1. Two NSF Data Services Projects Rick Hooper, President Consortium of Universities for the Advancement of Hydrologic Science, Inc.

2. Services-Oriented Architecture for Publishing Time-Series Data Links geographically distributed information servers through internet Web Services Description Language (WSDL from W3C) We designed WaterML as 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

3. National Water Metadata Catalog Synthesis and communication of the nation’s water data http://his.cuahsi.org http://his.cuahsi.org HydroseekWaterML Government Water DataAcademic Water Data

4. 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

5. Hydroseek: Data Access Federal Agencies, State Agencies, and Academic Researchers

6. Map-based or Basin-based Search

7. Enter Data Type

8. Results USGS EPA Chesapeake Bay Program

9. Get Data with one request! Data Cart

10. Accomplishments Observations Data Model (ODM) is robust; WaterOneFlow web services provide reliable access to ODM data; WaterML is a common language for water observations data from academic and government sources National Water Metadata Catalog is the most comprehensive index of the nation’s water observations presently existing.

11. Limitations Focus on observations data measured as time series at fixed point locations; – Needs adaptation for moving sensors, transects, one-time data collections and field surveys; Need to work more on – Coverages for weather, climate and remote sensing – Linking data and models – Linking geographic features WaterML Observations Geography Models Coverages

12. CUAHSI and Federal Agencies Signed CRADA with US Geological Survey on instrumentation Signed MoU with USGS and National Climatic Data Center (NOAA) on data services Developing MoU with EPA Office of Water on data services

13. HIS Team and Collaborators University of Texas at Austin – David Maidment, 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, Yoori Choi University of South Carolina – Jon Goodall, Tony Castronova

14. HIS Overview Report Summarizes the conceptual framework, methodology, and application tools for HIS version 1.1 Shows how to develop and publish a CUAHSI Water Data Service Available at: http://his.cuahsi.org/documents/HISOverview.pdf

15. Hydro-NEXRAD: A Community Resource for Hydrologic Research and Applications Project Goal: …to provide the hydrologic community with ready access to the vast archives and real-time information collected by the national network of NEXRAD radars. What is it? A WEB-based prototype information retrieval system that allows ordering customized radar-rainfall maps for hydrologic applications based on WSR- 88D data. Extreme events: flash-floods, urban flooding, debris flow, landslides, etc. Extreme events: flash-floods, urban flooding, debris flow, landslides, etc. Hydrologic forecasting: distributed models of water and contaminant transport, flood forecasting Hydrologic forecasting: distributed models of water and contaminant transport, flood forecasting Variability, predictability, complexity of water cycle Variability, predictability, complexity of water cycle Support of WATERS network Support of WATERS network Remote sensing …and much more… Remote sensing …and much more… Science Goals

16. Basin centric (USGS HUC System) Basin centric (USGS HUC System) Relational database (large-scale prototype, 40 radars, over 250 radar years) Relational database (large-scale prototype, 40 radars, over 250 radar years) Web-based GUI (map server, database) Web-based GUI (map server, database) Extensive metadata base: basin, radar, points Extensive metadata base: basin, radar, points Numerous radar-rainfall algorithms Numerous radar-rainfall algorithms Highly customizable (e.g. resolution, map projection) Highly customizable (e.g. resolution, map projection) High performance, ease of use High performance, ease of use Modular design Modular design Over 60 beta users Over 60 beta users

17. Updates, Plans & Challenges Handling super resolution data and producing sub kilometer resolution rainfall products (under testing and evaluation) Handling super resolution data and producing sub kilometer resolution rainfall products (under testing and evaluation) Adaptation to real-time service for the community (working prototype exists) Adaptation to real-time service for the community (working prototype exists) Expanding to full national coverage (NCDC? CUAHSI?) Expanding to full national coverage (NCDC? CUAHSI?) Expanding to multisensor (rain gauge, satellite data) capability (planned, algorithms exist) Expanding to multisensor (rain gauge, satellite data) capability (planned, algorithms exist) Comprehensive performance evaluation (in progress) Comprehensive performance evaluation (in progress) Dynamic and modular nature of the system: ready for implementation of new ideas (fundamental design feature) Dynamic and modular nature of the system: ready for implementation of new ideas (fundamental design feature) Facing the question “What’s next?” Upkeep, growth, architecture: central or distributed, etc. etc. Facing the question “What’s next?” Upkeep, growth, architecture: central or distributed, etc. etc.