Abstract
The eWaterCycle platform(https://www.ewatercycle.org/) is a fully Open
Source system designed explicitly to advance the state of Open and FAIR
Hydrological modelling. Reproducibility is a key ingredient of FAIR, and
one of the driving principles of eWaterCycle. While working with
Hydrologists to create a fully Open and FAIR comparison study, we
noticed that many ad-hoc tools and scripts are used to create input
(forcing, parameters) for a hydrological model from the source datasets
such as climate reanalysis and land-use data. To make this part of the
modelling process better reproducible and more transparent we have
created a common forcing input processing pipeline based on an existing
climate model analysis tool: ESMValTool (https://www.esmvaltool.org/).
Using ESMValTool the eWaterCycle platform can perform commonly required
pre-processing steps such as cropping, re-gridding, and variable
derivation in a standardized manner. If needed, it also allows for
custom steps for a Hydrological model. Our pre-processing pipeline
directly supports commonly used datasets such as ERA-5, ERA-Interim, and
CMIP climate model data, and creates ready-to-run forcing data for a
number of Hydrological models. Besides creating forcing data, the
eWaterCycle platform allows scientists to run Hydrological models in a
standardized way using Jupyter notebooks, wrapping the models inside a
container environment, and interfacing to these using BMI, the Basic
Model Interface (https://bmi.readthedocs.io/). The container environment
(based on Docker) stores the entire software stack, including the
operating system and libraries, in such a way that a model run can be
reproduced using an identical software environment on any other
computer. The reproducible processing of forcing and a reproducible
software environment are important steps towards our goal of fully
reproducible, Open, and FAIR Hydrological modelling. Ultimately, we hope
to make it possible to fully reproduce a Hydrological model experiment
from data pre-processing to analysis, using only a few clicks.