smart systems for water management · empowering water consumers through smart metering: evidence...
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SMARTSYSTEMSFORWATERMANAGEMENTModelling,Simulation,AnalyticsandICTforBehaviouralChange
22-25August2016,MonteVerità–Switzerland
BOOKOFABSTRACTSEditedbyAndreaCastellettiandAndreaEmilioRizzoli
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TheSmartSystemforWaterManagementSymposiumandSummerSchoolisaninitiativeoftheSmartH2Oproject
whichismemberoftheICT4Watercluster
TheSmartH2OprojectreceivesfundingfromtheEuropeanCommission
TheconferenceissupportedbyCongressiStefanoFranscini,adepartmentofETHZürichanditishostedatCentroMonteVerità,inAscona,Switzerland,withpartialsupportfromtheSwissNationalResearchFund
AndreaCastellettiandAndreaEmilioRizzoliacknowledgesupportfromtheirinstitutions,respectivelyPolitecnicodiMilanoandSUPSI
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CONFERENCEPROGRAMMENote:thepresentationsallocatedintotheworkshopslotswillhavealengthof30minutesmaximum,theremainderofthetimeisforworkshopdiscussion.
Monday22ndofAugust
9:30–10:00-WelcomeaddressbythedirectorsofCentroStefanoFranscini
10:00–11:00-Waterresourceeconomicsandfinance-GregCharacklis,UniversityofNorthCarolinaatChapelHill,USA
11:00–12:00-Waterpricingpoliciesandconsumerbehaviour-JulienHarouandCharlesRougé,UniversityofManchester,UK
12:00–14:00Lunch
14:00–15:00Integratedmodellingofdemandandsupply.Theroleofhydroeconomicmodels-ManuelPulidoVelasquez,UniversitatPolitecnicadeValencia,Spain
15:00–16:00Behavioralinterventionstosuccessfullyreduceresidentialwaterconsumption-VerenaTiefenbeck,ETHZurich,CH
16:00–18:00Workshop-Thedriversofwateruserbehaviour:socialnormsandeconomicreasons
Empoweringwaterconsumersthroughsmartmetering:evidencefromafieldstudyinaresidentialsuburbofMontpellier(southofFrance)-MarielleMontginoul-Irstea–UMRG-Eau,MontpellierFrance
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Tuesday–23rdofAugust
9:00–10:00-Synergisticwaterandenergydemandmodeling,management,andconservation-DavidRosenberg,UtahStateUniversity,USA
10:00–11:00-Economicandenergyanalysisofhouseholdwaterconservation-JayLund,UCDavis,USA
11:00–12:00-Forecastingwaterdemand-WojciechFroelich,UniversityofSilesia,Poland
12:00–14:00Lunch
14:00–15:00-Modellingwateruserbehaviour:fromsmartmetereddatatoagentbasedmodelling-MatteoGiuliani,PolitecnicodiMilano,Italy&AlessandroFacchini,SUPSI,CH
15:00–16:00-HardwareandsoftwaretoolsforpreciseEndUsedisaggregation-FranciscoArreguidelaCruz,UPV,Spain
16:00–16:30-Stochasticgenerationofresidentialwaterend-usedemandtraces–AndreaCominola,PolitecnicodiMilano,Italy
16:30-18:00Workshop-Understandingandmodellingthebehaviourofwaterusers
AFrameworkforReal-TimeSpatiallyDistributedDemandEstimationandForecasting,DominicL.Boccelli,UniversityofCincinnati,Cincinnati,OH,USA
Wednesday24thofAugust
9:00–10:00MultiobjectiveWaterManagementUnderUncertainty-PatrickM.Reed,CornellUniversityUSA
10:00–11:00ICTsolutionsforrealtimesmartwatermanagement-LydiaVamvakeridou&DraganSavic,UniversityofExeter,UK
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11:00–12:00StandardizationActivitiesandGapsforSmartSustainableCities-GabrielAnzaldi,EURECAT,Spain
12:00-13:00Lunch
13:00–14:00Newcontroltechniquesforsmartwatersystems-PantelisSopasakis,IMTLucca,Italy
14:00–16:00-Workshop-InnovationinICTforwatermanagement
TheGIS-integratedFREEWATplatformasanICTtoolforsustainablewaterresourcesmanagement.GiovannaDeFilippis-ScuolaSuperioreSant’Anna,Pisa(Italy)
Hydra3D:ATooltoSimulateHydricResourcesScenarios.JavierDíaz,,LINTI,LaPlataNationalUniversity,BuenosAires(Argentina)
16:00–18:00Publicevent–Increasingtheawarenessonwateruse
Thursday25thofAugust
9:00–10:00-WaterSavingsClustering:Whichtypesofhouseholdsrespondbesttosocialnormsmessaging?-WilliamHolleran,WaterSmart,CA,USA
10:00–11:00Gamificationforwaterutilities-PieroFraternali,PolitecnicodiMilano,Italy,IsabelMicheel,JasminkoNovak,EuropeanInstituteforParticipatoryMedia,Berlin
11:00–11:15Awardceremony:bestyoungresearcheraward
11:15–12:00Plenarysession:thefuturechallengesofurbanwatermanagementPaneldiscussionwithJayLund,LydiaVamvakeridou,PatrickReed,GregCharacklis,WilliamHolleran,andDavidRosenberg.ModeratedbyAndreaE.Rizzoli.
