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Journal articles on the topic 'Algal blooms'

Author: Grafiati

Published: 4 June 2021

Last updated: 25 July 2025

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1

Ma, Jinge, Feng He, Tianci Qi, et al. "Thirty-Four-Year Record (1987–2021) of the Spatiotemporal Dynamics of Algal Blooms in Lake Dianchi from Multi-Source Remote Sensing Insights." Remote Sensing 14, no. 16 (2022): 4000. http://dx.doi.org/10.3390/rs14164000.

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Lake Dianchi is one of the most eutrophic lakes in China. The decline in water quality and the occurrence of massive algal blooms pose a significant threat to the health and environmental safety of the water ecosystem, making Lake Dianchi a key concern for algal bloom management in China. Obtaining the spatiotemporal dynamics of algal blooms for the longest time possible is crucial to algal bloom management and future prediction. However, it is difficult to acquire a long-term record of algal blooms from a single sensor in order to cover a more extended period of eutrophication in the lake due

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2

Jing, Yuanyuan, Yuchao Zhang, Minqi Hu, Qiao Chu, and Ronghua Ma. "MODIS-Satellite-Based Analysis of Long-Term Temporal-Spatial Dynamics and Drivers of Algal Blooms in a Plateau Lake Dianchi, China." Remote Sensing 11, no. 21 (2019): 2582. http://dx.doi.org/10.3390/rs11212582.

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Algal blooms in eutrophic lakes have been a global issue to environmental ecology. Although great progress on prevention and control of algae have been made in many lakes, systematic research on long-term temporal-spatial dynamics and drivers of algal blooms in a plateau Lake Dianchi is so far insufficient. Therefore, the algae pixel-growing algorithm (APA) was used to accurately identify algal bloom areas at the sub-pixel level on the Moderate Resolution Imaging Spectroradiometer (MODIS) data from 2000 to 2018. The results showed that algal blooms were observed all year round, with a reduced

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3

Yi, Hye-Suk, Sunghwa Choi, Dong-Kyun Kim, and Hojoon Kim. "Improvement of Algal Bloom Identification Using Satellite Images by the Algal Spatial Monitoring and Machine Learning Analysis in a New Dam Reservoir." GEO DATA 5, no. 3 (2023): 126–36. http://dx.doi.org/10.22761/gd.2023.0021.

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Algal blooms are major issues and an ongoing cause of water quality problems in inland waters globally. In the case of harmful algal blooms, the water temperature rises after nitrogen and phosphorus inflow, which occurs in the summer, is the main cause of the algae bloom. In South Korea, algae monitoring methods have been performed by collecting water in point monitoring stations. Recently, in order to overcome the limitations of these existing monitoring methods, spatial monitoring methods using hyperspectral images and satellite images has been researched. We used satellite images for analys

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4

Wang, Shu Hang, Wen Wen Wang, and Xia Jiang. "The Process of Algal Bloom Formation and the Effects of Wind - An Enclosure Experiment and In Situ Investigation in a Large Hyper-Eutrophic Shallow Lake in China." Advanced Materials Research 518-523 (May 2012): 4303–14. http://dx.doi.org/10.4028/www.scientific.net/amr.518-523.4303.

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An enclosure experiment was conducted to evaluate the processes involved in algal bloom formation at different trophic levels in Chaohu Lake, which is a large hyper-eutrophic shallow lake in China. In situ investigations were conducted concurrently to quantitatively describe the effects of wind on the horizontal transference and vertical hybridization of algal blooms. The results revealed that certain nutrient trophic levels played a crucial role in the formation of algal blooms. Specifically, sediments were identified as an important source of nutrients and algal seeds that are necessary to m

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5

Lathrop, Richard C. "Evaluation of Whole-Lake Nitrogen Fertilization for Controlling Blue-Green Algal Blooms in a Hypereutrophic Lake." Canadian Journal of Fisheries and Aquatic Sciences 45, no. 12 (1988): 2061–75. http://dx.doi.org/10.1139/f88-240.

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Indian Lake, a shallow hypereutrophic lake in southern Wisconsin, was treated with ammonium nitrate to test whether high dissolved inorganic nitrogen (DIN) concentrations or high total nitrogen to phosphorus (N:P) ratios could prevent the development of summer blue-green algal blooms (predominately Microcystis aeruginosa). The fertilizer was applied weekly from late April to early July 1981–82 in annual amounts of 14 and 23 g N/m2, respectively. In 1981, a dense summer blue-green algal bloom developed, although both dissolved inorganic phosphorus (DIP) and algal P (particulate P/chlorophyll a)

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6

Yun, Hongwon. "Prediction model of algal blooms using logistic regression and confusion matrix." International Journal of Electrical and Computer Engineering (IJECE) 11, no. 3 (2021): 2407. http://dx.doi.org/10.11591/ijece.v11i3.pp2407-2413.

