Predicting soil water and mineral nitrogen contents with the STICS model for estimating nitrate leaching under agricultural fields

To link to this article:

DOI:10.1016/j.agwat.2012.01.007

http://dx.doi.org/10.1016/j.agwat.2012.01.007

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Eprints ID: 5702

To cite this version: Jégo, G. and Sanchez-Pérez, José-Miguel and Justes, Eric

Predicting soil water and mineral nitrogen contents with the STICS model for

estimating nitrate leaching under agricultural fields. (2012) Agricultural Water

Management, vol. 107 . pp. 54-65. ISSN 0378-3774

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Predicting

soil

water

and

mineral

nitrogen

contents

with

the

STICS

model

for

estimating

nitrate

leaching

under

agricultural

fields

G.

Jégo

_,

_J.M.

_{Sánchez-Pérez}

_,

_E.

_Justes

a_{UniversitédeToulouse,LaboratoireÉcologieFonctionnelleetEnvironnement(ECOLAB),ÉcoleNationaleSupérieureAgronomiquedeToulouse(ENSAT),avenuedel’Agrobiopole,BP} 32607,AuzevilleTolosane,31326Castanet-TolosanCedex,France

b_{INRA,UMRAGIR(AgrosystèmesetAgricultures,Gestionderessources,InnovationetRuralité),INRA-INP-ENSAT,BP52627,31326Castanet-TolosanCedex,France}

c_{CNRS,LaboratoireÉcologieFonctionnelleetEnvironnement(ECOLAB),ÉcoleNationaleSupérieureAgronomiquedeToulouse(ENSAT),avenuedel’Agrobiopole,BP32607,Auzeville} Tolosane,31326Castanet-TolosanCedex,France

a

r

t

i

c

l

e

i

n

f

o

Keywords: Soilwatercontent Soilnitratecontent Simulateddrainage Simulatednitrateleaching STICSmodel

Agriculturalpractices Alluvialplain Groundwater

a

b

s

t

r

a

c

t

TheperformanceoftheSTICSsoil-cropmodelforthedynamicpredictionofsoilwatercontent(SWC)and soilmineralnitrogen(SMN)intherootzone(120cm)ofsevenagriculturalfieldswasevaluatedusing fieldmeasurementsinacoarse-grainedalluvialaquiferoftheGaronneRiverfloodplain(southwestern France)from2005to2007.TheSTICSmodelwasusedtosimulatedrainageandnitrateconcentration indrainagewaterinalltheagriculturalfieldsofthestudyarea,inordertoquantifyandassessthe temporalandspatialvariabilityofnitrateleachingintogroundwater.SimulationsofSWCandSMNin thesevenmonitoredfieldswerefoundtobesatisfactoryasindicatedbyrootmeansquareerror(RMSE) andmodelefficiencybeing6.8and0.84%forSWCand22.8and0.92%forSMN,respectively.Onaverage, SWCwasslightlyoverestimatedbyameandifferenceof10mm(3%)andtherewasalmostnobiasin SMNestimations(<0.5%).ThesesatisfactoryresultsdemonstratethepotentialforusingtheSTICSmodel toaccuratelysimulatenitrateleaching.

Acrossthestudyarea,simulateddrainageandnitrateconcentrationwereextremelyvariablefromone fieldtoanother.Forsomefields,simulatedmeanannualnitrateconcentrationindrainagewaterexceeded 300mgNO3−L−1andpredictednitrateleachingwascloseto100kgNha−1,whileotherfieldshadvery lownitratelosses.About15%ofthefarmers’fieldswereresponsiblefor60–70%ofnitrateleaching.The SMNinlateautumn,beforewinterdrainage,wasfoundthemaindeterminingfactorexplainingthis variability.Thissituationmaybeattributedtounsatisfactorycumulativenitrogenmanagementoverthe mediumterm.Ineffectivenitrogenmanagementwasfoundtobemoredetrimentalthanasingleannual incidentofoverfertilization,particularlyinsituationsofdeepsoilsandincasesofloworhighlyvariable drainagebetweenyears.

1. Introduction

The EuropeanWater Framework aims to achieve long-term sustainablewatermanagementfor bothsurfaceand groundwa-terbodies. Thefirst stepof thisframework is toachieve “good status”forallwatersby2015.Onecomponentofgoodstatusis thenitrateconcentrationinbothsurfacewaterandgroundwater. Intensiveagriculturehascontributedtoanincreaseinnitratelevels inmany areas ofEurope(Strebelet al.,1989).Alluvial ground-waterisparticularlyvulnerabletonitrate(NO3−)leachingdueto

∗ Correspondingauthor.Tel.:+330534323920;fax:+330534323955. E-mail addresses: jose-miguel.sanchez-perez@univ-tlse3.fr, sanchez@cict.fr

(J.M.Sánchez-Pérez).

1 _{Presentaddress:AgricultureandAgri-FoodCanada,SoilsandCropsResearch} andDevelopmentCentre,2560boulevardHochelaga,Quebec,QC,G1V2J3Canada.

nitrogen(N)lossesfromagriculturalsoils,sinceagriculturallandis characterizedbythepresenceofshallowgroundwaterandfertile soilssuitableforfarming.Severalstudieshaveshownthatnitrate leachingthroughunsaturatedsoilcanhaveanimportantimpacton groundwaterpollution(Gustafson,1983;Bijay-Singhetal.,1995; Arrateetal.,1996;Sánchez-Pérezetal.,2003c).However,the rela-tionshipbetweengroundwaterNO3−concentrationandNsources usedatthesoilsurfaceiscomplex.

Previousstudieshaveprovedthatcropmodelspresent poten-tialforquantifyingtheimpactofagriculturalactivitiesonnitrate leachingintogroundwater(WagenetandHutson,1996;Loagueand Corwin,1996;HoffmannandJohnson,1999).First,theyareableto simulatecomplexprocessesandcalculatevariablesthatare diffi-culttomeasure.SeveralimportantsourcesofNinagriculturalsoils, suchasmineralizationfromorganicmatterornitrogen-richcrop residues(e.g.,legumes),fertilizeroratmosphericdeposition,can beconvertedtoNO3−andincorporatedintogroundwaterrecharge

Fig.1. Mapofthestudyareashowing(a)thelocationofthestudyarea,(b)thefloodplainlimit,thefoursoiltypesdefinedandthepiezometerlocations,and(c)2006and (d)2007landuseandlocationsofthemonitoredfields(indicatedbynumbers).

(Böhlke,2002).Thatiswhysoil-cropmodels,validatedusinginsitu measurablevariables,suchassoilwatercontent(SWC)andsoil mineralnitrogen(SMN)content,areusefulforquantifyingnitrate leachinginagriculturalareas.

Anotheradvantageofcropmodelsistheirabilitytosimulate thecroprotationpatternandthefallowperiodbetweentwomain cropsoverseveralyears.Thisiscriticalforstudyingnitrate leach-ing becausethe temporal dynamics of this process are greatly influencedbythestatusofthecropandclimaticvariations.This temporalaspectisalsousefulforpredictingthemitigationeffects ofimprovedagriculturalpractices,suchasoptimizedNfertilizer applicationsandcatchcropestablishment,onsoilandwaterstatus. IftheSMNlevelatharvestishighandnonewcropissown imme-diately,theuseofacatchcropisanefficientwaytoreducenitrate leachingduringfallowperiods(seereviewbyThorup-Kristensen etal.,2003).However,theeffectsofanycatchcropshouldbe eval-uatedoverthelongtermratherthanjusttheshortterm(Berntsen etal.,2006).

Manymodels suchasCropEnvironment REsource Synthesis (CERES)(RitchieandOtter,1984;JonesandKiniry,1986),Erosion ProductivityIntegratedCalculator(EPIC)(Williamsetal.,1989)and SimulateurmulTIdisciplinairepourlesCulturesStandard(STICS) (Brissonetal.,1998)areabletosimulatecropgrowthandwater andnitrogenbalancesatfieldscale.However,thepredictive qual-ityofthesemodelshasbeenevaluatedmainlyonthebasisofannual experimentsand/orexperimentalconditions.Theirabilityto pre-dictwater and nitrogenleaching over 2–3years in “real” farm conditions,whichmaydifferfromtheagriculturalpracticesapplied onexperimentalsites,needstobemorewidelyevaluatedbefore theyareusedtosimulateexantescenariosofcroppingsystems (Beaudoinetal.,2008).Onepossibilityistocomparetemporal sim-ulatedandmeasuredsoilwaterandmineralnitrogenintherooting zoneinordertoevaluatetheabilityofthemodeltosimulatethe

nitrogencycleandwaterandnitratemovementsintheunsaturated zoneofthesoiltowardthegroundwater.

