StudIP

An application-oriented introduction to statistical and engineering hydrology at master's level, focused on methods used in engineering practice and industry. Topics include probability models and distributions in hydrology, extreme value analysis (annual maxima and peaks-over-threshold), parameter estimation with emphasis on L-moments, intensity–duration–frequency (IDF) curves, design precipitation and hyetographs, and rainfall–runoff transformation using the unit hydrograph concept. Additional topics cover low-flow analysis, drought characterisation, and reservoir design. Assessment is based on an applied project with datasets and tasks representative of real engineering problems.

Concepts, methods, and tools for modelling uncertainty in engineering applications, with a focus on quantitative description of uncertainty, risk assessment, and decision support under incomplete information. Topics include probability distributions, extreme value theory, regression models, joint distributions for dependent random variables, probabilistic reliability analysis, and an introduction to Bayesian inference and decision theory. The course is application-oriented throughout, combining theoretical foundations with computational examples using real or synthetic datasets.

Key aspects of water protection with a strong focus on hydrological extremes, risk, and data-driven analysis. Topics include extreme precipitation, floods, and droughts — and their implications for water resources, infrastructure, and society. Students learn statistical and stochastic methods for analysing extreme hydrological events, including extreme value analysis, time series analysis, and risk concepts. The emphasis is on interpreting results, discussing assumptions and uncertainties, and situating findings in engineering decision processes.

Fundamental principles and best practices of scientific visualization with a strong emphasis on hands-on application in engineering and environmental sciences. Students learn how to create clear, accurate, and interpretable figures — covering visual perception, graph anatomy (axes, scales, aspect ratios, typography, line weights), and colour theory including accessible and colourblind-safe palettes. The course covers essential visualization types: time series, histograms, bar and pie charts, scatter plots, box plots, heatmaps, and table-based displays. Students are required to bring their own laptops; visualization tasks use spreadsheet-based and scripting tools.

Advanced visualization for master's students in engineering and environmental sciences. Builds on the BSc course, extending into complex data types, multi-panel layouts, animated and interactive graphics, and publication-quality figure production. The course emphasises visual communication of uncertainty, probabilistic results, and spatial data. Students work on a progressive project producing a portfolio of figures based on their own or provided research datasets. Advanced scripting and programmatic visualization tools are introduced.

Climate-related risks in urban environments and strategies for climate change adaptation in cities. The focus is on analysing climate hazards — heat waves, extreme precipitation, flooding — assessing exposure and vulnerability, and evaluating adaptation measures in an urban context. The course introduces conceptual frameworks for climate risk assessment and data-driven approaches for analysing risks and adaptation options. Students work with real datasets, analyse case studies from different cities, and discuss uncertainties, trade-offs, and the limits of adaptation strategies. The course features day excursions to existing adaptation infrastructure in Hamburg. Maximum 20 participants.

Hydroclimatological extremes in the context of climate change — how extreme events such as heavy precipitation, droughts, floods, and heat waves are described, analysed, and interpreted using observational data, reanalysis products, and climate model simulations. The course focuses on understanding the indicators used in climate science, and how changes under climate change can be interpreted from available data. Students work with real datasets and discuss uncertainties, data limitations, and differences between observations and model output. The emphasis is on process understanding and data interpretation rather than statistical method derivation.

Global water security and hydropolitics — the processes by which water becomes a source of geopolitical tension, cooperation, and conflict. Topics include global water diplomacy, transboundary water governance, international relations frameworks, state doctrines, and conflict transformation mechanisms. Students analyse case studies, apply critical thinking, and discuss uncertainties, data limitations, and pathways for cooperation and peacebuilding. Delivered online with two in-person campus meetings for discussion and interaction. Assessment is based on an applied project (Pass/Fail) with a final presentation.

An advanced seminar examining water security through the lens of complex systems and dynamic thinking. Students analyse interactions between climate security, cascading socio-environmental effects, and how water-related challenges are interconnected across regions and sectors. The course emphasises the Water–Energy–Food nexus and situates water security within the broader context of global security and the United Nations Sustainable Development Goals. Through seminar discussions, case studies, and project-based analysis, students develop conceptual and analytical skills for systemic assessment of global water challenges. Delivered online with two in-person campus meetings.