Dear Colleagues,

Reliable and functioning infrastructures such as energy, transport, water, waste, telecommunications, and flood defenses are essential for maintaining social well-being and economic prosperity. Recent studies have shown that such infrastructures directly or indirectly influence about 72% of targets set out towards meeting the Sustainable Development Goals [1]. As global investment needs for infrastructures are projected to be around US$ 94 trillion till 2040 [2], there is a danger that rapid infrastructure development might not be beneficial if underlying risks are not taken into account. In particular, climate change-driven extreme weather hazards will most likely pose some of the biggest risks to infrastructures over the next decade [3].  Though climate risks are recognized as a major threat to infrastructures there is still a lack of knowledge and tools for quantifying such risks effectively for decision-making. Methods and tools to quantify systemic climate vulnerabilities and risks to infrastructures across space and time are becoming increasingly relevant, which focuses on planning decisions to be made beyond an individual asset scale and aiming to build systemic resilience. Demonstrating and improving such methods through case studies worldwide has been highlighted as one of the greatest opportunities for climate adaptation of infrastructures [4].            

This Special Issue will address the challenges of understanding systemic risks to infrastructure systems due to environmental stressors. We invite theoretical, methodological, and quantitative studies that enrichen our knowledge and understanding of climate vulnerabilities, risks, and resilience of infrastructure systems.  We encourage multi-disciplinary approaches that combine quantitative and qualitative modeling approaches across climate science, infrastructure modeling, and social sciences with a focus on how models can better inform decision-making and policy on climate adaptation of infrastructures.

The topics covered in this Special Issue include (but are not limited to) the following:

• Literature reviews that identify the state-of-art of current approaches and identify gaps for future research challenges
• Empirical approaches that document novel evidence and data resources on systemic risk analysis  
• Interdependency analyses models
• Network science-based models and approaches
• Agent-based models
• Macroeconomic input–output and computational general equilibrium approaches
• Economics of climate risk and adaptation
• Optimization models
• Complex system dynamics models
• Data-driven approaches such as artificial intelligence, machine learning, and big data for improved monitoring and operational planning
• Uncertainty analysis methods for robust decision-making

The Special Issue covers the following infrastructure systems:

• Energy – electricity, gas, power plants
• Transportation – road, railways, ports, airports
• Telecommunications and digital services
• Water – supply and distribution
• Waste – supply and distribution
• Flood defenses
• Green infrastructures

[1]. Thacker, S., Adshead, D., Fay, M., Hallegatte, S., Harvey, M., Meller, H., O’Regan, N., Rozenberg, J., Watkins, G., Hall, J.W., 2019. Infrastructure for sustainable development. Nature Sustainability, 2(4), pp.324–331.

[2]. Global Infrastructure Hub, 2017. Global infrastructure outlook. Global Infrastructure Hub: Sydney, Australia.

[3]. World Economic Forum (WEF), 2020. The Global Risks Report 2020. World Economic Forum, Geneva, Switzerland. Available at http://www3.weforum.org/docs/WEF_Global_Risk_Report_2020.pdf.

[4]. Hall, J.W. et al., 2019. Adaptation of Infrastructure Systems: Background Paper for the Global Commission on Adaptation. Oxford: Environmental Change Institute, University of Oxford. doi: https://cdn.gca.org/assets/2019-12/GCA-Infrastructure-background-paperV11-refs_0.pdf.

Dr. Raghav Pant
Dr. Xi Hu
Guest Editors

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• infrastructure systems
• vulnerability assessment
• risk analysis
• climate resilience
• climate adaptation
• decision-making
• uncertainty