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GIS in Water Resources

GIS in Water Resources. David R. Maidment Center for Research in Water Resources University of Texas at Austin. GIS Day @ KU 19 November 2008. GIS and Water Resources. WaterML – Water Data Language Observations Data Model Observations Data Layers Harvesting water data in GIS.

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GIS in Water Resources

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  1. GIS in Water Resources David R. Maidment Center for Research in Water Resources University of Texas at Austin GIS Day @ KU 19 November 2008

  2. GIS and Water Resources • WaterML – Water Data Language • Observations Data Model • Observations Data Layers • Harvesting water data in GIS

  3. GIS and Water Resources • WaterML – Water Data Language • Observations Data Model • Observations Data Layers • Harvesting water data in GIS

  4. GIS and Water Resources Water Resources GIS • Data: • Static in time • Complex in space • Standardized formats • Data: • Dynamic in time • Simple in space (points) • No standardized formats

  5. What is “Hydro”? • Hydrology • Hydrography Circulation of the waters of the earth through the hydrologic cycle The “blue lines” on maps Properties of Water – WaterML Features of Water Environment

  6. What is CUAHSI? UCAR • CUAHSI –Consortium of Universities for the Advancement of Hydrologic Science, Inc • Formed in 2001 as a legal entity • Program office in Washington (5 staff) • NSF supports CUAHSI to develop infrastructure and services to advance hydrologic science in US universities Unidata Atmospheric Sciences Earth Sciences Ocean Sciences CUAHSI National Science Foundation Geosciences Directorate HIS

  7. CUAHSI Member Institutions 122 Universities as of October 2008

  8. Water Data Water quantity and quality Rainfall Soil water Modeling Meteorology Groundwater

  9. Water Data Web Sites

  10. HTML as a Web Language Text and Pictures in Web Browser HyperText Markup Language <title>Texas Water Development Board</title> <!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN"> <html> <head> <meta name = "Robots" content = "index,follow"> <meta name = "Priority" content = "home,twdb,homepage"> <meta name = "Author" content = "Texas Water Development Board, Agency Number 580"> <meta name = "Title" content = "Texas Water Development Board"> <meta name = "Description" content = "Texas Water Development Board Home Page"> <meta name = "Keywords" content = "water,drought,rain,conservation,groundwater,surfacewater,lake,reservoir,hydrology,geology,desalination,TWDB,loans,grants,wastewater,sewage,Clean Water,Drinking Water,State Revolving Fund,planning,State Water Plan,GIS,Geographic Information Systems,Mapping,data">

  11. WaterML as a Web Language Discharge of the San Marcos River at Luling, June 28 - July 18, 2002 Streamflow data in WaterML language

  12. Point Observations Information Modelfor USGS Daily Values USGS Data Source GetSites Streamflow gages Network GetSiteInfo San Marcos River at Luling, TX (Site: 08172000) Sites GetVariables GetVariableInfo Discharge, stage (Daily or instantaneous) Variables GetValues Values 19000 cfs, 6 July 2002, A {Value, Time, Qualifier}

  13. Locations Variable Codes Date Ranges WaterML and WaterOneFlow TWDB Data GetSiteInfo GetVariableInfo GetValues Texas A&M NWIS Data WaterML Data WaterOneFlow Web Service Data Repositories Client EXTRACT TRANSFORM LOAD WaterML is an XML language for communicating water data WaterOneFlow is a set of web services based on WaterML

  14. Set of query functions Returns data in WaterML WaterOneFlow

  15. Services-Oriented Architecture for Water Data • Links geographically distributed information servers through internet • Web Services Description Language (WSDL from W3C) • We designed WaterMLas a web services language for water data • Functions for computer to computer interaction HIS Servers in the WATERS Network HIS Central at San Diego Supercomputer Center Web Services

  16. Get Data WaterML HIS Central National Water Metadata Catalog Get Metadata

  17. Data Sources NASA Storet Snotel Unidata NCDC Extract Academic NWIS Transform CUAHSI Web Services Excel Visual Basic ArcGIS Java Load Matlab Applications http://www.cuahsi.org/his/ Operational services

  18. Web pages Web services We are at a tipping point …. Internet Internet Computer Person Computer Computer People interact with a remote information server Networks of information servers provide services to one another

  19. Water web pages Water web services Information communication Water Markup Language (WaterML) HyperText Markup Language (HTML)

  20. GIS and Water Resources • WaterML – Water Data Language • Observations Data Model • Observations Data Layers • Harvesting water data in GIS

  21. CUAHSI Point Observation Data Services • Data Loading • Put data into the CUAHSI Observations Data Model • Data Publishing • Provide web services access to the data • Data Indexing • Summarize the data in a centralized cataloging system

  22. CUAHSI Point Observation Data Services • Data Loading • Put data into the CUAHSI Observations Data Model • Data Publishing • Provide web services access to the data • Data Indexing • Summarize the data in a centralized cataloging system

  23. Data Values – indexed by “What-where-when” Time, T t “When” A data value vi (s,t) “Where” s Space, S Vi “What” Variables, V

  24. Data Values Table Time, T t vi (s,t) s Space, S Vi Variables, V

  25. Observations Data Model 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.

  26. HIS Implementation in WATERS Network Information System National Hydrologic Information Server San Diego Supercomputer Center • 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

  27. CUAHSI Point Observation Data Services • Data Loading • Put data into the CUAHSI Observations Data Model • Data Publishing • Provide web services access to the data • Data Indexing • Summarize the data in a centralized cataloging system

