Exploring and strengthening reproducible research practices in urban drainage

To enhance the reproducibility of research practices within the urban drainage community, particularly focusing on improving the interpretability and reusability of both data and code, it is imperative to enhance the documentation of the origins of open datasets and the outcomes of workflows and models utilizing these datasets. Our goal is twofold: develop prototype Open Research Data (ORD) tools with the Swiss Data Science Center and assess their effectiveness with the international urban drainage community. We will explore if RENKU can serve as a comprehensive platform for this, given its features like collaborative workflow management, version control, and integration with data science tools, promoting reproducibility, and efficient collaboration among researchers. Planned use cases include i) individual researchers sharing results, ii) benchmarking rainfall-runoff models in our department, iii) and distributed groups providing pre-processed datasets with full provenance information. We will start by enhancing the FAIRness of a 20-year-old dataset on sewer mixing. Additionally, we will evaluate different EPA-SWMM model implementations and engage the international urban drainage community in ORD practices. This initiative could establish a cornerstone for data sharing in urban drainage, extending beyond Eawag's research.