Open science is commonly associated with open access publications, and FAIR (findable, accessible, interoperable and reusable) data. Open source code is progressively being considered an essential component of open science, too. However, even if all these ingredients are available and openly accessible, it is often impossible to reproduce the graphs in a paper from the data and code provided. Which script was used on what part of the data to generate a given plot? Which version of a cited database was used, and what query to extract the presented data points? Moreover, even the basic steps of a scientific analysis, i.e. the derivation of mathematical equations, are often not traceable. Ever came across the famous “it follows that”, where, what follows, contains variables that were not present in the preceding equations?

Here I present part of a hydrology course based on a framework designed to address many of the above challenges. It is based on the open-source RENKU platform and deployed in a Jupyterhub instance at https://renkulab.io. RENKU enables the tracking of datasets and their versions, and records executions of code with their respective input and output files, producing a knowledge graph of the entire project and enabling the user to easily re-do all necessary steps to update relevant results whenever a data or code file is updated. RENKULAB uses the docker system to help reproduce the computational environment needed to re-execute the analysis. This greatly facilitates collaborative research and learning, as it removes the need for collaborators and students to recreate the computational environment in their local systems. Integration of GITLAB in RENKULAB facilitates student feedback and collaborative problem solving through issue tracking, where students can gain points by submitting meaningful issues and helping others.

The course also uses an open source package for mathematical derivations (ESSM, https://essm.readthedocs.org), which is based on the Python package Sympy, and facilitates clear definitions of variables including their dimensions and units, and dimensionally consistent fundamental equations. These can then be used to deduce derived equations by automatic solving of systems of equations for unknown variables, derivatives, integrations, and many other mathematical operations contained in Sympy. The package combines graphical depiction of equations, as seen in papers, with computational reproducibility of derivations and transparent re-use of equations in numerical code.

By employing Open Science approaches from the start, students become naturally accustomed to reproducible research and can use the skills they learn in any professional environments, as they are not bound to proprietary software that their future employers and collaborators may or may not have purchased licenses for.

How to cite: Schymanski, S.: The benefits of Open Science approaches when teaching hydrology, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-12489, https://doi.org/10.5194/egusphere-egu23-12489, 2023.

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. 

How to cite: Kovacek, D. and Weijs, S.: Lessons from Adapting Applied Hydrology Instruction to Open Source Software Tools, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-10592, https://doi.org/10.5194/egusphere-egu23-10592, 2023.

Recent developments in hydrologic science include a strong focus on open-source data sets and modeling tools. These developments can easily be leveraged into hydrologic education in the form of classroom exercises and term projects. Here we present a computational exercise designed to teach the concept of model structure uncertainty to students, using a specific selection of two catchments and two simple conceptual models from open-source data and tools.

The exercise first familiarizes the students with the modeling tool they will use and then has them calibrate and evaluate model performance on each combination of model and catchment. For these specific catchment and models, model structure uncertainty is the dominant source of uncertainty (compared to data, parameter and objective function uncertainties). The exercise includes guiding questions that help the students reach the defined learning goals. Trials at the Technische Universität Dresden show that the exercises are effective in doing so. This introduction to open-source models and data yields the benefit of being easily expanded on during further exercises and term projects.

How to cite: Knoben, W. and Spieler, D.: An example of using open-source data and hydrology models for classroom exercises and term projects, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-2675, https://doi.org/10.5194/egusphere-egu23-2675, 2023.

Active learning strategies such as simulations or problem sets have been shown again and again to be critically useful for helping students understand complex concepts. Students develop a more thorough understanding of processes or problem solving strategies when they are able to practice or explore them with hands-on activities. In hydrology, however, there are several concepts taught, even in introductory classes, where developing suitable activities for this type of learning is difficult. For example, even a simple water balance activity often requires a relatively thorough understanding of spreadsheets or a lot of tedious hand-calculations if students are going to explore relationships between multiple inputs and outputs. Similarly, even the most basic discussion of how a simple box model works is difficult to supplement with an activity that doesn’t involve spreadsheets or writing computer code. Furthermore, it is often beyond the scope of introductory level hydrology classes to teach programming or spreadsheet skills, and hand calculations often take a prohibitive amount of time. Web applications offer a tool to address some of these issues. With the development of tools like Shiny apps for R or Python, instructors with programming experience can relatively easily create interactive learning tools for their classes. Many studies in fields such as statistics and mathematics have shown that these web-apps aid in student learning. Furthermore, hosting and sharing these apps is becoming more accessible, with organizations like CUAHSI running shiny servers. In this presentation, I will show two examples of implementations of a web app to aid in student learning, one on the concept of a water balance, and one on running and parameterizing a basic catchment hydrology model. I will also discuss tools and strategies for building and hosting your own shiny app to address the learning goals for your classes.

How to cite: Gannon, J.: Web-apps as active learning tools in hydrology classrooms, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-8427, https://doi.org/10.5194/egusphere-egu23-8427, 2023.

Groundwater represents more than 97% of the globally available freshwater resources. Groundwater is situated in geological structures in the subsurface and is therefore not visible, difficult to characterize, and manage. As a consequence, it is often not adequately considered by authorities, the general public – and in education. However, teaching and learning Hydrogeology and Groundwater Management at universities, but also as a part of continuing education training for professionals, is essential to deal with future challenges. For this reason, it is important to use suitable teaching material to improve the understanding of the complex topic of groundwater among these target groups. The recent challenge of the COVID-19 pandemic has increased the demand for digital and remote teaching. An ongoing Erasmus+ cooperation project named iNUX – interactive understanding of groundwater hydrogeology aims to address the need for digital teaching material. The project aims to achieve an interactive and digital learning environment in hydrogeology and groundwater management with a European but also global target of teachers and students.