12:00Closing
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ABSTRACTSOFTUTORIALS
Theme:Thedriversofwateruserbehaviour:socialnormsandeconomicreasons
Waterresourceeconomicsandfinance
GregCharacklis,UniversityofNorthCarolinaatChapelHill,USA
Theparticipantswillbeexposedtotheprinciplesofwaterresourceeconomicsinamanagement/policycontext,withadditionalattentiontothefinancingchallenges(andpotentialsolutions)thataccompanymoresophisticatedmanagementstrategies.
Waterpricingpoliciesandconsumerbehaviour
JulienHarouandCharlesRougé,UniversityofManchester,UK
Smartmetersandnewtypesofinteractionwithconsumersmakeemergenewhorizonsinwaterpricing,includingpricingstructureswheretheconsumerbillislinkedtoshortand/orlongtermwaterscarcity.Inthislecturewewillanalysehownewpricingstructurecanactuallyaffectconsumerbehaviour.
Integratedmodellingofdemandandsupply.Theroleofhydroeconomicmodels
ManuelPulidoVelasquezandFranciscoArreguidelaCruz,UniversitatPolitecnicadeValencia,Spain.
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Overviewofapproachesfortheeconomiccharacterizationofurbanwaterdemands(eg.simplepoint-expansionmethod,econometricapproaches,mathprogramming,etc)anduseintheassessmentofconsumerandproducersurplus.Introductiontohydroeconomicmodelsintegratingdemandsandsupply;applicationtotheassessmentoftheimpactsofdroughts(scarcitycost)andtheconsequencesofdifferentwatermanagementandplanningpolicies(usingreliabilityindicatorsandeconomicnetbenefits).
Gamificationforwaterutilities
PieroFraternali,PolitecnicodiMilano,Italy,IsabelMicheel,JasminkoNovak,EuropeanInstituteforParticipatoryMedia,Berlin
Gamificationisgainingmomentumasatooltomotivateandengagecustomers.Inthisworkshopweshowhowitcanalsobesuccessfullyappliedinordertomodulateurbanwaterdemand,thusprovidinganinvaluabletooltowaterutilities.Intheafternoonworkshop,theparticipantswillexplorenewideasandsolutionsforeffectivecustomerengagementinaninteractivesession.
Behavioralinterventionstosuccessfullyreduceresidentialwaterconsumption
VerenaTiefenbeck,ETHZurich,CH
WaterheatingisthesecondlargestenergyenduseinEuropeanandU.S.households,makingshoweringoneofthemostenergy-intensivebehaviorsweengageinonadailybasis.Yetmostindividualshaveaverylimitedunderstanding-andfundamentalmisconceptions-oftheirenergyandwaterconsumptionathome.Inthisworkshop,wediscusstheimpactofdifferentfeedbackstrategiestoreduceenergyandwaterconsumptionintheshower.Inparticular,wewillcomparebehavior-specificfeedbackthatisprovidedin
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realtimewithotherdemandmanagementstrategies(includingflowrestrictorsandfeedbackonahousehold'saggregatedresourceconsumption).Basedonaseriesofrecentrandomizedcontrolledfieldtrialsindifferentcountries,wewillinvestigatewhyreal-timefeedbackinducessuchalargebehaviorchange,analyzeeffectpersistenceandcosteffectiveness,andevaluatewhichsegmentsofthepopulationareparticularlyresponsivetothiskindofbehavioralintervention.
WaterSavingsClustering:Whichtypesofhouseholdsrespondbesttosocialnormsmessaging?
