Adaptation Investments for Transport Resilience: Trends and Recommendations

Adaptation Investments for Transport Resilience: Trends and Recommendations

Maria Pregnolato David A. Dawson 

School of Engineering, Newcastle University, Newcastle (UK)

School of Civil Engineering, University of Leeds, Leeds (UK)

30 September 2018
| Citation



Climate change, extreme weather and flooding threaten to increase damage and disruption to our transport networks and the services that they provide. There is increased need for adaptation to maintain current asset conditions and services, and a strategic requirement to prioritise such investments in adaptation to reduce future risks. Physical network risks will not be evenly distributed across nations (e.g. due to geographical and climate change patterns), and some regions will require more investment and adaptive interventions than others to maintain services due their vulnerability to natural hazards. Comparatively, the distribution of investment for transport infrastructure does not have a uniform spatial distribution, and can favour schemes that reduce congestion on networks with high demand without considering the actual risk of being impacted. These two issues, if unchallenged, will present an unfavourable future for areas with high network risks and low transport demand that will widen spatial inequality or resilience, mobility and potential for economic growth. This study advances a method- ological framework to analyse the spatial distribution of flood risk on UK road and rail networks in the light of potential bias of regional investment. Using GIS mapping, network data and risk analysis, regional futures are categorised and discussed. There is a clear North/South divide in transport networks at risk from potential coastal and fluvial flooding, with southern regions having 10–30% of their network situated in known flood risk areas. Investment in transport infrastructure is also disproportionately favoured towards regions with high transport demand, and peripheral regional such as wales and the South west are at risk from increase disparity from high flood risk networks and a low potential for investment. The study provides preliminary evidence for the need to consider assessment approaches for long-term investment in resilience, drawing recommendations for future research.


adaptation, flood, risk, investment, network, rail, resilience, road, transport


[1] IPCC, Managing the Risks of Extreme Events and Disasters to Advance Climate Change Adaptation. A Special Report of Working Groups I and II of the Intergovernmental Panel on Climate Change [Field, C.B., V. Barros, T.F. Stocker, D. Qin, D.J. Dokken, K.L. Ebi, M.D. Mastrandrea, K.J. Mach, G.-K. Plattner, S.K. Allen, M. Tignor, and P.M. Midgley (eds.)]. Cambridge University Press, Cambridge, UK, and New York, NY, USA, 582 pp, 2012.

[2] Mattsson, L.-G. & Jenelius, E., Vulnerability and resilience of transport systems – A discussion of recent research. Transportation Research Part A: Policy and Practice, 81, pp. 16–34, 2015.

[3] Jaroszweski, D., Chapman, L. & Petts, J., Assessing the potential impact of climate change on transportation: the need for an interdisciplinary approach. Journal of Transport Geography, 18(2), pp. 331–335, 2010.

[4] Eddington, R., The Eddington Transport Study: Transport’s role in sustaining the UK’s productivity and competitiveness, HM Treasury, London, 2006.

[5] Banister, D. & Berechman, J., Transport Investment and Economic Development, University College London Press, London, 2000.

[6] SPERI, Public infrastructure investment and business activity in the English regions (British Political Economy Brief No. 15). Sheffield Political Economy Research Institute (SPERI), 2015.

[7] IPPR, New transport figures reveal London gets £1,500 per head more than the North – but North West powerhouse ‘catching-up’, Institute for Public Policy Research, 2017

[8] Birkmann, J. & Mechler, R., Advancing climate adaptation and risk management. New insights, concepts and approaches: what have we learned from the SREX and the AR5 processes? Climatic Change, 133(1), pp. 1–6, 2015.

[9] Department for Transport, Transport Analysis Guidance (TAG) Data Book, July 2017, 2017a.

[10] Department for Transport, Transport Analysis Guidance (TAG) on the analysis of user and provider impacts in transport appraisals. TAG unit A1.3 user and provider impacts, March 2017, pp. 1–35, 2017b.

[11] Meunier, D. & Quinet, E., Value of time estimations in cost benefit analysis: the French experience. Transportation Research Procedia, 8, pp. 62–71, 2015.

[12] Börjesson, M. & Eliasson, J., Experiences from the Swedish value of time study. Transportation Research part A: Policy and Practice, 59(2014), pp. 144–158, 2014.

[13] Hickman, R. & Dean, M., Incomplete cost – incomplete benefit analysis in transport appraisal. Transport Reviews, pp. 1–21, 2017.

[14] Penning-Rowsell, E.C., Priest, S., Parker, D., Morris, J., Tunstall, S., Viavattene, C., Chatterton, J. & Owen, D., Flood and coastal erosion risk management: A Manual for Economic Appraisal. Routledge, Middlesex (UK), 2013.

[15] Metroeconomica, Costing the impacts of climate change in the UK: Overview of guidelines. UKCIP Technical Report. UKCIP, Oxford, 2004.

[16] Dawson, D.A., Shaw, J. & Gehrels, W.R, Sea-level rise impacts on transport infrastructure: The notorious case of the coastal railway line at Dawlish, England. Journal of Transport Geography, 51, pp. 97–109, 2016.

[17] Pregnolato, M., Ford, A., Glenis, V., Wilkinson, S., & Dawson, R., Impact of flooding and urban adaptation in a changing climate. Journal of Infrastructure Systems, 23(4), pp. 1–13, 2017.

[18] Pant, R., Hall, J. W. & Blainey, S. P., Vulnerability assessment framework for interdependent critical infrastructures: case-study for Great Britain’s rail network. European Journal of Transport and Infrastructure Research, 16(1), pp. 174–194, 2016

[19] British Geological Society, BGS indicators of flooding, 2016, available at (accessed 30th November 2017)

[20] Ordnance Survey, Integrated Transport Network (ITN) [GML2 geospatial data], Scale 1:1250, Tiles: GB, Updated: 22 May 2014, Ordnance Survey (GB), Using: EDINA Digimap Ordnance Survey Service, available at (accessed 30th November 2017).

[21] Jalayer, F., De Risi, R., De Paola, F., Giugni, M., Manfredi, G., Gasparini, P., Topa, M., Yonas, N., Yeshitela, K., Nebebe, A., Cavan, G., Lindley, S., Printz, A. & Renner, F., Probabilistic GIS-based method for delineation of urban flooding risk hotspots. Natural Hazards, 73(2), pp. 975–1001, 2014.

[22] CIRIA, Contaminated land risk assessment. A guide to good practice, CIRIA, London, 2001.

[23] Larsen, M., Nielsen, N.H. & Rasmussen, S.F., The blue spot model. Development of a screening to assess flood risk on national roads and highways system, Danish Road Directorate, Copenaghen (Denmark), 2010.

[24] Naso, S., Chen, A.S., Aronica, G.T. & Djordjević, S., A novel approach to flood risk assessment: the Exposure-Vulnerability matrices. E3S Web Conf., 7, p. 08007, 2016.

[25] UKCIP, Socio-economic scenarios for climate change impact assessment: A guide to their use in the UK Climate Impacts Programme, UK Climate Impacts Programme, Oxford, 2001.

[26] ONS, Office of National Statistics. Developing new measures of infrastructure investment: July 2017, available at (accessed 30th November 2017).

[27] Elmontsri, M., Review of the strengths and weaknesses of risk matrices. Journal of Risk Analysis and Crisis Response, 4(1), pp. 49–57, 2014.