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Information
| Unit | INSTITUTE OF NATURAL AND APPLIED SCIENCES |
| AGRICULTURAL STRUCTURES AND IRRIGATION (MASTER) (WITH THESIS) | |
| Code | TS556 |
| Name | Extreme Value Analysis in Hydrology |
| Term | 2018-2019 Academic Year |
| Term | Spring |
| Duration (T+A) | 3-0 (T-A) (17 Week) |
| ECTS | 6 ECTS |
| National Credit | 3 National Credit |
| Teaching Language | Türkçe |
| Level | Yüksek Lisans Dersi |
| Type | Normal |
| Mode of study | Yüz Yüze Öğretim |
| Catalog Information Coordinator | Prof. Dr. MAHMUT ÇETİN |
| Course Instructor |
The current term course schedule has not been prepared yet.
|
Course Goal / Objective
The primary objectives of this course are: a) To teach the basic properties of extreme values such as minimum and maximum temperatures in meteorology, droughts and floods in hydrology etc., b) to determine the likely probability distributions and to estimate parameters of extreme values, c) to apply them to hydrological and hydrometeorological variables.
Course Content
Basic concepts and definition of extreme values (EV). Factors affecting EV: natural factors and human activities. EV analysis techniques: a)Descriptive statistics and interpretations, problems encountered and solutions, b) Homogeneity, trend and periodicity issue, c) Frequency analysis: Normal, Log-Normal, Gamma, Pearson Type III, Log-Pearson Type III, Extreme Value Type I (Gumbel), Extreme Value Type III (Weibul) probability distribution functions (pdf) and parameter estimation; d) Goodness of Fits tests of pdf: Khi-square, Kolmogorov-Smirnov and probability line correlation coefficient tests; e) Estimation of EV at unsampled points or on sub-catchments based on at any given risk level. EV Applications to real data such as minimum and maximum temperatures, low flow rates, low or high floods etc.; synthetic data generation and interpretations.
Course Precondition
Resources
Notes
Course Learning Outcomes
| Order | Course Learning Outcomes |
|---|---|
| LO01 | Learns the concept of extreme value. |
| LO02 | Interprets descriptive statistics of extreme value variables. |
| LO03 | Performs frequency analysis analysis on extreme values and interprets technically. |
| LO04 | Knows implementation procedures of goddness-of-fit tests and performs them accordingly. |
| LO05 | Make estimations of misssing extreme values in sub-catchments, and derives sentetic series of extreme values. |
Relation with Program Learning Outcome
| Order | Type | Program Learning Outcomes | Level |
|---|---|---|---|
| PLO01 | Bilgi - Kuramsal, Olgusal | Has the ability to develop and deepen the level of expertise degree qualifications based on the knowledge acquired in the field of agriculture and irrigation structures | |
| PLO02 | Bilgi - Kuramsal, Olgusal | Has the ability to understand the interaction between irrigation and agricultural structures and related disciplines | |
| PLO03 | Bilgi - Kuramsal, Olgusal | Qualified in devising projects in agricultural structures and irrigation systems. | |
| PLO04 | Bilgi - Kuramsal, Olgusal | Conducts land applications,supervises them and assures of development | |
| PLO05 | Bilgi - Kuramsal, Olgusal | Has the ability to support his specilist knowledge with qualitative and quantitative data. Can work in different disciplines. | 3 |
| PLO06 | Bilgi - Kuramsal, Olgusal | Solves problems by establishing cause and effect relationship | 4 |
| PLO07 | Bilgi - Kuramsal, Olgusal | Has the ability to apply theoretical and practical knowledge in the field of agricultural structures and irrigation department | |
| PLO08 | Bilgi - Kuramsal, Olgusal | Able to carry out a study independently on a subject. | 3 |
| PLO09 | Bilgi - Kuramsal, Olgusal | Has the ability to design and apply analytical, modelling and experimental researches, to analyze and interpret complex issues occuring in these processes. | 5 |
| PLO10 | Beceriler - Bilişsel, Uygulamalı | Can access resources on his speciality, makes good use of them and updates his knowledge constantly. | |
| PLO11 | Yetkinlikler - Öğrenme Yetkinliği | Has the ability to use computer software in agricultural structures and irrigation; can use informatics and communications technology at an advanced level. | 5 |
Week Plan
| Week | Topic | Preparation | Methods |
|---|---|---|---|
| 1 | Basic concepts and definition of extreme values (EV) | Studying in detail the relevant chapters in different sources such as books, reports or scientific papers; reviewing and reading articles related to the subject from scientific journals | |
| 2 | Basic concepts and definition of extreme values (EV) | Studying in detail the relevant chapters in different sources such as books, reports or scientific papers; reviewing and reading articles related to the subject from scientific journals | |
