The educational platform and eBook for data insights with Python programming, numerical modeling, software guidance, and geospatial analysis in water resources engineering & research.
Preface¶
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
Contents¶
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 fundamentals with illustrative exercises and Python implementations:
Introduction to supervised learning
Tutorial for support vector machines (SVM) for classification of fluvial morphological patterns
Numerical modeling of rivers with:
The ETH Zurich’s BASEMENT (v4) 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!
- Abbott, M. B. (1991). A Central Issue of Teaching within the Hydroinformatics Paradigm. La Houille Blanche, 77(3–4), 257–261. 10.1051/lhb/1991024