Source Region Geochemistry From Unmixing Downstream Sedimentary Elemental Compositions
Abstract The geochemistry of river sediments is routinely used to obtain information about geologic and environmental processes occurring upstream. For example, downstream samples are used to constrain chemical weathering and physical erosion rates upstream, as well as the locations of mineral depos...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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Wiley
2021-10-01
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| Series: | Geochemistry, Geophysics, Geosystems |
| Subjects: | |
| Online Access: | https://doi.org/10.1029/2021GC009838 |
| _version_ | 1797638109276405760 |
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| author | Alex G. Lipp Gareth G. Roberts Alexander C. Whittaker Charles J. B. Gowing Victoria M. Fernandes |
| author_facet | Alex G. Lipp Gareth G. Roberts Alexander C. Whittaker Charles J. B. Gowing Victoria M. Fernandes |
| author_sort | Alex G. Lipp |
| collection | DOAJ |
| description | Abstract The geochemistry of river sediments is routinely used to obtain information about geologic and environmental processes occurring upstream. For example, downstream samples are used to constrain chemical weathering and physical erosion rates upstream, as well as the locations of mineral deposits or contaminant sources. Previous work has shown that, by assuming conservative mixing, the geochemistry of downstream samples can be reliably predicted given a known source region geochemistry. In this study, we tackle the inverse problem and “unmix” the composition of downstream river sediments to produce geochemical maps of drainage basins (i.e., source regions). The scheme is tested in a case study of rivers draining the Cairngorms, UK. The elemental geochemistry of the <150 μm fraction of 67 samples gathered from the beds of channels in this region is used to invert for concentrations of major and trace elements upstream. A smoothed inverse problem is solved using the Nelder‐Mead optimization algorithm. Predictions of source region geochemistry are assessed by comparing the spatial distribution of 22 elements of different affinities (e.g., Be, Li, Mg, Ca, Rb, U, V) using independent geochemical survey data. The inverse approach makes reliable predictions of the major and trace element concentration in first order river sediments. We suggest this scheme could be a novel means to generate geochemical baselines across drainage basins and within river channels. |
| first_indexed | 2024-03-11T12:57:53Z |
| format | Article |
| id | doaj.art-c726fbcc11e94c11839ea74a0ff5e4ed |
| institution | Directory Open Access Journal |
| issn | 1525-2027 |
| language | English |
| last_indexed | 2024-03-11T12:57:53Z |
| publishDate | 2021-10-01 |
| publisher | Wiley |
| record_format | Article |
| series | Geochemistry, Geophysics, Geosystems |
| spelling | doaj.art-c726fbcc11e94c11839ea74a0ff5e4ed2023-11-03T16:56:09ZengWileyGeochemistry, Geophysics, Geosystems1525-20272021-10-012210n/an/a10.1029/2021GC009838Source Region Geochemistry From Unmixing Downstream Sedimentary Elemental CompositionsAlex G. Lipp0Gareth G. Roberts1Alexander C. Whittaker2Charles J. B. Gowing3Victoria M. Fernandes4Department of Earth Science and Engineering Imperial College London London UKDepartment of Earth Science and Engineering Imperial College London London UKDepartment of Earth Science and Engineering Imperial College London London UKCentre for Environmental Geochemistry British Geological Survey Keyworth UKDepartment of Earth Science and Engineering Imperial College London London UKAbstract The geochemistry of river sediments is routinely used to obtain information about geologic and environmental processes occurring upstream. For example, downstream samples are used to constrain chemical weathering and physical erosion rates upstream, as well as the locations of mineral deposits or contaminant sources. Previous work has shown that, by assuming conservative mixing, the geochemistry of downstream samples can be reliably predicted given a known source region geochemistry. In this study, we tackle the inverse problem and “unmix” the composition of downstream river sediments to produce geochemical maps of drainage basins (i.e., source regions). The scheme is tested in a case study of rivers draining the Cairngorms, UK. The elemental geochemistry of the <150 μm fraction of 67 samples gathered from the beds of channels in this region is used to invert for concentrations of major and trace elements upstream. A smoothed inverse problem is solved using the Nelder‐Mead optimization algorithm. Predictions of source region geochemistry are assessed by comparing the spatial distribution of 22 elements of different affinities (e.g., Be, Li, Mg, Ca, Rb, U, V) using independent geochemical survey data. The inverse approach makes reliable predictions of the major and trace element concentration in first order river sediments. We suggest this scheme could be a novel means to generate geochemical baselines across drainage basins and within river channels.https://doi.org/10.1029/2021GC009838sedimentary geochemistryinverse modelingfluvial geomorphologymixinggeochemical mapping |
| spellingShingle | Alex G. Lipp Gareth G. Roberts Alexander C. Whittaker Charles J. B. Gowing Victoria M. Fernandes Source Region Geochemistry From Unmixing Downstream Sedimentary Elemental Compositions Geochemistry, Geophysics, Geosystems sedimentary geochemistry inverse modeling fluvial geomorphology mixing geochemical mapping |
| title | Source Region Geochemistry From Unmixing Downstream Sedimentary Elemental Compositions |
| title_full | Source Region Geochemistry From Unmixing Downstream Sedimentary Elemental Compositions |
| title_fullStr | Source Region Geochemistry From Unmixing Downstream Sedimentary Elemental Compositions |
| title_full_unstemmed | Source Region Geochemistry From Unmixing Downstream Sedimentary Elemental Compositions |
| title_short | Source Region Geochemistry From Unmixing Downstream Sedimentary Elemental Compositions |
| title_sort | source region geochemistry from unmixing downstream sedimentary elemental compositions |
| topic | sedimentary geochemistry inverse modeling fluvial geomorphology mixing geochemical mapping |
| url | https://doi.org/10.1029/2021GC009838 |
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