1. Ocean Sciences CUAHSI-Hydrologic Information Systems CUAHSI – Consortium of Universities for the Advancement of Hydrologic Science, Inc Formed in 2001 as a legal entity 100 member universities (May 2005) Program office in Washington (5 staff) Rick Hooper is Executive Director Earth Sciences Atmospheric Sciences NSF Geosciences Directorate UCAR CUAHSI Unidata HIS

2. CUAHSI Hydrologic Information Systems

3. Project co-PI Collaborator CUAHSI Hydrologic Information System

4. Environmental Cyberinfrastructure Part of NSF Cyberinfrastructure program CUAHSI Hydrologic Information Systems is one of several pilot projects – CUAHSI, CLEANER, ORION, NEON, GEON, …..

5. Cyberinfrastructure Components

6. Workflow Sequencing using ModelBuilder

7. HIS Goals Data Services for Hydrologists – get me the data I want quickly and painlessly Support for Observatories – data structure for Digital Watersheds Advancement of Hydrologic Science – flux coupler, HydroObjects Hydrologic Education – how to get data into the classroom

8. Digital Watershed Hydrologic Observation Data Geospatial Data Remote Sensing Data Weather and Climate Data (NetCDF) (GIS) (Relational database or delimited ascii) (EOS-HDF) Digital Watershed

9. CUAHSI HIS Overview HIS User Assessment Hydrology Data Portal Digital Watershed Hydrologic Analysis

10. HIS User Assessment First survey done for HIS White Paper (2003) HIS Symposium in March – 4 institutional surveys and a survey of participants CUAHSI Web Surveyor – developed by David Tarboton and Christina Bandaragoda (75 responses from 38 institutions) Summary paper circulated by email yesterday

11. Please rank these four HIS service categories for helping you. Conclusion: Data services are the highest priority Value Score (counting 4 for first, 4 for second, 2 for third and 1 for fourth).

12. % of time spent preparing data

13. Which operating systems do you use for your research? If you use more than one operating system, select all that apply.

14. Please indicate one dataset that you believe would most benefit from increased ease of access through a Hydrologic Information System (HIS). Conclusion: EPA STORET Water Quality, Streamflow and Remote Sensing Data are perceived to be able to benefit from improved access. I am surprised USGS streamflow is up there. Is this an indication of importance over difficulty?

15. How we use software (Austin Symposium)

16. Which of the following data analysis difficulties are most important for HIS to address? Conclusion: High priorities are: - Data formats - Metadata - Irregular time steps Value Score (counting 3 for first, 2 for second and 1 for third).

17. How we use software (Web Surveyor) Programming (85% of respondents): Fortran, C/C++, Visual Basic Data Management (93%): Excel, MS Access GIS (93%): ArcGIS Mathematics/Statistics (98%): Excel, Matlab, SAS, variety of other systems Hydrologic models (80%): Modflow, HEC models A general, simple, standard, and open interface that could connect with many systems is the only way to accommodate all these

18. CUAHSI HIS Overview HIS User Assessment Hydrology Data Portal Digital Watershed Hydrologic Analysis

19. Hydrologic Observations Database A relational database stored in Access, PostgreSQL, SQL/Server, …. Stores observation data made at points Access data through web interfaces Fill using automated data harvesting Streamflow Flux tower data Precipitation & Climate Groundwater levels Water Quality Soil moisture data

20. Hydrologic Observations Data Model Review conducted by David Tarboton with 22 responses – redesign of this model is now being done Relationships

21. Proposed CUAHSI Observations Database Schema (for details see chap 6 at http://www.cuahsi.org/docs/ HISStatusSept15.pdf)

22. Example: Lake Water Chemistry

23. Data Access and Viewing System in ArcMap

25. CUAHSI Data Portal

27. Plot from the Hydrology Data Portal Produced using a CUAHSI Hydrology Web Service: getDailyStreamflowChartgetDailyStreamflowChart

28. CUAHSI Hydrology Web Services for NWIS http://water.sdsc.edu/HydrologicTimeSeries/NWIS.asmx

29. Documentation: getDailyStreamflowChart https://webspace.utexas.edu/jgoodall/HydrologicTimeSeriesWebServices.htm

30. Applications and Services Web Services Library Web application: Data Portal Your application Excel, ArcGIS, Matlab Fortran, C/C++, Visual Basic Hydrologic model ……………. Your operating system Windows, Unix, Linux, Mac Internet

31. Utah State University Streamflow Analyst

32. CUAHSI HIS Overview HIS User Assessment Hydrology Data Portal Digital Watershed Hydrologic Analysis

33. Digital Watershed How can hydrologists integrate observed and modeled data from various sources into a single description of the environment?

