Probabilistic analysis of phytoplankton biomass at the Frisian Inlet (NL)

• A reliable ecological model is introduced to predict the variation of phytoplankton biomass (in terms of chlorophyll a).
• A mathematical function is used to perform the validation of the model.
• The predicted chlorophyll a is fitted well by a normal distribution.
• The study aims to improve the prediction with respect to uncertainty.

The BLOOM II model is applied in this study to interrogate the variation of phytoplankton biomass (in terms of chlorophyll a) at the Frisian Inlet (NL), located in the north of the Netherlands. The validation results of the model show that more than 90% of the comparisons between model results and observations have a good agreement, while only 3.1% are classified as poor. Chlorophyll a is significantly correlated with the ecological indicators of Si and NH4 by observational analysis. The modelled chlorophyll a is fitted well by a normal distribution function (μ = 3.95 mg m−3, σ = 2.96 mg m−3). Relationships between the modelled ecological indicators are investigated. Secchi depth as another important indicator is closely linked with chlorophyll a  , PAR and KdKd. Moreover, particular attention is paid to the phytoplankton biomass in response to nutrient availability. The decrease rate of chlorophyll a is from 16.8% to 19.2% for N-reduction, 17.4%–21.3% for P-reduction and 21.7%–28.0% for both N- and P-reduction. In the presence of uncertainty, the improved prediction of chlorophyll a is derived by Bayesian Markov Chain Monte Carlo (BMCMC) in this study. The improved prediction of chlorophyll a concentrations vary from 0.147 to 15.34 mg m−3 within the 95% confidence interval. This study emphasises the use of an ecological model to predict the variation of phytoplankton biomass, and improves the prediction with the integration of uncertainty analysis.