1. Deployment and Evaluation of an Observations Data Model Jeffery S Horsburgh David G Tarboton Ilya Zaslavsky David R. Maidment David Valentine http://www.cuahsi.org/his.html Support EAR 0622374

2. WaterOneFlow Web Services Data accessthrough web services Data storage through web services Downloads Uploads Observatory data servers CUAHSI HIS data servers 3 rd party data servers e.g. USGS, NCDC GIS Matlab IDL Splus, R Excel Programming (Fortran, C, VB) Web services interface Data Access System for Hydrology (DASH) Website Portal and Map Viewer Information input, display, query and output services Preliminary data exploration and discovery. See what is available and perform exploratory analyses HTML -XML WSDL - SOAP ODM

3. CUAHSI Observations Data Model 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 Streamflow Flux tower data Precipitation & Climate Groundwater levels Water Quality Soil moisture data

4. CUAHSI Observations Data Model http://www.cuahsi.org/his/odm.html

5. Discharge, Stage, Concentration and Daily Average Example

6. Stage and Streamflow Example

7. ODM Implementation in WATERS Network Information System 11 WATERS Network test bed projects 16 ODM networks (some test beds have more than one network) Data from 1246 sites, of these, 167 sites are operated by WATERS investigators National Hydrologic Information Server San Diego Supercomputer Center

8. Florida – Santa Fe Watershed Nitrate Nitrogen (mg/L) Millpond Spring PI: Wendy Graham, ….; DM: Kathleen McKee, Mark Newman

9. Utah – Little Bear River and Mud Lake Turbidity Continuous turbidity observations at the Little Bear River at Mendon Road from two different turbidity sensors.

10. Managing Data Within ODM - ODM Tools Load – import existing data directly to ODM Query and export – export data series and metadata Visualize – plot and summarize data series Edit – delete, modify, adjust, interpolate, average, etc.

11. Methods for Data Loading SQL Server Integration Services Interactive Data Loader Scheduled Data Loader

12. Direct analysis from your favorite analysis environment. e.g. Matlab % create NWIS Class and an instance of the class createClassFromWsdl('http://water.sdsc.edu/wateroneflow /NWIS/DailyValues.asmx?WSDL'); WS = NWISDailyValues; % GetValues to get the data siteid='NWIS:02087500'; bdate='2002-09-30T00:00:00'; edate='2006-10-16T00:00:00'; variable='NWIS:00060'; valuesxml=GetValues(WS,siteid,variable,bdate,edate,'');

13. Summary Syntactic heterogeneity (File types and formats) Semantic heterogeneity –Language for observation attributes –Language to encode observation attribute values A national network of consistent data Enhanced data availability Metadata to facilitate unambiguous interpretation Enhanced analysis capability

14. Future Considerations Additional data types (grid, image etc.) Additional catalog sets to enhance discovery Unit standardization and conversion Ownership, security, authentication, provenance Improve controlled vocabulary constraints to enhance integrity

15. Databases: Structured data sets to facilitate data integrity and effective sharing and analysis. - Standards - Metadata - Unambiguous interpretation Analysis: Tools to provide windows into the database to support visualization, queries, analysis, and data driven discovery. Models: Numerical implementations of hydrologic theory to integrate process understanding, test hypotheses and provide hydrologic forecasts. Advancement of water science is critically dependent on integration of water information Databases Analysis Models ODM Web Services

16. HIS Website http://www.cuahsi.org/his.html http://www.cuahsi.org/his.html Project Team – Introduces members of the HIS Team Data Access System for Hydrology – Web map interface supporting data discovery and retrieval Prototype Web Services – WaterOneFlow web services facilitating downlad of time series data from numerous national repositories of hydrologic data Observations Data Model – Relational database schema for hydrologic observations HIS Tools – Links to end-user applications developed to support HIS Documentation and Reports – Status reports, specifications, workbooks and links related to HIS Feedback – Let us know what you think Austin Workshop – Material from WATERS workshop in Austin