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Algal blooms data are collected and refined as experimental data for algal blooms prediction. Refined algal blooms dataset is analyzed by logistic regression analysis, and statistical tests and regularization are performed to find the marine environmental factors affecting algal blooms. The predicted value of algal bloom is obtained through logistic regression analysis using marine environment factors affecting algal blooms. The actual values and the predicted values of algal blooms dataset are applied to the confusion matrix. By improving the decision boundary of the existing logistic regress

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7

Hongwon, Yun. "Prediction model of algal blooms using logistic regression and confusion matrix." International Journal of Electrical and Computer Engineering (IJECE) 11, no. 3 (2021): 2407–13. https://doi.org/10.11591/ijece.v11i3.pp2407-2413.

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Algal blooms data are collected and refined as experimental data for algal blooms prediction. Refined algal blooms dataset is analyzed by logistic regression analysis, and statistical tests and regularization are performed to find the marine environmental factors affecting algal blooms. The predicted value of algal bloom is obtained through logistic regression analysis using marine environment factors affecting algal blooms. The actual values and the predicted values of algal blooms dataset are applied to the confusion matrix. By improving the decision boundary of the existing logistic regress

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8

Zhao, Dongzhi, Qinshun Luo, and Zhongfeng Qiu. "Chromaticity-Based Discrimination of Algal Bloom from Inland and Coastal Waters Using In Situ Hyperspectral Remote Sensing Reflectance." Water 16, no. 16 (2024): 2276. http://dx.doi.org/10.3390/w16162276.

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The rapid growth of phytoplankton and microalgae has presented considerable environmental and societal challenges to the sustainable development of human society. Given the inherent limitations of satellite-based algal bloom detection techniques that rely on chlorophyll and fluorescence methods, this study proposes a method that employs hyperspectral data to calculate water chromatic indices (WCIs), including hue, saturation (S), dominant wavelength (λd), and integrated apparent visual wavelength (IAVW), to identify algal blooms. A global in situ hyperspectral dataset was constructed, comprisi

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9

Sidabutar, Tumpak, Endang Sunarwati Srimariana, Hendrik Cappenberg, and Sam Wouthuyzen. "Comprehensive analysis of harmful algal blooms in indonesia: from occurrence to impact." BIO Web of Conferences 87 (2024): 02003. http://dx.doi.org/10.1051/bioconf/20248702003.

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The occurrence and frequency of harmful algal blooms have become a significant problem in Indonesia's coastal waters since 1991. This article aims to thoroughly analyze the diversity of algal species involved in these harmful algal blooms (HABs). It highlights that some algae, such as toxic species, can produce dangerous toxins, while others, such as non-toxic algae, remain harmless. This article reviews research studies that describe the occurrence, frequency, and causative types of bloom events in several contaminated coastal regions of Indonesia. The blooms had many consequences for fisheri

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10

Zhang, Yuchao, Steven Loiselle, Kun Shi, et al. "Wind Effects for Floating Algae Dynamics in Eutrophic Lakes." Remote Sensing 13, no. 4 (2021): 800. http://dx.doi.org/10.3390/rs13040800.

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Wind-speed decline is an important impact of climate change on the eastern Asian atmospheric circulation. Although wind does not determine algae biomass in eutrophic lakes, it is a decisive factor in the formation and severity of algae blooms. Based on 2000–2018 MODIS images, this study compared the effects of wind speed on algal blooms in three typical eutrophic lakes in China: Lake Taihu, Lake Chaohu and Lake Dianchi. The results indicate that climate change has different effects on the wind speed of the three lakes, but a common effect on the vertical distribution of algae. A wind speed of

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11

Zhao, Ziyue, Xuemei Liu, Yanfeng Wu, et al. "A Review on the Driving Mechanism of the Spring Algal Bloom in Lakes Using Freezing and Thawing Processes." Water 16, no. 2 (2024): 257. http://dx.doi.org/10.3390/w16020257.

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Spring algal blooms in mid–high-latitude lakes are facing serious challenges such as earlier outbreaks, longer duration, and increasing frequency under the dual pressure of climate warming and human activities, which threaten the health of freshwater ecosystems and water security. At present, the freeze-thaw processes is the key to distinguishing spring algal blooms in mid- to high-latitude lakes from low-latitude lakes. Based on the visualization and an analysis of the literature in the WOS database during 2007–2023, we clarified the driving mechanism of the freeze-thaw process (freeze-thaw,

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12

BHANDAGE, Venkatesh, and Manohara PAI M. M. "SEMANTIC SEGMENTATION OF ALGAL BLOOMS ON THE OCEAN SURFACE USING SENTINEL 3 CHL_NN BAND IMAGERY." Applied Computer Science 20, no. 3 (2024): 34–50. http://dx.doi.org/10.35784/acs-2024-27.

