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Course Description Course Name : Extreme Value Analysis in Hydrology Course Code : TS-556 Course Type : Optional Level of Course : Second Cycle Year of Study : 1 Course Semester : Spring (16 Weeks) ECTS : 6 Name of Lecturer(s) : Prof.Dr. MAHMUT ÇETİN Learning Outcomes of the Course : 1. Lerans the concept of extreme value. 2. Knows the factors affecting extreme values. 3. Gains the ability how to model any extreme vararible, and performs modelling. 4. Makes risk assesment of any exteme variable, and applies in practice. Mode of Delivery : Face-to-Face Prerequisites and Co-Prerequisites : None Recommended Optional Programme Components : None Aim(s) of Course : The aim of this course is mainly to teach the analysis techniques of extreme values such as minimum and maximum temperatures, floods ect. in hydrology, and to provide students with parameter estimation techniques for extrrem value distributions used commonly in hydrological sciences. Course Contents : 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. Language of Instruction : Turkish Work Place : Class   Course Outline /Schedule (Weekly) Planned Learning Activities Week Subject Student's Preliminary Work Learning Activities and Teaching Methods 1 Basic concepts and definition of extreme values (EV). Books and other study materials Self-study plus lecturing 2 Factors affecting EV: natural factors and human activities. Books and other study materials Self-study plus lecturing 3 EV analysis techniques: Introduction Books and other study materials Self-study plus lecturing 4 EV analysis techniques: a)Descriptive statistics and interpretations, problems encountered and solutions, Books and other study materials Self-study plus lecturing 5 EV analysis techniques: b) Homogeneity, trend and periodicity issue, Books and other study materials Self-study plus lecturing 6 EV analysis techniques: 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 Books and other study materials Self-study plus lecturing 7 EV analysis techniques: 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 (CONT.) Books and other study materials Self-study plus lecturing 8 EV analysis techniques: 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 (CONT.) Books and other study materials Self-study plus lecturing 9 EV analysis techniques: 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 (CONT.) Books and other study materials Self-study plus lecturing 10 Mid-term exam Books and other study materials Take-home exam 11 EV analysis techniques: d) "Goodness of Fits" tests of pdf: Khi-square test, Books and other study materials Self-study plus lecturing 12 EV analysis techniques: e) Kolmogorov-Smirnov test Books and other study materials Self-study plus lecturing 13 EV analysis techniques: f) probability line correlation coefficient test Books and other study materials Self-study plus lecturing 14 EV analysis techniques: e) Estimation of EV at unsampled points or on sub-catchments based on at any given risk level. Books and other study materials Self-study plus lecturing 15 EV Applications to real data such as minimum and maximum temperatures, low flow rates, low or high floods etc.; synthetic data generation and interpretations. Books and other study materials Self-study plus lecturing 16/17 Final exam Books and other study materials Take-home exam   Required Course Resources Resource Type Resource Name Recommended Course Material(s)  McMahon, T. A. and Arenas, A. D. (Editors), 1982. Methods of computation of low stream flow. UNESCO, Paris, France, 95 pp.  Kottegoda, N. T., 1980. Stochastic water resources technology. Department of Civil Engineering, University of Birmingham, The McMillan Press Ltd., London. Required Course Material(s)  Other text books, and published papers in the esteemed national and international journals.   Assessment Methods and Assessment Criteria Semester/Year Assessments Number Contribution Percentage     Mid-term Exams (Written, Oral, etc.) 1 70     Homeworks/Projects/Others 4 30 Total 100 Rate of Semester/Year Assessments to Success 40   Final Assessments 100 Rate of Final Assessments to Success 60 Total 100   Contribution of the Course to Key Learning Outcomes # Key Learning Outcome Contribution* 1 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 0 2 Has the ability to understand the interaction between irrigation and agricultural structures and related disciplines 1 3 Qualified in devising projects in agricultural structures and irrigation systems. 3 4 Conducts land applications,supervises them and assures of development 2 5 Has the ability to apply theoretical and practical knowledge in the field of agricultural structures and irrigation department 5 6 Has the ability to support his specilist knowledge with qualitative and quantitative data. Can work in different disciplines. 5 7 Solves problems by establishing cause and effect relationship 4 8 Able to carry out a study independently on a subject. 4 9 Has the ability to design and apply analytical, modelling and experimental researches, to analyze and interpret complex issues occuring in these processes. 3 10 Can access resources on his speciality, makes good use of them and updates his knowledge constantly. 5 11 Has the ability to use computer software in agricultural structures and irrigation; can use informatics and communications technology at an advanced level. 3 * Contribution levels are between 0 (not) and 5 (maximum).   Student Workload - ECTS Works Number Time (Hour) Total Workload (Hour) Course Related Works     Class Time (Exam weeks are excluded) 14 3 42     Out of Class Study (Preliminary Work, Practice) 14 2 28 Assesment Related Works     Homeworks, Projects, Others 4 12 48     Mid-term Exams (Written, Oral, etc.) 1 10 10     Final Exam 1 10 10 Total Workload: 138 Total Workload / 25 (h): 5.52 ECTS Credit: 6