Cr17.40.960.899.151.090.81 Cu16.20.880.9119.30.880.84 Ni7.960.950.9116.520.900.86 Pb28.860.700.9527.50.730.90 Zn21.160.850.9725.060.850.94

where (Deaths)i istheaccumulativesumofthe deathsofCOVID-19and (Deaths)isthetotalsum ofthedeathsofCOVID-19.

Theaccuracyofthesuggestedstatisticalmodels (Eqs.1and2)hasbeenevaluateddependingonthe coefficientofdetermination(R2 ).Thecoefficientofdetermination(R2 )isdefinedasfollows: R2 = ⎛ ⎝ i (xi x )(yi y ) i (xi x )2 i (yi y )2 ⎞ ⎠ 2 (3)

where yi istheactualvalue, xi isthepredictedvalue fromthestatisticalmodel, y isthearithmeticmeanof theactualvalues,and x isthearithmeticmeanofcalculatedvalues.

AlltheproposedstatisticalmodelshavebeenvalidatedusingthereportedIraqiCOVID-19datawith thevariousheavymetalconcentrationsindifferent Iraqicities.Severalrandomvariations(gradualincrease)wereinvestigatedforbothCOVID-19cases andheavymetalconcentrations,andthebestdistributionwiththehighestR2 waschosen.Thevariationsof COVID-19withCdconcentrationforconfirmedand deathcasesareshowninFigure6aandb.Inaddition, themodelparametersforconfirmedanddeathcases concerningallheavymetalvariationsaresummarized inTable3.Itisclearlyshownthattheproposedstatisticalmodelshavepredictedthevariationsofconfirmed anddeathcasesverywellwithavalueof(R2 )reaching 0.84(Table3).FromFigure6candd,thevariations oftheCOVID-19withCrconcentrationforconfirmed anddeathcasesbecomeclear.Thesuggestedstatisticalmodelshavepredictedthevariationsofconfirmed anddeathcasesverywellwithamaximumvalueofR2 of0.89(Table3).Similarly,thevariationsofCOVID19confirmedanddeathcaseswithCu,Ni,Pb,and ZnconcentrationsappearinFigures6eandf,7aand b,7candd,and7eandf,respectively.Theproposed statisticalmodelshavepredictedthevariationsofconfirmedanddeathcasesverywell,andthisistrueforall thevariousheavymetalconcentrations.Themaximum

obtainedR2 forthevariationswithCu,Ni,Pb,andZn were0.91,0.91,0.95,and0.97,respectively.

Basedontheresultsoftheproposedstatisticalmodels,thereisapositivelinearrelationshipbetweenconfirmedanddeathCOVID-19caseswiththedifferent typesofheavymetaldistribution.Thisindicatesthat increasinganytypeofheavymetalconcentrationbeyondtheallowableupperlimitmayresultinincreasing COVID-19confirmedanddeathcases.

RegardingbothCOVID-19victimsandheavymetal contaminationdistribution,severalIraqicitiesmight beunderarealthreatofsuchsevereheavymetalpollution,whichhasharsherconsequencesthanCOVID-19 virus.Inaddition,thedistributionofheavymetalcontaminationwouldweakenthehumanimmunesystem, andthismightreflectanincreaseofCOVID-19cases insuchplacesinshort-orlong-termevaluations.

CONCLUSIONS

Inthisstudy,theeffectsofbothCOVID-19and heavymetaldistributioninallIraqicitiesuptoMay 2,2020,havebeeninvestigated.Ontheonehand,the detailsofconfirmedandrecoveredcaseswithtotal deathsinallIraqicitieshavebeeninspected.Onthe otherhand,theheavymetalcontaminationinallIraqi citieshasbeenstudiedusingthevariousavailableliterature.Inaddition,thestudyhassuggestedalinearstatisticalrelationshiptocorrelateconfirmedanddeath COVID-19caseswithdifferentheavymetalconcentrations.Ingeneral,thestudyhasrevealedthefollowing:

1.Uptothestudieddate,thetotalnumberofIraqi COVID-19confirmedcasesperpopulationwas 0.004percentcomparedto0.461percentinSpain (thehighestrateintheworld).

