816355 Uncertainties in hydrological and ecosystem modelling
This page is available under these URLs:
- Lecture and exercise
- Semester hours
- Lecturer (assistant)
- Offered in
- Wintersemester 2019/20
- Languages of instruction
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); modell 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.
- Previous knowledge expected
It is expected that participant have some background in statistics, calculus and environmental systems. Experience in Excel and R will be advantageous for progressing in the practical parts of the course. The course is designed for students at the M.Sc. or PhD level with interest in ecosystem modelling.
- Objective (expected results of study and acquired competences)
After having finished the course, students should have
- an understooding of the theoretical background of the methods and topics covered in the course and listed above;
- the ability to transfer these methods to other systems and problem areas; this will include evaluating the model complexity needed given the available objectives and data/information available;
- the ability to critically assess the quality of data and final model predictions.
You can find more details like the schedule or information about exams on the course-page in BOKUonline.