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Satellite imagery plays an important role in detecting algal blooms because of its ability to cover larger geographical regions. Excess growth of Sea surface algae, characterized by the presence of Chlorophyll-a (Chl-a), is considered to be harmful. The detection of algal growth at an earlier stage may prevent hazardous effects on the aquatic environment. Semantic segmentation of algal blooms is helpful in the quantization of algal blooms. A rule-based semantic segmentation approach for the segregation of sea surface algal blooms is proposed. Bloom concentrations are classified into three diff

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13

Hu, Xiaokun, Kuixuan Lin, Rui Wang, et al. "The Spatial Evolution Characteristics of Phytoplankton and the Impact of Environmental Factors in a Harbor-Construction-Formed Reservoir." Water 16, no. 19 (2024): 2813. http://dx.doi.org/10.3390/w16192813.

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Phytoplankton are an important part of aquatic ecosystems and substantially contribute to primary productivity. Under certain conditions, phytoplankton can grow or cluster in large numbers, resulting in enormous economic losses and serious threats to human life and health. In this study, complex causative species of algal blooms were examined and regulatory factors were determined in a reservoir formed by harbor construction. The reservoir is isolated from the harbor by sluice gates, forming a separate water region. Twelve species of phytoplankton, including normally and abnormally blooming sp

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14

Li, Yachun, Shihua Zhu, Xin Hang, et al. "Variation of Local Wind Fields under the Background of Climate Change and Its Impact on Algal Blooms in Lake Taihu, China." Water 15, no. 24 (2023): 4258. http://dx.doi.org/10.3390/w15244258.

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Global climate change can greatly promote the continuing expansion of algal blooms in eutrophic inland lakes. Wind fields, an important climate factor, provide an external driving force for the movement of algal blooms. Based on algal bloom satellite imageries and wind observation data from 2003 to 2022, this study explored a quantitative assessment of the variations in surface wind fields and their impacts on the algal blooms in Lake Taihu, China. The results indicate that the mean wind speed at different time scales in the Lake Taihu area presents a continuous descending tendency in recent d

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15

Luo, Qinshun, Dongzhi Zhao, Zhongfeng Qiu, Sheng Jiang, and Yuanzhi Zhang. "Research on the Detection Method of Cyanobacteria in Lake Taihu Based on Hyperspectral Data from ZY-1E." Journal of Marine Science and Engineering 13, no. 3 (2025): 540. https://doi.org/10.3390/jmse13030540.

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Cyanobacterial blooms are a widespread phenomenon in aquatic ecosystems worldwide, causing significant harm to the ecological environment. Lake Taihu is the third-largest freshwater lake in China. The region has been increasingly affected by cyanobacterial blooms, drawing greater attention from people. Currently, numerous models have been developed for detecting algal bloom based on spectral characteristics. However, the intuitive basis of optical detection lies in water color. Therefore, constructing an algal bloom detecting model from the perspective of chromaticity is worth exploring. This

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16

Liu, Jia, Chunlin Xia, Hui Xie, Xiaodong Wang, and Yinguo Qiu. "Accurate Monitoring of Algal Blooms in Key Nearshore Zones of Lakes and Reservoirs Using Binocular Video Surveillance System." Water 14, no. 22 (2022): 3728. http://dx.doi.org/10.3390/w14223728.

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In recent years, algal blooms break out frequently and often accumulate in nearshore zones of eutrophic lakes and reservoirs, which seriously threaten regional water supply security. It is of great significance to grasp the status of algal blooms in key nearshore zones timely for the emergency prevention and control of algal blooms. A video surveillance system provides a new method for achieving this goal. The results of algal-bloom monitoring in current research, however, are usually interfered by onshore vegetation for their similar textural features. Accordingly, there are great limitations

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17

Schleyer, Guy, and Assaf Vardi. "Algal blooms." Current Biology 30, no. 19 (2020): R1116—R1118. http://dx.doi.org/10.1016/j.cub.2020.07.011.

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18

Li, Gege. "Algal blooms." New Scientist 258, no. 3439 (2023): 30–31. http://dx.doi.org/10.1016/s0262-4079(23)00911-9.

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19

Gong, Xingrui, Chao Ma, Beili Sun, and Junyi Zhang. "An Efficient Self-Organized Detection System for Algae." Sensors 23, no. 3 (2023): 1609. http://dx.doi.org/10.3390/s23031609.

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Algal blooms have seriously affected the production and life of people and real-time detection of algae in water samples is a powerful measure to prevent algal blooms. The traditional manual detection of algae with a microscope is extremely time-consuming. In recent years, although there have been many studies using deep learning to classify and detect algae, most of them have focused on the relatively simple task of algal classification. In addition, some existing algal detection studies not only use small datasets containing limited algal species, but also only prove that object detection al

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20

Sidabutar, Tumpak, Endang Sumarwati S Srimariana, Hendrik Cappenberg, and Sam Wouthuyzen. "EARLY WARNING SYSTEM (EWS) FOR ALGAL BLOOMS USING SATELLITE IMAGERY IN JAKARTA BAY." Jurnal Ilmu dan Teknologi Kelautan Tropis 15, no. 3 (2023): 369–88. http://dx.doi.org/10.29244/jitkt.v15i3.52627.

