Mapping Dynamic Turbidity Maximum Zone of the Yellow River Estuary from 38 Years of Landsat Imagery

Author:

Chang Maoxiang,Li PengORCID,Sun Yue,Wang HoujieORCID,Li ZhenhongORCID

Abstract

Turbidity maximum zone (TMZ) plays a crucial role in estuarine ecosystems, exerting effects on erosion, environment evolution and socioeconomic activities in the coastal area. However, the long-term understanding of the TMZ in large river estuary such as the Yellow River estuary is still lacking. In this study, we focus on the TMZ distribution, variation and regulation mechanisms in the Yellow River estuary from different time scales. Based on time series Landsat images during the period 1984 to 2021 and Google Earth Engine (GEE), we proposed a TMZ extracting method in the Yellow River estuary to generate 322 TMZ maps. The overall accuracy of our algorithm reached 97.4%. The results show that there are clear decadal and seasonal TMZ variations during the 38-year period in the Yellow River estuary. Morphology, currents and wind speeds combined with seawater stratification have direct effects on TMZ at different time scales, while the direct impacts of tides and fluvial output of the Yellow River on TMZ are limited. In this article, the highly robust method provides a cost-effective alternative to accurately map the TMZ in global large river estuaries and systematically reveals the spatiotemporal evolution of TMZ, shedding light on the response mechanism of coastal geomorphology, marine ecological environment and biogeochemical cycle.

Funder

National Natural Science Foundation of China

National Key Research and Development Program of China

State Key Laboratory of Geodesy and Earth's Dynamics from Innovation Academy for Precision Measurement Science and Technology, Chinese Academy of Sciences

Publisher

MDPI AG

Subject

General Earth and Planetary Sciences

Cited by 1 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. InSAR-Derived Coastal Subsidence Reveals New Inundation Scenarios Over the Yellow River Delta;IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing;2023

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