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Spatio-temporal variability of suspended particulate matter in a high-arctic estuary (Adventfjorden, Svalbard) using sentinel-2 time-series

  • Arctic coasts, which feature land-ocean transport of freshwater, sediments, and other terrestrial material, are impacted by climate change, including increased temperatures, melting glaciers, changes in precipitation and runoff. These trends are assumed to affect productivity in fjordic estuaries. However, the spatial extent and temporal variation of the freshwater-driven darkening of fjords remain unresolved. The present study illustrates the spatio-temporal variability of suspended particulate matter (SPM) in the Adventfjorden estuary, Svalbard, using in-situ field campaigns and ocean colour remote sensing (OCRS) via high-resolution Sentinel-2 imagery. To compute SPM concentration (C-SPMsat), a semi-analytical algorithm was regionally calibrated using local in-situ data, which improved the accuracy of satellite-derived SPM concentration by similar to 20% (MRD). Analysis of SPM concentration for two consecutive years (2019, 2020) revealed strong seasonality of SPM in Adventfjorden. Highest estimated SPM concentrations andArctic coasts, which feature land-ocean transport of freshwater, sediments, and other terrestrial material, are impacted by climate change, including increased temperatures, melting glaciers, changes in precipitation and runoff. These trends are assumed to affect productivity in fjordic estuaries. However, the spatial extent and temporal variation of the freshwater-driven darkening of fjords remain unresolved. The present study illustrates the spatio-temporal variability of suspended particulate matter (SPM) in the Adventfjorden estuary, Svalbard, using in-situ field campaigns and ocean colour remote sensing (OCRS) via high-resolution Sentinel-2 imagery. To compute SPM concentration (C-SPMsat), a semi-analytical algorithm was regionally calibrated using local in-situ data, which improved the accuracy of satellite-derived SPM concentration by similar to 20% (MRD). Analysis of SPM concentration for two consecutive years (2019, 2020) revealed strong seasonality of SPM in Adventfjorden. Highest estimated SPM concentrations and river plume extent (% of fjord with C-SPMsat > 30 mg L-1) occurred during June, July, and August. Concurrently, we observed a strong relationship between river plume extent and average air temperature over the 24 h prior to the observation (R-2 = 0.69). Considering predicted changes to environmental conditions in the Arctic region, this study highlights the importance of the rapidly changing environmental parameters and the significance of remote sensing in analysing fluxes in light attenuating particles, especially in the coastal Arctic Ocean.show moreshow less

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Author details:Daniela M. R. Walch, Rakesh K. Singh, Janne E. Soreide, Hugues LantuitORCiDGND, Amanda Poste
DOI:https://doi.org/10.3390/rs14133123
ISSN:2072-4292
Title of parent work (English):Remote sensing
Publisher:MDPI
Place of publishing:Basel
Publication type:Article
Language:English
Date of first publication:2022/06/29
Publication year:2022
Release date:2024/06/14
Tag:Arctic coast; SPM; coastal darkening; coastal ecosystems;; land-ocean-interaction; ocean colour; regional tuning; remote sensing; riverine inputs; sediment plumes
Volume:14
Issue:13
Article number:3123
Number of pages:22
Funding institution:Research Council of Norway [268458, 296836]; FramCenter for High North; Research "Fjord and Coast" - flagship ('FreshFate' project) [132019];; 2017-2018 Belmont Forum and BiodivERsA joint call for research; proposals, under the BiodivScen ERA-Net COFUND programme; Fonds de; recherche du Quebec; Nunataryuk project - European Union's Horizon 2020; Research and Innovation Program [773421]; Svalbard Science Forum's; Arctic Field Grant [RIS-ID: 11386]; Svalbard Integrated Arctic Earth; Observing System (SIOS), Norway; SIOS
Organizational units:Mathematisch-Naturwissenschaftliche Fakultät / Institut für Umweltwissenschaften und Geographie
DDC classification:5 Naturwissenschaften und Mathematik / 55 Geowissenschaften, Geologie / 550 Geowissenschaften
Peer review:Referiert
Publishing method:Open Access / Gold Open-Access
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License (German):License LogoCC-BY - Namensnennung 4.0 International
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