Coupling the water footprint accounting of crops and in-stream monitoring activities at the catchment scale

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Method

Article

Coupling

the

water

footprint

accounting

of

crops

and

in-stream

monitoring

activities

at

the

catchment

scale

Ersilia

D

’Ambrosio

a,b

,

Anna

Maria

De

Girolamo

b,

*

,

Maria

Cristina

Rulli

a

DepartmentofCivilandEnvironmentalEngineering,PolitecnicodiMilano,Milan,Italy

b_Water_Research_Institute,_National_Research_Council,_Bari,_Italy

ABSTRACT

Inthiswork,asimpleapproachforcalibratingthewaterfootprint(WF)accountingofcropswithin-stream measurementsatthecatchmentscalewasdeveloped.ThegreenandbluecomponentsoftheWFwereevaluated byperforming asoil-waterbalance ata10-day time-interval.Thesurface runoffwas calibratedbased on continuousstreamﬂowmeasurements.Meanwhile,thegreycomponentoftheWFrelatedtonitrogenusewas quantiﬁedbymeansoftheresultsfromthein-streammonitoringactivities.

Themethodologycanbeappliedtoanycatchmentwheresoil,landuse,weather,agriculturalpractices,nitrogen balance and streamdata are available.This methodological approach cansupport local authoritiesin the decision-makingprocessforeffectiveagriculturalpolicysettingandwaterplanning.

TheWFaccountingforanagriculturalcatchmentiscoupledwithsurface-watermonitoringresults ThegreenandblueWFareassessedbyperformingasoil-waterbalance

Surfacerunoffandgreywateraccountsarebasedonin-streammonitoringactivities

(http://creativecommons.org/licenses/by-nc-nd/4.0/).

ARTICLE INFO

Methodname:Calibratingthewaterfootprintaccountingofcropswithin-streammeasurementsatcatchment-scale Keywords:Waterfootprint,Soilwaterbalance,Runoffcalibration,Nitrogenexportcoefﬁcient,Temporaryriver,Surfacewater monitoring

Articlehistory:Received27July2018;Accepted1October2018;Availableonline6October2018

*Correspondingauthorat:WaterResearchInstitute,NationalResearchCouncil,70132,Bari,Italy. E-mailaddress:annamaria.degirolamo@ba.irsa.cnr.it(A.M.DeGirolamo).

https://doi.org/10.1016/j.mex.2018.10.003

MethodsX5(2018)1221–1240

ContentslistsavailableatScienceDirect

MethodsX

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SpeciﬁcationsTable

Subjectarea AgriculturalandBiologicalSciences Morespeciﬁcsubjectarea WaterFootprintsassessments

Methodname Calibratingthewaterfootprintaccountingofcropswithin-streammeasurementsat catchment-scale

Nameandreferenceof originalmethod

Waterfootprintaccountingforcatchmentsandriverbasins.Calculationofthegreen,blue andgreywaterfootprintofgrowingacroportree-Irrigationscheduleoption(Hoekstra, A.Y.,Chapagain,A.K.,Aldaya,M.M.,Mekonnen,M.M.,2011.TheWaterFootprint AssessmentManual.London–WashingtonDC)

Estimatetheleaching-runofffractionfornitrogendiffusepollutionsources(Franke,N.A., Boyacioglu,H.,Hoekstra,A.Y.,2013.Greywaterfootprintaccounting:Tier1supporting guidelines.Unesco-IHE,Delft)

Resourceavailability -Software:SoilWaterCharacteristics(SPAW)(ars.usda.gov/research/software) -Software:BaseflowFilterProgram(swat.tamu.edu/software/baseflow-filter-program) -Loadstool[1]

Methoddetails Thewaterfootprint

Thewaterfootprint(WF)isarelativelynewindicator,introducedbyHoekstraandHung[2]to enablethequantiﬁcationofwaterconsumptionandpollution,andtofostertheimplementationof moresustainablewater-use practices. Galli etal. [3] included theWF in their‘footprintfamily’, togetherwithecologicaland carbon footprints,as asuiteof indicatorsusefulin trackinghuman pressureson the planet from different aspects. The WF is a multidimensional indicator, which accountsforboththedirectandindirectappropriationoffreshwaterresources.

WFassessmentsshouldbeconductedattheriverbasinscaleinthecontextofintegratedwater resourcemanagementaimedatsustainabledevelopment[4–6].Despitethisobservation,agricultural WFaccountingsattheriverbasinscalearerare,duetothelackofreliabledataatthisscale,especially foraridandsemi-aridregions,becauseofthehighfragmentationoflanduseandvariableadopted managementpractices[7].

Methodobjectives

ThisstudyaimedtogivegeneralguidanceonhowtoperformaWFaccountingofcropproduction atthecatchmentscale,inordertoevaluatethesustainabilityofagriculturalactivitiesbyconsidering bothwaterquantityandquality.Inparticular,thedeﬁnedmethodologiesaimedto:i)gatherreliable dataonlanduseand agriculturalpractices adoptedwithinthecatchment;ii) suggesta detailed programof surface-watermonitoring, in ordertobetterunderstandthehydrologicaland water-quality processes acting in the catchment, especially for arid and semi-arid regions containing temporary rivers1 _[₈_]; _iii) _estimate _loads _when _ﬂow _and _{concentration} _measurements _are _not

continuousandsimultaneous;andiv)coupletheassessmentofthetotalWFofcatchment-scalecrops andin-streammonitoringactivities.Themethodologyforcalibratingandquantifyingnitrogenexport

coefﬁcients and water balance components useful for WF assessment constitutes the ﬁrst

experimental work ina basin witha temporary river network. Themethodology proposedhere cansupportlocalauthoritiesinthedecision-makingprocessforeffectiveagriculturalpolicysetting andwaterplanning,thusfosteringimplementationoftheEUWaterFrameworkDirective[9].

