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

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    PanagosPUB3918.pdf (2.225Mb)
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    Author(s)
    Panagos, Panos
    Borrelli, Pasquale
    Meusburger, Katrin
    Yu, Bofu
    Klik, Andreas
    Lim, Kyoung Jae
    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
    Griffith University Author(s)
    Yu, Bofu
    Year published
    2017
    Metadata
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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 ...
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    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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    Journal Title
    Scientific Reports
    Volume
    7
    DOI
    https://doi.org/10.1038/s41598-017-04282-8
    Copyright Statement
    © The Author(s) 2017. 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/.
    Subject
    Climatology
    Publication URI
    http://hdl.handle.net/10072/347226
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    • Journal articles

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