Plume dispersion from the Nelson and Hayes rivers into Hudson Bay using satellite remote sensing of CDOM and suspended sediment
International audience Change in the dispersion pattern of Arctic river plumes due to climate change and hydroelectric regulation is challenging to monitor, calling for synoptic and continuous observation using satellite remote sensing. Algorithms for colored dissolved organic matter (CDOM) and tota...
Published in: | Elementa: Science of the Anthropocene |
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Format: | Article in Journal/Newspaper |
Language: | English |
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ftunivnantes:oai:HAL:hal-04007582v1 2023-05-15T15:16:00+02:00 Plume dispersion from the Nelson and Hayes rivers into Hudson Bay using satellite remote sensing of CDOM and suspended sediment Basu, Atreya Mccullough, Greg Bélanger, Simon Mukhopadhyay, Anirban Doxaran, David Sydor, Kevin Barber, David Ehn, Jens Laboratoire d'océanographie de Villefranche (LOV) Institut national des sciences de l'Univers (INSU - CNRS)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Institut de la Mer de Villefranche (IMEV) Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS) 2023-02-28 https://hal.science/hal-04007582 https://hal.science/hal-04007582/document https://hal.science/hal-04007582/file/Atreya_et_al_2023.pdf https://doi.org/10.1525/elementa.2022.00076 en eng HAL CCSD University of California Press info:eu-repo/semantics/altIdentifier/doi/10.1525/elementa.2022.00076 hal-04007582 https://hal.science/hal-04007582 https://hal.science/hal-04007582/document https://hal.science/hal-04007582/file/Atreya_et_al_2023.pdf doi:10.1525/elementa.2022.00076 info:eu-repo/semantics/OpenAccess EISSN: 2325-1026 Elementa: Science of the Anthropocene https://hal.science/hal-04007582 Elementa: Science of the Anthropocene, 2023, 11, ⟨10.1525/elementa.2022.00076⟩ River discharge River plume dispersion CDOM TSS Ocean color remote sensing Hudson Bay River discharge River plume dispersion CDOM TSS Ocean color remote sensing Hudson Bay [SDE]Environmental Sciences info:eu-repo/semantics/article Journal articles 2023 ftunivnantes https://doi.org/10.1525/elementa.2022.00076 2023-03-08T00:46:19Z International audience Change in the dispersion pattern of Arctic river plumes due to climate change and hydroelectric regulation is challenging to monitor, calling for synoptic and continuous observation using satellite remote sensing. Algorithms for colored dissolved organic matter (CDOM) and total suspended solids (TSS) were applied to moderate resolution imaging spectroradiometer (MODIS) imagery to study Nelson and Hayes river plume dispersion into southwestern Hudson Bay, employing quantile regressions to capture dispersion variability along a freshwater-marine gradient. MODIS-derived CDOM and TSS quantile concentrations (Q 0.05-Q 0.95) decreased exponentially with distance from the Nelson River mouth. The Q 0.95 asymptote marked the offshore extent of the river plume and was used to determine the marine and river water fractions of surface water in southwestern Hudson Bay. At about 125 km from the Nelson River mouth, CDOM was reduced by 75% of its river mouth values. Owing to the significant co-variability between CDOM dilution and river discharge, a 0.25 river water fraction was estimated at this distance, which varied by ±35 km during flood and ebb flows. Anti-cyclonic winds transported the river plume along the 54 azimuth towards central Hudson Bay, while cyclonic winds propagated the plume eastward along the south shore. Particle settling in the coastal waters and resuspension events from mudflats and/or bank erosion caused non-significant relationships between TSS and river discharge. This non-conservative behavior renders TSS a less useful optical tracer of Nelson and Hayes river water in southwestern Hudson Bay. The novel quantile regression approach for defining boundaries of river water dilution in transitional waters may provide helpful information for coastal management on a spatial scale of tens to hundreds of kilometers, ranging from near real-time monitoring to seasonal and multi-year studies. Article in Journal/Newspaper Arctic Climate change Hudson Bay Université de Nantes: HAL-UNIV-NANTES Arctic Bay River ENVELOPE(-81.662,-81.662,78.882,78.882) Hayes ENVELOPE(-64.167,-64.167,-66.833,-66.833) Hudson Hudson Bay Elementa: Science of the Anthropocene 11 1 |
institution |
Open Polar |
collection |
Université de Nantes: HAL-UNIV-NANTES |
op_collection_id |
ftunivnantes |
language |
English |
topic |
River discharge River plume dispersion CDOM TSS Ocean color remote sensing Hudson Bay River discharge River plume dispersion CDOM TSS Ocean color remote sensing Hudson Bay [SDE]Environmental Sciences |
spellingShingle |
River discharge River plume dispersion CDOM TSS Ocean color remote sensing Hudson Bay River discharge River plume dispersion CDOM TSS Ocean color remote sensing Hudson Bay [SDE]Environmental Sciences Basu, Atreya Mccullough, Greg Bélanger, Simon Mukhopadhyay, Anirban Doxaran, David Sydor, Kevin Barber, David Ehn, Jens Plume dispersion from the Nelson and Hayes rivers into Hudson Bay using satellite remote sensing of CDOM and suspended sediment |
