The course develops knowledge and skills for the advanced modelling, planning and management of natural resources systems. The emphasis will be on the operational aspects of resources management, including: stochastic and robust optimal control, approximate methods (e.g. simulation-based approaches, approximate dynamic programming, reinforcement learning), real time control, and complexity reduction methods. The course is aimed at graduate students preparing to work in environmental and water resources engineering field.
- R. Soncini-Sessa, A. Castelletti, E. Weber, Integrated and participatory water resources management. Theory, Elsevier, Amsterdam, 2007.
- R. Soncini-Sessa, F. Cellina, F. Pianosi, E. Weber, Integrated and participatory water resources management. Practice, Elsevier, Amsterdam, 2007.
- S.P. Simonovic, Managing water resources: Methods and tools for a systems approach, Earthscan, London, Sterling VA, 2009.
- D.P. Loucks, E. van Beek, Water Resources Systems Planning and Management : An Introduction to Methods, Models and Applications, UNESCO, Paris, 2005.
- K.D.W. Nandalal, J. Bogardi Dynamic Programming Based Operation of Reservoirs, Cambridge University Press, Cambridge, 2007.
- L. Busoniu, R. Babuska and B.De Schutter, D. Ernst, Reinforcement Learning and Dynamic Programming Using Function Approximators, CRC Press, Boca Raton, Florida, 2010.
Matlab support for the laboratory:
- A. Quarteroni, F. Saleri, Scientific Computing with MATLAB and Octave, Springer-Verlag, Heidelberg, 2006.
- A. Quarteroni, F. Saleri, Calcolo scientifico. Esercizi e problemi risolti con MATLAB e Octave, Springer-Verlag, Heidelberg, 2008 (in Italian)