A River Flood and Earthquake Risk Assessment of Railway Assets along the Belt and Road

Mitigating the disaster risk of transportation infrastructure networks along the Belt and Road is crucial to realizing the area’s high trade potential in the future.This study assessed the exposure and risk of existing and planned railway assets to river flooding and earthquakes.We found that about 9.3%of these railway assets are exposed to a one in 100 year flood event,and 22.3%are exposed to a one in 475 year earthquake event.The combined flood and earthquake risk of physical damage to railway assets,expressed by expected annual damage(EAD),is estimated at USD 1438(between 966 and 2026)million.Floods contribute the majority of the risk(96%).China has the highest EAD for both floods and earthquakes(between USD 240 and 525 million in total).Laos and Cambodia are the countries with the highest EAD per km from flooding(USD 66,125–112,154 and USD 31,954–56,844 per km,respectively),while Italy and Myanmar have the highest EAD per km from earthquakes(USD 1000–3057 and USD 893–3019 per km,respectively).For the newly built and planned projects along the Belt and Road,the EAD is estimated at USD 271(between 205 and 357)million.The China–Indochina Peninsula Economic Corridor and China–Pakistan Economic Corridor have the highest absolute EAD and EAD per km,with EADs reaching USD 95 and USD 67 million,and USD 18 and USD 17 thousand per km,on average,respectively.For railway segments with high risks,we found that if the required adaptation cost within 20 years to realize a 10%increase of the railway quality is below 8.4%of the replacement cost,the benefits are positive.

Seismic Risk Assessment of the Railway Network of China’s Mainland

Earthquakes pose a great risk to railway systems and services around the world.In China alone,earthquakes caused 88 rail service disruptions between 2012 and 2019.Here,we present a first-of-its-kind methodology to analyze the seismic risk of a railway system using an empirically derived train service fragility curve.We demonstrate our methodology using the Chinese railway system.In doing so,we generate a set of stochastic earthquake scenarios for China based on a national-scale seismicity model.Using disruption records,we construct an empirically grounded fragility curve that relates the failure probability of train services to peak ground acceleration.By combining the simulated earthquakes,the fragility curve,and empirical train flow data from 2016,we quantitatively assess the seismic impact and the risk faced by the Chinese railway system.The maximum train trip loss could reach 2400 trips in response to a single seismic event,accounting for 34%of the national daily train trips.Due to the spatially uneven daily train flow and seismicity distribution,the seismic impact on the railway system in different seismic zones is highly heterogeneous and does not always increase when the hazard intensity increases.More specifically,the results show that the railway lines located in the Qinghai-Tibet and Xinjiang seismic zones exhibit the highest risk.The generated impact curves and the risk map provide a basis for railway planning and risk management decisions.

Risk of Tropical Cyclones and Floods to Power Grids in Southeast and East Asia

Power grids play a critical role in modern society, serving as the lifeline of a well-functioning economy. This article presents a first large-scale study on the risk estimation of tropical cyclone(TC)-induced winds and coastal floods, which can widely impact power grids in Southeast and East Asia. Our comprehensive risk model incorporates detailed infrastructure data from OpenStreetMap(OSM) and government power grid maps, along with global hazard maps and vulnerability curves. The results reveal that the estimated expected annual damages from TCs and coastal floods to OSM-mapped assets account for approximately 0.07%(0.00–0.38%) and 0.02%(0.00–0.02%) of the total GDP of the study area, respectively. We analyzed the main sources of uncertainty in the risk model and emphasized the importance of understanding asset vulnerability.These results highlight the urgent need to strengthen power infrastructure to withstand the impacts of natural hazards, and the significance of reliable risk information for improving power grid design and planning. Focusing on developing more region-specific infrastructure data and vulnerability curves will improve the accuracy of risk estimation and provide valuable insights not only for the electricity sector but also for customers of other infrastructure systems that heavily rely on a stable supply of electricity.