Monitoring, simulation and early warning of cyanobacterial harmful algal blooms: An upgraded framework for eutrophic lakes

IF 7.7 2区 环境科学与生态学 Q1 ENVIRONMENTAL SCIENCES Environmental Research Pub Date : 2024-11-05 DOI:10.1016/j.envres.2024.120296
Yinguo Qiu , Jiacong Huang , Juhua Luo , Qitao Xiao , Ming Shen , Pengfeng Xiao , Zhaoliang Peng , Yaqin Jiao , Hongtao Duan
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Abstract

Cyanobacterial Harmful Algal Bloom (CyanoHAB) is a global aquatic environmental issue, posing considerable eco-environmental challenges in freshwater lakes. Comprehensive monitoring and accurate prediction of CyanoHABs are essential for their scientific management. Nevertheless, traditional satellite-based monitoring and process-oriented prediction methods of CyanoHABs failed to satisfy this demand due to the limited spatiotemporal resolutions of both monitoring data and prediction results. To address this issue, this paper proposes an upgraded framework for comprehensive monitoring and accurate prediction of CyanoHABs. A collaborative CyanoHAB monitoring network was firstly constructed by integrating space, aerial, and ground-based monitoring means. As a result, CyanoHAB conditions were assessed frequently covering the entire lake, its key areas, and core positions. Furthermore, by overcoming technical limitations associated with high-precision simulation of the growth-drift-accumulation process of CyanoHABs, such as the unclear drifting process of CyanoHABs and the mechanism of its coastal accumulation, the multi-scale CyanoHAB prediction was realized interconnecting the entire lake and its nearshore areas. The implemented framework has been applied in Lake Chaohu for over three years. It provided high-frequency and high-spatial-resolution CyanoHAB monitoring, as well as its multi-scale and accurate simulation. The application of this framework in Lake Chaohu had significantly improved the accuracies of CyanoHAB monitoring, simulation, and early warning. This advancement holds significant scientific value and offers potential for CyanoHAB prevention and control in eutrophic lakes.

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蓝藻有害藻华的监测、模拟和预警:富营养化湖泊的升级框架。
蓝藻有害藻华(CyanoHAB)是一个全球性的水生环境问题,给淡水湖泊的生态环境带来了巨大挑战。对蓝藻有害藻华进行全面监测和准确预测对科学管理蓝藻有害藻华至关重要。然而,由于监测数据和预测结果的时空分辨率有限,传统的卫星监测和面向过程的 CyanoHABs 预测方法无法满足这一需求。为解决这一问题,本文提出了一个全面监测和准确预测 CyanoHABs 的升级框架。首先,通过整合空间、航空和地面监测手段,构建了一个 CyanoHAB 协同监测网络。因此,对整个湖泊、重点区域和核心位置的 CyanoHAB 状况进行了频繁评估。此外,通过克服高精度模拟 CyanoHABs 生长-漂移-积累过程的技术限制,如 CyanoHABs 漂移过程不清晰、沿岸积累机理等,实现了整个湖泊及其近岸区域的多尺度 CyanoHAB 预测。该框架已在巢湖应用了三年多。它提供了高频率、高空间分辨率的 CyanoHAB 监测及其多尺度的精确模拟。该框架在巢湖的应用大大提高了蓝藻水华监测、模拟和预警的准确性。这一进展具有重要的科学价值,为富营养化湖泊的 CyanoHAB 防治提供了可能。
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来源期刊
Environmental Research
Environmental Research 环境科学-公共卫生、环境卫生与职业卫生
CiteScore
12.60
自引率
8.40%
发文量
2480
审稿时长
4.7 months
期刊介绍: The Environmental Research journal presents a broad range of interdisciplinary research, focused on addressing worldwide environmental concerns and featuring innovative findings. Our publication strives to explore relevant anthropogenic issues across various environmental sectors, showcasing practical applications in real-life settings.
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