Optimizing drip irrigation for eggplant crops in semi-arid zones using evolving thresholds

(1)

ContentslistsavailableatScienceDirect

Agricultural

Water

Management

j o ur na l h o me p a g e :w w w . e l s e v i e r . c o m / l o c a te / a g w a t

Optimizing

drip

irrigation

for

eggplant

crops

in

semi-arid

zones

using

evolving

thresholds

T. Müller

a,b,∗

_,

_C.

_Ranquet

_Bouleau

a

_,

_P.

_Perona

b,c

a_Cooperation_&_Development_Center_(CODEV),_Ecole_{Polytechnique}_Fédérale_de_Lausanne_(EPFL),_Lausanne,_Switzerland

b_Laboratory_of_Applied_{Hydroeconomics}_and_Alpine_{Environmental}_Dynamics_(AHEAD),_Ecole_{Polytechnique}_Fédérale_de_Lausanne_(EPFL),_Lausanne,

Switzerland

c_Institute_for_{Infrastructure}_&_Environment,_School_of_Engineering,_The_University_of_Edinburgh,_UK

a

r

t

i

c

l

e

i

n

f

o

Articlehistory:

Received26November2015 Receivedinrevisedform1June2016 Accepted20June2016

Keywords:

Triggereddripirrigation Soilmatricpotentialthreshold Eggplant

Irrigationwatermanagement Soilwatermodeling Semi-aridregions

a

b

s

t

r

a

c

t

Fieldexperimentswerecombinedwithanumericalmodeltooptimizedripirrigationmanagementbased

onsoilmatricpotential(SMP)measurements.AnexperimentalcropofeggplantwasgrowninBurkina

FasofromDecember2014toMarch2015andplantresponsetowaterstresswasinvestigatedbyapplying

fourdifferentirrigationtreatments.Treatmentsconsistedinusingtwodifferentirrigationdepths(low

orhigh),combinedwithawaterprovisionof150%,100%or66%(150/100/66)ofthemaximumcrop

evapotranspiration(T150low,T66low,T100high,T66high).Soilmatricpotentialmeasurementsat5,10

and15cmdepthweretakenusingawirelesssensornetworkandwerecomparedwithmeasurementsof

plantandrootbiomassandcropyields.Fielddatawereusedtocalibrateanumericalmodeltosimulate

triggereddripirrigation.DifferentsimulationswerebuiltusingthesoftwareHYDRUS2D/3Dtoanalyze

theimpactoftheirrigationdepthandfrequency,theirrigationthresholdandthesoiltextureonplant

transpirationandwaterlosses.Numericalresultshighlightedthegreatimpactoftherootdistributionon

thesoilwaterdynamicsandtheimportanceofthesensorlocationtodeﬁnethresholds.Aﬁxedoptimal

sensordepthof10cmwasfoundtomanageirrigationfromthevegetativestatetotheendoffruit

development.Thresholdsweredeﬁnedtominimizewaterlosseswhileallowingasufﬁcientsoilwater

availabilityforoptimalcropproduction.Athresholdat10cmdepthof−15kPaisrecommendedforthe

earlygrowthstageand−40kPaduringthefruitformationandmaturationphase.Simulationsshowedthat

thosethresholdsresultedinoptimaltranspirationregardlessofthesoiltexturesothatthismanagement

systemcanconstitutethebasisofanirrigationscheduleforeggplantcropsandpossiblyothervegetable

cropsinsemi-aridregions.

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

1. Introduction

Semi-aridregionsinsub-Saharan Africarelyonirrigationfor agricultural activities during the dry season, characterized by extremetemperatureanddrywindconditions,andanalmosttotal absenceofprecipitation.Agriculturetraditionallytakesplace dur-ingtherainyseason,buttheimpactsofclimatechange,theshift ofrainfallstotheSouth,thegreatvariabilityofinterannualrainfall andtheseverityofdroughtpocketshavemadedryseason agricul-turecrucialforfoodsecurity(FAO,2014).

Waterisascarceresourceinsemi-aridregions,andhighyields aredifﬁculttoobtain.FAO(2014)estimatesthat,in2014,80%ofthe

∗ Correspondingauthorat:Cooperation&DevelopmentCenter(CODEV),Ecole PolytechniqueFédéraledeLausanne(EPFL),Lausanne,Switzerland.

E-mailaddress:[email protected](T.Müller).

foodwasproducedbyfamilyfarmersinasampleof30countries andfurtherstatesthattheymustinnovatetotackleatriple chal-lenge:yieldgrowthtomeettheworld’sneedsforfoodsecurityand betternutrition;environmentalsustainabilitytoprotectsoiland waterresourcesinrelationtotheirownproductivecapacity; pro-ductivitygrowthandlivelihooddiversiﬁcationtoliftthemselves outofpovertyandhunger.

Whiletechnologiessuchasdripirrigationkitsreducethetime spenttoirrigatethecropand improvewaterallocationbyonly irrigating neartheroot zone, estimatingadequate water needs andtimingtomaximizeyieldsremainsachallenge.Irrigationis usuallydoneona visualassessmentofthesoiland plantstate, andproducersmostlyrelyontheirownexperience,often result-inginover-irrigationandwaterlosses.Inthiscontext,therecent developmentofautonomouswirelesssensornetworksoffersnew perspectivesfor precisetriggered irrigation(Barrenetxea et al., 2008;RanquetBouleauetal.,2015).

http://dx.doi.org/10.1016/j.agwat.2016.06.019

(2)

Anappropriateirrigationscheduleaimsatavoidingplantwater stressbyoptimizing thesoilwateravailability intherootzone. Waterstressfirstmodifiestheplant’sturgorpressureandaffects cellgrowthandwallsynthesis(Laioetal.,2001)whichis partic-ularlyproblematicduringtheplant’svegetativeanddevelopment stages.Duringtheplant’smid-seasonandyieldformation,water stresscanbeidentifiedbystomatalclosureleadingtoreduced tran-spirationfollowedbypollinationfailure(Stedutoetal.,2012).In FAO’smodels(Raesetal.,2012),aparameterp,whichcharacterizes thefractionofsoilwaterdepletioninthewholerootzone,isused todeterminethedegreeofwaterstressanditsimpactonyield.This parameterisdifficulttoassesson-site,andothermethodsto man-ageirrigationhavethereforebeeninvestigated.Otherparameters totrackwaterstressarebasedeitherondirectmonitoringofthe plantresponse(tissuewaterpotential,Thompsonetal.,2007,or sapflow,Patakasetal.,2005),onplantremotesensing(infrared thermometry,Taghvaeian etal.,2012)or indirectlyby measur-ingthesoilwater availability (soilwater contentor soilmatric potential).

Managingirrigationusingsoilmatricpotential(SMP)thresholds hasshownapromisingpotentialforsavingwaterandimproving yieldswiththeuseofsimplesensors.Incontrasttosoilwater con-tentmonitoring,SMPthresholdsareless dependentonthesoil texturesincetheSMPisdirectlylinkedtotheplant’srootability touptakewater.AnimportantchallengeofSMPbasedirrigation isthat measurementsaredoneat specificlocationswhichmay notberepresentativeoftheSMPinthewholerootzone,asroot wateruptakedependsonrootdensity.Table1listsselectedrecent scientificarticlesproposingthresholdstotriggerirrigationgiven thecroptype.Itcanbeobservedthatnoclearconsensusseemsto emergefromthosestudiesasexperiment-specificconditionslead togreatdifferencesinoptimalthresholds,evenwitharelatively similarsoiltextureorcroptype.Comparisonsareespecially diffi-cultasthesensorisplacedatdifferentdepthsinasoilprofilewhere wateravailabilityisnothomogeneous.Moststudiesalsopropose thresholdsonlyforthemid-seasonwhentranspirationismaximal, butdo notconsiderpreviousgrowthstageswhere waterlosses duetoevaporationaregreaterandimportantwatersavingsmay beachieved.

Inthiscontext,theresearchprojectInfo4Dourou2.0basedat theEcole PolytechniqueFédéraledeLausanne(EPFL)has devel-opedan innovativeautonomouswireless sensornetwork based on continuous SMP measurements that is adapted to extreme climates (Ranquet Bouleau et al., 2015). Relying on this wire-less sensor network, the main objective of this study was to set the basis for an optimized irrigation management system using SMP measurements that can bemore easilyreproduced, comparedandthatcanprovidesimpleandpractical recommen-dationsforlocalproducersorengineers.Thesystemisprimarily designedforfamilyfarmersinsemi-aridregions,andthegoalwas tousea singleSMP sensorat a certaindepthtomake it more affordable.

Wefirstfocusedontheplantresponsetowaterstressduring thewholeplantgrowthandtheimpactof theirrigation sched-uleonaerialbiomassandrootdevelopment.Inasecondphase,a numericalmodelwasbuiltusingthesoftwareHYDRUS2D/3Din ordertoachieveamorecomprehensiveunderstandingofthe spa-tialsoilwaterdistributionandtooptimizethesensorplacement andirrigationthresholds.Dabachetal.(2013)showedthepotential ofthesoftwaretosimulatetheevolutionoftheSMPandtooptimize theirrigationthreshold,butonlytestedhighthresholdvalues(−3 to−20kPa).Inthispaper,simulationswerecreatedtoassessthe impactofdifferentirrigationdepthsandfrequenciesand thresh-oldsonthewaterfluxes(evaporation,transpiration,leakages).The finaloutcomesofthepaperwere:(i)toselectanoptimizedsensor location;(ii)todefineappropriateirrigationthresholdsforeach

eggplantgrowthstages;(iii)toassesstheinﬂuenceofthesoil tex-tureontheproposedmanagementsystem.

