Estimation of Phytoplankton Primary Productivity in Qinghai Lake Using Ocean Color Satellite Data: Seasonal and Interannual Variations

被引:0
|
作者
Ban, Xuan [1 ]
Dang, Yingchao [2 ]
Shu, Peng [3 ]
Qi, Hongfang [4 ]
Luo, Ying [4 ]
Xiao, Fei [1 ]
Feng, Qi [1 ]
Zhou, Yadong [1 ]
机构
[1] Chinese Acad Sci, Innovat Acad Precis Measurement Sci & Technol, Key Lab Environm & Disaster Monitoring & Evaluat H, Wuhan 430077, Peoples R China
[2] China Three Gorges Corp, Chinese Sturgeon Res Inst, Hubei Key Lab Three Gorges Project Conservat Fishe, Yichang 443100, Peoples R China
[3] Wuhan Univ, State Key Lab Water Resources & Hydropower Engn Sc, Wuhan 430072, Peoples R China
[4] Rescue Ctr Gymnocypris Przewalskii, Key Lab Breeding & Protect Gymnocypris Przewalskii, Xining 810016, Peoples R China
关键词
Qinghai Lake; Vertically Generalized Production Model; chlorophyll-a; phytoplankton primary production; remote sensing; MODEL;
D O I
10.3390/w16101433
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Estimation of primary production in Qinghai Lake is crucial for the aquatic ecosystem management in the northeastern Qinghai-Tibet Plateau. This study used the Vertically Generalized Production Model (VGPM) with ocean color satellite data to estimate phytoplankton primary productivity (PP) in Qinghai Lake during the non-freezing period from 2002 to 2023. Field data from 2018 and 2023 were used to calibrate and verify the model. The results showed a seasonal trend in chlorophyll-a and PP, with the lowest values in May and peaks from June to September. Qinghai Lake was identified as oligotrophic, with annual mean chlorophyl-a of 0.24-0.40 mu g/L and PP of 40-369 mg C/m2/day. The spatial distribution of PP was low in the center of the lake and high near the shores and estuaries. An interesting periodic increasing trend in PP every 2 to 4 years was observed from 2002 to 2023. This study established a remote sensing method for PP assessment in Qinghai Lake, revealing seasonal and interannual variations and providing a useful example for monitoring large saline mountain lakes.
引用
收藏
页数:15
相关论文
共 50 条
  • [21] Shifting of phytoplankton community in the frontal regions of Indian Ocean sector of the Southern Ocean using in situ and satellite data
    Mishra, Rajani Kanta
    Jena, Babula
    Anilkumar, Narayana Pillai
    Sinha, Rupesh Kumar
    JOURNAL OF APPLIED REMOTE SENSING, 2017, 11
  • [22] Global estimation of phytoplankton pigment concentrations from satellite data using a deep-learning-based model
    Li, Xiaolong
    Yang, Yi
    Ishizaka, Joji
    Li, Xiaofeng
    REMOTE SENSING OF ENVIRONMENT, 2023, 294
  • [23] Depth-Resolved and Depth-Integrated Primary Productivity Estimates From In-Situ and Satellite Data in the Global Ocean
    Sundararaman, Harish Kumar Kashtan
    Shanmugam, Palanisamy
    IEEE ACCESS, 2023, 11 : 21144 - 21159
  • [24] Stressors of primary productivity in the north Indian ocean revealed by satellite, reanalysis and CMIP6 data
    Sunanda, N.
    Kuttippurath, J.
    Chakraborty, A.
    Peter, R.
    PROGRESS IN OCEANOGRAPHY, 2023, 219
  • [25] Estimation of the Primary Productivity in Pearl River Estuary Using MODIS Data
    Ye, Haibin
    Chen, Chuqun
    Sun, Zhaohua
    Tang, Shilin
    Song, Xingyu
    Yang, Chaoyu
    Tian, Liqiao
    Liu, Fenfen
    ESTUARIES AND COASTS, 2015, 38 (02) : 506 - 518
  • [26] Estimation of near-infrared water-leaving reflectance for satellite ocean color data processing
    Bailey, Sean W.
    Franz, Bryan A.
    Werdell, P. Jeremy
    OPTICS EXPRESS, 2010, 18 (07): : 7521 - 7527
  • [27] Model Estimation of the Phytoplankton Biomass of Lake Issyk-Kul Using Remote Sensing Data
    Abakumov, A. I.
    Pak, S. Ya.
    Morozov, M. A.
    Tynybekov, A. K.
    INLAND WATER BIOLOGY, 2019, 12 (SUPPL 2) : 111 - 118
  • [28] Model Estimation of the Phytoplankton Biomass of Lake Issyk-Kul Using Remote Sensing Data
    A. I. Abakumov
    S. Ya. Pak
    M. A. Morozov
    A. K. Tynybekov
    Inland Water Biology, 2019, 12 : 111 - 118
  • [30] Monitoring the frozen duration of Qinghai Lake using satellite passive microwave remote sensing low frequency data
    Che Tao
    Li Xin
    Jin Rui
    CHINESE SCIENCE BULLETIN, 2009, 54 (13): : 2294 - 2299