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.
