基于Sentinel-2数据的湖泊蓝藻水华时空动态监测  

Spatiotemporal Dynamics Monitoring of Lake Cyanobacterial Blooms Based on Sentinel-2 Data

作　　者：宋挺 徐超 严飞 张军毅 SONG Ting;XU Chao;YAN Fei;ZHANG Junyi(Wuxi Environmental Monitoring Center of Jiangsu Province,Wuxi 214000,China)

机构地区：[1]江苏省无锡环境监测中心,江苏无锡214000

出　　处：《中国环境监测》2025年第1期214-224,共11页Environmental Monitoring in China

基　　金：江苏省生态环境科研成果转化与推广项目(2022012)。

摘　　要：蓝藻水华是内陆水域面临的最严重的环境问题之一,其对全球公共卫生安全和水生生态系统健康均构成严重威胁。与现场调查相比,卫星遥感是一种监测蓝藻水华的高效且有效方法。传统的遥感处理面临着数据下载量大、处理时间长、存储要求高等诸多缺陷,阻碍了长时间序列蓝藻水华遥感自动监测的进一步推广。将相关处理程序嵌入到Google Earth Engine云平台中,开发了基于Sentinel-2 MSI数据的可人机交互的蓝藻水华监测工作流。使用该工作流对2016-2022年呼伦湖、太湖、巢湖和滇池4个典型富营养化湖泊进行了蓝藻水华时空分布分析,结果表明,太湖、巢湖和滇池蓝藻水华面积呈逐年波动下降趋势,而呼伦湖蓝藻水华面积则整体不断增大,2022年其更是成为4个湖泊中蓝藻水华暴发形势最为严峻的湖泊。针对相关湖泊,实行外源营养盐控制、水生植被修复、鱼类群落结构调整等水华防控管理措施是十分必要且有效的。研究结果为蓝藻水华长期监测提供了一种自动化、一体化的快速监测方案,可以有效服务于内陆水体,特别是面积较小水体的蓝藻水华业务化监测工作。Inland water ecosystems face escalating threats from cyanobacterial blooms,which have profound implications for both global public health and aquatic biodiversity.While field investigations have their merits,satellite remote sensing emerges as a more streamlined and robust approach for monitoring these blooms.However,the traditional remote sensing approach is hampered by challenges such as vast data downloads,protracted processing durations,and substantial storage demands.These impediments have stymied advancements in the continuous automated tracking of cyanobacterial blooms.To address this,this study integrates specific processing routines into the Google Earth Engine cloud platform,culminating in the creation of an interactive monitoring protocol using Sentinel-2 MSI data.This protocol facilitates the spatiotemporal evaluation of cyanobacterial bloom patterns across four emblematic eutrophic lakes:Hulun,Taihu,Chaohu,and Dianchi,spanning 2016 to 2022.The findings elucidate that while Taihu,Chaohu,and Dianchi experienced periodic reductions in bloom intensity,Hulun witnessed an annual exacerbation,peaking in 2022 as the most adversely impacted.It is imperative to institute strategies that mitigate nutrient influx,rejuvenate aquatic flora,and recalibrate lacustrine fish populations,as these measures are pivotal in curtailing cyanobacterial proliferation.The devised protocol in this research offers a cohesive,swift,and automated monitoring framework,adeptly catering to long-term surveillance needs of inland aquatic habitats,with a particular emphasis on smaller water bodies,to streamline cyanobacterial bloom management endeavors.

关 键 词：蓝藻水华 Google Earth Engine 云计算 

分 类 号：X87[环境科学与工程—环境工程]