Lessons from Adapting Applied Hydrology Instruction to Open Source Software Tools

Resource use decisions in the extractive resource industry in Canada are supported in various ways by collection and analysis of water resources data.  Data quality assurance and analysis are influenced by the methods taught in academic training, the tools used to teach and practice, and industry standards and culture.  The growth in popularity of computer programming languages such as Matlab, Python, and R, and new web-based collaboration and publishing tools from Project Jupyter (Notebook, Book) have created opportunities for teaching applied hydrology in new ways that can support the evolving nature of data in hydrology practice, namely in treating open-ended problems more typical to industry practice.

The abrupt shift to web-based instruction at the undergraduate level in 2019 spurred development of interactive instructional content in an applied hydrology course at the University of British Columbia, in Vancouver, Canada.  Using the open-source Jupyter Book software framework, we developed open-access course material to complement the hydrology theory curriculum.  The new course content consists of a set of tutorials designed to give students a practical introduction to important components of engineering practice such as data quality assurance, and uncertainty in hydrological models.  The content is provided as an open-access online textbook with an embedded Python code interpreter.   With each successive cohort, the material has adapted to student feedback, namely in treating the types of open problems common in industry, and in the amount of programming experience required.