2.Uptothedateofthisstudy,Iraqhadthelowestrate oftotaldeathcasesperpopulation(0.0002percent) comparedwiththetopthreecountriesintheworld, whereasSpainhadthehighestrate(0.0534percent).

3.Forheavymetalcontamination,Dohukhadthe highestCdcontent(56.52 µg/g;61percentofthe

Figure6.HierarchicalmodelpredictionforthevariationofCOVID-19withdifferentchemicalelementsfor(a)Cd-confirmedcases,(b) Cd-deathcases,(c)Cr-confirmedcases,(d)Cr-deathcases,(e)Cu-confirmedcases,and(f)Cu-deathcases.

totalconcentrationinallIraqicities),whileWasit showedthehighestCrconcentration(425.2 µg/g; 25percentofthetotalconcentrationinallIraqi cities).

4.TheextremecontentsofCu,Ni,Pb,andZnare concentratedinAl-Qadisiyah,Al-Sulaimaniyah, Erbil,andBaghdad,withlimitsof160 µg/g, 240.9 µg/g,378 µg/g,and1,080 µg/g,respectively.

5.InvariousIraqicities,thelevelsofheavymetalcontaminationfordifferentchemicalelementshaveexceededtheupperallowableworldlimits.wherethe maximumratewasforCdcontentinDohuk,exceedingtheallowableupperlimitby30times.

6.Basedontheproposedstatisticalmodel,thereisa linearpositiverelationshipforboththeconfirmed rateandthedeathrateofCOVID-19caseswith

Figure7.HierarchicalmodelpredictionforthevariationofCOVID-19withdifferentchemicalelementsfor(a)Ni-confirmedcases,(b)Nideathcases,(c)Pb-confirmedcases,(d)Pb-deathcases,(e)Zn-confirmedcases,and(f)Zn-deathcases.

differentlevelsofheavymetalcontaminationwith amaximumR2 valueof0.97.

DISCLAIMER

Itisherebydeclaredthatthisarticlehasnoconflict ofinterest.DatafromofficialIraqisourceshavebeen used.

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ADVISORY BOARD

Watts, Chester “Skip” F. Radford University Hasan, Syed University of Missouri, Kansas City Nandi, Arpita East Tennessee State University

Oommen, Thomas Board Chair, Michigan Technological University Sasowsky, Ira D. University of Akron

ASSOCIATE EDITORS

Ackerman, Frances Ramboll Americas Engineering Solutions, Inc. Bastola, Hridaya Lehigh University Beglund, James Montana Bureau of Mines and Geology

Bruckno, Brian Virginia Department of Transportation Clague, John Simon Fraser University, Canada Dee, Seth

University of Nevada, Reno Fryar, Alan University of Kentucky Gardner, George Massachusetts Department of Environmental Protection

Hauser, Ernest Wright State University Keaton, Jeff AMEC Americas May, David USACE-ERDC-CHL Pope, Isaac Book Review Editor Santi, Paul Colorado School of Mines Schuster, Bob Shlemon, Roy R.J. Shlemon & Associates, Inc. Stock, Greg National Park Service Swanson, Susan (Sue) Beloit College Ulusay, Resat Hacettepe University, Turkey West, Terry Purdue University

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Cover photo

Eric Peterson

Department of Geography, Geology, and the Environment Illinois State University Normal, IL 61790 309-438-5669 ewpeter@ilstu.edu

Karen E. Smith, Editorial Assistant, kesmith6@kent.edu

Photographed on January 21, 1924 were slope failures that undermined buildings along South Jackson Street in Seattle, Washington, complicating regrading projects. This photo and others are compiled in the City of Seattle historic landslide database which is used to evaluate present-day landslide hazards. Photographer unknown, City of Seattle landslide file SED J-1B. Courtesy of Elizabeth Davis. See article on page 335.