Modeling the effects of environmental variables on short-term spatial changes in phytoplankton biomass in a large shallow lake, Lake Taihu

Understanding the short-term response of phytoplankton biomass on environmental variables is needed for issuing early warnings of harmful algal blooms in aquatic ecosystems. Predicting harmful algal blooms are particularly challenging in large shallow lakes due to their complex mixing patterns. This study used a two-dimensional hydrodynamic–phytoplankton model to evaluate the effects of environmental variables on short-term changes in the horizontal distribution of phytoplankton biomass in a large shallow lake, Lake Taihu, China. Two simulations were performed using daily and hourly average wind condition and water temperature data collected in 2009. Other model inputs were identical for these two simulations. The response of phytoplankton to wind conditions, light intensity, water temperature, and total dissolved phosphorus and nitrogen concentrations were examined based on a sensitivity analysis using the hourly data. Hourly simulation achieved a more realistic distribution of phytoplankton biomass than the daily simulation. This finding implies that data with a higher temporal resolution are more useful for short-term prediction of phytoplankton biomass in this lake. Sensitivity analysis indicated that water temperature and light intensity dominate short-term changes in phytoplankton biomass in this lake. Wind conditions also affect phytoplankton biomass distribution by causing advective water movement.