Worldwide Exchange of Water Data

Transcription

1 Worldwide Exchange of Water Data Fernando R. Salas and David R. Maidment Center for Research in Water Resources University of Texas at Austin 2014 AWRA Spring Specialty Conference: GIS and Water Resources VII Snowbird, Utah May 13, 2014 Acknowledgements: CRWR, ESRI, Kisters, Microsoft, WMO, OGC, GEO, USGS, CUAHSI

2 Hydrological Measurement Water Quantity Rainfall Soil Water Water Quality Meteorology Groundwater Time series data at point locations

3 Every Country Collects These Data United States WMO does Global Water Data Integration Mexico Australia Many kinds of hydrological measurements......integration is somewhat ad-hoc

4 WMO Guide to Hydrological Practices Guide to Hydrological Practices Volume I Hydrology From Measurement to Hydrological Information Science and Measurement Chapter 10 Data Storage, Access, and Dissemination Guide to Hydrological Practices Volume II Management of Water Resources and Application of Hydrological Practices Application and Management Guide to Hydrological Practices WMO recommendations for National Hydrological Surveys

5 Consortium of Universities for the Advancement of Hydrologic Science, Inc. CUAHSI A consortium representing 125 US universities Dr. Richard Hooper, President and CEO Presentation to Chy-14 on Wednesday Supported by the National Science Foundation Earth Science Division Advances hydrologic science in nation s universities Includes a Hydrologic Information System project Invented WaterML language for water resources time series Building an academic prototype system

6 Consortium of Universities for the Advancement of Hydrologic Science, Inc. CUAHSI A consortium representing 125 US universities Dr. Richard Hooper, President and CEO Presentation to Chy-14 on Wednesday Building an academic prototype system

7 WaterML the US Geological Survey Water time series data on the internet 24/7/365 service For daily and real-time data... Operational water web services system for the United States

8 WaterML the US Geological Survey Water time series data on the internet sites= &parametercd=00060&statcd=00003&period=p7d 24/7/365 service For daily and real-time data... Operational water web services system for the United States

9 Open Geospatial Consortium Features with geometry: defined by points, lines and polygons Web Feature Service (WFS) Features as coverage: multidimensional arrays Web Coverage Service (WCS) Features with observations: uses a procedure to determine a property of a feature of interest and produces a result Sensor Observation Service (SOS) More than 400 companies and agencies globally... Internet data standards for maps and observational data

10 OGC/WMO Hydrology Domain Working Group 4-Year International Effort WaterML A time series for one variable at one location Hydrology Domain Working Group formed OGC observer at CHy-13 November 2009 Technical Meetings Each 3 Months Four Interoperability Experiments (Surface water, groundwater, forecasting) Annual week-long workshops Involvement by many countries Acknowledgements: OGC, WMO, GRDC, CUAHSI, BoM/CSIRO, USGS, GSC, Kisters,

11 WIS WMO Information System Ingests data from National Centers synthesized globally through communication networks

12 GEOSS Global Earth Observation System of Systems Group on Earth Observations (GEO) located with WMO in Geneva

13 Three Categories of Water Services Web Services Stack for Time Series Catalog Service for the Web with standard metadata: ISO, FGDC, ANZLIC, Dublin Core Who? What? Time Series Services Catalog (CSW) Metadata (WFS) Data (SOS) Where? When? CSW = Catalog Service for the Web WFS = Web Feature Service for Maps SOS = Sensor Observation Service for Time Series *WaterML 2.0 is an encoding Access Data Existing OGC Data Services are Adequate Need to Be Customized for Water Information

14 United States Services Stack Catalog Metadata Data Web Feature Service for Observation Metadata Colorado River at Austin, Texas WaterML time series service for data An attribute of each mapped observation point is a web link to the WaterML data service

15 National Service Stacks Globally Federated USA Dominican Republic Australia Mexico Catalog GEOSS WIS Metadata Data GEOSS Indexes Geospatial Data WIS Indexes Observational Data

16 Global Streamflow Services Global Runoff Data Centre USA New Zealand Italy Dominican Republic Building a national system federating regions builds a global system federating countries

17 A Key Challenge Integrating GIS and Water Observations Data GIS Water Environment (Watersheds, streams, gages, sampling points) Water Observations The Water Itself (Flow, water level, precipitation, water quality)

18 Common Hydrologic Feature Model Courtesy of Irina Dornblut (GRDC) and Rob Atkinson (CSIRO)

19 Crossing the Digital Divide

20 Maps Observations Models

21 Scales of Application Global World Assessment Water and Climate National Landscape Accounting How much water? Regional River Basin, Aquifer Management Solving water problems Local My house, My well, My ranch Personal How does this affect me? A scale-independent information model for maps and observations more detail as focus narrows

22 World Hydro Overlay Map World United States Texas My Home My Stream

23 Congo River Basin World Hydro Overlay Map River Basin Delineation Delineate a watershed from any point on a river

24 Collecting Water Data Globally (GRACE) Force of gravity responds to changes in water volume. Water is really heavy! Grace Satellites In 2011 Texas lost 100 Km 3 of water overall Texas lost 5 times the water volume of the Great Salt Lake in 2011 drought and in a few months it returned!

25 GRACE and Texas Reservoir Water Storage Grace Satellites In 2011 Texas lost 100 Km 3 of water overall Reservoirs In 2011 Texas lost 9 Km 3 of water from reservoirs Total water volume stored in 119 surface water reservoirs closely correlated with GRACE gravity anomaly over Texas

26 System of Systems for Water Data

27 Land Data Assimilation System (LDAS) Observations Datasets, Numerical Weather Model Soil Vegetation Terrain Forcing: Radiation Precipitation Surface climate Land Surface Model Deduction: Given these forcing and land surface conditions Then, using a land surface simulation model Derive surface moisture and energy balance Evaporation Soil Moisture Runoff Recharge Domain Space Time North America 1979 to present 1/8 degree 1 hour Global 1/4 degree 3 hours

28 NASA Data Rod Soil Moisture North American Land Data Assimilation System Time

29 Contact: Gonzalo Espinoza

30 World Soil Moisture from the NASA Global Land Data Assimilation System (GLDAS) Charts show 3-hourly variation (37,000 values) of soil water content of the top 1m of soil from 2000 to 2012 Popup on point links to data and chart New Zealand A very wet region with little seasonality A dryer region with significant seasonality

31 Flow in the Mississippi River Basin RAPID model, March-May 2008, 3 hour time steps David et al. (2011) DOI: /2011JHM GIS data describes 1.2 million river reaches simulate flow in each reach in each time step

32 Water Operations Model San Antonio/Guadalupe River Basins Map Services geospatial context Data Services historical context

33 Map and Data Services Map Services NWS Runoff Forecasts TCEQ Real-time Diversions Data Services

34 Water Maps Describe a water property over a domain of space and time History Current conditions Forecasts Precipitation Evaporation Soil Moisture Streamflow Groundwater Reservoirs

35 Website:

36 World Water Online Hydrology on the web Watersheds Maps Global to Local Models Observations Open Information systems include both commercial and open source software linked by open standards