Use este identificador para citar ou linkar para este item: http://repositorio.ufla.br/jspui/handle/1/57003
Título: Tracing the origin of deposited sediments: a study applying proximal sensing in a drainage subbasin
Palavras-chave: Ferralsols
Acrisols
Magnetic susceptibility
Portable X-ray fluorescence spectrometer (pXRF)
Soil conservation
Tropical soils
Fingerprinting
Data do documento: Mar-2023
Editor: Elsevier
Citação: LIMA, W. de et al. Tracing the origin of deposited sediments: a study applying proximal sensing in a drainage subbasin. Journal of South American Earth Sciences, [S.l.], v. 123, Mar. 2023.
Resumo: Erosion is a major cause of soil degradation. Understanding the sources of sediment and the processes that exacerbate this problem is crucial for soil conservation. Remote and proximal sensing technologies have contributed to advance our understanding of soil erosion processes and support soil conservation research. The objective of this study is to use two proximal sensors, a portable X-ray fluorescence spectrometer (pXRF) and a magnetic susceptibilimeter, to identify the origin of sediments deposited in the lower portion of a drainage subbasin by using a fingerprinting approach. Five sediment tracing elements were selected: Fe, Si, Al, Ti, and Zr. The sediment source area is composed of gabbro, granite, and felsic orthogneiss, upon which two soil classes were formed: Rhodic Ferralsol (Dystric) (Latossolo Vermelho Distroférrico típico, LV) and Haplic Acrisol (Argissolo Vermelho-Amarelo Distrófico típico, PVA). In the source area, 35 samples were collected from the topsoil layer (0–2 cm of depth) using a regular grid of 50 × 50 m2. In the deposition area, 24 samples were collected in a regular grid of 7 × 7 m2. The source of the sediments was determined using cluster analysis with data provided by the proximal sensors and topographic attributes. Results indicated that the Haplic Acrisol, which is more susceptible to erosion, contributed most to sediment deposition. Analysis of pXRF data showed its potential to identify and differentiate sediments and their sources. Cluster models based on the abundance of Fe, Si and Al, as well as the Ti/Zr ratio, demonstrated the best results with a global accuracy of 88% and a Kappa coefficient of 0.74. The use of the susceptibilimeter data alone did not yield satisfactory results. Results indicate the usefulness of pXRF in identifying the source of sediments in drainage basins, making it a valuable tool in soil conservation and erosion assessments.
URI: https://www.sciencedirect.com/science/article/pii/S0895981123000524
http://repositorio.ufla.br/jspui/handle/1/57003
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