Mitarbeitende
Raoul Collenteur


Über mich
Hydrologist focusing on groundwater related problems and developing open-source software to solve them. In my free time I enjoy exploring the mountains by foot, rope, or kayak.
Software projects
I strongly believe in the use and development of open-source software. I currently lead or contribute to the development of the following open-source softwares:
Curriculum Vitae
2024 - Ongoing | Part-time (40%) self-employed at HydroConsult (Switzerland) |
2022 - Ongoing | Part-time (60%) PostDoc at Eawag (Switzerland) |
2018 - 2022 | PhD at the University of Graz (Austria) |
2016 - 2018 | Hydrologist at Artesia Water (The Netherlands) |
2012 - 2016 | MSc. in Water Management at TU Delft (The Netherlands) |
2009 - 2012 | BSc. in Earth Sciences and Economics at VU Amsterdam (The Netherlands) |
Project: Swiss Groundwater Database (v1.0)
Groundwater level data contains invaluable information about the subsurface conditions and the driving forces and environmental factors causing water level fluctuations. More and more hydrological studies are using large data sets to improve our understanding of this important resource. Large data sets of groundwater are, unfortunately, not easy to obtain and often contain heterogeneous data. In this project, started at the end of 2023, we are collecting groundwater data in Switzerland to develop the first-ever Swiss Groundwater Database. The goal of this project is to develop a fully open-source (FAIR) database of groundwater data for Switzerland. The first release is planned mid-2025. Contact Raoul.Collenteur@eawag.ch for more info and collaboration!
Project:AI-generated unit tests for Pastas
Pastas is currently tested with continuous integration using a moderately-sized set of unit tests written by the developers. This system has enabled us to improve code quality and catch errors more easily before new releases. The current test suite (~150 tests) contains rudimentary tests covering ~70% of the code, but not all methods are tested. Recently, generative AI-tools such as CodiumAI [13] have become available to generate unit tests. Initial application of these tools gave promising results, although manual oversight remains necessary. We will use AI-tools with human oversight to generate a comprehensive set of unit tests for Pastas. The goal is to cover 95% of the code, with more than two tests per method (on average). A protocol will be developed to aid new commits with AI-generated tests.
Project: Improved understanding and forecasting of the impact of climate extremes on groundwater systems
Groundwater has historically been perceived as a secure source of freshwater that is relatively
Publikationen
Diese Person arbeitet nicht mehr an der Eawag. Bitte wenden Sie sich an info@eawag.ch für weitere Auskünfte.
- https://bsky.app/profile/rcollenteur.bsky.social
- https://github.com/raoulcollenteur
- https://hydroconsult.ch
Forschungsgruppen
Hydrogeology