Α2.3 Hydroinformatics

The course aims to introduce students to the main applications of Hydroinformatics, focusing on systems analysis, simulation and optimization techniques with an emphasis on water resources problems, both at the urban and catchment scales. The topics of model calibration and uncertainty analysis are also addressed, as well as state of the art topics from the field of Hydroinformatics, including artificial neural networks, fuzzy logic, agent-based modelling, surrogate based model optimization, meta-models and data mining etc. At the same time, students are introduced to basic concepts of computer science and technical computing. During the course, applications relevant to water management are developed using a programming environment. The structure of the course is asfollows:

1. Introduction to water systems analysis
2. Modelling and simulation of water systems
3. Developing water system simulation models using a programming environment
4. Optimization of water systems using local search techniques
5. Global optimization techniques applied to water systems
6. Optimization of water system models using a programming environment
7. Uncertainty analysis
8. Artificial neural networks
9. Surrogate based optimization
10. Fuzzy logic
11. Data mining
12. Agent based modelling