1_Temporary_rivers_are_deﬁned_as_rivers_that_experience_dry_periods_over_the_entire_water_body,_or_only_in_parts_of_it,_recorded

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Analysisofagriculturalpractices

Officialdata onanthropogenic activitiesand agriculturalmanagement practices adoptedin a catchmentcomefromagriculturalcensuses;however,agronomicdataaregenerallyaggregatedat differentspatiallevels(region,province,municipality),andtheirdownscalingneedstobeverified throughadetailedsurveycampaign.Indeed,alargedifferenceintheamountoffertiliserusedcanbe foundbetweenruralmountainousareasandplainsareasdevotedtointensiveagriculture[10].Taking into account this difference, local citizens and farmers were interviewed, and the information providedbyfiveownerswasselectedasbeingrepresentativeofagriculturalholdingsforlanduse, cultivation techniques and management practices for the integrated census data.These owners providedinformationonthetype,timingandamountoffertilisersusedforeachcrop,annualcrop yields,croprotation,tillageoperationsandirrigationsupply.

Theamountofthetotalnitrogen(TN)applicationratehadtobeestimatedforeachcropwithinthe catchmentboundaries,includingtheTNinsyntheticfertilisers(NSF),andinanimalmanure(NAF)if that was used as fertiliser. In this study, the TN fromNAF was estimated for each animal type, multiplyingtheanimal-speciﬁcTNexcretion ratesbythelive weightof eachanimal type[11,12] (Table1).Adistinctionbetweenindoorandoutdoorfarmingwasmade.Formanureproducedby indoor farming, a 27.5% of TN loss during manure handling and storage was considered [13].

AppendixAcontainsalltheacronyms/abbreviationsusedinthispaper. Surface-watermonitoring

Hydrologicalprocessesarecharacterisedbyhightemporalandspatialvariability,especiallyinarid andsemi-aridregionswithtemporaryrivers[14,15].Aquantificationofpollutantsdeliveredtorivers requiresmonitoringactivitiesthatanalyseallstreamflowconditions(floodevents,normalandlow flow)[16–18].

Inthecasestudylocation(Celone,Apulia,Italy),anautomaticsampler(ISCOmodel6712FS)with aninternaldataloggerwasinstalled[17](Fig.1).Thesamplerwasconnectedtoaflowmodule(ISCO 750AreaVelocityFlowModule)tomeasurestreamwaterstageandvelocity,whichwereconvertedto streamflow usinga predefined stage-discharge ratingcurve. Thesampler offersdifferent sets of programming.Inparticular, two setswereselected:i) a time-space samplingprogram;and ii)a programthatwastriggeredbywater-levelchangesduringtherisinglimbofthehydrograph,andflow ratesduringfloodrecession.Withthefirststandardprogram,periodicsamplesweretakenatmonthly orfortnightlyintervalsduringsummerandautumn,andonceortwiceaweekfromNovembertoJune. Forfloodevents(secondprogram),thetimeintervalsvariedfrom15minto2hovertherisinglimbof thehydrograph,andfrom2htoonedayoverthefloodrecession.Theconcentrationsofammonia (N-NH4),nitrate(N-NO3),nitrite(N-NO2),totalorganicnitrogen(TON)andTN(TN=TON+N-NH4+ N-NO3+N-NO2)weredeterminedusingtheAPAT-IRSAchemicalstandardanalyticalmethods[19].

In order to evaluate the contribution of point sources (i.e., wastewater treatment plants dischargingintotheriversystem),ifpresent,itwas necessarytoanalysenitrogenconcentrations upstreamanddownstreamfromthepoint-sourcedischarge.IntheCelonecatchment,wastewater Table1

Manureproduction,liveweight(LW)andTNexcretionratesofdifferentanimaltypes.

Animaltype Manureproductionrates Liveweight TNexcretionrate

ttLW1_y1 _Kg_LW_animal1 _kg_animal1_y1 Horse 15.0 360.0 24.9 Dairycattle 26.0 450.0 59.5 Beefcattle 26.0 400.0 33.6 Sheep,goat 15.0 50.0 5.0 Swine 22.0 119.5 13.9 Hen 9.5 1.4 0.3 Poultry 8.0 3.8 0.7 Rabbit 8.0 3.5 0.2

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wastreatedinthreetreatmentplants(about3000inhabitantequivalents)anddischargedintothe river(Fig.2).

DetaileddescriptionsoftheinstrumentsandmethodsusedcanbefoundinDeGirolamoetal. [10,16,17].

Riverinenitrogenexportestimates

Estimating load, when ﬂow and concentration measurements are not continuous and

simultaneous, is not an easy task. In recent years, several methodologies have been developed [20–22].Tanetal.[23]summarisedthedatarequirementsandapplicabilityofthedifferentmethods. Theysuggested using averaging methods if nosignificant relationship betweenstreamflow and nutrientconcentrationexists.The'Loads'tool[1]providesmonthlyandannualloadcalculationsasa resultof differentmethods.Thetool requiresdailystreamflowdata(continuoustime-series)and discretedailyconcentrationvalues.

Apreliminarycalculationofthedailyequivalentconcentrationwasneededforthosedaysduring whichseveralsamplingswereperformed(ﬂoodevents).Eq.(1)wasusedfortheCelonecatchment, sincethetimeintervalofstream_ﬂowmeasurementswas15min.

DailyL¼0:9X

96 i¼1

qici ð1Þ

,whereDailyListhedailyload(kg)passingthroughtheriversection(L),qiismeasuredstreamﬂow(L) attimeintervalt(1,2, ...96),ciisthemeasuredorlinearly-interpolatedconcentration(mgL1)at

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timet(1,2, ...96),0.9isthetimeinterval(1560=900s,whichincludestheconversionfactor 10001).BydividingDailyLbythedailyvolume,thedailyequivalentconcentrationwasobtained.

FortheCelonecatchment,fourmethods,usingsomeformofaverageinthecalculationoftheloads,

we employed. These are: Method 1 – intersample mean concentration (Eq. (2)); Method 2 –

intersample mean concentration using mean flow (Eq. (3)); Method 3 – linear interpolation of concentration(Eq.(3));andMethod4–concentrationpowercurvefitting(Eq.(4)).Weusedthese methodssincethenumberofsampleswashighthroughouttheyear(100ormore),andthesamples coveredallflowconditions(high,normalandlowflow)[20–22].

InMethod1,theconcentrationvalueswereaveragedtoestimateunsampleddays:

L¼Xn

j¼1

cjþcjþ1

2 Qj ð2Þ

,whereCjisthejth_sample_{concentration}_and_Q

jisthejthﬂow.