2. Materialsandmethods 2.1. Experimentalsite

The experimentswereconducted in a ruralarea8km away from Ouagadougou,Burkina Faso (12◦2024N, 1◦ 278O). The experimentstookplacefromDecember5,2014toMarch25,2015 onadripirrigationsystemof 200m2 _cultivated_with_eggplants. Thespecies ofeggplantselectedwasKalenda.Before transplan-ting,thesoilwasploughedmanuallytoadepthof10cm.1kg/m2 of a NPK soil amendmentand 0.25kg/50m2 _of _urea_were _also appliedhomogeneouslyoverthecropbeforetransplantation.The dripirrigationkitswereprovidedbythenon-proﬁtsocial enter-prise“InternationalDevelopmentEnterprises”(iDE).The200m2 dripirrigationsystemconsistedof24sublines,8mlong,separated by1mbetweenrows.Eachsublinewasequippedwith15drippers withaspacingof0.5m.Drippersconsistedofsmallmicrotubeswith adischargerateofabout2.5l/h.Theirrigationwaterwaspumped fromadam250mawayandstoredina1m3_reservoir._One egg-plantwastransplantedatabout2cmfromeachmicrotube.Thesoil texturecorrespondedtoacompactsandyclayloamsoil,withvery poororganicmatter.Ahardlayerofferraliticrock,madeofpartially crumblyrockmixedwithsomesandyearth,waslocatedatadepth of25–30cm.

2.2. Irrigationtreatments

Theparcelwasdividedintofoursubplotsconsistingof6sublines each.90eggplantswereplantedoneachsubplot,theyhadatotal canopycoverof17.7m2_at_full_growth._The_irrigation_depth_was cal-culatedbydividingthetotalwatervolumeappliedtothesubplot inlitersbythetotalwettedareaofthedrippersinsquaremeters. Thewettedradiusofeachdripperwasestimatedto0.25mwhich correspondedtotheradiusofthecanopyatfullgrowth.Thefour irrigationtreatmentswerecodedasT150low,T66low,T100high andT66high.Thecodenumber(150/100/66)correspondstothe percentageofwaterneedsthatwereprovidedforeachtreatment. Waterneedsinmm/daywereestablishedbasedonstandardcrop evapotranspiration (ETc)given thecropgrowthstage.Thecode “low”or“high”,identifiesthetypeofschedule.For“low” treat-ments,afixedwateramountof5.6mm(l/m2₎_was_applied_to_each irrigationevent,andtheirrigationfrequencywasdefinedtomeet thecorrespondingpercentageofETc.5.6mmcorrespondedtothe standarddepthappliedbythelocalproducersandwasconsidered lowasitrepresentedonly35%ofthereadilyavailablewater(RAW) (Allenetal.,1998).“High”treatmentsreceivedahigherirrigation depthcorrespondingto150%oftheRAW,whichwasadaptedfor each growthstage becauseof rootgrowth. Thisledtoa lower irrigationfrequencytomeetthecorrespondingwaterneeds.Afixed irrigationschedulewasdefinedforeach treatmentandforeach growthstage,summarizedinTable2.

T150lowisthecontrolexperimentandfollowsthepracticeof localproducers.The“low”irrigationdepthcorrespondedto5.6mm and irrigationwastriggeredtwiceadayas donebyproducers. This practicecorrespondedto providing 150% of theestimated ETcduringthemid-season.ForT66low,thesame“low”irrigation amount was applied but only 66% of the ETc was restored by usinga lowerirrigationfrequency than T150low,sothat water stresswasinduced.T100highreceiveda “high”irrigationdepth and a lower irrigation frequency to meet 100% of ETc. Finally, T66highreceivedthesame“high”irrigationamountbutonly66% ofETcwasprovided.Thedifferenttreatmentsbegan20daysafter

(3)

Table1

LiteraturereviewofproposedSMPirrigationthresholdsfordifferentcropsinthelastdecade.

Author Croptype Threshold[kPa] Sensordepth[cm] Growthstage Soiltype

Oliveiraetal.(2011) Cucumber −30 12.5 Cropdevelopment Dystroferricredlatosol

Oliveiraetal.(2011) Cucumber −15 12.5 Mid-season Dystroferricredlatosol

Bilibioetal.(2010) Eggplant −15 12.5 Mid-season ?

Thompsonetal.(2007) Melon −35 10 Mid-season Sandyloam

Encisoetal.(2009) Onion −30 20 Mid-season Sandyclayloam

Thompsonetal.(2007) Pepper −58 10 Mid-season Sandyloam

Coolongetal.(2012) Pepper −60 20 Mid-season Siltloam

Liuetal.(2012) Chili-Pepper −30to−40 20 Mid-season Sandyloam

Wangetal.(2007b) Potato −25to−35 20 Mid-season Loam

KangandWan(2005) Radish −35to−55 20 Mid-season Siltloam

Wangetal.(2007a) Tomato −50 20 Mid-season Siltloam

Coolongetal.(2011) Tomato −45 20 Mid-season Siltloam

Zhengetal.(2013) Tomato −40 25 Mid-season Silt

MarouelliandSilva(2007) Tomato −35 10 Cropdevelopment Clayeyoxysol

MarouelliandSilva(2007) Tomato −12 15 Mid-season Clayeyoxysol

MarouelliandSilva(2007) Tomato −15 20 Maturation Clayeyoxysol

Wangetal.(2005) Tomato −30 ? Mid-season Gravellyloam

Thompsonetal.(2007) Tomato −38to−58 10 Mid-season Sandyloam

Table2

Irrigationschedulesusedforthefourtreatmentsontheeggplantcrop.ThedifferentgrowthstagesusedbytheFAO(Allenetal.,1998)andtheircorrespondinglengthdeﬁned asdaysaftertransplanting(DAT)arealsoshown.

Growthstage DAT T150low T66low T100high T66high

[–] [days] Frequency Depth Frequency Depth Frequency Depth Frequency Depth [1/day] [mm] [1/day] [mm] [1/day] [mm] [1/day] [mm]

Initialgrowth 0–20 2 5.6 1/1 5.6 1/1 5.6 1/1 5.6

Cropdevelopment 20–60 2 5.6 1/1.5 5.6 1/2 11.3 1/3 11.3

Mid-season 60–100 2 5.6 1/1.25 5.6 1/3 22.6 1/4 22.6

Lateseason 100–120 2 5.6 1/1.5 5.6 1/4 22.6 1/5 22.6

transplanting(DAT),whentheplantswerewellestablished.Those

four treatments allowed us to assess both the impact of the

irrigationschedule(irrigationdepthandfrequency)andtheeffect

ofwaterstress(percentageofETcprovided).

2.3. Cropevapotranspirationandreadilyavailablewater

The reference evapotranspiration (ET0) was calculated

according to the directive from the FAO, using the original

Penman–Monteith equation (Allen et al., 1998). Air

temper-ature, relative humidity and solar radiation were obtained using a Decagon VP-3 sensor for temperature and humidity and a Davis Solar Radiation sensor, which were connected to an automatic meteorological station located in the center of Ouagadougou, 8.4 km away from the experimental site. Wind measurements and precipitation amounts were taken on site formore precisionwitha Davis Anemometerand a Davis Rain Collector. The time resolution of thedata was1minand data wereaccessibleinrealtimeonawebinterface.ET0 calculations werevalidatedbycomparisonwithhistoricaldatafromtheFAO andtheNationalMeteorological InstituteofBurkinaFaso. Crop maximalevaporation(ETe)and transpiration(ETcb)were distin-guishedfromthecropevapotranspiration(ETc)byusingthedual cropcoefﬁcients (ke andkcb)(Allenet al.,1998).Thedualcrop coefﬁcientssuggestedbytheFAOwereusedandwereadaptedto thewindspeedandrelativehumidityassuggestedinAllenetal. (1998).

Thereadilyavailablewater(RAW)wascalculatedbyestimating thesoilmoistureatﬁeldcapacity(fc)andpermanentwiltingpoint (pwp),usingtheaveragefractionoftotalavailablesoilwaterthat canbedepletedfromtherootzone(p)suggestedbytheFAOin Allenetal.(1998)andusingdirectmeasurementsofthemaximum rootingdepth.Table3summarizesclimaticandplantdataforthe differentgrowthstages.

2.4. Soilmeasurements

TheSMPwasmonitoredeveryminuteusingWatermarksensors fromIrrometerwhichwereconnectedtoanautonomouswireless sensornetworkand datawereaccessiblein real-timeona web interface.Foreachtreatment,theSMPwasmeasuredon2plants, at5,10and15cmdepth.Inonecase,thesensorswereplacedat ahorizontaldistanceof5cmfromthedripper,whileonthe sec-ondplant,thedistancewas12cm.Additionally,twosoilmoisture sensors,a 5TEanda5TMfromDecagon,wereplaced closetoa Watermarksensorat10cmdepthtocomparebothmeasurements andtodrawtherelationshipbetweensoilmoistureandSMP. 2.5. Plantmeasurements

Plantgrowthwasmonitoredweeklyduringthewholegrowth, starting20daysaftertransplanting.Measurementsincluded(i)the diameterofthestem,2cmaboveground;(ii)themeandiameter ofthecanopy coverofeacheggplant;(iii)theplantheight;(iv) thetotalnumberofleaves;(v)thenumberofﬂowersand(vi)the weightofharvestedfruits.Foreachtreatment,measurementswere collectedonasampleof10eggplantsselectedrandomlyamonga totalamountof90.

