Transport infrastructure is exposed to natural hazards all around the world. Here we present the first global estimates of multi-hazard exposure and risk to road and rail infrastructure. Results reveal that ~27% of all global road and railway assets are exposed to at least one hazard and ~7.5% of all assets are exposed to a 1/100 year flood event. Global Expected Annual Damages (EAD) due to direct damage to road and railway assets range from 3.1 to 22 billion US dollars, of which ~73% is caused by surface and river flooding. Global EAD are small relative to global GDP (~0.02%). However, in some countries EAD reach 0.5 to 1% of GDP annually, which is the same order of magnitude as national transport infrastructure budgets. A cost-benefit analysis suggests that increasing flood protection would have positive returns on ~60% of roads exposed to a 1/100 year flood event.

Limited data on global power infrastructure makes it difficult to respond to challenges in electricity access and climate change. although high-voltage data on transmission networks are often available, medium-and low-voltage data are often non-existent or unavailable. this presents a challenge for practitioners working on the electricity access agenda, power sector resilience or climate change adaptation. Using state-of-the-art algorithms in geospatial data analysis, we create a first composite map of the global power system with an open license. We find that 97% of the global population lives within 10 km of a MV line, but with large variations between regions and income levels. We show an accuracy of 75% across our validation set of 14 countries, and we demonstrate the value of these data at both a national and regional level. The results from this study pave the way for improved efforts in electricity modelling and planning and are an important step in tackling the Sustainable Development Goals.

Critical infrastructure networks are geographically distributed systems spanning multiple scales. These networks are increasingly interdependent for normal operations, which causes localized asset failures from natural hazards or man-made interference to propagate across multiple networks, affecting those far removed from an initiating failure event. This paper provides methodology to identify such failure propagation effects by quantifying the spatial variability in magnitude, frequency, and disruptive reach of failures across national infrastructure networks. To achieve this, we present methodology to combine functionally interdependent infrastructure networks with geographic interdependencies by simulating complete asset failures across a national scale grid of spatially localized hazards. A range of metrics are introduced to compare the systemic vulnerabilities of infrastructure systems and the resulting spatial variability in both the potential for initiating widespread failures and the risk of being impacted by distant hazards. We demonstrate the approach through an application in New Zealand of infrastructures across the energy (electricity, petroleum supply), water and waste (water supply, wastewater, solid waste), telecommunications (mobile networks), and transportation sectors (passenger rail, ferry, air, and state highways). In addition to identifying nationally significant systemic vulnerabilities, we observe that nearly half (46%) of the total disruptions across the simulation set can be attributed to network propagation initiated asset failures. This highlights the importance in considering interdependencies when assessing infrastructure risks and prioritizing investment decisions for enhancing resilience of national networks.