Bayesian methods in hydrology, Hohai University, 28-29 October 2019
This 2-day course introduces the key principles of Bayesian methods for inference and uncertainty quantification, with applications in hydrology and water engineering
The following broad themes will be covered:
Day 1 – Mon 28 Oct: Principles of Bayesian Methods
- Bayesian methods: Intro
- Bayesian methods: Time series models
- Bayesian methods: Prediction and diagnostics
- Practice exercises
Day 2 – Tue 29 Oct: 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 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) understanding of key concepts in Bayesian methods;
(ii) ability to develop and implement simple likelihood functions, use them to estimate model parameters, 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 Hohai.
Please complete and send the application form (see link below) to organisers <dmitri.kavetski@adelaide.edu.au> before 25 Oct 2019.
Course location / classrooms
Liuguangwen Building, Room 105. Hohai University, Nanjing.
The course will run 9am-5pm on both Day 1 and Day 2
Notes
1. Participants are expected to bring their own laptops with programming language of choice for the exercises.
2. Exercises will be presented in Excel.