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Jakarta Bay is experiencing eutrophication, primarily due to nutrient inflows from agriculture, industry, and urban sources. This abundance of nutrients has led to significant algae blooms. A study using Terra and Aqua MODIS satellite data from 2004 to 2007 monitored these blooms by measuring chlorophyll-a levels. During this period, large-scale fish kills were observed directly related to the algal blooms, as evidenced by high chlorophyll-a concentrations and blooms covering more than a quarter of the bay. Interestingly, not all intense blooms resulted in massive fish kills. The study suggest

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21

Zhang, Tiantian, Hong Hu, Xiaoshuang Ma, and Yaobo Zhang. "Long-Term Spatiotemporal Variation and Environmental Driving Forces Analyses of Algal Blooms in Taihu Lake Based on Multi-Source Satellite and Land Observations." Water 12, no. 4 (2020): 1035. http://dx.doi.org/10.3390/w12041035.

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The algal blooms caused by the eutrophication of lakes is a major environmental problem. In this study, we took China’s Taihu Lake as the research area, using multi-source satellite imagery data to monitor the information of algal blooms from 2008 to 2017. Following the analyses of the temporal and spatial variation trends of the blooms, water quality and meteorological data from land observation stations were employed to investigate the main environmental driving forces of the algal bloom outbreaks. The results show that, over the decade, the blooms with medium and higher hazard degrees mainl

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22

Podsosonnaya, Mayya, Maria J. Schreider, and Sergei Schreider. "Modeling Estuarine Algal Bloom Dynamics with Satellite Data and Spectral Index-Based Classification." Hydrology 12, no. 6 (2025): 130. https://doi.org/10.3390/hydrology12060130.

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Macroalgae are an integral part of estuarine primary production; however, their excessive growth may have severe negative impacts on the ecosystem. Although it is generally believed that algal blooms may be caused by a combination of excessive nutrients and temperature, their occurrences are hard to predict, and quantitative monitoring is a logistical challenge which requires the development of reliable and inexpensive techniques. This can be achieved by implementation of processing algorithms and indices on multi-spectral satellite images. Tuggerah Lakes estuary on the Central Coast of NSW wa

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23

Son, Geunsoo, Dongsu Kim, Young Do Kim, Siwan Lyu, and Soojeong Kim. "A Forecasting Method for Harmful Algal Bloom(HAB)-Prone Regions Allowing Preemptive Countermeasures Based only on Acoustic Doppler Current Profiler Measurements in a Large River." Water 12, no. 12 (2020): 3488. http://dx.doi.org/10.3390/w12123488.

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Harmful algal blooms (HABs) have been recognized as a serious problem for aquatic ecosystems and a threat to drinking water systems. The proposed method aimed to develop a practical and rapid countermeasure, enabling preemptive responses to massive algal blooms, through which prior to the algal bloom season we can identify HAB-prone regions based on estimations of where harmful algae initiates and develops significantly. The HAB-prone regions were derived from temperature, depth, flow velocity, and sediment concentration data based only on acoustic Doppler current profilers (ADCPs) without rel

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24

Sidabutar, T., E. S. Srimariana, H. Cappenberg, and S. Wouthuyzen. "An overview of harmful algal blooms and eutrophication in Jakarta Bay, Indonesia." IOP Conference Series: Earth and Environmental Science 869, no. 1 (2021): 012039. http://dx.doi.org/10.1088/1755-1315/869/1/012039.

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Abstract Algal blooms have been occurring in Jakarta Bay for twenty years. However, recently the occurrence of algal blooms, their harmful effects, and their duration have been intensified. Algal blooms have devastated the marine environment, caused fish mortality, and been detrimental to local tourism, local fishing, and other industries along the coast. It comes to speculation that the increase of anthropogenic activity from surrounding areas is taking a toll on the environment. So, this research aimed to study the recent rise of algal blooms in Jakarta Bay and the possible anthropogenic lin

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25

Das, Mautushi, Sheikh Runima Begum, Marchia K. Sangma, and Monalisa Bora Deka. "Water Chemistry Dynamics in Dighalipukhuri Lake: The Influence of Cyanobacterial Bloom Density." Ecology, Environment and Conservation 31, April Suppl. Issue (2025): 26–35. https://doi.org/10.53550/eec.2025.v31i03s.006.