Theaimofthisstudywastoanalyzeandquantifywhenand where nitrateleaching occurs in an alluvialfloodplain, using a dynamicsoil-cropmodel.Theobjectivesofourworkweretwofold: (1)toevaluatethepredictivequalityofthedynamicSTICS soil-cropmodelforsimulatingsoilwaterandmineral-Ncontentsover threesuccessiveannualperiodsincomparisonwithfield measure-ments;(2)toanalyzeandquantifytheimpactofcropsequenceand theeffectofinitialsoilmineralcontentonsimulatedspatialand temporalnitrateleaching.Theworkwascarriedoutinfarmfields locatedinthealluvialfloodplain,inwhichconventionalagricultural practicesareapplied.

2. Materialsandmethods

2.1. Studyarea

ThestudysiteislocatedinameanderoftheGaronneRiverat Monbéqui insouthwesternFrance(43◦5330N,1◦1300E).The area extends over approximately 12km2_{, with 50 agricultural} fields,mostofwhichareusedforcrops,makingupabout75%of thetotalarea(Fig.1).

The alluvialplain of theGaronne River comprises a succes-sionofterraces.Analluvialaquiferissituatedinthefirstterrace, whichiscomposedofcoarsealluvium.Thefirst50–100mfrom theriverbankare coveredby riparianforest andpoplar planta-tions, beyondwhich lies agricultural land. The alluvial aquifer comprises a layer, about 6–7m thick, overlying impermeable andinduratemarl.Previousmeasurementsofnitrate concentra-tioninthisaquifershowedconsiderablespatialvariabilityovera shortdistance.Themeasurednitrateconcentrationinthe ground-water (see Fig. 1 for piezometers location) varies widely from

Table1

Climaticdata(rainfall,minimumandmaximumtemperatureandcumulativesolarradiation)recordedfromNovember2004toOctober2007.

Period Rainfall(mm) MeanTmin(◦C) MeanTmax(◦C) Cumulativesolar

radiation(MJm−2)

1/1/04–30/11/05 501 8.7 17.7 4861

1/12/05–31/10/06 644 8.5 20.2 4896

1/11/06–31/10/07 600 8.7 19.0 4971

10 to 90mgNO3L−1, whereas in theriver it varies from10 to 20mgNO3L−1(Sánchez-Pérezetal.,2003b).Interactionsbetween

theriverand thegroundwatercouldexplainpartofthespatial distributionofnitrateconcentrations.Indeed, dilutionand den-itrificationprocessescouldexplainthelowgroundwaternitrate concentration(∼10mgNO3L−1)observedin thealluvialaquifer alongtheriverbank(Sánchez-Pérezetal.,2003a;Iribaretal.,2008). Infact,thereare“hotspots”ofdenitrificationintheaquiferareathat areregularlysubjectedtomixingofriverwaterandaquiferwater (McClainetal.,2003;Sánchez-Pérezetal.,2003a;Iribaretal.,2008). Inaddition,inthisareathenitrateconcentrationsingroundwater aredilutedbytheriverwater(Wengetal.,2003;Peyrardetal., 2008).However,therearealsolargespatialvariationsin ground-waternitrateconcentrationinsidethealluvialaquiferunderlying agriculturalland,wheretheinfluenceofriverwaterisverylow.

Themaincropsinthestudyareaarewheatandmaize, with lessimportantcropsbeingpeas,sorghum,soybean,rapeseedand sunflower.Melonsandvetch(greenmanure)arealsogrown occa-sionally.Someofthemaizeandwheatfieldswerebeingusedto evaluatenewcultivarsinlargetrialscarriedoutbyseed compa-nies.Poplarplantationsrepresentedabout15%ofthetotal area andwerelocatedneartheriver.Therestoftheareawascovered bybuildings(5%)andriparianforest(5%).

Meanannualprecipitationinthestudyareaisabout660mm (1994–2007).MeteorologicaldatafortheperiodfromDecember 2005toOctober2007werecollectedonthesiteusinganautomatic meteorologicalstation(Table1).FromJanuary2005toDecember 2005,precipitationdatawereobtainedfromtheMonbéqui meteo-rologicalstation(MeteoFrance),located1kmfromthestudysite. Data ontemperature, wind, humidity and solarradiation were obtained from Toulouse-Blagnac meteorological station (Meteo France),located50kmfromthesite.Forthethreecropsequences onthemonitoredfields,the2004–2005periodwasthedriestand the2005–2006periodthewettest.Themeanminimum temper-atureandthemeandailysolarradiationwerealmostthesame forallthreecroppingperiods.Totalannualrainfallwas501mm forthe2004–2005period,644mmforthe2005–2006periodand 600mmforthe2006–2007period.Seasonalprecipitation distri-butionshowsthatprecipitationtendstobelowerinwinterthan inspring,summerandautumn.Insummer,showersandstorms cangenerateshort,intenseprecipitationevents(ca.30mmday−1).

Duringthestudyperiod,thegroundwaterlevelvariedbetween2.5 and5mbelowthesoilsurfaceandthegroundwaterdidnotinteract withtherootsystemsofarablecrops.

2.2. Experimentaldesign

2.2.1. Monitoredfieldsandfield-scalemodeling

Soilscoreswerecollectedfrom25fields(includingseven mon-itoredfields)inordertodeterminesoilcharacteristics,i.e.,texture, organicmatter,pH,totalcarbonates(Table2).Therewasatexture gradientfromtheriverbanktotheendofthefirstterraceranging fromsandyloamtosiltyclayloamtexture.Thisgradientwas par-ticularlypronouncedneartheriverbank,wherethereareriparian forestsandpoplarplantations.Thesoilcharacteristicsofthe agri-culturalfieldswerefairlyhomogenous.Fromthesoilanalysis,four classesofsoilsweredistinguished(Fig.1).Soil1wassituatednear theGaronneriverbank,itstexturewasloamy,anditcontaineda highpercentageoflimestone.Soil2,situatedalittlefartherfrom theriverbed,wasasiltyloam,andcontainedlesssandandmoresilt thansoil1.Soils3and4weresiltyclayloams,butsoil3contained lesssandandCaCO3thansoil4,anditspHwaslower.

A groupof seven fields wasmonitoredfrom February 2005 (fields1,6,and 10)orDecember2005(fields2,3,5,and 8)to October2007.Thesefieldswerearepresentativesampleofallmain cropsandsoiltypesatthesite.Theyincludedsixagriculturalfields (1,2,3,6,8,and10)andafallowfield(5),occasionallygrazed,with nocroppingormineral-Nfertilizer,whichwasusedasthecontrol representingminimumNleachingundertheprevailing pedocli-maticconditions(Fig.1b).Thecropsequencesandthequantityof Nfertilizerandirrigationwaterappliedtoeachofthemonitored agriculturalfieldsarereportedinTable3.Onlymaizeandsorghum wereirrigated.Peaandsoybeanweregenerallynotfertilized.One wheatfieldwasnotfertilizedin2006,becausethesamplingzone waslocatedinanunfertilizedareaofawheattrial.Sunfloweris usuallynotfertilizedwithNbecauseithaslowNrequirements anditsNneedsaremetbyahighlevelofsoilNmineralizationin springandsummer.

Foreachfield,soilcoreswereextractedon7–13samplingdates, fromFebruary2005toNovember2007(seeFig.1).Thesoilcores werecollectedtoadepthof1.2musinganautomaticsoilcorer. Inordertotakeintra-fieldvariabilityintoaccount,between6and

Table2

Soilpropertiesofthefoursoilsidentifiedinthestudyarea.