  28. Publishing an ODM Water Data Service Texas A&M Corpus Christi Utah State University University of Florida Assemble Data From Different Sources ODM Data Loader Ingest data using ODM Data Loader WaterML Load Newly Formatted Data into ODM Tables in MS SQL/Server Observations Data Model (ODM) USU ODM UFL ODM TAMUCC ODM Wrap ODM with WaterML Web Services for Online Publication

  29. Publishing a Hybrid Water Data Service Snotel Metadata are Transferred to the ODM WaterML Snotel DataValues Snotel METADATA ODM Web Services can both Query the ODM for Metadata and use a Web Scraper for Data Values Snotel Water Data Service Get Values from: Metadata From: ODM Database in San Diego, CA Snotel Web Site in Portland, OR http://river.sdsc.edu/snotel/cuahsi_1_0.asmx?WSDL Calling the WSDL Returns Metadata and Data Values as if from the same Database

  30. CUAHSI Point Observation Data Services • Data Loading • Put data into the CUAHSI Observations Data Model • Data Publishing • Provide web services access to the data • Data Indexing • Summarize the data in a centralized cataloging system

  31. Data Series – Metadata description Time End Date Time, t2 There are C measurements of Variable Vi at Site Sj from time t1 to time t2 Count, C Begin Date Time, t1 Site, Sj Space Variable, Vi Variables

  32. Series Catalog Time Sj End Date Time, t2 Vi Count, C Begin Date Time, t1 Site, Sj Space Variable, Vi Variables t1 t2 C

  33. CUAHSI National Water Metadata Catalog • Indexes: • 50 observation networks • 1.75 million sites • 8.38 million time series • 342 million data values NWIS STORET TCEQ

  34. request return return request NAWQA request return return request NAM-12 request return NWIS request return request return return request NARR Data Searching • Search multiple heterogeneous data sources simultaneously regardless of semantic or structural differences between them Searching each data source separately Michael Piasecki Drexel University

  35. NAWQA NWIS NARR HODM Semantic Mediation Searching all data sources collectively GetValues GetValues GetValues GetValues generic request GetValues GetValues Michael Piasecki Drexel University GetValues GetValues

  36. Hydroseekhttp://www.hydroseek.org Bora Beran, Drexel Supports search by location and type of data across multiple observation networks including NWIS and Storet

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

  38. Synthesis and communication of the nation’s water data http://his.cuahsi.org Government Water Data Academic Water Data National Water Metadata Catalog Hydroseek WaterML

  39. GIS and Water Resources • WaterML – Water Data Language • Observations Data Model • Observations Data Layers • Harvesting water data in GIS

  40. Prototype Texas HIS • Texas Water Development Board is supporting a project at UT to start building a prototype Texas Hydrologic Information System HIS servers at data sources (State agencies, River authorities, Water Districts, Cities, Counties….) Web Services Texas Hydrologic Information Server (at TNRIS) Texas Observations Catalogs and some state water datasets

  41. Levels of Government National data services (USGS, EPA, NCDC, NWS...) Web State data services (TCEQ, TWDB, TCEQ, ….) Services Regional data services (LCRA, BRA, City of Austin, ...)

  42. Texas Hydrologic Information System Sponsored by the Texas Water Development Board and TNRIS using CUAHSI technology for state and local data sources (using state funding)

  43. Observations Data Layer for Water Quality in Texas • Attributes are time series of: • Bacterial concentrations • Water temperature • Nitrogen components • …….

  44. GIS and Water Resources • WaterML – Water Data Language • Observations Data Model • Observations Data Layers • Harvesting water data in GIS

  45. What is HydroGET? • A web service client for ESRI‘s ArcGIS environment. • Harvests time series data from data repositories on the web and stores them in the ArcHydro data model. • Default Mode: Downloads data from national data sources to describe components of the hydrological cycle. Atmospheric data from Daymet or Unidata Surface data from USGS NWIS Subsurface data from USGS NWIS Illustration courtesy of the United States Geological Survey • Custom Mode: Downloads data from any combination of CUAHSI web services to describe other properties (e.g. biological) of a study area.

  46. HydroGet

  47. HydroGET Interface Types of data and sources Main Interface User inputs GIS layer that contains points of interest. Atmospheric data from Daymet and Unidata Default Mode Target geodatabase for downloaded data Surface data from USGS NWIS List of variables of interest (each tab holds a different set of variables) Subsurface data from USGS NWIS Data from user- specified sources for single point Custom Mode Period of interest Data from user- specified sources for multipoints

  48. Assembling data for hydrological insights Precipitation data from watershed centroids Precipitation (cm) Streamflow data from USGS gages. Streamflow (cfs) Groundwater data from USGS wells. Groundwater level (m above ground surface)

  49. What is MySelect? • A featureclass with an attribute table that contains query parameters for downloading and storing web service data. • Each record in the table is one web service request. • A MySelect table can have several requests, essentially making it a shopping list for environmental data. Get precipitation Get streamflow Get groundwater level

  50. MySelect in action LEGEND TCOON (Texas Coastal Ocean Observation Network ) platforms ! > HRI (Harte Research Institute ) Stations SERF (Shoreline Environmental Research Facility) platforms ! > ! > Plume tracking stations (Dr. Ben Hodges) Evidence of hypoxic conditions Map of Corpus Christi Bay in southeast Texas

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