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

被引:0
|
作者
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
机构
[1] Joint Research Centre,European Commission
[2] University of Basel,Environmental Geosciences
[3] Griffith University,School of Engineering
[4] University of Natural Resources and Life Sciences,BOKU
[5] Kangwon National University,College of Environmental Sciences and Engineering
[6] Peking University,College of Global Change and Earth System Science
[7] Beijing Normal University,Faculty of Natural Resources
[8] India Meteorological Department,Faculty of Geography
[9] Tarbiat Modares University,Faculty of Agriculture
[10] Lomonosov Moscow State University, Soil Science Departement
[11] Israel Meteorological Service,Departamento de Ingeniería Hidráulica y Ambiental
[12] Ankara University,Department of Geography and Environmental Science
[13] University of Costa Rica,USDA
[14] Universidad del Norte,ARS
[15] Laboratoire des Sciences du Climat et de l′Environnement,undefined
[16] IPSL-LSCE,undefined
[17] Federal University of Mato Grosso do Sul,undefined
[18] Pontificia Universidad Católica de Chile,undefined
[19] Ecole Nationale Supérieure d’Hydraulique de Blida,undefined
[20] University of Fort Hare,undefined
[21] Department of Meteorology,undefined
[22] Met European Research Observatory,undefined
[23] Université Catholique de Louvain,undefined
[24] Southwest Watershed Research Center,undefined
来源
Scientific Reports | / 7卷
关键词
D O I
暂无
中图分类号
学科分类号
摘要
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.
引用
收藏
相关论文
共 50 条
  • [1] Global rainfall erosivity assessment based on high-temporal resolution rainfall records
    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
    SCIENTIFIC REPORTS, 2017, 7
  • [2] Rainfall erosivity estimation over the Tibetan plateau based on high spatial-temporal resolution rainfall records
    Chen, Yueli
    Duan, Xingwu
    Zhang, Guo
    Ding, Minghu
    Lu, Shaojuan
    INTERNATIONAL SOIL AND WATER CONSERVATION RESEARCH, 2022, 10 (03) : 422 - 432
  • [3] Rainfall erosivity mapping over mainland China based on high-density hourly rainfall records
    Yue, Tianyu
    Yin, Shuiqing
    Xie, Yun
    Yu, Bofu
    Liu, Baoyuan
    EARTH SYSTEM SCIENCE DATA, 2022, 14 (02) : 665 - 682
  • [4] Incorporating return period in the assessment of rainfall erosivity of India using high temporal resolution satellite precipitation product
    Das, Tapasranjan
    Sarma, Arup Kumar
    JOURNAL OF EARTH SYSTEM SCIENCE, 2024, 134 (01)
  • [5] Rainfall erosivity estimation based on rainfall data collected over a range of temporal resolutions
    Yin, S.
    Xie, Y.
    Liu, B.
    Nearing, M. A.
    HYDROLOGY AND EARTH SYSTEM SCIENCES, 2015, 19 (10) : 4113 - 4126
  • [6] Rainfall erosivity in Italy: a national scale spatio-temporal assessment
    Borrelli, Pasquale
    Diodato, Nazzareno
    Panagos, Panos
    INTERNATIONAL JOURNAL OF DIGITAL EARTH, 2016, 9 (09) : 835 - 850
  • [7] The influence in rainfall erosivity calculation by using different temporal resolution in Mediterranean area
    Piccarreta, Marco
    Lazzari, Maurizio
    Bentivenga, Mario
    SCIENCE OF THE TOTAL ENVIRONMENT, 2024, 906
  • [8] On the Use of Microwave Sounder Data for High-Temporal Rainfall Maps based on Microwave Radiometers
    Shige, Shoichi
    Yamamoto, Tomoya
    Kida, Satoshi
    Tsukiyama, Takeaki
    Kubota, Takuji
    Okamoto, Ken'ichi
    2008 MICROWAVE RADIOMETRY AND REMOTE SENSING OF THE ENVIRONMENT, 2008, : 200 - +
  • [9] The spatiotemporal variations of global rainfall erosivity and erosive rainfall event based on half-hourly satellite rainfall data
    Yang, Qianxi
    Xu, Ximeng
    Tang, Qiuhong
    Jia, Guoqiang
    CATENA, 2025, 252
  • [10] Global rainfall erosivity projections for 2050 and 2070
    Panagos, Panos
    Borrelli, Pasquale
    Matthews, Francis
    Liakos, Leonidas
    Bezak, Nejc
    Diodato, Nazzareno
    Ballabio, Cristiano
    JOURNAL OF HYDROLOGY, 2022, 610