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<p>Water clarity (Secchi disk depth, <i>Z</i><sub>SD</sub>) and Forel-Ule Index (FUI) are critical ecological indicators for assessing water quality. Although satellite remote sensing serves as a vital tool for large-scale and long-term water quality monitoring, low accuracy, coarse resolution, and incomplete spatial coverage of existing satellite <i>Z</i><sub>SD</sub> and FUI products hindered the reliable ecological assessment of water quality. Here, a long-term (2003–2023) satellite dataset of monthly <i>Z</i><sub>SD</sub> and FUI was developed by applying the advanced high-accuracy retrieval algorithms and reconstruction method to 35 546 Moderate-resolution Imaging Spectroradiometer (MODIS) images over China coastal waters. The new dataset exhibited superior performance compared to the existing one, in terms of higher accuracy (Mean Absolute Percentage Error, MAPE = 28.89% for <i>Z</i><sub>SD</sub> and MAPE = 34.46% for FUI), spatio-temporal resolution (monthly, 1 km), and spatial coverage (99.53%), with the most significant improvement found in the nearshore turbid waters. By leveraging this dataset, the ecological impact of human activities on water quality was accurately revealed, as indicated by the significant <i>Z</i><sub>SD</sub> improvements during terrestrial pollution control, which was misinterpreted by previous satellite products. Besides, natural factor-induced water quality variability was also successfully captured, particularly the seasonal dynamics of suspended sediment plumes in the East China Sea. The new dataset and adopted methods may provide essential support for the accurate monitoring, ecological assessment, and sustainable management of marine ecosystems.</p>

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A high accuracy, spatiotemporal coverage, and resolution satellite dataset of water clarity and Forel-Ule Index over China coastal waters (2003–2023)

  • 期刊论文

  • 发表日期：

    2025年9月1日

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  • Tianyi Hao,
  • Binyu Wang,
  • Xuyan Li,
  • Jinzhao Xiang,
  • Bing Mu,
  • Tingwei Cui

摘要

Water clarity (Secchi disk depth, ZSD) and Forel-Ule Index (FUI) are critical ecological indicators for assessing water quality. Although satellite remote sensing serves as a vital tool for large-scale and long-term water quality monitoring, low accuracy, coarse resolution, and incomplete spatial coverage of existing satellite ZSD and FUI products hindered the reliable ecological assessment of water quality. Here, a long-term (2003–2023) satellite dataset of monthly ZSD and FUI was developed by applying the advanced high-accuracy retrieval algorithms and reconstruction method to 35 546 Moderate-resolution Imaging Spectroradiometer (MODIS) images over China coastal waters. The new dataset exhibited superior performance compared to the existing one, in terms of higher accuracy (Mean Absolute Percentage Error, MAPE = 28.89% for ZSD and MAPE = 34.46% for FUI), spatio-temporal resolution (monthly, 1 km), and spatial coverage (99.53%), with the most significant improvement found in the nearshore turbid waters. By leveraging this dataset, the ecological impact of human activities on water quality was accurately revealed, as indicated by the significant ZSD improvements during terrestrial pollution control, which was misinterpreted by previous satellite products. Besides, natural factor-induced water quality variability was also successfully captured, particularly the seasonal dynamics of suspended sediment plumes in the East China Sea. The new dataset and adopted methods may provide essential support for the accurate monitoring, ecological assessment, and sustainable management of marine ecosystems.