G-P03 · TOPIC · multi-hazard-exercisesGCRI dossier · service level R0
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Topic dossier · Disaster Resilience and Recovery

Multi hazard exercises

Exercises test plans, people and systems before a real disaster does. They range from discussion-based tabletop exercises to functional exercises and full-scale drills, and increasingly combine hazards, sectors and borders. This page sets out how exercises are designed, run and evaluated, why lessons are often identified but not learned, and what evidence serves the authorities that commission and run them.

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Layers 3

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NASA GIBS / EOSDIS · ASTER GDEM (METI, NASA) · Blue Marble (NASA) · © OpenStreetMap contributors (ODbL) · Natural Earth

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Drag to move. Ctrl or ⌘ and scroll, pinch or the buttons to zoom; hover for the values under the pointer; reset returns to the region.

For multi hazard exercises, in GCRI's spatial-intelligence reading, the map opens on population density, true-colour imagery and flood water, framed on the Philippines; every other NASA layer, live feed and forecast waits in the layer list.Satellite and model products as NASA publishes them, each with its own date; indicators, not assessments of any place; claim ceiling INTEGRATED.

Data: NASA GIBS · ASTER GDEM · Blue Marble · © OpenStreetMap contributors · Natural Earth · NASA EONET · GDACS · Copernicus Sentinel-2 L2ASources and licences

  • We acknowledge the use of imagery provided by services from NASA's Global Imagery Browse Services (GIBS), part of NASA's Earth Science Data and Information System (ESDIS). Colours redrawn from the published colour map; values averaged into H3 cells where shown (modified). NASA open data
  • We acknowledge the use of imagery provided by services from NASA's Global Imagery Browse Services (GIBS), part of NASA's Earth Science Data and Information System (ESDIS). Colours redrawn from the published colour map; values averaged into H3 cells where shown (modified). NASA open data
  • Center for International Earth Science Information Network (CIESIN), Columbia University. 2018. Gridded Population of the World, Version 4 (GPWv4): Population Density, Revision 11. NASA Socioeconomic Data and Applications Center (SEDAC). Licensed under CC BY 4.0. Colours redrawn from the published colour map; values averaged into H3 cells where shown (modified). CC BY 4.0
  • VIIRS near-real-time products (flood, land surface temperature, snow cover, corrected reflectance), NASA LANCE; imagery via NASA GIBS. Colours redrawn from the published colour map; values averaged into H3 cells where shown (modified). NASA open data
  • NASA Fire Information for Resource Management System (FIRMS), VIIRS 375 m active fire product, NASA LANCE; vector tiles via NASA GIBS. Colours redrawn from the published colour map; values averaged into H3 cells where shown (modified). NASA open data
  • MODIS land products (vegetation indices, gross primary production, land cover), NASA LP DAAC and LANCE; imagery via NASA GIBS. Colours redrawn from the published colour map; values averaged into H3 cells where shown (modified). NASA open data
  • ASTER GDEM is a product of METI and NASA (ASTER Global Digital Elevation Model V003, NASA LP DAAC); imagery via NASA GIBS. Colours redrawn from the published colour map; values averaged into H3 cells where shown (modified). NASA open data
  • Made with Natural Earth. Free vector and raster map data @ naturalearthdata.com. Public domain
  • © OpenStreetMap contributors (ODbL), via NASA GIBS (coastlines, boundaries, roads and place names). Colours redrawn from the published colour map; values averaged into H3 cells where shown (modified). ODbL
  • Blue Marble, NASA Earth Observatory; imagery via NASA GIBS. Colours redrawn from the published colour map; values averaged into H3 cells where shown (modified). NASA open data
  • Context on the globe and flat map: coastlines, boundaries, roads and place names from NASA GIBS reference layers (OpenStreetMap data, ODbL, © OpenStreetMap contributors); Blue Marble imagery as an optional base; 3D terrain and the elevation read-out from the ASTER GDEM elevation colour index (5 m to 200 m classes, exaggerated for legibility). Boundaries are drawn as published and imply no position on any territory.
  • Globe: MapLibre GL JS 6.9.1, BSD-3-Clause, © MapLibre contributors.
  • Live: NASA EONET Events are indicative, not official warnings.
  • Live: GDACS (EC JRC / UN OCHA) Events are indicative, not official warnings.
  • Observed (EO): Copernicus Sentinel-2 L2A (contains modified Copernicus Sentinel data 2026), Microsoft Planetary Computer
  • Optional layers (35 sources in the layer list: live, forecast, observed and context) print their provider credit on the map and here when switched on; forecasts are model output and derived indices are estimates.

