AUTHOR=Cao Shuhui , Xiao Fei , Chen Miaomiao , Wang Zhou , Luo Jiahuan , Du Yun 

TITLE=Inversion and analysis of transparency changes in the eastern coastal waters of China from 2003 to 2023 by an improved QAA-based method

JOURNAL=Frontiers in Marine Science

VOLUME=11

YEAR=2024

URL=https://www.frontiersin.org/journals/marine-science/articles/10.3389/fmars.2024.1503177

DOI=10.3389/fmars.2024.1503177

ISSN=2296-7745

ABSTRACT=<p>Transparency (<inline-formula><mml:math display="inline" id="im1" xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mrow><mml:msub><mml:mi>Z</mml:mi><mml:mrow><mml:mi>s</mml:mi><mml:mi>d</mml:mi></mml:mrow></mml:msub></mml:mrow></mml:math></inline-formula>) can most intuitively reflect changes in marine ecosystems, therefore; the data of <inline-formula><mml:math display="inline" id="im2" xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mrow><mml:msub><mml:mi>Z</mml:mi><mml:mrow><mml:mi>s</mml:mi><mml:mi>d</mml:mi></mml:mrow></mml:msub></mml:mrow></mml:math></inline-formula> is crucial to protect marine ecosystems. However, there is still a relative lack of long-term sequence data on <inline-formula><mml:math display="inline" id="im3" xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mrow><mml:msub><mml:mi>Z</mml:mi><mml:mrow><mml:mi>s</mml:mi><mml:mi>d</mml:mi></mml:mrow></mml:msub></mml:mrow></mml:math></inline-formula> for coastal turbid waters. Satellite remote sensing inversion provides an efficient means of obtaining long-term, large-scale <inline-formula><mml:math display="inline" id="im4" xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mrow><mml:msub><mml:mi>Z</mml:mi><mml:mrow><mml:mi>s</mml:mi><mml:mi>d</mml:mi></mml:mrow></mml:msub></mml:mrow></mml:math></inline-formula>. The method proposed by Lee et al. is currently one of the most widely used methods, which is divided into clear water and turbid water models based on the 670 nm remote sensing reflectance (<inline-formula><mml:math display="inline" id="im5" xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mrow><mml:msub><mml:mi>R</mml:mi><mml:mrow><mml:mi>r</mml:mi><mml:mi>s</mml:mi></mml:mrow></mml:msub></mml:mrow></mml:math></inline-formula>). In this study, we employed an improved model building upon the aforementioned method. The improved model simulates the continuous transition from clear to turbid water, which allows for automatic adjustment of model weights based on a logistic curve. Utilizing this improved model, this study inverts <inline-formula><mml:math display="inline" id="im6" xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mrow><mml:msub><mml:mi>Z</mml:mi><mml:mrow><mml:mi>s</mml:mi><mml:mi>d</mml:mi></mml:mrow></mml:msub></mml:mrow></mml:math></inline-formula> within 100 km of the eastern coast of China from 2003 to 2023 using MODIS Aqua Level 2 <inline-formula><mml:math display="inline" id="im7" xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mrow><mml:msub><mml:mi>R</mml:mi><mml:mrow><mml:mi>r</mml:mi><mml:mi>s</mml:mi></mml:mrow></mml:msub></mml:mrow></mml:math></inline-formula> data. <inline-formula><mml:math display="inline" id="im8" xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mrow><mml:msub><mml:mi>Z</mml:mi><mml:mrow><mml:mi>s</mml:mi><mml:mi>d</mml:mi></mml:mrow></mml:msub></mml:mrow></mml:math></inline-formula> shows an increasing trend with the distance from the coast, with high <inline-formula><mml:math display="inline" id="im9" xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mrow><mml:msub><mml:mi>Z</mml:mi><mml:mrow><mml:mi>s</mml:mi><mml:mi>d</mml:mi></mml:mrow></mml:msub></mml:mrow></mml:math></inline-formula> in the northern Yellow Sea, the southern Shandong Peninsula, and the far shore of the East China Sea, and the low <inline-formula><mml:math display="inline" id="im10" xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mrow><mml:msub><mml:mi>Z</mml:mi><mml:mrow><mml:mi>s</mml:mi><mml:mi>d</mml:mi></mml:mrow></mml:msub></mml:mrow></mml:math></inline-formula> in the coast of Bohai Sea and northern Jiangsu. As for the long-term changes, the number of pixels with significantly increased <inline-formula><mml:math display="inline" id="im11" xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mrow><mml:msub><mml:mi>Z</mml:mi><mml:mrow><mml:mi>s</mml:mi><mml:mi>d</mml:mi></mml:mrow></mml:msub></mml:mrow></mml:math></inline-formula> and those with significantly decreased <inline-formula><mml:math display="inline" id="im12" xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mrow><mml:msub><mml:mi>Z</mml:mi><mml:mrow><mml:mi>s</mml:mi><mml:mi>d</mml:mi></mml:mrow></mml:msub></mml:mrow></mml:math></inline-formula> and no significant changes accounted for 20.84%, 1.14%, and 78.02%, respectively. The order of seasonal <inline-formula><mml:math display="inline" id="im13" xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mrow><mml:msub><mml:mi>Z</mml:mi><mml:mrow><mml:mi>s</mml:mi><mml:mi>d</mml:mi></mml:mrow></mml:msub></mml:mrow></mml:math></inline-formula> is summer &gt; autumn &gt; spring &gt; winter, and the seasonal variability amplitude increases synchronously with the offshore distance of seawater on the whole. Interestingly, the correlation between <inline-formula><mml:math display="inline" id="im14" xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mrow><mml:msub><mml:mi>Z</mml:mi><mml:mrow><mml:mi>s</mml:mi><mml:mi>d</mml:mi></mml:mrow></mml:msub></mml:mrow></mml:math></inline-formula> and the annual runoff of rivers exhibits spatial differentiation among six typical estuaries: there are positive correlations in northern, whereas negative correlations in the south. Additionally, the <inline-formula><mml:math display="inline" id="im15" xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mrow><mml:msub><mml:mi>Z</mml:mi><mml:mrow><mml:mi>s</mml:mi><mml:mi>d</mml:mi></mml:mrow></mml:msub></mml:mrow></mml:math></inline-formula> in five of six estuaries have negative correlations with annual sediment transport. Overall, this study not only provides more accurate and continuous data of <inline-formula><mml:math display="inline" id="im16" xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mrow><mml:msub><mml:mi>Z</mml:mi><mml:mrow><mml:mi>s</mml:mi><mml:mi>d</mml:mi></mml:mrow></mml:msub></mml:mrow></mml:math></inline-formula> for nearshore turbid waters compared to those obtained by the original model, but also offers valuable insights on the spatiotemporal variation in the <inline-formula><mml:math display="inline" id="im17" xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mrow><mml:msub><mml:mi>Z</mml:mi><mml:mrow><mml:mi>s</mml:mi><mml:mi>d</mml:mi></mml:mrow></mml:msub></mml:mrow></mml:math></inline-formula> of large-scale seawater.</p>