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

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 regiona...

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Detalles Bibliográficos
Autores principales: Dai, Qiang, Zhu, Jingxuan, Lv, Guonian, Kalin, Latif, Yao, Yuanzhi, Zhang, Jun, Han, Dawei
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Association for the Advancement of Science 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10411884/
https://www.ncbi.nlm.nih.gov/pubmed/37556540
http://dx.doi.org/10.1126/sciadv.adg5551
Descripción
Sumario: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.