Table3

Estimatedclimaticparameters.Kcisthesinglecropcoefﬁcient;ET0isthereference

evapotranspiration;zristherootdepth;pisthetotalavailablesoilwaterthatcanbe

depletedfromtherootzoneandRAWisthereadilyavailablewater.BasedonAllen etal.(1998). Kc ET0 zr p RAW [–] [mm/day] [m] [-] [mm] Initialgrowth 0.6 5.23 0.1–0.2 0.45 3.6–7.2 Cropdevelopment 0.6-1.1 5.76 0.2–0.4 0.45 7.2–14.4 Mid-season 1.1 6.63 0.4 0.45 14.4 Lateseason 1.04 5.81 0.4 0.45 14.4

(4)

Table4

Soilmodelparameters.ristheresidualwatercontent;pwpisthewatercontentatpermanentwiltingpoint;fcisthewatercontentatﬁeldcapacity;sisthesaturated

watercontent;˛andnarecalibrationparametersandKsisthesaturatedhydraulicconductivity.

r pwp fc s ˛ n Ks

[cm3_cm−3_] _[cm3_cm−3_] _[cm3_cm−3_] _[cm3_cm−3_] _[cm−1_] _[–] _[cm/day]

0.102 0.1054 0.1858 0.315 0.0558 1.6328 15

Therootstructurewasanalyzedbydirectlyextractingtheroot

systemfromthesoil.Thegroundaroundtheplantwasexcavated

anda largevolumeofsoilcontainingthemajorityofrootswas

extracted.Theearthandrockswerethenwashedaway.Samplings

weredone ontwo plants for each treatment at 30, 55 and 75

daysaftertransplanting.Theonedimensionalrootdistributionwas

assessedbyimageprocessing.Apictureoftherootdistribution

wastaken,processedintoablackandwhiteimageandthedensity

withdepthwasmeasuredbysummingupthenumberofblack

pix-elsforeachlayerasalsodonebyPasqualeetal.(2012).Statistical

validationofrootdistributiondifferencesbetweentreatmentswas notpossibleasonlyonetotworootextractionsoccurredforeach treatment.

2.6. Numericalmodel

HYDRUS2D/3D(ˇSim ˚uneketal.,2012)isadedicatedsoftware thatsimulateswater,heatandsolutemovementsintwo dimen-sionalunsaturatedsoils.Itallowsyoutosimulatesoilevaporation, transpirationandrootwateruptake,aswellaswaterstress.The 2.042D-liteversionofthenumericalmodelwasusedtotest differ-entirrigationschedulesandirrigationthresholds,andtoassessthe degreeofwaterstressandtheirrigationamounts.Thesimulation domainconsistedofasimple2Dverticalrectangulardomain.The discretizationofthedomainhadagridspacingof10mmforthe z-coordinateand25mmforthex-coordinate.Theboundary con-ditionswere“AtmosphericBoundaryconditions”forthetopsoil evaporationrate,“VariableFlux1”forthedripperﬂuxesand“Free Drainage”atthebottom.

Theparametersforthesoilhydraulicpropertieswerebasedon thevanGenuchten–Mualemequations(Genuchten,1980).Asoil waterretentioncurve(SWRC)wasdrawnwiththeﬁelddatawhich allowedthecalibrationoftheunknownparametersby minimiz-ingtheRootMeanSquareError(RMSE)betweenthemodeledand measuredSWRC.Thecalibrationmatchedthecharacteristicsofa SandyClayLoamtextureproposedinHYDRUS2D/3Dandasimilar parameterizationwasdonebyMermoudetal.(2005)inan experi-mentalﬁeld17kmawayfromoursite.Theparametersusedforthe modelaresummarizedinTable4.Forcalibrationonly,areduced saturatedhydraulicconductivityof5cm/daywasusedatadepth of300mmtosimulatetherockysoillayer.

Therootwateruptakestressfunctionresponsiblefor transpi-rationreductionwasbasedonthemodelproposedbyGenuchten (1987).Thefollowingvalueswerecalibratedwithfield measure-ments: h50=−50kPa and p=3 which allows an early decrease in transpiration(50% uptake reduction at −50kPa(h50);18% at −30kPa;6%at−20kPa).Thesamecalibrationwasalsousedby Dabach et al.(2015) for aneggplant crop. HYDRUS2D/3Dalso implementsadimensionlesswaterstressindexωc(ˇSim ˚unekand Hopmans,2009), which allowsyou to compensatefor theroot wateruptakereductioninacertainzonebyincreasingthewater uptake inotherpartsof therootzone.Compensationtherefore allowsthesustainmentofmaximaltranspirationevenwhenasmall partoftherootzoneisstressed.ωchasavaluebetween0(full com-pensation)and1(nocompensation).Debetal.(2011)showedthat compensation(ωc<0.5)significantlyimprovesthesimulationofthe wateruptakefromdeeplayersandYadavetal.(2009)confirmed

thatitplaysanimportantroleinmaintainingthetranspirationrate whenwaterstressoccursinthetopsoillayers.Aftercalibration,a ωcvalueof0.7wasselectedforoursimulations.Thespatial distri-butionoftherootwateruptakewasdeﬁnedin2D,basedondirect measurementsoftheextractedrootsystems.

2.7. Triggeredirrigationscenarios

Scenarioswerebuilttoassesstheeffectofdifferentirrigation depthsandthresholdsonwaterstressandwaterconsumption.We used,forallscenarios,similarsoilcalibration,similarwaterstress functionandthesamesimulation duration,aswellasthesame evaporationandtranspirationrates.InHYDRUS2D/3D,irrigation canbetriggeredbyspecifyinganobservationnodewhich corre-spondstothesensorlocation.WhentheSMPfallsbelowadeﬁned valueatthatnode,anirrigationeventistriggeredwithaspeciﬁc irrigationtimeandrate.HYDRUS2D/3Ddoesnotimplementatime lapsebetweenirrigationeventsthatisdifferentfromtheirrigation time.Consequently,ifthewettedfrontofanirrigationeventdoes notreachthedesiredsensordepthwithintheirrigationtime,a secondirrigationeventistriggered,doublingtheirrigationdepth. Thisprecludedmodelingtriggeredirrigationatlowersensordepths than5cmforscenarioswithlowirrigationdepthupto5.6mm.

Twodifferentgrowthperiodswereanalyzed.Theﬁrstperiod correspondedtotheinitialgrowthstage,betweendays10and30 aftertransplanting.Thesecondperiodcorrespondedtothe mid-season,during yieldformation, between80 and 100days after transplanting.Fortheﬁrstperiod,thethresholdstestedwere:−5, −10,−15, −20,−25,−30, −35,−40,−50and −100kPa. These scenarioswerealsotestedwithdifferentirrigationdepths corre-spondingto1.4mm(38%RAW),2.8mm(75%RAW)and5.6mm (150%RAW).Forthemid-seasonperiod,thethresholdswere:−5, −10,−20,−30,−40,−50,−70,−100, −150and −200kPa.The differentirrigation depthscorresponded to5.6mm (38%RAW), 11.3mm(75%RAW)and22.6mm(150%RAW).Forscenarioswith anirrigation lowerthanor equal to5.6mm,thethreshold was locatedatadepthof5cmand5cmawayfromthedripper hori-zontally.Forhigherirrigationdepths,athresholdat10cmdepth wasalsoconsidered.

3. Results

3.1. Soilmatricpotentialandplantgrowth

ContinuousmeasurementsoftheSMPandplantgrowthwere collectedfromdays20–100aftertransplantingforthesensorsat5 and15cmdepth,12cmawayfromthemicrotubes(Fig.1).

InFig.1,duetotheday-to-dayvariabilityoftheweather condi-tions,waterneedsandtheﬁxedirrigationschedule,theSMPdoes notshowacompletelycyclicbehavior,sothatirrigationdoesnot occurforthesamevalueofSMP.Thesensorsattwodifferentdepths illustratethattheSMPintherootzoneisnotconstantwithdepth. TreatmentT150lowkeepsSMPvaluescloseto0kPabecauseofthe frequentirrigationeventsandtheprovisionof150%ofthewater needs.FortreatmentT66low,thesensorat15cmdepthbecomes disconnected fromthe wetted bulb due tothe small irrigation amounts anditsvalue dropsrapidlybelow −200kPa.T100high

(5)

−200 −150 −100 −50 0 20 30 40 50 60 70 80 90 100

Days after transplanting

Soil Mat ric P otential [k P a] Sensor depth 5 cm 15 cm −200 −150 −100 −50 0 20 30 40 50 60 70 80 90 100

Soil Mat ric P otential [k P a] Sensor depth 5 cm 15 cm

Fig.1.EvolutionofthesoilmatricpotentialforT150low,T66low,T100high,T66high (toptobottom)forsensorsat5and15cmdepth,12cmawayfromamicrotube.

andT66highshowlowerSMPvaluesduetothelowerirrigation frequency,butthesoilisrecharged moreindepththanT66low duetothehigherirrigationdepth.On45DAT,averyshortrainy event(0.5mm)occurred,leadingtolowerrootwateruptakeand anincreaseinSMPduringthenextirrigationevent.

