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Caravan - A global community dataset for large-sample hydrology
High-quality datasets are essential to support hydrological science and modeling. Several CAMELS (Catchment Attributes and Meteorology for Large-sample Studies) datasets exist for specific countries or regions, however these datasets lack standardization, which makes global studies difficult. This p...
Autores principales: | , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9887008/ https://www.ncbi.nlm.nih.gov/pubmed/36717577 http://dx.doi.org/10.1038/s41597-023-01975-w |
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author | Kratzert, Frederik Nearing, Grey Addor, Nans Erickson, Tyler Gauch, Martin Gilon, Oren Gudmundsson, Lukas Hassidim, Avinatan Klotz, Daniel Nevo, Sella Shalev, Guy Matias, Yossi |
author_facet | Kratzert, Frederik Nearing, Grey Addor, Nans Erickson, Tyler Gauch, Martin Gilon, Oren Gudmundsson, Lukas Hassidim, Avinatan Klotz, Daniel Nevo, Sella Shalev, Guy Matias, Yossi |
author_sort | Kratzert, Frederik |
collection | PubMed |
description | High-quality datasets are essential to support hydrological science and modeling. Several CAMELS (Catchment Attributes and Meteorology for Large-sample Studies) datasets exist for specific countries or regions, however these datasets lack standardization, which makes global studies difficult. This paper introduces a dataset called Caravan (a series of CAMELS) that standardizes and aggregates seven existing large-sample hydrology datasets. Caravan includes meteorological forcing data, streamflow data, and static catchment attributes (e.g., geophysical, sociological, climatological) for 6830 catchments. Most importantly, Caravan is both a dataset and open-source software that allows members of the hydrology community to extend the dataset to new locations by extracting forcing data and catchment attributes in the cloud. Our vision is for Caravan to democratize the creation and use of globally-standardized large-sample hydrology datasets. Caravan is a truly global open-source community resource. |
format | Online Article Text |
id | pubmed-9887008 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-98870082023-02-01 Caravan - A global community dataset for large-sample hydrology Kratzert, Frederik Nearing, Grey Addor, Nans Erickson, Tyler Gauch, Martin Gilon, Oren Gudmundsson, Lukas Hassidim, Avinatan Klotz, Daniel Nevo, Sella Shalev, Guy Matias, Yossi Sci Data Data Descriptor High-quality datasets are essential to support hydrological science and modeling. Several CAMELS (Catchment Attributes and Meteorology for Large-sample Studies) datasets exist for specific countries or regions, however these datasets lack standardization, which makes global studies difficult. This paper introduces a dataset called Caravan (a series of CAMELS) that standardizes and aggregates seven existing large-sample hydrology datasets. Caravan includes meteorological forcing data, streamflow data, and static catchment attributes (e.g., geophysical, sociological, climatological) for 6830 catchments. Most importantly, Caravan is both a dataset and open-source software that allows members of the hydrology community to extend the dataset to new locations by extracting forcing data and catchment attributes in the cloud. Our vision is for Caravan to democratize the creation and use of globally-standardized large-sample hydrology datasets. Caravan is a truly global open-source community resource. Nature Publishing Group UK 2023-01-31 /pmc/articles/PMC9887008/ /pubmed/36717577 http://dx.doi.org/10.1038/s41597-023-01975-w Text en © The Author(s) 2023 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/) . |
spellingShingle | Data Descriptor Kratzert, Frederik Nearing, Grey Addor, Nans Erickson, Tyler Gauch, Martin Gilon, Oren Gudmundsson, Lukas Hassidim, Avinatan Klotz, Daniel Nevo, Sella Shalev, Guy Matias, Yossi Caravan - A global community dataset for large-sample hydrology |
title | Caravan - A global community dataset for large-sample hydrology |
title_full | Caravan - A global community dataset for large-sample hydrology |
title_fullStr | Caravan - A global community dataset for large-sample hydrology |
title_full_unstemmed | Caravan - A global community dataset for large-sample hydrology |
title_short | Caravan - A global community dataset for large-sample hydrology |
title_sort | caravan - a global community dataset for large-sample hydrology |
topic | Data Descriptor |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9887008/ https://www.ncbi.nlm.nih.gov/pubmed/36717577 http://dx.doi.org/10.1038/s41597-023-01975-w |
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