We will have two talks about uncertainty quantification (Kristoffer) and structural errors in hydrology models (Janneke).
Kristoffer Aalstad : Understanding uncertainty using Bayesian inference
"We are certainly living in uncertain times. How should we approach uncertainty as scientists? The Bayesian approach to statistical inference turns out to be a useful framework. As an accidental statistician, I will give a brief overview of this approach which I have found very helpful in my LATICE related work."
Janneke Remmers : Can model structure families be inferred from model output?
"This study explores the compatibility of two approaches for hydrological model structure uncertainty assessment: modular modelling frameworks, and model ensemble runs. Results from a synthetic experiment over 671 climate instances showed that the performance of the inference depends on the type of signature evaluated, and the climate. However, the performance of the inference is overall low, implying that model structure families are different from model output families."
The seminar is open for all interested in uncertainty.