TheevolutionofplantgrowthisillustratedinFig.2.Onlythe totalnumberofleavesisshownasanexample,sincetherewasa highcorrelationbetweenthedifferentmeasurements(r>0.8)and statisticalanalysesweresimilar.

TheStudent’st-testwasusedtodetermineifsamplesofplant growthfor eachtreatmentweresigniﬁcantlydifferentinFig.2. Thenormalityofthesampleswasconﬁrmedusinga ShapiroW-ilktest,andsampleswereconsidereddifferentwhenthep-value

0 10 20 30 40 20 30 40 50 60 70 80 90 100

Number of leaves [−] Treatment T150low T66low T100high T66high

Fig.2.Evolutionofthenumberofleavesforalltreatments.Linesshowthemean valueswhileribbonsrepresent1standarddeviation.

ofthet-testwaslowerthan0.05(p<0.05).Theresultsindicatethat plantsfromT100highandT66highbecamesigniﬁcantlydifferent fromT150lowandT66lowstarting52daysaftertransplanting (p-valuebetween0.003and0.037).T66highremainsdifferentuntil theendoftheexperiment,whileT100highwasnolonger signiﬁ-cantlydifferentafter80DAT.

A“non-identified”vasculardisease,which attackedtheroots andledtoripeningoftheplant,infectedthecropatthe begin-ningofthefloweringperiod,60DAT,andwasparticularlysevere inT150lowandT100high.Thesensorswereonlyplacedonhealthy plants,sothatthediseasedidnotaffectthemeasurementsofthe SMP.Attheend oftheexperimentthefollowingpercentagesof plantswereleft:18.6%forT150low,84.9%forT66low,41.8%for T100highand83.7%forT66high.Inordertoanalyzetheeffectof waterstressonplantgrowth,onlytheareaofhealthyplants,which growthwasmainlyinfluencedbytheSMP,wasconsidered.This procedurewasacceptablesinceitwasobservedthatthedisease wasnotdirectlylinkedtohighsoilmoisture.Indeed,fromFig.1, theSMPofT100highreachesvaluesbelow−50kPaevery2–3days, whileT66lowpresentedmuchhigherSMPvaluesat5cmbut suf-feredfromtheleastplantlosses.Fromthisobservationandthe spatialdiffusionofthedisease,itseemsthatthediseasewas ran-domlyspreadinallexperimentsatfirst.T150lowandT100high favoredthediffusionofthediseasetoneighboringplants,asthose treatmentsallowedawidersoilmoisturerechargebetweentwo plantsafteranirrigationevent.Asaresult,thediseasewasinstead linkedtothespatialdistancebetweenplantsandtheconnectionof wettedbulbs.

Table5showsthetotalharvestofeachtreatments.The rela-tiveyieldswerecalculatedbydividingtheharvestweightbythe cropareaof healthy plants. The irrigation water useefﬁciency (IWUE)wascalculatedbydividingtherelativeyieldbythetotal amountof irrigation water appliedand multiplied bythe total croparea.ReportedmeanyieldsforeggplantsinBurkinaFasoand IvoryCoastarearound20T/ha(2kg/m2₎₍_Fondio_et_al.,_2009;_Anon, 2003).

Table5

Marketableharvestsfortheeggplantexperiment.

Harvest Relativeyield IWUE [kg] [kg/m2_] _[kg/m3_]

T150low 10.5 2.12 1.664

T66low 23.7 1.09 1.894

T100high 10.3 0.97 1.221

(6)

Fig.3.Horizontalandverticalrootdensityforalltreatmentsat(a)30DATand(b)55DAT.

3.2. Rootdevelopment

Fig.3showstherootdensitymeasuredbothhorizontallyaway fromadripperand verticallywithdepth, at30 and55DAT.No significantrootdensitychangesoccurredbetween55and75DAT. Ateachgrowthstage,thegeneralpatternofrootlengthdensity for allextractionswas similar,regardlessoftreatment.Density increasessharplyfromthegroundtoadepthofbetween5and 12.5cm,withameanat7cmdepthandthendecreasesrelatively linearlytothemaximalrootdepth.Forthehorizontaldistance,a relativelylineardecreaseinrootwateruptakeuntilthemaximal lengthwasobserved. Such a profile wassimilarto other stud-iesCoelhoandOr(1998)andwellreflectsthewateravailability inthefield.Differencesbetweentreatmentsduetowaterstress are not clearas the analysisrelied only onone sample. Maxi-malrootdepthwasrelativelysimilarfor alltreatmentsandthe majorityoftheroots wassystematicallycontainedintheupper 15–20cm(from82.8to98.7%ofthetotalrootbiomassgiventhe treatment).InFig.3(b),T66lowseemstoinduceahigherroot con-centrationintheupper10cm(77.3%ofrootbiomasscontainedin the0–10cmlayer,21.3%inthe10–20cmlayer),whileT66high pos-sessesamoreconstantrootdensityuntiladepthof20cm(40.8% from0to10cm;42.0%from10to20cm).Thisbehaviorsuggests anadaptation ofthe rootdevelopmentto theirrigation sched-ulewhentheplantissubjecttowaterstress.Rootadaptationto thezoneofhighsoilmoistureforvariousplantspecieswasalso observedbyGorlaetal.(2015),Zotarellietal.(2009)andPheneetal. (1991).

3.3. Modelcalibrationandvalidation

Aftercalculationofthesoilandmeteorologicalparameters, cal-ibrationoftherootwateruptakereductionfunctionwascritical,as itdirectlyinfluenceswaterstress.Calibrationoftheparametersof thatfunction(h50andp)wasdoneusingthedatafromexperiment T66highfrom80to95DAT.Usingthesameclimaticinputandfield dataandtherootzonedistributionmeasuredinthefield,different valuesweretested.TheRMSEbetweenobservedandmodeledSMP at5,10and15cmwasthencalculatedoverthewholesimulation periodandwascomparedwithotherstatisticalparameterssuch astheCoefficientofdetermination(R2_),_the_slope_from_the_linear model,theModelingefficiency(EF)andtheCoefficientofResidual Mass(CRM).Thethreebestsetsofparameterswereh50=−40kPa, p=3;h50=−50kPa, p=3 and h50=−50kPa, p=4. Thesecond set ofparameters wasselectedasitbestsimulatedthedecreasein SMPjustbeforeanirrigationevent(Fig.4),whichwasessentialto correctlycalibratetherootwateruptakereductionfunction.The calibrationwiththeselectedparameterswasthentestedwith dif-ferentvaluesofthewaterstressindexωcwhichisusedforwater uptakecompensation.Avaluebetween0.6and0.8ledtothelowest RMSE.Avalueof0.7wasselectedforfurthersimulationstoallowan earlytranspirationreductionandahighsensitivitytowaterstress. Duetoirregularitiesinthewaterdistributionofthedripsystem andinhomogeneitiesinthesoiltexture,aperfectfitbetweenthe modeledandmeasuredSMPwasnotpossible.Moreover,theroot distributionusedinthemodelwastimeindependentwhichdoes notallowanygrowthormodificationduringthesimulation.

(7)

h50=−50 kPa; p=3 −150 −100 −50 0 −150 −100 −50 0 −150 −100 −50 0 5cm depth 10cm depth 15cm depth 80 85 90

Soil matric potential [kPa]

Hydrus model Field data

Fig.4.ComparisonbetweenmodeledandmeasuredSMPforT66lowat5,10and 15cmdepthfrom80to94DATforthebestsetofparameters.

Theparameters of theselectedroot water uptake reduction function werevalidated by comparing simulated and observed SMPfromtheotherexperiments.Inparticular,itwasveriﬁedthat theminimumSMPvaluesbeforetheirrigationeventswere sim-ilar.Forinstance,for T100high,forthesamesimulation period, usingthebestsetofparameters,theRMSEovertimewere25.7kPa and23.4kPaat5and15cmrespectivelyandtheRMSEbeforethe irrigationeventswere17.9kPaand11.8kPaat5and15cm respec-tively.

Interestingly,foralltreatments, itwasfoundthat the simu-latedwater frontafteranirrigationeventonly reachedadepth of20–25cm.ThiscouldalsobeobservedfromtheSMP measure-ments,wherethesensorsat15cmdepthpartiallyreactedtothe irrigationevents(Fig.1).Fromtherootdensityanalysis,theroot structuredidnotseemtohavebeengreatlyaffectedbytherocky layer,asonly few ﬁnerroots reachedthis depthand were not packedjustaboveit.Itseemsthattherootsdevelopedprimarily intheupper25cmwherewaterwasmostavailable.Thedepthof therootzoneandwettedfrontwasthereforemainlylinkedtothe differentirrigationschedules.For thisreason,forthe hypotheti-calscenarios,themaximalrootdepthandthemaximalhorizontal lengthoftherootsweredeﬁnedtomatchthedimensionofthe wettedbulbsimulatedbythemodel.

