A comprehensive time-series dataset linked to cyanobacterial blooms in Lake Taihu

Lake Taihu has a history of recurrent harmful cyanobacterial blooms. There is a need to better understand the aquatic ecosystem of Lake Taihu in order to improve methods for controlling the cyanobacterial blooms. Based on the field measurement and satellite remote sensing, we produced and collected a time-series dataset, including the water quality, bio-optics, climate, and anthropogenic data of Lake Taihu (THQBCA), which could provide comprehensive information regarding cyanobacterial blooms. The THQBCA dataset contains 26 variables organized into four categories: water quality, bio-optics, climate, and anthropogenic data. The water quality and climate data are field measured data with sampling frequency from daily to quarterly, and bio-optics and anthropogenic data are satellite-derived annual data. The dataset spans more than 15 years (8 of which cover approximately 35 years, 4 of which cover 20 years), and the spatial resolutions of the satellite-derived data range from 30 m to 500 m. This dataset is expected to advance research on evaluating and predicting cyanobacterial blooms, and support science-based management decisions for sustainable ecological development.

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Publication Details

Journal
Scientific Data
Published
2024-12-18
DOI
https://doi.org/10.1038/s41597-024-04224-w
Citations
5
Primary Topic
Aquatic Ecosystems and Phytoplankton Dynamics
Type
article
Field-Weighted Citation Impact
1.25

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article

A comprehensive time-series dataset linked to cyanobacterial blooms in Lake Taihu

Ronghua Ma, Yanru Wu, Junfeng Xiong, Kun Xue et al.
5 citations
Scientific Data
Aquatic Ecosystems and Phytoplankton Dynamics
1.25
article

A comprehensive time-series dataset linked to cyanobacterial blooms in Lake Taihu

Ronghua Ma, Yanru Wu, Junfeng Xiong, Kun Xue, Jinduo Xu, Minqi Hu, Zhigang Cao, Guangwei Zhu, Zehui Huang, Yibo Zhang
article en
5 citations

Abstract

Lake Taihu has a history of recurrent harmful cyanobacterial blooms. There is a need to better understand the aquatic ecosystem of Lake Taihu in order to improve methods for controlling the cyanobacterial blooms. Based on the field measurement and satellite remote sensing, we produced and collected a time-series dataset, including the water quality, bio-optics, climate, and anthropogenic data of Lake Taihu (THQBCA), which could provide comprehensive information regarding cyanobacterial blooms. The THQBCA dataset contains 26 variables organized into four categories: water quality, bio-optics, climate, and anthropogenic data. The water quality and climate data are field measured data with sampling frequency from daily to quarterly, and bio-optics and anthropogenic data are satellite-derived annual data. The dataset spans more than 15 years (8 of which cover approximately 35 years, 4 of which cover 20 years), and the spatial resolutions of the satellite-derived data range from 30 m to 500 m. This dataset is expected to advance research on evaluating and predicting cyanobacterial blooms, and support science-based management decisions for sustainable ecological development.

Scientific DataVol. 11(1)
Chinese Academy of Sciences (CN), Nanjing University of Information Science and Technology (CN), Nanjing Institute of Geography and Limnology (CN), Huaiyin Normal University (CN), University of Chinese Academy of Sciences (CN)
National Natural Science Foundation of China, Chinese Academy of Sciences, National Key Research and Development Program of China
Openalex Percentile: Top 22%
Aquatic Ecosystems and Phytoplankton Dynamics
1.25
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