Layers and dates

  • Population density, 2020: Population: CIESIN, Columbia University, Gridded Population of the World v4.11 (2018), NASA SEDAC, CC BY 4.0 · static
  • True colour: VIIRS NOAA-20 corrected reflectance, NASA LANCE · 13 Oct 2026
  • Flood water, 3-day composite: VIIRS Global Flood Product, NASA LANCE · 14 Oct 2026
  • Active fires and thermal anomalies, last day: VIIRS NOAA-20 375 m (FIRMS), NASA LANCE FIRMS · 13 Oct 2026
  • Land cover type (IGBP), yearly: MODIS Terra and Aqua land cover (MCD12Q1), NASA LP DAAC · 2024
  • Land surface temperature, day, 8-day composite: VIIRS NOAA-20 Level 3, 8-day, NASA LANCE · 14 Sep 2026

01In brief

The short answer.

Disaster exercises are planned simulations that test plans, people and systems before a real disaster does, from tabletop discussions to functional exercises and full-scale drills. Multi-hazard exercises combine hazards, sectors and borders. Lessons count only when plans, training and resources change afterwards and the changes are tracked.

02Console

Anticipatory action console, in outline.

The working screen behind this subject: its structure, terms and states. Names are placeholders and values illustrative.

Anticipatory action console

Multi hazard exercises · Province C · Monsoon season

Readiness trigger reachedGCRI · Disaster Resilience and Recovery

Protocol

  1. Readinessforecast lead 10 d
  2. Activationlead 3 d
  3. Early actions72 h window
  4. Responseif event
  5. Learningreview

River forecast at trigger gauge

Pre-agreed actions

Cash to at-risk households72 h44Yes
Livestock evacuation48 h19Partial
Shelter kits72 h23Yes
Anticipatory action console: the screen's structure, terms and states for Multi hazard exercises.Placeholder names and illustrative values; a design, not a record or a live system.
03The question

Multi hazard exercises: how the risk develops.

Scenario design and learning. The dossier below sets out how the risk develops, what is measured, where the data come from, how it is modelled and who decides.

Mechanism

The scenario sets the test

An exercise tests only what its scenario stresses. Scenarios built around familiar single hazards leave untested the compound and cascading events that cause the greatest difficulty.

Mechanism

Discussion reveals assumptions

Tabletop exercises surface assumptions about roles, resources and timing that differ between agencies. Many problems appear before any resource moves.

Mechanism

Functional tests reveal limits

Functional and full-scale exercises move information, people and equipment, exposing bottlenecks in communication, logistics and decision-making that discussion misses.

Mechanism

Lessons must change practice

After-action reviews identify improvements, but lessons are learned only when plans, training and resources change. Without tracking, the same findings recur in the next exercise.

04Key terms

Terms used on this page.

Each term as this page uses it. Where a standard-setting body defines the term, the wording follows that body.

TermDefinition
Tabletop exerciseA discussion-based exercise in which participants talk through decisions in response to a scenario.
Full-scale exerciseAn exercise that deploys people and equipment in the field under realistic conditions.
After-action reviewA structured review after an exercise or event that records what happened and what should change.
05Indicators

What is measured, and how well.

Each indicator carries its unit, its cadence, the kind of source behind it and the evidence label a value would carry. No values are shown: a programme supplies them under its own authority.

IndicatorUnitCadenceSource typeLabel
Exercises heldcount by type and hazardannualExercise programme recordsREPORTED
Multi-agency participationcount of organizations taking partper exerciseExercise recordsREPORTED
Exercise objectives metpercent of objectivesper exerciseEvaluation reportsREPORTED
Improvement actions completedpercent of actions closed on timequarterlyAction trackingREPORTED
Repeat findingscount of findings recorded in earlier exercisesper exerciseAfter-action reviewsREPORTED
Exercises with compound or cascading scenariospercent of exercisesannualExercise programme recordsREPORTED
06Canvas

From sources to decisions.

The topic as a computational graph: named sources feed the methods, an evidence review gates the outputs, and the decisions stay with the authorities that hold them.

Pipeline canvas · Multi hazard exercises as a run graphDesign, not a record
Multi hazard exercises: disaster risk finance by layersThe risk profile is split into layers: frequent events from contingency budgets, less frequent from contingent credit, rare from insurance or risk transfer; pre-agreed plans and triggers make funds reach people fast. Design of the process, not a record of a run.

Fig. 02Nodes carry their type, two metric rows and a state; connectors show what feeds what; dashed frames name the owners; the timeline is the cadence. Design of the pipeline, not a record of a run.

07Sources

Where the evidence comes from.

