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1 CUAHSI Web Services and Hydrologic Information Systems By David R. Maidment, University of Texas at Austin Collaborators: Ilya Zaslavsky and Reza Wahadj, San Diego Supercomputer Center, Tim Whiteaker, Venkatesh Merwade, UT Austin, Steve Ansari, NCDC, Ken Lanfear and Mark Hamill, USGS, Jonathan Goodall, Duke University WSTB Committee on Integrated Observations for Hydrologic and Related Sciences, Dec 1, 2005
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2 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
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3 CUAHSI Hydrologic Data Access System (HDAS) A common data window for accessing, viewing and downloading hydrologic information USGS NASANCDC EPANWS Observatory Data
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4 NWIS Station Information in HDAS http://river.sdsc.edu/HDAS
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5 Observation Site Files Ameriflux TowersAutomated Surface Observing System USGS NWIS Stations Climate Reference Network
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6 Observation Site Map for US USGS NWIS ASOS Climate Research Network Ameriflux + others…….
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7 Neuse Basin with all points NWIS Streamflow and Water Quality NWIS Groundwater ASOS NARR Ameriflux
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8 NWIS Streamflow and Water Quality ASOS NARR Ameriflux Filtered Site Map
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9 http://public.ornl.gov/ameriflux/ Building each web service requires a site map and a web services library Ameriflux site map Web services library Ameriflux towers measure vertical fluxes of water, heat, CO 2
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10 NWIS ArcGIS Excel NCAR LTER NAWQA Storet NCDC Ameriflux Matlab AccessSAS Fortran Visual Basic C/C++ CUAHSI Web Services Some operational services
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11 Direct and Indirect Web Services Direct web service –The data agency provides direct querying ability into its archives through SOAP or OpenDAP (NCDC) Indirect web service –CUAHSI constructs a “web page mimic” service, housed at SDSC, that programmatically mimics the manual use of an agency’s web pages (USGS, Ameriflux)
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12 HydroObjects Library CUAHSI has developed a HydroObjects Library with web service wrappers that know where to access each web service and how to interpret its output User Application (Excel, ArcGIS, …..) HydroObjects Library with web service wrappers for NWIS, Ameriflux, NCDC, … Direct or Indirect web services Web data
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13 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
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14 Accessing Ameriflux data directly from Excel using CUAHSI web services
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15 Transfer of research results CUAHSI web services for NWIS were announced at a cyberseminar on Friday Oct 28 On Wednesday Nov 2, Jason Love, from a private firm, RESPEC, in Sioux Falls, South Dakota, posted on the EPA Basins list server: “Occasionally one comes across something that is worth sharing; the CUAHSI Hydrologic Information Systems - Web Services Library for NWIS is a valuable tool for those of us interested in rapidly acquiring and processing data from the USGS, e.g., calibrating models and performing watershed assessments.” He provided a tutorial on how to use the services from Matlab (which CUAHSI had not developed) Technology transfer took less than 1 week!
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16 Standards are the Key standards … –Industry standards already exists: SOAP = Simple Object Access Protocol WSDL = Web Service Definition Language –Hydrologic community must add their own to the mix: HTSS = Hydrologic Time Series Service HML = Hydrologic Markup Language software development … –If we adopt SOAP and WSDL standards, we can utilize industry support –Hydrology standards will increase interoperability and code reuse
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17 CUAHSI Web Services Web Services Library 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 Object Access Protocol
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18 Impact of Web Services CUAHSI web data services are significantly simplifying user access to federal water observation data This will increase appreciation of the collective information content of these data Next step is to set the data in context of their environment – Digital Watershed Web services may turn out to be as important or even supersede web pages as a data delivery mechanism
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