A Digital Twin Lake Framework for Monitoring and Management of Harmful Algal Blooms

Harmful algal blooms (HABs) caused by lake eutrophication and climate change have become one of the most serious problems for the global water environment. Timely and comprehensive data on HABs are essential for their scientific management, a need unmet by traditional methods. This study constructed...

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Main Authors: Yinguo Qiu, Hao Liu, Jiaxin Liu, Dexin Li, Chengzhao Liu, Weixin Liu, Jindi Wang, Yaqin Jiao
Format: Article
Language:English
Published: MDPI AG 2023-11-01
Series:Toxins
Subjects:
Online Access:https://www.mdpi.com/2072-6651/15/11/665
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author Yinguo Qiu
Hao Liu
Jiaxin Liu
Dexin Li
Chengzhao Liu
Weixin Liu
Jindi Wang
Yaqin Jiao
author_facet Yinguo Qiu
Hao Liu
Jiaxin Liu
Dexin Li
Chengzhao Liu
Weixin Liu
Jindi Wang
Yaqin Jiao
author_sort Yinguo Qiu
collection DOAJ
description Harmful algal blooms (HABs) caused by lake eutrophication and climate change have become one of the most serious problems for the global water environment. Timely and comprehensive data on HABs are essential for their scientific management, a need unmet by traditional methods. This study constructed a novel digital twin lake framework (DTLF) aiming to integrate, represent and analyze multi-source monitoring data on HABs and water quality, so as to support the prevention and control of HABs. In this framework, different from traditional research, browser-based front ends were used to execute the video-based HAB monitoring process, and real-time monitoring in the real sense was realized. On this basis, multi-source monitored results of HABs and water quality were integrated and displayed in the constructed DTLF, and information on HABs and water quality can be grasped comprehensively, visualized realistically and analyzed precisely. Experimental results demonstrate the satisfying frequency of video-based HAB monitoring (once per second) and the valuable results of multi-source data integration and analysis for HAB management. This study demonstrated the high value of the constructed DTLF in accurate monitoring and scientific management of HABs in lakes.
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spelling doaj.art-5039957363414132a818f62f251e24062023-11-24T15:09:38ZengMDPI AGToxins2072-66512023-11-01151166510.3390/toxins15110665A Digital Twin Lake Framework for Monitoring and Management of Harmful Algal BloomsYinguo Qiu0Hao Liu1Jiaxin Liu2Dexin Li3Chengzhao Liu4Weixin Liu5Jindi Wang6Yaqin Jiao7Key Laboratory of Watershed Geographic Sciences, Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, Nanjing 210008, ChinaPowerchina Zhongnan Engineering Corporation Limited, Changsha 410014, ChinaKey Laboratory of Watershed Geographic Sciences, Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, Nanjing 210008, ChinaPowerchina Zhongnan Engineering Corporation Limited, Changsha 410014, ChinaPowerchina Zhongnan Engineering Corporation Limited, Changsha 410014, ChinaPowerchina Zhongnan Engineering Corporation Limited, Changsha 410014, ChinaKey Laboratory of Watershed Geographic Sciences, Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, Nanjing 210008, ChinaKey Laboratory of Watershed Geographic Sciences, Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, Nanjing 210008, ChinaHarmful algal blooms (HABs) caused by lake eutrophication and climate change have become one of the most serious problems for the global water environment. Timely and comprehensive data on HABs are essential for their scientific management, a need unmet by traditional methods. This study constructed a novel digital twin lake framework (DTLF) aiming to integrate, represent and analyze multi-source monitoring data on HABs and water quality, so as to support the prevention and control of HABs. In this framework, different from traditional research, browser-based front ends were used to execute the video-based HAB monitoring process, and real-time monitoring in the real sense was realized. On this basis, multi-source monitored results of HABs and water quality were integrated and displayed in the constructed DTLF, and information on HABs and water quality can be grasped comprehensively, visualized realistically and analyzed precisely. Experimental results demonstrate the satisfying frequency of video-based HAB monitoring (once per second) and the valuable results of multi-source data integration and analysis for HAB management. This study demonstrated the high value of the constructed DTLF in accurate monitoring and scientific management of HABs in lakes.https://www.mdpi.com/2072-6651/15/11/665digital twin lakewater environment managementharmful algal bloomsvideo monitoringsatellite remote sensing
spellingShingle Yinguo Qiu
Hao Liu
Jiaxin Liu
Dexin Li
Chengzhao Liu
Weixin Liu
Jindi Wang
Yaqin Jiao
A Digital Twin Lake Framework for Monitoring and Management of Harmful Algal Blooms
Toxins
digital twin lake
water environment management
harmful algal blooms
video monitoring
satellite remote sensing
title A Digital Twin Lake Framework for Monitoring and Management of Harmful Algal Blooms
title_full A Digital Twin Lake Framework for Monitoring and Management of Harmful Algal Blooms
title_fullStr A Digital Twin Lake Framework for Monitoring and Management of Harmful Algal Blooms
title_full_unstemmed A Digital Twin Lake Framework for Monitoring and Management of Harmful Algal Blooms
title_short A Digital Twin Lake Framework for Monitoring and Management of Harmful Algal Blooms
title_sort digital twin lake framework for monitoring and management of harmful algal blooms
topic digital twin lake
water environment management
harmful algal blooms
video monitoring
satellite remote sensing
url https://www.mdpi.com/2072-6651/15/11/665
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