Dynamic modelling of multiple phytoplankton groups in rivers with an application to the Thames river system in the UK. (December 2015)

• Record Type: Journal Article
• Authors: Whitehead, Paul G.; Bussi, Gianbattista; Bowes, Michael J.; Read, Daniel S.; Hutchins, Michael G.; Elliott, J. Alex; Dadson, Simon J.
• Is Part Of: Environmental modelling & software. Volume 74(2015:Dec.)
• Page Start: 75
• Page End: 91
• Publication Date: 2015-12
• Subjects: Phytoplankton modelling -- Phytoplankton growth -- General sensitivity analysis -- River water quality -- River Thames; Environmental monitoring -- Computer programs -- Periodicals; Ecology -- Computer simulation -- Periodicals; Digital computer simulation -- Periodicals; Computer software -- Periodicals; Environmental Monitoring -- Periodicals; Computer Simulation -- Periodicals; Environnement -- Surveillance -- Logiciels -- Périodiques; Écologie -- Simulation, Méthodes de -- Périodiques; Simulation par ordinateur -- Périodiques; Logiciels -- Périodiques; Computer software; Digital computer simulation; Ecology -- Computer simulation; Environmental monitoring -- Computer programs; Periodicals; Electronic journals; 363.70015118
• DOI: 10.1016/j.envsoft.2015.09.010
• Languages: English
• ISSNs: 1364-8152

Abstract

Abstract: A process-based phytoplankton model developed to simulate the movement and growth of phytoplankton in river systems is presented in this paper. The model is based on mass-balance, and takes into account water temperature, light, self-shading, dissolved phosphorus and silicon concentrations. It was implemented in five reaches of the River Thames (UK), and the results compared to a novel dataset of cytometric data which includes concentrations of chlorophytes, diatoms, cyanobacteria and picoalgae. A Multi-Objective General Sensitivity Analysis was carried out in order to test the model robustness and to quantify the sensitivity to its parameters. The results show a good agreement between the simulations and the measured phytoplankton abundance. The most influential parameters were phytoplankton growth and death rates, while phosphorus concentration showed little influence, due to the high concentration of phosphorus in the Thames. The model is an important step forward towards understanding and predicting algal dynamics in river systems. Highlights: A new phytoplankton model is presented and tested on the River Thames (UK). It takes into account temperature, light, phosphorus, silica and self-shading. The parameter uncertainty is assessed through a general sensitivity analysis. Growth and death rates are the most influent model parameters. Phosphorus concentration is not a limiting factor in the River Thames.