1. Dataintensivehydrologicmodeling: ACloudstrategyforintegratingPIHM,GIS, andWebServices LorneLeonard ChrisDuffy Gopal Bhatt Xuan Yu Civil&EnvironmentalEngineering,PSU, UniversityPark,PA, UnitedStates.

2. OurBigGoal Tobeabletorapidly prototypeanywatershed modelintheworldanytime Yes,anywhere Dorealtimeforecastingandanalysisto improveourmodels UsingNationalDatasetsofETVs Data Intensive

3. Issues DataComputationallyIntensive! 100sTerabytesofETVdatatomodelwatersheds anywhereintheUSA 1000sTerabytesofdataforaroundtheworld. Federaldataserversareslow NocentraldatastoreforourETVdataneeds ComplexWorkflowstoautomatedataandmodel developmentprocessing Computationrequirementsvaryperproject ITisexpensive!Wearefocusedonresearchonly

4. TheappealoftheCloud Cloudcomputingenablesusto: haveaccesstoDataIntensiveandHPC computationalneedsdynamically tobescalable dodataintensiveoperationsnearHPCforfaster access Enableotherresearchersandeducatorstouse ourscientificsoftwareviathewebwithoutthe needtoinstallandmaintainsoftwareand systems

5. OurdefinitionofCloud Dynamicallyscalable(virtualizedresources),from Desktop,HPCclustertoNCSABlueWaters,grid Resourcesareprovidedasawebbasedservice (data,software) DataIntensiveandparallelcomputing Privatecloudtoprivatecloudconduitbetween PSUandNCSAforhydrologicalresearch Thisisaprototype!

6. PIHMandtheCloud:WhatisPIHM Fullycoupledmultiprocessdistributedhydrological model Usessemidiscretefinitevolumemethod Unstructuredmesh(TIN) http://www.pihm.psu.edu

7. 2268HUC8 103,444HUC12

8. OurStrategy

9. OurStrategy

10. OurStrategy AtmosphericForcing(precipitation, snowcover,wind,relativehumidity, temperature, netradiation,albedo, photosyntheticatmosphericradiation, leafareaindex) Digitalelevationmodels River/StreamDischarge Soil(class,hydrologicproperties) Groundwater(levels,extent, hydrogeologicproperties) Lake/Reservoir/Wetlands(levels,extent) LandCover/Use(biomass, humaninfrastructure,demography, ecosystemdisturbance) WaterUse

11. OurStrategy AtmosphericForcing(precipitation, snowcover,wind,relativehumidity, temperature, netradiation,albedo, photosyntheticatmosphericradiation, leafareaindex) Digitalelevationmodels River/StreamDischarge Soil(class,hydrologicproperties) Groundwater(levels,extent, hydrogeologicproperties) Lake/Reservoir/Wetlands(levels,extent) LandCover/Use(biomass, humaninfrastructure,demography, ecosystemdisturbance) WaterUse

12. PIHMCloudReAnalysisandForecast WithNCSAwearedevelopinga PIHMcloudprototypeto distributethePIHMwebservice workflowandmodel componentsoverthecloudfor researchandeducation. Calibratemodels spawn100s ofdataflowexecution parameterstoprocess, compute,analyzeandvisualize thetransformedresults.

13. PIHMCloudReAnalysisandForecast WithNCSAwearedevelopinga PIHMcloudprototypeto distributethePIHMwebservice workflowandmodel componentsoverthecloudfor researchandeducation. Calibratemodels spawn100s ofdataflowexecution parameterstoprocess, compute,analyzeandvisualize thetransformedresults.

14. PIHMCloudReAnalysisandForecast WithNCSAwearedevelopinga PIHMcloudprototypeto distributethePIHMwebservice workflowandmodel componentsoverthecloudfor researchandeducation. Calibratemodels spawn100s ofdataflowexecution parameterstoprocess, compute,analyzeandvisualize thetransformedresults.

15. ExampleofPIHMWebServices

16. ExampleofPIHMWebServices

17. ExampleofPIHMWebServices

18. ExampleofPIHMWebServices

19. ExampleofPIHMWebServices

20. ExampleofPIHMWebServices

21. ArcPIHM PIHMwillsoonbeavailableasa toolboxforESRIusers Developmentplansinclude developingprotocolstoencourage furthermodularitysoother developerscanplugandplaycode intothePIHMworkflow.For example,otherPhysicengines, datasetsetc ConsumeCUAHSIHydroServer, HydroGML resources

22. InternationalCZOsitesat CreteandPlynlimon

23. PIHMCloudForecastExample Realtimeforecasting

24. Conclusion Data&ComputationallyIntensiveWatershed Simulations! 1000sTerabytesofdatarequiredtomodelany watershedintheUSA Workflowstoautomatedataprocessingand distributethecomputationonthecloud Whatisneededisfastaccesstodatacenters thatareclosetoHPCresources

25. Thankyouforlistening Visithttp://www.pihm.psu.edu Formoreinformationandupdates Kumar,M.,G.Bhatt,andC.J.Duffy,2009,Anefficientdomaindecompositionframeworkforaccurate representationofgeodataindistributedhydrologicmodels,IJGIS. Kumar,M.,G.Bhatt,andC.J.Duffy,2008,TheRoleofPhysical,NumericalandDataCouplingina MesoscaleWatershedModel,AdvancesinWaterResources. Bhatt,G.,M.Kumar,andC.J.Duffy,2008,Bridgingthegapbetweengeohydrologicdataand distributedhydrologicmodeling,InProceedingsofInternationalCongressonEnvironmentalModeling andSoftware