Abstract
Transportation infrastructures are generally designed to have multi-decadal service lives. Transport infrastructure design, however, is largely based on historical conditions. Yet, in the face of global warming, we are likely going to experience more intense and frequent extreme events, which may put infrastructure at severe risk. In this study, we comprehensively analyze the exposure of road and railway infrastructure assets to changes in precipitation return periods globally. Under ~2 degrees of warming in mid-century (RCP 8.5 scenario), 43.6% of the global transportation assets are expected to experience at least a 25% decrease in design return period of extreme rainfall (a 33% increase in exceedance probability), which may increase to 69.9% under ~4 degrees of warming by late-21st century. To accommodate for such increases, we propose to incorporate a safety factor for climate change adaptation during the transportation infrastructure design process to ensure transportation assets will maintain their designed risk level in the future. Our results show that a safety factor of 1.2 would work sufficient for most regions of the world for quick design process calculations following the RCP4.5 path.
| Original language | English |
|---|---|
| Article number | 2541 |
| Pages (from-to) | 1-9 |
| Number of pages | 9 |
| Journal | Nature Communications |
| Volume | 14 |
| DOIs | |
| Publication status | Published - 3 May 2023 |
Bibliographical note
Funding Information:This work was supported by the National Natural Science Foundation of China [grant number 41771538]. The financial support is highly appreciated. Climate scenarios used were from the NEX-GDDP dataset, prepared by the Climate Analytics Group and NASA Ames Research Center using the NASA Earth Exchange, and distributed by the NASA Center for Climate Simulation (NCCS). The data support is highly appreciated.
Funding Information:
This work was supported by the National Natural Science Foundation of China [grant number 41771538]. The financial support is highly appreciated. Climate scenarios used were from the NEX-GDDP dataset, prepared by the Climate Analytics Group and NASA Ames Research Center using the NASA Earth Exchange, and distributed by the NASA Center for Climate Simulation (NCCS). The data support is highly appreciated.
Publisher Copyright:
© 2023, The Author(s).
Funding
This work was supported by the National Natural Science Foundation of China [grant number 41771538]. The financial support is highly appreciated. Climate scenarios used were from the NEX-GDDP dataset, prepared by the Climate Analytics Group and NASA Ames Research Center using the NASA Earth Exchange, and distributed by the NASA Center for Climate Simulation (NCCS). The data support is highly appreciated. This work was supported by the National Natural Science Foundation of China [grant number 41771538]. The financial support is highly appreciated. Climate scenarios used were from the NEX-GDDP dataset, prepared by the Climate Analytics Group and NASA Ames Research Center using the NASA Earth Exchange, and distributed by the NASA Center for Climate Simulation (NCCS). The data support is highly appreciated.
