Articles | Volume 24, issue 11
https://doi.org/10.5194/hess-24-5407-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/hess-24-5407-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
17 Nov 2020
Research article |
| 17 Nov 2020
| 17 Nov 2020
Estimation of rainfall erosivity based on WRF-derived raindrop size distributions
Qiang Dai
Key Laboratory of VGE of Ministry of Education, Nanjing Normal
University, Nanjing, China
Department of Civil Engineering, University of Bristol, Bristol, UK
Jingxuan Zhu
Key Laboratory of VGE of Ministry of Education, Nanjing Normal
University, Nanjing, China
Shuliang Zhang
CORRESPONDING AUTHOR
Key Laboratory of VGE of Ministry of Education, Nanjing Normal
University, Nanjing, China
Shaonan Zhu
College of Geographical and Biological Information, Nanjing University of Posts and Telecommunications, Nanjing, China
Dawei Han
Department of Civil Engineering, University of Bristol, Bristol, UK
Guonian Lv
Key Laboratory of VGE of Ministry of Education, Nanjing Normal
University, Nanjing, China
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Cited
21 citations as recorded by crossref.
- Radar Remote Sensing Retrieval of Vertical Profile of Rainfall Kinetic Energy in the U.K J. Zhu et al. https://doi.org/10.1109/TGRS.2025.3542493
- Coordinated Development Path of Cultivated Land Utilization in Henan Section of the Yellow River Basin Y. Cheng et al. https://doi.org/10.3390/land12071342
- Large-Scale Soil Erosion Estimation Considering Vegetation Growth Cycle H. Zhuang et al. https://doi.org/10.3390/land10050473
- Erosion of Biotreated Field-Scale Slopes under Rainfalls Y. Xiao et al. https://doi.org/10.1061/(ASCE)CF.1943-5509.0001732
- Raindrop size distribution (DSD) retrieval from polarimetric radar observations using neural networks J. Zhu et al. https://doi.org/10.1016/j.atmosres.2024.107638
- Reshaping global rainfall erosivity rates: A study on precipitation phase correction from 2015 to 2022 D. Ji et al. https://doi.org/10.1016/j.jhydrol.2025.133271
- ASSESSMENT AND MAPPING OF RAINFALL EROSIVITY INDEX (R) FOR MAJHA REGION, PUNJAB IS A STATE IN NORTHERN, INDIA P. Kumar https://doi.org/10.18510/ijsrtm.2021.932
- WRF Rainfall Modeling Post-Processing by Adaptive Parameterization of Raindrop Size Distribution: A Case Study on the United Kingdom Q. Yang et al. https://doi.org/10.3390/atmos13010036
- Raindrop Size Distribution Retrieval Model for X-Band Dual-Polarization Radar in China Incorporating Various Climatic and Geographical Elements Q. Yang et al. https://doi.org/10.1109/TGRS.2022.3168586
- Evaluation of WRF-simulated raindrop size distributions using disdrometer observations across eastern and southern China Q. Yang et al. https://doi.org/10.1016/j.atmosres.2026.108789
- Investigation of the Vertical Microphysical Characteristics of Rainfall in Guangzhou Based on Phased-Array Radar J. Zhu et al. https://doi.org/10.3390/rs18020322
- Microphysics-based rainfall energy estimation using remote sensing and reanalysis data J. Zhu et al. https://doi.org/10.1016/j.jhydrol.2023.130314
- Raindrop Size Distribution Characteristics of Heavy Precipitation Events Based on a PWS100 Disdrometer in the Alpine Mountains, Eastern Tianshan, China P. Chen et al. https://doi.org/10.3390/rs15205068
- Spatial and temporal variation of raindrop size distribution in Great Britain S. Jiang et al. https://doi.org/10.1016/j.atmosres.2025.108699
- Microphysical properties of various precipitation systems worldwide classified via objective methods based on dual-frequency precipitation radar observations Y. Zhang et al. https://doi.org/10.5194/acp-26-4727-2026
- Global assessment of storm disaster-prone areas N. Diodato et al. https://doi.org/10.1371/journal.pone.0272161
- DREE-RF: A Radar-Based Rainfall Energy Estimation Model Using Random Forest J. Zhu et al. https://doi.org/10.1109/TGRS.2024.3487221
- Radar remote sensing reveals potential underestimation of rainfall erosivity at the global scale Q. Dai et al. https://doi.org/10.1126/sciadv.adg5551
- Rainfall Erosivity in Tropical Catchment Area: Empirical Models vs Machine Learning Approach P. Pudyastuti et al. https://doi.org/10.1088/1755-1315/1631/1/012012
- Raindrop size distributions of summer monsoon rainfall observed over Eastern India B. Seela et al. https://doi.org/10.1016/j.atmosres.2024.107581
- An assessment of rainfall kinetic energy functional relationships with GPM DPR J. Janapati et al. https://doi.org/10.1016/j.jhydrol.2022.128754
21 citations as recorded by crossref.