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This study investigates the productivity and cell count of Microcystis aeruginosa and the Physico-chemical properties of Dighalipukhuri Lake, a rectangular man-made pond in Guwahati. The research provides a comprehensive overview of algal growth, its concentration, and its correlation with the lake’s physical and chemical attributes. Water samples were analyzed following APHA (2005) protocols. Results indicated an alkaline pH, which promotes cyanobacterial blooms, and consistently low dissolved oxygen (DO) levels across all seasons, likely due to surface cyanobacterial proliferation. The lake’

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26

Guo, Yansen, Wenrui Fu, Nan Xiong, Jian He, and Zheng Zheng. "Phosphorus Threshold for the Growth of Microcystis wesenbergii, Microcystis aeruginosa, and Chlorella vulgaris Based on the Monod Formula." Water 15, no. 24 (2023): 4249. http://dx.doi.org/10.3390/w15244249.

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The outbreak of algae in freshwater bodies poses an important threat to aquatic ecosystems, making finding an effective method for controlling algal blooms imperative. Numerous key factors influence algal bloom outbreaks, with nutrient levels in the water body being the decisive factor. Current research regarding the effect of nutrient levels on algal growth shows that phosphorus is a nutrient that influences algal blooms. Herein, we propose the concept of a modified Monod model for the relationship between algal specific growth rate and phosphorus concentration. Through this improved Monod mo

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27

Havens, Karl. "The Future of Harmful Algal Blooms in Florida Inland and Coastal Waters." EDIS 2018, no. 1 (2018): 4. http://dx.doi.org/10.32473/edis-sg153-2018.

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Microscopic algae in oceans and inland waters sometimes grow to excessive levels called “blooms.” Warmer water temperatures and increased nutrient levels exacerbate blooms, and when nutrients are high, temperature increases of just a few degrees cause exponential increases of algae and blooms. This 4-page fact sheet written by Karl Havens and published by the Florida Sea Grant College Program and UF/IFAS Extension explains why algal blooms can be harmful and provides advice for communities seeking to reduce nutrient levels in their lakes, streams, and other bodies of water. In a warmer future,

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28

Al-Ghelani, H. M., A. Y. A. AlKindi, S. Amer, and Y. K. Al-Akhzami. "Harmful Algal Blooms: Physiology, Behavior, Population Dynamics and Global Impacts- A Review." Sultan Qaboos University Journal for Science [SQUJS] 10 (June 1, 2005): 1. http://dx.doi.org/10.24200/squjs.vol10iss0pp1-30.

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Harmful, toxic algae are now considered as one of the important players in the newly emerging environmental risk factors. The apparent global increase in harmful algal blooms (HABs) is becoming a serious problem in both aquaculture and fisheries populations. Not only has the magnitude and intensity of public health and economic impacts of these blooms increased in recent years, but the number of geographic locations experiencing toxic algal blooms has also increased dramatically. There are two primary factors causing HABs outbreaks. The natural processes such as upwelling and relaxation, and t

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Ali, Maisam, Muhammad Yaseen, Sikandar Ali, and Hee-Cheol Kim. "Deep Learning-Based Approach for Microscopic Algae Classification with Grad-CAM Interpretability." Electronics 14, no. 3 (2025): 442. https://doi.org/10.3390/electronics14030442.

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The natural occurrence of harmful algal blooms (HABs) adversely affects the quality of clean and fresh water. They pose increased risks to human health, aquatic ecosystems, and water bodies. Continuous monitoring and appropriate measures must be taken to combat HABs. Deep learning models that utilize computer vision play a vital role in identifying and classifying harmful algal blooms in aquatic environments and water storage facilities. Inspecting algal blooms using conventional methods, such as algae detection under microscopes, is difficult, expensive, and time-consuming. Deep learning algo

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Namsaraev, Zorigto, Anna Melnikova, Anastasia Komova, Vasily Ivanov, Anastasia Rudenko, and Evgenii Ivanov. "Algal Bloom Occurrence and Effects in Russia." Water 12, no. 1 (2020): 285. http://dx.doi.org/10.3390/w12010285.

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Eutrophication caused by the entry of nutrients into a water body may lead to algal bloom. Russia possesses the world’s second highest supply of renewable freshwater resources and has faced the problem of eutrophication for many years. Nevertheless, as far as we know, no general analysis of Russia’s algal bloom situation has been before carried out. We have analyzed mass media and scientific reports about algal outbreaks from 2016 to 2018, which allowed us to determine the geographical distribution of algal blooms in Russia, as well as the major effects of eutrophication. As a result, we showe

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31

Dembowska, Ewa. "Cyanobacterial blooms in shallow lakes of the Iławskie Lake District." Limnological Review 11, no. 2 (2011): 69–79. http://dx.doi.org/10.2478/v10194-011-0028-y.

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Cyanobacterial blooms in shallow lakes of the Iławskie Lake DistrictThe dominance of blue-green algae observed in many lakes is related to a high trophic level. Shallow eutrophic lakes are particularly often abundant in blue-green algae. The research on phytoplankton, the results of which are presented in this paper, was carried out between 2002 and 2005 in six lakes. These lakes differed considerably in their size and management methods applied in the catchment (drainage) area. A few types of water blooms were distinguished, which is related to the catchment area management, the intensity of

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Lihepanyama, Deogratias Ladislaus, Patrick Alois Ndakidemi, and Anna Christina Treydte. "Spatio–Temporal Water Quality Determines Algal Bloom Occurrence and Possibly Lesser Flamingo (Phoeniconaias minor) Presence in Momella Lakes, Tanzania." Water 14, no. 21 (2022): 3532. http://dx.doi.org/10.3390/w14213532.