34. Digital Watershed Hydrologic Observation Data Geospatial Data Remote Sensing Data Weather and Climate Data (NetCDF) (GIS) (Relational database or delimited ascii) (EOS-HDF) Digital Watershed A digital watershed is a synthesis of hydrologic observation data, geospatial data, remote sensing data and weather and climate data into a connected database for a hydrologic region

35. Created first for the Neuse basin Digital Watershed: An implementation of the CUAHSI Hydrologic Data Model for a particular region

36. Neuse Atmospheric Water Daily precipitation data from NCDC gages Nexrad daily rainfall rasters Land surface – atmosphere fluxes from North American Regional Reanalysis of climate

38. Neuse Surface Water Streamflow, water quality hydrologic observational data GIS: River network, water bodies, watersheds, monitoring points Land cover, soils, MODIS remote sensing (Praveen Kumar) MODIS Terrain and Land Cover

39. ArcIMS Web Server displaying data compiled in Neuse HO Planning Study http://neuse.crwr.utexas.edu/

40. Neuse Basin: Coastal aquifer system * From USGS, Water Resources Data Report of North Carolina for WY 2002 Section line Beaufort Aquifer

41. Neuse Groundwater Geovolumes of hydrogeologic units from US Geological survey (GMS)

42. Create a 3 dimensional representation Geovolume Each cell in the 2D representation is transformed into a 3D object Geovolume with model cells

43. Page 3 Drexel University, College of Engineering Data Centers NCDC USGS NWIS NCEP NWS NGDC Sensor Arrays Numerical Models Prediction HSPF Air-Q MM5 Individual Samples METADATA The Demands

44. ISO 19103 Units/Conversion Page 21 Drexel University, College of Engineering Ontology Examples Hydrologic Metadata We currently have ISO 19108 Temporal ObjectsUSGS Hydrologic Unit CodeISO 19115 Geospatial Hydrologic Processes Sedimentation ARCHydro What we need is Many More Upper Hydrologic Ontology Michael Piasecki is our expert in this subject!

45. CUAHSI HIS Overview HIS User Assessment Hydrology Data Portal Digital Watershed Hydrologic analysis

46. Hydrologic Analysis Hydrologic Process Modeling Statistics and Hypothesis Testing Visualization Data Mining and Knowledge Discovery Digital Watershed

47. Data Driven Discovery Tools Praveen Kumar is our expert on this subject!

48. Data Files FebJan 4-D Data Model Space, L Time, T Variables, V D Geostatistics Time Series Analysis Multivariate analysis D Image to Knowledge Data to Knowledge

49. Hydrologic Flux Coupler Hydrologic Fluxes and Flows Digital Watershed (Atmospheric, surface and subsurface water) We want to do water, mass, energy and water balances

50. Neuse Observatory Prototype Study

51. HydroVolumes Take a watershed and extrude it vertically into the atmosphere and subsurface A hydrovolume is “a volume in space through which water, energy and mass flow, are stored internally, and transformed”

52. Watershed Hydrovolumes Geovolume is the portion of a hydrovolume that contains solid earth materials USGS Gaging stations Hydrovolume

53. Stream channel Hydrovolumes

54. Atmospheric science – hydrology Weather and climate fields are the drivers – continuous in space and time across the nation Local watersheds are the reactors – each behaving according to its location and characteristics

55. GeoTemporal Reference Frame A defined geospatial coordinate system for (x,y,z) A defined time coordinate system (UTC, Eastern Standard Time, ….) A set of variables, V Data values v(x,y,z,t) Space (x,y,z) Time, t Variables, V v – data values Data Cube

56. Continuous Space-Time Model -- NetCDF Space, L Time, T Variables, V D Coordinate dimensions {X} Variable dimensions {Y}

57. Space, FeatureID Time, TSDateTime Variables, TSTypeID TSValue Discrete Space-Time Data Model

58. Geospatial Time Series Value Time Shape Time Series Properties (Type) A Value-Time array A time series that knows what geographic feature it describes and what type of time series it is

59. Neuse Water Balance Precipitation Evaporation Streamflow Define the fluxes and flows associated with each hydrovolume Groundwater recharge

60. Coupling Table – Connects fluxes and flows with hydrovolumes A geospatial time series object A geospatial time series object vector Hydrovolume object Coupling FeatureID SourceSinkID TSTypeID Direction FeatureIDSourceSinkIDTSTypeIDDirection 1020925001 1121 113 1141 TSTypeIDVariable 1Daily Streamflow 2Daily Precipitation 3Daily Evaporation 4Daily Subsurface Recharge

61. Monthly Fluxes and Flows P, E, R Q

62. Net Inflow and Cumulative Storage Net Inflow Storage This water balance does not close very well – we need better data! Monthly water balance for one watershed hydrovolume for 2001

63. HydroObjects Class Library HydroObjects API Remote and local Data sources ArcGIS Excel Matlab Custom Models Web Services Backbone of a Hydrologic Information System

64. Hydrology Data Portal is a common data window on point observation data sources CUAHSI web services library supports the data portal and local applications on your computer Digital watershed is a data fusion of point observations, GIS, remote sensing and weather and climate grids Hydrologic Flux Coupler key to integrating atmospheric, surface and subsurface water Conclusions In production In developmentIn research