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Simulation of phytoplankton biomass in Quanzhou Bay using a back propagation network model and sensitivity analysis for environmental variables

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Abstract

Prediction and sensitivity models, to elucidate the response of phytoplankton biomass to environmental factors in Quanzhou Bay, Fujian, China, were developed using a back propagation (BP) network. The environmental indicators of coastal phytoplankton biomass were determined and monitoring data for the bay from 2008 was used to train, test and build a three-layer BP artificial neural network with multi-input and single-output. Ten water quality parameters were used to forecast phytoplankton biomass (measured as chlorophyll-a concentration). Correlation coefficient between biomass values predicted by the model and those observed was 0.964, whilst the average relative error of the network was −3.46% and average absolute error was 10.53%. The model thus has high level of accuracy and is suitable for analysis of the influence of aquatic environmental factors on phytoplankton biomass. A global sensitivity analysis was performed to determine the influence of different environmental indicators on phytoplankton biomass. Indicators were classified according to the sensitivity of response and its risk degree. The results indicate that the parameters most relevant to phytoplankton biomass are estuary-related and include pH, sea surface temperature, sea surface salinity, chemical oxygen demand and ammonium.

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Authors and Affiliations

  1. First Institute of Oceanography, State Oceanic Administration, Qingdao, 266061, China

    Wei Zheng  (郑伟) & Honghua Shi  (石洪华)

  2. Institute of Oceanography, Chinese Academy of Sciences, Qingdao, 266071, China

    Xikun Song  (宋希坤)

  3. Monitoring Center of Marine Environment and Fishery Resources of Fujian Province, Fuzhou, 350003, China

    Xikun Song  (宋希坤) & Dongren Huang  (黄东仁)

  4. School of Mathematical Sciences, Fudan University, Shanghai, 200433, China

    Long Hu  (胡龙)

Authors
  1. Wei Zheng  (郑伟)
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  2. Honghua Shi  (石洪华)
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  3. Xikun Song  (宋希坤)
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  4. Dongren Huang  (黄东仁)
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  5. Long Hu  (胡龙)
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Corresponding author

Correspondence to Honghua Shi  (石洪华).

Additional information

Supported by the Ocean Public Welfare Scientific Research Project, State Oceanic Administration of China (No. 200705029), the National Special Fund for Basic Science and Technology of China (No. 2012FY112500), and the National Non-profit Institute Basic Research Fund (No. FIO2011T06)

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Zheng, W., Shi, H., Song, X. et al. Simulation of phytoplankton biomass in Quanzhou Bay using a back propagation network model and sensitivity analysis for environmental variables. Chin. J. Ocean. Limnol. 30, 843–851 (2012). https://doi.org/10.1007/s00343-012-1216-6

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  • DOI: https://doi.org/10.1007/s00343-012-1216-6

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