Method2assumedthattheaveragedailyconcentrationonnon-sampleddayswasdeterminedbya simplelinearaverageoftheconcentrationsfromthelastsampledataandthenextsampledate.The ﬂowwasassumedtobetheaverageﬂowuptothenextsampledconcentrationvalue.

L_¼X

n j¼1

cjþcjþ1

2 Qjþ1 ð3Þ

,whereCjisthejthsampleconcentrationandQjþ1istheaverageﬂowtotheendofthej+1period.

Method3usedEq.(3),butassumedthattheconcentrationonnon-sampleddayswasdetermined bylinearlyinterpolatingbetweenfortnightlyormonthlysampledconcentrations.

Fig.2.LandcovermapoftheCelonecatchment(CorineLandCover–IVLevel,2011).

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Meanwhile,Method4usedapowerfunction: kX n i¼1 ci n Xn i¼1 qi n¼kcq ð4Þ

,whereciistheithconcentration,whenitexists,andaqibotherwise,abeingacalculatedcoefﬁcient,qi is ith _sampled _discharge ₍_ﬂow), _b _is _the _calculated _power, _c _is _the _average _of _n _{concentration} measurements,qistheaverageofndischargemeasurementsandkisthenumberoftimeintervalsina period.

Thesemethodsprovidedfourdifferentvaluesforthemonthlyandannualloads.Theresultswere similarfortheaveragingmethods(Methods1,2,3;inthecasestudy,beingfrom280ty1and292t y1),whilstMethod4providedalowervalueforload(199ty1).Previousstudieshavedemonstrated thatpowercurvemethods (Method 4)underestimate highconcentrationsand overestimate low values[24].Theaccuracyoftheaveragingmethodsdependsonthenumberofsamplesandonthe timebetweentwosuccessivesamples.Intemporarystreams,datastratiﬁcationcouldbeapplied, basedonthehydrologicalregime,toimprovetheestimation.

Themean,minimumandmaximumannualnitrogenriverineexport(NRE,mean,NRE,min,NRE,max) werecalculatedinordertocalibratetheleaching-runofffractions,andestimatetheuncertainty. Nitrogeninputfrompointsources

Whendataconcerningpointsourcesweremissing,nitrogeninputwasteloads(TNpointsources– NPS)wereestimatedbyusingthefollowingequation:

NPS¼QwCw¼QrCrQuCu ð5Þ

,whereQuistheupstreamflow,Qwisthewastewaterflowrate,Qristheflowratedownstreamofthe source,CuistheupstreamTNconcentration,CwistheconcentrationofthewastewaterandCristhe

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concentrationdownstream.Ifonesamplepermonthiscollected,theﬂowsandconcentrationsare assumedtobethesamethroughoutthemonthasonthedayofsampling.Theequationmustbe appliedtoeachpointsourcedischargingintotherivernet.

Deﬁnitionofland-usesystems

Landuseisthefirstlevelofinformationthatisgenerallyderivedfromalandcovermap.Inthis study,weusedthelandcovermapprovidedbythelocalauthorities(CorineLandCover–IVLevel, 2011),which wasobtainedfromsatelliteimagery(www.sit.puglia.it).Since themaphasaspatial resolutionof1:100,000,anddoesnotallowdistinctionamongarablelandtypes,itwasreclassifiedby crossing data fromagricultural censuses with data from local surveys and field inspections. In particular,theagriculturalcensusprovideddataoncropareasatamunicipalscale.Meanwhile,from localsurveysandfieldinspections,informationoncropirrigationwasobtained.

Figs.2and3showtheinitiallandcovermapalongwiththereclassifiedlandusemapobtainedfor theCelonecatchment(PugliaRegion,SEItaly),respectively.Irrigatedandnon-irrigatedarablelandsof thelandcovermapweredividedamongcrucifers,durumwheat,fieldbean,herbage,legumes,potato, sugarbeet,sunflower,tomato,vegetablecrop,vetchandwinterwheat,asdeducedfrommunicipal agriculturalcensusesandfarmerinterviews.

Inordertoperformasoil-waterbalance,calibratetheleaching-runofffractionand_finallyassess thetotalWFofcatchment-scalecrops,thewatershedwaspreliminarilydividedintoland-usesystems (LUSs),definedasareaswithsimilarlanduse,soilcharacteristicsandprecipitationamounts[25,26]. Therefore,land-usemaps,soilmapsandrainfallzones(Thiessenpolygons)canbeintersectedby meansofspecificGIStools.Previously,soilmapshadtobereclassifiedaccordingtohydrologicalsoil groups(i.e.,A,B,C,D)[27].

Considering the Celone catchment, in addition to the precipitation gauges present in the catchment, all the gauging stations within a 25km buffer were included in the analysis. Thus,

Fig.4. Landusemap,soilmapandrainfallzonesusedforidentifyingLUSswithintheCelonecatchment.

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21precipitationgaugeswereconsidered.Fourrainfallzones,twohydrologicalsoilgroups(C,D)and 24land-useclasseshavebeendistinguished[27](Fig.4).Hence,103LUSswereidentiﬁed(Fig.5). Accountingofthewaterfootprint

TheWFincludesdifferenttypesofwaterconsumption,suchaswatervolumefromrainfall,which evapotranspirates(greenwater), irrigationwatervolume (bluewater)and thewater requiredto assimilatepollution(greywater).

ThetotalWF(m3_t1₎_was_calculated_as_the_sum_of_the_green_(WF

green),blue(WFblue)andgrey (WFgrey)components[28]:

WF¼WFgreenþWFblueþWFgrey ð6Þ

ToperformacompleteWFassessmentofcropproductiononariverbasinscale,itisnecessaryto evaluatetheWFsassociatedwitheachcropgrowingwithinthewatershed.Hydrologicalandwater qualitymodelscanbeusedforestimatingtheWFcomponents,althoughtheseapproachesrequire speciﬁcknowledgeaboutthemodelanddatafortheircalibrationandvalidation[29].

Inthis study,aneasyapproachforestimatingthegreen,blueandgreycomponentsoftheWF assessmentwasperformedbyslightlymodifyingthecalculationframeworkproposedbyFrankeetal. [30]and Hoekstraetal.[28] (Fig.6).Theproposedapproachdoesnotrequire speciﬁcmodelling training.

