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Global rainfall erosivity assessment based on high-temporal resolution rainfall records

The exposure of the Earth’s surface to the energetic input of rainfall is one of the key factors controlling water erosion. While water erosion is identified as the most serious cause of soil degradation globally, global patterns of rainfall erosivity remain poorly quantified and estimates have larg...

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Autores principales: Panagos, Panos, Borrelli, Pasquale, Meusburger, Katrin, Yu, Bofu, Klik, Andreas, Jae Lim, Kyoung, Yang, Jae E., Ni, Jinren, Miao, Chiyuan, Chattopadhyay, Nabansu, Sadeghi, Seyed Hamidreza, Hazbavi, Zeinab, Zabihi, Mohsen, Larionov, Gennady A., Krasnov, Sergey F., Gorobets, Andrey V., Levi, Yoav, Erpul, Gunay, Birkel, Christian, Hoyos, Natalia, Naipal, Victoria, Oliveira, Paulo Tarso S., Bonilla, Carlos A., Meddi, Mohamed, Nel, Werner, Al Dashti, Hassan, Boni, Martino, Diodato, Nazzareno, Van Oost, Kristof, Nearing, Mark, Ballabio, Cristiano
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5482877/
https://www.ncbi.nlm.nih.gov/pubmed/28646132
http://dx.doi.org/10.1038/s41598-017-04282-8
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author Panagos, Panos
Borrelli, Pasquale
Meusburger, Katrin
Yu, Bofu
Klik, Andreas
Jae Lim, Kyoung
Yang, Jae E.
Ni, Jinren
Miao, Chiyuan
Chattopadhyay, Nabansu
Sadeghi, Seyed Hamidreza
Hazbavi, Zeinab
Zabihi, Mohsen
Larionov, Gennady A.
Krasnov, Sergey F.
Gorobets, Andrey V.
Levi, Yoav
Erpul, Gunay
Birkel, Christian
Hoyos, Natalia
Naipal, Victoria
Oliveira, Paulo Tarso S.
Bonilla, Carlos A.
Meddi, Mohamed
Nel, Werner
Al Dashti, Hassan
Boni, Martino
Diodato, Nazzareno
Van Oost, Kristof
Nearing, Mark
Ballabio, Cristiano
author_facet Panagos, Panos
Borrelli, Pasquale
Meusburger, Katrin
Yu, Bofu
Klik, Andreas
Jae Lim, Kyoung
Yang, Jae E.
Ni, Jinren
Miao, Chiyuan
Chattopadhyay, Nabansu
Sadeghi, Seyed Hamidreza
Hazbavi, Zeinab
Zabihi, Mohsen
Larionov, Gennady A.
Krasnov, Sergey F.
Gorobets, Andrey V.
Levi, Yoav
Erpul, Gunay
Birkel, Christian
Hoyos, Natalia
Naipal, Victoria
Oliveira, Paulo Tarso S.
Bonilla, Carlos A.
Meddi, Mohamed
Nel, Werner
Al Dashti, Hassan
Boni, Martino
Diodato, Nazzareno
Van Oost, Kristof
Nearing, Mark
Ballabio, Cristiano
author_sort Panagos, Panos
collection PubMed
description The exposure of the Earth’s surface to the energetic input of rainfall is one of the key factors controlling water erosion. While water erosion is identified as the most serious cause of soil degradation globally, global patterns of rainfall erosivity remain poorly quantified and estimates have large uncertainties. This hampers the implementation of effective soil degradation mitigation and restoration strategies. Quantifying rainfall erosivity is challenging as it requires high temporal resolution(<30 min) and high fidelity rainfall recordings. We present the results of an extensive global data collection effort whereby we estimated rainfall erosivity for 3,625 stations covering 63 countries. This first ever Global Rainfall Erosivity Database was used to develop a global erosivity map at 30 arc-seconds(~1 km) based on a Gaussian Process Regression(GPR). Globally, the mean rainfall erosivity was estimated to be 2,190 MJ mm ha(−1) h(−1) yr(−1), with the highest values in South America and the Caribbean countries, Central east Africa and South east Asia. The lowest values are mainly found in Canada, the Russian Federation, Northern Europe, Northern Africa and the Middle East. The tropical climate zone has the highest mean rainfall erosivity followed by the temperate whereas the lowest mean was estimated in the cold climate zone.