Finally,thecalculatedratioofactualovermaximal transpira-tion(Ta/Tmax)for thefourtreatments from80 to 95 DATwere thefollowing:T150low:99.9%;T66low:76.4%;T100high: 84.1% andT66high: 65.3%.These ratiosseemtoaccuratelyreﬂect the magnitudeofwaterstresswhencomparedtothemeasuredcrop yieldinTable5.Itwasconcludedthattranspirationreductionfrom HYDRUS2D/3Dcanbeusedasagoodindicatorofwaterstressfor furthersimulations.

3.4. Impactoftheirrigationthresholdandirrigationdepth

Differentsimulationswerebuiltfortheearlygrowthstageand themid-seasonstagebyvaryingtheirrigationthresholdsandthe irrigationdepth.Fig.5showsthecalculatedratiooftranspiration reduction(Ta/Tmax)andtheratioofirrigationwaterappliedtothe crop(Irr)tothecropmaximalevapotranspiration(ETcmax)forall scenarios.ETcmaxwascalculatedbasedonKcmaxinthedualcrop coefﬁcientasdescribedinAllenetal.(1998)andassumesmaximal soilevaporation(Kr=1).Coloredribbonsweredrawntoshowthe optimalthresholdregiongiventheirrigationdepth.Two parame-terswereused:First,thehighervalueoftheribbonwasselectedto avoidunnecessarywaterlossesfromevaporationandleakages.It waslocatedjustafterthesharpdropoftheirrigation/ETcratioand thestartofaﬂatterzoneinFig.5(b)and(d).Secondly,thelower ribbonvaluecorrespondedtotheonsetoftranspirationreduction (lowerthan99%ofmaximaltranspiration)toavoidwaterstressin Fig.5(a)and(c).

3.4.1. Earlygrowthstage

Fig.5(a)and(b)showstheresultsfortheearlygrowthstage. Theirrigationthresholddecreaseswithincreasingirrigationdepths at5cm, due toa more completerechargeof therootzonesoil moisture,andtheoptimalthresholdvaluescorrespondto−15kPa, −25kPaand−35kPaforanirrigationdepthof1.4,2.8and5.6mm respectively.The irrigationwater needscorrespondingtothose thresholdsarethesame,around42%ofETcmax.Withhigher thresh-olds,toofrequentirrigationsleadtoahighersoilevaporation,while beyondthesethresholds,theirrigationamounts decreasemore slowly,asmostofthewaterlossesareminimized,sothatonly transpirationreductionreducestheirrigationwaterneeds.

Duetothelowirrigationdepths,thethresholdcouldonlyhave beenplacedat5cmdepth.Basedonthesimulationswitha thresh-oldat5cmdepth,thecorrespondingminimumSMPvalueatother depthscanbenumericallymonitored.Fig.6showstheevolutionof theSMPforthethreeselectedscenarios.Withanirrigationdepth of1.4and2.8mm,thecorrespondingSMPat10cmdepthdecreases upto−20kPa.However,duetothelowirrigationdepth,theSMP isnotalwayscompletelyrechargedandfallsbelow₋₂₀kPa.For theirrigationdepthof5.6mm,theSMPat10cmdecreasesupto −15kPa.Below10cmdepth,theSMPhardlyﬂuctuateswithtime duetolowrootwateruptake.

Fortheearlygrowthstage,asensordepthof5cmisadequate buttheoptimalthresholddependsontheirrigationdepth.At5cm depth,athresholdof−15to−20kPaisrecommendedinorderto avoidwaterstressevenforlowirrigationdepths(Fig.5(a)),while keeping water lossesrelatively low even withhigherirrigation depths(Fig.5(b)).Amaximalsensor depthof10cmcanalsobe recommendedsinceevenlowirrigationdepthscanbemonitored, butnotbelow.At10cmdepth,thethresholdhasasmalleroptimal rangebetween−15and−20kPatoavoidwaterstress,thoughthis couldnotbevalidatedbydirectsimulations.

3.4.2. Mid-seasonstage

Fig.5(c)and(d)showstheresultsforthemid-season.Itappears thatthebeginningoftranspirationreductionoccursatrelatively similarthresholds,around−40kPafor11.3mmand−50kPafor 22.6mm.Additionally,itseemsthatathresholdof−30kPawould besufﬁcienttoavoidmostwaterlossesregardlessoftheirrigation depth. It is therefore recommended to use a threshold value between−30 and −40kPa to triggerirrigationat 10cm depth, whichavoidsmostwaterlosseswhilemaintainingmaximal tran-spiration.

(8)

Fig.5.Resultsofallscenariosforvaryingirrigationthresholdsat5cmdepthfortheearlygrowthstageand10cmdepthforthemid-seasonandfordifferentirrigationdepth. (a)and(b)representscenariosfortheearlygrowthstage(10–30DAT);(c)and(d)showtheresultsforthemid-season(60–80DAT);(a)and(c)showthesimulatedcumulative actualtranspirationvolumesoverthecumulativemaximaltranspirationamounts.(b)and(d)representthereductioninirrigationwaterappliedtothecrop,usingtheratio ofcumulativeirrigationamounts(Irr)tothecumulativeamountsofmaximalcropevapotranspiration(ETcmax).Thecoloredribbonsshowtheregionsofoptimalthresholds

giventheirrigationdepth(highervalueavoidswaterlosses,lowervaluelimitstranspirationreduction).(Forinterpretationofthereferencestocolorinthisﬁgurelegend, thereaderisreferredtothewebversionofthearticle.)

3.5. Impactofthesoiltexture

Forthemid-seasonstage,theinﬂuenceofdifferentsoiltextures ontheoptimalityoftheselectedthresholdswasalsoevaluated. Indeed,textureinﬂuencestheSMPandrootdistribution,sothat

itmayimpactonthethreshold,giventhesensordepth.Similarly toFig.5,scenarioswerebuiltbyvaryingtheirrigationthreshold and testingdifferentsoiltypeswitha singleirrigationdepthof 11.3mm.Texturesfromcoarsesoils(sandyloam)toﬁnetextures (silt,clayloam)wereusedbasedontheparametrizationofCarsel

Threshold = −15 [kPa]; depth = 1.4 [mm] Threshold = −25 [kPa]; depth = 2.8 [mm] Threshold = −35 [kPa]; depth = 5.6 [mm]

−60 −40 −20 0

10 15 20 25 30 10 15 20 25 30 10 15 20 25 30

Soil mat ric potential [k P a] Sensor depth 5 cm 10 cm 15 cm 20 cm

(9)

Fig.7.(a)Ratioofactualovermaximaltranspiration;(b)ratioofcumulativeirrigationamounts(Irr)overcumulativemaximalcropevapotranspiration(ETcmax)forthe

mid-season,andfordifferentsoiltextures.

andParrish(1988).Fig.7showstheresults.Thethresholdemerges clearlyforallsoilsat−40kPa,asthereishardlyanytranspiration reduction.Usingathresholdat−30kPaseemslessadequate,since irrigationamountsarestillrelativelyhighfortheﬁnersoiltextures. Itappearsthatbyplacingthesensornearthedepthwhere maxi-malrootwateruptaketakesplace,itispossibletodeﬁneastable thresholdindependentlyofthesoiltexture.

4. Discussion

Twocomplementary approaches were usedin this studyto acquirea complete understandingof the complex relationship betweensoilwaterdynamicsandplantresponse.Thenumerical modelenabledustoconsidertheSMPatmultiplelocationsgiven thedepthandthehorizontaldistancefromthedripper,andnot onlyatasinglepointmeasurement,asitisthecasewithasensor. ThisallowsabetteranalysisofthespatialevolutionoftheSMPand thecorrespondingrootwateruptakeresponse.Inparallel,theﬁeld measurementswereusedtocalibrateandvalidatethemodeland thewaterstressfunction.

4.1. Cropresponsetowaterstress

FieldexperimentsshowthatT150low,thecontroltreatment, ledtooptimalfruityieldandwastheonlyexperimentwhichdid notsufferfromwaterstress.TheSMPwaskeptmostlybetween0 and−15kPabutthesoilwasnotcompletelysaturatedsothatno signiﬁcantsoilaerationproblemsseemtohaveoccurred.The con-stantlywettersoilsurfaceledhowevertohigherwaterlosseswhich ledtoalowerIWUEforT150low(Table5).Duringthecrop devel-opmentstage(20-60DAT),thehighirrigationdepthwitha low frequency(every2days)appliedforT100highledtowaterstress andsuboptimalaerialbiomassdevelopment.Incontrast,restoring only66%ofETcwithalowerirrigationdepthandahigherfrequency didnotinﬂuencetheplantgrowthofT66low.ReferringtotheSMP evolution(Fig.1),itseemspreferabletoirrigateregularlyandto maintaintheSMPabove−50kPainthetop10cm(T66low)rather thantoapplyalowerirrigationfrequency,lettingtheSMPdrop below−50kPaatboth5and15cmdepth(T100high).

