GCRI · Systems Science and Modelling

Systems engineering for models

Systems engineering is the method this platform stewards for the network. It brings requirements, architecture, interfaces, verification and life cycle management to models and coupled systems, so that complex modelling efforts are defined, built and tested deliberately.

01Register

Systems engineering for models on the record.

Method recordSTEM method
  1. MethodSystems engineering
  2. StewardSystems Science and Modelling
  3. Applied inSystems Science and Modelling
  4. Canonical pageSTEM Commons
02Application

What systems engineering does here.

Systems engineering is an interdisciplinary approach to designing and managing complex systems over their life cycle. It focuses on requirements, interfaces and interactions so that the whole performs as intended. In methods and modelling, risk management and systemic risk and research and evidence, systems engineering exposes interfaces where failures propagate between components and organisations. It supports designing interconnected infrastructure with explicit dependency management. The canonical description is on the STEM Commons.

Requirements for decision models

The questions a model must answer, the accuracy needed and the conditions it must cover are written as requirements before modelling begins, then traced to tests.

Interface control for coupled models

Variables, units, time steps and owners at each model interface are documented, so coupling errors can be found and fixed.

Model life cycle management

Models are managed from design through use to retirement, with versions, reviews and change control recorded.

03Geography

Hazards and exposure in North America.

Population density, flood water and night lights over North America, from NASA GIBS. Each layer carries its own date.

The interactive map needs JavaScript; the layer list and sources are below.

Layers 3

Hazards and exposure, for this page

About this layer
Evidence
Estimated
Source
Gridded Population of the World v4.11 (NASA SEDAC (CIESIN, Columbia University))
Provider
NASA SEDAC (CIESIN, Columbia University)
Licence
CC BY 4.0
Vintage
null; Census-based estimate, static (2020)
Resolution
about 1 km grid
Uncertainty
Census-based estimate of people per square kilometre in 2020, shown as exposure context; not a count of people affected by any hazard.
Reached through
gibs.earthdata.nasa.gov, only after you allow the live map
About this layer
Evidence
Observed (clouds leave gaps)
Source
VIIRS Global Flood Product (NASA LANCE)
Provider
NASA LANCE
Licence
NASA open data
Vintage
daily; Satellite detection; clouds leave gaps
Newest at build
2026-10-14
Resolution
about 250 m grid
Uncertainty
Satellite detection; clouds leave gaps. Satellite or model raster as the provider publishes it. Clouds, swath gaps and retrieval error leave gaps and noise; values are indicators, not measurements at a place.
Reached through
gibs.earthdata.nasa.gov, only after you allow the live map
About this layer
Evidence
Observed
Source
VIIRS Black Marble (VNP46A2) (NASA LAADS DAAC)
Provider
NASA LAADS DAAC
Licence
NASA open data
Vintage
daily; Satellite radiance, corrected for moonlight and atmosphere
Newest at build
2026-10-12
Resolution
about 500 m grid
Uncertainty
Satellite night-time radiance for the date shown; lights are a proxy for electricity use and outages, not a measurement of supply or access.
Reached through
gibs.earthdata.nasa.gov, only after you allow the live map
About this layer
Evidence
Observed
Source
VIIRS NOAA-20 corrected reflectance (NASA LANCE)
Provider
NASA LANCE
Licence
NASA open data
Vintage
daily; Satellite image
Newest at build
2026-10-14
Resolution
about 250 m grid
Uncertainty
Satellite image. Satellite or model raster as the provider publishes it. Clouds, swath gaps and retrieval error leave gaps and noise; values are indicators, not measurements at a place.
Reached through
gibs.earthdata.nasa.gov, only after you allow the live map
About this layer
Evidence
Observed (clouds and overpass timing leave gaps)
Source
VIIRS NOAA-20 375 m (FIRMS) (NASA LANCE FIRMS)
Provider
NASA LANCE FIRMS
Licence
NASA open data
Vintage
daily; Satellite detection; clouds and overpass timing leave gaps
Newest at build
2026-10-13
Resolution
about 500 m grid
Uncertainty
Satellite hot-spot detections for the day shown, including gas flares and industrial heat; not a confirmed fire, an incident report or a warning.
Reached through
gibs.earthdata.nasa.gov, only after you allow the live map
About this layer
Evidence
Modelled (latest year GIBS publishes)
Source
MODIS Terra and Aqua land cover (MCD12Q1) (NASA LP DAAC)
Provider
NASA LP DAAC
Licence
NASA open data
Vintage
yearly; Satellite classification; latest year GIBS publishes
Newest at build
2024-01-01
Resolution
about 500 m grid
Uncertainty
Satellite land cover classes for the year shown, including croplands; a classification with known errors, not a farm register.
Reached through
gibs.earthdata.nasa.gov, only after you allow the live map

Latest available

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

Loading the latest NASA imagery.

