The objectives of the course are:
1. To understand the hydrological processes at the watershed/catchment scale.
2. To understand the fundamental principles of hydrological modelling.
3. To gain experience in using state-of-the-art modelling tools for water resources management.
4. To integrate hydrological modelling into water resources management.
Learning Outcomes
By the end of the course, students will be able to:
• Critically select proper hydrological modelling tools for water resources management
• Use hydrological models of difference complexities
• Perform model sensitivity analysis
• Perform model uncertainty analysis
• Familiarize with computational programming (MATLAB/Python)
Course Content
This course provides an in-depth exploration of the computational tools that we can use to simulate the hydrological cycle at the catchment scale. The course will provide a detailed description of hydrological models of different complexities, starting from simple empirical/statistical models and expanding to lumped/conceptual, and physics based hydrological model. During the course we will provide a detailed overview on how hydrological models can be used under data limitations, and how data uncertainties can propagate from hydrological modelling to assessment of water resources management. Finally, we will provide a detailed description on how hydrological modelling is integrated into operational water resources management plans from the regional catchment to the national level.
Number of ECTS
8
Level of Course
2nd Cycle (Master’s Degree)
Lectures/Week
1 (3 hours per lecture)
Prerequisites
None
Co-requisites
None
Teaching Methodology
• Lectures
• Coursework
• Recitation for solving sample problems
• Field trips: Visits to local or regional sites relevant to the course topics
• Office hours
• Chow, VenTe. Applied hydrology. McGraw-hill, 1971.
• Beven, Keith J. Rainfall-runoff modelling: the primer. John Wiley & Sons, 2012.
• Saltelli, Andrea, Marco Ratto, Terry Andres, Francesca Campolongo, Jessica Cariboni, Debora Gatelli, Michaela Saisana, and Stefano Tarantola. Global sensitivity analysis: the primer. John Wiley & Sons, 2008.
• Mays, Larry W. Water resources engineering. John Wiley & Sons, 2010.
• Selected journal articles and case studies from current literature