Duringthemid-season(60–100DAT),whenrootdepthbecomes maximum,thehighdepthand low frequency of T100highwas bettertoleratedastheplants’biomasscatchesupwiththelevel of T150low and T66low and the ﬁnal yields of T66low and T100highweresimilar.It islikelythatyieldwaslimitedmainly becauseofreducedbiomassdevelopmentforT100highduringthe

developmentstage,whilefruitdevelopmentwaslimitedduring themid-seasonforT66lowduetothepartialprovisionofthewater needs.ItthereforeseemsthataSMPthresholdhigherthan−50kPa at5cmdepthonlyresultsinoptimalyieldswhenahigherirrigation depthrechargesthesoilatleastinthetop15cm.Below−100kPa atboth5and 15cm depth,fruitdevelopmentwasconsiderably reduced(T66high).Asageneralconclusion,eggplantsseemto tol-erateadecreaseinSMPofupto−50kPaifthewholerootzoneis rechargedbytheirrigationevents.

4.2. Thresholdsensitivity

The threshold selected from the different models is clearly dependentonthetranspirationreductionfunction,andthewater stressindex(ωc)whichallowwateruptakecompensation.

Inorder toassess thesensitivityofthethreshold,additional simulationswereperformedwithamoresensitivetranspiration reductionfunctionwithh50=−30kPa.Resultsshowthat transpi-ration reduction occurs earlier, witha decrease of 3.5%with a threshold of −30kPa and of 8.8% with a threshold of −40kPa. It appears therefore that, even with a very sensitive reduction functionthatisexaggeratedforeggplants,transpirationiskept rel-ativelyhigh,sothatthethresholdof−40kPaappearsquiterobust. Theeffectofthewaterstressindex(ωc)onthetranspiration reductionwasalsoevaluatedbyrunningourbestselectedscenario (thresholdof₋₄₀kPaat10cmdepth,withanirrigationdepthof 11.3mm)withdifferentvaluesofωc.Table6showstheratioof actualoverpotentialtranspirationgivendifferentvaluesofωc.

Compensation clearly inﬂuences transpiration reduction. A valueofωcof1oreven0.9howeverdoesnotseemrealisticwithour model.Indeed,inthemodel,therootwateruptakeisdirectlylinked tothespatial rootdistributionwithoutcompensation(ˇSim ˚unek andHopmans,2009),sothatitcannotevolvespatiallyintimeand doesnotadapttothewateravailabilityinthesoil.The compensa-tioncouldthereforebeseenasadynamicadaptationoftheroot zonetothesoilmoisture.Suchrapidrootwateruptake adapta-tionwasdiscussedbyCoelhoandOr(1998)asresultingfromrapid growthofﬁnerootsorchangesinrootconductivity.Aωcvalue

Table6

Ratioofactualoverpotentialtranspiration(Ta/Tp)givendifferentvaluesofωcfor

athresholdof−40kPaat10cmdepthandanirrigationdepthof11.3mm.

ωc 0.5 0.6 0.7 0.8 0.9 1

(10)

0 50 100 150 200 250 −100 −75 −50 −25 0

Soil matric potential [kPa]

Depth [mm]

Fig.8.SMPdistributionwithdepthjustbeforeanirrigationeventforathreshold of−40kPaat10cmdepth.

of0.7representsalowadaptivityoftherootwateruptake,andis

likelyunderestimated.Thethresholdof−40kPaisconsequently

sensitivetowaterstress.

4.3. SMPdistributionandimpactonthesensorlocation

The numerical simulations showed that the root zone SMP

cannotbeconsideredtobehomogeneous.Fig.8showstheSMP

dis-tributionwithdepthjustbeforeanirrigationeventforanirrigation thresholdof−40kPaat10cmdepthanddifferentsoiltextures.It appearsthattheSMPdistributionisdependentonthesoiltexture. Indeed,thecoarsertexturesshowgreaterSMPvariationsindepth thanforﬁnersoils(clayloam,siltyloam,silt).

For instance, if the sensor were placed at 20cm depth, the threshold would be −35kPa for a silty loamtexture and only −25kPafor a sandysoil.Thisismainlydue totherelationship betweensoilmoistureandSMP.Inthecaseofsandyloam,most ofthesoilmoisturehasbeendepletedbelow−20kPa,sothat fur-therwateruptakeleadstoarapiddecreaseinSMP.Additionally, coarsesoilshave lowerunsaturated hydraulic conductivity.For sandyloam,aSMPdropstartedoccurringjustafewhoursbefore theirrigationevent,whererootdensitywasmaximalatadepthof 70mm.Thisillustratesthatwaterstressoccursdifferentlygiventhe soiltexture.Incoarsesoils,stressoccursmorerapidlyandseverely inaspeciﬁczoneoftherootsystem,whileinﬁnersoils,amilder butlongerstressoccursinthewholerootsystem.

In coarse soils, the sensor location is therefore essential: it shouldbeplacedinthezoneofmaximalrootdensityinorderto monitortheonsetofwater stress.Ifthesensoris placedbelow thiszone,thethresholdmustbesethigherinordertoavoid possi-blestressintheupperpartoftherootzone.Inﬁnersoiltextures, theSMPappearsmorehomogeneoussothatthesensorlocationis lessimportantinmonitoringtheonsetofwaterstress.Placingthe sensornearthezoneofmaximalwateruptakeisrecommendedin ordertomeasurearepresentativevalueofwaterstress.

4.4. Recommendedsensorposition

From theﬁeld experiments and numerical simulations, it is recommendedtoplacethesensoratadepthof10cmandata hori-zontaldistanceof5cmfromthedripper.Itisassumedherethatthe dripperislocatedneartheplantstem.Therearedifferentreasons forthisoptimallocation.Fromtheresultsattheearlygrowthstage, thebestsensordepthislocatedbetween5and10cmdepth.Below 10cm depth,almostnovariationsinSMPoccursothatalower

Table7

Summaryoftheproceduretodeterminetheirrigationthresholdgiventheplant growthstage.Thedifferentgrowthstagesarebasedontheclassiﬁcationusedby theFAOinAllenetal.(1998).

Cropstage Threshold(10cmdepth) 10DATtoendoftheinitialgrowth −15kPa

Cropdevelopment Lineardecreasefrom−15kPato−40kPa

Mid-season −40kPa

depthisinadequatetocontrolirrigation(Fig.6).Thisisvalidatedby

theﬁeldmeasurements,whereeachsensorat15cmdepthhardly respondedtotheirrigationeventsat20to40DAT(Fig.1).During themid-season,10cmdepthappearedtobeanadequatesensor depthasitmatchedthedepthofmaximalrootdensityandwater uptake.Usingashallowsensordepthsuchas5cmmayhowever notbeoptimal.Indeed,iftheirrigationdepthislow,onlythetop soilwillbewettedandwaterstressatlowerrootdepthwillnotbe monitored.ThiswasobservedfromtheﬁeldexperimentT66low inFig.1wheretheSMPremainedmostlyabove−40kPaat5cm depthwhiletheSMPdecreasedbelow−200kPaat15cmandled tolimitedcropyield.

Basedonthegoaltomanageirrigationduringthewholecrop growthwithasinglesensoratafixeddepth,weconcludethatusing asensordepthof10cmwillprovidethemostefficientirrigation system.Indeed,thisdepthseemstobethebesttrade-offbetween earlyandmid-seasonstages.Duringtheveryearlystage,this rec-ommendationshouldbeusedcarefully,as10cmwasnotdirectly verifiedbynumericalsimulationsandrootlengthmaydependon theseedlingage.

10cm depthis thereforerecommendedforplantswith shal-lowrootsystems.Consideringsemi-aridregions,thisplacementis deemedadequateasmostsoilsarecompactandusuallyshallow (DembeleandSome,1991).

Regardingthehorizontalplacementofthesensor,amaximal distanceof5cmawayfromtheplantstemwasadequate.Atgreater distance,littleﬂuctuationsinSMPwereobservedduringtheearly growthstage.Duringthemid-season,thisdistanceshowedclear ﬂuctuationsinSMPandbetterresponsetotheirrigationeventsso thatitwasconsideredadequate.Finally,Dabachetal.(2015)also showedthatplacingthesensorcloserthan10cmfromthedripper leadstomorestablemeasurementsgivenvariationsinthespatial soilstructure,and theyrecommendplacingthesensornearthe dripper.

Finally,inthisstudy,weonlyproposeanoptimalsensor loca-tionandthresholdtooptimizeirrigation,butwedonotconsider variationsinthesoilstructureoverthecropordifferencesinroot wateruptakeortranspirationratesbetweenplants.Thenumber ofsensorsneededtoacquirearepresentativemeasurementofthe wholecropstateisnotdiscussedandgoesbeyondthescopeofthis study.

4.5. Recommendedthresholds

Table7summarizestherecommendedthresholdsforthewhole growing period at 10cm depth. The period of establishment betweensowingandtransplantingisnottakenintoaccount.

Theﬁrsttendaysaftertransplantationarecritical,sinceroots maystillbeshallow.Itisrecommendedtoirrigateeveryday dur-ingtendaysandthentostartusingthresholds.Attheearlygrowth stage,resultsconvergedtowardsathresholdof−15kPaat10cm depth,though5cm sensordepthwasalsoadequate.During the cropdevelopmentstage,rootdevelopmentanddeepeningmainly increasethezoneofrootwateruptake.Assumingthesame sensi-tivitytowaterstress(sametranspirationreductionfunction),we proposeloweringthethresholdfrom−15kPato−40kPalinearly

(11)

withtime,reﬂectingthegrowthoftherootsystem.Marouelliand Silva(2007)reportedthatthecropdevelopmentperiodisless sen-sitivetowaterstressfortomatoes,whichisinthesamefamilyas eggplants,sothatevenlowerthresholdsmaybefoundadequate. Inthemid-season,athresholdof−40kPaat10cmdepthallowed themostwatersavingswhilekeepingmaximaltranspirationand wasadequatefordifferentsoiltextures.

