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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...

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Autores principales: Schaperow, Jacob R., Li, Dongyue, Margulis, Steven A., Lettenmaier, Dennis P.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2021
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.
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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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