1. Digital Environments and WATERS Observatories Dr. Richard P. Hooper, President, Consortium of Universities for the Advancement of Hydrologic Science, Inc.

2. Why Observatories? Some Conceptual Bases Pragmatic goal: “Transcending the uniqueness of place” –Systematic and coherent observations for testing hypotheses in many places to determine their generality Lofty goal: “Reliably predict water quantity and quality anywhere in the U.S. as a function of…” Modeling goal: “Move from prediction at point (e.g., watershed outlet) to continuous, dynamic fields (e.g., entire river)” (from discharge and heads to fluxes and flowpaths)

3. -Mathematical Formulae -Solution Techniques Abstractions in Modeling Physical World Conceptual Frameworks Data Representation Model Representations “Digital Environment”Real World Measurements Theory/Process Knowledge Perceptions of this place Intuition Water quantity and quality Meteorology Remote sensing Geographically Referenced Mapping Validation DNA Sequences Vegetation Survey Hydrologist Q, Gradient, Roughness? Hillslope Contribution? Snowmelt Processes? Biogeochemist Hyporheic exchange? Mineralogy? Chemistry? Redox Zones? DOC Quality? Geomorphologist Glaciated Valley Perifluvial Well sorted? Thalweg? Aquatic Ecologist Backwater habitat Substrate Size, Stability? Benthic Community Oligotrophic? Carbon source?

4. Data Representation Four-dimensional {x,y,z,t} Continental scope Multi-scale, multi- resolution Point, coverage, dynamic fields Space, L Time, T Variable, V D A data value 1:1200 scale United States 1:500,000 scale River Basin 1:100,000 scale Watershed 1:24,000 scale River reach Point scale A plot 1:1,000,000 scale North American and Global

5. Digital Continent Integrating monitoring and research data yields a single body of information for the country Observatories contribute intensive information to this body Observatories are placed within context of climate, geology, soils, etc. but are not assumed to be representative of an area. Digital environments may be watersheds, aquifers, river reaches, or any region that is part of the continent

6. Inference Space “Transcending place” means testing hypotheses in areas thought to be similar (in some attributes). Digital watershed will enable identification of “similar” areas and (some) data about that spot. Observatories will enable inference about similar regions (e.g., presumably one can infer more about Delaware R. from Potomac than about Rio Grande).

7. DEs are the foundation of EOs Collaboration of Mission and Science Agencies –DE contains both monitoring and research data –DE supports hypothesis test, decision support systems, mgmt models Interdisciplinary communication –Scientists can access multiple conceptualizations to improve understanding –Everyone benefits from context provided Incentives must exist for people and agencies to want to contribute (and they do!)

8. HIS 1.0 (1 Nov 2006) –Point Time Series Discovery and Publication Agencies –USGS NWIS –NCDC –EPA Storet [LTER Trends] –Static Federation to Observatory Test Beds

9. Digital Environments Data Representation –Need to develop integrated 4-dimensional data base –Add coverages (easy) and fields (more complicated) Conceptual Frameworks and Modeling –Testbeds: can single data representation fulfill diverse set of science needs? –LTER Sevilleta Site

10. HIS Extensions Integration of Weather Data –Work with NCAR (Olga Wilhelmini); prototype on Ohio –Move from gridded to watershed-based delivery of data Hydrogeology –Constructing stratigraphy for continent Geologic Framework –Geomorphic and geologic history Incorporation of human dimension –Transportation; structures –Permits, Toxic Release Inventory, etc. –Flood plain (contribution from real estate sector?) –FEMA Lidar products Explicit development of AK, HI, PR beyond CONUS

11. WATERS Design Digital environments provide flexibility— watersheds or problemsheds DE’s embedded within a single Digital Continent that provides context CI is the key to observatories

12. Beyond WATERS Critical Zone Observatories (GEO)– 2 sites selected Spring 2007, $1M/yr each Other large-scale PI-led projects –Illinois Carbon/Water Cycle –HydroKansas –SAHRA and NCED Field Facilities –LTER Sites

13. WATERS and CUAHSI Community Engagement –Web site (template ready) –Coordinating Committee (Pedro Alvarez (Rice), Jean Bahr (Wisc), Dave Goodrich (ARS), Peter Goodwin (Idaho) Geophysical characterization –HMF-Geophysics (Rosemary Knight, Stanford) Digital Observatories –HIS Project

14. WATERS People NSF Program Officers Pat Brezonik (ENG) Doug James (GEO) CLEANER Program Office Jami Montgomery (Ex. Dir) Barbara Minsker (PI) Jerry Schnoor (co-PI) Chuck Haas (co-PI) CUAHSI Staff Rick Hooper, Ex. Dir Wendy Graham, Chair Claire Welty, Chair-Elect

15. CUAHSI Staff Jon Duncan, Program Manager Conrad Matiuk, Webmaster Jessica Annadale, Controller Scott Muir, Accounting Assistant