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

Abstract 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...

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Autores principales: Panos Panagos, Pasquale Borrelli, Katrin Meusburger, Bofu Yu, Andreas Klik, Kyoung Jae Lim, Jae E. Yang, Jinren Ni, Chiyuan Miao, Nabansu Chattopadhyay, Seyed Hamidreza Sadeghi, Zeinab Hazbavi, Mohsen Zabihi, Gennady A. Larionov, Sergey F. Krasnov, Andrey V. Gorobets, Yoav Levi, Gunay Erpul, Christian Birkel, Natalia Hoyos, Victoria Naipal, Paulo Tarso S. Oliveira, Carlos A. Bonilla, Mohamed Meddi, Werner Nel, Hassan Al Dashti, Martino Boni, Nazzareno Diodato, Kristof Van Oost, Mark Nearing, Cristiano Ballabio
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Publicado: Nature Portfolio 2017
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Acceso en línea:https://doaj.org/article/07f598e8e6e94108b92a17641e260430
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spelling oai:doaj.org-article:07f598e8e6e94108b92a17641e2604302021-12-02T15:05:44ZGlobal rainfall erosivity assessment based on high-temporal resolution rainfall records10.1038/s41598-017-04282-82045-2322https://doaj.org/article/07f598e8e6e94108b92a17641e2604302017-06-01T00:00:00Zhttps://doi.org/10.1038/s41598-017-04282-8https://doaj.org/toc/2045-2322Abstract 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.Panos PanagosPasquale BorrelliKatrin MeusburgerBofu YuAndreas KlikKyoung Jae LimJae E. YangJinren NiChiyuan MiaoNabansu ChattopadhyaySeyed Hamidreza SadeghiZeinab HazbaviMohsen ZabihiGennady A. LarionovSergey F. KrasnovAndrey V. GorobetsYoav LeviGunay ErpulChristian BirkelNatalia HoyosVictoria NaipalPaulo Tarso S. OliveiraCarlos A. BonillaMohamed MeddiWerner NelHassan Al DashtiMartino BoniNazzareno DiodatoKristof Van OostMark NearingCristiano BallabioNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 7, Iss 1, Pp 1-12 (2017)
institution DOAJ
collection DOAJ
language EN
topic Medicine
R
Science
Q
spellingShingle Medicine
R
Science
Q
Panos Panagos
Pasquale Borrelli
Katrin Meusburger
Bofu Yu
Andreas Klik
Kyoung Jae Lim
Jae E. Yang
Jinren Ni
Chiyuan Miao
Nabansu Chattopadhyay
Seyed Hamidreza Sadeghi
Zeinab Hazbavi
Mohsen Zabihi
Gennady A. Larionov
Sergey F. Krasnov
Andrey V. Gorobets
Yoav Levi
Gunay Erpul
Christian Birkel
Natalia Hoyos
Victoria Naipal
Paulo Tarso S. Oliveira
Carlos A. Bonilla
Mohamed Meddi
Werner Nel
Hassan Al Dashti
Martino Boni
Nazzareno Diodato
Kristof Van Oost
Mark Nearing
Cristiano Ballabio
Global rainfall erosivity assessment based on high-temporal resolution rainfall records
description Abstract 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.
format article
author Panos Panagos
Pasquale Borrelli
Katrin Meusburger
Bofu Yu
Andreas Klik
Kyoung Jae Lim
Jae E. Yang
Jinren Ni
Chiyuan Miao
Nabansu Chattopadhyay
Seyed Hamidreza Sadeghi
Zeinab Hazbavi
Mohsen Zabihi
Gennady A. Larionov
Sergey F. Krasnov
Andrey V. Gorobets
Yoav Levi
Gunay Erpul
Christian Birkel
Natalia Hoyos
Victoria Naipal
Paulo Tarso S. Oliveira
Carlos A. Bonilla
Mohamed Meddi
Werner Nel
Hassan Al Dashti
Martino Boni
Nazzareno Diodato
Kristof Van Oost
Mark Nearing
Cristiano Ballabio
author_facet Panos Panagos
Pasquale Borrelli
Katrin Meusburger
Bofu Yu
Andreas Klik
Kyoung Jae Lim
Jae E. Yang
Jinren Ni
Chiyuan Miao
Nabansu Chattopadhyay
Seyed Hamidreza Sadeghi
Zeinab Hazbavi
Mohsen Zabihi
Gennady A. Larionov
Sergey F. Krasnov
Andrey V. Gorobets
Yoav Levi
Gunay Erpul
Christian Birkel
Natalia Hoyos
Victoria Naipal
Paulo Tarso S. Oliveira
Carlos A. Bonilla
Mohamed Meddi
Werner Nel
Hassan Al Dashti
Martino Boni
Nazzareno Diodato
Kristof Van Oost
Mark Nearing
Cristiano Ballabio
author_sort Panos Panagos
title 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_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_sort global rainfall erosivity assessment based on high-temporal resolution rainfall records
publisher Nature Portfolio
publishDate 2017
url https://doaj.org/article/07f598e8e6e94108b92a17641e260430
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