Bayesian Waterloo 2019

Environmental models and Bayesian methods, University of Waterloo, 25-27 March 2019

This 3-day course introduces the key principles of environmental modelling, with applications in hydrology and water engineering. A major emphasis is on Bayesian methods for inference and uncertainty quantification

The following broad themes will be covered:

Day 1 – Mon 25 March: Basics of Modelling

  • Principles of environmental modelling
  • Sensitivity analysis
  • Optimisation methods
  • Practice exercises

Day 2 – Tue 26 March: Bayesian Methods

  • Bayesian methods: Intro
  • Bayesian methods: Time series models
  • Bayesian methods: Prediction and diagnostics
  • Practice exercises

Day 3 – Wed 27 March: Applications and Research Topics

  • MCMC methods
  • Applications in hydrological modelling
  • Improving the inference
  • Practice exercises
  • Wrap up

The course will be delivered by Prof Dmitri Kavetski (Univ of Adelaide) and Dr Juliane Mai (Univ of Waterloo) and will include a combination of theory and practical exercises.

The technical level will best suit research students (Masters and PhDs), as well as industry colleagues interested in research approaches.

Reading List / Selected References

A reading list / selected references for the course is given here.

Expected outcomes

(i) improved understanding of key concepts in environmental/hydrological modelling;

(ii) ability to develop and implement simple reservoir models, estimate their parameters in a systematic way, undertake posterior diagnostics and generate probabilistic predictions;

(iii) awareness of the principles underlying advanced Bayesian methods.

The course is free, and the maximum number of participants is limited to 15. Participants are expected to organise their own travel to Waterloo, including accommodation, insurance and so forth.

Please complete and send the application form (see link below) to organisers <> before 8 March 2019.

The list of participants will be announced by 11 March or earlier.

Course location / classrooms at Univ Waterloo

Mon 25 Mar: AL-209 9am – 5pm
Tue 26 Mar: E2-2350 9am – 4pm
Wed 27 Mar: MC-4064 9am – noon and DWE-2527 1pm – 5pm


1. Participants are expected to bring their own laptops with programming language of choice for the exercises.

2. Exercises will be presented in Excel and Python. Limited support will be available in Fortran, Matlab and R.