Hydroinformatics

A PDF file of the entire course syllabus is available here.

Class Time: Tuesday / Thursday 3:00 - 4:15 PM

Class Locations:

Utah State University: Distance Education 105
University of Utah: Park Bldg 302
Brigham Young University: 368F Clyde Building

Instructors:

Jeff Horsburgh

Utah State University

Offices: ENGR 223 / UWRL 201

Office Hours: T/TH 4:15 – 5:15 PM in ENGR 223, or by appointment

E-mail: jeff.horsburgh@usu.edu

Phone: 435-797-2946

David Rosenberg

Utah State University

Offices: ENGR 213 / UWRL 205

Office Hours: T/TH 4:15 to 5:15 PM in ENGR 213, or by appointment

E-mail: david.rosenberg@usu.edu

Phone: 435-797-8689

Dan Ames

Brigham Young University

Office: 242J Clyde Building

Office Hours:

E-mail: dan.ames@byu.edu

Phone: 208-406-8055

Steven Burian

University of Utah

Offices: MCE 2044

Office Hours: M/W 10-11 am, or by appointment

E-mail: steve.burian@utah.edu

Phone: 801-585-5721

Course Offering

This course will be simultaneously offered across the CI-WATER (http://ci-water.org/) partner campuses (USU, UofU, and BYU). Additional support is being provided by the iUTAH Project (http://www.iutahepscor.org/). Each university has designated an instructor to manage things on their end, be present during class time, help deliver course content, and evaluate plus support work by students on their campus. Support for development of this course was provided by National Science Foundation Grants No. EPS 1135482, and EPS 1208732. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.

nsf_epscor_lg.jpg.gif

Course Overview

Hydroinformatics is the study, design, development, and deployment of hardware and software systems for hydrologic data collection, distribution, interpretation, and analysis to aid in the understanding and management of water in the natural and built environment. This class will introduce students to fundamental and advanced hydroinformatics concepts and procedures including automated data collection networks, relational databases and data management software, metadata and semantics, data storage file formats and standards, data transformations and automation of data manipulation tasks to support modeling and analysis, web based data distribution and access using web services, and integrated networks of hydro-climate data.

The course has an open, project-type format where students will work individually or in a small group over the semester to discover, organize and manage data for a hydrology or water resources problem of their interest. Projects may include designing appropriate data models and automating data loading, manipulation, and transformations in support of data intensive analyses or modeling. Class time will include lectures focused on learning and developing data management, transformation, and task automation skills, class discussions, code writing exercises to solve data manipulation tasks, demonstration of software and data systems, and student presentations of their project work. The course will better prepare students to work in data-intensive research and project work environments and emphasize development of reproducible processes for managing and transforming data in ways that others can easily and completely reproduce on their own to support analyses and modeling. Additionally, this course will better prepare students to work across multiple software platforms and systems used in data management.

Learning Objectives

Upon successfully completing this course, students will be able to:

Data and the Data Life Cycle:

Describe the data life cycle
Determine the dimensionality of a dataset, including the scale triplet of support, spacing extent for both space and time
Generate metadata and describe datasets to support data sharing
Discover and access data from major data sources

Databases and Data Models:

Store, retrieve, and use data from important data models used in Hydrology such as ArcHydro, NetCDF, and the Observations Data Model (ODM)
Develop data models to represent, organize, and store data
Design and use relational databases to organize, store, and manipulate data
Query, aggregate, and pivot data using Structured Query Language (SQL), Excel, R, and other software systems

Visualization, Transformations, Analysis, and Modeling:

Create reproducible data visualizations
Write and execute computer code to automate difficult and repetitive data related tasks
Manipulate data and transform it across file systems, flat files, databases, programming languages, etc.
Retrieve and use data from Web services
Organize data in a variety of platforms and systems common in hydrology and engineering
Prepare data to support hydrologic, water resources, and/or water quality modeling

Pre-requisites

Required:

Graduate student standing
Proficiency in Microsoft Excel and Geographic Information Systems (GIS)
Familiarity and ability to write simple programs in any programming language such as C, C++, C#, Fortran,Visual Basic, R, Matlab, Python, or Java.