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Eutrophication and algal blooms have sparked worldwide concern because of their widespread effects on water-dependent species. Harmful algal blooms can cause fatal effects to lesser flamingos (Phoeniconaias minor), obligatory filter feeders and vital bio-indicators in soda lakes. Thus, early detection of algal blooms and potential indicators in water quality is critical, but general tools are lacking in eastern African soda lakes. We monitored algal biomass changes and related water physico–chemical variables for 12 consecutive months in the lakes Big Momella and Rishateni in northern Tanzania

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Rostam, Nur Aqilah Paskhal, Nurul Hashimah Ahamed Hassain Malim, Nur Afzalina Azmee, Renato J. Figueiredo, Mohd Azam Osman, and Rosni Abdullah. "Harmful algal blooms (HAB) open issues: A review of ecological data challenges, factor analysis and prediction approaches using data-driven method." Computing and Artificial Intelligence 1, no. 1 (2023): 100. http://dx.doi.org/10.59400/cai.v1i1.100.

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Ongoing research on the temporal and spatial distribution of algae ecological data has caused intricacies entailing incomprehensible data, model overfit, and inaccurate algal bloom prediction. Relevant scholars have integrated past historical data with machine learning (ML) and deep learning (DL) approaches to forecast the advent of harmful algal blooms (HAB) following successful data-driven techniques. As potential HAB outbreaks could be predicted through time-series forecasting (TSF) to gauge future events of interest, this research aimed to holistically review field-based complexities, infl

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EPSTEIN, P. "Harmful algal blooms." Lancet 342, no. 8879 (1993): 1108. http://dx.doi.org/10.1016/0140-6736(93)92085-8.

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Zawadzki, Jarosław, and Piotr Fabijańczyk. "Application of Geostatistical Methods in the Study of Algae in Water Reservoirs: A Review." Ecological Chemistry and Engineering S 31, no. 4 (2024): 473–91. https://doi.org/10.2478/eces-2024-0031.

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Abstract The growing pollution of aquatic environments, primarily of anthropogenic origin, combined with global climate change, has led to significant increases in eutrophication. This process often results in harmful algal blooms (HABs) of phytoplankton and algae in various water bodies, including inland lakes, marshes, rivers, seas, and oceans. These blooms pose a serious threat not only to aquatic ecosystems but also to human health. Understanding phytoplankton and algal blooms is inherently complex, as these phenomena manifest on multiple spatial and temporal scales. Comprehensive studies

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Krimsky, Lisa, Elizabeth Staugler, Dail Laughinghouse IV, and Joy Hazell. "Florida Sea Grant Symposia Promote Collaboration Among Harmful Algal Bloom Stakeholders." Oceanography 37, no. 1 (2024): 70–74. http://dx.doi.org/10.5670/oceanog.2024.209.

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Algal blooms are a pervasive problem for Florida, and successful management decisions must rely on the best available science. In 2019, Florida Sea Grant convened a forum of harmful algal bloom (HAB) scientists for the first Harmful Algal Bloom State of the Science Symposium. The goals of the two-day forum were to develop consensus statements identifying the current state of the science regarding what we know and what we think we know, data gaps and areas of uncertainty, and research priorities, with a focus on Karenia brevis red tides and Microcystis aeruginosa cyanobacterial blooms. In 2023,

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Zhu, Shengyuan, Yinglei Wu, and Xiaoshuang Ma. "Deep Learning-Based Algal Bloom Identification Method from Remote Sensing Images—Take China’s Chaohu Lake as an Example." Sustainability 15, no. 5 (2023): 4545. http://dx.doi.org/10.3390/su15054545.

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Rapid and accurate monitoring of algal blooms using remote sensing techniques is an effective means for the prevention and control of algal blooms. Traditional methods often have difficulty achieving the balance between interpretative accuracy and efficiency. The advantages of a deep learning method bring new possibilities to the rapid and precise identification of algal blooms using images. In this paper, taking Chaohu Lake as the study area, a dual U-Net model (including a U-Net network for spring and winter and a U-Net network for summer and autumn) is proposed for the identification of alg

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Al-Shehhi, Maryam R., and Yarjan Abdul Samad. "Identifying Algal Bloom ‘Hotspots’ in Marginal Productive Seas: A Review and Geospatial Analysis." Remote Sensing 14, no. 10 (2022): 2457. http://dx.doi.org/10.3390/rs14102457.