Acalibrationprocedureaimedatquantifyingthenitrogenexportcoefﬁcients(leachingandrunoff fractions)and thewaterbalancecomponents(runoff),bymeansofobservedsurfacerunoff data, measurednitrogenloadandnitrogenbalanceresults,wasdeveloped.

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Greenwaterfootprint

TheWFgreenwascalculatedastheratioofthevolumeofgreenwaterusedforcropproduction (CWUgreen,m3ha1y1)totheaverageannualcropyield,Y(tha1y1)[28]:

WFgreen¼

CWUgreen

Y ð7Þ

CWUgreenreferstothepartoftheprecipitationthatdoesnotrunofforleach,sinceitistemporarily storedontopofthesoilorvegetationand/orinthesoil.Thiswatercanevaporateortranspirethrough plants,andbeanimportantfactorinagriculturalproduction,especiallyinrain-fedcroplands[31]. A multitude of different empirical formulae or crop models exist to estimate CWUgreen in agriculture[28].Inthisstudy,the‘irrigationscheduleoption’wasused,sinceitismoreaccurate,andis applicabletobothoptimalandwater-stressedgrowingconditions.Accordingtothisprocedure,the CWUgreen of a crop is assumed to be equal tothe crop evapotranspiration under non-standard conditions(alsocalled‘actual’,or‘adjustedcrop’,evapotranspiration),andassumingthatthesoildoes notreceiveanyirrigation(ETc,adj):

CWUgreen¼ETc;adj¼KcET0Ks ð8Þ

,whereKcisthesinglecropcoefﬁcient(dimensionless),ET0isthereferenceevapotranspiration(mm time1)andKsisthestresscoefﬁcient(dimensionless).

Fig.6.WFaccountingmethodology.

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Calculatingevapotranspiration

ThecomputationofETc,adjisgenerallydonefollowingthemethodsandassumptionsprovidedby Allenetal.[32].Atimeintervalof10days(10-d)isconsideredtoprovideagoodrepresentationof hydrologicalprocesses[33].

SinceKcvariesintimeasafunctionofplantgrowthstage,10-d-averagedsinglecropcoefﬁcients (Kc,i)are calculated for each crop in thecatchment from thecropcoefﬁcient curves, which are constructedusinginitialKc(Kc,ini),middleKc(Kc,mid)andendKc(Kc,end).Dataconcerningcropplanting datesand length of croppingseason wereprovided from theabove-mentioned interviewswith farmersandlocaldealers.

ReferringtothecalculationmethodologyadoptedfortheET0estimate(mmd1),thefollowing equation[34]wasappliedtothetemperaturegauges,ifsolarradiation,relativehumidityandwind speeddata,requiredbyothermethods(i.e.,thePenman–Monteithequation),weremissinginthe studyarea[32,35]:

ET0¼0:0023

RA

l

ðTmaxTminÞ0:5ðTmeanþ17:8Þ ð9Þ

,where

l

isthelatentheatofvapourisation(MJkg1),RAistheextraterrestrialsolarradiation(MJm2 d1)and Tmax,Tminand Tmeanarethedailymaximum,minimumand meanairtemperatures (C), respectively.

Daily

l

isobtainedbyapplyingtheHarrisonformula[36]:

l

¼2:50:002Tmean ð10Þ

DailyET0valueswerecalculatedbyapplyingEq.(9),thenappropriatelysummingtheseinorderto obtainvaluesona10-dbasis(ET0,i).

Finally,aGIS-basedinversedistanceweightedmethodwasusedinordertospatiallyinterpolate thepunctualET0,ivaluesintheentirewatershed,consideringa 10-dtime-interval[37,38].Forthe Celonecatchment,inadditiontothetemperaturegaugespresentinthecatchment,allthegauging stationswithina 25kmbufferwereincluded intheanalysis. Thus,13temperaturegauges were considered.

Aftercalculatingthecropevapotranspirationunderstandardconditions(ETc,i=Kc,iET0,i),Kswas evaluatedasfollows[32]:

Ks;i¼

TAWD_r;i1

TAWRAW Dr;i1>RAW K_s;i¼1 D_r;i1RAW 8

<

: ð11Þ

,whereTAW(mm)isthetotalavailablewaterintherootzone,RAW(mm)isthereadilyavailablewater intherootzoneandDr,i-1(mm)istherootzonedepletionatthestartofthe10-dperiodconsidered. Formulae(12)and(13)wereusedtoassessTAWandRAWvalues,respectively:

TAW¼1000ð

u

FC

u

WPÞZr ð12Þ

RAW¼pTAW ð13Þ

,where

u

FCisthewatercontentatﬁeldcapacity(m3m3),

u

WPisthewatercontentatwiltingpoint

(m3_m3_),_Z

ristherootingdepth(m)andpisthesoil-waterdepletionfractionfornostress,thevalues ofwhichhavebeentabulatedbyAllenetal.[32].

The

u

FCand

u

WPdependonthetypeofsoil,andaveragevaluescanbeestimatedwiththesoftware

SoilWaterCharacteristics,implementedbytheUSDAAgriculturalResearchService.Zrisestimated consideringthelowestvaluebetweenthedepthofthesoillayersinthewatershedandthatreported forvariouscropsbyAllenetal.[32].

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Soil-waterbalancecomputation

Lastly,awaterbalancecomputationfortherootzonewasimplementedona10-dbasis,inorderto estimaterootzonedepletionattheend ofthe10-dperiod(Dr,i,mm).Hence,aGISmodelwitha resolutionof20mwasdeveloped.AccordingtoAllenetal.[32],theincoming(irrigation,rainfall)and outgoing(runoff,deeppercolation,evapotranspiration)waterﬂuxintothecroprootzonehavetobe assessed.Watertransferredhorizontallybysubsurfaceﬂowinoroutoftherootzoneisignored. Moreover,ifthegroundwatertableismorethan1mbelowthebottomoftherootzone,theamount ofwatertransportedupwardsbycapillaryactioncanbeassumedtobezero.

