Extreme weather phenomena and climate change challenge our transport system – part 3

In the third part of the blog series, we continue going through OECD’s recommendations, having reached the last ones, numbers 7 to 9. We conclude by estimating the Finnish transport system from the viewpoint of climate risks and extreme weather risks. Recommendations 1–3 are discussed here and 4–6 here.

At the turn of the year, the Organisation for Economic Co-operation and Development’s (OECD) International Transport Forum (ITF) published a research report on the challenges posed by extreme weather phenomena and climate change to the transport system, particularly the transport infrastructure. The report Adapting Transport to Climate Change and Extreme Weather: Implications for Infrastructure Owners and Network Managers lists recommendations for OECD Member Countries on minimising adverse effects. VTT is one of the report’s main authors.

7: Re-evaluate: are there infrastructures that are redundant or less useful?

When one part of a network fails, an old part of the network that has perhaps previously been considered redundant or less useful may suddenly turn out to be quite usable. Let us use an old bridge as an example. If a new bridge is built next to the old one, and its service ability drops for one reason or another, due to such a reason as extreme weather phenomenon or an accident, the old bridge may increase in importance beyond all recognition.

Under certain circumstances, an old and useless part of a transport network may be a useful emergency passage or an alternative route e.g. for light traffic.

8: Traditional cost-benefit analysis is not sufficient for appraising the profitability of transport projects

A traditional cost-benefit analysis does not observe the increased extreme weather risks and climate risks to a sufficient degree. Forecasting the future constitutes a specific risk factor (because the future is always uncertain!). In transport projects, the appraisal is made for a time horizon of 30–50 years ahead, and such a horizon already includes major climate change risks. However, we need to be able to assess and monetise such risks to ensure that we make as wise project and investment decisions as possible for now and with a view to the future in particular.

Therefore, project evaluations and cost-benefit analyses must be developed to take better account of the changed “risk landscape”. The same advice applies to almost all other long-term investment activities as well.

Already in the course of the EWENT (Extreme weather impacts on European networks of transport) project, the European Investment Bank started to develop its own project evaluation system, and today climate risks are observed in EIB project evaluations.

9: Develop decision-support tools and methods for the new age of uncertain future

Advanced and often a little hard-to-understand decision-support methods, such as real-options and multi-criteria analyses are excellent decision tools in spite of the complicated mathematics involved, as long as they are applied correctly and the users understand the nature, the framework conditions and the limitations of the tool. Real-options analysis is particularly well suited for the appraisal of new investments – this involves making significant decisions that are difficult to reverse and that you need to live with for a long time. Transport infrastructure projects are typical examples of such decisions. Real-options analysis can be used, for example, for monetising “flexibility” (keeping different options open) and postponement of a decision (when the future is uncertain, it may be wise to wait…). In other words, sometimes it may be sensible to update old infrastructure and postpone large investments, when there are major uncertainty factors involved.

Multi-criteria analysis methods can be applied, for example, for selecting investments, projects and strategies in such a manner that enables finding options that function sufficiently well in most of the selected scenarios – even if the selected option was not the best in any of them. In game theory, this is referred to as minimising the possible losses instead of trying to maximise the gains.

The strengths and weaknesses of the Finnish transport system in the light of extreme weather risks

In the broad sense, the Finnish transport system consists of the infrastructure, as well as the vehicles using the infrastructure, the transport information infrastructure, transport system operators (administration, companies, transport operators, passengers), and the operating and steering systems associated with all of the above. This is in fact a genuine “meta system”, a system of systems.

The physical modes of transport – road, rail, water and airborne transport systems – differ significantly from each other in terms of technology, utilisation rate and properties affecting their resilience. Furthermore, each physical infrastructure is supported by subsystems supplementing it, such as drainage systems, lighting, signs and intelligent transport applications (e.g. changing signals, information systems), not to mention the vehicles, terminals, railway yards and stations. Therefore, the transport system consists of complex subsystems, the management of which requires not only a holistic approach, but also an immense amount of concrete hands-on work varying from managerial strategy drafting to snow-plowing.

Transport system and elements affecting its resilience.

Resilience can be most efficiently and cost-effectively affected when transport systems are in their planning stages. As a rule, any solutions added at later stages, no matter how necessary, are in relative terms more expensive and less efficient. Therefore, the primary starting point for ensuring a functional operation system lies in the planning of transport systems and land use.

Opportunities to influence and expenses required for improved resilience
(adapted from Leviäkangas & Michaelides, 2014).

The Finnish transport system is relatively complete, comprehensive and functional, and the share of major network investments of the overall expenses of the system is relatively low. The use and maintenance of the existing infrastructure constitute the biggest expense items over the life-cycle of the asset. Therefore, there is only a limited amount of methods available for improving resilience once the infrastructure asset is put in its place. Efforts can still be made by focusing on preventive and enhanced maintenance strategies.

Some threats to the resilience of the transport system are associated with the subsystems supporting the physical infrastructure, such as serious disturbances in the power supply, communications and information systems (cyber threats), transport logistics and security of supply; increasingly severe and exceptional extreme weather phenomena; and, to a certain degree, crime that threatens societal order (e.g. terrorism) as well. It is necessary to draw up risk management strategies, plans and guidelines also for these threats. It is equally important to increase the resource readiness by making sure that maintenance and removal fleets and manpower are at disposal once the adverse event hits.


ITF (2016) Adapting Transport to Climate Change and Extreme Weather: Implications for Infrastructure Owners and Network Managers, ITF Research Reports, OECD Publishing, Paris. http://dx.doi.org/10.1787/9789282108079-en

The report can be downloaded at: http://www.oecd-ilibrary.org/transport/adapting-transport-to-climate-change-and-extreme-weather_9789282108079-en;jsessionid=5o0iqml8ohiq9.x-oecd-live-03

EWENT project: http://ewent.vtt.fi/index.htm


Leviäkangas, P. & Aapaoja, A. (2015) Resilienssin käsite ja operationalisointi – case liikennejärjestelmä. Kunnallistieteellinen aikakauskirja 1/2015. (In Finnish.)

Leviäkangas, P. & Michaelides, S. (2014) Transport system management under extreme weather risks: views to project appraisal, asset value protection and risk-aware system management. Natural Hazards, Vol. 72, No. 1, pp. 263–286.

Pekka Leviäkangas VTT

Pekka Leviäkangas, Principal Scientist

Aki Aapaoja VTT

Aki Aapaoja, Research Scientist

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