Recommended:

Concurrent or prior enrolment in a database class, Hydrologic Modeling, Integrated River Basins/Watershed Planning and Management (CEE 6490), GIS in Water Resources (CEE6440)

Texts

Required readings will be posted on this website or distributed in class.

Some potential references, but not required:

Kumar, P., (2005), Hydroinformatics: Data Integrative Approaches in Computation, Analysis, and Modeling, CRC Press, 552 p.
Grayson, R. and G. Blöschl, ed. (2000), Spatial Patterns in Catchment Hydrology: Observations and Modelling, Cambridge University Press, Cambridge, 432 p, full PDF text available at http://www.catchment.crc.org.au/special_publications1.html.

Class Schedule

The class schedule is subject to change. Please check the Syllabus link regularly for updates to the class schedule. Lecture materials and assigned readings are being posted to the Lecture Materials page.

Description of Required Course Work

Individual Learning Opportunities (ILOs)

Students will complete a series individual learning opportunities (ILOs). Each ILO will pose a problem related to data organization, management, or transformation and will require use of software tools and/or computer programming/automation to solve. The list of ILOs follows, but is subject to change:

ILO-1. Metadata and the data lifecycle
ILO-2. Data model design
ILO-3. Google Fusion Tables and visualization and mapping in Excel
ILO-4. Database implementation and loading data
ILO-5. Querying, visualizing, transformation, and analysis
ILO-6. Automation of data management tasks
ILO-7. Accessing data using web services
ILO-8. Deploying an HIS HydroServer to share your data
ILO-9. Preparing data for input to a model

Students will submit the answer to each ILO in the format of a 1-page engineering report or briefing paper. Each report should be formatted with standard 12-point font, 1-inch margins, and be fully self-contained to include an introduction to the problem, methods used, and results obtained so that a technically-versed reader not familiar with the problem statement can understand the rationale for, methods used, and results of the work presented. The restriction to 1 page is to help develop clear and succinct writing skills. Planners, managers, politicians, and decision makers rely on the work of engineers and hydroinformatics experts but are very busy people who rarely understand computer code or the underlying technologies. References, figures, tables, listing of code, and more detailed explanations can be included in appendices that do not count towards the 1-page limit. Students not satisfied with their performance on an ILO report may revise and resubmit it up to 1 week after the instructors evaluate and return the ILO report.

Semester Project

A large part of the course work will involve a semester-long project. Individuals or groups of up to 3 students will choose a hydrology or water resources data management problem to study for the semester. As part of the project, students will identify the data, data dimensionality, and lifecycle of the data required to solve the problem and develop metadata to describe and a data model to organize the data. Subsequently, students will implement the data model in a data management system and undertake querying, pivoting, and transformation activities to move the data into a model and/or analysis that uses the data. Students will report and make recommendations based on their results. Semester project work will comprise the following components:

Topic: A title and short paragraph describing the data management problem to be explored (not graded).
Interim oral presentation: A brief, in-class presentation that gives background on the data management problem you have selected for your semester project. Described the data, including dimensionality, lifecycle, metadata, and data model and/or formats that you will use to organize the data.
Final Project Report: Students will write a final project report providing general information on their data management project, as well as documentation of and results of their work. Final reports should synthesize all the work done on the project for the semester and allow readers to access and reproduce the methods developed and used. Please note that final project reports will be made publicly available on the course website.
Peer review: Students will be assigned to provide feedback to another project report. Students will assess whether the work they review is reproducible and identify ways the study and write-up could be improved.
Final oral presentation: Your final project oral presentation should expand upon the first interim presentation to include details about software used, code written, databases developed, data transformations performed, modeling and/or analysis undertaken, and key results. You will deliver your final presentation in class, and it will be broadcast to all three campuses.

