Pastas: Analysis of Groundwater Time Series

Pastas: what is it?

Pastas is an open source python package for processing, simulating and analyzing groundwater time series. The object oriented structure allows for the quick implementation of new model components. Time series models can be created, calibrated, and analysed with just a few lines of python code with the built-in optimization, visualisation, and statistical analysis tools.

Documentation & Examples

• Documentation is provided on the dedicated website pastas.dev
• Examples can be found on the examples directory on the documentation website
• A list of publications that use Pastas is available in a dedicated Zotero group
• View and edit the example notebooks of Pastas in GitHub Codespaces

Quick Example

# Import Python packages
import pandas as pd
import pastas as ps

# Load head and meteorological observations into a pandas Series
obs = pd.read_csv("head.csv", index_col="datetime", parse_dates=["datetime"]).squeeze()
prec = pd.read_csv("prec.csv", index_col="datetime", parse_dates=["datetime"]).squeeze()
evap = pd.read_csv("evap.csv", index_col="datetime", parse_dates=["datetime"]).squeeze()

# Create and calibrate Pastas model
ml = ps.Model(obs, name="head")
sm = ps.RechargeModel(ml, prec, evap, rfunc=ps.Exponential(), name="recharge")
ml.solve()

# Visualize the model results
ml.plots.results()

Get in Touch

• Questions on Pastas can be asked and answered on Github Discussions.
• Bugs, feature requests and other improvements can be posted as Github Issues.
• Pull requests will only be accepted on the development branch (dev) of this repository. Please take a look at the developers section on the documentation website for more information on how to contribute to Pastas.

Quick installation guide

To install Pastas, a working version of Python has to be installed on your computer. We recommend using uv to manage Python and your project dependencies. However, you are free to use any Python installation method you prefer. The Anaconda Distribution is another popular option.

Stable version

To get the latest stable version, use:

pip install pastas

Or with uv:

uv pip install pastas

Update

To update pastas, use:

pip install pastas --upgrade

Developers

To get the latest development version, use:

pip install git+https://github.com/pastas/pastas.git@dev#egg=pastas

Related packages

• Pastastore is a Python package for managing multiple timeseries and pastas models
• Metran is a Python package to perform multivariate timeseries analysis using a technique called dynamic factor modelling.
• Hydropandas can be used to obtain Dutch timeseries (KNMI, Dinoloket, ..)
• PyEt can be used to compute potential evaporation from meteorological variables.

Dependencies

Pastas depends on a number of Python packages, of which all of the necessary are automatically installed when using the pip install manager. To know which dependencies exist, check the pyproject.toml file.

To install the most important optional dependencies (solver with LmFit and caching via cachetools) at the same time with Pastas use:

pip install pastas[full]

or for the development version use:

pip install git+https://github.com/pastas/pastas.git@dev#egg=pastas[full]

How to Cite Pastas?

If you use Pastas in one of your studies, please cite the Pastas article in Groundwater:

• Collenteur, R.A., Bakker, M., Caljé, R., Klop, S.A., Schaars, F. (2019) Pastas: open source software for the analysis of groundwater time series. Groundwater. doi: 10.1111/gwat.12925.

To cite a specific version of Pastas, you can use the DOI provided for each official release (>0.9.7) through Zenodo. Click on the link to get a specific version and DOI, depending on the Pastas version.

• Collenteur, R., Bakker, M., Caljé, R. & Schaars, F. (XXXX). Pastas: open-source software for time series analysis in hydrology (Version X.X.X). Zenodo. http://doi.org/10.5281/zenodo.1465866