Abstract
Lake Taihu is a shallow, wind-driven lake where eutrophication is always a serious problem. The study presented herein
investigates the effect of wind on the eutophication of the lake, by using a two-dimensional (2D) hydrodynamic model coupled
with a 2D water quality model. The 2D water quality model looks in particular at the water quality situation of Lake Taihu in the
year 2008 and predicts future changes in the algae bloom situation. The Delft3D modelling tool was used to build the
hydrodynamic model based on the measured geomorphologic and meteorological data of Lake Taihu. Three different sets of
wind conditions (no wind, constant wind and measured wind) were considered as wind effects on the water level and velocity, in
both the wet and dry seasons. Based on the calibrated hydrodynamic model a 2D water quality model was built which was
calibrated based on estimated data for nutrient loads. A one-year hydrodynamic simulation was performed, in order to determine
the water quality situation of Lake Taihu. The estimated nutrient loads included total nitrogen (TN) and total phosphorus (TP)
concentrations. The estimates are based on the population of cities around Lake Taihu, and the wastewater treatment plant
capacity of the provinces of Jiangsu and Zhejiang, where the main sources of pollutants come from. Two time periods (spring
and autumn) of algae blooms development for the year 2008 are presented. The results of the study indicate that: 1) the
hydrodynamic model with constant wind conditions (southeast, 5m/s) showed better results than the one where measured wind
conditions were used, simply because the measured wind data is insufficient at the moment; 2) the model clearly represents the
water quality to an acceptable degree; 3) an increase in population in the area would lead to an increase in the maximum value of
algae concentration from 35% to 76%; 4) if there is an improvement in technology at the wastewater treatment plant, then the
maximum value of algae concentration will be between 17% and 42%.