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CUAHSI Hydrologic Information Systems

CUAHSI Hydrologic Information Systems. By David R. Maidment

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CUAHSI Hydrologic Information Systems

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  1. CUAHSI Hydrologic Information Systems By David R. Maidment With support from many collaborators: Ilya Zaslavsky, Reza Wahadj, Chaitan Baru, Praveen Kumar, Michael Piasecki, Rick Hooper, Jon Duncan, David Tarboton, Jeff Horsburgh, Venkat Lakshmi, Chunmaio Zheng, Xu Liang, Yao Liang, Ken Reckhow, Upmanu Lall, LeRoy Poff, Dennis Lettenmaier, Barbara Minsker, …… And many graduate students and post-docs: Venkatesh Merwade, Tim Whiteaker, Jon Goodall, Gil Strassberg, Ben Ruddell, Luis Bermudez, Bora Boran, …… Thanks to everyone for all their help!

  2. CUAHSI Hydrologic Information Systems

  3. Environmental Cyberinfrastructure • Part of NSF Cyberinfrastructure program • CUAHSI Hydrologic Information Systems is one of several pilot projects – CUAHSI, CLEANER, ORION, NEON, …..

  4. Project co-PI Collaborator CUAHSI Hydrologic Information System

  5. See http://www.cuahsi.org/docs/HISStatusSept15.pdf Summary of knowledge to date in the CUAHSI HIS project Your comments and feedback are welcome: maidment@mail.utexas.edu HIS Status Report Available

  6. HIS Goals • Hydrologic Data Access System – better access to a large volume of high quality hydrologic data • Support for Observatories – synthesizing hydrologic data for a region • Advancement of Hydrologic Science – data modeling and advanced analysis • Hydrologic Education – better data in the classroom, basin-focused teaching

  7. HIS Goals • Hydrologic Data Access System – better access to a large volume of high quality hydrologic data • Support for Observatories – synthesizing hydrologic data for a region • Advancement of Hydrologic Science – data modeling and advanced analysis • Hydrologic Education – better data in the classroom, basin-focused teaching

  8. HIS User Assessment (Chapter 4 in Status Report) Which of the four HIS goals is most important to you? Data Access Observatory support Science Education

  9. CUAHSI Hydrologic Data Access System(HDAS) NCDC NASA EPA NWS USGS Observatory Data A common data window for accessing, viewing and downloading hydrologic information

  10. USGSNWIS website provides manual query and download capabilities for data at ~ 1.4 million locations in the US CUASHI web services for NWIS provide automated query and download capabilities National Water Information System http://waterdata.usgs.gov/nwis “Get the web pages out of the way”

  11. NWIS Station Information in HDAS http://river.sdsc.edu/HDAS

  12. Charting Data in HDAS Data Downloads Executed Here

  13. Web Services Web application: Data Portal • Your application • Excel, ArcGIS, Matlab • Fortran, C/C++, Visual Basic • Hydrologic model • ……………. • Your operating system • Windows, Unix, Linux, Mac Internet Simple Open Access Protocol Web Services Library

  14. CUAHSI Web Services Library for NWIS http://river.sdsc.edu/NWISTS/nwis.asmx These web services are available now for you to use in your programming

  15. Utah State Time Series Analyst(developed by Jeff Horsburgh) http://water.usu.edu/nwisanalyst/ -- operates on CUAHSI web services -- operates on local data for Neuse basin http://water.usu.edu/analyzer/

  16. http://public.ornl.gov/ameriflux/ Ameriflux site map Building each web service requires a site map and a web services library Ameriflux towers measure vertical fluxes of water, heat, CO2 Web services library

  17. Accessing Ameriflux data directly from Excel using CUAHSI web services

  18. Numerical Models Prediction HSPF Sensor Arrays NGDC NWS NCDC USGS NWIS NCEP Air-Q MM5 Individual Samples Data Centers Page 3 Description of Data Michael Piasecki is our expert on this complex subject METADATA (see Chapter 5 of Status Report for details) Drexel University, College of Engineering

  19. CLEANER-CUAHSI Cybercollaboratory • A common portal for web applications resident at many locations • User support and feedback forums • Do collaborative research using shared tools and dialog with a group of scientists • CLEANER—CUAHSI joint projects http://cleaner.ncsa.uiuc.edu/cybercollab/ Thanks to Barbara Minsker and NCSA for hosting this service for us This service is still under development

  20. HIS Goals • Hydrologic Data Access System – get me the data I want quickly and painlessly • Support for Observatories – synthesizing hydrologic data for a region • Advancement of Hydrologic Science – data modeling and advanced analysis • Hydrologic Education – better data in the classroom, basin-focused teaching

  21. Digital Watershed How can hydrologists integrate observed and modeled data from various sources into a single description of the environment?

