Reports · GCRI · Established
Methods and modelling · Risk management and systemic risk · Research and evidence
Systems Science and Modelling in Reports
The shared mathematical and engineering foundation for every Nexus field: how coupled systems are modelled, tested, validated and explained, so that a flood model, a grid model and a contagion model can be compared and combined honestly. This page shows the series it feeds, the evidence behind it and how to contribute.
- Series
- 2
- Systems
- 4
- Methods
- 8
01In brief
What this area brings to the editions.
The shared mathematical and engineering foundation for every Nexus field: how coupled systems are modelled, tested, validated and explained, so that a flood model, a grid model and a contagion model can be compared and combined honestly.
02Field
Systems Science and Modelling on the map.
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
- static product; 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
Keyboard, with the map focused
Hold Ctrl or ⌘ and scroll to zoom
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-ALERT
Sources 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). 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 H3 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 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). 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 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 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
03In the editions
9 findings of the drafted editions that bear on Systems Science and Modelling.
Drawn from the Baseline Edition 2026 drafts through the systems this area reads. Each opens at its anchor in its edition, with its numbered sources.
- AREUnited Arab EmiratesThe leading compound pathway for 2027 testing is a humid summer heat peak that loads power, desalination and outdoor-work protection together.EXPERT INPUT · COUNTRY-ARE-SYS-012
- ARGArgentinaThe leading compound pathway for 2027 testing is a multi-year drought with low Paraná flows that cuts harvests, river exports, hydropower and public revenue together.EXPERT INPUT · COUNTRY-ARG-SYS-012
- AUAfrican UnionThe leading compound pathway for 2027 testing is a drought year across several member states, met by high food prices and a disease outbreak.EXPERT INPUT · COUNTRY-AU-SYS-012
- AUSAustraliaThe leading compound pathway for 2027 testing is a hot, dry summer in which fire, smoke, heat and grid stress coincide in the populated south-east.EXPERT INPUT · COUNTRY-AUS-SYS-012
- BRABrazilThe leading compound pathway for 2027 testing is a strong El Niño drought that lowers Amazon rivers and hydropower while fire and thermal dispatch rise together.EXPERT INPUT · COUNTRY-BRA-SYS-012
- CHESwitzerlandThe leading compound pathway for 2027 testing is a dry year with low reservoirs and low river flows that cuts hydropower and raises winter import dependence at the same time as farm and forest stress.EXPERT INPUT · COUNTRY-CHE-SYS-012
- CHNChinaThe leading compound pathway for 2027 testing is extreme rain on a dense plain in a hot summer that cuts roads, underground transport, water and care together.EXPERT INPUT · COUNTRY-CHN-SYS-012
- EUEuropean UnionThe leading compound pathway for 2027 testing is a summer of heat, drought and fire across several member states at once, met by tight energy supply.EXPERT INPUT · COUNTRY-EU-SYS-012
- GS-02Global EnergyThe leading compound pathway for 2027 testing is a fuel supply shock that coincides with a hot, high-demand season and a stressed grid.EXPERT INPUT · SECTOR-ENERGY-GLOBAL-SYS-012
04Evidence path
From Foundry evidence to the series.
The evidence, step by step, from the systems this area reads to the series it feeds.
How Systems Science and Modelling reaches Reports: what it reads, how it reads it, the sealed cut and the series it feeds.
| Step | What happens | Source |
|---|---|---|
| 01 What it reads | Systems Science and Modelling reads NXS-DSS (decision cases and deliberation) and NXS-LAB (research, experiments and simulations): governed sources with their releases, never a value without its source. | |
| 02 How it reads them | Systems engineering and Probability and statistics turn the evidence into findings, with assumptions and limits stated beside each value. | |
| 03 The cut is sealed | Each quarter the evidence is sealed in one cut, so OBSERVED, REPORTED and ESTIMATED values stay apart and every edition can be rebuilt. | |
| 04 The series it feeds | The cut feeds Methods and Technical and Scenario and Stress-Test, from the Baseline Edition 2026 into the quarterly series. | |
| 05 Who decides | Decisions stay with the authorities that hold them, under their own rules; an edition informs a decision and never makes it. |
A teaching model of the evidence path, not a forecast and not a record of any run; the systems, methods and series named come from the registries. Sources: Systems Science and Modelling in Reports (2026); Systems Science and Modelling home (2026).
05Series
The series it feeds, and what backs each.
| Series | Foundry systems it draws on | Academy disciplines | Series home |
|---|---|---|---|
| Methods and Technical | The Global Risks Index (NXS-GRX) the methods, indicators and validation studies behind each product NXS-LAB method comparisons under transparent test conditions NXS-NXQ (software, models and capability lifecycle) the fitness record of models and tools the methods use | Quantitative risk analysis and statistics Model risk and validation Risk indicators and composite indices | Methods and Technical series home |
| Scenario and Stress-Test | NXS-DSS combined scenario sets and the option appraisals run on them NXS-GRX the cascade paths a stress test follows | Scenario analysis and stress testing Uncertainty and decision making Systemic, compound and cascading risk | Scenario and Stress-Test series home |
06Backed by
The systems, methods and teaching behind it.
- NXS-DSSNXS-DSSNXS-DSSRooms: Scenarios, Decisions.
- NXS-LABNXS-LABNXS-LABRooms: Experiments, Benchmarks.
