Adaptation measures
Quantifying risk is only half the job. The final step asks what can be done about it, and whether doing it would be worth the money.
Soft and hard measures
Once risk has been quantified, adaptation measures are introduced to reduce it and build resilience into both the population and the network.
| Type | What it changes | Example |
|---|---|---|
| Soft | Behaviour and operations | Early warning systems that prevent population displacement |
| Hard | Physical infrastructure | Improving specific road links to prevent flooding |
Testing them against a baseline
This is the part that makes the framework a decision tool.
With a measure in place, the entire framework runs again. Those results are then compared against the baseline scenario: the same event, the same region, no intervention.
The comparison is made across all three perspectives, economic, social and environmental, which reveals not just whether a measure works but where and when it works, and who benefits.
Why a baseline re-run, rather than an estimate
An adaptation measure changes the hazard and how people travel through it. Those knock-on effects compound in ways a simple deduction cannot capture, since rerouting can move congestion somewhere worse. Running the full framework twice is the only way to see the net effect.
Reusing the framework elsewhere
The processes in the framework diagram are not tied to one scale, one hazard or one mode. The same structure supports quite different questions.
A present-day event on the roads. Simulate an observed extreme rainfall event to assess direct impacts on a road network, plus the indirect impacts on the people and goods moving through it. These impacts can then be quantified to provide data-driven insights.
A week-long heatwave on the railways. Assess how extreme temperatures disrupt long-distance travel between urban areas.
Infrastructure failure, with no weather at all. Drop the climate data entirely and simulate assets going out of service, such as bridges and tunnels lost to ageing, prolonged weather exposure, or overuse causing total or partial deterioration. The framework still reports impacts on transport network resilience, the main alternative routes used, and the increase in average travel times and distances for specific population groups.
Transferability
The framework and its modelling workflow were deliberately built on open-source models and nationally available open datasets. In theory, the IMP can therefore be developed and applied for any region in the UK.
The real constraint is skills, not licences
Because nothing is locked behind a licence, the limiting factor on replicating this methodology is having the skills to develop the model simulations and operationalise the framework.
It extends existing tools, it does not replace them
The IMP is expected to be compatible with the tools, methods and datasets organisations already use. It is not intended to completely replace existing frameworks, but to extend and complement them.
Many components can be substituted with equivalents that produce comparable results, such as an in-house hydrological model in place of the IMP's.
Proving it in practice
The IMP is being used across DARe's programme through a set of case studies. These demonstrate how the framework applies in practice and what insight it delivers, while producing knowledge about decarbonisation, adaptation and resilience that feeds DARe's broader findings.
In detail
The measures themselves, covering green infrastructure, grey infrastructure and soft measures, are described in Adaptation measures.