Course detail

Selected Chapters of Landscape Water Management

FAST-NSA013Acad. year: 2022/2023

Selected chapters from operative hydrology focused on neural network and uncertainties of measurement.
Selected chapters from fluvial geomorphology, river restoration.
Selected parts from hydropedology and basics of modeling of pedology.

Language of instruction

Czech

Number of ECTS credits

5

Mode of study

Not applicable.

Guarantor

Ing. Tomáš Kozel, Ph.D.

Department

Institute of Landscape Water Management (VHK)

Learning outcomes of the course unit

Student gains overview of actual problems in water management and the ways of their solution. Each student works on individual solution of selected partial tasks.

Prerequisites

Hydrology, hydraulics, reservoirs and water management systems, soil science and irrigation, river basin protection, drainage structures, ponds, land consolidation.

Co-requisites

Not applicable.

Planned learning activities and teaching methods

Metody vyučování závisejí na způsobu výuky a jsou popsány článkem 7 Studijního a zkušebního řádu VUT.
Studenti absolvují 13 základních přednášek z klasické i aplikované hydrologie, hydromorfologie, revitalizace vodních toků a pedologie.
Ve cvičeních studenti zpracují podle zadání několik základních hydrologických úloh s využitím počítačů a dostupného software.
Na závěr kursu vypracují test z celého rozsahu přednášené látky.

Assesment methods and criteria linked to learning outcomes

To successfully complete the course, the student must meet the following conditions:

- attendance at exercises,

- elaboration of the project from selected chapters,

- submission of the project and its presentation,

- written exam.

Course curriculum

1. Uncertainty of measured hydrologic data.
2. Artificial intelligence methods and their use in water management.
3.–4. Artificial neural networks and their properties and applications to specific tasks.
5.–6. Basics of fluvial geomorphology, application in landcape water management.
7.–8. Small water courses restoration, problems and obstacles, subsidy programmes, model projects.
9. Pedotransfer functions and creation of the database HYPRES, software HYDRUS.
10.–11. Introduction to modeling in pedology, pedogenetic models, models of porous systems.
12. Infiltration, variability of hydropedological variables.
13. Selected lecture on the topic of current practice.

Work placements

Not applicable.

Aims

Overview of actual problems in water management and the ways of their solution, individual solution of selected partial tasks

Specification of controlled education, way of implementation and compensation for absences

Extent and forms are specified by guarantor’s regulation updated for every academic year.

Recommended optional programme components

Not applicable.

Prerequisites and corequisites

Not applicable.

Basic literature

Not applicable.

Recommended reading

Not applicable.

eLearning

eLearning: currently opened course

Classification of course in study plans

  • Programme NPC-SIV Master's, 1. year of study, winter semester, compulsory

Type of course unit

 

Lecture

26 hours, optionally

Teacher / Lecturer

Ing. Tomáš Kozel, Ph.D.

Syllabus

1. Uncertainty of measured hydrologic data. 2. Artificial intelligence methods and their use in water management. 3.–4. Artificial neural networks and their properties and applications to specific tasks. 5.–6. Basics of fluvial geomorphology, application in landcape water management. 7.–8. Small water courses restoration, problems and obstacles, subsidy programmes, model projects. 9. Pedotransfer functions and creation of the database HYPRES, software HYDRUS. 10.–11. Introduction to modeling in pedology, pedogenetic models, models of porous systems. 12. Infiltration, variability of hydropedological variables. 13. Selected lecture on the topic of current practice.

Exercise

26 hours, compulsory

Teacher / Lecturer

Ing. Tomáš Kozel, Ph.D.

Syllabus

1. Determination of the uncertainty of point and vertical velocity measured hydrometric propeller. 2.–4. The use of artificial neural networks in predicting the average monthly flow. 5.–8. Hydromorphological mapping and evaluation of water courses. 9.–12. Application of sofware HYDRUS (simulation of water flow in the soil profile, ponded infiltration, boundary conditions, complex processing mathematical model).

eLearning

eLearning: currently opened course