WilliamHolleran,WaterSmart,CA,USA
WaterSmartSoftwarehasdatafromover30RandomizedControlTrialimplementationsacrosstheUnitedStatesofitswaterconservationandcustomerengagementprogram.Leveragingthatdatawithasyntheticcontrolsmodelwillallowcalculationsofindividuallevelsavings.Applyingatime-seriesclassificationmodeltothesavingsatamonthly,weeklyanddailylevelwillrevealcharacteristicsthatwillimproveunderstandingofhowsocialnormsbasedmessagingvariesinitsimpactonindividualbehaviors.Thiswillinformfutureprogramdesignandallowfortargetingofspecificgroupstomaximizeprogramimpact.
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Theme-Understandingandmodellingthebehaviourofwaterusers
Synergisticwaterandenergydemandmodeling,management,andconservation
DavidE.Rosenberg,UtahStateUniversity,UT,USA
Welinkdetailedend-useanalysisofresidentialwaterandassociatedenergyusestostochasticoptimizationtoidentifythecost-effectivemixofconservationactionsresidentialuserssuppliedbyawatersystemcanadopttomeetsystem-widesynergisticwaterandenergyconservationtargets.Theend-useanalysisdrawsfromadatabasecontainingtiming,duration,frequency,andvolumeinformationof1.4millionwater-useeventsrecordedfor800householdsin11U.S.andCanadiancitiesovertwoormoreweeksofhighfrequencywaterusemonitoringoverthelast15years.Energyusesincludetheembeddedenergytocollect,treat,convey,anddistributewatertohouseholds,energytoheatwaterwithinthehouseholdforhotwateruses,andembeddedenergytocollectandtreatwastewater.Thisdataisusedtosamplealarge,simulatedsetofhouseholdswithindoorandoutdoorwaterappliances,behaviors,andconservationpotentialspecifictothestudycity.Thestochasticoptimizationprogramthenidentifiesthemixofhouseholdapplianceandbehavioralchangeconservationactionsthatminimizecity-widecoststoachievesystem-widewaterandenergyreductiontargets.Theminimizationisalsosubjecttolowerandupperboundsonthenumberofconservationactionsimplementsandupperboundsonhouseholds’paybackperiodforconservationactions.Resultsidentifyfeasiblecity-widecollaborativewaterandenergyconservationtargets,selectandsizewaterandenergyconservationprograms,identifysynergiesandtradeoffsbetweenwaterandenergy,andquantifypaybackperiodsforhouseholdconservationactions.Additionally,thepresentationwillshareapproachesUtahStateUniversityisnowdevelopingtoorganizeandmanagehigh-frequencyend-
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usedataanddeploylow-costsmartmeterstomonitorwateruseandsavingsbynon-residential,institutional,andresidentialusers.
Economicandenergyanalysisofhouseholdwaterconservation
JayLund,UCDavis,CA,USA
Householdwaterconservationwillbeexaminedforitsenergy,wateruse,andemissionimpacts.Theoptimizationofhouseholdconservationactivitiesfortheseobjectiveswillbeexaminedanddiscussed.Additionaldiscussionandanalysiswillincludehowchangesinprobabilisticwatersupplyreliabilityaffectoptimizedwateruserconservationactivities.
Forecastingwaterdemand
WojciechFroelich,UniversityofSilesia,Poland
Thistutoriallectureconsidersselectedissuesrelatedtowaterdemandforecasting.Attheurbanlevel,theforecastingisappliedtotheefficientmanagementofwaterresourcesandasapartofthesystemthatcontrolspressureinthewaterdistributionsystem.Atthehouseholdlevel,theforecastingisexploitedbythedecisionsupportsystem,encouragingconsumerstosavewater.Theoreticalpreliminariestotimeseriesarepresentedtogetherwithabriefoverviewofthemostknownforecastingmodels.Theonlineavailabilityofwaterdemanddataisassumed.Theconceptsofgrowingandslidingwindowsarepresentedtoillustratedifferentmodesoflearningmodels.Practicalmethodstodealwithmissingvaluesandoutliersarealsopresented.Inaddition,itisshownhowtorecognizestationarity,linearityandotherfeaturesofwaterdemandtimeseries.Theknowledgeofthesefeatureshelpstoselectthemosteffectiveforecastingmodelforthegiventimeseries.Differentmethodsofdealingwithseasonalityintimeseriesarepresented,includingautoregression,seasonaladjustment,andtheapplicationofdummyvariables.Anexampleofcombiningforecasts
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generatedbydifferentmodelsispresented.Alltheoreticalpresentationsareillustratedbypracticalexamples.TheKNIMEtoolkitandtheRsoftwarepackageareusedforthispurpose.Anintroductiontobothtoolsismade.Inallofthepresentedexperiments,scale-independentforecastingerrorsarecalculated.
