1. CUAHSI Hydrologic Information System
Project co-PI
Collaborator

2. Meeting Agenda Monday Tuesday Wednesday --Training
8:30 to 10 Project Overview
10:30 – noon Project PIs
Lunch provided here
1-3 Live HIS demos
3:30 – 5PM Discussion and feedback, User Assessment
Tuesday
8:30 – 10AM Summary of User Assessment
10:30 – noon Related programs
1-3 National data sets
3:30 – 5PM Other projects related to HIS
Wednesday --Training
Hydrologic Digital Library
Digital Watershed

3. CUAHSI Hydrologic Information Systems

4. Environmental Cyberinfrastructure
Part of NSF Cyberinfrastructure program
Special emphasis on environmental sciences fostered by Margaret Leinen (Asst Dir for GeoSciences)
CUAHSI Hydrologic Information Systems is one of several pilot projects

5. Contains documents, datasets, tools, presentations, tutorials
More data at ftp sites linked to CD
links to project websites at individual universities
Link to CD

6. Hydrologic Information System

7. 1. Hydrologic Observations Database
System
Sampling
Sensing
Transmission
Recording
Laboratory Analysis
Transmission
Editing
Storage
Recording
Off-Site
Measurement
On-Site
Measurement
Retrieval

8. 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
Groundwater
levels
Precipitation
& Climate
Soil
moisture
data
Water Quality
Flux tower
data

9. Data Cube
Space, L
Time, T
Variables, V D

10. Data Cube in Arc Hydro Time, TSDateTime TSValue Space, FeatureID
Variables, TSTypeID

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

12. ArcIMS Website for hydrologic observational data
Neuse basin
Thanks to ESRI San Antonio

13. Output from the ArcIMS website
Data open directly in Excel

14. Database Design
Relationships

15. Automated Data Harvesting
Begin with a site file showing where data are available
Develop automated harvesting tools to ingest observations from agency websites
John Helly has done this for the NWIS data
NWIS Surface Water Sites
(Ken Lanfear)
ACIS Climate Stations
(Bill Noon)

16. Hydrologic Statistics
Upmanu Lall
is our expert in
this area
Time Series Analysis D
Geostatistics
Multivariate analysis
How do we understand space-time correlation fields of many variables?

17. Aquatic Ecology
What kind of ecological observation data should we be collecting?
What kind of HIS does an aquatic ecologist need?
LeRoy Poff is our expert in this area
Hydrology
Ecology
Geomorphology

18. Some Conclusions
Hydrologic Observations Database design works and is ready for independent review and testing
Automated data harvesting may produce a “one stop shop” for observational data
There will never be enough database fields to describe all we want to know about data
We need a hybrid database—files solution
This is what the San Diego Supercomputer Center is doing for us
“Pile of files”
Relational
database

19. Hydrologic Information System

20. Sensor Network Interfaces to Digital Library
John Helly is our expert in this subject!
Example is for wireless network in Santa Margarita watershed, San Diego

21. HydroViewer Provides Access to…
Neuse Watershed Collection
Santa Margarita Watershed Collection
+ your Hydrologic Observatory Data Collection

22. CUAHSILink enables ArcMap to read files directly from the Digital
Library through an application programming interface

23. New Concept of Publication
Hydrologic
Digital Library
Normal Method +

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

25. Ontologies for Metadata Profile
Page 10
Ontologies for Metadata Profile
Hydrologic Metadata
A consistent suite of
geographic information
schemata that will allow
Geographic information
to be integrated with
information technology.
ISO norm
Semantic WEB
Definition: The Semantic Web is
the representation of data on
the World Wide Web. It is based
on the Resource Description
Framework (RDF), which integrates
a variety of applications using
XML for syntax and URIs for naming.
"The Semantic Web is an extension of
the current web in which information is
given well-defined meaning, better
enabling computers and people to work
in cooperation."
Hydrologic Ontology
Prepare the CUAHSI
Metadata Profile
for the Future!
Drexel University, College of Engineering

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

27. Hydrologic Information System

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

29. Hydrologic Data Model We need to represent the physical environment
Hydrologic Fluxes and Flows
Digital Watershed (Atmospheric, surface and subsurface water)
We need to represent the physical environment
and water flowing through it

30. Created first for the Neuse basin
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. 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

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. HIS-USA
Base map information for building digital watersheds anywhere in the US
Hydrologic Observatory regions
Monitoring site files
National river network connected to HUC watersheds
Hydrologic landscape regions

39. Hydrologic Information System

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

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

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

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

44. Neuse Observatory Prototype Study

45. 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”

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

47. Stream channel Hydrovolumes

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

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

50. Flux Coupling Table All Hydrofeatures have a unique HydroID
Coupling table links all features that have
flux and flow data needed for the water balance
9748
9614
9623
9749
Flux and flow data

51. Flows and Fluxes Q
P, E, R

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

53. Hydrologic Information System
A combination of geospatial and temporal hydrologic information
which supports analysis, modeling and decision making
Modeling

54. Connecting Arc Hydro and Hydrologic Models
GIS
Interface data models
HMS
Geo
Database
Arc Hydro
data model
RAS
Modflow
This requires time series data bridges
between geodatabase and binary
files for hydrologic models

55. Conclusions
Hydrologic Observations Database and Hydrologic Digital Library are functional and reading for testing
Digital Watershed for Neuse has been built and can be expanded
we’d be pleased to work with other Observatory teams to help them build a Digital Watershed
Work on hydrologic flux coupler is developing