Understanding the sensitivity of the response of chlorophyll (Chla) to nutrients (e.g., nitrogen and phosphorus) concentrations is important for predicting cyanobacterial bloom risk. However, the processes by which nutrients in lake that affect cyanobacterial growth and outbreaks are nonlinear, gradual and spatially and temporally heterogeneous, and the single response thresholds of concentrations between nutrients and the Chla proposed in current studies maybe hardly reflect these characteristics. Due to three decades of rapid regional socio-economic development, the eutrophication in Taihu Lake of China is serious and there are cyanobacterial blooms every year. In this study, we quantified the interaction effects of different forms of nitrogen and phosphorus on Chla concentrations in lake water and sediment pore water. And a refined response threshold range with continuous variation was proposed to characterize the relationship between the Chla concentration and the NH4-N, total nitrogen (TN) and total phosphorus (TP) concentrations. The results showed that TP was the dominant factor influencing the spatial variation of cyanobacteria blooms in most areas of Taihu Lake, followed by TN. TP should therefore be the highest priority for future pollution load reduction in Taihu Lake. The effects of the interactions between the pollution factors were greater than the sum of them individually. NH4-N and dissolved inorganic phosphorus (DIP) are likely to be preferentially consumed by algae for growth and should be the focus of nutrient control efforts in Taihu Lake. For cyanobacterial risk prediction, prevention and control, NH4-N, TN and TP concentrations of 0.06 mg/L, 2.89 mg/L and 0.06 mg/L, respectively, can be used to indicate the beginning of cyanobacterial blooms in Taihu Lake, and concentrations of 0.34 mg/L, 4.67 mg/L and 0.11 mg/L, respectively, can be used as reference thresholds to indicate serious cyanobacterial blooms.

Harmful cyanobacterial blooms are exemplified as a major environmental concern due to producing toxin, and have generated a serious threat to public health. Knowledge on the spatial-temporal distribution of cyanobacterial blooms is therefore crucial for public health organizations and environmental agencies. In this study, field data and charge coupled device (CCD) image were collected in Lakes Gaoyang and Hanfeng of the Three Gorges Reservoir (TGR), China. We conducted the risky grade index (RGI) and coverage area index to develop a feasible estimation framework of cyanobacterial blooms. First, the close relationships between CCD reflectance spectral indices and water quality parameters were constructed based on water optical classification. Then, a regional algorithm for the RGI classification was established by density peaks. Finally, our proposed algorithm was applied to investigate dynamics of cyanobacterial blooms in the two lakes from 6-year series of CCD images. Encouraging results demonstrated that satellite remote sensing in conjunction with field observation can aid in the estimation of cyanobacterial blooms in the TGR.