  22. Digital Watershed Hydrologic Observation Data Geospatial Data (GIS) (Relational database) Digital Watershed Remote Sensing Data Weather and Climate Data (EOS-HDF) (NetCDF) A digital watershed is a synthesis of hydrologic observation data, geospatial data, remote sensing data and weather and climate data into a connected database for a hydrologic region

  23. A relational database stored in Access, PostgreSQL, SQL/Server, …. Stores observation data made at points Repository for summary data from sensor networks Access data through web interfaces Hydrologic Observations Database Streamflow Groundwater levels Precipitation & Climate Soil moisture data Water Quality Flux tower data

  24. Hydrologic Observations Data Model (Draft version) Relationships • CUAHSI review conducted by David Tarboton with 22 responses • Redesign done by David and Jeff Horsburgh

  25. ProposedCUAHSI Observations Data Model(for details see chap 6 of status report)

  26. Digital Watershed:Prototype for the Neuse basin (See Chapter 8 in the Status Report for details)

  27. Neuse Atmospheric Water • Daily precipitation data from NCDC gages • Nexrad daily rainfall rasters • Land surface – atmosphere fluxes from North American Regional Reanalysis of climate

  28. Streamflow, water quality hydrologic observational data GIS: River network, water bodies, watersheds, monitoring points Land cover, soils, MODIS remote sensing (Praveen Kumar and Venkat Lakshmi) Neuse Surface Water MODIS Terrain and Land Cover

  29. Neuse Basin: Coastal aquifer system Section line Beaufort Aquifer * From USGS, Water Resources Data Report of North Carolina for WY 2002

  30. Neuse Groundwater Geovolumes of hydrogeologic units from US Geological survey (GMS)

  31. GeoVolume – 3D representation of the surface and subsurface Geovolume Geovolume with groundwater model cells Geovolume of layered soil texture for the Neuse basin

  32. HIS Goals • Hydrologic Data Access System – better access to a large volume of high quality hydrologic data • Support for Observatories – synthesizing hydrologic data for a region • Advancement of Hydrologic Science – data modeling and advanced analysis • Hydrologic Education – better data in the classroom, basin-focused teaching

  33. Hydrologic Science • It is as important to represent hydrologic environments precisely with data as it is to represent hydrologic processes with equations • Hydrologic Process Science • Equations, simulation models, prediction, • Hydrologic Information Science • Digital watershed, data models, integration with data of neighboring disciplines Hydrologic information science supports hydrologic process science

  34. HydroVolumes Take a watershed and extrude it vertically into the atmosphere and subsurface A hydrovolume is “a volume in space through which water, energy and mass flow, are stored internally, and transformed”

  35. Watershed Hydrovolumes Hydrovolume Geovolume is the portion of a hydrovolume that contains solid earth materials USGS Gaging stations

  36. Stream channel Hydrovolumes

  37. Hydrologic Flux Coupler Hydrologic Fluxes and Flows Digital Watershed(Atmospheric, surface and subsurface water) We want to do water, mass, energy and water balances

  38. Hydrologic Flux Coupler Define the fluxes and flows associated with each hydrovolume Evaporation Precipitation Streamflow See Chapter 9 of Status Report for Details Groundwater recharge

  39. Time, T D Space, L Time Series Analysis Variables, V D Geostatistics Multivariate analysis Praveen Kumar Is our expert on this subject Data to Knowledge D2K Jan Feb 4-D Data Model Image to Knowledge i2K (See Chapter 10 of the status report for details) Data Files

  40. HIS Goals • Hydrologic Data Access System – better access to a large volume of high quality hydrologic data • Support for Observatories – synthesizing hydrologic data for a region • Advancement of Hydrologic Science – data modeling and advanced analysis • Hydrologic Education – better data in the classroom, basin-focused teaching

  41. Focus class on interpretation of a single river basin Interdisciplinary teaching Water balances for each phase of hydrologic cycle Use Unidata Integrated Data Viewer to access weather info Basin-oriented teaching http://www.ce.utexas.edu/prof/maidment/gradhydro2005/gradhydro2005.htm

  42. Where to from here? • “Test bed” informatics project • Determine best way to get tools that are ready to go into users’ hands • Deliver Hydrologic Data Access System • Support Hydrologic Information Toolkit (e.g., Time Series Analyst from USU) • Further development where required (e.g., digital watershed, flux coupler, shared data models with neighboring science communities)

  43. Funding Opportunities • Earth Sciences Instrumentation and Facilities competition • Open competition with proposals due 8 Feb, 2006 • NSF is encouraging proposals for “test bed” project for 5-year period with funding in order of $4million • Developmental projects can also be submitted to this competition • Role of CUAHSI • Prioritization, Liaison w/ Federal Agencies, Testing, Community Education, Coordination among Informatics projects • CUAHSI will support any successful project in this competition that requests CUAHSI engagement • Standard language will be available from web site • Discuss budget requirements with Rick Hooper • Jon Duncan will chair a Users Committee for reviewing HIS products • Statement will be posted on CUAHSI web site shortly

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