topic_facet |
River discharge River plume dispersion CDOM TSS Ocean color remote sensing Hudson Bay River discharge River plume dispersion CDOM TSS Ocean color remote sensing Hudson Bay [SDE]Environmental Sciences |
description |
International audience Change in the dispersion pattern of Arctic river plumes due to climate change and hydroelectric regulation is challenging to monitor, calling for synoptic and continuous observation using satellite remote sensing. Algorithms for colored dissolved organic matter (CDOM) and total suspended solids (TSS) were applied to moderate resolution imaging spectroradiometer (MODIS) imagery to study Nelson and Hayes river plume dispersion into southwestern Hudson Bay, employing quantile regressions to capture dispersion variability along a freshwater-marine gradient. MODIS-derived CDOM and TSS quantile concentrations (Q 0.05-Q 0.95) decreased exponentially with distance from the Nelson River mouth. The Q 0.95 asymptote marked the offshore extent of the river plume and was used to determine the marine and river water fractions of surface water in southwestern Hudson Bay. At about 125 km from the Nelson River mouth, CDOM was reduced by 75% of its river mouth values. Owing to the significant co-variability between CDOM dilution and river discharge, a 0.25 river water fraction was estimated at this distance, which varied by ±35 km during flood and ebb flows. Anti-cyclonic winds transported the river plume along the 54 azimuth towards central Hudson Bay, while cyclonic winds propagated the plume eastward along the south shore. Particle settling in the coastal waters and resuspension events from mudflats and/or bank erosion caused non-significant relationships between TSS and river discharge. This non-conservative behavior renders TSS a less useful optical tracer of Nelson and Hayes river water in southwestern Hudson Bay. The novel quantile regression approach for defining boundaries of river water dilution in transitional waters may provide helpful information for coastal management on a spatial scale of tens to hundreds of kilometers, ranging from near real-time monitoring to seasonal and multi-year studies. |
author2 |
Laboratoire d'océanographie de Villefranche (LOV) Institut national des sciences de l'Univers (INSU - CNRS)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Institut de la Mer de Villefranche (IMEV) Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS) |
format |
Article in Journal/Newspaper |
author |
Basu, Atreya Mccullough, Greg Bélanger, Simon Mukhopadhyay, Anirban Doxaran, David Sydor, Kevin Barber, David Ehn, Jens |
author_facet |
Basu, Atreya Mccullough, Greg Bélanger, Simon Mukhopadhyay, Anirban Doxaran, David Sydor, Kevin Barber, David Ehn, Jens |
author_sort |
Basu, Atreya |
title |
Plume dispersion from the Nelson and Hayes rivers into Hudson Bay using satellite remote sensing of CDOM and suspended sediment |
title_short |
Plume dispersion from the Nelson and Hayes rivers into Hudson Bay using satellite remote sensing of CDOM and suspended sediment |
title_full |
Plume dispersion from the Nelson and Hayes rivers into Hudson Bay using satellite remote sensing of CDOM and suspended sediment |
title_fullStr |
Plume dispersion from the Nelson and Hayes rivers into Hudson Bay using satellite remote sensing of CDOM and suspended sediment |
title_full_unstemmed |
Plume dispersion from the Nelson and Hayes rivers into Hudson Bay using satellite remote sensing of CDOM and suspended sediment |
title_sort |
plume dispersion from the nelson and hayes rivers into hudson bay using satellite remote sensing of cdom and suspended sediment |
publisher |
HAL CCSD |
publishDate |
2023 |
url |
https://hal.science/hal-04007582 https://hal.science/hal-04007582/document https://hal.science/hal-04007582/file/Atreya_et_al_2023.pdf https://doi.org/10.1525/elementa.2022.00076 |
long_lat |
ENVELOPE(-81.662,-81.662,78.882,78.882) ENVELOPE(-64.167,-64.167,-66.833,-66.833) |
geographic |
Arctic Bay River Hayes Hudson Hudson Bay |
geographic_facet |
Arctic Bay River Hayes Hudson Hudson Bay |
genre |
Arctic Climate change Hudson Bay |
genre_facet |
Arctic Climate change Hudson Bay |
op_source |
EISSN: 2325-1026 Elementa: Science of the Anthropocene https://hal.science/hal-04007582 Elementa: Science of the Anthropocene, 2023, 11, ⟨10.1525/elementa.2022.00076⟩ |
op_relation |
info:eu-repo/semantics/altIdentifier/doi/10.1525/elementa.2022.00076 hal-04007582 https://hal.science/hal-04007582 https://hal.science/hal-04007582/document https://hal.science/hal-04007582/file/Atreya_et_al_2023.pdf doi:10.1525/elementa.2022.00076 |
op_rights |
info:eu-repo/semantics/OpenAccess |
op_doi |
https://doi.org/10.1525/elementa.2022.00076 |
container_title |
Elementa: Science of the Anthropocene |
container_volume |
11 |
container_issue |
1 |
_version_ |
1766346316601884672 |