Brief description

Due to increasing demands on river basin management, especially concerning legal requirements based on the Water Framework Directive, integrated river basin models have become an essential tool for practical concerns. Integrated models have largely increased in complexity due to the broad range of tasks requested. Both, the representation of natural processes in the model and the input data are associated with considerable uncertainties, which are propagated into model results and the quantification of these uncertainties has increasingly become important for evaluating model results and decision making.

The general objectives of Marie Curie European ToK Project are:

• to build up competence in stochastic simulation und uncertainty analysis
• to contribute to the development of integrated modelling tools

The research project will also study the effect of model complexity on predictive uncertainty with respect to the scale of the model application ranging from small headwater catchments to large river basins. The concept of balancing uncertainties as a paradigm for model selection shall also be assessed. Within the Marie Curie Project, the propagation of errors will be studied using a set of hydrologic models of different complexity. The models will be applied to selected catchments of varying size ranging from 8 to 5000 km². Uncertainty propagation is analysed with respect to data uncertainty, model complexity, the scale of the simulation, and the spatial resolution of the models. It is intended to find optimum combinations of model complexity, spatial resolution, and data uncertainty yielding a minimum prediction uncertainty.