Optimization methods for shallow water flow modeling

The aim of this study is to develop new methods and techniques to link optimization procedure with river models to find optimal solutions and to automate work processes. This should be realized with available shallow water models coupled with optimization methods. Additionally, a tool has to be developed, which will provide new objective functions dependent on the engineering problem and will involve methods and techniques of High Performance Computing, especially of Parallel Computing.

Appropriate optimization methods for different shallow water models and issues will be worked out by applying the combined simulation optimization tool for three different problems:           

1- model calibration (e.g. Thies experiment, Heumös slope).

2- optimization of engineering measures (e.g. river Panke, water town Koepenick).

3- parameter identification for highly parameterized models (e.g. Iffezheim reservoir, Lake Tegel).