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.

Hazards and exposure, framed on North America.Satellite and model products as NASA publishes them, each with its own date. They are indicators, not assessments of any place.

Data: NASA GIBS · ASTER GDEM · Blue Marble · © OpenStreetMap contributors · Natural Earth · NASA EONET · U.S. Geological Survey · NASA JPL OPERA DIST-ALERTSources 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 hexagonal 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 hexagonal 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 hexagonal cells where shown (modified). doi:10.7927/H49C6VHW. 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 hexagonal cells where shown (modified). NASA open data
  • VIIRS Black Marble night-time lights, NASA Goddard Space Flight Center; distributed by the NASA Level-1 and Atmosphere Archive and Distribution System (LAADS DAAC); imagery via NASA GIBS. Colours redrawn from the published colour map; values averaged into hexagonal 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 hexagonal 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 hexagonal 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 hexagonal cells where shown (modified). Cite as: NASA/METI/AIST/Japan Spacesystems and U.S./Japan ASTER Science Team (2019). ASTER Global Digital Elevation Model V003. doi:10.5067/ASTER/ASTGTM.003. 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 hexagonal cells where shown (modified). ODbL
  • Blue Marble, NASA Earth Observatory; imagery via NASA GIBS. Colours redrawn from the published colour map; values averaged into hexagonal 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.
  • Live events: NASA Earth Observatory Natural Event Tracker (EONET); events are indicative and keep their original source links.
  • Live: NASA EONET Events are indicative, not authority warnings.
  • Live: U.S. Geological Survey Events are indicative, not authority warnings.
  • Observed (EO): NASA JPL OPERA DIST-ALERT (contains modified Copernicus Sentinel data 2026). 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).
  • NASA GIBS: 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).
  • River discharge forecast, 30 days with range (GloFAS via Open-Meteo): Contains modified Copernicus Emergency Management Service information 2026; not a flood warning.
  • Weather data by Open-Meteo.com (https://open-meteo.com/), licensed under CC BY 4.0 (https://creativecommons.org/licenses/by/4.0/).
  • Optional layers (11 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
  • Flood water, 3-day composite: VIIRS Global Flood Product, NASA LANCE · 14 Oct 2026
  • Night-time lights, daily: VIIRS Black Marble (VNP46A2), NASA LAADS DAAC · 12 Oct 2026
  • True colour: VIIRS NOAA-20 corrected reflectance, NASA LANCE · 13 Oct 2026
  • Active fires and thermal anomalies: 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

04Data

What the method consumes.

Datasets and records used by systems engineering on this platform, with the role each plays and the label its values carry. Sources are listed in the source register.

DataRoleLabel
Requirements documentsPurpose and accuracyDECLARED
Interface control documentsCoupling specificationsDECLARED
Test and review recordsVerificationOBSERVED
05Twin and cascade simulator

Model systems engineering for models as a system. Run the cascade.

Assembled from the Nexus Standards area profile Compound and cascading hazard standards: the hazards it names, the systems and sectors that carry the loss, the controls that dampen it and the data that observe it. Choose the components, pick an initiating hazard and step through the cascade. The Map view places the run on an example geography with open data. Every coupling weight is a stated assumption you can change. A teaching model, not a forecast, an assessment or a certification. To model a place of your own choosing, open the full System Builder.

Hazards

Controls

  • NS-0 Constitution and principles
  • NS-3 Risk record UNIs (grammar, legacy crosswalk, allocation authority)
  • NS-9 Contextual UNIs (deployments, instances, programme instances)
  • NS-11 Verification and monitoring (evidence, attestations, zero-trust conformance observation)
  • NRS-H61 Hazard family: Cascading failure (NHS-1 sys.cascade)
  • NRS-H62 Hazard family: Compound and multi-hazard events (NHS-1 sys.compound)
  • NRS-H60 Hazard family: Supply-chain and flow disruption (NHS-1 sys.supply-chain)
  • NRS-H94 Hazard family: Systemic cyber events (NHS-1 cyber.systemic-cyber)
  • NRS-H107 Hazard family: Digital infrastructure concentration and monoculture (NHS-1 tech.digital-concentration)
  • NRS-H7 Hazard family: Large-scale circulation anomalies (NHS-1 atmo.climate-mode)

Observation

  • Copernicus EMS rapid mapping activations (listed for reference)
  • OpenStreetMap planet and replication (listed for reference)
  • ERA5 reanalysis (Copernicus Climate Data Store) (listed for reference)
  • Direct economic loss attributed to disasters in relation to global GDP
  • Number of disruptions to basic services attributed to disasters

Example geography

  • Bangladesh: 134 hexagonal cells
  • Night lights tonight, outages (VIIRS Day/Night Band), NASA GIBS
  • Carbon monoxide, smoke transport (AIRS), NASA GIBS
  • Vegetation disturbance alerts, 30 m (OPERA DIST-ALERT), NASA GIBS
06Validation

How results are checked.