Soil1 Soil2 Soil3 Soil4

Depth(cm) 0–30 30–120 0–30 30–120 0–30 30–120 0–30 30–120 Sand(%) 36 38 30 28 12 10 20 23 Silt(%) 44 44 52 50 59 52 51 48 Clay(%) 20 18 18 22 29 38 29 29 pH 8.2 8.4 8 8.3 7.3 7.5 8.5 8.3 CaCO3(%) 6.7 7.6 1.7 2.8 0.1 0.1 2 2.6 Organic-C(gkg−1_{) 10 5 9 6 12 8 12 8} Organic-N(gkg−1_{) 0.9 0.4 0.8 0.5 1.0 0.6 1.0 0.6}

Fieldcapacity(wateringg−1_{ofsoil) 22.6 15.7 21.6 20.9 24.2 23.1 23.0 22.0}

Field Croprotation 2005 2006 2007 Crop Fertilization (kgNha−1₎ Irrigation (mm) Crop Fertilization (kgNha−1₎ Irrigation (mm) Crop Fertilization (kgNha−1₎ Irrigation (mm)

1 Soybean 0 0 Winterpea 0 0 Maize 150 175

2 Maize 95 140 Wheat 140 0

3 Sorghum 220 80 Wheat 108 0

5 Fallow 0 0 Fallow 0 0

6 Springpea 0 0 Wheat 0 0 Rapeseed 178 0

8 Soybean 80 0 Soybean 50 0

10 Sunflower 0 0 Wheat 134 0 Soybean 40 0

10cores,dependingonthesizeofthefield,weretakenfromeach fieldoneachsamplingdate.Eachsamplewasfirstdividedintofour layersof30cmandthenmixedbetweenthe6and10coreslayerby layerbeforeanalysis.Thefirst30cmcorrespondedtotheplowed horizon;theotherlayersdidnotcorrespondstrictlyto pedologi-calhorizonsbutwereselectedtoevaluatethecapacityoftheSTICS soil-cropmodeltosimulatewaterandnitratemovementinsidethe soilprofile.Thecoreswerehomogenizedandmoisturecontentwas measuredafterdryingat105◦Cfor24h.Sampleswereextracted with1molL−1KClsolutionper100goffreshsoil,andnitrateand ammoniumcontentsweremeasuredbycontinuousflow colorime-try(autoanalyzer,SkalarAnalytical).

Soilmoistureat fieldcapacity andatwiltingpoint was esti-matedfromgravimetricinsitusoilmeasurements.Fieldcapacity ofeach30cmlayerwasestimatedfromsoilcoressampled2–3 daysafterrainfalleventsduringthethreewintersstudied. Wilt-ingpointmoisturewasestimatedfrommeasurementsmadeatthe endofsummerandthebeginningofautumnafterthecropswere harvested.ThesevaluesaresummarizedinTable2.Theestimated fieldcapacityvalueswereingoodagreementwiththoseestimated usingthepedotransferfunctiondevelopedbySaxtonandRawls (2006),whilethewiltingpointsweregenerallyalittlelower(1–2%) thanthoseestimatedwiththisfunction.Moreover,insitusoil mois-turemeasurementsaremorerepresentativethanstandardizedlab experiments(soilhomogenizedandsievedthrough2mmmesh) carriedoutonde-structuredsoil(Maryetal.,1999).Forthefields studied,theavailablesoilwaterforcropsvariedbetween190and 235mmtoadepthof1.2m.

The STICS model was initialized once using soil water and mineral-NcontentsmeasuredinFebruary2005forfields1,6and 10,wherespringcropsweresownin2005;andwiththe corre-spondingdatafromDecember2005forfields2,3,5and8,where wintercropsweresown.Theoutputvariablesusedformodel eval-uationwerethewaterandmineral-Ncontentsinthewhole1.2m deepsoilprofile.

2.2.2. Samplinginsupplementaryfieldsandmodelingofthe wholestudyarea

InordertoevaluateSMNvariabilityforthewholestudyarea, allfieldsweresampledin2007,specificallyinJulyafter harvest-ingofthewintercrops(wheat,rapeseed,winterpea)andinearly Novemberafterharvestingofthespringcrops(maize,sorghum, sunflower,melon,andsoybean).Thesefieldsweresampledand analyzed(waterandmineral-Ncontents)usingthesamemethods asforthemonitoredfields.WhilemeasuredSMNandSWCwere usedastheinitializationdataforthemonitoredfields,initialization fortheotherfieldsinthealluvialzonewasperformedinNovember 2005usingvaluesobtainedbyinversionoftheSTICSmodelinorder tominimizedifferencesbetweenpredictedandmeasuredSWCand SMNvaluesatharvest2007.TheinitialSWCvaluesobtainedwere closetofieldcapacityasforthemonitoredfields.InitialSMNvalues

variedbetween25and300kgNha−1,whichisthesamerangeof variationasforthemonitoredfields.Usingthismethodandthe esti-matedinitialvalues,thesimulatedSMNvaluesatharvestin2007 wereinreasonablygoodagreementwiththemeasuredvalues.The biaswassmall(ME=3.1kgN-NO3ha−1)andRMSEwasfairlygood (RMSE=26.9kgN-NO3ha−1).Itwasthenpossibletorunthemodel andtocalculatenitrateleachingforeachfieldinthestudyarea.As thesimulationsofthe7monitoredfieldsshowedthatdrainagewas eithernilorverylowduringthe2004–2005cropsequence,the sim-ulationswereonlyperformedonthe2005–2006and2006–2007 cropsequences,whicharepresentedinFig.1b.Cropmanagement practiceswereassessedusingdataonrealfarmpracticescollected insurveysofthefarmerswhomanagethemonitoredfields. 2.3. Modelevaluation

ThestatisticalevaluationofthemodelfocusedonbothSMN andSWCmeasuredonthesamplingdates.Threestatisticalcriteria wereused(Smithetal.,1996):

Modelefficiency(EF):optimalvalue=1

EF=1−



i=1(Pi−Oi)2



i=1(Oi− ¯O)2

Meanerror(ME)anditsrelativevaluein%(ME%):optimalvalue=0

ME= 1 n n







Rootmeansquareerror(RMSE)and itsrelativevalue(RMSE%): optimalvalue=0 RMSE=















wherenisthenumberofobservations,Oitheobservedvalue, ¯O themeanoftheobservedvalues,andPithevaluepredictedbythe model.

Amodelefficiencylevelhigherthan0.6isgenerallyaccepted asveryefficient.Ameanerror(%)andaRootmeansquareerror (%)lowerthan15%canbeconsideredveryefficientconsideringall theprocessessimulatedandthesimplificationsusedinthemodel (Smithetal.,1996).

Fig.2.Observedandsimulatedvaluesof(a)soilwaterand(b)soilnitrogencontent overa1.2mdepthinthemonitoredfields.

2.4. TheSTICSmodel

ThisstudywascarriedoutusingtheSTICSmodel,whichwas mainlydevelopedattheNationalInstituteofAgronomicResearch (INRA)inFrance.STICSisadynamicsoil-cropsimulationmodel functioningatthedaytimescale(Brissonetal.,1998,2002,2003, 2008).Thecropof interestis characterizedby itsaboveground

biomass(carbonandnitrogen),leafareaindex,andnumberand biomass(carbonandnitrogen)ofharvestedcroporgans.Thesoil descriptionincludesfourcompartments:microporosity(or textu-ral porosity),macroporosity(orstructural porosity),fissures(in thecaseofswellingclaysoils)andstones(varioustypesofstones accordingtotheirporosityandwaterstorage).Thesoilisdivided into a maximum of 5 horizonsbut calculations of microporos-ityaredoneper1cm layer,which istheresolution requiredto derive nitrateconcentration with relevanceas shown byMary etal.(1999).Watertransportinsoilmicroporeswascalculatedfor each1cmlayerusingatippingbucketapproach.Thedailywater budgetallowscalculationofthewaterstatusofthesoil, includ-ingactualevaporationandcroptranspiration,aswellasindices ofwaterstress,whichreduceleafgrowthandnetphotosynthesis ofplants.Itisbasedonestimatingthewaterrequirementsofthe soil–leafsystemontheonehandandonthewatersupplytothe soil–rootsystemontheother.Thedailynitrogenbudgettakesinto accountmineralizationfromhumusandcropresidues, denitrifica-tion,nitrogenabsorptionandsymbioticN2fixationforleguminous crops.

