Please use this identifier to cite or link to this item: http://repositorio.ufla.br/jspui/handle/1/34787
metadata.artigo.dc.title: Using pedological knowledge to improve sediment source apportionment in tropical environments
metadata.artigo.dc.creator: Batista, Pedro V. G.
Laceby, J. Patrick
Silva, Marx L. N.
Tassinari, Diego
Bispo, Diêgo F. A.
Curi, Nilton
Davies, Jessica
Quinton, John N.
metadata.artigo.dc.subject: Erosion processes
Geochemical fingerprinting
Sediment particle size
Sediment sources
Sediment tracing
Tropical soils
metadata.artigo.dc.publisher: Springer
metadata.artigo.dc.date.issued: 2018
metadata.artigo.dc.identifier.citation: BATISTA, P. V. G. et ak. Using pedological knowledge to improve sediment source apportionment in tropical environments. Journal of Soils and Sediments, [S.l.], p. 1-16, 2018.
metadata.artigo.dc.description.abstract: Purpose Soils are important regulators of Critical Zone processes that influence the development of geochemical signals used for sediment fingerprinting. In this study, pedological knowledge of tropical soils was incorporated into sediment source stratification and tracer selection in a large Brazilian catchment. Materials and methods In the Ingaí River basin (~ 1200 km2), Brazil, three source end-members were defined according to the interpretation of soil and geological maps: the upper, mid, and lower catchment. A tributary sampling design was employed, and sediment geochemistry of three different size fractions was analyzed (2–0.2 mm; 0.2–0.062 mm, and < 0.062 mm). A commonly used statistical methodology to element selection was compared to a knowledge-based approach. The mass balance un-mixing models were solved by a Monte Carlo simulation. Modeled source contributions were evaluated against a set of artificial mixtures with known source proportions. Results and discussion For the coarse fraction (2–0.2 mm), both approaches to element selection yielded high errors compared to the artificial mixtures (23.8% and 17.8% for the statistical and the knowledge-based approach, respectively). The knowledge-based approach provided the lowest errors for the intermediate (0.2–0.062 mm) (10.9%) and fine (< 0.062 mm) (11.8%) fractions. Model predictions for catchment outlet target samples were highly uncertain for the coarse and intermediate fractions. This is likely the result of the spatial scale of the source stratification not being able to represent sediment dynamics for these fractions. Both approaches to element selection show that most of the fine sediments (median > 90%) reaching the catchment outlet were derived from Ustorthents in the lower catchment. Conclusions The different element selection methods and the artificial mixtures provide multiple lines of evidence for evaluating the fingerprint approaches. Our findings highlight the importance of considering pedogenetic processes in source stratification, and demonstrate that different sampling strategies might be necessary to model specific sediment fractions.
metadata.artigo.dc.identifier.uri: https://link.springer.com/article/10.1007/s11368-018-2199-5
http://repositorio.ufla.br/jspui/handle/1/34787
metadata.artigo.dc.language: en_US
Appears in Collections:DCS - Artigos publicados em periódicos

Files in This Item:
There are no files associated with this item.


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.