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Adaptation and Resilience of Roads to Extreme Hydrological Events

8 pagesPublished: September 20, 2018

Abstract

Road infrastructure networks are exposed to multiple damages caused by the occurrence of floods, generally, associated to hydrometeorological extreme phenomena. This can be attributed to the lack of drainage efficiency in the current designed hydraulic infrastructure. In order to renew the current methodologies for designing and improving the performance of road drainage, we proposed an approach that allows to revise the road drainage under current and future climate scenarios. For this, digital elevation information combined with a simplified shallow water equations model were used to reproduce the transversal flows to a highway located in the state of Oaxaca, Mexico. The drainage performance for both scenarios was tested along a set of identified critical points of the highway, and in those locations where hydrological design showed to be insufficient, adaptation measures were provided. This approach proved to be scalable and useful for identifying points where road drainage redesign or adaptation were needed and, to prioritize actions that minimize direct and indirect damages on roads.

Keyphrases: drainage design, flood, modeling, roads

In: Goffredo La Loggia, Gabriele Freni, Valeria Puleo and Mauro De Marchis (editors). HIC 2018. 13th International Conference on Hydroinformatics, vol 3, pages 1252-1259.

BibTeX entry
@inproceedings{HIC2018:Adaptation_Resilience_Roads_Extreme,
  author    = {Marco López and Adrian Pedrozo Acuña and José Agustín Breña Naranjo},
  title     = {Adaptation and Resilience of Roads to Extreme Hydrological Events},
  booktitle = {HIC 2018. 13th International Conference on Hydroinformatics},
  editor    = {Goffredo La Loggia and Gabriele Freni and Valeria Puleo and Mauro De Marchis},
  series    = {EPiC Series in Engineering},
  volume    = {3},
  publisher = {EasyChair},
  bibsource = {EasyChair, https://easychair.org},
  issn      = {2516-2330},
  url       = {/publications/paper/bwFj},
  doi       = {10.29007/5qgh},
  pages     = {1252-1259},
  year      = {2018}}
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