Examples

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.

Basics

Preprocessing user-provided time series

A basic model

Fixing parameters while fitting

Calibration

Modeling with different timesteps

Stressmodels

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

Model check module

Reducing autocorrelation

Uncertainty quantification

MCMC uncertainty

MCMC vs. LS

Applications

Standardized Groundwater Index

Groundwater signatures

Ensemble predictions

Time Series Analysis Manual

The notebooks from the Dutch Manual on Time Series Analysis, which use Pastas, have been translated into English and are available below. The full manual can be found here: Von Asmuth, J., Baggelaar, P., Bakker, M., Brakenhoff, D., Collenteur, R., Ebbens, O., Mondeel, H., Klop, S., & Schaars, F. (2021). Handleiding Tijdreeksanalyse (STOWA rapport nr. 32). Stichting Toegepast Onderzoek Waterbeheer, Amersfoort.

Preprocessing

Model structure

Model calibration

Model assessment

Case Study 1 Assessing contributions

Case Study 2 Determining characteristics

Case Study 3 System analysis

Case Study 4 Forecasting

Pastas Performance

Caching for performance

Groundwater Article

These notebooks are supplementary material to the following article in Groundwater: Collenteur, R.A., Bakker, M., Caljé, R., Klop, S.A. and Schaars, F. (2019). Pastas: Open Source Software for the Analysis of Groundwater Time Series. Groundwater, 57: 877-885. doi:10.1111/gwat.12925

Example 1 Modeling Groundwater Levels with Pastas

Example 2 Analysis of groundwater monitoring networks using Pastas