Class Participation

We expect students to read assigned readings ahead of time and come to class and share their impressions of the reading(s) or ask questions on points they did not understand. At times, we may discuss readings in a seminar format. During lectures or discussions, the instructors will ask many questions, and, if needed, call on you individually to ensure everyone participates.

Grading of and Expectations for Submitted Work

Approximate Grading:

Individual Learning Opportunities			50%
Semester Project			40%
	Interim oral presentation	10%
	Final project report	15%
	Peer review	5%
	Final oral presentation	10%
Class Participation			10%

90 to 100% -- at least some sort of A
80 to 90% -- at least some sort of B
70 to 80% -- at least some sort of C
< 70% -- most probably some sort of F

There is no curve. All submitted work (that meets grading rubric standards) will earn an “A”.

All submitted work will be graded for technical correctness, organization, clarity, presentation, and other criteria according to the Grading Rubric available on the class website for the item. We will ask to meet with students who submit low quality work to discuss improvement strategies.

Submitted work must be:

Original, typed with 1” margins in a standard 12-point font, printed, and stapled.
Have a title page with title, student name(s), date, email address(es), class, and instructor.
Handed in at the beginning of class on the due date listed on the class web page.
Turned in with the self-assessment portion of the Grading Rubric completed.
Turned in with the Group (and self) Rating Form completed (for group work items).
Turned in with duplicate electronic copy and the self-assessment via Canvas.
For group work, only one paper and Canvas copy need be submitted.
We do not accept late assignments. They will be graded as zero. In extenuating circumstances (birth/death in the immediate family; grave illness with doctor’s note), contact the instructors prior to the due date and make alternative arrangements.

Academic Integrity: We expect each student to uphold academic integrity. See http://www.usu.edu/policies/PDF/Acad-Integrity.pdf. For example, USU, the CEE department, and the instructors take plagiarism seriously, and we will hold offending parties to the full extent of the USU Code. When in doubt, acknowledge sources, cite references, and properly quote material that is not your own.

Electronic Policies

Class Webpage: We will post all class materials to the class webpage (this website in Canvas) including readings, lecture materials, and descriptions of and grading rubrics for all course work.
Canvas: Submit electronic versions of all work and self evaluations to Canvas (for grading and archiving purposes).
Project Reports: Please note that your project reports will be made publicly available.
Email: Include “Hydroinformatics” in the subject line of all email so that we can timely attend and respond to emails. Unless you request that we don’t, we may forward email questions and answers to the entire class.

Expectations of Students

Be on-time to class and ready to learn / participate when class starts.
Read assigned readings ahead of time and come to class prepared to share your impression(s) of the reading(s) and/or ask questions on points you do not understand.
Turn off or keep silent all electronic devices that may distract the instructors or other students. We will ask students using phones, pagers, PDAs, music players, etc. to leave class.
Contribute to class discussions while being respectful of and listening to others’ points of view.
Turn in all work on time in the required format.
Bring questions and concerns forward during class, office hours, or by chat or email.
Put in approximately 2 – 5 hours outside of class for each 1 hour of in-class time.

Expectations of the Instructors

Start class on time.
Respect the value of student’s time.
Call equally on all students for class participation.
Learn student names by some point through the semester.
Facilitate an environment of inclusivity and non-discrimination.
Respond to email within 30 hours when we are not traveling out of town.
Return graded work within 1 week from when work is submitted.

Disability/Special Accommodations

Please talk to one of the instructors immediately if you require disability or other special accommodations.

Additional Resources for Students

Partial list of data management problems for semester study
CUAHSI Hydrologic Information System Website: http://his.cuahsi.org
Class web page: http://jeffh.usu.edu/teaching/2012/CEE6930/
Dr. Rosenberg’s web page: http://www.engr.usu.edu/cee/faculty/derosenberg/
Dr. Horsburgh’s web page: http://jeffh.usu.edu
Dr. Burian’s web page: http://www.civil.utah.edu/~burian/

Please direct further questions or concerns about the syllabus or the course to one of the instructors by email, in person, or phone.