The corruption of water quality is caused mostly by the volatile odorous substances from the metabolism of bacterial algae in the water. Therefore, the monitoring of odorous substances plays a certain role in controlling water quality. In order to solve the problem that the current detection means is not effective, in this paper, the instrument analysis method and regression analysis method were combined to establish a model of odour detection and early warning control. This model can make real-time analysis of water quality, ensuring early warning of algal bloom etc., reducing water pollution, and guaranteeing the cleanliness of water resources. Then, through simulation of the cyanobacterial bloom process in Taihu Lake, the feasibility of this model was validated. It’s found that the variations of ß-ionone and methyl isopropanol (MIB) have a good indication of that in algae concentration, that is, when these two organic matters in the water quality of Taihu Lake changes abnormally, it indicates that there may be the abnormality of algal bloom. It has very important practical significance to use this model for control the water quality of Taihu Lake.