Each requirement is traced to verification evidence from analysis, inspection, demonstration or test. Independent reviews check completeness at life cycle gates.

CheckHow it is done
Requirements traceabilityEach requirement is traced to a verification activity
Interface reviewInterface specifications are reviewed by both model owners
Change impact analysisChanges are assessed for effects on validated results

Emergent behaviour in open or socio-technical systems may not be captured by requirements. Rigid processes can slow adaptation to change.

07Methods and evidence

How systems engineering for models is modelled, measured and tested.

The model, its assumptions, its data and its uncertainty, in the form a scientist or engineer would check. Structures follow published methods. The values drawn are illustrative, not findings.

Model, equations and assumptions

The model structure used for systems engineering for models, the assumptions it makes and how each is tested.

Risk of element iRi = f(Hi, Ei, Vi, Ci)hazard, exposure, vulnerability and coping capacity
Expected annual lossEAL = ∑k pk · Lkover events k with annual probability pk
Coupled systemsxt+1 = A xt + B ut + εtA carries the couplings, u the shock, ε the error
AssumptionWhy it is madeHow it is tested
Hazard and exposure are independent within an eventKeeps the loss integral tractableCompare with a copula fit on joint records
Couplings are linear near the operating pointLets shocks propagate through APerturb beyond the linear range and compare
Vulnerability curves transfer between placesLocal curves are rarely availableValidate against observed losses where they exist
Inputs
versioned datasets with provenance
Outputs
distributions, never single numbers
Code
released with the model card and tests
Reproduction
same data, code, environment and seed
Standard risk and state-space formulations; the assumptions listed are typical of the method, stated for review, not results.
FAIR guiding principles · GO FAIR and FORCE11W3C PROV · World Wide Web ConsortiumGuidance on consistent treatment of uncertainties · IPCCCEOS Analysis Ready Data · Committee on Earth Observation Satellites
09Process

How the process runs.

Process

Systems engineering for models: Cascade across systems

An initial hazard can trigger later risks and events; this illustration draws one cascade across systems such as energy, water, ICT, health and transport.

  1. 01 Hazard

    1. 01Initiating hazardDataset · Model stewardCascading risk is the risk that hazard events trigger later risks and events, through chains of interrelated hazards or impacts.
  2. 02 First-order systems

    1. 02Example system: energyModel · System operatorAn example of a system a hazard can hit first. What depends on it is set by a dependency survey.
    2. 03Example system: waterModel · System operatorA second example of a system a hazard can hit first. Its links to other systems are shown as examples only.
  3. 03 Second-order systems

    1. 04Example system: ICTModel · System operatorAn example of a system that may depend on others, for example on backup power. Survey data set the real dependencies.
    2. 05Example system: health servicesModel · System operatorAn example of a system that may depend on water, power and data. Survey data set the real dependencies.
    3. 06Example system: transportModel · System operatorAn example of a system that may depend on ICT, fuel and logistics. Survey data set the real dependencies.
  4. 04 Limiting the cascade

    1. 07Buffers and redundancyStep · Model stewardBuffers, redundancy and restoration can limit how far an impact spreads. The OECD report moves from single assets to system resilience.
    2. 08Restoration prioritiesDecision · Model stewardThe responsible party sets which services are restored first, under its own rules.

Outline of an external standard or method, from its public sources. It describes what the framework says, not a record of any run. It does not show that Nexus or any partner performs, certifies or approves a step. A gate is a step of the method, never a Nexus approval. The dependencies are examples. A dependency survey for the place sets them.

10Stewardship

Who maintains the method.

Systems Science and Modelling stewards systems engineering for the Consortium and reviews how it is applied across platforms.

11Questions

Questions and answers.

What are the limits of systems engineering in this field?
Emergent behaviour in open or socio-technical systems may not be captured by requirements. Rigid processes can slow adaptation to change.
How are results checked?
Each requirement is traced to verification evidence from analysis, inspection, demonstration or test. Independent reviews check completeness at life cycle gates.
Are the values on this page real?
The data names, roles and checks are real descriptions of practice. The canvas shows a design of the method’s use, not a run; no result is reported here.
Where else is this method applied?
The canonical method page lists every platform that applies it.
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Editors and the expert reviewers named on each article decide what we publish. Funders and partners do not review or approve articles before publication.

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