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Tracking the weight of Hurricane Harvey’s stormwater using GPS data
On 26 August 2017, Hurricane Harvey struck the Gulf Coast as a category four cyclone depositing ~95 km(3) of water, making it the wettest cyclone in U.S. history. Water left in Harvey’s wake should cause elastic loading and subsidence of Earth’s crust, and uplift as it drains into the ocean and evap...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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American Association for the Advancement of Science
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6155028/ https://www.ncbi.nlm.nih.gov/pubmed/30255155 http://dx.doi.org/10.1126/sciadv.aau2477 |
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author | Milliner, Chris Materna, Kathryn Bürgmann, Roland Fu, Yuning Moore, Angelyn W. Bekaert, David Adhikari, Surendra Argus, Donald F. |
author_facet | Milliner, Chris Materna, Kathryn Bürgmann, Roland Fu, Yuning Moore, Angelyn W. Bekaert, David Adhikari, Surendra Argus, Donald F. |
author_sort | Milliner, Chris |
collection | PubMed |
description | On 26 August 2017, Hurricane Harvey struck the Gulf Coast as a category four cyclone depositing ~95 km(3) of water, making it the wettest cyclone in U.S. history. Water left in Harvey’s wake should cause elastic loading and subsidence of Earth’s crust, and uplift as it drains into the ocean and evaporates. To track daily changes of transient water storage, we use Global Positioning System (GPS) measurements, finding a clear migration of subsidence (up to 21 mm) and horizontal motion (up to 4 mm) across the Gulf Coast, followed by gradual uplift over a 5-week period. Inversion of these data shows that a third of Harvey’s total stormwater was captured on land (25.7 ± 3.0 km(3)), indicating that the rest drained rapidly into the ocean at a rate of 8.2 km(3)/day, with the remaining stored water gradually lost over the following 5 weeks at ~1 km(3)/day, primarily by evapotranspiration. These results indicate that GPS networks can remotely track the spatial extent and daily evolution of terrestrial water storage following transient, extreme precipitation events, with implications for improving operational flood forecasts and understanding the response of drainage systems to large influxes of water. |
format | Online Article Text |
id | pubmed-6155028 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | American Association for the Advancement of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-61550282018-09-25 Tracking the weight of Hurricane Harvey’s stormwater using GPS data Milliner, Chris Materna, Kathryn Bürgmann, Roland Fu, Yuning Moore, Angelyn W. Bekaert, David Adhikari, Surendra Argus, Donald F. Sci Adv Research Articles On 26 August 2017, Hurricane Harvey struck the Gulf Coast as a category four cyclone depositing ~95 km(3) of water, making it the wettest cyclone in U.S. history. Water left in Harvey’s wake should cause elastic loading and subsidence of Earth’s crust, and uplift as it drains into the ocean and evaporates. To track daily changes of transient water storage, we use Global Positioning System (GPS) measurements, finding a clear migration of subsidence (up to 21 mm) and horizontal motion (up to 4 mm) across the Gulf Coast, followed by gradual uplift over a 5-week period. Inversion of these data shows that a third of Harvey’s total stormwater was captured on land (25.7 ± 3.0 km(3)), indicating that the rest drained rapidly into the ocean at a rate of 8.2 km(3)/day, with the remaining stored water gradually lost over the following 5 weeks at ~1 km(3)/day, primarily by evapotranspiration. These results indicate that GPS networks can remotely track the spatial extent and daily evolution of terrestrial water storage following transient, extreme precipitation events, with implications for improving operational flood forecasts and understanding the response of drainage systems to large influxes of water. American Association for the Advancement of Science 2018-09-19 /pmc/articles/PMC6155028/ /pubmed/30255155 http://dx.doi.org/10.1126/sciadv.aau2477 Text en Copyright © 2018 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). http://creativecommons.org/licenses/by-nc/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution-NonCommercial license (http://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 Milliner, Chris Materna, Kathryn Bürgmann, Roland Fu, Yuning Moore, Angelyn W. Bekaert, David Adhikari, Surendra Argus, Donald F. Tracking the weight of Hurricane Harvey’s stormwater using GPS data |
title | Tracking the weight of Hurricane Harvey’s stormwater using GPS data |
title_full | Tracking the weight of Hurricane Harvey’s stormwater using GPS data |
title_fullStr | Tracking the weight of Hurricane Harvey’s stormwater using GPS data |
title_full_unstemmed | Tracking the weight of Hurricane Harvey’s stormwater using GPS data |
title_short | Tracking the weight of Hurricane Harvey’s stormwater using GPS data |
title_sort | tracking the weight of hurricane harvey’s stormwater using gps data |
topic | Research Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6155028/ https://www.ncbi.nlm.nih.gov/pubmed/30255155 http://dx.doi.org/10.1126/sciadv.aau2477 |
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