Observatories in the context of the Digital Continent: CZO s and HIS

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1 Observatories in the context of the Digital Continent: CZO s and HIS Dr. Richard P. Hooper, President, Consortium of Universities for the Advancement of Hydrologic Science, Inc.

2 Why Observatories? From Grand Challenges to Decadal Goals Grand Challenge: Predict water quality and quantity anywhere in the US Quantitative integrated model of gw and sw (Flowpaths and residence time prediction) Grand Challenge: Effect of low frequency climate structure on hydrologic extremes Land surface-atmosphere model to predict soil moisture Grand Challenge: Adaptation and scaling or river networks, vegetation, and land forms Integrated model of fluvial geomorphology and ecohydrology

3 How many observatories? Network structure implied by decadal goal Example: GW/SW Interaction Hydrogeologic setting Depth of unsaturated zone Transfer of information from intensively studied observatories to less studied areas (inference ability) Modeling central to observatory efforts

4 Abstractions in Modeling Hydrologist Groundwater Contribution? Q, Gradient, Roughness?

5 Abstractions in Modeling Biogeochemist DOC Quality? Redox Zones? Hyporheic exchange? Mineralogy? Chemistry?

6 Abstractions in Modeling Geomorphologist Glaciated Valley Perifluvial Well sorted? Thalweg?

7 Abstractions in Modeling Aquatic Ecologist Oligotrophic? Carbon source? Backwater habitat Substrate Size, Stability? Benthic Community

8 Abstractions in Modeling Theory/Process Knowledge Perceptions of this place Intuition

9 Abstractions in Modeling Real World Physical World Conceptual Frameworks

10 Abstractions in Modeling Real World Water quantity and quality Conceptual Frameworks Physical World Measurements

11 Abstractions in Modeling Real World Physical World Conceptual Frameworks Meteorology Measurements

12 Abstractions in Modeling Real World Remote sensing Conceptual Frameworks Physical World Measurements

13 Abstractions in Modeling Real World Vegetation Survey Conceptual Frameworks Physical World Measurements

14 Abstractions in Modeling Real World DNA Sequences Conceptual Frameworks Physical World Measurements

15 Abstractions in Modeling Real World Physical World Conceptual Frameworks Geographically Referenced Measurements

16 Abstractions in Modeling Real World Conceptual Frameworks Physical World Mapping Data Representation

17 Real World Abstractions in Modeling Conceptual Frameworks Physical World Mapping Data Representation -Mathematical Formulae -Solution Techniques

18 Abstractions in Modeling Real World Digital Observatory Physical World Conceptual Frameworks Mapping Data Representation Model Representations Validation A single Data Representation supports multiple conceptualizations and models.

19 Data Representation Four-dimensional {x,y,z,t} Time, T D A data value Space, L Variable, V

20 Data Representation Four-dimensional {x,y,z,t} Continental scope

21 Data Representation Four-dimensional {x,y,z,t} Continental scope Multi-scale, multiresolution 1:1,000,000 scale North American and Global 1:500,000 scale United States 1:100,000 scale 1:24,000 scale 1:1200 scale Point scale River Basin Watershed River reach A plot

22 Data Representation Four-dimensional {x,y,z,t} Continental scope Multi-scale, multiresolution Points, coverages, dynamic fields

23 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 observatories may be watersheds, aquifers, river reaches, or any region that is part of the continent

24 Observation Stations Map for the US Ameriflux Towers (NASA & DOE) NOAA Automated Surface Observing System USGS National Water Information System NOAA Climate Reference Network

25 Observation Stations Map for the US Integrated through common data portal

26 Inference Space Transcending place means testing hypotheses in areas thought to be similar (in some attributes). Digital continent 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).

27 DOs are the foundation of EOs Collaboration of Mission and Science Agencies DO contains both monitoring and research data DO 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!)

28 Water Resource Regions and HUC s

29 NHDPlus for Region 17E

30 NHDPlus Reach Catchments ~ 3km 2 Average reach length = 2km 2.3 million reaches for continental US About 1000 reach catchments in each 8-digit HUC

31 Reach Attributes Slope Elevation Mean annual flow Corresponding velocity Drainage area % of upstream drainage area in different land uses Stream order

32 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

33 CUAHSI Hydrologic Information System Architecture National HIS San Diego Supercomputer Center Map interface, observations catalogs and web services for national data sources Workgroup HIS river authority, research centre or univ. Map interface, observations catalogs and web services for regional data sources; observations databases and web services for individual investigator data HIS Server Personal HIS an individual scientist or manager Application templates and HydroObjects for direct ingestion of data into analysis environments: Excel, ArcGIS, Matlab, programming languages; MyDB for storage of analysis data HIS Analyst

34 Supports data discovery, delivery and publication Data discovery how do I find the data I want? Map interface and observations catalogs Data delivery how do I acquire the data I want? Use web services or retrieve from local database Data Publication how do I publish my observation data? Use Observations Data Model HIS Server

35 National and Workgroup HIS National HIS Workgroup HIS National HIS has a polygon in it marking the region of coverage of a workgroup HIS server For HIS 1.0 the National and Workgroup HIS servers will not be dynamically connected. Workgroup HIS has local observations catalogs for coverage of national data sources in its region. These local catalogs are partitioned from the national observations catalogs.

36 Data Sources Storet NASA Ameriflux Extract NCDC Unidata NWIS NCAR Transform CUAHSI Web Services Excel ArcGIS Visual Basic C/C++ Load Applications Matlab Access Java Fortran Some operational services

37 How Excel connects to ODM Excel Obtains inputs for CUAHSI web methods from relevant cells. Available Web methods are GetSiteInfo, GetVariableInfo GetValues methods. HydroObjects parses user inputs into a standardized CUAHSI web method request. CUAHSI Web service converts standardized request to SQLquery. SQL query Observations Data Model imports VB object into Excel and graphs it converts XML to VB object converts response to a standardized XML. Response

38 Data Types Hydrologic Observation Data (Relational database) Digital Watershed Geospatial Data (GIS) Weather and Climate Data (NetCDF) Remote Sensing Data (EOS-HDF)

39 Digital Observatories Data Representation Need to develop integrated 4-dimensional data base Add coverages (easy) and fields (more complicated) Conceptual Frameworks and Modeling Can single data representation fulfill diverse set of science needs? Data assimilation techniques to guide sensor deployment and operation

40 HIS Extensions Integration of Weather Data Work with NCAR; 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

41 HIS and CZOs CZOs can deploy workgroup HIS Need dedicated server (~$5K) ArcServer, SQLServer (potentially free) DataLoader for point data (ODM) provided Need information manager HIS can provide Clipped data catalogs for point time series, coverages Registration in national catalog for publication

42 CZOs and CUAHSI CZOs are high priority for support from CUAHSI HMF pilot geophysics activities Beta test group for HIS products and set priorities for development Community access Data publication Basin user s guides Education and outreach

43 Beyond CZOs O&M for Environmental Observatories a major concern for NSF Seeking active engagement from science and regulatory agencies to develop collaborative observatories Academic research: new technology, basic research and students Mission agencies: Operational support, infrastructure, applied research Use CZO experience to tailor effective engagement of mission agencies