The Global Centre for Risk and Innovation (GCRI)
Systems science studies how the parts of a system interact to produce behaviour that none of them shows alone. Modelling is its main tool: the disciplined representation of a system in mathematics or code, so that its behaviour can be explored, tested and explained. This page defines the field, explains why it matters for society and shows how it connects to every other risk.
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The Systems Science and Modelling field covers the shared mathematical and engineering foundation for every Nexus field. Experts in it study questions such as model intercomparison and uncertainty and validation, with methods such as systems engineering as well as probability and statistics. Its counterparts at GRF and GRA look at the same systems through governance and finance.
Fig.How GCRI, GRF and GRA share one field while the authorities decide. Design, not a record.
The working screen behind this subject: its structure, terms and states. Names are placeholders and values illustrative.
The field brings together systems engineering, which designs and analyses complex engineered systems; probability and statistics and uncertainty quantification and model validation, which describe what is known and how confidently; network science and contagion and complex systems and agent-based modelling, which explain how structure and behaviour create emergent effects such as cascades; and optimization and operations research and decision analysis under uncertainty, which support choices under constraints and uncertainty.
It is defined less by a subject than by a way of working: making assumptions explicit, testing them against evidence, and stating what a model can and cannot say.
Grids, water networks and transport systems are planned and run with models.
Transmission models inform preparedness and response decisions.
Loss, stress and capital models shape financial resilience.
Each term as this page uses it. Where a standard-setting body defines the term, the wording follows that body.
| Term | Definition |
|---|---|
| Validation | Confirming that a system meets its users' needs in its intended use, often summarised as building the right thing. |
| Uncertainty quantification | Characterising and propagating the uncertainties in a model to state confidence in its outputs. |
| Coupled model | A set of models linked so that outputs of one become inputs to others. |
| Systemic risk | Risk arising from the interactions and dependencies within and between systems, where a shock can propagate and threaten the functioning of the whole. |
Every Nexus field uses these methods, which makes the field a dependency of all of them. Those links are set out in dependencies and consequences.
The field gateways for methods and modelling, risk management and systemic risk and research and evidence list every Consortium platform working on these subjects.
The current service level is R0: information and enquiries. An enquiry receives a reference and names the next step; applications, payments, compute allocations and registrations open only when their team, terms and review capacity exist.