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Monitoring suspended sediment concentration in the Yellow River Estuary from 1984 to 2021 using landsat imagery and Google Earth Engine

Yu, Dingfeng, Bian, Xiaodong, Yang, Lei, Zhou, Yan, An, Deyu, Zhou, Maosheng, Chen, Shenliang and Pan, Shunqi ORCID: https://orcid.org/0000-0001-8252-5991 2023. Monitoring suspended sediment concentration in the Yellow River Estuary from 1984 to 2021 using landsat imagery and Google Earth Engine. International Journal of Remote Sensing 44 (10) , pp. 3122-3145. 10.1080/01431161.2023.2216849

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Abstract

The transport of suspended sediment in estuaries affects the erosion and deposition of estuaries and changes in landform patterns, and it has a profound impact on primary productivity and ecosystem regulation in estuaries. It is of great value for coastal construction and environmental monitoring to study the surface suspended sediment concentration (SSC) in estuaries and adjacent waters. Using 2355 Landsat 5/7/8 satellite images from the Google Earth Engine, the SSC in the surface layer of the Yellow River Estuary from 1984 to 2021 was studied. The results showed that from 1984 to 2021, the SSC declined by more than 30%. The Xiaolangdi Dam and Water and Sediment Regulation Scheme have affected the sediment transport and runoff of the Yellow River, which can explain more than 40% of the SSC in the buffer area of the estuary and have a close relationship with the inter-monthly changes in SSC. The diversion of estuaries and circulation to the transport of suspended sediment have largely affected the changes in nearshore SSC, including the spatial patterns and temporal variations in SSC. Wave changes caused by wind speed on the sea surface can explain the inner-annual changes in SSC in Laizhou Bay and southern Bohai Bay. From January to February, the area of high concentration zones (100 mg L−1≤SSC) accounts for more than 10%, higher than in other months, and re-suspension of sediment caused by wind is the main reason for the increase in SSC.

Item Type: Article
Date Type: Published Online
Status: Published
Schools: Advanced Research Computing @ Cardiff (ARCCA)
Engineering
Publisher: Taylor and Francis Group
ISSN: 0143-1161
Date of Acceptance: 13 May 2023
Last Modified: 12 Jun 2024 12:37
URI: https://orca.cardiff.ac.uk/id/eprint/160292

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