Organic Carbon transport model of abandoned river channels - A motif for floodplain geomorphology influencing biogeochemical swaying of arsenic

Devanita Ghosh*, Santosh Kumar, Marinus Eric Donselaar, Cynthia Corroto, Ashok K. Ghosh

*Corresponding author for this work

Research output: Contribution to journalArticleScientificpeer-review

9 Citations (Scopus)

Abstract

Meandering-river geomorphology, forming abandoned channels/lakes with organic carbon-burial and microbial reductive dissolution, play many crucial roles in controlling arsenic (As) fluxes in sinks such as contaminated aquifers of riverine alluvial plains across the world. Suhiya oxbow-lake in the middle alluvial plain of the River Ganga, was selected as the natural laboratory. A top-down multidisciplinary approach was chosen employing satellite imagery to analyse the annual oxbow-lake surface vegetation dynamics (Eichhornia and Hydrilla). Side-scan sonar profiles across two oxbow lakes along with River Ganga core data and vintage topographical maps, estimated the lake-sedimentation rate of 9.6 cm/yr. Organic carbon [amino acids, aromatics, lingo-phenols and lipids hydrocarbons] infiltration-based on hydrophobicity and molecular-mass was detected at different depths along the water and sedimentary column. Elemental analysis showed lake surface to groundwater the As conc. varied from (0.37 to 185 μg/l). A microbial diversity based study showed that large sized photoautotrophs Nostoc, Anabaena are replaced by Fe-oxido-reducing As-metabolizing bacteria e.g. Acidovorax, Dechloromonas and enteric organisms e.g. Enterobacter, Salmonella at bottom of water column. Based on these inferences, a conceptual organic carbon transport model was constructed to understand the preferential preservation and microbial diagenesis resulting in mobilization of As and other geogenic elements.

Original languageEnglish
Article number144400
Number of pages14
JournalScience of the Total Environment
Volume762
DOIs
Publication statusPublished - 2021

Keywords

  • Arsenic
  • Biomarkers
  • Organic carbon
  • Oxbow Lakes
  • Remote sensing

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