Therefore,thefollowingequationforthewaterbalancewasused:

Dr;i¼Dr;i1Pn;iþROiIiþETc;adj;iþDPi ð14Þ

,wherePn,i(mm)isthenetprecipitation,ROi(mm)istherunofffromthesoilsurface,Ii(mm)isthe irrigationdepth,ETc,adj,i(mm)istheactualcropevapotranspirationandDPi(mm)isthewaterlossout oftherootzonebydeeppercolation.Dr,iandDr,i-1canassumevaluesbetween0andTAW.

ThePn,iisdeterminedasfollows:

Pn:i¼Pi0:2ET0;i ð15Þ

,wherePi(mm)isthetotalprecipitationamount.Thiessenpolygonsarebuiltandrainfallzonesare distinguished[25,26]. ETc,adj,i is determined accordingto Eq. (8),whilst Eq. (16) is used for the determinationofDPi:

DPi¼PiROiþIiETcadj;iDr;i1>0 Dr;i¼0

DPi¼0 0Dr;iTAW

ð16Þ TheIivaluesaresettozeroforirrigatedcrops,bothinEqs.(14)and(16),inordertoestimateCWUgreen [28,39].

ROiwasestimatedusingtheSoilConservationServiceCurveNumber(SCS-CN)method[27],which isoneofthemostcommonly-usedmodelsduetoitssimplicityandtherequirementforfewdata [40,41].Thismodelisusedtopredictthedepthofsurfacerunoff(RO,mm)foragivenrainfallevent, andcanbeexpressedasfollows:

RO¼ðP0:2SÞ 2 Pþ0:8S P>0:2S RO¼0 P0:2S 8 < : ð17Þ

Fig.7.Measureddailystreamflow(QG)andsumofbaseflow(BF)andinterflow(IF)intheCelonecatchmentclosingsection.

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,whereSisthepotentialmaximumretentionorinﬁltration(mm)andPisthetotalstormrainfall (mm).Swasevaluatedusingthefollowingequation:

S¼25:4 1000_CN 10

ð18Þ , where CN is the curve number (dimensionless) that ranges from 1 (minimum runoff) to100 (maximumrunoff).Thisparameterwasdeterminedandtabulatedbasedonhydrologicalsoilgroup andsoilcovertype,treatmentandhydrologicalcondition[42].Thetabulatedvalues(CNII)refertothe average antecedent moisturecondition (AMC II). The AMC deﬁnition depends on the total 5-d antecedentrainfall,andtheseasoncategory(dormantorgrowing)thatisdeﬁnedfromdailyaverage temperatures[43].DifferentCNconversionformulae,fromAMCII,todryAMC(AMCI–CNI)andwet AMC(AMCIII–CNIII),havebeenproposed[44].For thiscasestudy,theHawkinsetal.[45] CN conversionformulaewereused.

Insummary,CNIItabulatedvalueswereassociatedwitheachLUSidentifiedinthebasin;AMCwas evaluatedfortheidentifiedrainfallzonesand,wherenecessary,CNIandCNIIIwerecalculated.After that,Eqs.(17)and(18)wereapplied,andtherunoffassociatedwithsingleprecipitationeventswas estimatedforeachLUS.Consideringa10-dtimeinterval,therunoffwasappropriatelyadded,andthe preliminaryROi(mm)wasobtained.Thislattervaluewasthenmodified,followingthecalibration proceduredescribedbelow,andbasedonthecontinuousflowmeasurementsatthegauge.

Thewaterbalancefortherootzone(Eq.(14))wasinitiatedintheﬁrst10-dperiodofareallywet month.Therefore,itwasassumedthat,inthatmonth,therootzonewasnearﬁeldcapacityand,hence, Dr,i-1=0,Ks,i=1andETc,adj,i=ETc,i[46].

Calibratingcurvenumbers

Dailymeanbaseflow(BF,m3_s1_),_daily_mean_inter_flow_(IF,_m3_s1₎_and_total_daily_mean_wastewater discharge(WW,m3_s1₎_were_subtracted_from_the_mean_daily_stream_flow_recorded_at_the_gauge_(Q

G, m3_s1_),_as_follows:

SFG¼QGBFIFWW ð19Þ

,whereSFG(m3 s1)istheestimateddailymeanstormflow,QGisobtainedfromthecontinuous measurementof_flow,andBFandIFcanbeassessedbymeansofthebase_flow_filterprogram(swat. tamu.edu/software/baseflow-filter-program).Fig.7showsthemeasuredstreamflow,thesumofthe dailymeanbaseflowandthedailymeaninterflowintheCelonecatchmentclosingsection.

Volumesofsurfacerunoff(SFG,i,m3)wereestimatedthroughoutthestudyperiod,consideringa 10-dtimestep(i).Basedonthesevalues,theCNsassociatedwitheachLUSwererecalculated,sothatthe sum(m3₎_of _RO

i (PROi, Eq. (17))was equal toSFG,i (Eq.(19), thetargetfunction).To do this, a spreadsheetwasspeciﬁcallycreated,andthetargetfunctionwasset.Finally,calibratedCNvalues wereusedtoestimatetheROi(mm),requiredforthesoil-waterbalance.

ResultsfortheCelonecatchmentcanbefoundinD’Ambrosioetal.[47]. Bluewaterfootprint

The WFblue referstotheconsumption ofgroundwater and/orsurface-waterresourcesthatare utilisedincropproduction(i.e.,irrigationwater)[28].Inotherwords,itistheamountofgroundwater and/orsurfacewaterthatdoesnotreturntothesourceintheformofreturnﬂow,andisdifferentfrom waterwithdrawnforirrigation,insofarasthiswaterisreturnedtowhereitcamefrom.

The WFblue(m3t1)wascalculated bydividingthetotalvolumeof bluewaterused–CWUblue (m3_ha1_y1₎_–_by_the_quantity_of_the_annual_production_–_Y_(t_ha1_y1_):

WFblue¼

CWUblue

Y ð20Þ

TheCWUblue(mmtime1)wascalculatedbyperforminganothersoil-waterbalance(Eq.(9))ona10-d basis,andirrigation(Ii)wasconsidered,asproposedbyHoekstraetal.[28]andappliedbyMekonnen

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andHoekstra[39],deMigueletal.[48],Zhuoetal.[46]andRulliandD’Odorico[49].Iivaluescouldbe deducedfromtheabove-mentionedinterviews.Thefollowingequationwasthenused:

CWUblue¼ETIc6¼0;adjETc;adj ð21Þ

,whereETI_c6¼0_;adjistheadjustedcropevapotranspiration,estimatedbymeansofthesameprocedure appliedforETc,adjevaluation(Eq.(8)),butconsideringalsoIiinEqs.(14)and(16).Inthecaseofrain-fed crops,CWUblueiszero.

