Large-scale algal biomass mapping from OLCI observations for lakes in both basins of the Changjiang (Yangtze) River and the Huaihe River, China

Zhengyang YU; Ronghua MA; Chuanmin HU; Minqi HU; Kun XUE; Junfeng XIONG

doi:10.1007/s00343-026-5485-x

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Large-scale algal biomass mapping from OLCI observations for lakes in both basins of the Changjiang (Yangtze) River and the Huaihe River, China

Inland water color remote sensing algorithms | Updated：2026-09-15

- Large-scale algal biomass mapping from OLCI observations for lakes in both basins of the Changjiang (Yangtze) River and the Huaihe River, China
- Journal of Oceanology and Limnology Vol. 44, Pages: 2119-2135(2026)
- Affiliations：
  
  1.School of Geography and Planning, Huaiyin Normal University, Huai'an 223300, China
  2.Key Laboratory of Lake and Watershed Science for Water Security, Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, Nanjing 210008, China
  3.University of Chinese Academy of Sciences, Nanjing 211135, China
  4.College of Marine Science, University of South Florida, St. Petersburg 33701, USA
- Author bio：
  
  rhma@niglas.ac.cn
- Funds：
- DOI：10.1007/s00343-026-5485-x
  CLC：
- Received：27 November 2025，
  
  Online First：15 September 2026，
  
  Published：01 September 2026
- Accepted：
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YU Zhengyang,MA Ronghua,HU Chuanmin,et al.Large-scale algal biomass mapping from OLCI observations for lakes in both basins of the Changjiang (Yangtze) River and the Huaihe River, China[J].Journal of Oceanology and Limnology,
DOI：

YU Zhengyang,MA Ronghua,HU Chuanmin,et al.Large-scale algal biomass mapping from OLCI observations for lakes in both basins of the Changjiang (Yangtze) River and the Huaihe River, China[J].Journal of Oceanology and Limnology, DOI：.

摘要

Abstract

While existing studies on the remote estimation of algal biomass have focused predominantly on case-specific analyses

systematic assessments of large-scale spatial patterns remain underexplored. To address this knowledge gap

we developed a novel classification-based framework utilizing Ocean and Land Color Instrument (OLCI) satellite imagery

enabling the first multiyear (2016–2023) mapping of algal biomass within the euphotic depth (

) across 24 lakes in the middle-lower Changjiang (Yangtze) and Huaihe rivers basins

China. The methodology employed the adjusted Davies-Bouldin index (ADBI) as a metric for assessing classification efficacy and was validated through the match-up dataset (root mean square error=13.24 mg/m²

mean absolute percentage error=36.3%

=40). Spatiotemporal analysis revealed that the total algal biomass within the euphotic zone (total

) of the hyper-sized lakes was lower in 2018 and 2023 than in the other years and remained relatively stable for four years (2019–2022). For large lakes

the interannual total

showed a distinct single-peak trend over the study period

with the highest value occurring in 2019. In contrast

medium-sized lakes exhibited relatively subtle interannual fluctuations without a clear temporal pattern. Our work reveals previously undocumented spatial heterogeneity in the distribution of algal biomass and provides a foundational dataset for monitoring eutrophication dynamics under climate change.

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