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When floods hit the road: Resilience to flood-related traffic disruption in the San Francisco Bay Area and beyond

As sea level rises, urban traffic networks in low-lying coastal areas face increasing risks of flood disruptions. Closure of flooded roads causes employee absences and delays, creating cascading impacts to communities. We integrate a traffic model with flood maps that represent potential combination...

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Autores principales: Kasmalkar, Indraneel G., Serafin, Katherine A., Miao, Yufei, Bick, I. Avery, Ortolano, Leonard, Ouyang, Derek, Suckale, Jenny
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Association for the Advancement of Science 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7406370/
https://www.ncbi.nlm.nih.gov/pubmed/32821823
http://dx.doi.org/10.1126/sciadv.aba2423
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author Kasmalkar, Indraneel G.
Serafin, Katherine A.
Miao, Yufei
Bick, I. Avery
Ortolano, Leonard
Ouyang, Derek
Suckale, Jenny
author_facet Kasmalkar, Indraneel G.
Serafin, Katherine A.
Miao, Yufei
Bick, I. Avery
Ortolano, Leonard
Ouyang, Derek
Suckale, Jenny
author_sort Kasmalkar, Indraneel G.
collection PubMed
description As sea level rises, urban traffic networks in low-lying coastal areas face increasing risks of flood disruptions. Closure of flooded roads causes employee absences and delays, creating cascading impacts to communities. We integrate a traffic model with flood maps that represent potential combinations of storm surges, tides, seasonal cycles, interannual anomalies driven by large-scale climate variability such as the El Niño Southern Oscillation, and sea level rise. When identifying inundated roads, we propose corrections for potential biases arising from model integration. Our results for the San Francisco Bay Area show that employee absences are limited to the homes and workplaces within the areas of inundation, while delays propagate far inland. Communities with limited availability of alternate roads experience long delays irrespective of their proximity to the areas of inundation. We show that metric reach, a measure of road network density, is a better proxy for delays than flood exposure.
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spelling pubmed-74063702020-08-19 When floods hit the road: Resilience to flood-related traffic disruption in the San Francisco Bay Area and beyond Kasmalkar, Indraneel G. Serafin, Katherine A. Miao, Yufei Bick, I. Avery Ortolano, Leonard Ouyang, Derek Suckale, Jenny Sci Adv Research Articles As sea level rises, urban traffic networks in low-lying coastal areas face increasing risks of flood disruptions. Closure of flooded roads causes employee absences and delays, creating cascading impacts to communities. We integrate a traffic model with flood maps that represent potential combinations of storm surges, tides, seasonal cycles, interannual anomalies driven by large-scale climate variability such as the El Niño Southern Oscillation, and sea level rise. When identifying inundated roads, we propose corrections for potential biases arising from model integration. Our results for the San Francisco Bay Area show that employee absences are limited to the homes and workplaces within the areas of inundation, while delays propagate far inland. Communities with limited availability of alternate roads experience long delays irrespective of their proximity to the areas of inundation. We show that metric reach, a measure of road network density, is a better proxy for delays than flood exposure. American Association for the Advancement of Science 2020-08-05 /pmc/articles/PMC7406370/ /pubmed/32821823 http://dx.doi.org/10.1126/sciadv.aba2423 Text en Copyright © 2020 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works. Distributed under a Creative Commons Attribution NonCommercial License 4.0 (CC BY-NC). https://creativecommons.org/licenses/by-nc/4.0/ https://creativecommons.org/licenses/by-nc/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution-NonCommercial license (https://creativecommons.org/licenses/by-nc/4.0/) , which permits use, distribution, and reproduction in any medium, so long as the resultant use is not for commercial advantage and provided the original work is properly cited.
spellingShingle Research Articles
Kasmalkar, Indraneel G.
Serafin, Katherine A.
Miao, Yufei
Bick, I. Avery
Ortolano, Leonard
Ouyang, Derek
Suckale, Jenny
When floods hit the road: Resilience to flood-related traffic disruption in the San Francisco Bay Area and beyond
title When floods hit the road: Resilience to flood-related traffic disruption in the San Francisco Bay Area and beyond
title_full When floods hit the road: Resilience to flood-related traffic disruption in the San Francisco Bay Area and beyond
title_fullStr When floods hit the road: Resilience to flood-related traffic disruption in the San Francisco Bay Area and beyond
title_full_unstemmed When floods hit the road: Resilience to flood-related traffic disruption in the San Francisco Bay Area and beyond
title_short When floods hit the road: Resilience to flood-related traffic disruption in the San Francisco Bay Area and beyond
title_sort when floods hit the road: resilience to flood-related traffic disruption in the san francisco bay area and beyond
topic Research Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7406370/
https://www.ncbi.nlm.nih.gov/pubmed/32821823
http://dx.doi.org/10.1126/sciadv.aba2423
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