- NXS-NXQNXS-NXQNXS-NXQRooms: Capabilities, Competence.
- NXS-COR (compute, nodes and runtimes)NXS-CORNXS-CORNXS-COR
- STEM methodSTEM CommonsSystems engineeringThe canonical method page, with its limits.
- STEM methodSTEM CommonsProbability and statisticsThe canonical method page, with its limits.
- STEM methodSTEM CommonsUncertainty quantification and model validationThe canonical method page, with its limits.
- STEM methodSTEM CommonsNetwork science and contagionThe canonical method page, with its limits.
- STEM methodSTEM CommonsComplex systems and agent-based modellingThe canonical method page, with its limits.
- STEM methodSTEM CommonsOptimisation and operations researchThe canonical method page, with its limits.
- Academy disciplineRisk AcademyComplex systems and systems modellingFaculty of Systems and Nexus Studies
- Academy disciplineRisk AcademyUncertainty and decision makingFaculty of Risk Science and Methods
- FieldGCRIMethods and modellingThe field across science, governance and finance.
- FieldGCRIRisk management and systemic riskThe field across science, governance and finance.
- FieldGCRIResearch and evidenceThe field across science, governance and finance.
07Across the Consortium
Where the same subject is reported elsewhere.
- Counterpart · GRFReportsResearch NexusShared: Research and evidence.
- Counterpart · GRFReportsPolicy NexusShared: Risk management and systemic risk.
- Counterpart · GRFReportsForesight NexusShared: Risk management and systemic risk.
- Counterpart · GRFReportsGovernance NexusShared: Risk management and systemic risk.
- Counterpart · GRAReportsFinancial StabilityShared: Risk management and systemic risk.
- Counterpart · GRAReportsActuarial and Quantitative RiskShared: Methods and modelling.
- Standards areaNexus StandardsData and datasetsData and evidence. Parts NS-3, NS-3b, NS-11, NS-1.
- Standards areaNexus StandardsDocumentation and publicationData and evidence. Parts NS-2, NS-4, NS-7, NS-8.
- Standards areaNexus StandardsProvenance and evidenceData and evidence. Parts NS-3b, NS-11, NS-3.
- Standards areaNexus StandardsVerification and monitoringTrust, verification and assurance. Parts NS-11, NS-10, NS-14.
- Standards areaNexus StandardsPrivacy and data protectionData and evidence. Parts NS-10, NS-11, NS-3.
- Standards areaNexus StandardsFinance and payments dataFinance, insurance and the economy. Parts NS-9, NS-10, NS-11, NS-14.
08Topics
Topic pages on Systems Science and Modelling.
09Contribute
Contribute on Systems Science and Modelling.
Evidence, a case, a correction, a method or profile input on this subject. The composer tags it with this area and its series.
Contribution composer
Write a contribution the editor can act on.
Say what it is, where its record is kept and on which licence. It arrives tagged with this page, its area and its gateway, so it reaches the editor who owns it.
Your email opens with the subject and a template already filled in for GW-GCRI.
- Evidence
- Correction
- Case study
- Analysis or method
- Peer review
- Translation
- Profile input
Never send personal data or sensitive infrastructure detail. A contribution is reviewed before use; sending it confers no authorship or editorial rights.
10Open science
Open science for Systems Science and Modelling.
How a contribution on this subject is deposited, identified, credited, licensed and found, and the metadata for it prefilled from this page.
Systems Science and Modelling’s open record
- Area
- Systems Science and Modelling
- Feeds
- Methods and Technical, Scenario and Stress-Test
- Record
- A UNI for every accepted contribution; cited with its DOI in the edition that uses it
- Links
- isSupplementTo the edition it informs; isNewVersionOf its earlier version
- Licence
- CC BY 4.0 (SPDX CC-BY-4.0) for original material; metadata CC0 1.0
Credit and identity
- ORCID
- Your iD in the deposit and the contribution record; DataCite can then add the work to your ORCID record
- ROR
- Your organisation by its ROR identifier, never by a typed name alone
- CRediT
- Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Software, Validation, Visualisation, Writing, review and editing
- Account
- None needed to contribute; never a password
Find and follow
Search the open indexes for Systems Science and Modelling; software is cited by its SWHID from Software Heritage. Annotation is your choice: Hypothesis opens this page in its own viewer.
Mirrors and harvest
The DOI is canonical. At release each signed bundle is also given an IPFS content identifier and a bloxberg anchor as mirrors; both are listed in the record once they exist. Zenodo exposes every record over OAI-PMH, and reviews and endorsements can arrive through COAR Notify where the repository supports it.
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}11Latest
Releases for this area.
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ReportsContribute
Send evidence on Systems Science and Modelling.
Reports is the Consortium’s quarterly publication, written by six desks. This page sits with the Global Centre for Risk and Innovation (GCRI) Systems Evidence desk. What you know about this subject can become evidence, a case or a correction in the next edition, credited to you and published under CC BY 4.0 where it is your own work. Sent to the wrong desk, it is forwarded, not refused.
GCRI Systems Evidence deskSystems Science and ModellingMethods and TechnicalScenario and Stress-Test
- EmailGateway GW-GCRISend it from this pageEvidence, a correction, a case, a method, a review, a translation or profile input. It arrives tagged with this page, so the editor who owns it receives it.
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