江淮水利科技Issue(5)：42-47,64,7.DOI:10.20011/j.cnki.JHWR.202505009
基于蓝藻预警尖点突变模型的巢湖蓝藻暴发特征分析
Analysis of cyanobacterial blooms characteristics in Chaohu Lake based on the cyanobacterial early warning spike mutation model
摘要
Abstract
To establish a cyanobacterial bloom early-warning model suitable for the Chaohu Lake water area,the study focused on addressing key scientific issues such as quantifying the spatiotemporal patterns of blooms,identifying critical driving factors,and coordinating verification using multi-source data.This paper aimed to form a key technology that effectively enhances cyanobacteria prevention and control.Key water quality factors influencing bloom occurrence were selected,and a spike muta-tion early-warning model for cyanobacteria was established based on mutation theory.The model's validity and accuracy were verified through standardization,potential function construction,least squares solution,and integration of water quality data with MODIS remote sensing data.The study revealed that the western half of Chaohu Lake exhibits pronounced eutrophication char-acteristics.Based on correlation analysis,the correlation coefficients between temperature,total phosphorus,dissolved oxygen,and chlorophyll were 0.71,0.84,and-0.63,respectively,indicating that these three indicators are the key driving factors for cyanobacterial blooms.The results of multi-source data integration revealed that cyanobacterial blooms were most likely to oc-cur in June,July,August,and October each year,primarily in the northwestern region of the lake and along the coastal river mouths,and then migrated toward the southwestern and central parts of the lake.The sharp-point mutation model based on driving factors could effectively predict cyanobacterial blooms,showing significant consistency with the spatiotemporal charac-teristics of cyanobacterial blooms monitored by remote sensing.This study confirmed that cyanobacterial blooms were a nonlin-ear sudden change process driven by multiple factors.The warning model constructed achieves bidirectional validation of mul-ti-source data from water quality and remote sensing,overcoming the limitations of traditional single-dimensional monitoring.It can identify the critical state of cyanobacterial blooms in advance,providing ample decision-making time for implementing e-cological scheduling,emergency algae removal,and other control measures.关键词
巢湖/蓝藻暴发/遥感/水质/预警模型Key words
Chaohu Lake/cyanobacterial blooms/remote sensing/water quality/warning model分类
资源环境引用本文复制引用
丰顺,戴新荣,袁少伟,杜明..基于蓝藻预警尖点突变模型的巢湖蓝藻暴发特征分析[J].江淮水利科技,2025,(5):42-47,64,7.基金项目
安徽省(水利部淮河水利委员会)水利科学研究院科技攻关计划项目(KJGG202304) （水利部淮河水利委员会）
