Welcome to ewatercycle’s documentation!
The eWaterCycle Python package brings together many components from the eWaterCycle project. An overall goal of this project is to make hydrological modelling fully reproducible, open, and FAIR.
Modelled after PyMT, it enables interactively running a model from a Python environment like so:
from ewatercycle.models import Wflow model = Wflow(version="2020.1.1", parameterset=example_parameter_set, forcing=example_forcing) cfg_file, cfg_dir = model.setup(end_time="2020-01-01T00:00:00Z") model.initialize(cfg_file) output =  while model.time < model.end_time: model.update() discharge = model.get_value_at_coords("RiverRunoff", lat=[52.3], lon=[5.2]) output.append(discharge)
Typically the eWaterCycle platform is deployed on a system that can be accessed through the browser via JupyterHub, and comes preconfigured with readily available parameter sets, meteorological forcing data, model images, etcetera. This makes it possible for researchers to quickly run an experiment without the hassle of installing a model or creating suitable input data. To learn more about the system setup, read our System setup page.
In general eWaterCycle tries to strike a balance between making it easy to use standard available elements of an experiment (datasets, models, analysis algorithms), and supplying custom elements. This does mean that a simple usecase sometimes requires slightly more lines of code than strictly nescessary, for the sake of making it easy to adapt this code to more complex and/or custom usecases.
To avoid miscommunication, here we define explicitly what we mean by some terms that are commonly used throughout this documentation.
Experiment: A notebook running one or more hydrological models and producing a scientific result.
Model: Software implementation of an algorithm. Note this excludes data required for this model.
Forcing: all time dependent data needed to run a model, and that is not impacted by the model.
Model Parameters: fixed parameters (depth of river, land use, irrigation channels, dams). Considered constant during a model run.
Parameter Set: File based collection of parameters for a certain model, resolution, and possibly area.
Model instance: single running instance of a model, including all data required, and with a current state.