Abstract

Suspended sediment is closely linked to nutrients, pollutants, and heavy metals, profoundly affecting aquatic ecosystems and widely recognized as a vital indicator of inland water health. Consequently, Suspended sediment concentration (SSC) can affect the growth of aquatic organisms in fish ponds, posing a substantial threat to aquaculture production. However, research on the long-term spatial and temporal dynamics of SSC, along with its response to various natural and anthropogenic factors in small water bodies like fish ponds, remains relatively scarce. This study aims to recalibrate current unified models using measured data to derive a more applicable SSC retrieval model specifically for the Guangdong-Hong Kong-Macao Greater Bay Area (GBA). Using Landsat top-of-atmosphere reflectance data from Google Earth Engine (GEE), the recalibrated model was utilized to generate SSC data for fish ponds in GBA spanning from 1986 to 2019.The results indicate that SSC in GBA fish ponds is significantly elevated during spring and summer compared to autumn and winter, with spring SSC recording the highest levels in most years. In the last 34 years, there has been a substantial overall decline in SSC in fish ponds, with an almost 50% reduction in the annual average SSC. Notably, this reduction was most pronounced in the northern, western, and eastern regions, resulting in a spatial pattern of higher SSC concentrations in the central and southern areas and lower concentrations in the surrounding regions. Correlation analysis unveiled substantial relationships (P < 0.01) between SSC interannual variations and factors like wind, speed, river sediment load, and NDVI, except for precipitation (P > 0.05). The surrounding land use of fish ponds and their proximity to rivers emerged as critical determinants influencing the spatial distribution of SSC. Furthermore, diverse aquaculture activities, such as the pond's farming cycle and production, play a significant role in regulating SSC, thereby influencing its temporal and spatial variations. GBA is one of China's highly developed aquaculture regions with dense populations, thus rendering the findings of this study valuable from both economic and ecological perspectives.

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