- Radar Remote Sensing Retrieval of Vertical Profile of Rainfall Kinetic Energy in the U.K J. Zhu et al. https://doi.org/10.1109/TGRS.2025.3542493
- Coordinated Development Path of Cultivated Land Utilization in Henan Section of the Yellow River Basin Y. Cheng et al. https://doi.org/10.3390/land12071342
- Large-Scale Soil Erosion Estimation Considering Vegetation Growth Cycle H. Zhuang et al. https://doi.org/10.3390/land10050473
- Erosion of Biotreated Field-Scale Slopes under Rainfalls Y. Xiao et al. https://doi.org/10.1061/(ASCE)CF.1943-5509.0001732
- Raindrop size distribution (DSD) retrieval from polarimetric radar observations using neural networks J. Zhu et al. https://doi.org/10.1016/j.atmosres.2024.107638
- Reshaping global rainfall erosivity rates: A study on precipitation phase correction from 2015 to 2022 D. Ji et al. https://doi.org/10.1016/j.jhydrol.2025.133271
- ASSESSMENT AND MAPPING OF RAINFALL EROSIVITY INDEX (R) FOR MAJHA REGION, PUNJAB IS A STATE IN NORTHERN, INDIA P. Kumar https://doi.org/10.18510/ijsrtm.2021.932
- WRF Rainfall Modeling Post-Processing by Adaptive Parameterization of Raindrop Size Distribution: A Case Study on the United Kingdom Q. Yang et al. https://doi.org/10.3390/atmos13010036
- Raindrop Size Distribution Retrieval Model for X-Band Dual-Polarization Radar in China Incorporating Various Climatic and Geographical Elements Q. Yang et al. https://doi.org/10.1109/TGRS.2022.3168586
- Evaluation of WRF-simulated raindrop size distributions using disdrometer observations across eastern and southern China Q. Yang et al. https://doi.org/10.1016/j.atmosres.2026.108789
- Investigation of the Vertical Microphysical Characteristics of Rainfall in Guangzhou Based on Phased-Array Radar J. Zhu et al. https://doi.org/10.3390/rs18020322
- Microphysics-based rainfall energy estimation using remote sensing and reanalysis data J. Zhu et al. https://doi.org/10.1016/j.jhydrol.2023.130314
- Raindrop Size Distribution Characteristics of Heavy Precipitation Events Based on a PWS100 Disdrometer in the Alpine Mountains, Eastern Tianshan, China P. Chen et al. https://doi.org/10.3390/rs15205068
- Spatial and temporal variation of raindrop size distribution in Great Britain S. Jiang et al. https://doi.org/10.1016/j.atmosres.2025.108699
- Microphysical properties of various precipitation systems worldwide classified via objective methods based on dual-frequency precipitation radar observations Y. Zhang et al. https://doi.org/10.5194/acp-26-4727-2026
- Global assessment of storm disaster-prone areas N. Diodato et al. https://doi.org/10.1371/journal.pone.0272161
- DREE-RF: A Radar-Based Rainfall Energy Estimation Model Using Random Forest J. Zhu et al. https://doi.org/10.1109/TGRS.2024.3487221
- Radar remote sensing reveals potential underestimation of rainfall erosivity at the global scale Q. Dai et al. https://doi.org/10.1126/sciadv.adg5551
- Rainfall Erosivity in Tropical Catchment Area: Empirical Models vs Machine Learning Approach P. Pudyastuti et al. https://doi.org/10.1088/1755-1315/1631/1/012012
- Raindrop size distributions of summer monsoon rainfall observed over Eastern India B. Seela et al. https://doi.org/10.1016/j.atmosres.2024.107581
- An assessment of rainfall kinetic energy functional relationships with GPM DPR J. Janapati et al. https://doi.org/10.1016/j.jhydrol.2022.128754
Saved (final revised paper)
Latest update: 11 Jun 2026
Short summary
Rainfall is a driving force that accounts for a large proportion of soil loss around the world. Most previous studies used a fixed rainfall–energy relationship to estimate rainfall energy, ignoring the spatial and temporal changes of raindrop microphysical processes. This study proposes a novel method for large-scale and long-term rainfall energy and rainfall erosivity investigations based on rainfall microphysical parameterization 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....
