78594 - Flood and Drought Risk Management

Course Unit Page


This teaching activity contributes to the achievement of the Sustainable Development Goals of the UN 2030 Agenda.

Clean water and sanitation Sustainable cities

Academic Year 2018/2019

Learning outcomes

At the end of the course students have an understanding of the factors causing and aggravating both river floods and drought, and a knowledge of the options and measures available for reducing and managing such risks. In particular, the course will provide advanced theoretical bases, knowledge of the tools and applied skills for (i) the assessment of flood and drought risk, in terms of hazard and vulnerability and (ii) the appraisal and design of measures for mitigating and managing such risks (such as structures for flood protection/mitigation, flood and drought policies/plans/mapping; forecasting and managing flood and drought emergencies).

Course contents

Requirements/Prior knowledge

Basic knowledge in open-channel hydraulics, hydrology and statistics is needed.

Course Contents/Syllabus

- Acquisition and processing of hydro-meteorological data to support flood and drought modelling: rainfall fields estimates and streamflow measurements, open databases, data analysis and validation.

- Remote sensing of water-related variables (satellites and radar)

- GIS algorithms for automatic watershed delineation and characterization.
- Hands-on experiments on GIS hydrological tools (QGIS & GRASS GIS)

- Approaches and tools for predicting hydrological design variables (e.g. design floods, low-flow indices, design rainstorms, etc.) in gauged and ungauged catchments. An introduction to Regional Flood Frequency Analysis.

- Hands-on experiments on at-site flood frequency estimation and associated uncertainty (R programming environment).

- Drought analysis: introduction to droughts (definitions , characteristics). Climatological and human-induced causes. Drought impacts: social, environmental, economic aspects.

- Drought monitoring and warning, indexes and models, evaluation of meteorological droughts, evaluation of hydrological droughts.

- Methods for the assessment of flood hazard: rainfall-runoff modelling, river flow propagation modelling, flood mapping.

- Structural and non-structural measures for flood defense: structures for flood peak reduction and for hydraulic conveyance increase; floodplain management; individual protection measures, flood forecasting and warning, managing flood emergencies.

- Flood risk analysis: flood impacts, damage evaluation, vulnerability assessment.


There is not a required textbook for the course. Lecture slides, as well as review articles and research papers that are not open access, will be made available in the collection AMS Campus - AlmaDL University of Bologna for registered students.

In particular, additional reading material includes:

-WMO (2008): Guide to Hydrological Practices. WMO No. 168. World Meteorological Organization, Geneva.

- WMO(2008): Manual on Low-flow Estimation and Prediction, WMO No, 1029. World Meteorological Organization, Geneva.

- WMO (2011): Manual on flood forecasting and warning, WMO No. 1072. World Meteorological Organization, Geneva.

- “HYDROLOGICAL DROUGHT – Processes and Estimation Methods for Streamflow and Groundwater”
edited by Lena M. Tallaksen and Henny A.J. van Lanen, Published by Elsevier (2004), now freely available at:

-Grimaldi, S., S.C. Kao, A. Castellarin, S.M. Papalexiou, A. Viglione, F. Laio, H. Aksoy, A. Gedikli (2011): Statistical Hydrology. In Treatise on Water Science. (479 – 517). ISBN: 978-0-444-53199-5. OXFORD: Elsevier (UK).

Teaching methods

Frontal lectures.

Seminars with experts and technical visits.

In-class exercises and home assignments, including computer programming and use of specific software(e.g. Matlab and cross-platform Free and Open-Source Software -FOSS).

Assessment methods

Student achievement is assessed through an oral exam where the student presents a report of the in-class and home assignments and is asked to reply to 3-4 questions focusing on the topics covered during the lectures (students should attend all lectures or obtain the notes from their colleagues when absent). Students may be asked to solve a short exercise.

To pass the exam, the students are required to master the main theoretical principles and methodologies taught during the lectures. The laude is awarded to students who, in addition to master all the covered topics and to present top-grade assignments, show to have integrated their knowledge with personal in-depth analysis.

Teaching tools

Handouts on the topics covered in the course, lecture slides, assignments and exercises and their draft solutions in R (The R Project [http://www.r-project.org/] for Statistical Computing) or Matlab scripts are published in the collection "Insegnamenti OnLine" (iol.unibo.it) University of Bologna for registered students.

Office hours

See the website of Elena Toth

See the website of Attilio Castellarin