Greywaterfootprint

TheWFgreyreferstothevolumeofwaterneededtodilutealoadofpollutantsdischargedintothe naturalwaterbodyinsuchawaythatthequalityofthereceivingwatersystemisnotcompromised, withrespecttospeciﬁcqualitystandardsandnaturalbackgroundconcentrations[6,28].Inthisstudy, theWFgreyrelatedtonitrogenusewasquantiﬁed,thusexcludingtheeffectsofothernutrientsand fertilisers.Hence,theintensityofwaterpollutioncausedbyagriculturalactivitiesand,inparticular,by theTNapplicationrate,wasmeasured.

TheWFgrey(m3t1)wascalculatedbydividingthedilutionwaterrequirement,CWUgrey(m3ha1 y1),bythecropyield,Y(tha1y1)[28]:

WFgrey¼CWUgrey

Y ð22Þ

TheCWUgrey(mmy1)was calculated bymultiplyingthefractionofTN thatleaches or runsoff (leaching-runofffraction–α)bytheTNapplicationrate(AR,kgha1y1),anddividingthisbythe differencebetweenthemaximum(Cmax)andnatural(Cnat)concentration(mgl1)ofTNinfreshwater:

CWUgrey¼

a

AR

CmaxCnat ð23Þ

TheARwas estimatedfor each LUS,basedontheabove-mentioned interviews.Meanwhile,a calibrationprocedurewasdeﬁnedinthisstudyinordertodivideαbetweenleaching(αL)andrunoff (αR), as follows. Finally, CWUgrey was estimated by summing the values associated with runoff (CWUgrey,R)andleaching(CWUgrey,L).

Calibratingtherunoffandleachingnitrogenfraction

Inmostofthepreviousstudies,αhasbeensetataconstantvalueof10%[39,46,50]or7%[51].In contrasttotheuseofastatic_αthroughoutthewatershed,theproceduresuggestedbyFrankeetal. [30],andappliedbyBrueckandLammel[52],Munroetal.[53]andGiletal.[54],waspreliminarily usedinthis study.Thisapproachconsidersthat αdepends onpotentialfactors– (j)– whichare atmosphericinput(TNdeposition),soiltype(textureandnaturaldrainage),climate(precipitation) andagriculturalpractice(TNﬁxation,applicationrate,plantuptakeandmanagementpractice).Theα valueswerecalculatedforeachLUS(k),usingthefollowingequation:

a

k¼

a

minþ P jsj;kwj;k P jwj;k " # ð

a

max

a

minÞ ð24Þ

,whereαministheminimumleachingrunofffraction(0.01),αmaxisthemaximumleachingrunoff fraction(0.25),sj,kisthescorefortheabove-mentionedpotentialfactor,j,associatedwiththeLUSk, andwj,kistheweightofthefactorjassociatedwithk.

Frankeet al.[30] providedspecificcriteriaused toscore (s) and weight(w) allthedifferent influencingfactors(j).Unlikeinpreviousstudies,theproceduresuggestedbyFrankeetal.[30]was slightlymodi_fiedinthisstudy,and_αkwasdividedbetweenleaching(αL,k)andrunoff(αR,k).Then,azero weight(wj,k)wasassignedtofactorsspecificallyrelatedtorunoff(i.e.,textureandnaturaldrainage relevanttorunoff)andleaching(i.e.,textureandnaturaldrainagerelevanttoleaching),respectively.

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Atthewatershedclosingsection,TNrunoff(R,kgy1)andTNinsoilandleaching(L,kgy1)were estimatedusingEqs.(25)and(26):

R¼X n k¼1

a

R;kARkAk ð25Þ L¼Xn k¼1

a

L;kARkAk ð26Þ

,where nisthenumberofLUSsidentiﬁedwithinthewatershed,αR,k andαL,karetherunoffand leachingfractionassociatedwiththeLUSk,ARk(kgha1y1)istheapplicationrateassociatedwith theLUSkandAk(ha)isthesurfaceoftheLUSk.

Followingthis,αL,kandαR,kwererecalculated,followingacalibrationprocedurebasedonthefield measurements[55].Thus,R(Eq.(25))andL(Eq.(26))wereequalisedtoTNrunoff(RM,Eq.(27))andTN insoilandleaching(LM,Eq.(28))estimatedfromfieldmeasurements.Hence,thevaluesofαR,kandαL,k weremultipliedbyanappropriateconstantfactor.Aspreadsheetwasspecificallycreatedinorderto setthetargetfunctionandobtaintheconstantfactor.

RM¼NRENBFNADNPS NNAT ð27Þ

LM¼

D

ðNRENPSNNATÞNBF; soilDNAD; soilD ð28Þ

,whereNRE(kgy1)istheannualTNriverineexport,NBF(kgy1)istheTNbiologicalﬁxation,NAD(kg y1)istheTNatmosphericdeposition,NPS(kgy1)istheTNinwastewater,NNAT(kgy1)istheTN naturallypresentintheriver,

D

(kgy1)isthedifferencebetweenTNinput(NSF,NAF,NBF,NAD)and output(cropuptake–NCU,NH3volatilisation–NVanddenitriﬁcationinsoil–ND)inthestudyarea. Moreover,NBF,soilDandNAD,soilDareNBFandNAD,respectively,associatedwithsoilofhydrologicalgroup D,whereinﬁltrationdoesnotoccur.

NNATwasassessedbymultiplyingCnatforthetotaldischarge,QTOT(m3y1),measuredatthegauge, andNPSwas determined, asdescribed in thesection above.Meanwhile,

D

was obtainedfroma nitrogenbalance[10,56,57].Inparticular,fortheCelonecatchment,NBF(64,891kgy1),NAD(39,744kg y1)and

D

(306,397kgy1)valuesarereportedinDeGirolamoetal.[10].

