Comparative study using spectroscopic and mineralogical fingerprinting for suspended sediment source apportionment in a river–reservoir system

Abstract The need to control soil erosion has received increasing attention, but quantitative data on the sources of suspended sediment in many river–reservoir systems is still lacking. The goal of this research was to compare the application of spectroscopic [mid‐infrared (MIR)] and mineralogical [X‐ray diffraction (XRD)] fingerprints for assessing relative sediment source contributions from different land use groups (agricultural lands, forests and human settlements) in the Konar–Damodar river–reservoir system in India. Source apportionment was estimated using partial least square (PLS) regression for spectroscopic tracers (MIR) and the Bayesian MixSIAR model for mineralogical tracers. Both methods identified differences between the pre‐ and post‐monsoon sediment contributions of forests (overall contribution bounds of ~35–43%). During monsoon seasons, both fingerprinting methods indicated agricultural land use as the primary source of suspended sediment. Although there were some temporal variations in the predicted contributions of the land use sources, the MIR‐PLS and mineralogical–MixSIAR methods produced comparable ranges. The respective variations in contributions, using MIR‐PLS and mineralogical–MixSIAR, were ~31 to 66% compared with ~36 to 61% for agricultural lands, ~21 to 43% compared with ~15 to 39% for forests and ~16 to 37% compared with ~19 to 32% for human settlements.

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Publication Details

Journal
Earth Surface Processes and Landforms
Published
2024-08-29
DOI
https://doi.org/10.1002/esp.5972
Citations
1
Primary Topic
Geochemistry and Geologic Mapping
Type
article
Field-Weighted Citation Impact
0.35

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article

Comparative study using spectroscopic and mineralogical fingerprinting for suspended sediment source apportionment in a river–reservoir system

Renji Remesan, Ashok K. Gupta, Adrian L. Collins, Arnab Das et al.
1 citations
Earth Surface Processes and Landforms
Geochemistry and Geologic Mapping
0.35
article

Comparative study using spectroscopic and mineralogical fingerprinting for suspended sediment source apportionment in a river–reservoir system

Renji Remesan, Ashok K. Gupta, Adrian L. Collins, Arnab Das, Somsubhra Chakraborty
article en
1 citations

Abstract

Abstract The need to control soil erosion has received increasing attention, but quantitative data on the sources of suspended sediment in many river–reservoir systems is still lacking. The goal of this research was to compare the application of spectroscopic [mid‐infrared (MIR)] and mineralogical [X‐ray diffraction (XRD)] fingerprints for assessing relative sediment source contributions from different land use groups (agricultural lands, forests and human settlements) in the Konar–Damodar river–reservoir system in India. Source apportionment was estimated using partial least square (PLS) regression for spectroscopic tracers (MIR) and the Bayesian MixSIAR model for mineralogical tracers. Both methods identified differences between the pre‐ and post‐monsoon sediment contributions of forests (overall contribution bounds of ~35–43%). During monsoon seasons, both fingerprinting methods indicated agricultural land use as the primary source of suspended sediment. Although there were some temporal variations in the predicted contributions of the land use sources, the MIR‐PLS and mineralogical–MixSIAR methods produced comparable ranges. The respective variations in contributions, using MIR‐PLS and mineralogical–MixSIAR, were ~31 to 66% compared with ~36 to 61% for agricultural lands, ~21 to 43% compared with ~15 to 39% for forests and ~16 to 37% compared with ~19 to 32% for human settlements.

Earth Surface Processes and LandformsVol. 49(13)
Indian Institute of Technology Kharagpur (IN), Rothamsted Research (GB)
UK Research and Innovation, Directorate for Biological Sciences, Biotechnology and Biological Sciences Research Council
Life in Land
Openalex Percentile: Top 34%
Geochemistry and Geologic Mapping
0.35
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