The default behavior for adding and solving with noisemodels has changed from Pastas 1.5. Find more information here


Below you can find examples of how Pastas models are used for the analysis of groundwater levels. Examples in the form of Python scripts can also be found on the examples directory on GitHub.


Preprocessing user-provided time series

A basic model

`Fixating parameters while fitting`_


Modeling with different timesteps


Adding surface water levels

Adding pumping wells

Adding multiple wells

Adding trends

Changing response functions

Non-linear (Recharge) Models#

Threshold non-linearities

Non-linear recharge models

Estimating recharge

Modeling snow

Model Evaluation#

Comparing models visually

Diagnostic checking

Reducing autocorrelation

Uncertainty quantification

MCMC uncertainty


Standardized Groundwater Index

Groundwater signatures

STOWA Manual (Dutch only)#

In 2021 the STOWA published a manual on time series analysis. This manual has some general notebooks on preprocessing data, model structure, calibration and assessment with Pastas. There are also more case-specific notebooks available on determining stresses, characteristics, system analysis and predicting. The notebooks (currently Dutch only) can be found here.