General course objectives:
The objective of the course is to be able to describe hydrological processes by means of relatively simple models such as purely statistical and combined statistical and deterministic models and then apply them to problems typical in applied hydrology. There are large uncertainties and high natural variability in both urban and catchment hydrological applications such as flooding and hydrologic design. Often lumped models are needed, because the actual processes are either not sufficiently well understood or we lack the data to describe the processes. Therefore we need a range of tools to quantify uncertainty and variation. Hydrological processes, statistical testing procedures, and basic data analysis and management by using Matlab are assumed known. Hence the major novelty lies in combining these skills and working with actual data. En studerende, der fuldt ud har opfyldt kursets mål, vil kunne:

• Manage and analyze hydrological data by means of professional software
• Apply simple data verification and validation steps in hydrological data
• Apply statistical methods to model hydrological processes for different time scales
• Decompose a hydrological time series into deterministic and stochastic elements
• Identify rainfall-runoff components in a hydrological series and construct and validate simple rainfall runoff models for these components
• Combine sub-models into one hydrological model and apply time series analysis methods to assess the overall model performance
• Select a proper statistical model for prediction of hydrologic extremes in consideration of the prediction uncertainty
• Assessing climate change impacts on water resources and climatic extremes

Data analysis. Decomposition of runoff time series and description of their deterministic and stochastic components. Stochastic models for description of extreme hydrological events. 04. maj, 2017