蓝藻生长的主要影响因子筛选及预测模型研究  

Selection of Main Influencing Factors of Cyanobacteria Growth and Construction of Pre-diction Model

作　　者：李勇 李东海 Li Yong;Li Donghai(School of Materials Engineering(Environmental Engineering)Changzhou Institute of Industry Technology,Changzhou 213164,China)

机构地区：[1]常州工业职业技术学院材料工程(环境工程)学院,江苏常州213164

出　　处：《广东化工》2021年第22期51-54,共4页Guangdong Chemical Industry

摘　　要：蓝藻生物量是水华形成的基础物质条件,准确预测蓝藻生物量的变化规律有助于进行湖泊治理。本研究收集了2003年至2018年太湖的气象、营养盐和叶绿素等数据。皮尔逊结果显示叶绿素与TN、氨氮及风速呈显著的负相关关系;与TP、COD、温度和日照时长均呈显著的正相关关系。通过理论分析筛选出影响太湖蓝藻生长的主要因子为TP、COD、风速、温度和日照时长,并利用1stopt 6.0软件快速且精准的建立蓝藻生物量与主要环境因子的关系模型,其决定系数(R2)和均方根误差(RMSE)分别为0.85和8.92。Mann-Kendall趋势检验分析指出太湖的风速呈显著逐年降低的趋势,而春季气温和降雨呈显著逐年升高的趋势。模型指出气候变化明显提升了叶绿素水平,为了降低气候变化的影响,太湖TP浓度的控制将面临巨大的挑战。Cyanobacteria biomass is the basic condition for the formation of blooms.Accurate prediction of the variation of cyanobacteria biomass is helpful for lake management.This study collected meteorological,nutrient and chlorophyll data from 2003 to 2018 in Taihu Lake.Pearson's results showed that chlorophyll a was negatively correlated with TN,ammonia nitrogen and wind speed.And chlorophyll a was significantly positively correlated with TP,COD,temperature and sunshine duration.Through theoretical analysis,the main factors affecting the growth of cyanobacteria in Taihu Lake were selected as TP,COD,wind speed,temperature and sunshine duration.1stopt 6.0 software was used to quickly and accurately establish the relationship model between cyanobacteria biomass and the main environmental factors,and the R2 and RMSE were 0.85 and 8.92,respectively.The Mann-Kendall trend test showed that the wind speed decreased significantly,while the air temperature and rainfall in spring increased significantly from 2003 to 2018.The model indicates that climate change has significantly increased chlorophyll levels,and in order to reduce the impact of climate change,the control of TP concentration in Taihu Lake will be a huge challenge.

关 键 词：气象要素 营养盐因子 蓝藻 叶绿素 模型 

分 类 号：TQ[化学工程]