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

5 What is Hydro? Hydrology Circulation of the waters of the earth through the hydrologic cycle Properties of Water WaterML Hydrography The blue lines on maps 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 HIS National Science Foundation Geosciences Directorate

7 CUAHSI Member Institutions 122 Universities as of October 2008

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

9 Water Data Web Sites

10 HTML as a Web Language 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,hydr ology,geology,desalination,twdb,loans,grants,wastewater,sewage,clean Water,Drinking Water,State Revolving Fund,planning,State Water Plan,GIS,Geographic Information Systems,Mapping,data"> Text and Pictures in Web Browser

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

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

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

14 WaterOneFlow Set of query functions Returns data in WaterML

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

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

17 Data Sources Storet Extract NASA Snotel NCDC Unidata NWIS Academic Transform CUAHSI Web Services Excel Visual Basic ArcGIS Load Java Matlab Applications Operational services

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

19 Information communication Water web pages Water web services 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 1. Data Loading Put data into the CUAHSI Observations Data Model 2. Data Publishing Provide web services access to the data 3. Data Indexing Summarize the data in a centralized cataloging system

22 CUAHSI Point Observation Data Services 1. Data Loading Put data into the CUAHSI Observations Data Model 2. Data Publishing Provide web services access to the data 3. Data Indexing Summarize the data in a centralized cataloging system

23 Data Values indexed by What-wherewhen Time, T When t A data value vi (s,t) s What Vi Variables, V Where Space, S

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

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: /2007wr

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 1. Data Loading Put data into the CUAHSI Observations Data Model 2. Data Publishing Provide web services access to the data 3. Data Indexing Summarize the data in a centralized cataloging system

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

Web Site in Portland, OR http://river.sdsc.edu/snotel/cuahsi_1_0.asmx?

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

30 CUAHSI Point Observation Data Services 1. Data Loading Put data into the CUAHSI Observations Data Model 2. Data Publishing Provide web services access to the data 3. 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 Variable, Vi Variables Site, Sj Space

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

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

ne ric re q ue st GetValues GetValues GetValues NAWQA

35 Semantic Mediation Searching all data sources collectively GetValues GetValues NWIS GetValues g e ne ric re q ue st GetValues GetValues GetValues NAWQA Michael Piasecki Drexel University GetValues GetValues NARR HODM

Hydroseek Bora Beran, Drexel http://www.hydroseek.

36 Hydroseek 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 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 HIS servers at Hydrologic Information System 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

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.

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

HydroGET Interface User inputs GIS layer that contains points of interest.

Atmospheric data from Daymet and Unidata Surface data from USGS NWIS

point Data from userspecified sources for multipoints Custom Mode Period of

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

Assembling data for hydrological insights Precipitation data from

9/27/2002 4/15/2003 11/1/2003 0 2 4 6 8 10 12 14 16 18 Precipitation

1200 1000 800 600 400 200 0 1/1/2000 7/19/2000 2/4/2001 8/23/2001

Streamflow (cfs) Groundwater data from USGS wells. 0.

48 Assembling data for hydrological insights Precipitation data from watershed centroids 1/1/2000 7/19/2000 2/4/2001 8/23/2001 3/11/2002 9/27/2002 4/15/ /1/ Precipitation (cm) Streamflow data from USGS gages /1/2000 7/19/2000 2/4/2001 8/23/2001 3/11/2002 9/27/2002 4/15/ /1/2003 4/15/ /1/2003 Streamflow (cfs) Groundwater data from USGS wells /1/2000 7/19/2000 2/4/2001 8/23/2001 3/11/2002 9/27/ 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

51 Semantic mediation with MySelect TSTypeID/VarID Variable 1001 HRI: DOConcCon HRI: DOConGrab HRI: DOBottomGrab HRI: DOBottomCon Hodges: DO Dissolved_Oxygen_Concentratio n SERF: oxygen Salinity Temperature Wind_Direction MySelect HRI: SalinityCon HRI: SalinityGrab Hodges: Salinity SERF: salinity HRI: TempGrab HRI: TempCon Hodges: Temperature SERF: temperature TCOON: wdr 1006 Wind_Speed TCOON: wsd Data sources may have different names for the same variable. However, differences can be sorted out in ArcHydro by appropriately assigning related variables with the same TSTypeID/ VarID.

52 Example: DataCube diagrams Subset table with x,y,z,t coordinates and oxygen values DataCube diagrams

53 Conclusions A new web services technology has emerged for water observations data From GIS perspective, this means the creation of observations data layers of water data time series Texas is building a Hydrologic Information System using the CUAHSI approach Could Kansas do the same? For more information, see

The CUAHSI Hydrologic Information System

The CUAHSI Hydrologic Information System Presented by Dr. Tim Whiteaker The University of Texas at Austin 18 November, 2010 Session T1B About the Speaker PhD 2004 Research Associate What You Will Learn