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C3. STATISTICS FOR WATER ENGINEERING
(KUL-code: I742 (Th); I743 (Pr))
Lecturer: WILLEMS P.
ECTS-credit: 5 pts
Contact hours: 30 hrs. of theory / 30 hrs. of practical
Prerequisites: Basic knowledge of calculus
Time and place: 1st semester, 13 sessions of 3 hours each, K.U.Leuven
Course syllabus: Lecture notes + selection of texts from different handbooks
Evaluation: Oral exam with prepared exercises, additional information on the exam will be provided
to the students.
Comparable handbook: Shahin, M., H.J.L. Van Oorschot and S.J. Lange, 1993. Statistical analysis in water
resources engineering. Applied Hydrology Monographs 1. A.A. Balkema, Rotterdam,
394 p.
Benjamin, J.R. and C.A. Cornell, 1987. Probability, statistics, and decision for civil
engineers. McGraw-Hill Book Company, New York, 652 p.
Learning objectives:
The learning objective of the course is to give the students a fundamental knowledge and a pratical
understanding of the common techniques for data processing in hydrology and water management. This
knowledge and understanding must allow the students to select and apply most appropriate techniques to
summarize and organize data. It also allows them to have an insight in the limitations of data collection, and the
corresponding consequences for the water management. More specifically, the consequences to the
development and the calibration of mathematical models and other predictive tools are discussed. Also the
consequences to the evaluation, the exploitation and the management of the water systems are addressed. The
latter water management and research tasks may be based on mathematical modelling or not. The understanding
of the data limitations and their consequences are also useful in setting up most appropriate data collection
programs for specific water management and planning problems. Based on discussions of the different
uncertainty sources, also a fundamental insight is given in the general process of mathematical modelling. By
using examples from specific water fields (surface hydrology, hydraulics, wastewater treatment, …) in the
lectures and the pratical sessions, this course has an important interaction with the other courses.
Course description:
An overview is given of the important concepts of probability and statistics as they are used in hydrology and
water management. After an introduction of the basic terminology, an overview is given of techniques for data
handling and data processing. These techniques can be classified into two groups: descriptive statistics and
inferential statistics. In descriptive statistics, most common techniques are considered for summarizing and
organizing the data in a sample (a dataset). These consist of both numerical and graphical techniques. In
inferential statistics, techniques are studied to draw conclusions about the physical reality (the full population),
based on a limited amount of data available (a sample). Regarding the latter techniques, also the notion of
mathematical modelling is explained together with the different sources of uncertainty involved. In this way,
the students are given a basic understanding of the limitations of mathematical modelling and their
consequences to water management and planning decisions.
The course uses examples in theory as well as for the exercises. These examples are mainly hydrological and
water quality data that are typically available for surface waters.
The following topics are addressed in the course, in chronological order:
1. Initial definitions:
statistics, probability, hydrological variables, -series, -processes and -data;
population vs. sample, errors in data
2. Descriptive statistics:
- Presentation of data:
7 / Course syllabi