Radar remote sensing reveals potential underestimation of rainfall erosivity at the global scale

Qiang Dai*, Jingxuan Zhu, Guonian Lv, Latif Kalin, Yuanzhi Yao, Jun Zhang, Dawei Han

*Corresponding author for this work

Research output: Contribution to journalArticle (Academic Journal)peer-review

7 Citations (Scopus)

Abstract

Rainfall kinetic energy (RKE) constitutes one of the most critical factors that drive rainfall erosivity on surface soil. Direct measurements of RKE are limited, relying instead on the empirical relations between kinetic energy and rainfall intensity (KE-I relation), which have not been well regionalized for data-scarce regions. Here, we present the first global rainfall microphysics–based RKE (RKEMPH) flux retrieved from radar reflectivity at different frequencies. The results suggest that RKEMPH flux outperforms the RKE estimates derived from a widely used empirical KE-I relation (RKEKE-I) validated using ground disdrometers. We found a potentially widespread underestimation of RKEKE-I, which is especially prominent in some low-income countries with ~20% underestimation of RKE and the resultant rainfall erosivity. Given the evidence that these countries are subject to greater rainfall-induced soil erosion, these underestimations would mislead conservation practices for sustainable development of terrestrial ecosystems.
Original languageEnglish
Article numbereadg5551
Pages (from-to)1-9
Number of pages9
JournalScience Advances
Volume9
Issue number32
DOIs
Publication statusPublished - 9 Aug 2023

Bibliographical note

Funding Information:
This research was made possible partly by the National Natural Science Foundation of China (nos. 41871299, 42071364 and 42201020) and Fundamental Research Funds for the Central Universities and State Key Laboratory of Tropical Oceanography, CAS (LTO2325).

Publisher Copyright:
Copyright © 2023 The Authors, some rights reserved.

Research Groups and Themes

  • Water and Environmental Engineering

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