Climate change projections indicate that many of the natural hazards (e.g. rainfall and heat) which affect critical infrastructure may intensify and occur more frequently. This has led to an increased interest in studying the effects of natural hazards on the networks for infrastructure operators, infrastructure users and society in general. The Dutch National Road Authority (Rijkswaterstaat) has the challenging ambition to establish a resilient road network by 2050. To reach that objective, a stresstest has been developed and applied to identify the effect of future climate conditions and associated weather extremes on the Dutch highway network.

Analysis of climate hazards

This stresstest provides the information needed to establish an Implementation Agenda that links to all the processes that Rijkswaterstaat uses for the management of the road network, being design, maintenance, renewal and renovation. In total, the stresstest covered 13 hazards, including pluvial flooding of the road due to intense rainfall, uplift of tunnels and lightweight materials, dike breaches (river and coastal flooding), heat expansion of bridges, heat effects on road foundations, drought-, nature- and roadside-related fires and road deformation caused by soil subsidence. Climate change effects were considered by keeping the damages and losses per climate event equal, but by changing the return period based on climate statics data delivered by the Royal Netherlands Meteorological Institute (KNMI) Dutch meteorological institute.

Resilience assessment

Hazard and susceptibility maps were being developed and projected on the road infrastructure at a 100 m level and its relevant assets (e.g. tunnels for uplift of tunnels and heat expansion of bridges) resulting in exposure maps. To evaluate the risk, an assessment of the combination of likelihood of the event occurring, multiplied with the impact of the event was undertaken. Impact results were monetized and split in the expected damages to the road and the potential losses for the road user (socio-economic losses).

To prioritise locations for adaptation, the exposure, damages and losses maps were presented in regional risk dialogues where asset managers and other regional experts were present. The prioritization module of RA2CE was used to identify at which locations the hazards have the highest priority, by combining road damage and socio-economic losses in a prioritization matrix, identifying the specific locations with highest priority.

It was considered that assessing solely economic impacts (damages and losses) did not reflect the entire need for evaluation of the resilience. Therefore, resilience was also evaluated using Rijkswaterstaat’s asset management framework, which provides a structured approach to derive the level of acceptable risk. The impact is classified using various criteria while using the acronym RAMSSHEEP: Reliability, Availability, Maintainability, Safety, Security, Health, Environment, Euro (monetary), and Politics. This approach was received well by the regional offices, since it links to daily practices and provides a clear way of evaluating all information.

How are adaptation solutions considered?

The following steps have been taken, starting with a qualitative overview of adaptation options, towards a quantitative substantiation:

(1) Providing a longlist of possible measures per event. The overview of measures from the ROADAPT project was used as a starting point and supplemented during interviews with experts. The list of 120 measures included both structural and non-structural measures, as well as measures that are linked to all processes of Rijkswaterstaat from design to maintenance and rehabilitation.

(2) A semi quantitative cost benefit assessment of the measures in the longlist was made. A cost estimate of the measures was made by making use of key cost figures along with a general estimation of the effectiveness of the measures. The effectiveness was scored against criteria that are applied in the asset management of Rijkswaterstaat, namely: availability, safety for road users, sustainability, and image/politics. Finally, other criteria were scored in order to gain better insight in the applicability of the measures. These criteria were robustness for various future developments, flexibility to change to other measures when needed, possibility to connect with other measures and feasibility in terms of governance aspects. By conducting a multi criteria analysis it was possible to select promising measures from the long list of measures.

(3) As a result of the semi quantitative analysis, a quantitative cost benefit assessment was made for 2 hazards, modelled in the RA2CE framework. For that purpose, the effectiveness of the measures needed to be obtained and new hazard maps and forthcoming exposure maps needed to be developed for each measure. This made it possible to conduct a cost benefit assessment per 100 meter of road segment for the entire road network. The assessment accounted for the expected change of likelihood of events due to climate change, the frequency of application of the measures (and thus cost) and a discount rate. This has resulted in maps and tables showing per measure whether and where an action perspective is present from an economic point of view.

How is the adaptation strategy implemented in practice?

Efforts are made by Rijkswaterstaat to take the results as input for policy and, ultimately, improving the construction, operation and maintenance to be more climate adaptive. For regions it serves as input for the assets under their administration to signal better what requirements their assets need to meet. The stresstest and visualisation of results in a Climate Effect Atlas are great tools for policymaking and risk dialogues. These sources provide a general overview for the whole country and a focus for analyses. This has furthermore been formalised in an implementation agenda .

The desired and acceptable levels of resilience for the road network are difficult to determine. Discussions with experts and policy makers lead to the choice of using the RAMSSHEEP asset management framework. It remains challenging to balance the ambition for a level of resilience with the cost of adaptation, when incorporating all possible impact criteria together with economic output of damages and losses. To promote implementation, effort was made to integrate adaptation into the asset management process of Rijkswaterstaat and make a clear ‘line of sight’ for adaptation choices. For this, goals must be set at policy level, that can be expressed in functional goals for the network. Asset managers should be able to make defendable choices between these goals and other goals in case of a deficit of money.

Lessons learned?

It has been learned though that when it comes to detailed planning of projects and climate adaptation measures, an additional more detailed assessment and cost benefit calculation will be necessary.

The work identified the potential impacts of climate change by quantifying damages and losses can aid policy makers in identifying the hotspots for potential impact. However, to identify specific interventions, an evaluation of the impacts and interventions can really pinpoint the locations where interventions are potentially cost beneficial efficient. Incorporating adaptation in asset management is a difficult process. Involving asset managers from the NRA during the analysis, but especially in the process of evaluation and intervention planning is recommended. This enables the inclusion of other criteria such as environmental effects, safety and politics/image, besides monetary information, in the evaluation.

Adaptation planning inherently introduces uncertainty. In our approach we have accounted for this in several stages of the approach. During the development of the susceptibility maps by using validation datasets and expert evaluation. However, prerequisite of such an approach is that the input data (e.g. evaluation data, topological features of the network and assets) should be well known. During the quantification of the impacts, we accounted for uncertainties in the different variables by making use of upper and lower limits. To improve this approach, a more integral uncertainty analysis could be considered.      


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