COURSE UNIT TITLE

: STOCHASTIC HYDROLOGY

DEGREE PROGRAMMES

Description of Individual Course Units

Course Unit Code Course Unit Title Type Of Course D U L ECTS
CIE 5124 STOCHASTIC HYDROLOGY ELECTIVE 3 1 0 8

Offered By

Graduate School of Natural and Applied Sciences

Level of Course Unit

Second Cycle Programmes (Master's Degree)

Course Coordinator

PROFESSOR DOCTOR GÜLAY ONUŞLUEL GÜL

Offered to

HYDRAULIC ENGINEERING AND WATER RESOURCES
HYDRAULIC ENGINEERING AND WATER RESOURCES
HYDRAULIC ENGINEERING AND WATER RESOURCES

Course Objective

Stochastic Hydrology is defined as the manipulation of statistical characteristics of hydrologic variables to solve hydrologic problems, on the basis of the stochastic properties of the problems . The ultimate objective of stochastic hydrology is to predict more efficient and economic design of water resources systems through analytical or simulation models.
Stochastic Processes in Hydrology does not differentiate between general stochastic processes and time series, because time series are considered a part of hydrologic processes. Stochastic Process in hydrology is aimed at three audiences: (1) practicing hydrologists, water resources engineers and water resources in general; (2) graduate students who intend to specialize in hydrology; and (3) specialists other than hydrologists in related fields who are interested in stochastic processes as applied to hydrology.

Learning Outcomes of the Course Unit

1   Students can analyze hydrological and climatological data using advance statistical methods.
2   Students can identify, formulate and solve general civil and environmental engineering problems, analyze and interpret scientific data by using the technical ability and proficiency gained through the course.
3   Students will be able to evaluate the quality of available data, the existence of trends, periodicities and other types of non-stationarity in data.
4   Students will also be able to describe and quantify variability in space and time in data and apply methods for interpolation and simulation, as well as performing extreme value analysis of precipitation, floods and low flow.
5   Students will improve their oral and written (both textual and graphical) communication skills.

Mode of Delivery

Face -to- Face

Prerequisites and Co-requisites

CIE 5113 - Hydrometric Data Evaluation

Recomended Optional Programme Components

None

Course Contents

Week Subject Description
1 Aıms And Means In Tıme Serıes Analysıs
2 Stationarity And Invertibility Function
3 Autocorrelatıon And Cross-Correlatıon Analysıs
4 Autocorrelatıon And Cross-Correlatıon Analysıs (Cont.)
5 Lınear Statıonary Stochastıc Process
6 Autoregressive and Moving average processes
7 Arma Processes
8 Perıodogram (Lıne Spectrum) Analysıs
9 Spectral Analysıs
10 Spectral Analysıs (Cont.)
11 Cross Correlatıon And Cross Spectral Analysıs
12 Cross Correlatıon And Cross Spectral Analysıs (Cont.)
13 The Experımental Statıstıcal Method In Hydrology
14 Presentation Of Student Applications

Recomended or Required Reading

YEVJEVICH, V., Stochastic Processes in Hydrology , Fort-Collins, Colorado, Water Resources Publ., 1972.
BOX, G. E. P.; JENKINS, G. M., Time Series Analysis, Forecasting and Control , SanFrancisco, Holden-Day, 1976.
SALAS, J., D., DELLEUR, J.W & Oth , Applied Modeling of Hydrologic Time Series , Littleton, Colorado, Water Resources Publ., 1985.

Planned Learning Activities and Teaching Methods

Formal presentation of subjects and recitation, homework assignments.

Assessment Methods

SORTING NUMBER SHORT CODE LONG CODE FORMULA
1 MTE MIDTERM EXAM
2 ASG ASSIGNMENT
3 FIN FINAL EXAM
4 FCG FINAL COURSE GRADE MTE * 0.25 + ASG *0.25 +FIN *0.50
5 RST RESIT
6 FCGR FINAL COURSE GRADE (RESIT) MTE * 0.25 + ASG *0.25 +RST *0.50


Further Notes About Assessment Methods

None

Assessment Criteria

LO 1-2-3-4: evaluated through tailor-made questions posed during mid-term and final exams.
LO 1-2-3-4-5: evaluated through reports prepared upon homework assignments.

Language of Instruction

Turkish

Course Policies and Rules

To be announced.

Contact Details for the Lecturer(s)

gulay.onusluel@deu.edu.tr

Office Hours

will be announced at the beginning of semester.

Work Placement(s)

None

Workload Calculation

Activities Number Time (hours) Total Work Load (hours)
Lectures 14 3 42
Tutorials 14 1 14
Preparations before/after weekly lectures 13 3 39
Preparation for midterm exam 1 10 10
Preparation for final exam 1 12 12
Preparing assignments 2 30 60
Preparing presentations 2 10 20
Midterm 1 4 4
Final 1 4 4
TOTAL WORKLOAD (hours) 205

Contribution of Learning Outcomes to Programme Outcomes

PO/LOPO.1PO.2PO.3PO.4PO.5PO.6PO.7PO.8PO.9PO.10PO.11
LO.144
LO.244
LO.355
LO.4444
LO.5

CONTACT INFORMATION
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Phone: +90(232) 412 12 12 - Fax: +90 (232) 464 81 35

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