As the third largest fresh water lake in China, Taihu Lake is suffering from serious eutrophication, where nutrient loading from tributary and surrounding river networks is one of the main contributors. In this study, water age is used to investigate the impacts of tributary discharge and wind influence on nutrient status in Taihu Lake, quantitatively. On the base of sub-basins of upstream catchments and boundary conditions of the lake, multiple inflow tributaries are categorized into three groups. For each group, the water age has been computed accordingly. A well-calibrated and validated three-dimensional Delft3D model is used to investigate both spatial and temporal heterogeneity of water age. Changes in wind direction lead to changes in both the average value and spatial pattern of water age, while the impact of wind speed differs in each tributary group. Water age decreases with higher inflow discharge from tributaries; however, discharge effects are less significant than that of wind. Wind speed decline, such as that induced by climate change, has negative effects on both internal and external nutrient source release, and results in water quality deterioration. Water age is proved to be an effective indicator of water exchange efficiency, which may help decision-makers to carry out integrated water management at a complex basin scale.

Ongoing eutrophication frequently causes toxic phytoplankton blooms. This induces huge worldwide challenges for drinking water quality, food security and public health. Of crucial importance in avoiding and reducing blooms is to determine the maximum nutrient load ecosystems can absorb, while remaining in a good ecological state. These so called critical nutrient loads for lakes depend on the shape of the load-response curve. Due to spatial variation within lakes, load-response curves and therefore critical nutrient loads could vary throughout the lake. In this study we determine spatial patterns in critical nutrient loads for Lake Taihu (China) with a novel modelling approach called Spatial Ecosystem Bifurcation Analysis (SEBA). SEBA evaluates the impact of the lake's total external nutrient load on the local lake dynamics, resulting in a map of critical nutrient loads for different locations throughout the lake. Our analysis shows that the largest part of Lake Taihu follows a nonlinear load-response curve without hysteresis. The corresponding critical nutrient loads vary within the lake and depend on management goals, i.e. the maximum allowable chlorophyll concentration. According to our model, total nutrient loads need to be more than halved to reach chlorophyll-a concentrations of 30–40 μg L⁻¹ in most sections of the lake. To prevent phytoplankton blooms with 20 μg L⁻¹ chlorophyll-a throughout Lake Taihu, both phosphorus and nitrogen loads need a nearly 90% reduction. We conclude that our approach is of great value to determine critical nutrient loads of lake ecosystems such as Taihu and likely of spatially heterogeneous ecosystems in general.