Modellingwateruserbehaviour:fromsmartmetereddatatoagentbasedmodelling
AndreaCastelletti,MatteoGiuliani,AndreaCominola,PolitecnicodiMilano,Italy,AlessandroFacchini,AndreaE.Rizzoli,IDSIAUSI/SUPSI,CH
Smartmeteredconsumptiondataallowsophisticateddatadrivenmodellingofwateruserbehaviours.Inthissession,weanalysehowtodisaggregatewaterconsumptionintoenduses,howtobuildwateruserprofilesusingbigdataminingtechniqueandhowtoanalysesocialinteractionthroughanagentbasedplatform.Modelsareusedtounderstandandpredictuserbehavioursaswellastosimulatesocialnormsmechanismsactivatedbyexternalstimuli(e.g.awarenesscampaign,pricingschemes).
HardwareandsoftwaretoolsforpreciseEndUsedisaggregation
FranciscoArreguiDeLaCruz,UniversitatPolitecnicadeValencia,Spain
ResidentialwaterEndUsedisaggregationisoneofthemostpowerfultoolsavailabletounderstandwaterdemandandalsotodesigntrulyeffectivewaterconsumptionreductionstrategies.EndUsedisaggregationallowsforamuchbetterunderstandingnotonlyofthetechnicalcharacteristicsoftheappliancesbutalsothewaycustomersinteractwiththem.
ThedevelopmentandstandardizationofAMIandAMRtechnologieshasfacilitatedtheremotemeteringofcustomers.However,theirlowest-possible-costdesignandworkingliferequirementsonlyallow,inmostcases,forhourly/dailymonitoring.Unfortunately,areliabledisaggregation
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requiresthattheflowsignalisavailableforanalysisatshortertimeintervals(10secondsorless).Thisreadingfrequencyexponentiallyincreasesthecommunicationcosts,theamountofdatatobeprocessedandthenumberofcommerciallyavailablehardwareoptions.
Takingintoaccountalltheseconstraintsaspecificcombinationofhardwareandsoftwarehasbeenmadeavailabletoreducethecostahighresolutionmonitoringofcustomers.Thissetincludes:
• Highresolutionpositivedisplacementmeterequippedwithapulseemitter.
• Anewloggercapableof:o Storingthetimeofoccurrenceofthepulseswitharesolutionof
1ms.Thisspecialfeaturegeneratesanundistortedflowtracesignalfromthemeterreadytobeprocessbythesoftware.
o SendingthedatatoadedicatedFTPserveronceeveryfewhours.
• Web-basedenduseanalysissoftwareo Alldata(theoriginalcomingfromtheloggersandtheprocessed
pulses)isstoredinanonlinedatabasewithouttheneedofhumanintervention.
o Advanceprocessingcapabilitiestoimprovetheanalysisofoverlappedconsumption.
o Flexibleandpowerfulconfigurationtoolstodefinedifferentendusesandtypesofusers.
ThesoftwareandhardwaredesignedallowforamuchpreciseEndUseclassificationwhichcanserveforresearchersandotherinterestgroupstodevelopmoreaccuratealgorithmsforautomaticEndUseclassificationtools.
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Theme-InnovationinICTforwatermanagement
MultiobjectiveWaterManagementUnderUncertainty
PatrickM.Reed,CornellUniversityUSA
Computingpowerischeap,optimizationalgorithmshaveadvanced,visualizationshavegottenmoresophisticated,andmanysystemsoptimizationframeworkshavefoundtheirwayintocommercialuse,yetfornearly25yearswehavecontinuedtoformulateandsolvewatermanagementproblemslargelythesameway.Manyoftheinnovationsdiscussedabovehaveoccurredinisolation,andthedesignofcomplexengineeredwaterresourcessystemsremainsplaguedbyneglecteduncertaintiesandnarrowdefinitionsofoptimalitythatfailtoencompasscriticalperformancetradeoffs.Thissessionwillintroduceemergingmultiobjectivedesigntoolsthatenhancesystemsengineeringdesignunderuncertainty.Beyondthefocusonmultiobjectiveoptimization,thecoursewillcoverrelevantresearchrelatedtoconstructivedecision-aidingtheoryanddecision-biasesrelatedtorisk,andrecentadvancesinvisualanalyticsthathavebeendemonstratedtoenhancedesignprocesses.Acoregoalofthiscourseistoshowthestate-of-the-artforintegratinghumanintelligenceandcomputationalpowertoeffectivelyexploredesignhypotheses,discovercriticalsystemtradeoffs,andfacilitaterobustdesigndecisions.
