Assessment of a new nutrient management strategy to control harmful cyanobacterial blooms in Lake Taihu using a hydrodynamic-ecological model

Abstract

Abstract The external nutrient loading significantly affects large shallow lakes, particularly those with intricate rive networks. In Lake Taihu, pollutant discharge standards have traditionally been quantified based on water environmental capacity, while neglecting the response characteristics of algal growth in different regions to boundary inputs. For that analysis, this study first estimated the river pollutant loadings of 16 most significant inflow and outflow rivers of Lake Taihu from 2008 to 2020 and explored the correlations between inflow water quality parameters and lacustrine chlorophyll-a levels. Results highlighted the significant influence of high river input of permanganate values in spring on the chlorophyll-a levels in the lake. Based on this, this study proposed the hypothesis that reducing the inflow concentration of permanganate in spring would inhibit algal growth, which was further validated using coupled hydrodynamic and ecological models. The simulation results indicated that the reduction of permanganate inflow concentration during spring would significantly decrease chlorophyll-a concentration in spring and summer, especially leading to a notable impact on peak values. However, due to variations in background concentrations among rivers, the extent of reduction in lake chlorophyll-a levels showed significant spatial differences. Additionally, analysis of extracted algal bloom areas revealed that there still remained a relatively high risk of algal blooms occurring in the main regions, particularly during autumn when inflow pollutant concentrations increased rapidly. These findings emphasized the importance of formulating reasonable exogenous reduction schemes, which should consider the concentration and variation trend of inflow pollutants, as well as the response characteristics of algal bloom growth in different lake zones to the boundary.