816355 Uncertainties in hydrological and ecosystem modelling (in Eng.)

Vorlesung und Übung
Vortragende/r (Mitwirkende/r)
Schulz, Karsten
Angeboten im Semester
Wintersemester 2023/24
Unterrichts-/ Lehrsprachen


The course will cover the following topics:
Introduction into hydrological and ecosystem modelling concepts; the quality of observation - parameter and input data; mathematical concepts for describing uncertainties (probability theory, fuzzy sets), methods to propagate uncertainties (error propapgation, stochastic simulation, monte carlo methods); model calibration, measures of goodness-of-fit, and optimization methods; parameter and prediction uncertainty; Introduction into Bayesaian uncertainty estimation „Generalized Likelihood Uncertainty Estimation (GLUE)“; Sensitivity analysis.

Inhaltliche Voraussetzungen (erwartete Kenntnisse)

It is expected that participants have some background in statistics, calculus and environmental systems. Starting in week 3, it is expected that students have developed via self-learning some introductory knowledge in R- or Python-programming.
The course is designed for students at the M.Sc. or PhD level with interest in ecosystem modelling.


After having finished the course, students should have understood the theoretical background of the methods and topics covered in the course and listed above. They should also be able to transfer these methods to other systems and problems. This will include evaluating the model complexity needed given the available objectives and data/information available. Also, students will be able to critically assess the quality of data and final model predictions.
Noch mehr Informationen zur Lehrveranstaltung, wie Termine oder Informationen zu Prüfungen, usw. finden Sie auf der Lehrveranstaltungsseite in BOKUonline.