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Hydrodynamic-phytoplankton model for short-term forecasts of phytoplankton in Lake Taihu, China |
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| Authors: | Jiacong Huang Junfeng Gao Georg Hörmann |
| Institution: | a Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, 73 East Beijing Road, Nanjing 210008, China b Graduate University of the Chinese Academy of Sciences, Beijing 100049, China c Department of Hydrology and Water Resources Management, Ecology Centre, Kiel University, Kiel, Germany |
| Abstract: | Phytoplankton biomass is an important factor for short-term forecasts of algal blooms. Our new hydrodynamic-phytoplankton model is primarily intended for simulating the spatial and temporal distribution of phytoplankton in Lake Taihu within a time frame of 1-5 days. The model combines two modules: a simple phytoplankton kinetics module for growth and loss; and a mass-transport module, which defines phytoplankton transport horizontally with a two dimensional hydrodynamic model. To adapt field data for model input and calibration, we introduce two simplifications: (a) exclusion of some processes related to phytoplankton dynamics like nutrient dynamics, sediment resuspension, mineralization and nitrification, and (b) use of monthly measured data of the nutrient state. Chlorophyll-α concentration, representing phytoplankton biomass, is the only state variable in the model. A sensitivity analysis was carried out to identify the most sensitive parameter set in the phytoplankton kinetics module. The model was calibrated with field data collected in 2008 and validated with additional data obtained in 2009. A comparison of simulated and observed chlorophyll-α concentration for 33 grid cells achieved an accuracy of 78.7%. However, mean percent error and mean absolute percent error were 13.4% and 58.2%, respectively, which implies that further improvement is necessary, e.g. by reducing uncertainty of the model input and by an improved parameter calibration. |
| Keywords: | Hydrodynamic-phytoplankton model Lake Taihu Chlorophyll-α Model calibration |
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