ICTsolutionsforrealtimesmartwatermanagement
LydiaVamvakeridou&DraganSavic,UniversityofExeter,UK
ThepotentialandthescientificchallengesfacingICTsolutionsforrealtimesmartwatermanagementarepresented.Forinstanceoneofthemainchallengesisthemanagementandextractionofinformationfromvastamountsofhighresolutionconsumptiondata;a“BigData”challenge,andhowitcanbefaced.
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StandardizationActivitiesandGapsforSmartSustainableCities
GabrielAnzaldi,EURECAT,Spain
InthistutorialwewillexploreaproposedframeworkofstandardsandmethodologiesforinteroperabilitywithinSmartSustainableCities,andwewillalsoworkinaproposalofstandardizationroadmap,takingintoconsiderationtheactivitiescurrentlyundertakenbythevariousstandardsdevelopingorganizationsandforums.Thetutorialwillincludeareviewofthei)SSCneedsforstandardizationandinteroperability;ii)currentframeworksofSSCstandards;ii)SSCrelatedStandardDevelopmentOrganizationsactivities;iii)outlinesofSSCstandardneedsandgapanalysis.
Newcontroltechniquesforsmartwatersystems
PantelisSopasakis,IMTLucca,Italy
Inthistutorialsessionwewilldiscusshowdynamicalmodelingcombinedwithtime-seriesanalysisandoptimizationcanleadtoanefficientmanagementofcomplexwatersystems.Wewillintroducekeyperformanceindicatorstoevaluatetheperformanceofthecontrolledsystemandformulateaneconomicmodelpredictivecontrol(EMPC)schemetoaddresstheprescribedcontrolobjectives.Wewillalsoseehowwecanharnessthecomputationalpowerofgraphicscardstoacceleratecomplexcomputationsinvolvedinourcontrolproblems.
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ABSTRACTSOFWORKSHOPPAPERS
Thefollowingabstracts,listedinalphabeticalorderofthepresentingauthor(underlined),summarisepresentationsthatwillbediscussedduringtheaccompanyingworkshops.Thislistisnotcomplete,andduringtheworkshopsitispossiblethatotherpresentationswillbedeliveredbesidesthoselistedhere.
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AFrameworkforReal-TimeSpatiallyDistributedDemandEstimationandForecastingJinduanChen,IDModeling,Arcadia,CA,USADominicL.Boccelli,UniversityofCincinnati,Cincinnati,OH,USA
Short-termwaterdemandforecastsarevaluablefordistributionsystemoperatorscontrollingtheproduction,storageanddeliveryofdrinkingwater.Incertainproblems,likereal-timepumpscheduling,thecycleofdataacquisition,modelcomputation,anddecision-makingistime-sensitive,andrequiresanautomaticproceduretohandlethetransferofinformationbetweendatasources,aforecastingmodel,andtheoperator.OurinitialresearchfocusedontheTimeSeriesForecastingFramework(TSFF)-aflexibleframeworkthataccommodatesdifferentdatasourcesandforecastingmodels-wasperformedasthefirststeptobridgethegapbetweenforecastingalgorithmsandengineeringpracticewithrespecttototalsystemdemand.OurcurrentresearchisextendingtheTSFFfromtotalsystemdemandtospatiallydistributeddemandestimationandforecasting.Anautoregressiveintegratedmovingaverage(ARIMA)timeseriesmodelshasbeenvectorized(VARIMA)toincludethepotentialspatialcorrelationindemandsthroughtheerrorcovariancematrix,andtheresultingestimation/forecastingalgorithmisformulatedasaDynamicBayesianNetwork.UsingdatacollectedfromautilitySCADAsystem(e.g.,pressures,flowrates,tanklevels,etc),theparametersoftheVARIMAmodelaswellasthedemandsatagiventimestepwillbeestimatedwithanExpectation-Maximization(E-M)algorithm,whichwasdesignedtocomputethemaximumlikelihoodestimatesformodelswithincompleteobservations.AspartoftheE-Malgorithm,adistributionofdemandsisgeneratedthatreflecttheuncertaintyinthecurrentdemandestimates.Thisinformation,whencoupledwiththeupdatedVARIMAmodelparameterestimates,canbeutilizedtoforecastspatiallycorrelateddemandsaswellastheuncertaintyinfuturedemandestimates.Thisworkwillpresenttheoverallmodellingframeworkandourpreliminarystudiesintotheuseoftheframeworkforperformingsystemwidedemandestimation.
