Climate Change Adaptation Strategies for Road Transportation Infrastructure: A Systematic Review on Flooding Events

During the last decades, the number of flooding events has increased significantly, due to the global trend of urbanization and climate change, becoming a recurring biophysical impact, resulting in major physical disruption to water and wastewater systems, life and economic losses, and damage to the critical infrastructure. For the road transportation sector, this reality is indisputable, as severe flooding events tend to severely damage the transportation infrastructure and reduce the network connectivity, increasing repair, maintenance, and construction costs. Thus, through a systematic literature review, with direct database searches and application of inclusion and qualification (quality and applicability) filters, a repository of 213 publications on adaptation strategies applied to reduce the impacts of flooding on road infrastructure is developed. Most of these studies have been published since 2014, due to the publication of the Fifth Assessment Report of the Intergovernmental Panel on Climate Change. It should also be noted that, of the overall total, only 47% of studies deal specifically with the road transportation sector (the remaining 53% cite the sector only as an example), thus demonstrating the urgency of further studies on the topic. It should also be noted that the climate risk assessment, involving the creation of current and future flood risk maps, is essential for determining the best climate change adaptation strategies for road transportation infrastructure. As flood damages and costs are largely and strictly site-specific, analyses are critical for guiding land use decisions and evaluating adaptation strategies that can be divided into hard adaptation (optimization or redesign of hydraulic components, installation of protective structures and optimization of environmental conditions) and soft adaptation (creation of transportation-focused master plans and development of quantitative models and systems).