Named public datasets and institutional records, each with its licence class. Sources by agreement are used only under their terms and never republished.

SourceWhat it givesLicence class
UNDRR guidance on scenario-based exercisesDesign guidance for preparedness exercisesPublic, UN terms of use
WHO simulation exercise manualMethods for planning, conducting and evaluating simulation exercisesPublic, WHO terms of use
US Homeland Security Exercise and Evaluation Program (HSEEP)Exercise design and evaluation doctrinePublic domain, US government
EU Civil Protection Mechanism exercise reportsMultinational exercise programmes and lessonsPublic, EU terms of use
INSARAG guidelines and exercisesInternational urban search and rescue standards and exercise practicePublic, UN terms of use
08Decisions

Who decides, and what the evidence serves.

Disaster Resilience and Recovery prepares evidence. The decisions below are taken by the authorities named, under their own rules, and never by the platform.

Who decidesThe questionEvidence this page serves
National disaster management authoritiesWhich scenarios and agencies the exercise programme should coverProgramme records; repeat findings
Exercise sponsors in ministries and agenciesWhich objectives an exercise must testEvaluation frameworks; previous findings
Heads of participating organizationsWhich improvement actions to fund and whenAfter-action reviews; action tracking

Outputs this topic produces

  • Exercise designs for compound and cascading scenarios
  • Evaluation frameworks with objectives and observable criteria
  • Lesson tracking templates linked to plans and training
  • Exercise reports prepared for the commissioning authority
09Core questions

What experts ask.

Exercise designers and evaluators work on a demanding set of questions.

  • What should an exercise test: plans, people, systems, decisions or coordination?
  • How realistic must a scenario be, and how can it include cascading and compound effects?
  • Who should take part, including operators, local governments and communities?
  • How are performance and lessons recorded objectively?
  • How are lessons turned into changed plans, and how is that change verified?
10Mechanisms and drivers

Why exercises reveal what plans hide.

Plans describe intended behaviour; exercises show actual behaviour. Discussion-based exercises walk participants through a scenario and expose gaps in understanding and authority. Functional and full-scale exercises test systems and people under time pressure. Multi-hazard scenarios, such as a flood that cuts power during a heatwave, reveal dependencies between agencies and infrastructure that are invisible when each plans alone.

The value of an exercise lies in what changes afterwards. Lessons identified are not lessons learned until plans, training or resources change and the change is tested again. Exercise programmes that focus on demonstration rather than discovery, or that avoid exposing failures, produce reassurance without improvement.

11Methods and data

How the evidence is built, and where it stops.

  1. 01

    Scenario design

    Building plausible, challenging scenarios with decision analysis and hazard science from Earth and geophysical science and hydrology. Scenarios can be anchored too closely on past events.

  2. 02

    Observation and evaluation

    Trained evaluators record decisions and timing against objectives. Observer bias and participant awareness affect results.

  3. 03

    After-action review

    Structured debriefs that identify causes, not blame. Candour depends on a safe environment.

  4. 04

    Improvement tracking

    Recording lessons and verifying implementation. Tracking often lapses between exercises.

12Methods

How it is studied, and what the methods cannot say.

  1. Decision analysis under uncertaintyCost-benefit of risk reduction · Acting on forecasts · Recovery prioritisationApplied here
  2. Social and behavioural scienceWarning response surveys · Participatory risk assessment · Social vulnerability analysisApplied here
  3. Forecasting and time-series analysisTrigger verification · Flood forecast lead time · Seasonal outlooks for drought preparednessApplied here
  4. Earth and geophysical scienceEarthquake scenarios for exercises · Landslide hazard in recovery planningApplied here
13Questions

Questions and answers.

What is a tabletop exercise?
A discussion-based exercise in which participants talk through their roles and decisions in response to a scenario, without moving resources.
What is the difference between a functional and a full-scale exercise?
A functional exercise tests specific functions such as coordination centres in a simulated environment. A full-scale exercise deploys people and equipment in the field.
Why do the same lessons recur?
Because identifying a lesson is not the same as learning it. Without owners, resources and tracking, improvement actions are not completed before the next exercise.
What is the difference between a tabletop and a full-scale exercise?
A tabletop exercise is discussion-based and tests understanding and decisions. A full-scale exercise mobilises people and equipment in real time to test operations.
Will the platform run exercises?
Exercises are designed to be part of the Nexus Universe programme governed by GRF, with an anticipatory action exercise planned for this platform. Each opens only with its own record, scope and participants.
Are exercise results published?
Lessons are designed to be published in anonymised and aggregated form where participants agree. Sensitive operational detail is not published.
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