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TheGIS-integratedFREEWATplatformasanICTtoolforsustainablewaterresourcesmanagementGiovannaDeFilippis-ScuolaSuperioreSant’Anna,Pisa(Italy)
IacopoBorsi-TEASISTEMIS.p.A.,Pisa(Italy)LauraFoglia-UCDavis,CA,USAMassimilianoCannata-ISTSUPSI,SwitzerlandVioletaVelascoMansilla-CSIC,Barcelona(Spain)RudyRossetto,ScuolaSuperioreSant’Anna-Pisa(Italy)
Duringthelastdecades,overexploitationoftheavailablefreshwaterresourcescauses qualitative and quantitative degradation of accessible ground- andsurface-watersupply,duetogrowinghumanpressureandclimatechanges.Forthisreason,addressingpropermanagementandplanningstrategiesisofparamount importance to restore unbalanced situations and/or preventfuturescenariosofdegradation.
As pointed out by regulations and recommendations of the EU and theEuropeanandEnvironmentAgency(EuropeanEnvironmentAgency,2004),developinginnovativesoftwaretoolstoaddresswatermanagementissuesisimperativeandnumericalmodelsrepresentvaluabletoolstoaddressthistaskas, thanks to their predictive function, they can help for the application ofplanningandmanagementstrategies.
TheEUHORIZON2020FREEWATproject (FREEandopensourcesoftwaretools for WATer resource management; Rossetto et al., 2015) aims atsimplifying the application of EU-water related Directives (EU, 2000), bydeveloping an open source and public domain, GIS-integrated platform forplanningandmanagementofground-andsurface-waterresources.
Suchplatformisexpectedtohelpinfacilitatingthewidespreaduseofcomplexmodeling environments and in producing scientifically and technicallysoundingdecisionandpolicymaking.Theseobjectiveswillbeachievedtakingadvantage of storing, managing and visualizing large spatial datasets andadoptingaparticipatoryapproach,toinvolvestakeholdersnotonlyinthefinalstageofresultdiscussion,butalsoduringthephaseofscenariosetting.
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The FREEWAT platform is integrated within the open source QGIS GIS,allowing the simulationof thewholehydrological cycle and the analysis ofseveral water data, where input and output data are managed through aSpatiaLite Data Base Management System (DBMS).The FREEWAThydrological model is based on fully distributed and physically-basednumerical codes,mainly from the open source USGSMODFLOW family. Assuch, the FREEWAT platform is conceived as a canvas, where severalsimulationcodesmightbevirtuallyintegrated.
FREEWATcapabilities include:modelling solute transportprocesses in the
saturated and unsaturated zones;pre-processing tools for the analysis,interpretation and visualization of hydrochemical and hydrogeologicaldata;tools for time-series processing;a module for sensitivity analysis,
calibration and parameter estimation;a module devoted to water
management and planning.Within the FREEWAT project, fourteen casestudieswillbesetupthroughoutEU,Switzerland,Turkey,UkraineandAfrica(with the cooperation of UNESCO-IHP), to demonstrate the full platformcapabilitiesatdifferentscales.AmongthetoolsintegratedinFREEWAT,theFarmProcess(FMP)embeddedinMODFLOW-OWHM(Hansonetal.,2014)isaremarkablemodule,whichallowstosimulateconjunctiveuseofground-andsurface-water,withparticular focusonruralenvironments,underdemand-driven and supply- constrained conditions, taking also into accountconstraintsonwellabstractionandwater-rightsrankingofwateraccountingunits.TheFMPallowstodynamicallyintegrateinfiltration,surfacerunoffanddeeppercolationcomponents,toeffectivelybalancecropwaterdemandandsupplyfrombothsourcesofwater.ItisfurthercoupledwiththeCropGrowthModule,afreeandopensourcemodulebasedontheEPICfamilymodels,toestimatecropwateruptakeandprovidecropyieldatharvest.
REFERENCES
EU,2000.Directive2000/60/ECoftheEuropeanParliamentandoftheCouncilestablishingaframeworkfortheCommunityactioninthefieldofwaterpolicy.OfficialJournal(OJL327)on22December2000.
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EuropeanEnvironmentAgency,2004.AgricultureandtheenvironmentintheEUaccessioncountries-ImplicationsofapplyingtheEUcommonagriculturalpolicy.EnvironmentalissuereportNo.37,55pp.
HansonRT,BoyceSE,SchmidW,HughesJD,MehlSM,LeakeSA,MaddockT,NiswongerRG,2014.One-WaterHydrologicFlowModel(MODFLOW-OWHM).U.S.GeologicalSurvey,Reston,Virginia.
