Compositional data analysis of Holocene sediments from the West Bengal Sundarbans, India: Geochemical proxies for grain-size variability in a delta environment

doi:10.1016/j.apgeochem.2016.06.006

Applied Geochemistry

Volume 75, December 2016, Pages 222-235

https://doi.org/10.1016/j.apgeochem.2016.06.006 Get rights and content

Highlights

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Multivariate statistical modelling of grain-size and geochemistry from the Holocene Ganges-Brahmaputra delta.
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Compositional data analysis through LRCE and PLS modelling approaches for proxy depositional information.
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Methodological framework for unravelling Holocene sedimentation patterns in the Ganges-Brahmaputra delta.

Abstract

This paper is part of a special issue of Applied Geochemistry focusing on reliable applications of compositional multivariate statistical methods. This study outlines the application of compositional data analysis (CoDa) to calibration of geochemical data and multivariate statistical modelling of geochemistry and grain-size data from a set of Holocene sedimentary cores from the Ganges-Brahmaputra (G-B) delta. Over the last two decades, understanding near-continuous records of sedimentary sequences has required the use of core-scanning X-ray fluorescence (XRF) spectrometry, for both terrestrial and marine sedimentary sequences. Initial XRF data are generally unusable in ‘raw-format’, requiring data processing in order to remove instrument bias, as well as informed sequence interpretation. The applicability of these conventional calibration equations to core-scanning XRF data are further limited by the constraints posed by unknown measurement geometry and specimen homogeneity, as well as matrix effects. Log-ratio based calibration schemes have been developed and applied to clastic sedimentary sequences focusing mainly on energy dispersive-XRF (ED-XRF) core-scanning. This study has applied high resolution core-scanning XRF to Holocene sedimentary sequences from the tidal-dominated Indian Sundarbans, (Ganges-Brahmaputra delta plain). The Log-Ratio Calibration Equation (LRCE) was applied to a sub-set of core-scan and conventional ED-XRF data to quantify elemental composition. This provides a robust calibration scheme using reduced major axis regression of log-ratio transformed geochemical data. Through partial least squares (PLS) modelling of geochemical and grain-size data, it is possible to derive robust proxy information for the Sundarbans depositional environment. The application of these techniques to Holocene sedimentary data offers an improved methodological framework for unravelling Holocene sedimentation patterns.

Section snippets

Geochemistry of Holocene sedimentary environments

The composition and physical properties of sediments and sedimentary rocks are for the most part controlled by chemical processes taking place during weathering, transport, and burial (diagenesis) (Bjørlykke, 2010). Thus, understanding the physical properties of sediments and sedimentary rocks requires an understanding of the chemical processes underlying sedimentary deposition. The formation of clastic sediments is a result of the erosion and weathering of source parent rocks. The dissolved

Background to the Indian Sundarbans

The Sundarbans is one of the largest coastal wetland sites in the world (∼1 million hectares) covering the western delta of the Ganges and Brahmaputra (G-B) rivers (Fig. 1). The Sundarbans is a complex network of tidal creeks and deltaic islands with most sediment arriving indirectly from the G-B river systems (which drain the Himalayas). The Indian Sundarbans comprises just over 400,000 ha in the western sector of the G-B delta, and is cross-cut by a number of approximately north-south

Introduction to XRF core-scanning

The application of X-ray fluorescence (XRF) to geological materials is well established, and recognised as a conventional technique for deriving elemental composition (Ramsey et al., 1995, Jenkins, 1999, De Vries and Vrebos, 2002, Weltje and Tjallingii, 2008). The underlying principle of XRF analysis is that excitation of electrons by incident X-radiation (X-rays) leads to the ejection of electrons from the inner ring of an atomic shell. This ejection results in a vacancy, which is filled by

Quantification of core-scan derived XRF through the LRCE

The LRCE works by using the relationship between elements derived from core-scan and conventional ED-XRF. Core-scan ED-XRF cannot be calibrated in standard equations due to unknown coefficients of such models, as it is not possible to correct for grain-size, water content etc., on a split core log without altering the sample. In principle, calibration of conventional ED-XRF faces the problems of being a closed dataset (i.e., appropriate data for compositional data analysis), but still

Results

The results presented in this section reflect the data processing and outline how the LRCE was applied to the integrated core-scan ED-XRF data along with the discrete samples analysed using conventional ED-XRF and grain-size analysis. The LRCE model depends on comparability of the intensity measured elemental composition (i.e., data from the core-scan ITRAX™ data) along with the % elemental composition (i.e., conventional XRF data) a sub-composition of the elements were examined for these

Reconstructing late Holocene environmental change from sediments in the West Bengal Sundarbans, India

The objective of the study is to investigate how the application of LRCE & PLS to Holocene sediments of a Delta environment can improve interpretation of geochemical indicators of grain-size variability. The geochemistry derived from the application of the LRCE to Holocene sediments in the present study illustrates the efficacy of these subset of elements as useful indicators of environmental change. The LRCE shows that, in the case of the Sundarbans, K, Rb, Fe, Ti, Zr, and Ca can be

Conclusion

Through CoDa it has been possible to calibrate core-scan derived XRF data, and produce useful elemental proxies for analysing a clastic sedimentary environment. When using the LRCE calibration model coefficients to examine such clastic sedimentary environments in the Indian Sundarbans quantified data outputs are possible, and combined with grain-size data a broader understanding of the depositional environment is possible. The lack of a full elemental suite, attributed to a poorer linear fit

Acknowledgements

RPF acknowledges the support provided by a Research Studentship from the Department for Employment and Learning (Northern Ireland) and the Department of Education and Science’s Higher Education Grant Scheme (ROI) provided through Laois County Council (ROI). RPF also acknowledges the School of Geography, Archaeology and Palaeoecology (GAP), Queen’s University, Belfast (QUB) for the fieldwork support provided by their Soulby Research Fund. RPF acknowledges the assistance and technical support

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Compositional data analysis of Holocene sediments from the West Bengal Sundarbans, India: Geochemical proxies for grain-size variability in a delta environment

Highlights

Abstract

Section snippets

Geochemistry of Holocene sedimentary environments

Background to the Indian Sundarbans

Introduction to XRF core-scanning

Quantification of core-scan derived XRF through the LRCE

Results

Reconstructing late Holocene environmental change from sediments in the West Bengal Sundarbans, India

Conclusion

Acknowledgements

Sediment. Geol.

Quat. Res.

Sediment. Geol.

Earth Sci. Rev.

Chemom. Intell. Lab. Syst.

Sed. Geol.

Mar. Geol.

Sediment. Geol.

Mar. Geol.

Sediment. Geol.

Sediment. Geol.

Quat. Res.

Mar. Geol.

Chem. Geol.

Estuar. Coast. Shelf Sci.

Chem. Geol.

Quat. Sci. Rev.

Dev. Sedimentol.

Sediment. Geol.

Earth Planet. Sci. Lett.

Sediment. Geol.

The statistical analysis of compositional data (with discussion)

J. R. Stat. Soc. Ser. B

The Statistical Analysis of Compositional Data

Geologic framework and environmental status of the Ganges-Brahmaputra delta

J. Coast. Res.

Historical changes in the Ganges-Brahmaputra delta

J. Coast. Res.