Assessing nearshore sediment and sea surface temperature dynamics using Landsat satellite imagery at Herschel Island, western Canadian Arctic

The Arctic is subject to substantial changes due to the greenhouse gas induced climate change. While impacts on lateral transport pathways such as rivers have been extensively studied yet, there is little knowledge about ecological and geological reactions of nearshore environments, even though thos...

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Bibliographic Details
Main Authors: Klein, Konstantin P., Lantuit, Hugues, Heim, Birgit, Fell, Frank, Vonk, Jorien E., Jong, Dirk J.
Format: Conference Object
Language:unknown
Published: 2018
Subjects:
Online Access:https://epic.awi.de/id/eprint/48157/
https://hdl.handle.net/10013/epic.750866d7-53c2-409e-b703-169421be0a89
Description
Summary:The Arctic is subject to substantial changes due to the greenhouse gas induced climate change. While impacts on lateral transport pathways such as rivers have been extensively studied yet, there is little knowledge about ecological and geological reactions of nearshore environments, even though those are of high importance for native communities. In this study, we use the extensive Landsat archive with comparable data from 1982 on to investigate sediment dispersal and sea surface temperatures under changing seasonal wind conditions in the nearshore zone of Herschel Island in the western Canadian Arctic. Even in the absence of an extensive in-situ dataset, we reveal clear differences between the two prevailing wind conditions (E and NW). During E wind conditions, the Mackenzie River Plume gets distributed over large parts of the Canadian Beaufort Shelf and is the main influencing factor for nearshore sediment dispersal and sea surface temperature dynamics. Contrary, the nearshore dynamics during NW wind conditions are not affected by the Mackenzie River plume, revealing the local nature of the nearshore environment. First field measurements from summer 2017 indicate that recently published SPM and turbidity models are not able to reflect this local nature and strongly underestimate reality. In future, we plan to collect an extensive validation dataset in Arctic nearshore environments to calculate accurate bio-optical models.