摘要
蓝藻水华问题持续影响着中国内陆湖泊,华中地区O湖近年6-10月均会受到蓝藻水华的侵扰,造成水体生物死亡,堆积与异味影响到了湖泊的休憩功能.该研究于2022年7-10月在O湖展开,通过对该湖蓝藻水华的持续低空监测与研究,分析其湖面分布情况,结合气象数据探究其漂移方向与规律,对其发展情况展开预测,并尝试通过物理阻隔等措施,减少其扩散范围.结果表明,2022年7月初O湖蓝藻主要分布在湖区东部区域,西部与南部区域蓝绿藻数量较低,未形成水华.通过气象数据分析结合自动站水质监测数据,提前预测蓝藻水华会由东部区域突破已设置的挡藻围隔进入西部湖区.因此,研究立即在O湖大桥布设档藻围隔,将水华控制在O湖东部区域,避免了其向其他区域漂移和扩散,使得O湖西部与南部区域未出现蓝藻水华.研究表明,水质自动站数据及无人机监测能够较准确地判断蓝藻的空间分布,结合气象数据能够预测蓝藻水华期的漂移,根据预测结果建设挡藻物理阻隔,能有效限制蓝藻水华的漂移,验证了蓝藻水华监控与防治方法的可行性,为蓝藻早期控制与治理提供了新的思路.
Abstract
The problem of blue-green algae blooms continues to affect my country's inland lakes.Lake O in Central China has been infested by blue-green algae blooms from June to October in recent years,causing the death of water organisms,and the accumulation and odor have affected the lake's recreational function.The research was carried out in Lake O from July to October 2022.Through continuous low-altitude monitoring and research of the cyanobacteria bloom in the lake,it analyzed its lake surface distribution,combined with meteorological data to explore its drift direction and law,and predicted its develop-ment.And try to reduce its spread through physical barriers and other measures.The results show that in early July 2022,blue-green algae in Lake O were mainly distributed in the eastern part of the lake area.The number of blue-green algae in the western and southern parts was lower and no algae blooms were formed.Through meteorological data analysis combined with water quality monitoring data from automatic stations,it is predicted in advance that Cyanobacteria blooms will break through the established algae barriers from the eastern region and enter the western lake area.Therefore,the study immediately set up an algae barrier at the O Lake Bridge to control the algae bloom in the eastern area of Lake O and prevent it from drifting and spreading to other areas,so that no cyanobacteria bloom occurred in the western and southern areas of Lake O.Research shows that water quality automatic station data and drone monitoring can more accurately determine the spatial distribution of cyanobacteria,and combined with meteorological data can predict the drift of Cyanobacteria blooms.Building physical barriers to block algae based on the prediction results can effectively limit the occurrence of cyanobacteria blooms.Drift has verified the feasibility of Cyanobacteria bloom monitoring and prevention methods,and provided new ideas for early control and management of Cyanobacteria.
基金项目
上海市2020年度"科技创新行动计划"启明星项目资助(20QB1403900)
NETL
NSTL
万方数据