Promoting FAIRness in Hydrology or “Putting Our Money Where Our Mouth Is”

In 2016, Hutton et al. provided a commentary on the irreproducibility of computational hydrology due to complex methods and a lack of transparency of code and data used in many studies. Irreproducibility inhibits our growth as a community and our work quality because our ability to learn from one another is limited and errors can go unrealized. They provided several suggestions for improving research and reporting practices to adhere to FAIR - Findability, Accessibility, Interoperability, and Reusability - principles. The piece sparked discussion in the hydrology community and further suggestions and ideas to facilitate FAIRness (Hut et al., 2017; Melsen et al., 2017). Particularly, the community has highlighted the importance of communication, collaboration, and adhering to best practices in research software.

Whether you study sustainability questions that require models from different fields of geosciences, economics, social sciences, or want to compare the river discharge predictions from your model to the predictions from another research groups model: running each other (hydrological) models is often a painstaking process.

Recognising the need for hydrologist to not only have access to the software code of each others models, but also to be able to run these models without the tech-support of the researcher that made the model, we have built the eWaterCycle II platform.

The goals for the eWaterCycle II project is to provide the hydrological community with tools that:

Allow the use of a wide variety of models, written in different programming languages, without having to learn those languages.
Have access to all the relevant datasets from the community (forcing, observations)
Allow advanced use cases such as data assimilation and model coupling studies. Allow the sharing of models with the entire community, both for citing (DOIs) and re-use. Ultimately providing hydrologists with a toolset that allows them to run each other models, but also adept, couple, and in general tinker with models without the headache of having to delve into each other’s code. This fits nicely with water and climate change-related challenges: it allows for quicker solutions by combining research efforts from different fields. We will demonstrate (and make available to the community) the system we have built during the presentation.