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Hydrology and Earth System Sciences An interactive open-access journal of the European Geosciences Union
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https://doi.org/10.5194/hess-2020-187
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/hess-2020-187
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

Submitted as: research article 15 Jun 2020

Submitted as: research article | 15 Jun 2020

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This preprint is currently under review for the journal HESS.

Estimation of rainfall erosivity based on WRF-derived raindrop size distributions

Qiang Dai1,2, Jingxuan Zhu1, Shuliang Zhang1, Shaonan Zhu3, Dawei Han2, and Guonian Lv1 Qiang Dai et al.
  • 1Key Laboratory of VGE of Ministry of Education, Nanjing Normal University, Nanjing, China
  • 2Department of Civil Engineering, University of Bristol, Bristol, UK
  • 3College of Geographical and Biological Information, Nanjing University of Posts and Telecommunications, Nanjing, China

Abstract. Soil erosion can cause various ecological problems, such as land degradation, soil fertility loss, and river siltation. Rainfall is the primary water-driving force for soil erosion and its potential effect on soil erosion is reflected by rainfall erosivity that relates to the raindrop kinetic energy (KE). As it is difficult to observe large-scale dynamic characteristics of raindrops, all the current rainfall erosivity models use the function based on rainfall amount to represent the raindrops KE. With the development of global atmospheric re-analysis data, numerical weather prediction (NWP) techniques become a promising way to estimate rainfall KE directly at regional and global scales with high spatial and temporal resolutions. This study proposed a novel method for large-scale and long-term rainfall erosivity investigations based on the Weather Research and Forecasting (WRF) model, avoiding errors caused by inappropriate rainfall–energy relationships and large-scale interpolation. We adopted three microphysical parameterizations schemes (Morrison, WDM6, and Thompson aerosol-aware [TAA]) to obtain raindrop size distributions, rainfall KE and rainfall erosivity, with validation by two disdrometers and 304 rain gauges around the United Kingdom. Among the three WRF schemes, TAA had the best performance compared with the disdrometers at a monthly scale. The results revealed that high rainfall erosivity occurred in the west coast area at the whole country scale during 2013–2017. The proposed methodology makes a significant contribution to improving large-scale soil erosion estimation and for better understanding microphysical rainfall–soil interactions to support the rational formulation of soil and water conservation planning.

Qiang Dai et al.

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Qiang Dai et al.

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Short summary
Rainfall is a driving force that accounts for a large proportion of soil loss around the world. Most previous studies used fixed rainfall-energy relationship to estimate rainfall energy, ignoring the spatial and temporal changes of raindrop microphysical process. This study proposes a novel method for large-scale and long-term rainfall energy and rainfall erosivity investigations based on rainfall microphysical parameterizations schemes in the Weather Research and Forecasting (WRF) model.
Rainfall is a driving force that accounts for a large proportion of soil loss around the world....
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