Welcome to Hydro-Informatics.com#
The educational platform and eBook for data analysis & programming, geospatial analysis, and modeling tools in water resources engineering & research.
Harness the potential of vast datasets, including airborne imagery and hydro-meteorological data, to advance water engineering and science. Traditional spreadsheet analysis tools often fall short when it comes to handling and interpreting extensive data. At hydro-informatics.com, our mission is to equip hydraulic engineers, geomorphologists, river ecologists, and anyone working with water resources-related challenges with the necessary knowledge and tools for efficient data analysis and presentation. Our approach leverages freely available software tools to facilitate international and interdisciplinary collaboration.
What is hydro-informatics/hydroinformatics?
The term hydroinformatics (or hydro-informatics) refers to a sub-discipline of hydraulics, environmental engineering, and informatics and has its origins in computational hydraulics. The syllable hydro goes back to the Greek word for water and the term informatics can be used as a synonym for studying computational systems. Hydroinformatics involves numerical modeling as well as data science methods for the efficient and sustainable use of water resources (definition derived from the IAHR’s and IWA Joint Committee on Hydroinformatics). In addition, Abbott [Abb91] emphasizes that “hydroinformatics is the technology of applying computational hydraulics within society”. Bearing this context in mind, the main purpose of this eBook is to make computational hydraulics knowledge freely available to society.
This eBook features a virtual classroom with open source/access materials for lectures and exercises. Students at the University of Stuttgart can learn more about registering for courses in the Take a Seat chapter.
We provide tutorials for:
Coding with Python, including
Collaborative development with version control through git
Guidance to Python (Installation)
A general introduction to Python programming and object orientation)
Guides for code and project documentation (Markdown / reStructuredText)
Machine learning with illustrative exercises and Python implementations to dive into:
the fundamentals of supervised learning
an introduction to unsupervised learning
a tutorial for support vector machines (SVM)
Numerical modeling with
The ETH Zurich’s BASEMENT (v3) software (2d hydrodynamics)
TELEMAC (2d, 3d, and morphodynamics)
OpenFOAM (3d hydrodynamics)
All applications use open-source or open-access software, and the software chapter provides guidance on finding and installing appropriate and efficient software.
The theory chapters come along with exercises that align with the learning contents of this eBook and feature applications in water resources management, hydraulic engineering, and ecohydraulics.
The Troubleshoot chapter provides solutions and information about how to debug known issues (not that issues ever existed…).
Enjoy a successful and entertaining learning experience!