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The CUAHSI Hydrologic Information System Support EAR 0622374 CUAHSI HIS Sharing hydrologic data

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Presentation on theme: "The CUAHSI Hydrologic Information System Support EAR 0622374 CUAHSI HIS Sharing hydrologic data"— Presentation transcript:

1 The CUAHSI Hydrologic Information System Support EAR CUAHSI HIS Sharing hydrologic data

2 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 US University members 6 affiliate members 12 International affiliate members (as of March 2009)

3 HIS Team and Collaborators University of Texas at Austin – David Maidment (PI), 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 University of South Carolina – Jon Goodall, Tony Castronova Idaho State University – Dan Ames, Ted Dunsford, Teva Veluppillai CUAHSI Program Office – Rick Hooper, David Kirschtel, Conrad Matiuk, Yoori Choi WATERS Network – Testbed Data Managers HIS Standing Committee USGS – Bob Hirsch, David Briar, Scott McFarlane NCDC – Rich Baldwin

4 What is HIS The CUAHSI Hydrologic Information System (HIS) provides web services, tools, standards and procedures that enhance access to more and better data for hydrologic analysis. PrecipitationWater quantity Meteorology Water quality

5 Data Searching – What we used to have to do NWIS NARR NAWQA NAM-12 request request return return Searching each data source separately Michael Piasecki Drexel University

6 What HIS enables Searching all data sources collectively NWIS NAWQA NARR generic request GetValues GetValues ODM Michael Piasecki Drexel University

7 Base Station Computer(s) Telemetry Network Sensors Query, Visualize, and Edit data using ODM Tools Excel, text ODM Database ODM Data Loader Streaming Data Loader GetSites GetSiteInfo GetVariableInfo GetValues WaterOneFlow Web Service WaterML Discovery Hydroseek Access Analysis GIS Matlab Splus R IDL Java C++ VB HIS Desktop HydroExcel Water Metadata Catalog Harvester Service RegistryHydrotagger HIS Central CUAHSI Water Data Services System USGS NWIS EPA STORET NCDCOthers

8 Hydroseek Supports search by location and type of data across multiple observation networks including NWIS and Storet Bora Beran, Drexel

9 Desktop Hydrologic Information System Harvesting and analyzing data from web services Observations Models Climate GIS Remote Sensing Goal for 2009

10 Direct analysis from your favorite analysis environment. e.g. Excel

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

12 Set of query functionsReturns data in WaterML Slide from David Valentine WaterML and WaterOneFlow WaterML is an XML language for communicating water data WaterOneFlow is a set of web services based on WaterML

13 What are the basic attributes to be associated with each single data value and how can these best be organized? Streamflow Flux tower data Precipitation & Climate Groundwater levels Water Quality Soil moisture data Observations Data Model (ODM) 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 ViVi v i (s,t) “Where” “What” “When” A data value

14 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: /2007WR CUAHSI Observations Data Model

15 Site Attributes SiteCode, e.g. NWIS: SiteName, e.g. Logan River Near Logan, UT Latitude, Longitude Geographic coordinates of site LatLongDatum Spatial reference system of latitude and longitude Elevation_m Elevation of the site VerticalDatum Datum of the site elevation Local X, Local Y Local coordinates of site LocalProjection Spatial reference system of local coordinates PosAccuracy_m Positional Accuracy State, e.g. Utah County, e.g. Cache

16 1 1 CouplingTable SiteID HydroID Sites SiteID SiteCode SiteName Latitude Longitude … Observations Data Model 1 1 OR Independent of, but can be coupled to Geographic Representation ODM Arc Hydro or NHD+

17 Stage and Streamflow Example

18 Loading data into ODM Interactive ODM Data Loader – Loads data from spreadsheets and comma separated tables in simple format Streaming Data Loader (SDL) – Loads data from datalogger files on a prescribed schedule – Interactive configuration SQL Server Integration Services (SSIS) – Microsoft application accompanying SQL Server useful for programming complex loading or data management functions ODM Data Loader SDL SSIS

19 Dynamic controlled vocabulary moderation system Local ODM Database Master ODM Controlled Vocabulary ODM Website ODM Controlled Vocabulary Moderator ODM Data Manager ODM Controlled Vocabulary Web Services ODM Tools Local Server XML From Jeff Horsburgh

20 Publishers – Register a data service Users – Find a data service Supported by – Metadata Catalog HIS Central

21 HydroTagger Ontology: A hierarchy of concepts Each Variable in your data is connected to a corresponding Concept

22 National Web Services implemented to date NWIS daily value data (e.g., daily average streamflow) NWIS groundwater data NWIS real time data NWIS instantaneous irregular data (field measurements, water quality) ORNL Daymet Meteorological model NCEP North American Mesoscale (NAM) Weather Research and Forecasting (WRF) model EPA STORET water quality data NASA MODIS Atmospheric data derived from remote sensing

23 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 Server San Diego Supercomputer Center HIS Implementation in WATERS Network Information System

24 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 at data sources (State agencies, River authorities, Water Districts, Cities, Counties….) WebServices

25 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

26 How CUAHSI works with agencies 1.Establish an agreement with the agency 2.Identify the scope of the service 3.Translate the semantics of the service to WaterML 4.Include agency personnel in OGC/WMO Hydrology Domain Working Group 5.Develop a first draft of the web service 6.Perform unit testing, over a series of validation cases 7.Harvest an observations metadata catalog for agency data 8.Develop a procedure for catalog updates 9.Document and register the water data service at HISCentral 10.Review and test the service together with the agency, for possible approval as “operational”

27 Demonstrations Hydroseek: Little Bear River: HydroExcel

28 Ideas for SWSI application HIS Server display of SWSI – ODM of SWSI Input data used to calculate SWSI Calculated SWSI values – WaterML based Web Services – Web Map/Feature/Raster geospatial data services – Map based display of SWSI

29 Ideas for SWSI application SWSI viewer as HIS Desktop/Mapwindow plugin – Access SWSI calculation inputs – Access published SWSI values – Access published SWSI maps – Compute and display custom SWSI products

30 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.


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