IntheSTICSmodel,thesoilischaracterizedbythickness,bulk density,fieldcapacityandwiltingpointvaluesforeachlayer;these propertiesneededtobespecifiedforeachlayerwhosedepthis determinedby theuser(actual pedologicalorsamplingdepth). Othersoilpropertydataarerequiredtorunthemodel,suchas the organic N, clay, pHand carbonate contents in the plowed layer;theseparametersdrivethesoilNmineralizationsimulation. The last inputs required are climate data, such as daily mini-mumandmaximumtemperatures,solarradiation(globalincoming energy),rainfallandcalculatedpotentialevapotranspiration.For cropmanagement,themodelrequiresdataonsowing(date,depth and density),mineraland organicNfertilization, irrigationand soiltillagewithplowingofcropresiduesandorganicproducts. The model can beused onsuccessive crop sequences without re-initializationeveryyear.Soilwater,mineralnitrogen,organic nitrogenandcarbonareupdatedaftereachcropcycle. Decomposi-tionofcropresiduesisalsotakenintoaccountfromharvesttothe nextcrop.TheSTICSmodelwasinitiallyparameterizedand vali-datedforbaresoilandwheatandmaizecrops(Brissonetal.,1998), butithassincethenbeenadaptedforothercropssuchasrapeseed, sunflower,soybean,flax,tomato,sorghum,lettuce,whitemustard, sugarbeetandpotato(Brissonetal.,2003).Morethan200output variablescanbesimulateddaily,suchas(i)soilwaterandnitrate contentsin eachlayer,(ii)cropwater andnitrogenuptake,and (iii)waterdrainage,nitrateleachingandnitrateconcentration—the outputvariableshighlightedinthisstudy.AstheSTICSmodelhad previouslybeencalibratedandvalidatedforallthecropsstudied inthepresentwork(Brissonetal.,1998,2003),weusedthemodel withoutanyspecificcalibrationofcropparameters.Moreover,no

Table4

Validationresultsofsimulatedsoilwatercontentandmineral-Ncontent.

Field1 Field2 Field3 Field5 Field6 Field8 Field10 Allfields

Soilwatercontenton0–120cm(mm)

Obsnumber 11 9 7 8 9 9 13 66 ME −9.7 −11.9 −25.7 27.7 −23.1 2.0 −4.5 −10.3 ME(%) −3.5 −3.4 −6.7 7.4 −6.3 0.5 −1.4 −3.0 RMSE 16.6 22.2 28.8 46.2 32.8 25.6 30.2 23.7 RMSE(%) 6.0 6.4 7.6 12.3 8.9 6.7 9.1 6.8 EF 0.92 −0.51 −4.70 −1.41 0.82 0.12 0.81 0.84

Soilmineral-Ncontenton0–120cm(kgNha−1₎

Obsnumber 11 9 7 8 9 9 13 66 ME −6.2 −11.2 9.0 −4.0 18.8 8.0 2.4 0.5 ME(%) −7.0 −4.8 3.0 −31.2 14.0 9.0 3.6 0.4 RMSE 28.1 31.2 35.5 7.6 33.9 27.7 19.4 27.7 RMSE(%) 31.6 13.5 12.0 58.7 25.2 30.9 29.5 22.8 EF 0.59 0.90 0.51 −0.01 0.68 0.67 0.56 0.92

specificcalibrationwascarriedoutforanysoilorcropprocesses sincethemodelcansimulatea widerangeofpedoclimatic and croppingsystemconditions(Brissonetal.,2003).

3. Resultsanddiscussion

3.1. Modelvalidation

Forthesevenmonitoredfields,thesimulatedvalueswerein goodagreementwiththeobserveddata(Fig.2).Forsoilwater con-tent(SWC) thesimulationsweresatisfactory(Fig.2a;R2_=0.81; P<0.001).However,therewasasmalltendencyforthemodelto overestimatethelowerSWCvalues.Overall,SWCwas overesti-matedbyonly10.3mm(3.0%)onaverage(Table4).TheMEvalues werelowandrangedfrom−25.7mmto27.7mm.Therewasaslight overestimationforfields1,2,3,and6and10,andaslight underesti-mationforfields5and8.Thepredictionerror(RMSE)waslowand variedbetween6.0and12.3%.Modelefficiencywassatisfactory forfields1,6,and10.Forfield8,efficiencywasslightlyhigherthan zero,whilefortheotherfields(fields2,3and5)modelefficiency waslessthanzero.Thislowefficiencycouldbeexplainedbythe smallrangeofvariationintheobserveddata.Thusthemodelwas notabletosimulateverysmallvariationsinwatercontent(afew mmofwaterfor1.2msoildepth),whichcouldhavebeenpartly duetomeasurementprecision.

Withregardtosoilmineralnitrogen(SMN),themodelwasable tocorrectlysimulatetheobservationswithoutanybias(Fig.2b; R2_{=0.92;P<0.001).Therangeofvaluesoftheobserveddatawas} large,indicatingthatthemodelhassufficientsensitivitytosimulate largesoilmineral-N variations.The SMNcontent was overesti-matedbyonly0.5kgNha−1onaverage.ThisgoodoverallMEwas partlyduetocompensationeffectsbetweenfields.Thesoil mineral-N wasslightly overestimated in fields 1, 2 and 5, and slightly underestimatedinfields3,6,8and10.Thepredictionerror(RMSE) variedbetween12.0 and58.7%. Themodel efficiencywasgood (>0.6)forfields1,2,6,and8andlesssatisfactoryforfields3and10. Forfield5(fallowlandusedforgrazing),theefficiencywaslessthan zero;thehighMEandRMSE(31.2%and58.7%respectively)andthe poorefficiency(almostzero)couldbeexplainedbythelowvalues andvariationinsoilmineral-N.Nevertheless,theoveralltrendfor field5andthelevelofconcentrationwerecorrectlysimulated.In general,thevaluesofMEandRMSEwereingoodagreementwith thosereportedbySchnebelenetal.(2004),Beaudoinetal.(2008)

andJégoetal.(2008)forpredictingSMNusingtheSTICSmodel forvariousarablecrops.Furthermore,itisnoteworthythattheME, RMSEandEFwerealmostsimilarinthefoursoillayersstudied, indicatingthattheSTICS modelcansimulatedynamicSWCand SMNprofiles.

Fig.3showsthetemporalchangesinsimulatedsoilmoisture andSMNincomparisonwithobserveddataforeachsoillayerin field1asanillustrationofmodelperformance.Theseresults indi-catethatthemodelwasabletocorrectlysimulatethetemporal changesin water and mineral-Nquantitiesin thedifferentsoil layers.Theseasonalvariationsinsoilmoistureweresignificant. Summers were characterizedby a large decrease in soil mois-ture,up tovalues close towiltingpoint (at leastfor the three firsthorizons).However,thecropsequencehadanimpactonthe temporalpatternofthesevariations.Theshorterperiod charac-terizedbymoistureatfieldcapacityduring2005–2006compared with2006–2007couldbeexplainedbythelongerperiodofbare soilbetweenpeaharvest(2006)andmaizesowing(2007)as com-paredwiththeperiodbetweensoybeanharvest(2005)and pea sowing(2006).Inthedeepestsoillayer(90–120cm),soilmoisture decreasedsignificantlyonlyduringsummer2005.

SMNvaluesintheuppermostlayer(0–30cm)increasedinthe springbecauseofsoilorganicmatterandcropresidueN mineral-ization(andNfertilizationin2007).ThedecreasesinSMNobserved aftereachofthesethreeincreaseswereduetocropNuptakeand nitratetransfertodeepersoillayers.Inthe30–60cmand60–90cm layers,SMNdecreasedrapidlyafterthebeginningofthe simula-tionduetoNabsorptionbysoybean.SMNinitiallyincreasedatthe beginningof2006duetonitratetransferfromtheupperlayerand decreasedthereafterbecausethissignificantamountofnitratewas transferredtothelowerlayer.Thenextincreasewasalsodueto nitratetransferfromupperlayers.Finally,SMNdecreasedbecause oftransfertolowerlayersandNuptakebythemaizecrop.Inthe deepestlayer(90–120cm),SMNincreasedfromMarch2006due tonitratetransfer.

Simulatedsoilwaterandnitrogenlevelswereingood agree-ment with the measured values despite the wide range of agronomic(croptype,fertilizationandirrigation)and environmen-talconditionsencounteredduringourstudy.Althoughforsome fieldsandsomesamplingtimes,thesimulationswerenotalways completelysatisfactoryintermsofabsolutevalues,thetrendsand rangeofvariationweresatisfactoryforallfields.Thegood agree-mentbetweensimulatedandmeasuredvaluesprovidesconfidence inthesimulationsofnitrateleachingandwaterdrainagefluxes. Moreover,itcanbepostulatedthatthemodelcorrectlysimulated (i)theNmineralizationdynamicsofsoilorganicmatterandthe decompositionofcropresidues,and(ii)waterandnitrate trans-ferwithinthesoilprofile,becausenobiaswasobservedinthe simulationofSWCandSMNovertheentireyearforallthe moni-toredfields.Thisisparticularlytrueduringthelongbaresoilperiod betweentwomaincrops(springcropsownafterwintercrop,e.g. maize afterwinter wheat),where nointeraction occurredwith plantNuptake.Themodelcouldthenbeusedtoevaluatethe rel-ativeeffectsofdifferentinputvariablesonnitrateleaching,asalso shownbyotherauthors(e.g.Beaudoinetal.,2005).

