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A Chinese soil conservation dataset preventing soil water erosion from 1992 to 2019
Soil conservation service (SC) is defined as the ability of terrestrial ecosystems to control soil erosion and protect soil function. A long-term and high-resolution estimation of SC is urgent for ecological assessment and land management on a large scale. Here, a 300-m resolution Chinese soil conse...
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/PMC10220090/ https://www.ncbi.nlm.nih.gov/pubmed/37236982 http://dx.doi.org/10.1038/s41597-023-02246-4 |
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author | Li, Jialei He, Hongbin Zeng, Qinghua Chen, Liding Sun, Ranhao |
author_facet | Li, Jialei He, Hongbin Zeng, Qinghua Chen, Liding Sun, Ranhao |
author_sort | Li, Jialei |
collection | PubMed |
description | Soil conservation service (SC) is defined as the ability of terrestrial ecosystems to control soil erosion and protect soil function. A long-term and high-resolution estimation of SC is urgent for ecological assessment and land management on a large scale. Here, a 300-m resolution Chinese soil conservation dataset (CSCD) from 1992 to 2019, for the first time, is established based on the Revised Universal Soil Loss Equation (RUSLE) model. The RUSLE modelling was conducted based on five key parameters, including the rainfall erosivity (interpolation of daily rainfall), land cover management (provincial data), conservation practices (weighted by terrain and crop types), topography (30 m), and soil properties (250 m). The dataset agrees with previous measurements in all basins (R(2) > 0.5) and other regional simulations. Compared with current studies, the dataset has long-term, large-scale, and relatively high-resolution characteristics. This dataset will serve as a base to open out the mechanism of SC variations in China and could help assess the ecological effects of land management policies. |
format | Online Article Text |
id | pubmed-10220090 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-102200902023-05-28 A Chinese soil conservation dataset preventing soil water erosion from 1992 to 2019 Li, Jialei He, Hongbin Zeng, Qinghua Chen, Liding Sun, Ranhao Sci Data Data Descriptor Soil conservation service (SC) is defined as the ability of terrestrial ecosystems to control soil erosion and protect soil function. A long-term and high-resolution estimation of SC is urgent for ecological assessment and land management on a large scale. Here, a 300-m resolution Chinese soil conservation dataset (CSCD) from 1992 to 2019, for the first time, is established based on the Revised Universal Soil Loss Equation (RUSLE) model. The RUSLE modelling was conducted based on five key parameters, including the rainfall erosivity (interpolation of daily rainfall), land cover management (provincial data), conservation practices (weighted by terrain and crop types), topography (30 m), and soil properties (250 m). The dataset agrees with previous measurements in all basins (R(2) > 0.5) and other regional simulations. Compared with current studies, the dataset has long-term, large-scale, and relatively high-resolution characteristics. This dataset will serve as a base to open out the mechanism of SC variations in China and could help assess the ecological effects of land management policies. Nature Publishing Group UK 2023-05-26 /pmc/articles/PMC10220090/ /pubmed/37236982 http://dx.doi.org/10.1038/s41597-023-02246-4 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 Li, Jialei He, Hongbin Zeng, Qinghua Chen, Liding Sun, Ranhao A Chinese soil conservation dataset preventing soil water erosion from 1992 to 2019 |
title | A Chinese soil conservation dataset preventing soil water erosion from 1992 to 2019 |
title_full | A Chinese soil conservation dataset preventing soil water erosion from 1992 to 2019 |
title_fullStr | A Chinese soil conservation dataset preventing soil water erosion from 1992 to 2019 |
title_full_unstemmed | A Chinese soil conservation dataset preventing soil water erosion from 1992 to 2019 |
title_short | A Chinese soil conservation dataset preventing soil water erosion from 1992 to 2019 |
title_sort | chinese soil conservation dataset preventing soil water erosion from 1992 to 2019 |
topic | Data Descriptor |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10220090/ https://www.ncbi.nlm.nih.gov/pubmed/37236982 http://dx.doi.org/10.1038/s41597-023-02246-4 |
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