Assessing the Impact of Climate Change on Transportation Infrastructure Using the Hydrologic-Footprint-Residence Metric
Publication: Journal of Hydrologic Engineering
Volume 26, Issue 5
Abstract
Climate change is likely to increase the frequency and intensity of flooding. Transportation infrastructure is vulnerable to extreme precipitation because it was designed using frequency, duration, and intensity relationships that do not represent future climate. Therefore, there is a need for a better understanding of how future climate can disrupt roadways and bridges. This study proposes evaluating flood impacts on the transportation infrastructure with two novel metrics: the (roads) and (bridges). These metrics were based on the hydrological footprint residence (HFR), which represents the dynamics of the inundation area and its duration. The Hydrologic Engineering Center Hydrologic Modeling System (HEC-HMS) and the Hydrologic Engineering Center River Analysis System (HEC-RAS) one-dimensional/two-dimensional (1D/2D) models were used to calculate the HFR metrics. These metrics were estimated for the transportation infrastructure of San Antonio, Texas, for 24-h 100- and 500-year storms for representative concentration pathway (RCP) 4.5 and 8.5 scenarios. Results show that climate change will increase flood impacts in the city. The new metrics presented a larger relative increase with climate change when compared to traditional metrics, such as maximum flooded areas. This study highlights the importance of using duration components to evaluate flood impacts on transportation infrastructure.
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Data Availability Statement
Some or all data, models, or code that support the findings of this study are available from the corresponding author upon reasonable request.
The following data, models, or code generated or used during the study are available in a repository or online: climate projections from the US Bureau of Reclamation (2013), available at https://gdo-dcp.ucllnl.org/downscaled_cmip_projections/dcpInterface.html; bridges and culverts data from SARA (2020), available at https://d2mr.sara-tx.org/; and georeferenced streets and channels from COSA (2019a), available at https://www.sanantonio.gov/GIS.
LIDAR DEM data was acquired in person from the San Antonio River Authority. Direct requests for these materials may be made to the provider, as indicated in the Acknowledgments.
Acknowledgments
The authors express their thanks and appreciation to the Transportation Consortium of South-Central States (TRANSET) and the City of San Antonio for providing funding. We also thank the San Antonio River Authority for sharing valuable data. We acknowledge the World Climate Research Programme’s Working Group on Coupled Modelling, which is responsible for the CMIP, and we thank the climate modeling groups for producing and making available their model output. For the CMIP, the US Department of Energy’s Program for Climate Model Diagnosis and Intercomparison provides coordinating support, and it also led the development of software infrastructure in partnership with the Global Organization for Earth System Science Portals.
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Published In
Journal of Hydrologic Engineering
Volume 26 • Issue 5 • May 2021
Copyright
© 2021 American Society of Civil Engineers.
History
Received: Jul 28, 2020
Accepted: Dec 14, 2020
Published online: Mar 12, 2021
Published in print: May 1, 2021
Discussion open until: Aug 12, 2021
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