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Open AccessArticle

Predicting Cyanobacterial Harmful Algal Blooms (CyanoHABs) in a Regulated River Using a Revised EFDC Model

Water Quality Assessment Research Division, Water Environment Research Department, National Institute of Environmental Research, Incheon 22689, Korea
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Academic Editor: Sophia Barinova
Water 2021, 13(4), 439; https://doi.org/10.3390/w13040439
Received: 19 January 2021 / Revised: 4 February 2021 / Accepted: 4 February 2021 / Published: 8 February 2021
(This article belongs to the Special Issue Assessment of Water Quality)
Cyanobacterial Harmful Algal Blooms (CyanoHABs) produce toxins and odors in public water bodies and drinking water. Current process-based models predict algal blooms by modeling chlorophyll-a concentrations. However, chlorophyll-a concentrations represent all algae and hence, a method for predicting the proportion of harmful cyanobacteria is required. We proposed a technique to predict harmful cyanobacteria concentrations based on the source codes of the Environmental Fluid Dynamics Code from the National Institute of Environmental Research. A graphical user interface was developed to generate information about general water quality and algae which was subsequently used in the model to predict harmful cyanobacteria concentrations. Predictive modeling was performed for the Hapcheon-Changnyeong Weir–Changnyeong-Haman Weir section of the Nakdong River, South Korea, from May to October 2019, the season in which CyanoHABs predominantly occur. To evaluate the success rate of the proposed model, a detailed five-step classification of harmful cyanobacteria levels was proposed. The modeling results demonstrated high prediction accuracy (62%) for harmful cyanobacteria. For the management of CyanoHABs, rather than chlorophyll-a, harmful cyanobacteria should be used as the index, to allow for a direct inference of their cell densities (cells/mL). The proposed method may help improve the existing Harmful Algae Alert System in South Korea. View Full-Text
Keywords: water quality modeling; harmful cyanobacteria; CyanoHABs; EFDC-NIER water quality modeling; harmful cyanobacteria; CyanoHABs; EFDC-NIER
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MDPI and ACS Style

Ahn, J.M.; Kim, J.; Park, L.J.; Jeon, J.; Jong, J.; Min, J.-H.; Kang, T. Predicting Cyanobacterial Harmful Algal Blooms (CyanoHABs) in a Regulated River Using a Revised EFDC Model. Water 2021, 13, 439. https://doi.org/10.3390/w13040439

AMA Style

Ahn JM, Kim J, Park LJ, Jeon J, Jong J, Min J-H, Kang T. Predicting Cyanobacterial Harmful Algal Blooms (CyanoHABs) in a Regulated River Using a Revised EFDC Model. Water. 2021; 13(4):439. https://doi.org/10.3390/w13040439

Chicago/Turabian Style

Ahn, Jung M.; Kim, Jungwook; Park, Lan J.; Jeon, Jihye; Jong, Jaehun; Min, Joong-Hyuk; Kang, Taegu. 2021. "Predicting Cyanobacterial Harmful Algal Blooms (CyanoHABs) in a Regulated River Using a Revised EFDC Model" Water 13, no. 4: 439. https://doi.org/10.3390/w13040439

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