ThevaluesofLMweresettobegreaterthanzero.IftheuncertaintyintheWFgreyestimaterelatedto αvariabilitywasassessed,themean,minimumandmaximumannualnitrogenriverineexport(NRE, mean,NRE,min,NRE,max)wereconsideredasNREinEqs.(27)and(28).

ResultsfortheCelonecatchmentcanbefoundinD’Ambrosioetal.[47].

MaximumandnaturalTNconcentrationsinsurfaceandgroundwater

RegardingtheCmaxvalueinEq.(23),despitethattheideaofmeasuringwaterpollutionintermsof theamountofwaterneededtodilutepollutantscanbetracedbacktoFalkenmarkandLindh[58],and wascontinuedbyPosteletal.[59]andChapagainetal.[50],stilltodaythereareuncertaintiesrelated to the standardisation of water-quality standards that should be used for a consistent WFgrey assessment,takingintoaccountthediverseambientwaterqualityandaquaticecosystems,aswellas thepresence of several pollutants in water-bodies[6]. Generally, WFgrey assessments haveused drinking-waterstandards.Regardlessof thefact that thisvalueis referred toa surface-wateror groundwaterbody,theUSEPA(10mgN-NO3l1)ortheEuropeanUnion/WorldHealthOrganization (50mgNO3l1,i.e.,11.3mgN-NO3l1)nitrogenstandardsfordrinking-waterarethemostcommonly usedwater-qualitystandards[39,50,51,60–62].Also,50mgNO3l1isthemaximumconcentration permittedbytheEUNitrateDirectiveingroundwater[63].Intheliterature,onlyafewstudieshave used ambient water-quality standards [46,64,65]. In Italy, the Decree of the Ministry of the Environment n. 260/2010 [66] identiﬁes, among various physicochemical factors, the threshold

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concentrationsofNH4,NO3andNO2thatarerequiredtosupportafunctioningecosystem.Concerning groundwater,agoodchemicalstatusisreachediftheconcentrationsofNH4,NO3andNO2arelower than0.5mgl1(i.e.,0.4mgN-NH4l1),50mgl1and0.5mgl1(i.e.,0.1mgN-NO2l1),respectively. Meanwhile,thethresholdvaluesassociatedwiththegoodwater-qualitystatusofa surface-water bodyforN-NH4andN-NO3are0.06and1.2mgl1,respectively.Currently,Italianlegislationdoesnot provideambientqualitythresholdsforTNineithersurfacewaterorgroundwater.FollowingLiuetal. [6],theTNambientwater-qualitystandard(good)adoptedforCelonecatchmentsurfacewateris 3mgl1.Meanwhile,thestandardadoptedforgroundwateris4.6mgl1[67].

RegardingtheCnatvalueinEq.(23),manypreviousstudieshaveconsideredthisvaluetobeequalto zero,duetoalackofdata[49,50,61,63,68];however,suchanassumptionleadstoanunderestimation ofCWUgreybecauseCnatisgenerallyhigherthanzero.FortheCelonecatchment,sincelocaldataarenot available,theCnatofTNwasset0.4mgNl1inbothriverwaterandgroundwater,asrecommendedby Frankeetal.[30],andusedbyMekonnenandHoekstra[69]andLiuetal.[6].

Limitationsofthestudy

Themainlimitationsoftheprocedureadoptedinthisstudyforthecalibrationofrunoffandthe nitrogenleachingrunofffractionare[47]:

theSCS-CNmethodwasusedbeyonditsoriginalscope,sinceitwasnotappliedconsideringasingle stormevent,butthesumofstormeventsthathappenedina10-dperiod.Inaddition,smalleventsthat producenorunoffwerenotexcluded.TheselimitationscanleadtoanoverestimationofCNIIvalues; thelimitedtimeperiodanalysed(1year),withwetterthanaverageconditions,couldhavegreatly in_ﬂuenced the outcomes, especially theWFgreythat could haveresulted in being higher than average.AnaverageovermultipleyearswouldbemoreappropriateforrepresentingtheWFandthe generalstatusofwaterscarcity;

thediscretisationofthewatershedintoLUSs(basedonlanduse,soiltypeandThiessenpolygons) adoptedinthisstudyleavesoutlocalfactors,suchasslope,rainfallintensityandriverdistance.The latter factors inﬂuence hydrological processes and the leaching and runoff fraction, hence, neglectingthemcouldleadtoanoverestimateorunderestimateofthesevariables;

thehighfragmentationoflanduse,andthedifferentmanagementpracticesadoptedwithinthe catchment,makestheassignmentofactualagriculturalpracticestoeachﬁeldimpossible,hence, theagriculturalpracticesusedinthecalculations(i.e.,fertiliseramount,cropyield)canbeaffected bycertainuncertainty;

TNaccumulationanddegradationprocessesinthereceivingwater-bodieswereneglectedintheTN loadcalculations,whilstbiochemicalprocessescanberelevant,especiallyintemporaryrivers; thein-streammonitoringofTNconcentrationprogram(i.e.,numberofsamples,timebetweentwo

successivesamples,hydrologicalconditions),aswellasthemethodusedforestimatingload,havea greatinfluenceonloadestimationthatresultsinalargeuncertaintyintherunoffandleaching nitrogenfractionestimation.AstandardprocedureisneededforfixingCmaxandCnat.Maximum allowableconcentrationsfixedonstandardsfordrinking-waterleadtoanunderestimationofgrey water,aswellasanaturalbackgroundfixedasequaltozero.

Funding

MonitoringactivitieswerefundedbytheMIRAGEProject(contract211735,7thEUFramework Programme2007–2011).

Acknowledgments

TheauthorsgratefullyacknowledgeGiuseppeAmorusoandSimonaLoconsolefromtheApulia CivilProtectionService,FrancescoSpinellifromtheNationalAgencyforNewTechnologies,Energyand SustainableEconomicDevelopment(ENEA),MauroBiaforeandMatteoGentilellafromtheCampania

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Region for providing climatic data. Thanks are also due to several local citizens who provided informationanddataaboutthemanagementpracticesandtotheagronomistDr.GiuseppeDeVitafor supervising thesedata. Lastly, the authorsare indebted to fouranonymous Reviewers for their scientiﬁccommentsandrecommendations.