3.2. Evaluationofspatialandtemporalvariabilityinnitrate leaching

3.2.1. Simulatedtemporalvariationsinthethreecroppingyears Temporalchangesinsimulateddrainage,nitrateleachingand nitrateconcentrationareillustratedinFig.4forfields1and6,which arerepresentativeofthesevenmonitoredfields.Duetothelow levelofprecipitationduringthepreviousyear,soilmoisturewas belowfieldcapacityduringthe2004–2005winter,whichledthe modeltosimulatenodrainageornitrateleachinginfield1(Fig.4a andb).Inthisfield,likeinothermonitoredfields,twoperiodsof drainageoccurred,asindicatedbythemeasuredsoilmoistureand waterbalance.Thetemporalpatternanddurationoftheseperiods canvaryfromfieldtofieldaccordingtothecroppingsequence.In 2006,themonthofMarchwasrainy(107mm)andthesoil microp-oresweresaturatedtoadepthof1.2mduringthisperiod.Thishigh rainfallcombinedwiththebaresoilwasresponsibleforthefirst sig-nificantsimulateddrainageevent(13mm)forfield1.Fromautumn 2006untilspring2007,allsoillayerswereclosetofieldcapacity, henceeverynewrainfalleventgenerateddrainage,assimulated bythemodel(Fig.4a).Forfield1,thesimulationindicated signifi-cantnitrateleachingof113kgNha−1duringthestudyperiodand aconsiderablevariationinnitrateconcentrationindrainagewater, thatis,50–240mgNO3−L−1(Fig.4c).Theweightedaveragenitrate concentrationoverthewholeperiodwas190mgNO3−L−1.

Fig. 4 also shows temporal changes in simulated drainage (Fig. 4d), nitrateleaching (Fig.4e)and nitrate concentrationin drainage water (Fig. 4f) for field 6. In this field, the temporal variationinsimulateddrainageandnitrateleachingwasslightly differentfromthatinfield1.Thefirstsignificantsimulateddrainage eventoccurredinFebruary2005,earlierthaninfield1,andthe

Fig.3. TemporalchangesinobservedandsimulatedgravimetricsoilmoistureandSMNforfield1atdifferentsoildepths.Croppingperiodsareindicatedingray.

seconddrainagefluxoccurredinApril2005.Thesedrainageevents maybeexplainedbytheinitialSWC,whichwashigherinfield6 thaninfield1becauseoftheprecedingcrop.Thesimulatedmain drainageperiod(almost200mm)occurredinfield6intheperiod fromNovember2005toApril2006,inspiteofthepresenceofa

winter wheatcrop, andthesimulated amountofnitrate leach-ingwas44kgNha−1 (Fig.4e),orhalfthatinfield1.Mostofthis nitrateleachingoccurredduringthe2006drainageperiodwiththe winterwheatcropbeingpresent,whentheamountofdrainage waterwassignificantandassociatedwithnitrateconcentrations

Fig.4.Simulatedtemporalchanges(aandd)indrainageandcumulativedrainage,(bande)innitrate-NleachingandcumulativeNleaching,and(candf)ininstantaneous nitrateconcentrationindrainagewaterandflowweightedmeanNO3−_{concentrationinfields1and6.ArrowsindicatetimeandamountofN-fertilization.Croppingperiods} areindicatedingray.

varyingbetween60and100mgNO3−L−1(Fig.4f).Finally,the sim-ulationsindicatedthereweretwomainperiodsofdrainagein2007, January–MarchandSeptember–October.

Fields1and6showedtwodifferentpatternsoftemporal distri-butionofdrainageandalsoofnitrateleaching.Spatialanalysisof nitrateleachinginallfieldsinthestudyareacouldhelpto deter-minewhichofthesetwopatternsofdistributionisdominant. 3.2.2. Simulatedspatialvariationinnitrateleaching

Fig.5showsthecumulativenitrateleachingsimulatedduring twosuccessivecropsequences(2005–2006and 2006–2007)on allfieldsin thestudyarea. The2004–2005cumulativeleaching resultsarenotpresentedbecausetherewasalmostnodrainage duringthatperiod.Inthesixmonitoredagriculturalfields,nitrate leachingrangedfrom5to160kgNha−1in2005–2006andfrom 5to120kgNha−1 in2006–2007.In thefallowfield (5),nitrate leachingwasstillpredictedtobelessthan5kgNha−1.Inallother

agriculturalfields,averagenitrateleachingwasslightlyhigherin 2006(38kgNha−1)thanin 2007(23kgNha−1)(P<0.05). Over-all,mostofthenitrateleachingoccurredduringspring2006,as illustratedforfield1(Fig.4b).Thelevelofnitrateleaching was lowerduring winter2006–2007and spring2007.Nevertheless, forbothyears,therangeofvariationinnitrateleachingbetween thefieldswasquitelarge.In2006and2007,just15%ofthefields accountedfor60and67%ofnitrateleaching,respectively.Nitrate pollutionofgroundwaterisoftencalled“diffusepollution”in ref-erencetothepolluterpaysprinciple.However,inthestudyareas, thenitrateleachingwasassociatedwithpointsourcepollution(at thefieldscale)andwascharacterizedbyconsiderablespatial vari-ationwithinashortdistanceandbytemporalvariations.Therewas nosignificantdifferenceinsimulatednitrateleachingbetweenthe twomaincropsinthearea(wheatandmaize)ineither2006or 2007.Moreover,therewasnosignificantdifferenceinnitrate leach-ingamongtheothercropsbecauseofthehighspatialvariability

Fig.5. Spatialdistributionofsimulatednitrateleachingat1.2mdepthunderall fieldsinthestudyarea(a)in2005–2006and(b)in2006–2007.

betweenfields.However,in2007,simulatednitrateleachingwas significantlyhigher(P<0.05)fromthemaizeandcerealcultivar testingtrialfields,whereasin2006thedifferencewasnot signifi-cant(P=0.48).Thesefields,usedfortheassessmentofnewcultivars bybreeders,weregenerallyoverfertilizedinordertoavoidtherisks ofcropnitrogendeficiency.

Soil type didnot inducesignificantdifferences in simulated nitrate leaching, but initial SMN had a significant impact. In 2006,nitrateleachingwassignificantlycorrelatedwithinitialSMN (y=0.26x+8.8;R2_{=0.43),whilein2007thecorrelationwasnot} sig-nificant.In2007,theimpactofthenewcultivartrialfieldsofmaize andcerealwaspredominant.

Asshowninthisworkandinseveralpreviousstudies(Shepherd andLord,1996;Beaudoinetal.,2005),SMNatharvestwasthekey factorexplainingthevariationinnitrateleaching.SMNmeasuredat harvest(JulyforwintercropsandNovemberforspringcrops)inthe 40fieldsofthearea(thesevenmonitoredfieldsin2005,2006and 2007,and19additionalfieldssampledin2007)showedthatthere wasnosignificantdifferencebetweenSMNatharvestoveradepth of0–1.2mforthetwomaincrops,despitedifferencesinaverage values (wheat:60_±13kgNha−1; maize: 78_±25kgNha−1).The meanSMNafterwheattoadepthof1.2mwashigherthanthe 35–40kgNha−1reportedbyMakowskietal.(1999)andBeaudoin

et al.(2005)over a depthof 0–1.2min northernFrance. How-ever,overadepthof0–60cm,themeasuredSMNinawheatfield atharvest(38kgNha−1)issomewhatlowerthanthe43kgNha−1 over0–60cmreportedbyWebsteretal.(2003)intheUK.Forthe othercrops,SMNwasnotsignificantlydifferentbetweenwheatand maizebutitwaslowerforrapeseed(25±7kgNha−1)and consid-erablyhigherfortwofieldsoftrialmaizelines(215±25kgNha−1). Thesemaizelinesgenerallytakeuplessnitrogenthancommercial hybridcropsduetotheirsmallersizeandslowergrowthrate.This valueindicatesthattheNfertilizerapplicationrateswerenotwell tailoredtothesecrops,whichcouldexplainwhytheSMNatharvest wassohighinthesefields.