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spelling pubmed-54828772017-06-26 Global rainfall erosivity assessment based on high-temporal resolution rainfall records Panagos, Panos Borrelli, Pasquale Meusburger, Katrin Yu, Bofu Klik, Andreas Jae Lim, Kyoung Yang, Jae E. Ni, Jinren Miao, Chiyuan Chattopadhyay, Nabansu Sadeghi, Seyed Hamidreza Hazbavi, Zeinab Zabihi, Mohsen Larionov, Gennady A. Krasnov, Sergey F. Gorobets, Andrey V. Levi, Yoav Erpul, Gunay Birkel, Christian Hoyos, Natalia Naipal, Victoria Oliveira, Paulo Tarso S. Bonilla, Carlos A. Meddi, Mohamed Nel, Werner Al Dashti, Hassan Boni, Martino Diodato, Nazzareno Van Oost, Kristof Nearing, Mark Ballabio, Cristiano Sci Rep Article The exposure of the Earth’s surface to the energetic input of rainfall is one of the key factors controlling water erosion. While water erosion is identified as the most serious cause of soil degradation globally, global patterns of rainfall erosivity remain poorly quantified and estimates have large uncertainties. This hampers the implementation of effective soil degradation mitigation and restoration strategies. Quantifying rainfall erosivity is challenging as it requires high temporal resolution(<30 min) and high fidelity rainfall recordings. We present the results of an extensive global data collection effort whereby we estimated rainfall erosivity for 3,625 stations covering 63 countries. This first ever Global Rainfall Erosivity Database was used to develop a global erosivity map at 30 arc-seconds(~1 km) based on a Gaussian Process Regression(GPR). Globally, the mean rainfall erosivity was estimated to be 2,190 MJ mm ha(−1) h(−1) yr(−1), with the highest values in South America and the Caribbean countries, Central east Africa and South east Asia. The lowest values are mainly found in Canada, the Russian Federation, Northern Europe, Northern Africa and the Middle East. The tropical climate zone has the highest mean rainfall erosivity followed by the temperate whereas the lowest mean was estimated in the cold climate zone. Nature Publishing Group UK 2017-06-23 /pmc/articles/PMC5482877/ /pubmed/28646132 http://dx.doi.org/10.1038/s41598-017-04282-8 Text en © The Author(s) 2017 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/.
spellingShingle Article
Panagos, Panos
Borrelli, Pasquale
Meusburger, Katrin
Yu, Bofu
Klik, Andreas
Jae Lim, Kyoung
Yang, Jae E.
Ni, Jinren
Miao, Chiyuan
Chattopadhyay, Nabansu
Sadeghi, Seyed Hamidreza
Hazbavi, Zeinab
Zabihi, Mohsen
Larionov, Gennady A.
Krasnov, Sergey F.
Gorobets, Andrey V.
Levi, Yoav
Erpul, Gunay
Birkel, Christian
Hoyos, Natalia
Naipal, Victoria
Oliveira, Paulo Tarso S.
Bonilla, Carlos A.
Meddi, Mohamed
Nel, Werner
Al Dashti, Hassan
Boni, Martino
Diodato, Nazzareno
Van Oost, Kristof
Nearing, Mark
Ballabio, Cristiano
Global rainfall erosivity assessment based on high-temporal resolution rainfall records
title Global rainfall erosivity assessment based on high-temporal resolution rainfall records
title_full Global rainfall erosivity assessment based on high-temporal resolution rainfall records
title_fullStr Global rainfall erosivity assessment based on high-temporal resolution rainfall records
title_full_unstemmed Global rainfall erosivity assessment based on high-temporal resolution rainfall records
title_short Global rainfall erosivity assessment based on high-temporal resolution rainfall records
title_sort global rainfall erosivity assessment based on high-temporal resolution rainfall records
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5482877/
https://www.ncbi.nlm.nih.gov/pubmed/28646132
http://dx.doi.org/10.1038/s41598-017-04282-8
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