Uncertainty quantification in hydrology

Vortragende/r (Mitwirkende/r)
Umfang2 SWS
SemesterWintersemester 2022/23
Stellung in StudienplänenSiehe TUMonline
TermineSiehe TUMonline




The students at the end of the module will be able to: • Understand and analyse the theory, the methods and the results presented in a scientific paper focusing on uncertainty quantification in hydrology • Understand and analyse the methods inherent to uncertainty quantification in hydrology • Evaluate autonomously the relevant literature necessary for the understating of the assigned paper in the field of uncertainty quantification in hydrology • Create a presentation to explain an assigned topic in the field of uncertainty quantification in hydrology


Each student will receive one scientific publication related to uncertainty quantification in hydrology to be presented during the seminar. The assigned publications could be changed every year according to the most recent and valuable scientific publications. The publications will be chosen among open access journals or journals freely accessible to students from the library. Topics that will be discussed are: - Model uncertainty in hydrology - Parameter uncertainty in hydrology - Parameter estimation - Model inversion - Bayesian inversion - Latin hypercube method - Markov Chain Monte Carlo Simulations - Monte Carlo Simulations - Estimation of effective model parameters - Equifinality in hydrological models

Inhaltliche Voraussetzungen

• Advanced hydrological knowledge • Advanced statistical knowledge • Familiarity with preparation of slides and oral presentations

Lehr- und Lernmethoden

The 13 students participating to the seminar will be guided by the lecturer in the oral presentation of a scientific paper. The presentations must be prepared in electronic form by the students following the instructions provided by the lecturer. This teaching method will allow the students to achieve the four learning outcomes described above. An open discussion involving also the other participants will be moderated by the lecturer after each presentation. This teaching method will allow the students to achieve the first three learning outcomes described above. It is required that each student will participate to the discussion taking place after each student’s seminar.

Studien-, Prüfungsleistung

The students prepare a comprehensive presentation of 60 minutes about a seminal paper related to uncertainty quantification in hydrology. The evaluation considers the quality of the presentation (clarity of the oral presentation and slides), its structure (comprehensiveness beyond the literature provided by the lecturer), capability of answering questions and clarifying both mathematical and hydrological concepts. The oral presentation of a hydrological paper demonstrates the understanding of the student about the relevant issue of uncertainty quantification in hydrological parameter estimation and predictions. Moreover, it verifies how well the students can summarize complex mathematical and hydrological concepts and explain them to other students within a given period of time. Through short and precise answers to theoretical oral questions, the students demonstrate that they are able to understand the principles and the methods used for uncertainty quantification in hydrology

Empfohlene Literatur

The assigned publications could be changed every year according to the most recent and valuable scientific publications. Example of papers that could be used in the seminar are: Mattis, S. A., Butler, T. D., Dawson, C. N., Estep, D., & Vesselinov, V. V. (2015). Parameter estimation and prediction for groundwater contamination based on measure theory. Water Resources Research, 51(9), 7608-7629. Kitanidis, P. K. (1986). Parameter uncertainty in estimation of spatial functions: Bayesian analysis. Water resources research, 22(4), 499-507. Vrugt, J. A., Ter Braak, C. J., Clark, M. P., Hyman, J. M., & Robinson, B. A. (2008). Treatment of input uncertainty in hydrologic modeling: Doing hydrology backward with Markov chain Monte Carlo simulation. Water Resources Research, 44(12).