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Water Resources Management

Course Description:

The aim of the course is to introduce students to the basic principles of water resources management, and to explore the key concepts, methods and tools that support their design and optimal operation under uncertainty. Particular emphasis is given to reservoir design and modelling, uncertainty analysis, multi-criteria decision making, game theory and single/multiobjective optimization.

Prerequisite Knowledge

[Missing information in the English transcript]

Course Units

# Title Description Hours
1 Introduction Key definitions (hydrosystem, water resource systems analysis, water resource management, supply & demand), water resource management objectives. Legal Framework (WFD). 1Χ4=4
2 Supply: Hydrological Design of Hydrosystems Reservoirs and Aqueducts. Dimensioning and Design methods: Conventional, stochastic, dimensioning with simulation, dimensioning of a reservoir in a river without measurements. 3Χ4=12
3 Demand: Assessment and Management of Water Demand Basic demands (rural, urban). Demand vs needs. Rural development and best irrigation practices in agriculture. Urban development and management of urban water demand. A ‘hidden’ demand: ecological flow. 2Χ4=4
4 Matching Demand to Supply: Uncertainty and tools to manage it. Assess and manage uncertainty at different scales. Stochastic models, Socio-economic scenarios, Simulation techniques. Sensitive Analysis. Monte-Carlo method. The Latin Hypercube variant. 1Χ4=4
5 Multi-purpose hydrosystems: part 1 – top down. The fundamental water resource management problems. Building a model. Occam’s razor. Simulation and optimization as one. Dealing with multiple objectives. The idea of Pareto. 2Χ4=8
6 Multi-purpose hydrosystems: part 2 – bottom-up. Introduction to Game Theory. Tragedy of the Commons (with an application to groundwater management). One-off and recurrent games. A different kind of game: Water Monopolies. 1Χ4=4
7 Optimization in Water Resources Management: conventional methods. Analytical methods, Hill-climbing methods, Dynamic Programming, Linear programming. With examples from water allocation problems. 1Χ4=4
8 Optimization in Water Resources Management: advanced methods. Genetic algorithms, Evolutionary programming, Simulated Annealing. 1Χ4=4
9 Economics in Water Resources Management Basic concepts of economic theory. Water as an economic resource. Determining the full economic cost of water. 1Χ4=4

Learning Objectives

[Missing information in the English transcript]

Teaching Methods

Teaching methods Continuous flow of theoretical concepts and applications
Teaching media Blackboard use and Powerpoint presentations. Demonstration of calculations in MS Excel
Computer and software use Use of Excel and/or Matlab as part of homework exercises.
Problems - Applications 3 major assignments on probabilistic reservoir design and multi-reservoir, multi-use water resources management and optimisation.
Assignments (projects, reports) Each lecture is supported by relevant problems, solved in the classroom.
Student presentations Yes
Other Student presentations and oral examination of the final integrative assignment.

Student Assessment

  • Final written exam: 70%
  • Assignments (projects, reports): 30%

Textbooks - Bibliography

  1. Mimikou, M., Baltas, E. and Tsihrintzis, V. (2016). Hydrology and Water Resource Systems, CRC Press, Taylor and Francis Group.
  2. Mimikou, M. (2007). Water Resources Technology, Ed. Papasotiriou.
  3. Grigg, N. S., Water Resources Management, McGraw‐Hill, New York, 1996. 4 Loucks, D.P., E. van Beek, J.R. Stedinger, J.P.M. Dijkman, Water Resources Systems Planning and Management, An Introduction to Methods, Models and Applications, Studies and Reports in Hydrology, UNESCO Publishing, 680 pages, Paris, 2005
  4. Mays, L. W., and Y.K. Tung, Hydrosystems Engineering and Management, McGraw-Hill, New York, 1992.
  5. Palmieri, A., F. Shah and A. Dinar (2001), Economics of reservoir sedimentation and sustainable management of dams, Journal of Environmental Management (2001) 61, 149–163
  6. Water Framework Directive
  7. Box, P., and M. Muller, A Note on the Generation of Random Normal Deviates, The Annals of Mathematical Statistics (1958), Vol. 29, No. 2 pp. 610–611

Lecture Time - Place:

  • Wednesday, 08:45 – 12:30,
    Rooms:
    • Αμφ. Ηχοτεχνίας