1. GIS in Water Resources: Lecture 1
In-class and distance learning
Geospatial database of hydrologic features
GIS and HIS
Curved earth and a flat map

2. Six Basic Course Elements
Lectures
Powerpoint slides
Video streaming
Readings
“Arc Hydro: GIS in Water Resources”
Homework
Computer exercises
Hand exercises
Term Project
Oral presentation
HTML report
Class Interaction
Discussion
Examinations
Midterm, final

3. Our Classroom Dr David Tarboton Students at Utah State University
Dr Ayse Irmak Students at University of Nebraska - Lincoln
Dr David Maidment Students at UT Austin

4. University Without Walls
Traditional Classroom
Community
Inside and Outside
The Classroom

5. Learning Styles Instructor-Centered Presentation
Community-Centered Presentation
Instructor
Student
We learn from the instructors and each other

6. GIS in Water Resources: Lecture 1
In-class and distance learning
Geospatial database of hydrologic features
GIS and HIS
Curved earth and a flat map

7. Geographic Data Model
Conceptual Model – a set of concepts that describe a subject and allow reasoning about it
Mathematical Model – a conceptual model expressed in symbols and equations
Data Model – a conceptual model expressed in a data structure (e.g. ascii files, Excel tables, …..)
Geographic Data Model – a conceptual model for describing and reasoning about the world expressed in a GIS database

8. Data Model based on Inventory of data layers

9. Spatial Data: Vector format
Vector data are defined spatially:
(x1,y1)
Point - a pair of x and y coordinates
vertex
Line - a sequence of points
Node
DRM
Polygon - a closed set of lines

10. Themes or Data Layers
Vector data: point, line or polygon features

11. Kissimmee watershed, Florida
Themes

12. Attributes of a Selected Feature

13. Raster and Vector Data Vector Raster Point Line Polygon
Raster data are described by a cell grid, one value per cell
Vector
Raster
Point
Line
DRM
Zone of cells
Polygon

14. Santa Barbara, California

15. How do we combine these data?
Digital Elevation
Models
Watersheds
Streams
Waterbodies

16. An integrated raster-vector database

17. GIS in Water Resources: Lecture 1
In-class and distance learning
Geospatial database of hydrologic features
GIS and HIS
Curved earth and a flat map

18. What is CUAHSI?
UCAR
CUAHSI – Consortium of Universities for the Advancement of Hydrologic Science, Inc
Formed in 2001 as a legal entity
Program office in Washington (5 staff)
NSF supports CUAHSI to develop infrastructure and services to advance hydrologic science in US universities
Unidata
Atmospheric
Sciences
Earth
Sciences
Ocean
Sciences
CUAHSI
National Science Foundation
Geosciences Directorate
HIS

19. CUAHSI Member Institutions
122 Universities as of August 2008

20. Hydrologic Information System Goals
Data Access – providing better access to a large volume of high quality hydrologic data;
Hydrologic Observatories – storing and synthesizing hydrologic data for a region;
Hydrologic Science – providing a stronger hydrologic information infrastructure;
Hydrologic Education – bringing more hydrologic data into the classroom.

21. HIS Overview Report
Summarizes the conceptual framework, methodology, and application tools for HIS version 1.1
Shows how to develop and publish a CUAHSI Water Data Service
Available at:

22. Water quantity and quality
Water Data
Water quantity and quality
Soil water
Rainfall & Snow
Modeling
Meteorology
Remote sensing

23. Point Observations Information Model
Utah State
Univ
Data Source
Little Bear River
Network
GetSites
Little Bear River at Mendon Rd
Sites
GetSiteInfo
Dissolved Oxygen
Variables
GetVariableInfo
GetValues
9.78 mg/L, 1 October 2007, 5PM
Values
{Value, Time, Metadata}
A data source operates an observation network
A network is a set of observation sites
A site is a point location where one or more variables are measured
A variable is a property describing the flow or quality of water
A value is an observation of a variable at a particular time
A metadata quantity provides additional information about the value

24. WaterML and WaterOneFlow
Locations
Variable Codes
Date Ranges
Penn State
Data
GetSiteInfo
GetVariableInfo
GetValues
Utah State
Data
NWIS
WaterML
Data
WaterOneFlow
Web Service
Data
Repositories
Client
TRANSFORM
EXTRACT
LOAD
WaterML is an XML language for communicating water data
WaterOneFlow is a set of web services based on WaterML

25. WaterOneFlow
Set of query functions
Returns data in WaterML

26. CUAHSI National Water Metadata Catalog
Indexes:
50 observation networks
1.75 million sites
8.38 million time series
342 million data values
NWIS
STORET
TCEQ

27. National Water Metadata Catalog
Synthesis and communication of the nation’s water data
Government Water Data
Academic Water Data
National Water Metadata Catalog
Hydroseek
WaterML

28. Texas Water Data Services
Using CUAHSI technology for state and local data sources (using state funding)

29. Linking Geographic Information Systems and Water Resources
GIS

30. Arc Hydro: GIS for Water Resources
An ArcGIS data model for water resources
Arc Hydro toolset for implementation
Framework for linking hydrologic simulation models
Notes:
Industrial partners: ESRI, Danish Hydraulic Institute, Camp,Dresser and McKee, Dodson and Associates
Government partners:
Federal: EPA, USGS, Corps of Engineers (Hydrologic Engineering Center)
State: Texas Natural Resource Conservation Commission, Texas Water Development Board
Local: Lower Colorado River Authority, City of Austin, Dept of Watershed Protection
Academic Partners: University of Texas, Brigham Young University, Utah State University
The Arc Hydro data model and
application tools are in the public
domain

31. Arc Hydro — Hydrography
The blue lines on maps

32. Arc Hydro — Hydrology
The movement of water through the hydrologic system

33. Integrating Data Inventory using a Behavioral Model
Relationships between
objects linked by tracing path
of water movement

34. Arc Hydro Components Drainage System Hydro Network Time Series
Flow
Time
Time Series
Channel System
Hydrography

35. Hydrologic Information System
Analysis, Modeling,
Decision Making
Arc Hydro
Geodatabase
A synthesis of geospatial and temporal data supporting hydrologic analysis and modeling

36. GIS in Water Resources: Lecture 1
In-class and distance learning
Geospatial database of hydrologic features
GIS and HIS
Curved earth and a flat map

37. Origin of Geographic Coordinates
Equator
(0,0)
Prime Meridian

38. Latitude and Longitude
Longitude line (Meridian) N W E S
Range: 180ºW - 0º - 180ºE
Latitude line (Parallel) N W E S
(0ºN, 0ºE)
Equator, Prime Meridian
Range: 90ºS - 0º - 90ºN

39. Latitude and Longitude in North America
90 W
120 W
60 W
30 N
0 N
60 N
Austin:
Logan:
Lincoln:
(30°18' 22" N, 97°45' 3" W)
(41°44' 24" N, 111°50' 9" W)
(40°50' 59" N, 96°45' 0" W)

40. Map Projection Flat Map Curved Earth Cartesian coordinates: x,y
(Easting & Northing)
Curved Earth
Geographic coordinates: f, l
(Latitude & Longitude)
DRM

41. Earth to Globe to Map Map Projection: Map Scale: Scale Factor
Representative Fraction
Globe distance Earth distance =
Scale Factor
Map distance Globe distance =
(e.g. 1:24,000)
(e.g )

42. Coordinate Systems A planar coordinate system is defined by a pair
of orthogonal (x,y) axes drawn through an origin Y X
Origin
(xo,yo)
(fo,lo)