Programme

  Monday
16 April
Tuesday
17 April
Wednesday
18 April
Thursday
19 April
Friday
20 April
Theme Basics of hydrology Basics of Bayes   Bayes in practice Research ideas
9 – 9.50 Hydrological cycle of the Cantabria (CP) Review of probability theory (DK) Field trip (CP) Inference of time series models (DK) Flexible hydrological models (FF)
10 – 10.50 Fundamentals of hydrological models (FF) Bayesian inference: Basic building blocks (DK) Model predictions and diagnostics (DK) Prediction in ungauged basins (CP)
11 – 11.50 From hydrological concepts to a numerical model (DK) Optimization and MCMC (DK) Residual error modelling (DK) Hypothesis testing in hydrological modelling (FF)
12 – 13 Lunch Lunch Lunch Lunch Lunch
13 – 16 Exercise 1 (MM) Basic model building (Excel and Python) Exercise 2a (MM) Inference of simple flood frequency model   Exercise 2b (MM) MCMC implementation (Excel or Matlab) Field trip (CP) Exercise 3 (MM) SLS / WLS calibration of a bucket model (Matlab) Review of course, Final discussions, Feedback & wrap-up
16 – 17 Discussion Discussion Discussion Discussion Discussion

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