Abstract

Complex environmental models are often criticized as being difficult to analyze and poorly identifiable due to their nonlinearities and/or their large number of parameters relative to data availability. Others consider overparameterized models to be useful, especially for predicting system dynamics beyond the conditions for which the model was calibrated. In this paper, we present a complex eutrophication model that has been developed to simulate plankton dynamics in Lake Washington, USA. Because this model is to be used for testing alternative managerial schemes, the inclusion of multiple elemental cycles (org. C, N, P, Si, O) and multiple functional phytoplankton (diatoms, green algae and cyanobacteria) and zooplankton (copepods and cladocerans) groups was deemed necessary. The model also takes into account recent advances in stoichiometric nutrient recycling theory, and the zooplankton grazing term was reformulated to include algal food quality effects on zooplankton assimilation efficiency. The physical structure of the model is simple and consists of two spatial compartments representing the lake epilimnion and hypolimnion. Global sensitivity analysis showed background light attenuation, the maximum phytoplankton growth rate, the phytoplankton basal metabolic rate, the zooplankton maximum grazing rate and the grazing half saturation constant have the greatest impact on model behavior. Phytoplankton phosphorus stoichiometry (maximum and minimum internal concentrations, maximum uptake rate) interacts with these parameters and determines the plankton dynamics (epilimnetic and hypolimnetic phytoplankton biomass, proportion of cyanobacteria and total zooplankton biomass). Sensitivity analysis of the model forcing functions indicated the importance of both external and internal loading for simulating epilimnetic and hypolimnetic plankton dynamics. These results will be used to calibrate the model, to reproduce present chemical and biological properties of Lake Washington and to test this lake's potential response to different external nutrient loading scenarios.

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