RossettoR,BorsiI,FogliaL,2015.FREEWAT:FREEandopensourcesoftwaretoolsforWATerresourcemanagement.RendicontiOnlineSocietaGeologicaItaliana,35:252-255.DOI:10.3301/ROL.2015.113
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Hydra3D:ATooltoSimulateHydricResourcesScenariosJavierDíaz,LauraFava,AnabellaDiGrazia,EduardoNola-LINTI,LaPlataNationalUniversity,BuenosAires(Argentina)JuanPabloZamora-INTA,Maimará.Jujuy(Argentina)
Freshwater is a vulnerable and a finite resource, essential to support life,urban development, and the environment. It is one of themost importantresources of the planet and also, one of the most damaged by pollution,overexploitation,populationgrowth,energycrisesandclimatechange.Onechallenge that the Water Resources Integrated Management has to facenowadaysisrelatedtothetaskofbuildingskillsindifferentworkspacesandeducational settings, whether formal or informal, to achieve populationawareness on efficient water use. Information and CommunicationTechnologies offer tools that enable the exchange of experiences andknowledgeamonglearninggroups.Despitethis,duringtrainingworkshopsonwater technical capabilities, debates are held using physical models andposterswithmapsthatareexplainedorally.SpecialistsonHydricResourcesusepaperandphysicalmodelstocarryouttheiractivitiesthataretoanalyze,buildmock-ups,modifyandcreatehydricscenariosondifferentareas(Setta,2014).Theuseofpapersandstaticscalephysicalmodelshasitslimitations,especiallywhen itbecomesnecessary toworkwithhigh complexityhydricscenarios.
ThispaperpresentsHydra3D,developedinDiGrazia(2015),acomputertoolthat enables the simulation and recreation of hydric scenarios on a virtualground.Thissoftwareallowsfortheanalysisofdifferentalternativesofwaterresource allocation taking into account the interaction between varioussectorsofdemand(agricultural,urbanandindustrial).Thiscomputertoolletstheuserbuildahydricscenariobyincorporatingpredefinedcomponentsandaddingelementsonavirtualgeographicspace.Thecomponentsthatcanbeaddedrepresentdifferentelementsthattakepartinahydricscenarioinreallife,forexample:ariver,anindustry,anagriculturaldistrict,acity,amountain,
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amine,etc.Allofthesecomponentshavetheirownbehaviorthatwillaffectthescenarioandcanbeconfiguredbytheuser.Thegroundelevationandthegeneralstateofthescenario(theseason,forexample)canalsobemodified.Thetoolexecutesasimulationthat,dependingontheconfigurationmadebytheuser,allowsthevisualizationof theresulting indicators thatarepartofhydricresourcemanagement.Builtscenarioscanbesavedallowingtheuserthepossibilityofsharinghiscreationwithothers.ReportscanbeexportedinPDF format giving theuser a numeric representationof the scenariobeingexecuted.
It isexpectedthatthedevelopmentofthistoolwillprovidesupport fortheimplementation of capacity building processes in different areas andeducational levels, forresearchandforthetrainingofgraduatestudentsbyprovidingthemwithatoolthatletsthembuildmock-upsandexploredifferentscenariosofwatermanagementinavisualand3Denvironment.ThistoolwillbeusedinthetrainingprocessofHydricTechnicalCapabilitiesaimedatruralcommunitiesandruraldevelopment institutionsof thePunaJujeña(Bilbao,2012). Itmay also be used by other specialists during their training,morespecifically for the M.S. in Integrated Water Resources Management tocomplete exercises where the layout of water scenarios and its furtheranalysisisrequired(UNL,2016).
REFERENCES
Bilbao,L.,García,J.,Guzman,P.,Narmona,L.,Ariza,I.,Ochoa,V.,Zamora,J.P.,2012.PrimerprocesodeformaciónencapacidadestécnicashídricasdelaprovinciadeCatamarca-Intercambiodesaberesentretécnicosyproductoressobreelaprovechamientodelaguaencomunidadesrurales.EditorialCopiar.
DiGrazzia,A.,Nola.E.,2015.Hydra3Dunaherramientaparasimulacióndeescenariosdegestiónderecursoshídricos,availablefromhttp://edunola.com.ar/juegos/PruebaWin.rarorhttp://edunola.com.ar/juegos/SimulacionWeb.html
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Setta,D.,2014.SelanzóelProcesodeFormaciónenCapacidadesTécnicasHídricasComunitariasenlapunajujeña.ComunicaciónIPAFRegiónNOA,available:http://inta.gob.ar/noticias/se-lanzo-el-proceso-de-formacion-en-capacidades-tecnicas-hidricas-comunitarias-en-la-puna-jujena/.
