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2025-2026 / RISQ2019-1

Early warning system

Duration

20h Th, 20h Pr

Number of credits

 Advanced Master in Risk and Disaster Management in the Anthropocene Era5 crédits 

Lecturer

Bakary Djaby, Bernard Tychon

Coordinator

Bernard Tychon

Language(s) of instruction

French language

Organisation and examination

Teaching in the first semester, review in January

Schedule

Schedule online

Units courses prerequisite and corequisite

Prerequisite or corequisite units are presented within each program

Learning unit contents

The components of an early warning system (EWS)

10 basic principles for a successful early warning system

Data and information for early warning systems

Models in EWS

Examples in crop disease monitoring, food security and flood forecasting

Presentation of an example of SAP by each student at the end of the course

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Early Warning Information Systems 

Introduction to information systems (IS) for EWS

Evolution of national and international IS

Data access (stations, satellites, DIAS platforms, Copernicus)

Rainfall data and estimation methods

Vegetation data and NDVI indices

Fire data and environmental monitoring

Service development for early warning

Combined systems (IPC, Harmonized Framework, integrated climate approaches)

Case studies and practical work (national, regional, international IS analysis)

Learning outcomes of the learning unit

At the end of the course, the student will be able to make a critical analysis of an early warning system, to define its defaults, its limits and he/she will be able to propose its improvement.

At the end of the section on EWS-IS (Information Systems for Early Warning), the student will be able to:

Define and explain the role of IS in early warning systems.

Identify the components and actors of national, regional and international IS.

Use and compare different data sources (satellites, national databases, international platforms).

Handle and analyze indicators (rainfall, vegetation, fire, socio-economic) and thresholds.

Understand the challenges of interoperability, data access and IS governance.

Develop an integrated analysis (climate, agriculture, food security) using different IS.

Prerequisite knowledge and skills

No prerequisite

For IS-EWS, basic knowledge of climatology, agriculture and GIS recommended but not mandatory.

Planned learning activities and teaching methods

The basics of an EWS will be found from the vision of several videos. Then, this information will be structured to identify the fundamental elements of an EWS. A set of courses will then introduce students to the efficient acquisition of data and information and their association with models adapted to the specific context of EWS.

Students will be invited to present and criticize an example of EWS used in their country.

The course will end by a case study on a food security EWS

 

 

EWS Information Systems 

Lectures on concepts, methodologies and actors.

Practical sessions on data access (Copernicus, DIAS, FEWSNET, FAO-GIEWS, etc.).

Case studies on national IS (e.g., Madagascar, Niger), regional IS (CILSS/Agrhymet, ICPAC), and international IS (FAO, FIRMS, CPC).

Exercises: mapping climate anomalies, drought indicators, IPC integration.

Group work: critical review of an existing IS and improvement proposals.

Mode of delivery (face to face, distance learning, hybrid learning)

Face-to-face teaching

Course materials and recommended or required readings


Further information:

Course notes made up of powerpoints, articles, podcasts, videos, ... will be provided at the start of each course.    

 

  • FAO, 2000, Handbook for establishing a SISAAR.
  • Olivier de Sardan, J.-P. (2021). La revanche des contextes. Karthala.
  • Websites: FEWSNET, AGRHYMET, ICPAC, Copernicus DIAS.
  • Scientific papers on climate indicators, food security and IS.

Written work / report


Further information:

Any session :

- In-person

written exam ( open-ended questions )

- Remote

oral exam

- If evaluation in "hybrid"

preferred in-person


Additional information:

Closed book written exam 

Work placement(s)

Organisational remarks and main changes to the course

Contacts

Bernard Tychon (Bernard.Tychon@uliege.be)

Bakary Djaby (Bakary.Djaby@uliege.be)

Association of one or more MOOCs