Transcript 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.

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
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
– Email
– Discussion
• Examinations
– Midterm, final
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
University Without Walls
Traditional Classroom
Community
Inside and Outside
The Classroom
Learning Styles
• Instructor-Centered
Presentation
• Community-Centered
Presentation
Instructor
Student
We learn from the instructors and each other
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
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
Data Model
based on
Inventory of
data layers
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
Polygon - a closed set of lines
Themes or Data Layers
Vector data: point, line or polygon features
Kissimmee watershed, Florida
Themes
Attributes of a Selected Feature
Raster and Vector Data
Raster data are described by a cell grid, one value per cell
Vector
Raster
Point
Line
Zone of cells
Polygon
Santa Barbara, California
http://srtm.usgs.gov/srtmimagegallery/index.html
How do we combine these data?
Digital Elevation
Models
Watersheds
Streams
Waterbodies
An integrated
raster-vector
database
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
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
HIS
National Science Foundation
Geosciences Directorate
CUAHSI Member Institutions
122 Universities as of August 2008
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.
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:
http://his.cuahsi.org/documents/HISOverview.pdf
Water Data
Water quantity
and quality
Soil water
Meteorology
Remote sensing
Rainfall & Snow
Modeling
Point Observations Information Model
Utah State Data Source
Univ
Little Bear RiverNetwork
GetSites
Little Bear River at MendonSites
Rd
Dissolved OxygenVariables
GetSiteInfo
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
WaterML and WaterOneFlow
Locations
Variable Codes
Date Ranges
GetSiteInfo
GetVariableInfo
GetValues
WaterML
WaterOneFlow
Web Service
Data
Penn State
Data
Utah
Stat
Data
NWIS
Data
Repositories
Client
LOAD
TRANSFORM
EXTRACT
WaterML is an XML language for communicating water data
WaterOneFlow is a set of web services based on WaterML
WaterOneFlow
• Set of query functions
• Returns data in WaterML
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
Synthesis and communication of the
nation’s water data http://his.cuahsi.org
Government Water Data
Academic Water Data
National Water
Metadata
Catalog
Hydroseek
WaterML
Texas Water Data Services
Using CUAHSI technology for state and
local data sources (using state funding)
Linking Geographic Information Systems and
Water Resources
GIS
Water
Resources
Arc Hydro: GIS for Water Resources
• Arc Hydro
– An ArcGIS data model
for water resources
– Arc Hydro toolset for
implementation
– Framework for linking
hydrologic simulation
models
The Arc Hydro data model and
application tools are in the public
domain
Arc
Hydro
—
Hydrography
The blue lines on maps
Arc Hydro — Hydrology
The movement of water through the hydrologic system
Integrating Data Inventory using
a Behavioral Model
Relationships between
objects linked by tracing path
of water movement
Arc Hydro Components
Drainage System
Hydro Network
Flow
Time
Time Series
Hydrography
Channel System
Hydrologic Information System
Analysis, Modeling,
Decision Making
Arc Hydro
Geodatabase
A synthesis of geospatial and temporal data supporting hydrologic
analysis and modeling
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
Origin of Geographic Coordinates
Equator
(0,0)
Prime Meridian
Latitude and Longitude
Longitude line (Meridian)
N
W
E
S
Range: 180ºW - 0º - 180ºE
Latitude line (Parallel)
N
W
E
S
Range: 90ºS - 0º - 90ºN
(0ºN, 0ºE)
Equator, Prime Meridian
Latitude and Longitude
in North America
40 50 59 96 45 0
Austin:
(30°18' 22" N, 97°45' 3" W)
Logan:
(41°44' 24" N, 111°50' 9" W)
Lincoln:
(40°50' 59" N, 96°45' 0" W)
90 W
Map Projection
Flat Map
Cartesian coordinates: x,y
(Easting & Northing)
Curved Earth
Geographic coordinates: f, l
(Latitude & Longitude)
Earth to Globe to Map
Map Scale:
Map Projection:
Scale Factor
Representative Fraction
= Globe distance
Earth distance
(e.g. 1:24,000)
=
Map distance
Globe distance
(e.g. 0.9996)
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)