| 3 | Factors affecting EV: natural factors and human activities. | Studying in detail the relevant chapters in different sources such as books, reports or scientific papers; reviewing and reading articles related to the subject from scientific journals | |
| 4 | EV analysis techniques: a)Descriptive statistics and interpretations, problems encountered and solutions, | Studying in detail the relevant chapters in different sources such as books, reports or scientific papers; reviewing and reading articles related to the subject from scientific journals | |
| 5 | b) Homogeneity, trend and periodicity issue | Studying in detail the relevant chapters in different sources such as books, reports or scientific papers; reviewing and reading articles related to the subject from scientific journals | |
| 6 | c) Frequency analysis: Normal, Log-Normal, Gamma, Pearson Type III probability distribution functions (pdf) and parameter estimation; | Studying in detail the relevant chapters in different sources such as books, reports or scientific papers; reviewing and reading articles related to the subject from scientific journals | |
| 7 | c) Frequency analysis: Log-Pearson Type III, Extreme Value Type I (Gumbel) probability distribution functions (pdf) and parameter estimation; | Studying in detail the relevant chapters in different sources such as books, reports or scientific papers; reviewing and reading articles related to the subject from scientific journals | |
| 8 | Mid-Term Exam | Studying in detail the relevant chapters in different sources such as books, reports or scientific papers; reviewing and reading articles related to the subject from scientific journals | |
| 9 | c) Frequency analysis: Extreme Value Type III (Weibul) probability distribution function (pdf) and parameter estimation | Studying in detail the relevant chapters in different sources such as books, reports or scientific papers; reviewing and reading articles related to the subject from scientific journals | |
| 10 | d) Goodness of Fits tests of pdf: Khi-square test | Studying in detail the relevant chapters in different sources such as books, reports or scientific papers; reviewing and reading articles related to the subject from scientific journals | |
| 11 | d) Goodness of Fits tests of pdf: Kolmogorov-Smirnov and probability line correlation coefficient tests | Studying in detail the relevant chapters in different sources such as books, reports or scientific papers; reviewing and reading articles related to the subject from scientific journals | |
| 12 | e) Estimation of EV at unsampled points or on sub-catchments based on at any given risk level. | Studying in detail the relevant chapters in different sources such as books, reports or scientific papers; reviewing and reading articles related to the subject from scientific journals | |
| 13 | EV Applications to real data of minimum and maximum temperatures and data generation | Studying in detail the relevant chapters in different sources such as books, reports or scientific papers; reviewing and reading articles related to the subject from scientific journals | |
| 14 | EV Applications to real data such as low flow rates, low or high floods etc. | Studying in detail the relevant chapters in different sources such as books, reports or scientific papers; reviewing and reading articles related to the subject from scientific journals | |
| 15 | EV Applications to real data: Synthetic data generation and interpretations. | Studying in detail the relevant chapters in different sources such as books, reports or scientific papers; reviewing and reading articles related to the subject from scientific journals | |
| 16 | Term Exams | Studying in detail the relevant chapters in different sources such as books, reports or scientific papers; reviewing and reading articles related to the subject from scientific journals | |
| 17 | Term Exams | Studying in detail the relevant chapters in different sources such as books, reports or scientific papers; reviewing and reading articles related to the subject from scientific journals |
Student Workload - ECTS
| Works | Number | Time (Hour) | Workload (Hour) |
|---|---|---|---|
| Course Related Works | |||
| Class Time (Exam weeks are excluded) | 14 | 3 | 42 |
| Out of Class Study (Preliminary Work, Practice) | 14 | 5 | 70 |
| Assesment Related Works | |||
| Homeworks, Projects, Others | 0 | 0 | 0 |
| Mid-term Exams (Written, Oral, etc.) | 1 | 8 | 8 |
| Final Exam | 1 | 30 | 30 |
| Total Workload (Hour) | 150 | ||
| Total Workload / 25 (h) | 6,00 | ||
| ECTS | 6 ECTS | ||