AppendixA.Glossary

Abbreviation Description Unitofmeasure

TN TotalNitrogen –

Ak SurfaceoftheLandUseSystemk ha

AR TNapplicationrate kgha1_y1

ARk TNapplicationrateassociatedwiththeLandUseSystemk kgha1y1

BF Dailymeanbaseﬂow m3

s1

Cmax MaximumconcentrationofTNinthewaterbodies mgl1

CN Curvenumber dimensionless

Cnat NaturalconcentrationofTNinthewaterbodies mgl1

CWUblue Bluecropwateruse m3ha1y1(mm

time1)

CWUgreen Greencropwateruse m3ha1y1(mm

time1)

CWUgrey Dilutionwaterrequirement m3ha1y1(mm

time1) CWUgrey,L Dilutionwaterrequirement(leaching) m3ha1y1(mm

time1₎

CWUgrey,R Dilutionwaterrequirement(runoff) m3ha1y1(mm

time1) DPi Waterlossoutoftherootzonebydeeppercolationattheendofthe10-dperiod mm(10-d)1

Dr,i Rootzonedepletionattheendofthe10-dperiod mm(10-d)1

Dr,i-1 Rootzonedepletionatthestartofthe10-dperiod mm(10-d)1

ET0 Referenceevapotranspiration mmtime1

ET0,i 10-dreferenceevapotranspiration mm(10-d)1

ETc,adj Actual(oradjusted)cropevapotranspirationassumingthatthesoildoesnotreceive

anyirrigation

mmtime1 ETc,adj,i Actualcropevapotranspirationattheendofthe10-dperiodassumingthatthesoil

doesnotreceiveanyirrigation

mm(10-d)1 ETc,adj,iI6¼0 Actualcropevapotranspirationattheendofthe10-dperiodconsideringirrigation mm(10-d)1

ETc,i 10-dcropevapotranspirationunderstandardconditions mm(10-d)1

IF Dailymeaninterﬂow m3

s1

Ii Irrigationdepthattheendofthe10-dperiod mm(10-d)1

Kc Singlecropcoefﬁcient dimensionless

Kc,end Endsinglecropcoefﬁcient dimensionless

Kc,i 10-daveragesinglecropcoefﬁcient dimensionless

Kc,ini Initialsinglecropcoefﬁcient dimensionless

Kc,mid Middlesinglecropcoefﬁcient dimensionless

Ks Stresscoefﬁcient dimensionless

Ks,i 10-dstresscoefﬁcient dimensionless

L TNinsoilandleachingcalculatedwithEq.(26) kgy1

LM TNinsoilandleachingestimatedforthestudyareawithEq.(28) kgy1

NAD TNatmosphericdeposition kgy1

NAD,soilD TNatmosphericdepositionassociatedwithsoilD kgy1

NAF TNinanimalmanure kgy-1

NBF TNbiologicalﬁxation kgy1

NBF,soilD TNbiologicalﬁxationassociatedwithsoilD kgy1

NCU TNcropuptake kgy1

NNAT TNnaturallypresentintheriver kgy1

NPS TNpointsources kgy1

NRE TNriverineexport(NRE,mean;NRE,min;NRE,max) kgy1

NRE,max AnnualmaximumTNriverineexport kgy1

NRE,mean AnnualmeanTNriverineexport kgy1

NRE,min Annualminimumnitrogenriverineexport kgy1

NSF TNinsyntheticfertilisers kgy1

NV NH3volatilisation kgy1

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(Continued)

Abbreviation Description Unitofmeasure

P Totalstormrainfall mmtime1

Pi Totalprecipitationamountattheendofthe10-dperiod mm(10-d)1

Pn,i Netprecipitationattheendofthe10-dperiod mm(10-d)1

QG Meandailystreamﬂowrecordedatthegauge m3s1

QTOT Totaldischargemeasuredatthegauge m3y1

R TNrunoffcalculatedatthewatershedclosingsectionwithEq.(25) kgy1

RA Dailyextraterrestrialsolarradiation MJm2d-1

RAW Readilyavailablewaterintherootzone mm

RM TNrunoffestimatedatthewatershedclosingsectionwithEq.(27) kgy1

ROi Runofffromthesoilsurfaceattheendofthe10-dperiod mm

S Potentialmaximumretentionorinﬁltration mm

SFG Estimateddailymeanstormﬂow m3s1

SFG,i Volumesofsurfacerunoffattheendofthe10-dperiod m3(10-d)1

sj,k Scoreforthepotentialfactorthatinﬂuenceleachingandrunoff(j)associatedwith

theLandUseSystemk

dimensionless

TAW totalavailablewaterintherootzone mm

Tmax Dailymaximumairtemperature C

Tmean Dailymeanairtemperatures C

Tmin Dailyminimumairtemperature C

WF Totalwaterfootprint m3

t1

WFblue Bluewaterfootprint m3t1

WFgreen Greenwaterfootprint m3t1

WFgrey Greywaterfootprint m3t1

wj,k WeightofthepotentialfactorthatinﬂuenceTNleachingandrunoff(j)associated

withtheLandUseSystemk

dimensionless

WW Totaldailymeanwastewatertreatmentplant(WWTP)discharge m3

s1

Y Averageannualcropyieldproduced tha1y1

Zr Rootingdepth m

α Leaching-runofffraction dimensionless

αk αvaluescalculatedforeachLandUseSystemk dimensionless

αL Leachingfraction dimensionless

αL,k LeachingfractionassociatedwiththeLandUseSystemk dimensionless

αmax Maximumleaching-runofffraction dimensionless

αmin Minimumleaching-runofffraction dimensionless

αR Runofffraction dimensionless

αR,k RunofffractionassociatedwiththeLandUseSystemk dimensionless

D DifferencebetweenTNinputandTNoutput kgy1

uFC Watercontentatﬁeldcapacity m3m3

uWP Watercontentatwiltingpoint m3m3

l Latentheatofvaporisation MJkg1

AppendixB.Supplementarydata

Supplementarymaterialrelatedtothisarticlecanbefound,intheonlineversion,atdoi:https://doi. org/10.1016/j.mex.2018.10.003.

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