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CODE 97232
ACADEMIC YEAR 2026/2027
CREDITS
SCIENTIFIC DISCIPLINARY SECTOR ICAR/02
TEACHING LOCATION
  • GENOVA
SEMESTER 1° Semester
MODULES Questo insegnamento è un modulo di:

AIMS AND CONTENT

LEARNING OUTCOMES

Fornire conoscenze avanzate nell’ambito della modellazione dei processi idrologici e dell’idrologia statistica, con un particolare focus sugli eventi estremi (pioggia e portata), modellazione distribuita e semi-distribuita dei processi di trasformazione afflussi-deflussi.

AIMS AND LEARNING OUTCOMES

The module aims to provide students with a solid understanding of the statistical and probabilistic methods commonly used in hydrology, as well as the physical processes governing the generation and routing of streamflows.

Students will be able to:

  • Understand the principles of probability and statistical inference applied to hydrology.
  • Describe the main hydrological processes controlling rainfall-runoff transformation and river flow generation.
  • Understand local and regional approaches for the frequency analysis of extreme hydrological events.

 

  • Analyse hydrological datasets using appropriate statistical methods.
  • Estimate design rainfall and flood quantiles for engineering applications.
  • Evaluate flood peak discharges and flood volumes using suitable hydrological procedures.
  • Critically interpret the results of hydrological frequency analyses and discuss the underlying assumptions.

TEACHING METHODS

The module consists of 50 hours of teaching, organised as follows:

  • 35 hours of lectures devoted to theoretical concepts and methodologies.
  • 15 hours of practical sessions focused on the statistical analysis of hydrological variables (rainfall and streamflow records).

Students will perform frequency analyses of hydrological datasets provided during the course, applying statistical inference techniques to estimate rainfall and flood quantiles. The results of these activities will form the basis for the final assessment and oral examination.

Teaching activities include:

  • Lectures covering theoretical aspects of hydrological statistics, frequency analysis, and related hydrological processes.
  • Guided practical exercises using real datasets to investigate the influence of data characteristics on statistical modelling and the selection of appropriate probability distributions.

Working students are advised to contact the teacher at the beginning of the course to agree on teaching and exam methods which, in compliance with the teaching objectives, take into account individual ways of learning.

Students with a certified learning disability (DSA), a disability, or other special educational needs are invited to contact the instructor at the beginning of the lessons to discuss teaching and examination arrangements that, while respecting the learning objectives of the course, take individual learning needs into account and provide appropriate accommodations.
Please also note that requests for exam accommodations or exemptions must be submitted using the form available at this link https://modulionline.unige.it/richiesta-adattamenti#no-back , to the teaching professor, the SCUOLA contact person (federico.scarpa@unige.it), and the relevant office (inclusione.studenti@info.unige.it) at least seven working days before the examination, in accordance with the guidelines available at this link https://unige.it/disabilita-dsa/richiesta-servizi

SYLLABUS/CONTENT

The module covers the following topics:

  • Fundamentals of probability theory and statistical inference.
  • Statistical methods for the analysis of hydrological variables.
  • Frequency analysis of extreme rainfall and flood events at the local scale.
  • Regional approaches for the estimation of rainfall and flood quantiles.
  • Procedures for flood volume estimation.
  • Interpretation and application of hydrological statistical models for engineering design.

RECOMMENDED READING/BIBLIOGRAPHY

Lecture slides, supplementary teaching materials, datasets, and supporting documentation for practical activities will be made available through AulaWeb. These materials are intended as support to classroom teaching and do not replace attendance and independent study.

Reference textbooks

  • Chow, V.T., Maidment, D.R., Mays, L.W. (1988). Applied Hydrology. McGraw-Hill, New York.
  • Kottegoda, N.T., Rosso, R. (1997). Statistics, Probability, and Reliability for Civil and Environmental Engineers. McGraw-Hill, New York.

Additional references may be suggested during lessons according to specific topics and student interests.

TEACHERS AND EXAM BOARD

LESSONS

Class schedule

The timetable for this course is available here: Portale EasyAcademy

EXAMS

EXAM DESCRIPTION

Assessment consists of an individual hydrological analysis project followed by an oral examination.

Admission to the oral examination is conditional upon the satisfactory completion of the individual statistical analysis assigned during the course. Each student will analyse a specific hydrological dataset and develop an appropriate probabilistic model for the estimation of rainfall or flood quantiles.

During the oral examination, students will discuss the adopted methodology, justify the modelling choices and assumptions, and critically interpret the obtained results.

ASSESSMENT METHODS

The assessment is designed to evaluate both theoretical understanding and practical skills acquired during the course.

Students will be assessed on their ability to:

  • Apply statistical methods to hydrological datasets.
  • Perform frequency analysis of extreme rainfall and flood events.
  • Select and justify appropriate probabilistic models.
  • Interpret and critically discuss the results obtained.
  • Clearly and effectively communicate technical concepts and methodologies.

The final grade will be based on:

  • Quality and correctness of the individual hydrological statistical analysis.
  • Understanding of the adopted methodologies.
  • Ability to critically evaluate assumptions and results.
  • Clarity, accuracy, and completeness of the oral discussion.

FURTHER INFORMATION

For any additional information not included in the unit description, students are encouraged to contact the professor.