TheSMNcontentsmeasuredatharvestinthesevenmonitored fieldsin2007wereinagreementwiththeSMNsimulatedbySTICS (ME=15.4%;RMSE=30.5%).MeasuredSMNcontentswerealsoin goodagreementwiththemeanSMNmeasuredinallthefieldsofthe studyareaatharvestexceptforfields2and8,wheretheSMNover adepthof0–1.2mwasslightlyhigherthantherangeofvariationin theotherfieldsplantedtothesamecrop.Thisindicatesthat,overall, themonitoredfieldswererepresentativeofthefieldslocatedinthe studyarea.

Simulateddrainage,nitrateleachingandnitrateconcentration aredetailedinTable5forthemonitoredfields.Thedrainageand nitrateconcentrationwereextremelyvariablefromonefield to another,evenwithinthissmallstudyareawithitsfairly homoge-nouspedoclimaticconditionsandstocklessfarms.Inallcases,the nitrateconcentrationsindrainagewaterwereconsiderablyhigher than those in the Garonne Riverand, except for a few instan-taneousfluxesandthevaluesobtainedforthefallowfieldused forgrazing,thesimulationsindicatedthattheyweregreaterthan 50mgNO3−L−1.Thesimulatedmeanweightednitrate concentra-tionswereextremely highin 2006for fields2 and 3(241 and 334mgNO3−L−1respectively),andin2007forfields1,2and3(213, 385,and307mgNO3−L−1respectively).Theamountofdrainage wateranditsnitrateconcentrationbelowadepthof1.2mcould explainwhythenitrateconcentrationinthealluvialaquifercould reachvaluesupto60mgNO3−L−1insomepiezometersofthe allu-vialgroundwater.Asshownforfields1and6,drainagewasmore significantin2006and2007comparedto2005(almost negligi-ble),whichisexplainedbyrainfallvariability.Thesimulatednitrate leachingvalueswerehigherthan50kgNha−1forfield1in2007,for field2in2006and2007,forfield3in2006and2007,andforfield8 in2007,althoughplantNuptakeandyieldsfellwithintherangeof variationofthestudyarea(Table5).Thehighlevelofnitrate leach-ingwasassociatedwithhighnitrateconcentrationsindrainage water(>100mgNO3−L−1),whichweregenerallyassociatedwith highinitialSMN.Intheunfertilizedfallowlandusedforgrazing, thesimulationshowedthatsignificantdrainageoccurredonlyin 2007(63mm)but,owingtothegreencoverthroughouttheyear, thenitrateconcentrationswereverylow(<10mgNO3−L−1). 3.2.3. Relationshipbetweensimulatednitrateleachingand agriculturalpractices

Our work involved analyzing and explaining the high spa-tial variability of the piezometer measurements in the study area(Sánchez-Pérezetal.,2003b)in connectionwithsimulated drainage,nitrateleachingand nitrateconcentrationindrainage wateratthealluvialfloodplainscale.Therelationshipsbetween nitrateleachinganddrainage,andbetweennitrateleachingand nitrateconcentrationindrainagewaterwerenotsignificant, indi-catingthatdrainageandnitrateconcentrationindrainagewater werenotdirectlylinked.

Somestudieshaveshownthatpreviouscroptypehasanimpact onnitrateleaching(ShepherdandLord,1996;Halletal.,2001;Jégo etal.,2008).However,inourstudyareanosignificantrelationship wasfoundbetweenSMNatharvestandcroptype,probablybecause

model

for

estimating

nitrate

Table5

Inputdataandsimulatedoutputvariablesofthesevenmonitoredfields.

Inputdata Outputsvariablessimulated

Year Simulatedperiod Field Crop Rainfall (mm) InitialSMN (kgNha−1₎ Drainage (mm) Nitrate leaching (kgNha−1₎ Nitrate concentration indrainage water (mgNO3−L−1) SMNatharvest (kgNha−1₎ PlantN-uptake (kgNha−1₎ Dryyield (tha−1₎ 2005 18/02/05–30/11/05 1 Soybean 350 58 0 0 – 75 179 1.0 25/11/04–30/11/05 6 Springpea 425 159 74 10 63 167 231 4.3 18/02/05–30/11/05 10 Sunflower 350 74 77 7 39 53 139 5.3 2006 01/12/05–31/10/06 1 Winterpea 644 75 37 6 69 162 233 3.0 01/12/05–31/10/06 2 Maize 644 303 188 142 334 207 177 6.3 01/12/05–31/10/06 3 Sorghum 644 287 93 51 241 248 230 7.0 01/12/05–31/10/06 5 Fallow 644 25 0 0 – 14 60 – 01/12/05–31/10/06 6 Wheat 644 167 137 34 110 65 169 5.8 01/12/05–31/10/06 8 Soybean 644 58 156 9 24 101 177 4.1 01/12/05–31/10/06 10 Wheat 644 53 109 6 23 55 163 7.4 2007 01/11/06–31/10/07 1 Maize 600 162 222 107 213 119 240 9.6 01/11/06–31/10/07 2 Wheat 600 207 120 104 385 125 215 5.1 01/11/06–31/10/07 3 Wheat 600 248 118 81 307 75 258 10.0 01/11/06–31/10/07 5 Fallow 600 14 63 <1 <1 10 40 – 01/11/06–31/10/07 6 Rapeseed 600 63 106 <1 <1 87 277 3.3 01/11/06–31/10/07 8 Soybean 600 101 235 60 112 81 147 2.9 01/11/06–31/10/07 10 Soybean 600 54 253 30 53 41 165 4.2 Table6

SimulationoftheimpactofinitialSMNinfields2and3onwaterandnitratefluxes.SimulatedoutputvariablesusingactualinitialSMNarecomparedwithmodelsimulationsusinganaverageinitialSMNof80kgNha−1_.

Inputdata Simulatedoutputvariables

Field Simulationperiod Crop SMNinitial

(kgNha−1₎ Drainage (mm) Nitrate leaching (kgNha−1₎ Nitrate concentration indrainage water (mgNO3−L−1) FinalSMN (kgNha−1₎ 2 1/12/05–31/10/06 Maize 303₈₀ 188₁₈₉ 142₃₆ 334₈₄ 207₁₁₂ 1/11/06–31/10/07 Wheat 207₈₀ 120₁₂₈ 104₁₅ 385₅₂ 125₁₃₁ 3 1/12/05–31/10/06 Sorghum 287 93 51 241 248 80 93 12 57 141 1/11/06–31/10/07 Wheat 248 118 81 307 75 80 117 9 34 83

y = 1,24x -29,6 R² = 0,80 0 50 100 150 200 250 300 350 400 450 400 300 200 100 0 NO 3 -(m g .L -1) Initial SMN (kgN.ha-1₎

Fig.6. SimulatednitrateconcentrationindrainagewaterasafunctionofinitialSMN in2006and2007.

fertilizer-Nisnotproperlyadjustedtomeetcroprequirementsfor somecrops(e.g.newmaizecultivartrials)andalsobecause farm-ersdo not analyzeSMNaspartof theirapproachfor adjusting fertilizer-N.Inaddition,thethreeprecedingyearswereverydry andSMNcouldhaveaccumulatedinthesoil.Thus,no relation-shipwasfoundbetweenpreviouscropandsimulateddrainage, nitrateleaching,ornitrateconcentration(Table5).Therewasalso nosignificantcorrelationbetweennitrateconcentrationornitrate leachingandquantityofNfertilizerapplied(Fig.4a,c,d,andf). Thiswasprobablyduetothefactthatfertilizationrateswerenot adjustedbasedontheinitialSMNlevel.Consequently,thenitrate concentrationcouldvarywidelyforthesamefertilizerapplication rate.TheadjustmentofN-fertilization basedontheinitialSMN levelwouldhavedecreasedthenitrateconcentrationindrainage water,asreportedinotherstudies(HansenandDjurhuus,1996; Maryetal.,2002;Fergusonetal.,2002)anddemonstratedbythe scenariowithreducedinitialSMN.

Inthestudyarea,soiltypeanddepthwerealmosthomogenous andalthoughmanystudieshaveshownthatsoiltypehasan impor-tantimpactonnitrateleaching(Niederetal.,1995;Simmelsgaard, 1998;Hoffmannand Johnson, 1999), nosignificantimpactwas observedinourstudy.Thesmallvariabilityofsoilpropertiesand thesmallnumberofagriculturalfieldswithsoil1(3fields),soil3 (9fields)orsoil4(12fields),comparedtosoil2(26fields),could explainwhynosignificantrelationshipwasfound.

