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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Main Authors: Jing Tian, Shenglian Guo, Jun Wang, Heyu Wang, Zhengke Pan
Format: Article
Language:English
Published: Elsevier 2022-09-01
Series:Ecological Indicators
Subjects:
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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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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AT junwang preemptivewarningandcontrolstrategiesforalgalbloomsinthedownstreamofhanriverchina
AT heyuwang preemptivewarningandcontrolstrategiesforalgalbloomsinthedownstreamofhanriverchina
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