Development of a Community Hydrologic Information System David G Tarboton Jeffery S Horsburgh, David R. Maidment (PI), Tim Whiteaker, Ilya Zaslavsky, Michael Piasecki, Jon Goodall, David Valentine, Thomas Whitenack [email protected]Support EAR 0622374 CUAHSI HIS Sharing hydrologic data http://his.cuahsi.org/
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Development of a Community Hydrologic Information System David G Tarboton Jeffery S Horsburgh, David R. Maidment (PI), Tim Whiteaker, Ilya Zaslavsky, Michael.
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Development of a Community Hydrologic Information
System
David G TarbotonJeffery S Horsburgh, David R. Maidment (PI),
Tim Whiteaker, Ilya Zaslavsky, Michael Piasecki, Jon Goodall, David Valentine, Thomas
• CUAHSI and HIS data publication system• WaterML and WaterOneFlow web services• Observations data model (ODM)• Data publication system• Analysis using HIS• Implementation• Performance
Consortium of Universities for the Advancement of Hydrologic Science, Inc.
An organization representing more than one hundred United States universities, receives support from the National Science Foundation to develop infrastructure and services for the advancement of hydrologic science and education in the U.S.
An internet based system to support the sharing of hydrologic data comprising databases connected using the internet through web services as well as software for data discovery, access
• Each data value recorded in value element• Timestamp, plus metadata for the value,
recorded in element’s attributes
ISO Time valuequalifier
Slide from David Valentine
What are the basic attributes to be associated with each single data value and
how can these best be organized?
Value
DateTime
Variable
Location
Units
Interval (support)
Accuracy
Offset
OffsetType/ Reference Point
Source/Organization
Censoring
Data Qualifying Comments
Method
Quality Control Level
Sample Medium
Value Type
Data Type
CUAHSI Observations Data ModelStreamflow
Flux towerdata
Precipitation& Climate
Groundwaterlevels
Water Quality
Soil moisture
data
• A relational database at the single observation level (atomic model)
• Stores observation data made at points
• Metadata for unambiguous interpretation
• Traceable heritage from raw measurements to usable information
• Standard format for data sharing
• Cross dimension retrieval and analysis
Space, S
Time, T
Variables, V
s
t
Vi
vi (s,t)“Where”
“What”
“When”
A data value
Horsburgh, J. S., D. G. Tarboton, D. R. Maidment and I. Zaslavsky, (2008), A Relational Model for Environmental and Water Resources Data, Water Resour. Res., 44: W05406, doi:10.1029/2007WR006392.
CUAHSI Observations Data Model http://his.cuahsi.org/odmdatabases.html
Direct analysis from your favorite analysis environment. e.g. Matlab
% create NWIS Class and an instance of the classcreateClassFromWsdl('http://river.sdsc.edu/wateroneflow/NWIS/DailyValues.asmx?WSDL');WS = NWISDailyValues;% GetValues to get the datasiteid='NWIS:02087500';bdate='2002-09-30T00:00:00';edate='2006-10-16T00:00:00';variable='NWIS:00060';valuesxml=GetValues(WS,siteid,variable,bdate,edate,'');
• 11 WATERS Network test bed projects• 16 ODM instances (some test beds have more than one ODM
instance)• Data from 1246 sites, of these, 167 sites are operated by WATERS
investigators
National Hydrologic Information ServerSan Diego Supercomputer Center
HIS Implementation in WATERS Network Information System
Prototype Texas HIS• TWDB is supporting a small project at
University of Texas to start building a prototype Texas Hydrologic Information System
Texas Hydrologic Information Server (at TNRIS)Texas Observations Catalogs and some state water datasets
HIS servers atdata sources
(State agencies,River authorities,
Water Districts, Cities,Counties….)
Web Services
Intermountain Constellation of Experimental WATERsheds (ICEWATER)
The Inland Northwest Research Alliance (INRA) Water Research Consortium is establishing a HIS Network to share experimental
watershed data to address regional water resources
challenges
Great Salt Lake Information SystemA common window for accessing, viewing and downloading
data and information in the Great Salt Lake Basin
State AgenciesLocal Organizations Federal agenciesUniversities
Conclusions• Data Storage in an Observations Data Model
(ODM)• Data Access through internet-based Water Data
Services using a consistent data language, called WaterML
• Data Indexing through a National Water Metadata Catalog
• Data Discovery through federated map and thematic keyword search system
The combination of these capabilities creates a common window on water observations data for the United States unlike any that has existed before.
HIS Team and Collaborators• University of Texas at Austin – David Maidment, Tim Whiteaker, Ernest
To, Bryan Enslein, Kate Marney• San Diego Supercomputer Center – Ilya Zaslavsky, David Valentine,
Tom Whitenack• Utah State University – David Tarboton, Jeff Horsburgh, Kim
Schreuders, Justin Berger• Drexel University – Michael Piasecki, Yoori Choi• University of South Carolina – Jon Goodall, Tony Castronova• Idaho State University – Dan Ames• CUAHSI Program Office – Rick Hooper, David Kirschtel, Conrad Matiuk• WATERS Network – Testbed Data Managers• HIS Standing Committee • USGS – Bob Hirsch, David Briar, Scott McFarlane• NCDC – Rich Baldwin
HIS Overview Report• Summarizes the
conceptual framework, methodology, and application tools for HIS version 1.1
• Shows how to develop and publish a CUAHSI Water Data Service