Cargando…
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...
Autores principales: | , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , |
---|---|
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 |
_version_ | 1783245647201173504 |
---|---|
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. |
format | Online Article Text |
id | pubmed-5482877 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
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 |
work_keys_str_mv | AT panagospanos globalrainfallerosivityassessmentbasedonhightemporalresolutionrainfallrecords AT borrellipasquale globalrainfallerosivityassessmentbasedonhightemporalresolutionrainfallrecords AT meusburgerkatrin globalrainfallerosivityassessmentbasedonhightemporalresolutionrainfallrecords AT yubofu globalrainfallerosivityassessmentbasedonhightemporalresolutionrainfallrecords AT klikandreas globalrainfallerosivityassessmentbasedonhightemporalresolutionrainfallrecords AT jaelimkyoung globalrainfallerosivityassessmentbasedonhightemporalresolutionrainfallrecords AT yangjaee globalrainfallerosivityassessmentbasedonhightemporalresolutionrainfallrecords AT nijinren globalrainfallerosivityassessmentbasedonhightemporalresolutionrainfallrecords AT miaochiyuan globalrainfallerosivityassessmentbasedonhightemporalresolutionrainfallrecords AT chattopadhyaynabansu globalrainfallerosivityassessmentbasedonhightemporalresolutionrainfallrecords AT sadeghiseyedhamidreza globalrainfallerosivityassessmentbasedonhightemporalresolutionrainfallrecords AT hazbavizeinab globalrainfallerosivityassessmentbasedonhightemporalresolutionrainfallrecords AT zabihimohsen globalrainfallerosivityassessmentbasedonhightemporalresolutionrainfallrecords AT larionovgennadya globalrainfallerosivityassessmentbasedonhightemporalresolutionrainfallrecords AT krasnovsergeyf globalrainfallerosivityassessmentbasedonhightemporalresolutionrainfallrecords AT gorobetsandreyv globalrainfallerosivityassessmentbasedonhightemporalresolutionrainfallrecords AT leviyoav globalrainfallerosivityassessmentbasedonhightemporalresolutionrainfallrecords AT erpulgunay globalrainfallerosivityassessmentbasedonhightemporalresolutionrainfallrecords AT birkelchristian globalrainfallerosivityassessmentbasedonhightemporalresolutionrainfallrecords AT hoyosnatalia globalrainfallerosivityassessmentbasedonhightemporalresolutionrainfallrecords AT naipalvictoria globalrainfallerosivityassessmentbasedonhightemporalresolutionrainfallrecords AT oliveirapaulotarsos globalrainfallerosivityassessmentbasedonhightemporalresolutionrainfallrecords AT bonillacarlosa globalrainfallerosivityassessmentbasedonhightemporalresolutionrainfallrecords AT meddimohamed globalrainfallerosivityassessmentbasedonhightemporalresolutionrainfallrecords AT nelwerner globalrainfallerosivityassessmentbasedonhightemporalresolutionrainfallrecords AT aldashtihassan globalrainfallerosivityassessmentbasedonhightemporalresolutionrainfallrecords AT bonimartino globalrainfallerosivityassessmentbasedonhightemporalresolutionrainfallrecords AT diodatonazzareno globalrainfallerosivityassessmentbasedonhightemporalresolutionrainfallrecords AT vanoostkristof globalrainfallerosivityassessmentbasedonhightemporalresolutionrainfallrecords AT nearingmark globalrainfallerosivityassessmentbasedonhightemporalresolutionrainfallrecords AT ballabiocristiano globalrainfallerosivityassessmentbasedonhightemporalresolutionrainfallrecords |