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Sea Surface Salinity Spatio-Temporal Differentiation in Yangtze Estuarine Waters Using MODIS
Niu Ying, Zhao Xinyi, Zhou Yunxuan, Tian Bo, Wang Lihua
Journal of Jilin University(Earth Science Edition). 2019, 49 (5):
1486-1495.
DOI: 10.13278/j.cnki.jjuese.20180212
The Yangtze Estuary is located in the intersection of sea and land, and its sea surface salinity (SSS) is affected by the Yangtze River, East China Sea, and social and economic activities of the delta. Salinity can directly reflect the distribution of freshwater plumes;therefore, the research on the spatial and temporal distribution and variation of the Yangtze River salinity is significant for understanding the importance of freshwater plumes, material transport,and estuarine environment. Terra MODIS (moderate-resolution imaging spectroradiometer) remote sensing reflectance, reflectance ratio and field data in dry and flood seasons were used to establish the experienced retrieval models of the Yangtze Estuary, and their RMSE are 0.45‰ and 0.88‰ respectively. The applicability of the model in time scale was also analyzed. The models were used to retrieve SSS in the Yangtze estuarine waters from 2007 to 2016, combined with the runoff observational data from the Datong gauging station, the temporal and spatial variations of SSS were analyzed. The results showed that the SSS distribution in the Yangtze Estuary appeared increasing from the west to the east, which was deeply influenced by the Yangtze River runoff with obvious seasonal differentiation. The off-shore SSS appeared high in the dry season, with high SSS waters reaching westward 123°E, around the bifurcation of the southern and the northern branches of the Yangtze Estuary. Diluted water influenced a larger area in the flood season, which caused the high SSS waters gathering east of 123°E and south of 31°N, along with a low SSS area in the north of the Yangtze Estuary. The Datong gauging station runoff increased during 2007 to 2016 in the flood season, along with the decrease of the average SSS of the study area, and the average SSS was 29.27‰. The runoff decreased in the dry season, along with the increase of the average SSS, and the average SSS was 27.10‰. The SSS variations during 2007 to 2016 had a negative correlation with runoff.
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