Course detail

Hydrology

FAST-DSB022Acad. year: 2022/2023

Introduction of stochastic hydrology, modeling of artificial flow series, modelling of synthetic rainfall, problems of temporal and spatial rainfall distribution, meteorological radars and meteorological satelites, numerical meteorological prediction models, models of rainfall - runoff process in small and big river basins, operative prediction of river basin runoff, extreme flows

Language of instruction

Czech

Number of ECTS credits

Mode of study

Not applicable.

Guarantor

doc. Ing. Daniel Marton, Ph.D.

Department

Institute of Landscape Water Management (VHK)

Learning outcomes of the course unit

PdD student gains knowledge for applikation stochastic hydrology and operative hydrology methods in thesis

Prerequisites

Basic knowledge of higher mathematics, statistics and probability theory, physics. Detailed knowledge of hydrology (magister study level). Basic knowledge of Matlab and R programing.

Co-requisites

Not applicable.

Planned learning activities and teaching methods

Not applicable.

Assesment methods and criteria linked to learning outcomes

To evaluation of Hydrology course the examination have to be pass. Examination evaluates theoretical and practical knowledge.

Course curriculum

  1. Fundaments of stochastic hydrology.
  2. Modeling of artificial flow series.
  3. Modelling of synthetic rainfall.
  4. Assessment of spatial distribution of rainfall above the river basin.
  5. Meteorological radars and meteorological satelites.
  6. Numerical meteorological prediction models.
  7. Models of rainfall – runoff process in small small river basins.
  8. Models of rainfall – runoff process in big river basins.
  9. Operative prediction of river basin runoff.
  10. Operative prediction of river basin runoff.
  11. Operative prediction of river basin runoff.
  12. Extreme flows.
  13. Extreme flows.

Work placements

Not applicable.

Aims

Ability of detailed orientation in problems of hydrology, independent solution of difficult hydrological tasks, theoretical knowledge for following PhD. study aimed at water management problems

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

NACHÁZEL, K., ZEZULÁK J., STARÝ M., Využití metod umělé inteligence ve vodním hospodářství. Praha: Academia, 2004. ISBN 80-200-0229-4. (CS)
STARÝ, M., Hydrologie, Modul 01, Studijní opory, VUT v Brně, 2005. (CS)
STARÝ, M., Hydrologie, Modul 02, Studijní opory, VUT v Brně, 2005. (CS)
WAGENER, T., WHEATHER H. S., GUPTA H. V., Rainfall-Runoff Modelling in Gauged and Ungauged Catchments. Imperial College Press, 2004. ISBN-13: 978-1860944666. (EN)

Recommended reading

Not applicable.

Classification of course in study plans

  • Programme DPC-V Doctoral 1 year of study, summer semester, compulsory-optional
  • Programme DPC-V Doctoral 1 year of study, summer semester, compulsory-optional
  • Programme DKA-V Doctoral 1 year of study, summer semester, compulsory-optional
  • Programme DPA-V Doctoral 1 year of study, summer semester, compulsory-optional

Type of course unit

 

Lecture

39 hod., optionally

Teacher / Lecturer

doc. Ing. Daniel Marton, Ph.D.

Syllabus

  1. Fundaments of stochastic hydrology.
  2. Modeling of artificial flow series.
  3. Modelling of synthetic rainfall.
  4. Assessment of spatial distribution of rainfall above the river basin.
  5. Meteorological radars and meteorological satelites.
  6. Numerical meteorological prediction models.
  7. Models of rainfall – runoff process in small small river basins.
  8. Models of rainfall – runoff process in big river basins.
  9. Operative prediction of river basin runoff.
  10. Operative prediction of river basin runoff.
  11. Operative prediction of river basin runoff.
  12. Extreme flows.
  13. Extreme flows.