Kofi,A.,Matsuura,K.,Gordon,Y.,2007.WaterforPeopleWaterforLife.WorldWaterAssessmentProgramme.http://unesdoc.unesco.org/images/0012/001295/129556e.pdf
UNL,2016,MaestríaenGestiónIntegradadelosRecursosHídricos,FacultaddeIngenieríayCienciasHídricas,UniversidadNacionaldelLitoral,SantaFé,Argentina.Available:http://fich.unl.edu.ar/carrera.php?id=25
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Empoweringwaterconsumersthroughsmartmetering:evidencefromafieldstudyinaresidentialsuburbofMontpellier(southofFrance)MarielleMontginoul-Irstea–UMRG-Eau,MontpellierFranceArnaudVestier-MontpellierMéditerranéeMétropole,France,
Inacontextcharacterizedbyincreasingwaterscarcity,Frenchenvironmentallaws highly incite water managers to improve network performances byreducingwaterleaksanduserstosavewater.Smartmeteringseemsanewinteresting solution to reach suchobjectives, by informingwatermanagersand users on real-time consumption (Kendel and Lazaric, 2015). ThiscommunicationaimstoexploreitscurrentadoptioninFrancebyurbanusersofthisnewtechnology,whichseemstheoreticallydeliverarangeofbenefitseitherforwatermanagersorforwaterusers.Inparticular,itallowsforurbanwaterusers to consult theirdailywater consumptionand to createSMSorEmail-alertmessagestoinformthemwhenwaterconsumptionexceedsapre-definedthreshold.Butresultsshowthatthistechnologyisnotadopted,withaverylowsubscriptionrate.Isitbecauseusersandespeciallyhouseholdsareill-informedorill-intentionedagainstthisnewtechnology?Inordertobetterunderstandreasonsunderlyingsuchalowrate(Darby,2010,Fischer-Lokouand al, 2004, Kendel and Lazaric, 2015), we conducted a natural fieldexperimentstudyinaresidentialsuburbofMontpellier(SouthofFrance).261households where equipped from January 2015 with smart meters andofficiallyinformedinJune-Julyoftheassociatedservices(readingdailywaterconsumption, defining warning system in case of own-defined level ofoverconsumption). We took special care to inform them, in particular bytestingtwomodesofindividualcommunication(bymailorface-to-face),buttheadoptionisstilllow.Wethenconductedahouseholdsurveytoidentifythepotentialobstaclesandtoknowtheirsocialrepresentations(Ajzen,1991)ofwords“water”and“remotereading”.77householdsanswered,revealingnotechnical obstacles (like low interests/levels in new technologies) andhighlighting that remote reading seems related mostly to positiveconnotations(likeuseful,simple,allowstobewarnedofawaterleakorofan
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excesslevelofconsumption).Furtherresearcheshavethennowtofocusonthelaststep,thatonewhichgoesfromintentiontoaction.Inthatway,wewillinparticularexplorepotentialitiesofdifferenttypesofsmartwaterpricingbysimulatingtheimpactofsuchsystemsonhouseholds’waterbehaviorfromonadatasetof23,000watermeterslocatedinMontpelliermetropolis.
REFERENCES
Ajzen,I.,1991.TheoriesofCognitiveSelf-Regulation.Thetheoryofplannedbehavior.OrganizationalBehaviorandHumanDecisionProcesses,50(2),179-211
Darby,S.,2010."SmartMetering:WhatPotentialforHouseholderEngagement?"BuildingResearch&Information,38(5),442-57
Davies,K.;C.Doolan;R.VanDenHonertandR.Shi,2014."Water-SavingImpactsofSmartMeterTechnology:AnEmpirical5Year,Whole-of-CommunityStudyinSydney,Australia."WaterResourcesResearch,50(9),7348-58
Fischer-Lokou,J.;GuéguenN.,Lépy,N.,2004."EffetsDeLaCommunicationParRéseauxInformatiquesVersusEnFace-À-FaceSurLaReprésentationRéciproqueDesNégociateursEtLeurPriseDeDécision."BulletindePsychologie,57(5),525-3
Kendel,A.,Lazaric,N.,2015."TheDiffusionofSmartMetersinFrance.ADiscussionoftheEmpiricalEvidenceandtheImplicationsforSmartCities."JournalofStrategyandManagement,8(3),231-44