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GLOBathy, the global lakes bathymetry dataset
Waterbodies (natural lakes and reservoirs) are a critical part of a watershed’s ecological and hydrological balance, and in many cases dictate the downstream river flows either through natural attenuation or through managed controls. Investigating waterbody dynamics relies primarily on understanding...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8814159/ https://www.ncbi.nlm.nih.gov/pubmed/35115560 http://dx.doi.org/10.1038/s41597-022-01132-9 |
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author | Khazaei, Bahram Read, Laura K. Casali, Matthew Sampson, Kevin M. Yates, David N. |
author_facet | Khazaei, Bahram Read, Laura K. Casali, Matthew Sampson, Kevin M. Yates, David N. |
author_sort | Khazaei, Bahram |
collection | PubMed |
description | Waterbodies (natural lakes and reservoirs) are a critical part of a watershed’s ecological and hydrological balance, and in many cases dictate the downstream river flows either through natural attenuation or through managed controls. Investigating waterbody dynamics relies primarily on understanding their morphology and geophysical characteristics that are primarily defined by bathymetry. Bathymetric conditions define stage-storage relationships and circulation/transport processes in waterbodies. Yet many studies oversimplify these mechanisms due to unavailability of the bathymetric data. We developed a novel GLObal Bathymetric (GLOBathy) dataset of 1.4+ million waterbodies to align with the well-established global dataset, HydroLAKES. GLOBathy uses a GIS-based framework to generate bathymetric maps based on the waterbody maximum depth estimates and HydroLAKES geometric/geophysical attributes of the waterbodies. The maximum depth estimates are validated at 1,503 waterbodies, making use of several observed data sources. We also provide estimations for head-Area-Volume (h-A-V) relationships of the HydroLAKES waterbodies, driven from the bathymetric maps of the GLOBathy dataset. The h-A-V relationships provide essential information for water balance and hydrological studies of global waterbody systems. |
format | Online Article Text |
id | pubmed-8814159 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-88141592022-02-16 GLOBathy, the global lakes bathymetry dataset Khazaei, Bahram Read, Laura K. Casali, Matthew Sampson, Kevin M. Yates, David N. Sci Data Data Descriptor Waterbodies (natural lakes and reservoirs) are a critical part of a watershed’s ecological and hydrological balance, and in many cases dictate the downstream river flows either through natural attenuation or through managed controls. Investigating waterbody dynamics relies primarily on understanding their morphology and geophysical characteristics that are primarily defined by bathymetry. Bathymetric conditions define stage-storage relationships and circulation/transport processes in waterbodies. Yet many studies oversimplify these mechanisms due to unavailability of the bathymetric data. We developed a novel GLObal Bathymetric (GLOBathy) dataset of 1.4+ million waterbodies to align with the well-established global dataset, HydroLAKES. GLOBathy uses a GIS-based framework to generate bathymetric maps based on the waterbody maximum depth estimates and HydroLAKES geometric/geophysical attributes of the waterbodies. The maximum depth estimates are validated at 1,503 waterbodies, making use of several observed data sources. We also provide estimations for head-Area-Volume (h-A-V) relationships of the HydroLAKES waterbodies, driven from the bathymetric maps of the GLOBathy dataset. The h-A-V relationships provide essential information for water balance and hydrological studies of global waterbody systems. Nature Publishing Group UK 2022-02-03 /pmc/articles/PMC8814159/ /pubmed/35115560 http://dx.doi.org/10.1038/s41597-022-01132-9 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) applies to the metadata files associated with this article. |
spellingShingle | Data Descriptor Khazaei, Bahram Read, Laura K. Casali, Matthew Sampson, Kevin M. Yates, David N. GLOBathy, the global lakes bathymetry dataset |
title | GLOBathy, the global lakes bathymetry dataset |
title_full | GLOBathy, the global lakes bathymetry dataset |
title_fullStr | GLOBathy, the global lakes bathymetry dataset |
title_full_unstemmed | GLOBathy, the global lakes bathymetry dataset |
title_short | GLOBathy, the global lakes bathymetry dataset |
title_sort | globathy, the global lakes bathymetry dataset |
topic | Data Descriptor |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8814159/ https://www.ncbi.nlm.nih.gov/pubmed/35115560 http://dx.doi.org/10.1038/s41597-022-01132-9 |
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