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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Nature Portfolio
2017
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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) |
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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 |
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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 |
work_keys_str_mv |
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