Course detail

Selected parts of landscape water management

FAST-CS01Acad. year: 2014/2015

Selected chapters from operative hydrology focused on neural network and uncertainties of measurement.
Selected chapters from hydromorphology and 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.

Department

Institute of Landscape Water Management (VHK)

Learning outcomes of the course unit

Determination of measurement uncertainty of hydrological data
Overview of artificial intelligence methods that can be used in water management
Artificial neural networks - principles, properties, simulators, application examples
Models of porous systems - microscopic scale
Use of models in pedology - principles, data entry, evaluation of the resulting data, applications
Variability of hydropedological variables
Introduction to fluvial geomorphology, hydromorphological mapping of water sources, principles of small water courses restoration, river restoration problems and obstacles

Prerequisites

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

Co-requisites

Probability theory and mathematical statistics, operational and system analysis, open channels hydraulics, river engineering

Planned learning activities and teaching methods

Teaching methods depend on the type of course unit as specified in the article 7 of BUT Rules for Studies and Examinations.
Students pass the 13 basic lectures in applied hydrology, hydromorphology, river restoration and pedology.
In practice, students process according to entering some basic task using computers and software available.
At the end of course test draw from the full range of lectures.

Assesment methods and criteria linked to learning outcomes

For a successful finishing of the subject, student has to:
♦ - be present in seminars,
♦ - project processing in selected chapters,
♦ - hand over his 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. Selected chapters from meteorology and climatology (climate change)
7. - 8. Selected parts from fluvial morphology
9. Pedotransfer functions, sofware RETC, Rosetta and HYDRUS
10 Introduction to modeling in pedology
11. Models of porous systems - microscopic scale
12. 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

STARÝ, Miloš a KRÁLOVÁ, Helena a KAMENÍČKOVÁ, Ivana: Vybrané statě z vodního hospodářství krajiny. VUT FAST v Brně, 2007. [http://www.fce.vutbr.cz/studium/materialy/ucebnice.pdf] (CS)

Recommended literature

CÍSLEROVÁ, Mlena: Inženýrská hydropedologie. ČVUT v Praze, 1989. ISBN 80-01-00052-4. (CS)
Mays, Larry W.: Water Resources Handbook. Hong Kong : McGraw-Hill,, 1996. (EN)
Nacházel, K. - Starý, M. - Zezulák, J. a kol: Užití metod umělé inteligence ve vodním hospodářství. ACADEMIA Praha, 2004. (CS)
Just, T. a kol.: Vodohospodářské revitalizace a jejich uplatnění v ochraně před povodněmi. ZO ČSOP Hořovicko, AOPK ČR a MŽP ČR Praha, 2005. (CS)
KODEŠOVÁ, Radka: Modelování v pedologii. Česká zemědělská univerzita v Praze, 2005. ISBN 80-213-1347-1. (CS)

Classification of course in study plans

  • Programme N-K-C-SI Master's

    branch V , 1 year of study, winter semester, compulsory

  • Programme N-P-C-SI Master's

    branch V , 1 year of study, winter semester, compulsory

  • Programme N-P-E-SI Master's

    branch V , 1 year of study, winter semester, compulsory

Type of course unit

 

Lecture

26 hod., optionally

Teacher / Lecturer

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. Selected chapters from meteorology and climatology (climate change)
7. - 8. Selected parts from fluvial morphology
9. Pedotransfer functions, sofware RETC, Rosetta and HYDRUS
10 Introduction to modeling in pedology
11. Models of porous systems - microscopic scale
12. Variability of hydropedological variables
13. Selected lecture on the topic of current practice

Exercise

26 hod., compulsory

Teacher / Lecturer

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 evaluation of water courses, river restoration
9. - 12. Application of sofware HYDRUS (simulation of water flow in the soil profile, ponded infiltration, boundary conditions, complex processing mathematical model)