CUAHSI Hydrologic Information System

1. Project co-PI Collaborator CUAHSI Hydrologic Information System

2. CUAHSI Hydrologic Information Systems

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

4. 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

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

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

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

8. 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

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

10. % of time spent preparing data

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

12. 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?

13. How we use software (Austin Symposium)

14. 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).

15. 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

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

17. Hydrology Data Portal

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

19. Data Access and Viewing System in ArcMap

20. CUAHSI Data Portal

21. CUAHSI Data Portal

22. Plot from the Hydrology Data Portal Produced using a CUAHSI Hydrology Web Service: getDailyStreamflowChart

23. CUAHSI Hydrology Web Services for NWIShttp://water.sdsc.edu/HydrologicTimeSeries/NWIS.asmx

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

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

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

27. Issues • Variety of data sources, formats, and data models used in hydrologic sciences • Size and scale of data sources – observation databases, terrain models, NEXRAD, river networks, etc. • Disconnection between geospatial and temporal information systems

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

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

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

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

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

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

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

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

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

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

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

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

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

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

43. Time, T D Space, L Time Series Analysis Variables, V D Geostatistics Multivariate analysis Data to Knowledge D2K Jan Feb 4-D Data Model Image to Knowledge i2K Data Files

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

45. Neuse Observatory Prototype Study

46. 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”

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

48. Stream channel Hydrovolumes

49. 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

50. 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) Time, t v – data values Space (x,y,z) Data Cube Variables, V