Thresholds were found adequate for a wide range of the irrigationdepthat 10cm. However,using a verylow irrigation depthwillresultina smallerwettedareaandrootzone, which mayleadtoalowercapacitytouptakeessentialnutrients.Nutrients uptakewasnotpartofoursimulationsbutshouldbeconsideredin furtherstudies.Onthecontrary,ifmorethan150%oftheRAWis used,leakageswilloccurwhichwillnotbemonitoredbyoursingle sensorsystem.Amoderateirrigationdepthofaround75%ofthe RAWcanberecommended.

Simulationsshowedthatmostwatersavingscanbeachieved attheearlygrowthstageincomparison withthemaximalcrop evapotranspiration(ETcmax).Thisisduetothemuchhighersoil evaporationrateduringthatstage.Ontheotherhand,duringthe mid-season,theoptimalirrigationneedsarelocatedataround90% ofETcmax.Thisisin agreementwiththeFAOdirectivesandthe resultsofLovellietal.(2007)whoshowedthatproviding100%of ETcforeggplantgrowthwasindeedthemostproﬁtableirrigation schedule.

Thecroprootdistributionmayalsoinﬂuencetheadequacyof thethresholdat10cmdepth,sinceadifferentrootdensity pat-ternwillmodifythesoilwaterdynamics.However,literaturehas shownthatmostvegetablecrops(tomato,cucumber,watermelon, squash,onion,etc.)havethemajorityoftheirrootsintheupper 30cm(WeaverandBruner,1927;Zotarellietal.,2009).Moreover, ourexperiments,aswellasCoelhoandOr(1998),showedthatthe rootstructureadaptsitsdensitytothelocationwherewater avail-abilityisoptimized,whichwillbearoundthesensordepthinthe caseofdripirrigation.

Inthecontextofsemi-aridregions,itseemsthatthe recom-mendedsystemmayperformwellindifferentsemi-aridregions. Indeed,climaticconditionsarecharacterizedbyahigh evapora-tiverateandmostsoilsaresandyanddense.Concerningdifferent crops,ﬁeldexperimentsshouldberuntoassesstheirspeciﬁc toler-ancetowaterstress.However,itseemspossiblethatthethresholds proposedinthisstudymaybeappliedtoothervegetablecrops,as theselectedtranspirationreductionfunctionwasrelatively sensi-tivetowaterstress,andastherootdistributionofmostvegetable cropsislikelytobeconcentratedinthetop30cm.

5. Conclusion

Thecombinationof fieldexperimentsand numericalmodels allowedfora betterunderstandingof thecomplex interactions betweenwaterstress,rootwateruptake,soilwaterdynamicsand thresholdsdefinition.Whilethefieldexperimentsallowedusto assessbiomassandyieldproductionincomparisonwithsomelocal SMPmeasurements,themodelallowedamoregeneralized appre-ciationoftherootzonesoilwaterdynamicsasawhole.Numerical simulationsusingHYDRUS2D/3Dappearedtobeapowerfultoolto generalizesite-specificexperiments.Thestudytherefore empha-sizedtheimportanceoftakingintoaccountthesoilwaterdynamics whenrelatingasingleSMPmeasurementtowaterstressinorder toproposereproducibleirrigationthresholds.Inparticular, numer-icalresultsshowedthegreatimpactoftherootdistributionon thesoilwaterdynamicsandtheimportanceofthesensor loca-tiontodefinethresholds.Forabetterunderstandingoftheonset and the dynamics of water stress, more research is needed to linkthe spatial distributionof soil water availability withroot

architectureandtocharacterizethelinkedeffectsonrootwater uptake,compensationandreallocation.Resultsalsoemphasized thegreatpotentialofwatersavingsbeforethemid-season,aperiod duringwhichfewthresholdshavebeenrecommended. Remark-ably,itwasshownthatirrigatingusingasingleSMPsensorat10cm depthwithevolvingthresholdsduringcropgrowthwas appropri-atetoprovideaneggplant,andpossiblyothervegetableplants,with anoptimalinputofwatertooptimizeyieldswhilelimitingmost waterlossesindependentlyofthesoiltexture.Incontrasttomost site-speciﬁcresearches,thosereferencethresholdsweredesigned forpracticalusebylocalproducersinsemi-aridregions.

Acknowledgments

ThisstudyispartoftheprojectInfo4Dourou2.0managedby theCooperation&DevelopmentCenter(CODEV)basedattheEcole PolytechniqueFédéraledeLausanne(EPFL)whichaimstoimprove watermanagementbytheuseofsimplelow-costwirelesssensor networks.We thanktheteamofengineersinBurkinaFasowho offeredanessentialsupporttotheexperiments.Wewarmlythank thenonproﬁt social enterpriseInternational Development Enter-prises(iDE)in BurkinaFaso fortheprovisionoftheircropsand technicalsupportfor theduration ofourexperiments. Wealso thanktheSensorscopecompanythat manufacturedthewireless sensornetworkandofferedtheirtechnicalsupport.PPwishesto thanktheSwissNationalScienceFoundationforﬁnancialsupport throughthegrantREMEDY(PP00P2-153028/1).

References

Allen,R.G.,Pereira,L.S.,RaesDirk,Martin,S.,1998.Cropevapotranspiration– Guidelinesforcomputingcropwaterrequirements–FAOIrrigationand drainagepaper56.Rome.http://www.kimberly.uidaho.edu/water/fao56/ fao56.pdf.

Anon,2003.Analysedesrésultatsdel’enquètemaraichèrecamapgne1996à1997. TechnicalReport.Ministèredel’agriculturedel’hydrauliqueetdesressources halieutiques,Secrétariatgénéral,Directiongénéraledesprévisionsetdes statistiquesagricoles.Directiondesstatistiquesagricoles,Ouagadougou.

Barrenetxea,G.,Ingelrest,F.,Schaefer,G.,Vetterli,M.,2008.TheHitchhiker’sguide tosuccessfulwirelesssensornetworkdeployments.In:Proceedingsofthe6th ACMconferenceonEmbeddednetworksensorsystems–SenSys‘08.ACM Press,NewYork,NY,USA,pp.43–56,http://dx.doi.org/10.1145/1460412. 1460418.

Bilibio,C.,Carvalho,J.a.,Martins,M.,Rezende,F.C.,Freitas,E.a.,Gomes,L.a.a.,2010. Vegetativegrowthandyieldofeggplantunderdifferentsoilwatertensions. Rev.Brasil.Eng.Agríc.Ambient.14,730–735, http://dx.doi.org/10.1590/S1415-43662010000700007.

Carsel,R.F.,Parrish,R.S.,1988.Developingjointprobabilitydistributionsofsoil waterretentioncharacteristics.WaterResour.Res.24,755–769,http://dx.doi. org/10.1029/WR024i005p00755.

Coelho,E.F.,Or,D.,1998.Rootdistributionandwateruptakepatternsofcorn undersurfaceandsubsurfacedripirrigation.PlantSoil206,123–136,http:// dx.doi.org/10.1023/A:1004325219804.

Coolong,T.,Snyder,J.,Warner,R.,Strang,J.,Surendran,S.,2012.Therelationship betweensoilwaterpotential,environmentalfactors,andplantmoisturestatus forpoblanopeppergrownusingtensiometer-scheduledirrigation.Int.J.Veg. Sci.18,137–152,http://dx.doi.org/10.1080/19315260.2011.591483. Coolong,T.,Surendran,S.,Warner,R.,2011.Evaluationofirrigationthresholdand

durationfortomatogrowninasiltloamsoil.HortTechnology21,466–473

http://horttech.ashspublications.org/content/21/4/466.short.

Dabach,S.,Lazarovitch,N., ˇSimunek,J.,Shani,U.,2013.Numericalinvestigationof irrigationschedulingbasedonsoilwaterstatus.Irrig.Sci.31,27–36,http://dx. doi.org/10.1007/s00271-011-0289-x.

Dabach,S.,Shani,U.,Lazarovitch,N.,2015.Optimaltensiometerplacementfor high-frequencysubsurfacedripirrigationmanagementinheterogeneoussoils. Agric.WaterManage.152,91–98,http://dx.doi.org/10.1016/j.agwat.2015.01. 003.

Deb,S.K.,Shukla,M.K.,Mexal,J.G.,2011.Numericalmodelingofwaterﬂuxesinthe rootzoneofamaturepecanorchard.SoilSci.Soc.Am.J.75,1667–1680,http:// dx.doi.org/10.2136/sssaj2011.0086.

Dembele,Y.,Some,L.,1991.PropriétésHydrodynamiquesdesPrincipauxTypesde solduBurkinaFaso.INERA,Ouagadougou.

Enciso,J.,Wiedenfeld,B.,Jifon,J.,Nelson,S.,2009.Onionyieldandqualityresponse totwoirrigationschedulingstrategies.Sci.Hortic.120,301–305,http://dx.doi. org/10.1016/j.scienta.2008.11.004.

