Subject Datasheet
Completion requirements
Subject Datasheet
Download PDFI. Subject Specification
1. Basic Data
1.1 Title
Hydrologic Modelling
1.2 Code
BMEEOVVMSFIN05-00
1.3 Type
Module with associated contact hours
1.4 Contact hours
| Type | Hours/week / (days) |
| Lecture | 1 |
| Seminar | 1 |
1.5 Evaluation
Exam
1.6 Credits
3
1.7 Coordinator
| name | Dr. Szilágyi József |
| academic rank | Professor |
| szilagyi.jozsef@emk.bme.hu |
1.8 Department
Department of Hydraulic and Water Resources Engineering
1.9 Website
1.10 Language of instruction
hungarian
1.11 Curriculum requirements
Compulsory in the Water and Hydro-Environmental Engineering (MSc) programme
1.12 Prerequisites
1.13 Effective date
1 September 2025
2. Objectives and learning outcomes
2.1 Objectives
The aim of the course is to introduce students to the fundamentals of systems theory, linear algebra, and linear systems relevant to solving basic hydrological problems. Students will learn to apply the MATLAB programming language for solving hydrological tasks, and to build models with the most commonly applied tools. Another objective is to familiarize students with the theoretical background and practical application of several forecasting methods used in Hungary. The course will also expand their knowledge of time series models and enable them to solve practical problems. Additionally, students will gain insight into water management information systems, and forecasting methods in water management.
2.2 Learning outcomes
Upon successful completion of this subject, the student:
A. Knowledge
1. Familiarity with the most frequently encountered time series concepts and models employed in hydrological research and ability to apply them for one's own research.
2. Aware of the conditions necessary for applying the Kalman filter for optimal model parameter estimation.
3. Familiar with linear hydrological models and knows how to modify them for one’s own purpose.
4. Familiar with lumped models of watersheds, as well as the methods and data requirements for their calibration.
5. Understanding which geoinformatics techniques support surface runoff modeling and the hydromorphological analysis of watersheds.
B. Skills
1. Advanced problem solving capacity in hydrological modelling and forecasting using linear and time series models.
2. Capable of comprehensively understanding, modifying, and purposefully applying linear models used in hydrological practice.
3. Ability to understand, correctly apply, and further develop time series models used in hydrological practice.
4. Capable of calibrating and validating a lumped rainfall-runoff model.
5. Aptitude for writing MATLAB code performing calibration and its application for solving problems in hydrology and civil engineering.
6. Capacity of solving complex modelling problems by MATLAB.
C. Attitudes
1. Cooperates with the instructor during the learning process.
2. Continuously and actively seeks ways of gaining knew knowledge even beyond the required curriculum and employs the internet for finding intuitive answers to research problems.
3. Open to learn new software skills.
4. Attempts to perform precise problem solutions.
D. Autonomy and Responsibility
1. Resolution to solving homework on one's own within feasible limits.
2.3 Methods
Lectures on theory. Practical guidance about the steps needed for solving computational/modelling problems and the software required. Consultation of the homework individually or in groups using one's own laptop on top of written (e-mail) and personal oral communication during consultation hours.
2.4 Course outline
1. Systems theory. Linear ordinary differential equations.
2. Impulse response and convolution.
3. The Wiener-Hopf and Yule-Walker equations.
4. The Saint-Venant equations and its simplified versions.
5. State-space representation of the continuous-time, spatially discrete linear kinematic wave equation.
6. The Kalinin-Milyukov-Nash cascade.
7. The Discrete Linear Cascade Model: classical pulsed data system.
8. Autoregressive processes, the Gauss-Markov process.
9. The Kalman filter and its applications.
10. Hydrologic modelling.
11. Processes and tools of hydrologic modelling.
12. Rainfall-runoff modelling: methods, data requirements.
13. Rainfall-runoff modelling: geoinformatics.
14. Rainfall-runoff modelling: calibration, optimization.
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.
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
a) Textbooks
1. Szilágyi J., Szöllősi-Nagy A., 2010. Recursive streamflow forecasting: a state-space approach, CRC Press, London, UK.
2. Brockwell, P., 2010. Introduction to time-series and forecasting, Springer, New York, USA.
3. Bras, R. L., Rodriguez-Iturbe, I., 1993. Random functions and hydrology, Dover, London, UK.
2.6 Other information
None.
2.7 Consultation
Advertised on the course's webpage (occasionally by specific request), in the office of the course instructor.
This Subject Datasheet is valid for:
2025/2026 semester II
II. Subject requirements
Assessment and evaluation of the learning outcomes
3.1 General rules
Evaluation of the participant's learning progress described in 2.2. is performed by written exam and the homework assignment including subtasks.
3.2 Assessment methods
| Assessment Name (Type) | Code | Assessed Learning Outcomes |
|---|---|---|
| 1. homework assignment | HW1 | A.1.; A.3.; B.1.; B.2; B.6.; C.1.-C.4.; D.1. |
| 2. homework assignment | HW2 | A.1.; A.2; B.1.; B.2; B.6.; C.1.-C.4.; D.1. |
| 3. homework assignment | HW3 | A.1.; A.2.; B.1.-B.3.; C.1.-C.4.; D.1. |
| Written exam (final performance evaluation) | E | A.1-A.5; B.1-B.5; C.4; D.1 |
The dates of deadlines of assignments/homework can be found in the detailed course schedule on the subject’s website.
3.3 Evaluation system
| Code | Weight |
|---|---|
| HW1 | 15% |
| HW2 | 15% |
| HW3 | 20% |
| E | 50% |
| Total | 100% |
3.4 Requirements and validity of signature
Evaluation of the participant's learning progress described in 2.2. is performed by written exam and three homework assignments.
3.5 Grading system
| Grade | Score (P) |
|---|---|
| excellent (5) | 85≤P |
| good (4) | 70≤P<85% |
| satisfactory (3) | 60≤P<70% |
| pass (2) | 50≤P<60% |
| fail (1) | P<50% |
3.6 Retake and repeat
All homework assignments may be submitted late until the deadline specified in the detailed course outline, subject to the late submission fee regulations of the university.
3.7 Estimated workload
| Activity | Hours/Semester |
|---|---|
| participation in contact classes | 2x14=28 |
| preparation for the homework assignments | 3x5=15 |
| study from notes, textbooks | 45 |
| preparation for the final exam | 16 |
3.8 Effective date
1 September 2025
This Subject Datasheet is valid for:
2025/2026 semester II