Yang Junying, Deng Ruru, Ma Yiwei, Li Jiayi, Guo Yu, Lei Cong
School of Geography and Planning, Sun Yat-sen University, Guangzhou 510006, China.
Guangdong Engineering Research Center of Water Environment Remote Sensing Monitoring, Guangzhou 510006, China.
Sensors (Basel). 2025 Mar 11;25(6):1728. doi: 10.3390/s25061728.
The Guangdong-Hong Kong-Macao Greater Bay Area (GBA) is one of the most urbanized and industrialized coastal regions in China, where intense human activities contribute to substantial terrestrial sediment discharge into the adjacent marine environment. However, complex hydrodynamic conditions and high spatiotemporal variability pose challenges for accurate suspended sediment concentration (SSC) retrieval. Developing water quality retrieval models based on different classifications of water bodies could enhance the accuracy of SSC inversion in coastal waters. Therefore, this study classified the coastal waters of the GBA into clear and turbid zones based on Hue angle α, and established retrieval models for SSC using a single-scattering approximation model for clear zones and a secondary-scattering approximation model for turbid zones based on radiative transfer processes. Model validation with in-situ data shows a coefficient of determination (R) of 0.73, a root mean square error (RMSE) of 8.30, and a mean absolute percentage error (MAPE) of 42.00%. Spatial analysis further reveals higher SSC in the waters around Qi'ao Island in the Pearl River Estuary (PRE) and along the coastline of Guanghai Bay, identifying these two areas as priorities for attention. This study aims to offer valuable insights for SSC management in the coastal waters of the GBA.
粤港澳大湾区是中国城市化和工业化程度最高的沿海地区之一,人类活动频繁,导致大量陆地沉积物排入邻近海洋环境。然而,复杂的水动力条件和高时空变异性给准确反演悬浮泥沙浓度(SSC)带来了挑战。基于水体的不同分类开发水质反演模型,可以提高近岸海域SSC反演的准确性。因此,本研究基于色调角α将大湾区近岸海域划分为清水区和浊水区,并根据辐射传输过程,利用清水区的单次散射近似模型和浊水区的二次散射近似模型建立了SSC反演模型。利用现场数据进行模型验证,结果显示决定系数(R)为0.73,均方根误差(RMSE)为8.30,平均绝对百分比误差(MAPE)为42.00%。空间分析进一步显示,珠江口淇澳岛附近海域和广海湾沿岸的SSC较高,确定这两个区域为重点关注区域。本研究旨在为大湾区近岸海域的SSC管理提供有价值的见解。