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CUAHSI Hydrologic Information System Project co-PI Collaborator CUAHSI Hydrologic Information System Project co-PI Collaborator

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

CUAHSI Hydrologic Information Systems CUAHSI Hydrologic Information Systems

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

 • Contains documents, datasets, tools, presentations, tutorials • More data at ftp sites • Contains documents, datasets, tools, presentations, tutorials • More data at ftp sites linked to CD • http: // links to project websites at individual universities Link to CD

Hydrologic Information System Hydrologic Information System

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

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

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

Data Cube in Arc Hydro Time, TSDate. Time TSValue Space, Feature. ID Variables, TSType. Data Cube in Arc Hydro Time, TSDate. Time TSValue Space, Feature. ID Variables, TSType. ID

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

Arc. IMS Website for hydrologic observational data Thanks to ESRI San Antonio Neuse basin Arc. IMS Website for hydrologic observational data Thanks to ESRI San Antonio Neuse basin

Output from the Arc. IMS website Data open directly in Excel Output from the Arc. IMS website Data open directly in Excel

Database Design Relationships Database Design Relationships

Automated Data Harvesting • Begin with a site file showing where data are available 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)

Hydrologic Statistics Upmanu Lall is our expert in this area Time Series Analysis D 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?

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

Some Conclusions • Hydrologic Observations Database design works and is ready for independent review 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 Relational database “Pile of files”

Hydrologic Information System Hydrologic Information System

Sensor Network Interfaces to Digital Library John Helly is our expert in this subject! 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

Hydro. Viewer Provides Access to… http: //cuahsi. sdsc. edu Neuse Watershed Collection Santa Margarita Hydro. Viewer Provides Access to… http: //cuahsi. sdsc. edu Neuse Watershed Collection Santa Margarita Watershed Collection + your Hydrologic Observatory Data Collection 21

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

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

Page 3 The Demands Numerical Models Prediction Air-Q Sensor Arrays HSPF MM 5 NCDC Page 3 The Demands Numerical Models Prediction Air-Q Sensor Arrays HSPF MM 5 NCDC METADATA USGS NWIS NCEP NWS Data Centers Drexel University, College of Engineering NGDC Individual Samples

Page 10 Ontologies for Metadata Profile Hydrologic Metadata A consistent suite of geographic information 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 19115. Semantic WEB Hydrologic Ontology www. isotc 211. org 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. http: //www. w 3. org/2001/sw/ Prepare the CUAHSI Metadata Profile for the Future! Drexel University, College of Engineering "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. "

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

Hydrologic Information System Hydrologic Information System

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

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

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

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

Neuse Surface Water • Streamflow, water quality hydrologic observational data • GIS: River network, 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

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

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

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

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

HIS-USA • Base map information for building digital watersheds anywhere in the US • 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

Hydrologic Information System Hydrologic Information System

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

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

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

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

Neuse Observatory Prototype Study Neuse Observatory Prototype Study

Hydro. Volumes Take a watershed and extrude it vertically into the atmosphere and subsurface Hydro. Volumes 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”

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

Stream channel Hydrovolumes Stream channel Hydrovolumes

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

Discrete Space-Time Data Model Time, TSDate. Time TSValue Space, Feature. ID Variables, TSType. ID Discrete Space-Time Data Model Time, TSDate. Time TSValue Space, Feature. ID Variables, TSType. ID

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

Flows and Fluxes Q P, E, R Flows and Fluxes Q P, E, R

Net Inflow and Cumulative Storage Monthly water balance for one watershed hydrovolume for 2001 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!

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

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

Conclusions • Hydrologic Observations Database and Hydrologic Digital Library are functional and reading for 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