(12)

FAO,2014.Climate-SmartAgricultureSourcebook.FoodandAgriculture OrganizationoftheUnitedNations,Romehttp://www.fao.org/docrep/018/ i3325e/i3325e00.htm.

FAO,2014.InnovationinFamilyFarming.Number2014inTheStateofFoodand Agriculture.FoodandAgricultureOrganizationoftheUnitedNations,Rome

http://www.fao.org/publications/sofa/2014/en/.

Fondio,L.,N’Tamon,L.,Hala,F.,Dijdji,H.,2009.Evaluationagronomiquedesix cultivarsd’aubergineafricaine(Solanumspp.)delanouvellecollectiondes planteslégumièresduCNRA.Agron.Afr.20,69–79,http://dx.doi.org/10.4314/ aga.v20i1.1737.

vanGenuchten,M.T.,1980.Aclosed-formequationforpredictingthehydraulic conductivityofunsaturatedsoils.SoilSci.Soc.Am.J.44,892–898,http://dx. doi.org/10.2136/sssaj1980.03615995004400050002x.

vanGenuchten,M.T.,1987.Anumericalmodelforwaterandsolute

movementinandbelowtherootzone.ResearchReportNo121.U.S.Salinity Laboratory,USDA,ARS,Riverside,CAhttps://books.google.ch/

books?id=sPe5YgEACAAJ.

Gorla,L.,Signarbieux,C.,Turberg,P.,Buttler,A.,Perona,P.,2015.Transientresponse ofSalixcuttingstochangingwaterlevelregimes.WaterResour.Res.51, 1758–1774,http://dx.doi.org/10.1002/2014WR015543arXiv:2014WR016527. Kang,Y.,Wan,S.,2005.Effectofsoilwaterpotentialonradish(RaphanussativusL.)

growthandwateruseunderdripirrigation.Sci.Hortic.106,275–292,http:// dx.doi.org/10.1016/j.scienta.2005.03.012.

Laio,F.,Porporato,A.,Fernandez-Illescas,C.,Rodriguez-Iturbe,I.,2001.Plantsin water-controlledecosystems:activeroleinhydrologicprocessesandresponse towaterstress.Adv.WaterResour.24,745–762,http://dx.doi.org/10.1016/ S0309-1708(01)00007-0.

Liu,H.,Yang,H.,Zheng,J.,Jia,D.,Wang,J.,Li,Y.,Huang,G.,2012.Irrigation schedulingstrategiesbasedonsoilmatricpotentialonyieldandfruitquality ofmulched-dripirrigatedchilipepperinNorthwestChina.Agric.Water Manage.115,232–241,http://dx.doi.org/10.1016/j.agwat.2012.09.009. Lovelli,S.,Perniola,M.,Ferrara,A.,DiTommaso,T.,2007.Yieldresponsefactorto

water(Ky)andwateruseefﬁciencyofCarthamustinctoriusL.andSolanum melongenaL.Agric.WaterManage.92,73–80,http://dx.doi.org/10.1016/j. agwat.2007.05.005.

Marouelli,W.A.,Silva,W.L.C.,2007.Watertensionthresholdsforprocessing tomatoesunderdripirrigationinCentralBrazil.Irrig.Sci.25,411–418,http:// dx.doi.org/10.1007/s00271-006-0056-6.

Mermoud,a.,Tamini,T.,Yacouba,H.,2005.Impactsofdifferentirrigationschedules onthewaterbalancecomponentsofanonioncropinasemi-aridzone.Agric. WaterManage.77,282–295,http://dx.doi.org/10.1016/j.agwat.2004.09.033. Oliveira,E.C.,Carvalho,J.D.a.,Silva,W.G.D.,Rezende,F.C.,Almeida,W.F.D.,2011. EffectsofwaterdeﬁcitintwophenologicalstagesonproductionofJapanese cucumbercultivedingreenhouse.Eng.Agríc.31,676–686,http://dx.doi.org/ 10.1590/S0100-69162011000400006.

Pasquale,N.,Perona,P.,Francis,R.,Burlando,P.,2012.Effectsofstreamﬂow variabilityontheverticalrootdensitydistributionofwillowcutting experiments.Ecol.Eng.40,167–172,http://dx.doi.org/10.1016/j.ecoleng.2011. 12.002.

Patakas,A.,Noitsakis,B.,Chouzouri,A.,2005.Optimizationofirrigationwateruse ingrapevinesusingtherelationshipbetweentranspirationandplantwater status.Agric.Ecosyst.Environ.106,253–259,http://dx.doi.org/10.1016/j.agee. 2004.10.013.

Phene,C.,Davis,K.,Hutmacher,R.,Bar-Yosef,B.,Meek,D.,Misaki,J.,1991.Effectof highfrequencysurfaceandsubsurfacedripirrigationonrootdistributionof sweetcorn.Irrig.Sci.12,135–140,http://dx.doi.org/10.1007/BF00192284. Raes,D.,Steduto,P.,Hsiao,T.C.,Fereres,E.,2012.Chapter3:Calculation

procedures.In:AquacropReferenceManualverion4.0–ReferenceManual. FAO–FoodandAgricultureOrganizationoftheUnitedNations,Rome,pp.125.

RanquetBouleau,C.,Baracchini,T.,Barrenetxea,G.,Repetti,A.,Bolay,J.C.,2015. Low-costwirelesssensornetworksfordrylandirrigationagriculturein BurkinaFaso.In:TechnologiesforDevelopment.SpringerInternational Publishing,pp.19–31,http://dx.doi.org/10.1007/978-3-319-16247-83. Steduto,P.,Hsiao,T.C.,Fereres,E.,Raes,D.,2012.CropYieldResponsetoWater–

FAOIrrigationandDrainagePaperNo.66.Rome.http://www.fao.org/docrep/ 016/i2800e/i2800e00.htm.

ˇSim ˚unek,J.,vanGenuchten,M.T., ˇSejna,M.,2012.TheHYDRUSSoftwarePackage forSimulatingtheTwo-andThree-DimensionalMovementofWater,Heat, andMultipleSolutesinVariably-SaturatedPorousMediaTechnical,Technical Manual,Version2.0.PC-Progress,Prague,CzechRepublic.

ˇSim ˚unek,J.,Hopmans,J.W.,2009.Modelingcompensatedrootwaterandnutrient uptake.Ecol.Model.220,505–521,http://dx.doi.org/10.1016/j.ecolmodel. 2008.11.004.

Taghvaeian,S.,Chávez,J.,Hansen,N.,2012.Infraredthermometrytoestimatecrop waterstressindexandwateruseofirrigatedmaizeinNortheasternColorado. RemoteSens.4,3619–3637,http://dx.doi.org/10.3390/rs4113619.

Thompson,R.,Gallardo,M.,Valdez,L.,Fernández,M.,2007.Usingplantwater statustodeﬁnethresholdvaluesforirrigationmanagementofvegetablecrops usingsoilmoisturesensors.Agric.WaterManage.88,147–158,http://dx.doi. org/10.1016/j.agwat.2006.10.007.

Wang,D.,Kang,Y.,Wan,S.,2007a.Effectofsoilmatricpotentialontomatoyield andwateruseunderdripirrigationcondition.Agric.WaterManage.87, 180–186,http://dx.doi.org/10.1016/j.agwat.2006.06.021.

Wang,F.X.,Kang,Y.,Liu,S.P.,Hou,X.Y.,2007b.Effectsofsoilmatricpotentialon potatogrowthunderdripirrigationintheNorthChinaPlain.Agric.Water Manage.88,34–42,http://dx.doi.org/10.1016/j.agwat.2006.08.006. Wang,Q.,Klassen,W.,Li,Y.,Codallo,M.,Abdul-Baki,A.a.,2005.Inﬂuenceofcover

cropsandirrigationratesontomatoyieldsandqualityinasubtropicalregion. HortScience40,2125–2131http://handle.nal.usda.gov/10113/19049. Weaver,J.E.,Bruner,W.E.,1927.RootDevelopmentofVegetableCrops.

McGraw-HillBookCompany,Incorporatedhttps://sustainablefarmer.com/ pdﬂibrary/library-rootdevelopment.pdf.

Yadav,B.K.,Mathur,S.,Siebel,M.A.,2009.Soilmoisturedynamicsmodeling consideringtherootcompensationmechanismforwateruptakebyplants.J. Hydrol.Eng.14,913–922,http://dx.doi.org/10.1061/(ASCE)HE.1943-5584. 0000066.

Zheng,J.,Huang,G.,Jia,D.,Wang,J.,Mota,M.,Pereira,L.S.,Huang,Q.,Xu,X.,Liu,H., 2013.Responsesofdripirrigatedtomato(SolanumlycopersicumL.)yield, qualityandwaterproductivitytovarioussoilmatricpotentialthresholdsinan aridregionofNorthwestChina.Agric.WaterManage.129,181–193,http://dx. doi.org/10.1016/j.agwat.2013.08.001.

Zotarelli,L.,Scholberg,J.M.,Dukes,M.D.,Mu ˜noz-Carpena,R.,Icerman,J.,2009. Tomatoyield,biomassaccumulation,rootdistributionandirrigationwateruse efﬁciencyonasandysoil,asaffectedbynitrogenrateandirrigation

scheduling.Agric.WaterManage.96,23–34,http://dx.doi.org/10.1016/j.agwat. 2008.06.007.