LAWI301241 Exercises in hydrological processes and water resources management (in Eng.)

Art
Übung
Semesterstunden
2
Vortragende/r (Mitwirkende/r)
Räpple, Matthias Bernhard Johannes , Herrnegger, Mathew
Organisation
Hydrologie und Wasserwirtschaft
Angeboten im Semester
Wintersemester 2025/26
Unterrichts-/ Lehrsprachen
Englisch
Lehrinhalt

This course provides comprehensive training in hydrological modeling and water balance analysis using R programming. Students learn to apply the GR4J-CemaNeige rainfall-runoff model to real-world catchment data from the LamaH-CE dataset covering Central Europe.

The course covers: R programming fundamentals including data structures, visualization, and programming tools; hydrological model setup, calibration using multiple objective functions (NSE, KGE), and validation; processing and analyzing meteorological and discharge time series data; calculating water balance components including precipitation, evapotranspiration, runoff, and catchment exchange; temporal trend analysis and seasonal pattern identification; interpretation of hydrological processes in the context of climate variability and water resources management.

Students work independently on a catchment of their choice, gaining practical experience in data processing, model implementation, parameter optimization, and scientific reporting of hydrological findings.
Inhaltliche Voraussetzungen (erwartete Kenntnisse)

Basic understanding of hydrological processes and the water cycle; fundamental knowledge of statistics and data analysis; familiarity with scientific computing concepts (beneficial but not mandatory); ability to read and interpret technical documentation in English; willingness to learn programming with R/RStudio from introductory level; basic skills in data interpretation and visualization; ability to work independently and problem-solve technical challenges.
Lehrziel

Upon successful completion of this course, students will be able to:

Hydrological Modeling Expertise: Conduct hydrological modeling, including time series representation, model setup, and providing essential input parameters for model execution and understanding of water balance components.

Proficiency in Rainfall-Runoff Modeling: Competence in performing rainfall-runoff modeling, including understanding and applying methods for parameter estimation.

R Programming Competence: Proficiency in the R programming language, including coding, creating data visualizations, developing and using complex functions, and incorporating external packages for enhanced functionality.

Integrated Knowledge Application: Capability to combine expertise in hydrological modeling and R programming, using advanced programming skills to implement and optimize hydrological models, perform in-depth data analyses, and visually present results.

Critical Analysis and Scientific Communication: Ability to critically evaluate model performance using multiple objective functions, interpret hydrological processes and trends, identify potential climate and land-use impacts, and communicate findings effectively through technical reports with appropriate visualizations and evidence-based discussions.
Noch mehr Informationen zur Lehrveranstaltung, wie Termine oder Informationen zu Prüfungen, usw. finden Sie auf der Lehrveranstaltungsseite in BOKUonline.