Introduction #

Pastas is an open source Python package to analyse hydro(geo)logical time series. The objective of Pastas is twofold: to provide a scientific framework to develop and test new methods, and to provide a reliable ready‐to‐use software tool for groundwater practitioners. All code is available from the Pastas GitHub . Want to contribute to the project? Check out the Developers section.

Python

In this example a head time series is modelled in just a few lines of Python code.

# Import python packages
import pandas as pd
import pastas as ps
# Read head and stress data
obs = pd.read_csv("head.csv", index_col=0, parse_dates=True).squeeze("columns")
rain = pd.read_csv("rain.csv", index_col=0, parse_dates=True).squeeze("columns")
evap = pd.read_csv("evap.csv", index_col=0, parse_dates=True).squeeze("columns")
# Create and calibrate model
ml = ps.Model(obs, name="head")
sm = ps.RechargeModel(prec=rain, evap=evap, rfunc=ps.Exponential(), name="recharge")
ml.add_stressmodel(sm)
ml.solve()
ml.plots.results()
Using Pastas? Please cite us!#
If you find Pastas useful and use it in your research or project, we kindly ask
you to cite the Pastas article published in Groundwater journal as follows:
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.