Modelling groundwater level time series with Pastas - Live Training

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About

Pastas is an open source Python package to analyse hydro(geo)logical time series. Time series modelling is a powerful tool for understanding groundwater dynamics, offering a data-driven approach to analysing hydrological processes. This course provides a comprehensive introduction to time series modelling techniques using Pastas, focusing on lumped-parameter models that use impulse response functions to describe groundwater level fluctuations. Through a combination of theory and hands-on exercises, participants will learn to investigate key hydrological influences such as precipitation, evaporation, and groundwater pumping using Pastas and Jupyter Notebooks.

Designed for groundwater researchers and practitioners, this four-session course presented by the primary developers of Pastas, provides participants with the skills to integrate time series models into their hydrogeological studies. By working through practical case studies, attendees will gain experience in recognising when time series analysis is applicable and how to construct models to interpret groundwater behaviour. This structured learning approach ensures a balance between conceptual understanding and applied problem-solving.

By the end of the course, participants will have the confidence to implement simple time series models in real-world groundwater investigations. You will be able to assess groundwater recharge, evaluate pumping effects, and identify dominant hydrological drivers with a quantitative approach.

Details

Date	Thursday, 3 July 2025 - Thursday, 24 July 2025
Time	4:00pm (Australia/Sydney; find your local time)
Location	Online
Format	4 x 2-hour recordings + course material & resources
Cost	AUD $1100.00 (INC GST)
Code	LC-26-4-140
Contact	training@awschool.com.au
Tags	Groundwater / Python

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Register your interest: https://awschool.com.au/training/modelling-groundwater-pastas/

Presenters

Onno Ebbens

Artesia

Onno Ebbens is a Dutch geohydrologist who graduated from Delft University of Technology (TU Delft) in 2015 with a degree in Water Management. His master's thesis focused on utilising time series analy... Read more

Raoul Collenteur

HydroConsult

Raoul is a hydrologist focusing on groundwater related problems and developing open-source software to solve them. He leads and is involved in developing open-source software such as Pastas, PyEt and ... Read more

Course Overview

This course provides a comprehensive learning experience by the primary developers of Pastas, an open source Python package in modelling and analysing groundwater level time series. Participants will learn how to extract valuable insights into groundwater systems using Pastas and Python, with practical hands-on exercises in Jupyter Notebooks.

To know more about the theoretical background of Pastas, read the article published in Groundwater, a Journal of The National Groundwater Association.

Watch this AWS Webinar to get a sneak peek into the course and discover what you’ll gain from this hands-on learning experience using Pastas!

Learning Outcomes

In this course, you will be able to:

Analyse time series with the Python package Pandas.
Model groundwater level (GWL) time series using Pastas and Python scripts.
Understand how to develop different model structures to simulate GWLs.
Learn about lumped-parameter groundwater models and impulse response functions.

Course Outline

Session 1: Analysing time series with Pandas

Load different types of time series data into Pandas Series and DataFrames.
Analyse the time series data.
Plot the time series data to gain good understanding of the data.
Correct missing values and errors in the time series.
Prepare time series to use as input into Pastas models.

Session 2: Setting up your first Pastas Model

Learn about impulse response functions.
How to set up a basic Pastas model.
How to perform a basic calibration.
Plot and analyse the results.
Understand the meaning of model parameters and statistics.

Session 3: Different model structures for Pastas

Explore how to add different stresses (i.e., pumping, river levels) to the model.
Understand the different options to account for precipitation and potential evaporation.
Build more complex models and compare the results of different models.

Session 4: Model calibration and analysis

Learn how to perform better calibration by choosing different settings.
Learn how to model the residuals using a noise model.
Analyse the model residuals on their statistical assumptions.
Introduction into exploring model uncertainties.

Format

4 x 2hr live interactive sessions from 4 – 6 PM Sydney Time
- Session 1: Thursday, 3 July
- Session 2: Thursday, 10 July
- Session 3: Thursday, 17 July
- Session 4: Thursday, 24 July
Ability to ask questions and have them answered in a live forum;
Set of Jupyter notebooks and working model download/s;
Ability to access all the online course materials for a further 30 days after the final live session of the course;
Sessions are recorded & uploaded to the learning platform (LMS – within 2 business days after the session), if you cannot attend live.

Pre-requisites

A basic understanding of Python programming, including working with Jupyter notebooks.
If you need to gain the foundational knowledge and skills of Python programming, register now for these AWS On-demand Courses:
- Python essentials for water
- Groundwater modelling in Python

Requirements

A good internet connection.
The following software are required for the course:
- Python 3.11: https://www.python.org/downloads/release/python-3110/
- Pastas: https://github.com/pastas/pastas
- Visual Studio Code: https://code.visualstudio.com/
- GitHub Account: https://github.com/

Completion certification

Participants earn CPD hours/points (i.e. with Engineers Australia) for at least 8 hours for the entire course.
On completion of the course attendees will be issued with a Certificate of Completion.