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Algal blooms in the marginal productive seas of the Indian Ocean are projected to become more prevalent over the coming decades. They reach from lower latitudes up to the coast of the northern Indian Ocean and the populated areas along the Arabian Gulf, Sea of Oman, Arabian Sea, and the Red Sea. Studies that document algal blooms in the Indian Ocean have either focused on individual or regional waters or have been limited by a lack of long-term observations. Herein, we attempt to review the impact of major monsoons on algal blooms in the region and identify the most important oceanic and atmos

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Sun, Longfei, Leixiang Wu, Xiaobo Liu, et al. "Reducing the Risk of Benthic Algae Outbreaks by Regulating the Flow Velocity in a Simulated South–North Water Diversion Open Channel." International Journal of Environmental Research and Public Health 20, no. 4 (2023): 3564. http://dx.doi.org/10.3390/ijerph20043564.

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The reduction in open-channel flow velocity due to China’s South-to-North Water Diversion Project (SNP) increases the risk of benthic algal community blooms resulting in drinking water safety issues. Consequently, it has attracted attention from all walks of life. However, regulatory measures to mitigate the risk of algal blooms and the main risk-causing factors are unclear. This study simulated the river ecosystem of the SNP channel through water diversion. Simulated gradient-increasing river flow velocity affects environmental factors and benthic algal alterations, and can be used to explore

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Guan, Di, Da Wen Gao, Nan Qi Ren, and Yi Fan Li. "Viewpoints of Dominant Environmental Factors Influencing Algal Blooms." Applied Mechanics and Materials 66-68 (July 2011): 155–59. http://dx.doi.org/10.4028/www.scientific.net/amm.66-68.155.

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Harmful algal blooms (HABs) are generally known as excessive phytoplankton growth or rapidly concentrate to high biomass. This study summarized the situation of HABs in China, and discussed possible dominant factors stimulating algal blooms by analyzing several actual HABs cases. It was manifested nutrients may affect algae concentration principally, but such impact tended to decease with degradation of background water. Meanwhile the hydrological and meteorological factors expressed greater correlation to chlorophyll concentration under multiple coupling effects of complex environmental facto

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Cui, Jianglong, Xiaodie Zhang, Caili Du, and Guowen Li. "Remote Sensing Identification of Harmful Algae in Ulansuhai Lake with Machine Learning." Water 17, no. 1 (2024): 50. https://doi.org/10.3390/w17010050.

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Frequent algal blooms in lakes pose a serious threat to aquatic ecosystems. It is of great significance to quickly and accurately monitor the distribution of algae in lakes for the regulation of algal blooms. While remote sensing techniques and machine learning methods can be used in combination to identify algae and analyze their spatial and temporal distribution, these methods still face challenges in practical applications due to uncertainties in lake boundaries and imbalances between algae and non-algae. In order to overcome these difficulties, we studied the dynamic open water range of Ul

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Pu, Jing, Kaishan Song, Yunfeng Lv, et al. "Distinguishing Algal Blooms from Aquatic Vegetation in Chinese Lakes Using Sentinel 2 Image." Remote Sensing 14, no. 9 (2022): 1988. http://dx.doi.org/10.3390/rs14091988.

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Algal blooms frequently occur in numerous lakes in China, risking human health and the environment. In contrast, aquatic vegetation contributes to water purification. Due to the similar spectral characteristics shared by algal and aquatic vegetation, both are hardly distinguishable in remote sensing imaging, especially in turbid water bodies. To address this challenge, this study constructed a method to effectively extract algal blooms and aquatic vegetation from the turbid water bodies using Sentinel 2 images with high spatial resolution. Our results showed that the accuracy of the extraction

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Patiño, Reynaldo, Victoria G. Christensen, Jennifer L. Graham, Jane S. Rogosch, and Barry H. Rosen. "Toxic Algae in Inland Waters of the Conterminous United States—A Review and Synthesis." Water 15, no. 15 (2023): 2808. http://dx.doi.org/10.3390/w15152808.

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Cyanobacteria are the most common toxigenic algae in inland waters. Their toxins can affect the health of aquatic and terrestrial organisms, including humans. Other algal groups, such as haptophytes (e.g., Prymnesium parvum) and euglenoids (e.g., Euglena sanguinea), can also form harmful algal blooms (HABs) whose toxins cause injury to aquatic biota but currently have no known effects on human health. Prymnesium parvum, however, is responsible for some of the worst HAB-related ecological disasters recorded in inland waters. Here, we provide an overview of the primary toxigenic algae found in U

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Park, Jungsu, Hyunho Lee, Cheol Young Park, Samiul Hasan, Tae-Young Heo, and Woo Hyoung Lee. "Algal Morphological Identification in Watersheds for Drinking Water Supply Using Neural Architecture Search for Convolutional Neural Network." Water 11, no. 7 (2019): 1338. http://dx.doi.org/10.3390/w11071338.