Existing experience in teaching relevant groundwater subjects from highly reputable European universities will be used to develop interactive and digital teaching material focusing on basic and applied hydrogeology. The teaching material will cover basic theory in combination with field and laboratory applications in different European environments (Northern Europe, Central Europe, and the Mediterranean). The teaching material will comprise (1) various types of videos (e.g., field experiments, lab experiments, screencasts of calculations and software use), (2) interactive Jupyter notebooks that combine explanation with live code (e.g., based on Python), (3) various types of questions and problems that allow different assessments to enhance self-controlled learning of students. All materials are intended as open source and publicly available. The iNUX activities also comprise initiatives to establish interest groups to combine efforts towards larger pools of commonly developed digital teaching material (e.g., question pools) and to link with other activities like the 'Groundwater project' (https://gw-project.org/).

How to cite: Reimann, T., Barthel, R., Birk, S., Fernandez-Garcia, D., and Chen, Z.: Interactive understanding of groundwater hydrology and hydrogeology – the iNUX project, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-14794, https://doi.org/10.5194/egusphere-egu23-14794, 2023.

Precipitation is one of the essential parts of the hydrological cycle. Regardless of the important role that precipitation plays for life on Earth, in extreme conditions, such as high intensities and amounts, it can negatively affect various ecosystem services (e.g., flood protection, agriculture). Precipitation is spatially highly variable. Traditionally, precipitation, with rain as the most common type, is measured over very small surface areas (of a few square decimetres) by rain gauges or sensors. However, reliable and representative rainfall data are crucial for understanding the interconnection of different parts of the hydrological cycle (e.g., rainfall interception by vegetation, rainfall erosivity) and quantification of flood, drought, water quality, and other water-related problems. Reducing the negative consequences of the mentioned problems is part of the 2030 Agenda sustainable development goals. Therefore, an interdisciplinary student project on the design and construction of a rainfall simulator was submitted to the University of Ljubljana's call for sustainable development student projects. Rainfall simulators are recognized as important tools for studying the effects of rain on soil. Rainfall simulators can be used in controlled conditions in the laboratory or with additional settings also in the field. The design and construction of the simulator is entirely within the domain of the project team of six students of environmental civil engineering and electrical engineering. This includes the choice of pipe materials, pump capacity, size and type of spray nozzles, development of a control system for monitoring and recording of results, and, last but not least, the determination of rain properties we would like to simulate (e.g., intensity). Three pedagogical mentors and one mentor outside the academia supervise the project. With such a project, group work and co-creation are encouraged among students, theoretical knowledge acquired within the curriculum is transferred into practice and knowledge is exchanged between different disciplines. Skills such as communication, critical thinking, organization of tasks and time management, interdisciplinary problem solving, analytical reasoning, information and technology literacy, are developed in the project. Additionally, such equipment will be used for teaching and research purposes in the future, which is another sustainable feature of this project.

How to cite: Klun, M., Lebar, K., Zabret, K., and Zdešar, A.: Design and construction of a rainfall simulator: an interdisciplinary student project towards sustainable development goals achievement, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-5020, https://doi.org/10.5194/egusphere-egu23-5020, 2023.

Regular visitors of the EGU General Assembly are familiar with the ‘MacGyver’ sessions where hydrologists present measuring solution they have designed, build and tinkered (often ducttaped) themselves. We often get asked how we convey the MacGyver mentality to our students: how to teach them the skills and attitude to tackle their own problems hands on?

We teach this in the undergraduate course ‘measuring water’. In this course the learning goals include teaching hydrology students how to measure the different states and fluxes in the water cycle. We approach this by having teams of students design, make and demonstrate their own sensor. This ‘maker-education’ approach is known for stimulating intrinsic motivation in students to work on their projects, but it also comes with its own challenges: how to make sure that all students learn about all different types of sensors and not only about the one they choose? How to steer students towards choosing a project topic that is both challenging enough and not too challenging, without giving them the idea you are curbing their freedom to choose their own topic?

In this presentation we will reflect on lessons learned from a decade of teaching ‘Measuring Water’ and provide take-aways applicable for all geoscientific teaching.

How to cite: Hut, R., Coenders, M., and Vis, G.: Making MacGyvers: lessons from a decade of maker education, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-13088, https://doi.org/10.5194/egusphere-egu23-13088, 2023.

Public and private organizations and institutions distribute a large volume of Open Data on a continuous basis with aim of increasing efficiency, saving time or reducing costs. Technological advancement offers easy access to open datasets that have potentially added value as educational resources in teaching and learning processes. Open Data provides the educational community with learning experiences related to real world problems and allows students to engage with activities normally undertaken by professionals, without increasing the level of difficulty. In this study, we designed an educational intervention that uses open data from the Institute of Marine Biological Resources and Inland Waters, and we investigated how it can be integrated into the Greek secondary school curriculum. The results suggest that this open data-based practice has increased students’ motivation and has had an impact on selfbeliefs on topics of aquatic environments as well as an impact on students’ perception of the importance of aquatic environmental problems in rivers and lakes. 

How to cite: Tziortzioti, C., Dimitriou, E., and Mavrommati, I.: Introducing the use of Open Data into the secondary education: A study on inland water quality, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-2741, https://doi.org/10.5194/egusphere-egu23-2741, 2023.