Subject Datasheet

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I. Subject Specification

1. Basic Data
1.1 Title
Modelling of Hydrosystem
1.2 Code
1.3 Type
Module with associated contact hours
1.4 Contact hours
Type Hours/week / (days)
Lecture 2
Seminar 1
1.5 Evaluation
1.6 Credits
1.7 Coordinator
name Dr. Krámer Tamás
academic rank Associate professor
1.8 Department
Department of Hydraulic and Water Resources Engineering
1.9 Website
1.10 Language of instruction
1.11 Curriculum requirements
Compulsory in the Infrastructure Engineering (MSc) programme
1.12 Prerequisites
Recommended prerequisites:
  • Civil Engineering Informatics (BMEEOFTAT42)
  • Geoinformatics (BMEEOFTAT43)
1.13 Effective date
1 September 2021

2. Objectives and learning outcomes
2.1 Objectives
The objective of the course is to introduce students to methods of numerical modelling to analyse physical conditions in watercourses, lakes and reservoirs, and to predict the consequences of various measures or hydraulic structures. We define the scope of numerical models with various physical content or dimensionality, illustrated with practical examples. We devote classes to the coupling of models of interacting processes, modelling uncertainties, as well as post-processing and analysis informatics procedures that support water management planning effectively. It is also our objective that the students improve their practical skills and their complex thinking, making them more open to learn new software.
2.2 Learning outcomes
Upon successful completion of this subject, the student:
A. Knowledge
  1. Knows the general principles, rules and methods of mathematics, natural sciences and information technology required to practice engineering tasks supporting the design and operation of facilities,
  2. Has knowledge in 3D modeling of the natural or built environment,
  3. Knows and understands information and communication technologies required for the analysis of facilities,
  4. Knows the main types of simulation methods used in water management,
  5. Is able to describe lumped methods for rainfall runoff over hydrological catchments, their calibration procedures and data demand,
  6. Is familiar with geoinformatics procedures that support the modelling of surface runoff,
  7. Can identify the principles of constructing 1D river network models, their data input and their sources of uncertainty, and how these aspects vary with the purpose of the models,
  8. Knows the principles of evaluating flood hazard via numerical simulations, and how to apply these to lowland or hilly catchments,
  9. Understands the principles of the equations governing 3D river hydrodynamics, their calibration data input, boundary conditions, and can give examples of flow phenomena that can be studied with 3D modelling,
  10. Knows the main elements of model systems of lake hydrodynamics and the variables that connect them,
  11. Can explain the objective of accelerating numerical solutions and the principles of implicit solvers, parallel computation and adaptive mesh resolution;
B. Skills
  1. Is able to apply the necessary principles of natural sciences and information technology in the analysis of the elements of the natural and built environment,
  2. Selects and effectively applies the appropriate information technology tools to support the design of facilities,
  3. Produces a 3D model of the natural or built environment,
  4. Applies and develops processes, models and information technologies used by various trades in the design, construction, and operation of facilities,
  5. Can calibrate and validate a lumped catchment model,
  6. Is able to model the flood conveyance of a river reach in 2D and analyse results on a map,
  7. Can construct a boundary-fitted unstructured computational mesh, keeping numerical accuracy in consideration,
  8. Can operate a 1D-2D linked hydrodynamic model,
  9. Can summarize their results in writing, with a logical structure and precise charts / figures;
C. Attitudes
  1. Is open to solve the tasks individually and cooperate with other participants of the project,
  2. Is willing to acquire the ability of self-learning and self-development,
  3. Is open to apply new IT tools, methods and procedures related to a particular field,
  4. Collaborates with the lecturer and classmates during learning,
  5. Expands their knowledge on their specialization with continuous acquisition, and reaches out to reputable online sources in addition to the compulsory teaching materials to answer their questions,
  6. Is open to learn new software,
  7. Strives to solve assigned tasks precisely and error free;
D. Autonomy and Responsibility
  1. Takes responsibility for her/his decisions and work as well as for those of the professional team under their supervision,
  2. Contributes to the team’s mission by taking responsibility for their own tasks
2.3 Methods
Lectures on the theoretical knowledge. Practices to show the steps of solving modelling problems, to demonstrate software applied in homework assigments and to offer consultations. Homework is based on group collaboration, each group consulting on own laptop. Communication in email and orally.
2.4 Course outline
WeekTopics of lectures and/or exercise classes
1.Modelling methods in water management; scales and dimensions
2.Modelling rainfall runoff at catchment scale (methods, input, GIS aspects). Part I
3.Modelling rainfall runoff at catchment scale. Part II
4.1D model structure of river networks.
5.River flood conveyance modelling in 2D (calibration, uncertainty).
6.Evaluation of flood hazard in steep and lowland river floodplains.
7.Efficient computational methods, application of finite volume solvers on adaptive and irregular meshes, parallel computing. 1D-2D model coupling.
8.3D modelling of river reaches and hydraulic structures (governing equations).
9.3D Reynolds-averaged Navier-Stokes (RANS) models in practice, ecohydraulic studies.
10.Modelling morphodynamics in rivers.
11.Modelling systems for lake hydrodynamics (meteorology, waves, flows, sediment and thermodynamics). Part I
12.Modelling systems for lake hydrodynamics. Part II.
13.Modelling the interaction of surface and subsurface waters.
14.Probabilistic modelling to estimate design loads of hydraulic structures, including design flood levels.