Theinitialsoilnitrogencontent,thatis,themineral-Npresentin thewhole1.2mdepthprofileatthebeginningofthestudyand sim-ulationperiod,waspositivelyandsignificantlycorrelatedwiththe nitrateconcentrationindrainagewater(Fig.6).Thisisinagreement withotherstudies(ArreguiandQuemada,2006),whichreported thatSMNcontentbeforeplanting,togetherwithdrainage,wasthe mainfactor determiningtheamountofN leachedandthusthe nitrateconcentrationindrainagewater.TheinitialSMNvaluewas particularlyhighinfields2and3and,asaconsequence,themean simulatednitrateconcentrationindrainagewaterwasalsovery high.InordertoexaminetheimportanceofinitialsoilmineralN content,weusedscenarioswithlowerinitialSMNvalues.The sim-ulationsofthe2005–2006–2007cropsequencesshowedthatthe nitrateconcentrationindrainagewaterfromfields2and 3was veryhigh.Theuseofacatchcropwasnotpossibleinthese sit-uationsbecausetheperiodofbaresoilbetweenmaincropswas tooshort.Astrongpositivecorrelationwasfoundbetweenthese nitrateconcentrationsand initialSMN.Inordertoexaminethis relationshipmoreclosely,wecarriedoutsimulationsforthesetwo fieldswithaninitialSMNof80kgNha−1.Forthetwofieldsandfor thetwosuccessiveyearssimulated,decreasingtheinitialSMNled toalargedecreaseinnitrateleachingandnitrateconcentrationin

drainagewater,withoutaffectingthemaincropyields(Table6). TheseresultsillustratetheimportanceofreducinghighSMN con-tentsduringautumnbeforethewinterdrainageperiodinorderto reducenitrateleaching.Insuchasituation,acatchcropmaybe asolutionforreducingnitrateleaching(Thorup-Kristensenetal., 2003).

The SMN level in late autumn,before winter drainage, was foundtobethemaincontributingfactor.Thisdemonstratesthat Nmanagementwasunsatisfactoryinthemediumtermandthat cumulativeproblemsassociatedwithunsuitableagricultural prac-ticesmaybemoredetrimentalforNmanagement thana single annualcaseofnitrogenoverfertilizationincasesofdeepalluvial soils,particularlyinsituationsofloworhighlyvariabledrainage betweenyears.

4. Conclusions

ThesimulatedSWCand SMNvalues inthedynamic simula-tionsweregenerallyandspecifically(temporalandbetween-layer changes)ingoodagreementwiththemeasuredvalues.These sat-isfactory resultsallowed themodel tobeused tosimulate the temporal andspatial variabilityin nitrateleaching toprovidea diagnosticassessmentof thesituation.Thisworkcouldprovide thebasisforfuturestudiestoassesstheimpactofmodifications ofagriculturalpracticesaimedatdecreasingnitrateleachingand nitrateconcentrationindrainagewater.

TherewasnosignificantdifferenceinSMNvaluesatharvestor innitrateleachingforthedifferentmaincropsinthestudyarea, althoughlargebetween-fieldvariationswereobserved.Nitrogen managementinthispartofthealluvialfloodplainwasnot effec-tiveandhencethenitrateconcentrationsindrainagewaterunder cropsweretoohigh.Drainageandnitrateconcentrationvalues var-iedwidelyfromonefieldtothenext,dependingontheprevious crop,agriculturalpractices(withorwithoutirrigation)andannual climateconditions.Forsomefields,theaverageannualnitrate con-centrationindrainagewaterwasgreaterthan200mgNO3−L−1and nitrateleachingexceeded100kgNha−1.Analysesoftemporaland spatialvariabilityinnitrateleachingshowedthatthepatternof nitrateleachingwasextremelyspecificandirregular(spatiallyand temporally)andalsothattheSMNcontentattheendofautumn, beforethewinterdrainageperiod,wasthemostsignificantfactor explainingthisvariability.Forthestudyarea,thismeansthatN managementmustbeaimedatreducingSMNasmuchaspossible inNovember.ThismeansthatNfertilizationforthenextmaincrop mustbeadjustedbytakingintoaccounttheresidualSMNatthe beginningofthecropseason(soilanalysismaybenecessary)and byplantingcatchcropstodecreaseSMNbeforethewinter.

Inordertocomplementthisworkandtobetterassesstheimpact ofthespatialandtemporaldistributionofnitrateleachingunder agriculturalfieldsonthenitrateconcentrationingroundwaterand intheGaronneRiver,theSTICSsoil-cropmodelcouldbecoupled witha hydrogeologicalmodel. Thiswouldpermit simulationof (i)theimpacts of agriculturalactivitiesongroundwaternitrate concentrationanditsspatialvariability and(ii)theinteractions betweenriverwaterandgroundwater.Inthecaseoflargerivers suchastheGaronneRiver,groundwatercanbeinfluencedbyriver waterseveralhundredmetersfromtheriverbank.Thiswouldmake itpossibletosimulatetheimpactofagriculturalpracticesonnitrate concentrationsingroundwaterinaportionofthealluvialplainand betterexplainthespatialvariabilityofnitrateconcentrationsinthe groundwater.Theperformanceofthecoupledmodelcouldbe eval-uatedusingthegroundwaternitrateconcentrationmeasuredinthe piezometersthathavebeenusedonthissiteforseveralyears.

Acknowledgments

This study was supported by ECOBAG: ‘Zone atelier Adour Garonne’.TheauthorsthankD.ChesneauandP.Petibonfortheir assistancewithsoilcoresamplingandanalyses,andwethankall thefarmersinthestudyareaforallowingustotakesamplesin theirfields.

References

Arrate,I.,Sánchez-Pérez,J.M.,Antigüedad,I.,Vallecillo,M.A.,Iribar,V.,Ruiz,M.,1996. GroundwaterpollutioninthequaternaryaquiferofVitoria-Gazteiz(Basque country,Spain).Influenceofagriculturalactivitiesandwater-resources man-agement.EnvironmentalGeology30(3–4),257–265.

Arregui,L.,Quemada,M.,2006.Drainageandnitrateleachinginacroprotation underdifferentN-fertilizerstrategies:applicationofcapacitanceprobes.Plant andSoil288(1),57–69.

Beaudoin,N.,Saad,J.,VanLaethem,C.,Maucorps,J.,Machet,J.M.,Mary,B.,2005. NitrateleachinginintensiveagricultureinNorthernFrance:effectoffarming practicessoilsandcroprotations.AgricultureEcosystems&Environment111, 292–310.

Beaudoin,N.,Launay,M.,Sauboua,E.,Ponsardin,G.,Mary,B.,2008.Evaluationofthe soilcropmodelSTICSover8yearsagainstthe“onfarm”databaseofBruyères catchment.EuropeanJournalofAgronomy29,46–57.

Berntsen,J.,Olesen,J.E.,Petersen,B.M.,Hansen,E.M.,2006.Long-termfateof nitro-genuptakeincatchcrops.EuropeanJournalofAgronomy25,383–390. Bijay-Singh,Yadvinder-Singh,Sekhon,G.S.,1995.Fertilizer-Nuseefficiencyand

nitratepollutionofgroundwaterindevelopingcountries.Journalof Contami-nantHydrology20,167–184.

Böhlke,J.K.,2002.Groundwaterrechargeandagriculturalcontamination. Hydroge-ologyJournal10,153–179.

Brisson,N.,Mary,B.,Ripoche,D.,Jeuffroy,M.H.,Ruget,F.,Gate,P.,Devienne-Barret, F.,Antonioletti,R.,Durr,C.,Nicoullaud,B.,Richard,G.,Beaudoin,N.,Recous,S., Tayot,X.,Plenet,D.,Cellier,P.,Machet,J.M.,Meynard,J.M.,Delécolle,R.,1998. STICS:agenericmodelforthesimulationofcropsandtheirwaterandnitrogen balance.I.Theoryandparameterizationappliedtowheatandcorn.Agronomie 18,311–346.

Brisson,N.,Ruget,F.,Gate,P.,Lorgeou,J.,Nicoullaud,B.,Tayot,X.,Plenet,D.,Jeuffroy, M.H.,Bouthier,A.,Ripoche,D.,Mary,B.,Justes,E.,2002.STICS:agenericmodelfor thesimulationofcropsandtheirwaterandnitrogenbalance.II.Assessmentby comparingwithexperimentalrealityforwheatandcorn.Agronomie22,69–93. Brisson,N.,Gary,C.,Justes,E.,Roche,R.,Mary,B.,Ripoche,D.,Zimmer,D.,Sierra, J.,Bertuzzi,P.,Burger,P.,Bussière,F.,Cadiboche,Y.M.,Cellier,P.,Debaeke,P., Gaudillère,J.P.,Hénault,C.,Maraux,F.,Seguin,B.,Sinoquet,H.,2003.Anoverview ofthecropmodelSTICS.EuropeanJournalofAgronomy18,309–332. Brisson,N.,Launay,M.,Mary,B.,Beaudoin,N.,2008.ConceptualBasis,Formalisations

andParameterisationoftheSTICSCropModel.QUAE,INRA,Versailles,France, 297pp.

