4.7 Article

Satellite Remote Sensing of Water Quality Variation in a Semi-Enclosed Bay (Yueqing Bay) under Strong Anthropogenic Impact

Journal

REMOTE SENSING
Volume 14, Issue 3, Pages -

Publisher

MDPI
DOI: 10.3390/rs14030550

Keywords

nutrient; satellite remote sensing; support vector machine; long time series; driving factor; Yueqing Bay

Funding

  1. National Key Research and Development Program of China [2017YFA0603003]
  2. Key Special Project for Introduced Talents Team of Southern Marine Science and Engineering Guangdong Laboratory (Guangzhou) [GML2019ZD0602]
  3. Scientific Research Fund of the Second Institute of Oceanography, MNR [YJJC2105]
  4. National Natural Science Foundation of China [41825014]
  5. hejiang Provincial Natural Science Foundation of China [2017R52001, LR18D060001]

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This study explores the use of satellite-based water quality monitoring and variation analysis to understand the impact of anthropogenic activities on semi-enclosed bays. The research highlights the need for continuous monitoring and long-term ecological protection and restoration to effectively address issues such as eutrophication and water quality deterioration. The findings can provide a reference for ecological environment monitoring and remote sensing data application in similar bays and support sustainable development.
The semi-enclosed bays impacted by heavy anthropogenic activities have weak water exchange and purification capacities. Most of the sea bays have suffered severe eutrophication, water quality deterioration, ecosystem degradation and other problems. Although many countries and local governments have carried out corresponding environmental protection actions, the evaluation of their effectiveness still requires monitoring technology and data support for long-term water environment change. In this study, we take Yueqing Bay, the fourth largest bay in China, as a case to study the satellite-based water quality monitoring and variation analysis. We established a nutrient retrieval model for Yueqing Bay to produce a long-term series of nutrient concentration products in Yueqing Bay from 2013 to 2020, based on Landsat remote sensing images and long-term observation data, combined with support vector machine learning and water temperature and satellite spectra as input parameters, and then we analyzed its spatiotemporal variations and driving factors. In general, nutrient concentrations in the western part of the bay were higher than those in the eastern part. Levels of dissolved inorganic nitrogen (DIN) were lower in summer than in spring and winter, and reactive phosphate (PO4-P) levels were lower in summer and higher in autumn. In terms of natural factors, physical effects (e.g., seasonal variations in flow field) and biological effects (e.g., seasonal differences in the intensity of plankton photosynthesis) were the main causes of seasonal differences in nutrient concentration in Yueqing Bay. Nutrient concentration generally increased from 2013 to 2015 but decreased slightly after 2015. Over the past decade, the economy and industry of Yueqing Bay basin have developed rapidly. Wastewater resulting from anthropogenic production and consumption was transported via streams into Yueqing Bay, leading to the continuous increase in nutrient concentrations (the variation rates: a(DIN)> 0, a(PO4-P)> 0), which directly or indirectly caused high nutrient concentrations in some areas of the bay (e.g., Southwest Shoal at the mouth of Yueqing Bay). After 2015, the various ecological remediation policies adopted by cities around Yueqing Bay have mitigated, to some extent, the increasing nutrient concentration trends (the variation rates: a(DIN)< 0, a(PO4-P)< 0), but not significantly (P > 0.1). The environmental restoration of Yueqing Bay also requires continuous and long-term ecological protection and restoration work to be effective. This research can provide a reference for ecological environment monitoring and remote sensing data application for similar semi-enclosed bays, and support the sustainable development of the bay.

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