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A near-global, high resolution land surface parameter dataset for the variable infiltration capacity model
Hydrologic models predict the spatial and temporal distribution of water and energy at the land surface. Currently, parameter availability limits global-scale hydrologic modelling to very coarse resolution, hindering researchers from resolving fine-scale variability. With the aim of addressing this...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8357956/ https://www.ncbi.nlm.nih.gov/pubmed/34381058 http://dx.doi.org/10.1038/s41597-021-00999-4 |
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author | Schaperow, Jacob R. Li, Dongyue Margulis, Steven A. Lettenmaier, Dennis P. |
author_facet | Schaperow, Jacob R. Li, Dongyue Margulis, Steven A. Lettenmaier, Dennis P. |
author_sort | Schaperow, Jacob R. |
collection | PubMed |
description | Hydrologic models predict the spatial and temporal distribution of water and energy at the land surface. Currently, parameter availability limits global-scale hydrologic modelling to very coarse resolution, hindering researchers from resolving fine-scale variability. With the aim of addressing this problem, we present a set of globally consistent soil and vegetation parameters for the Variable Infiltration Capacity (VIC) model at 1/16° resolution (approximately 6 km at the equator), with spatial coverage from 60°S to 85°N. Soil parameters derived from interpolated soil profiles and vegetation parameters estimated from space-based MODIS measurements have been compiled into input files for both the Classic and Image drivers of the VIC model, version 5. Geographical subsetting codes are provided, as well. Our dataset provides all necessary land surface parameters to run the VIC model at regional to global scale. We evaluate VICGlobal’s ability to simulate the water balance in the Upper Colorado River basin and 12 smaller basins in the CONUS, and their ability to simulate the radiation budget at six SURFRAD stations in the CONUS. |
format | Online Article Text |
id | pubmed-8357956 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-83579562021-08-30 A near-global, high resolution land surface parameter dataset for the variable infiltration capacity model Schaperow, Jacob R. Li, Dongyue Margulis, Steven A. Lettenmaier, Dennis P. Sci Data Data Descriptor Hydrologic models predict the spatial and temporal distribution of water and energy at the land surface. Currently, parameter availability limits global-scale hydrologic modelling to very coarse resolution, hindering researchers from resolving fine-scale variability. With the aim of addressing this problem, we present a set of globally consistent soil and vegetation parameters for the Variable Infiltration Capacity (VIC) model at 1/16° resolution (approximately 6 km at the equator), with spatial coverage from 60°S to 85°N. Soil parameters derived from interpolated soil profiles and vegetation parameters estimated from space-based MODIS measurements have been compiled into input files for both the Classic and Image drivers of the VIC model, version 5. Geographical subsetting codes are provided, as well. Our dataset provides all necessary land surface parameters to run the VIC model at regional to global scale. We evaluate VICGlobal’s ability to simulate the water balance in the Upper Colorado River basin and 12 smaller basins in the CONUS, and their ability to simulate the radiation budget at six SURFRAD stations in the CONUS. Nature Publishing Group UK 2021-08-11 /pmc/articles/PMC8357956/ /pubmed/34381058 http://dx.doi.org/10.1038/s41597-021-00999-4 Text en © The Author(s) 2021 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 Schaperow, Jacob R. Li, Dongyue Margulis, Steven A. Lettenmaier, Dennis P. A near-global, high resolution land surface parameter dataset for the variable infiltration capacity model |
title | A near-global, high resolution land surface parameter dataset for the variable infiltration capacity model |
title_full | A near-global, high resolution land surface parameter dataset for the variable infiltration capacity model |
title_fullStr | A near-global, high resolution land surface parameter dataset for the variable infiltration capacity model |
title_full_unstemmed | A near-global, high resolution land surface parameter dataset for the variable infiltration capacity model |
title_short | A near-global, high resolution land surface parameter dataset for the variable infiltration capacity model |
title_sort | near-global, high resolution land surface parameter dataset for the variable infiltration capacity model |
topic | Data Descriptor |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8357956/ https://www.ncbi.nlm.nih.gov/pubmed/34381058 http://dx.doi.org/10.1038/s41597-021-00999-4 |
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