Abstract

Hutton (2016) argued that computational hydrology can only be a proper science if the hydrological community makes sure that hydrological model studies are executed and presented in a reproducible manner. We replied that to achieve this, hydrologists shouldn't ‘re-invent the water wheel’ but rather use existing technology from other fields (such as containers and ESMValTool) and open interfaces (such as BMI) to do their computational science (Hut, 2017). With this paper and the associated release of the eWaterCycle platform and software package1 we are putting our money where our mouth is and provide the hydrological community with a ‘FAIR by design’ platform to do our science. eWaterCycle is a platform that separates the experiment done on the model from the model code. In eWaterCycle hydrological models are accessed through a common interface (BMI) in Python and run inside of software containers. In this way all models are accessed in a similar manner facilitating easy switching of models, model comparison and model coupling. Currently the following models are available through eWaterCycle: PCR-GLOBWB 2.0, wflow, Hype, LISFLOOD, TopoFlex HBV, MARRMoT and WALRUS. While these models are written in different programming languages they can all be run and interacted with from the Jupyter notebook environment within eWaterCycle. Furthermore, the pre-processing of input data for these models has been streamlined by making use of ESMValTool. Forcing for the models available in eWaterCycle from well known datasets such as ERA5 can be generated with a single line of code. To illustrate the type of research that eWaterCycle facilitates this manuscript includes five case studies: from a simple ‘Hello World’ where only a hydrograph is generated to a complex coupling of models in different languages. In this manuscript we stipulate the design choices made in building eWaterCycle and provide all the technical details to understand and work with the platform. For system administrators who want to install eWaterCycle on their infrastructure we offer a separate installation guide. For computational hydologist who want to work with eWaterCycle we also provide a video explaining the platform from a users point of view. With the eWaterCycle platform we are providing the hydrological community with a platform to conduct their research fully compatible with the principles of Open Science as well as FAIR science.1available on Zenodo: doi.org/10.5281/zenodo.5119389

Highlights

  • In hydrology, scientists try to better quantify the movement of water in, out of, and through the land-surface and rivers in order 25 to better predict droughts, floods, navigation hazards, and reservoir operations (Wood et al, 2011)

  • The current pre-processing pipeline of the eWaterCycle using ESMValTool consists of hydrological model-specific recipes and supports ERA5 and ERA-Interim data provided by the ECMWF (European Centre for Medium-Range Weather Forecasts) through the Climate Data Source (CDS)

  • We have introduced the eWaterCycle platform for FAIR and Open hydrological modeling

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Summary

Introduction

Scientists try to better quantify the movement of water in, out of, and through the land-surface and rivers in order 25 to better predict droughts, floods, navigation hazards, and reservoir operations (Wood et al, 2011). FAIR Hydrological Models make it possible for other researchers to use a model to generate novel scientific results without needing extensive support from the original authors. The eWaterCycle platform builds on the BMI interface using containerized models offering an reproducible model software environment This includes the support for generating forcing and other needed input for each model, allowing scientists to 105 build on all data and models eWaterCycle provides access to. The example Jupyter notebooks provided with this paper demonstrate how hydrologsts can, for example, couple two models written in different programming languages, calibrate models, or run "what if?" scenario’s, using existing models from research groups all over the world, forced with datasets from different data-provides, all without having to install a single package on their own laptops.

Glossary
Explorer
Experiment
Analyze
Downloading ERA5 with era5cli
ESMValTool-based model input pre-processor
Interfacing models through grpc4bmi
Conclusions
Full Text
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