The above programme is tentative and subject to changes due to calendar variations and other reasons specific to the actual semester. Consult the effective detailed course schedule of the course on the subject website.
2.5 Study materials
  1. N.R.B. Olsen: Numerical Modelling and Hydraulics. NTNU, Norway. ISBN-82-7598-074-7 (NTNU weblapjáról szabadon letölthető)
  2. Pavel Novak, Vincent Guinot, Alan Jeffrey, Dominic E. Reeve: Hydraulic Modelling – An Introduction: Principles, Methods and Applications. CRC Press, 2010.
2.6 Other information
2.7 Consultation

Consultation: in the office of the lecturers, at their individual hours as published on the department www homepage and on the information display outside the department. No appointment necessary.

This Subject Datasheet is valid for:
2022/2023 semester I

II. Subject requirements

Assessment and evaluation of the learning outcomes
3.1 General rules
The learning outcomes in section 2.2. are evaluated based on homework and on the assessment in the exam period.
3.2 Assessment methods

Evaluation formAbbreviationAssessed learning outcomes
Homework 1 (small homework)HW1B.5, B.9; C.1-C.7; D.1-D.2
Homework 2 (small homework)HW2B.1-B.4, B.6-B.9; C.1-C.7; D.1-D.2
Exam (oral or written)EA.1-A.11; C.2, C.5

The dates of deadlines of assignments/homework can be found in the detailed course schedule on the subject’s website.
3.3 Evaluation system
Total in instruction period50%
3.4 Requirements and validity of signature
The condition to obtain the signature is that the student achieves at least40% of the maximum mark for each homework under section 3.2 individually.
For those that (1) already have the signature in the subject and (2) are studying in a regular, non-exam course, their results obtained in the instruction period will overwrite any previous one.
3.5 Grading system
A mark of less than 40% of the maximum at the exam will result in a failed exam grade.
The grade is calculated according to this table based on the total marks (see Section 3.3):
GradeMarks (P)
excellent (5)85%<=P
good (4)70<=P<85%
satisfactory (3)55<=P<70%
pass (2)40<=P<55%
fail (1)P<40%
3.6 Retake and repeat
  1. All homework can be submitted late - along with payment of a fee according to regulations - until the date specified in the detailed semester schedule.
3.7 Estimated workload
attendance of contact lessons14×3=42
midterm preparation to practices4
preparation of homework52
individual acquisition of the written study material6
preparation to the exam16
3.8 Effective date
1 September 2021
This Subject Datasheet is valid for:
2022/2023 semester I