Radar remote sensing reveals potential underestimation of rainfall erosivity at the global scale-Reference-Cited by-同舟云学术

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

Published:2023-08-11 Issue:32 Volume:9 Page:
ISSN:2375-2548
Container-title:Science Advances
language:en
Short-container-title:Sci. Adv.

Author:

Dai Qiang¹^ORCID,Zhu Jingxuan¹²^ORCID,Lv Guonian¹^ORCID,Kalin Latif³^ORCID,Yao Yuanzhi³⁴^ORCID,Zhang Jun¹⁵^ORCID,Han Dawei²^ORCID

Affiliation:

1. Key Laboratory of VGE of Ministry of Education, Nanjing Normal University, Nanjing, China.

2. Department of Civil Engineering, University of Bristol, Bristol, UK.

3. College of Forestry, Wildlife and Environment, Auburn University, Auburn, AL, USA.

4. School of Geographic Science, East China Normal University, Shanghai, China.

5. Department of Hydrology and Atmospheric Sciences, The University of Arizona, Tucson, USA.

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 ( RKE MPH ) flux retrieved from radar reflectivity at different frequencies. The results suggest that RKE MPH flux outperforms the RKE estimates derived from a widely used empirical KE-I relation ( RKE KE-I ) validated using ground disdrometers. We found a potentially widespread underestimation of RKE KE-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.

Publisher

American Association for the Advancement of Science (AAAS)

Subject

Multidisciplinary

Link

https://www.science.org/doi/pdf/10.1126/sciadv.adg5551

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