Preemptive warning and control strategies for algal blooms in the downstream of Han River, China
Riverine blooms have become a challenging global environmental problem owing to strong disturbances from intensified human activities and the construction or operation of hydraulic projects. Previous studies mainly paid attention to algal blooms in the lakes and reservoirs, while less focused on the...
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Elsevier
2022-09-01
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Series: | Ecological Indicators |
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Online Access: | http://www.sciencedirect.com/science/article/pii/S1470160X22006628 |
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author | Jing Tian Shenglian Guo Jun Wang Heyu Wang Zhengke Pan |
author_facet | Jing Tian Shenglian Guo Jun Wang Heyu Wang Zhengke Pan |
author_sort | Jing Tian |
collection | DOAJ |
description | Riverine blooms have become a challenging global environmental problem owing to strong disturbances from intensified human activities and the construction or operation of hydraulic projects. Previous studies mainly paid attention to algal blooms in the lakes and reservoirs, while less focused on the prediction and prevention of algal blooms in large rivers. As one of the highly regulated rivers in China, the downstream of Han River frequently occurred consecutive algal blooms in recent decades, was selected as the case study. Firstly, algal blooms in the downstream of Han River during 1992–2021 were investigated to find out the key environmental factors governing algal blooms. Secondly, the distribution lag model was applied to ascertain the time lag between key environmental factors and algal growth in January-April 2021. Thirdly, a random forest machine learning (RFML) model was established for prediction and early warning of river algal bloom. Finally, the threshold of controllable hydro-meteorological conditions and control strategies for the algal bloom prevention was proposed. Results reveal that: (1) The importance ranking of key environmental variables for algal bloom are antecedent air temperature, total phosphorus, flow discharge, total nitrogen, solar radiation and river turbidity; (2) The time-lag between algal growth and the key environmental drivers is the previous 1–5 days period; (3) The RFML model based on antecedent environmental variables can effectively predict the concentration of Chl-a; (4) The diatom bloom is very possible to outbreak if the 5-day sliding accumulated temperature is more than 43.13 °C and the average flow discharge is less than 780 m3/s. Our study may provide potential scientific guidance for the preemptive warning and control strategies of riverine blooms. |
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institution | Directory Open Access Journal |
issn | 1470-160X |
language | English |
last_indexed | 2024-12-10T18:50:14Z |
publishDate | 2022-09-01 |
publisher | Elsevier |
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series | Ecological Indicators |
spelling | doaj.art-c51315981e864dc88e92904e33922f092022-12-22T01:37:20ZengElsevierEcological Indicators1470-160X2022-09-01142109190Preemptive warning and control strategies for algal blooms in the downstream of Han River, ChinaJing Tian0Shenglian Guo1Jun Wang2Heyu Wang3Zhengke Pan4State Key Laboratory of Water Resources and Hydropower Engineering Science, Wuhan University, Wuhan 430072, ChinaState Key Laboratory of Water Resources and Hydropower Engineering Science, Wuhan University, Wuhan 430072, China; Corresponding author.State Key Laboratory of Water Resources and Hydropower Engineering Science, Wuhan University, Wuhan 430072, ChinaState Key Laboratory of Water Resources and Hydropower Engineering Science, Wuhan University, Wuhan 430072, ChinaChangjiang Institute of Survey, Planning, Design and Research, Wuhan 430010, ChinaRiverine blooms have become a challenging global environmental problem owing to strong disturbances from intensified human activities and the construction or operation of hydraulic projects. Previous studies mainly paid attention to algal blooms in the lakes and reservoirs, while less focused on the prediction and prevention of algal blooms in large rivers. As one of the highly regulated rivers in China, the downstream of Han River frequently occurred consecutive algal blooms in recent decades, was selected as the case study. Firstly, algal blooms in the downstream of Han River during 1992–2021 were investigated to find out the key environmental factors governing algal blooms. Secondly, the distribution lag model was applied to ascertain the time lag between key environmental factors and algal growth in January-April 2021. Thirdly, a random forest machine learning (RFML) model was established for prediction and early warning of river algal bloom. Finally, the threshold of controllable hydro-meteorological conditions and control strategies for the algal bloom prevention was proposed. Results reveal that: (1) The importance ranking of key environmental variables for algal bloom are antecedent air temperature, total phosphorus, flow discharge, total nitrogen, solar radiation and river turbidity; (2) The time-lag between algal growth and the key environmental drivers is the previous 1–5 days period; (3) The RFML model based on antecedent environmental variables can effectively predict the concentration of Chl-a; (4) The diatom bloom is very possible to outbreak if the 5-day sliding accumulated temperature is more than 43.13 °C and the average flow discharge is less than 780 m3/s. Our study may provide potential scientific guidance for the preemptive warning and control strategies of riverine blooms.http://www.sciencedirect.com/science/article/pii/S1470160X22006628Algal bloomRFML modelHydro-meteorological thresholdsPreemptive warningControl strategiesHan River |
spellingShingle | Jing Tian Shenglian Guo Jun Wang Heyu Wang Zhengke Pan Preemptive warning and control strategies for algal blooms in the downstream of Han River, China Ecological Indicators Algal bloom RFML model Hydro-meteorological thresholds Preemptive warning Control strategies Han River |
title | Preemptive warning and control strategies for algal blooms in the downstream of Han River, China |
title_full | Preemptive warning and control strategies for algal blooms in the downstream of Han River, China |
title_fullStr | Preemptive warning and control strategies for algal blooms in the downstream of Han River, China |
title_full_unstemmed | Preemptive warning and control strategies for algal blooms in the downstream of Han River, China |
title_short | Preemptive warning and control strategies for algal blooms in the downstream of Han River, China |
title_sort | preemptive warning and control strategies for algal blooms in the downstream of han river china |
topic | Algal bloom RFML model Hydro-meteorological thresholds Preemptive warning Control strategies Han River |
url | http://www.sciencedirect.com/science/article/pii/S1470160X22006628 |
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