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An excessive increase in algae often has various undesirable effects on drinking water supply systems, thus proper management is necessary. Algal monitoring and classification is one of the fundamental steps in the management of algal blooms. Conventional microscopic methods have been most widely used for algal classification, but such approaches are time-consuming and labor-intensive. Thus, the development of alternative methods for rapid, but reliable algal classification is essential where an advanced machine learning technique, known as deep learning, is considered to provide a possible ap

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TAS, S., and I. N. YILMAZ. "Potentially harmful microalgae and algal blooms in a eutrophic estuary in Turkey." Mediterranean Marine Science 16, no. 2 (2015): 432. http://dx.doi.org/10.12681/mms.1042.

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Distribution of potentially harmful microalgae and algal blooms were investigated at monthly and weekly time scales between October 2009 and September 2010 in the Golden Horn, a eutrophic estuary in the Sea of Marmara (Turkey). Several physical and chemical parameters were analysed together with phytoplankton composition and abundance. A total number of 23 potentially harmful and/or bloom-forming microalgae (14 dinoflagellates, 4 diatoms and 5 phytoflagellates) were identified throughout this study period, of which nine taxa have been confirmed to be toxic elsewhere in the world. Most harmful

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Wang, Haojiong, Elroy Galbraith, and Matteo Convertino. "Algal Bloom Ties: Spreading Network Inference and Extreme Eco-Environmental Feedback." Entropy 25, no. 4 (2023): 636. http://dx.doi.org/10.3390/e25040636.

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Coastal marine ecosystems worldwide are increasingly affected by tide alterations and anthropogenic disturbances affecting the water quality and leading to frequent algal blooms. Increased bloom persistence is a serious threat due to the long-lasting impacts on ecological processes and services, such as carbon cycling and sequestration. The exploration of eco-environmental feedback and algal bloom patterns remains challenging and poorly investigated, mostly due to the paucity of data and lack of model-free approaches to infer universal bloom dynamics. Florida Bay, taken as an epitome for biodi

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Zhang, Hong, Fayu Zhang, and Qing Huang. "Highly effective removal of malachite green from aqueous solution by hydrochar derived from phycocyanin-extracted algal bloom residues through hydrothermal carbonization." RSC Advances 7, no. 10 (2017): 5790–99. http://dx.doi.org/10.1039/c6ra27782a.

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Huge volumes of harmful algal bloom residues (ABR) are collected during emergency treatment of cyanobacteria blooms, and phycocyanin-extracted algal bloom residues (PE-ABR) are produced after extraction of phycocyanin from ABR.

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Sim, Bo-Ram, Hyung-Chul Kim, Chung-Sook Kim, et al. "Seasonal Distributions of Phytoplankton and Environmental Factors Generate Algal Blooms in the Taehwa River, South Korea." Water 12, no. 12 (2020): 3329. http://dx.doi.org/10.3390/w12123329.

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Algal blooms have occurred in the Taehwa River estuary in South Korea despite the improvement of water quality since environmental renewal projects in the 1990s. In this study, we investigated the causes of algal blooms by measuring the water retention time using a floating buoy, water quality parameters, and phytoplankton distribution data from 2012. An algal bloom did not occur in February because of phosphate limitations in the Taehwa River estuary; however, the concentration of nutrients in the water inflow from the basin triggered a significant algal bloom in the upper estuary in the mont

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Lathrop, Richard C., Stephen R. Carpenter, Craig A. Stow, Patricia A. Soranno, and John C. Panuska. "Phosphorus loading reductions needed to control blue-green algal blooms in Lake Mendota." Canadian Journal of Fisheries and Aquatic Sciences 55, no. 5 (1998): 1169–78. http://dx.doi.org/10.1139/f97-317.

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We evaluated the reductions in P loading needed to control blue-green algal blooms in Lake Mendota, Wisconsin. After developing a 21-year loading data set, we used a P mass balance model expressed as a difference equation with an annual time step indexed from mid-April. We defined and estimated a loss parameter lambda as the proportion of the lake's April P concentration lost through sedimentation and outflow during the following year. Using the distribution of annual lambda 's and input loadings, we predicted the steady-state distribution of April P concentrations that would result from scena

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Liao, Zihang, Shun Lv, Chenwu Zhang, Yong Zha, Suyang Wang, and Min Shao. "Analysis of Meteorological Drivers of Taihu Lake Algal Blooms over the Past Two Decades and Development of a VOCs Emission Inventory for Algal Bloom." Remote Sensing 16, no. 10 (2024): 1680. http://dx.doi.org/10.3390/rs16101680.

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Cyanobacterial blooms represent a common environmental issue in aquatic systems, and these blooms bring forth numerous hazards, with the generation of volatile organic compounds (VOCs) being one of them. Global climate change has led to alterations in various climatic factors affecting algal growth, indirectly impacting the quantity of VOCs released by algae. With advancements in remote sensing technology, exploration of the spatiotemporal distributions of algae in large water bodies has become feasible. This study focuses on Taihu Lake, characterized by frequent occurrences of cyanobacterial

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