Ferguson,R.B.,Hergert,G.W.,Schepers,J.S.,Gotway,C.A.,Cahoon,J.E.,Peterson, T.A.,2002.Site-specificnitrogenmanagementofirrigatedmaize:yieldandsoil residualnitrateeffects.SoilScienceSocietyofAmericaJournal66,544–553. Gustafson,A.,1983.Leachingofnitratefrom arablelandintogroundwaterin

Sweden.EnvironmentalGeology5,65–71.

Hall,D.,Schaffer,M.J.,Waskom,R.M.,Delgado,J.A.,2001.Regionalnitrateleaching variability:whatmakesadifferenceinnortheasternColorado.Journalofthe AmericanWaterResourcesAssociation37,139–150.

Hansen,E.M.,Djurhuus,J.,1996.Nitrateleachingasaffectedbylong-termN fertil-izationonacoarsesand.SoilUseandManagement12,199–204.

Hoffmann,M.,Johnson,H.,1999.Amethodforassessinggeneralisednitrogen leach-ingestimatesforagriculturalland.EnvironmentalModelingandAssessment4, 35–44.

Iribar,A.,Sánchez-Pérez,J.M.,Lyautey,E.,Garabétian,F.,2008.Differentiated free-livingandsediment-attachedbacterialcommunitystructureinsideandoutside denitrificationhotspotsintheriver–groundwaterinterface.Hydrobiologia598, 109–121.

Jégo,G.,Martínez,M.,Antigüedad,I.,Launay,M.,Sanchez-Pérez,J.M.,Justes,E.,2008. Evaluationoftheimpactofvariousagriculturalpracticesonnitrateleaching undertherootzoneofpotatoandsugarbeetusingtheSTICSsoil-cropmodel. ScienceoftheTotalEnvironment394,207–221.

Jones,C.A.,Kiniry,J.R.,1986.CERES-Maize,aSimulationModelofMaizeGrowthand Development.TexasA&MUniversityPress,CollegeStation,TX.

Loague,K.,Corwin,D.L.,1996.Uncertaintyinregional-scaleassessmentof non-pointsourcepollutants.In:Corwin,D.L.,Loague,K.(Eds.),ApplicationofGIS totheModellingofNon-PointSourcePollutantsintheVadoseZone.S.S.S.A.Inc., Madison,Specialpublication48.

Makowski,D.,Wallach,D.,Meynard,J.M.,1999.Modelsofyield,grainproteinand residualmineralNresponsestoappliedNforwinterwheat.AgronomyJournal 91,377–385.

Mary,B.,Beaudoin,N.,Justes,E.,Machet,J.M.,1999.Calculationofnitrogen miner-alizationandleachinginfallowsoilusingasimpledynamicmodel.European JournalofSoilScience50,549–566.

Mary,B.,Laurent,F.,Beaudoin,N.,2002.Lagestiondurabledelafertilisationazotée. In:65thIRBCongress,Brussels,13–14February2002,p.6.

McClain,M.E.,Boyer,E.W.,Dent,C.L.,Gergel,S.E.,Grimm,N.B.,Groffman,P.M.,Hart, S.C.,Harvey,J.W.,Johnston,C.A.,Mayorga,E.,McDowell,W.H.,Pinay,G.,2003. Biogeochemicalhotspotsandhotmomentsattheinterfaceofterrestrialand aquaticecosystems.Ecosystems6,301–312.

Nieder,R.,Kersebaum,K.C.,Richter,J.,1995.Significanceofnitrateleachingandlog termNimmobilisationafterdeepeningtheploughlayersfortheNregimeof arablesoilsinN.W.Germany.PlantandSoil173,167–175.

Peyrard,D.,Sauvage,S.,Vervier,P.,Sanchez-Perez,J.M.,Quintard,M.,2008.A cou-pledverticallyintegratedmodeltodescribelateralexchangesbetweensurface andsubsurfaceinlargealluvialfloodplainswithafullypenetratingriver. Hydro-logicalProcesses22,4257–4273.

Ritchie,J.T.,Otter,S.,1984.DescriptionandPerformanceofCERES-Wheat,a User-OrientedWheatYieldModel.USDA-ARS-SRGrasslandSoilandWaterResearch Laboratory,Temple,TX,pp.159–175.

Sánchez-Pérez,J.M.,Bouey,C.,Sauvage,S.,Teissier,S.,Antigüedad,I.,Vervier,P., 2003a.Astandardizedmethodformeasuringinsitudenitrificationinshallow aquifers:numericalvalidationandmeasurementsinriparianwetlands. Hydrol-ogyandtheEarthSciencesSystem7,87–96.

Sánchez-Pérez,J.M.,Vervier,P.,Garabétian,F.,Sauvage,S.,Loubet,M.,Rols,J.L., Bariac,T.,Weng,P.,2003b.Nitrogendynamicsintheshallowgroundwaterof ariparianwetlandzoneoftheGaronne,SouthwesternFrance:nitrateinputs, bacterialdensities,organicmattersupplyanddenitrificationmeasurements. HydrologyandtheEarthSciencesSystem7,97–107.

Sánchez-Pérez,J.M.,Antigüedad,I.,Arrate,I.,García-Linares,C.,Morell,I.,2003c. Theinfluenceofnitrateleachingthroughunsaturatedsoilongroundwater pol-lutioninanagriculturalareaoftheBasquecountry.TheScienceoftheTotal Environment317,173–187.

Saxton,K.E.,Rawls,W.J.,2006.Soilwatercharacteristicestimatesbytextureand organicmatterforhydrologicsolutions.SoilScienceSocietyofAmericaJournal 70,1569–1578.

Schnebelen,N.,Nicoullaud,B.,Bourennane,H.,Couturier,A.,Verbeque,B., Reva-lier,C.,Bruand,A.,Ledoux,E.,2004.TheSTICSmodeltopredictnitrateleaching followingagriculturalpractices.Agronomie24,423–435.

Shepherd,M.A.,Lord,E.I.,1996.Nitrateleachingfromasandysoil:theeffectof previouscropandpost-harvestsoilmanagementinanarablerotation.Journal ofAgriculturalScienceCambridge127,215–229.

Simmelsgaard,S.E.,1998.Theeffectofcrop,Nlevel,soiltypeanddrainageonnitrate leachingfromDanishsoils.SoilUseandManagement14,30–36.

Smith,J.,Smith,P.,Addiscott,T.M.,1996.Quantitativemethodstoevaluateand compareSoilOrganicMatter(SOM)models.In:Powlson,D.,Smith,P.,Smith, J.(Eds.),EvaluationofSoilOrganicMatterModels.Springer-Verlag,Berlin,pp. 181–199.

Strebel,O.,Duynisveld,W.H.M.,Böttcher,J.,1989.Nitratepollutionofgroundwater inwesternEurope.AgricultureEcosystems&Environment26,189–214. Thorup-Kristensen,K.,Magrid,J.,Jensen,L.S.,2003.Catchcropsandgreenmanures

asbiologicaltoolsinnitrogenmanagementintemperatezones.Advancesin Agronomy79,227–302.

Wagenet,R.J.,Hutson,J.L.,1996.Scale-dependencyofsolutetransportmodeling/GIS applications.JournalofEnvironmentalQuality25,495–510.

Webster,C.P.,Conway,J.S.,Crew,A.P.,Goulding,K.W.T.,2003.Nitrogenleaching lossesunderalessintensivefarmingandenvironmentintegratedsystem.Soil UseandManagement19,36–44.

Weng,P.,Sanchez-Perez,J.M.,Sauvage,S.,Vervier,P.,Giraud,F.,2003.Assessmentof thequantitativeandqualitativebufferfunctionofanalluvialwetland: hydro-logicalmodellingofalargefloodplain(GaronneRiver,France).Hydrological Processes17,2375–2392.

Williams,J.R.,Jones,C.A.,Kiniry,J.R.,Spanel,D.A.,1989.TheEPICcropgrowthmodel. TransactionsoftheASAE32,497–511.