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 – –Discussion Examinations –Midterm, final

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

University Without Walls Traditional Classroom Community Inside and Outside The Classroom

Learning Styles Instructor-Centered Presentation Community-Centered Presentation Student Instructor 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 Point Point - a pair of x and y coordinates (x 1,y 1 ) Line Line - a sequence of points Polygon Polygon - a closed set of lines Node vertex Vector data are defined spatially:

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

Kissimmee watershed, Florida Themes

Attributes of a Selected Feature

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

Santa Barbara, California

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

Ocean Sciences What is CUAHSI? 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 Earth Sciences Atmospheric Sciences UCAR CUAHSI Unidata 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:

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

Point Observations Information Model Data Source Network Sites Variables Values {Value, Time, Metadata} Utah State Univ Little Bear River Little Bear River at Mendon Rd Dissolved Oxygen 9.78 mg/L, 1 October 2007, 5PM 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 GetSites GetSiteInfo GetVariableInfo GetValues

Locations Variable Codes Date Ranges WaterML and WaterOneFlow GetSiteInfo GetVariableInfo GetValues WaterOneFlow Web Service Client Penn State Utah State NWIS Data Repositories Data EXTRACT TRANSFORM LOAD WaterML 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

National Water Metadata Catalog Synthesis and communication of the nation’s water data HydroseekWaterML Government Water DataAcademic Water Data

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

Flow Time Time Series HydrographyHydro Network Channel System Drainage System Arc Hydro Components

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 (0,0) Equator Prime Meridian

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

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)

Map Projection Curved Earth Geographic coordinates: , (Latitude & Longitude) Flat Map Cartesian coordinates: x,y (Easting & Northing)

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

Coordinate Systems (  o, o ) (x o,y o ) X Y Origin A planar coordinate system is defined by a pair of orthogonal (x,y) axes drawn through an origin