基于数据挖掘的太湖蓝藻生长水环境关键因子研究

为探究太湖水体富营养化演变机理，识别影响太湖富营养化及蓝藻生长的水环境关键因子，对2006—2018年太湖多源监测序列数据开展数据准备和数据清洗，采用K-means均值聚类方法获取离散的布尔型关联规则挖掘候选数据集，构建基于Apriori算法的太湖水环境关键因子关联规则挖掘模型，对影响太湖水体富营养化的水环境关键因子进行识别。结果表明:表征太湖富营养化程度的Chl-a质量浓度与TP质量浓度、NH₃-N质量浓度、pH和COD_Mn质量浓度均呈现不同强度的关联性，其中Chl-a质量浓度在0~18.36 mg/m³区间内与TP质量浓度在0~0.045 mg/L区间内关联性最强；从水环境治理角度看，若将太湖TP质量浓度控制在0.045 mg/L以下，则全湖Chl-a质量浓度小于18.36 mg/m³的概率最大，可以有效控制蓝藻数量总体处于较少状态，避免太湖蓝藻水华大规模暴发。

Research on key factors of water environment for cyanobacteria growth in Taihu Lake based on data mining

In order to explore the eutrophication evolution mechanism and identify the key factors of water environment that affect the eutrophication and cyanobacteria growth of Taihu Lake, the data preparation and data cleaning for the data of the multi-source monitoring sequence of Taihu Lake from 2006 to 2018 were carried out. The K-means clustering method was used to obtain the discrete Boolean association rule for the mining of candidate data sets, and a mining model of association rule for key factors of Taihu Lake was constructed based on the Apriori algorithm, from which the key factors of water environment that affect the eutrophication of Taihu Lake were identified. The results showed that the mass concentration of chlorophyll a, which characterizes the degree of eutrophication in Taihu Lake, has different degrees of correlation with total phosphorus, ammonia nitrogen, pH and permanganate index. Among them, the mass concentration of chlorophyll a in the range of 0-18. 36 mg/m³ has the strongest correlation with the total phosphorus in the range of 0-0. 045 mg/L. From the perspective of water environment management, if the total phosphorus concentration in Taihu Lake is controlled below 0. 045 mg/L, the probability that the mass concentration of chlorophyll a in the whole lake is below 18. 36 mg/m³ would be the highest, which can effectively control the number of cyanobacteria in the overall state of less and further avoid the large-scale outbreak of cyanobacteria bloom in Taihu Lake.