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, 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 the open-source software Pastas and Jupyter Notebooks.

Designed for groundwater researchers and practitioners, this four-session course 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. The 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.