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System Approach to Water Management

5 ECTS credits
125 h study time

Offer 1 with catalog number 4017558FNR for all students in the 1st semester at a (F) Master - specialised level.

Information about this course is applicable on academic year 2017-2018.

Semester
1st semester
Enrollment based on exam contract
Impossible
Grading method

Grading (scale from 0 to 20)

Can retake in second session
Yes
Enrollment requirements
Registration for Urban hydrology and hydraulics, for System Approach to Water Management or for Surface Water Modelling is allowed if one is registered for or has already successfully accomplished Surface Water Hydrology or Hydrologie en hydro-informatica.
Taught in
English
Partnership agreement
  • Under interuniversity agreement for degree program
Faculty
Faculty of Engineering
Responsible organisation
Hydrology and Hydraulic Engineering
Educational Team:
External partner(s)
KU Leuven
Activities and contact hours
  • 24 contact hours Lecture
  • 24 contact hours Seminar, Exercises or Practicals
  • 12 contact hours Independent or External Form of Study
Course content
Theoretical:
- Primer to water system modeling:
o Different modelling approaches: detailed versus simplified modelling, physically-based versus conceptual and empirical models;
o Model type selection (incl. complementary use of detailed and simplified models, required space and time scales, different modelling concepts);
- Linking of (sub)models at different complexity level;
- Numerical modelling: basic conservation equations, numerical techniques, time and space discretisation, solution schemes, stability, convergence;
- Model parameter calibration, model validation;
- Sensitivity and uncertainty analysis, risk-based analysis and design;
- Use of model results for decision support: multi criteria analysis, cost-benefit analysis, consideration of boundary conditions, etc.;
- The role of modelling in decision support systems: simulation strategies;
- Introduction to expert systems and genetic algorithms;
- Optimal control theory; and
- Basics of neural network modelling.

Practical:
Based on example datasets from water engineering, PC exercises will be given on:
- Model structure identification: identification and calibration of a simplified (conceptual, grey box or black box model) model to data or a more detailed physically-based model;
- Model performance evaluation;
- Uncertainty quantification;
- Statistical post-processing of model simulation results (for decision supporting purposes; e.g. extreme value analysis, QDF relationships);
- Climate change impact investigation;
- Control of a reservoir.
Course material
  • Digital course material (Required): Slides and course text
  • Digital course material (Required): Datasets and examples of results
Additional info

Available on e-platform:
 

Programme Objectives

Algemene competenties

This course aims to give general knowledge and understanding of generalized techniques used in mathematical modelling of water systems to support the model calibration, the model validation, the parameter calibration, the model uncertainty and sensitivity analysis, etc. Also a discussion is given of different types of models and modelling procedures and on the linking of various types of models in integrated water and river basin management. The course consequently forms the technical glue between different water system related modelling courses. In addition the course focuses on techniques of decision support, and more specifically on how model results can be used on the basis of water management decisions. Finally, advanced modeling techniques will be discussed as well as water system optimization and control.

General competences

The Master of Science in Engineering has in-depth knowledge and understanding of the advanced methods and theories to schematize and model complex problems or processes

The Master of Science in Engineering can reformulate complex engineering problems in order to solve them (simplifying assumptions, reducing complexity).

The Master of Science in Engineering can correctly report on research or design results in the form of a technical report or in the form of a scientific paper

The Master of Science in Engineering can present and defend results in a scientifically sound way, using contemporary communication tools, for a national as well as for an international professional or lay audience.

The Master of Science in Engineering can collaborate in a (multidisciplinary) team.

The Master of Science in Engineering can develop, plan, execute and manage engineering projects at the level of a starting professional

The Master of Science in Engineering can think critically about and evaluate projects, systems and processes, particularly when based on incomplete, contradictory and/or redundant information.

The Master of Science in Engineering has a creative, problem-solving, result-driven and evidence-based attitude, aiming at innovation and applicability in industry and society.

The Master of Science in Engineering has a critical attitude towards one’s own results and those of others.

The Master of Science in Engineering has the flexibility and adaptability to work in an international and/or intercultural context.

The Master of Science in Civil Engineering can quantify the hydrologic processes, select appropriate hydrologic simulation tools and integrate them into hydrologic design procedures.

The Master of Science in Civil Engineering – Option Water Resources can develop, calibrate, validate and use numerical tools used for the simulation of water systems (river basins, groundwater bodies, sewers,…) in the framework of water management problems.

Grading

The final grade is composed based on the following categories:

  • PRAC Presentation determines 50% of the final mark.
  • PRAC Report determines 50% of the final mark.

Within the PRAC Presentation category, the following assignments need to be completed:

presentation of results with a relative weight of 1 which comprises 50% of the final mark.

Note: presentation of results (50%)

Within the PRAC Report category, the following assignments need to be completed:

report on PC exercises with a relative weight of 1 which comprises 50% of the final mark.

Note: Report on PC exercises applied to new dataset (50%)

Additional info with regard to grading
Report on PC exercises applied to new dataset (50%) + presentation of results (50%)