• Journal of Korean Society on Water Environment
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• v.35 no.4
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• pp.352-361
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• 2019

The purpose of this study is to analyze the characteristics and correlations of the Yeongcheon Lake in order to reduce the occurrence of harmful cyanobacteria. In this study, we investigated the water quality and phytoplankton of the lake from May to November in 2017. Correlation and data mining analyses were performed to analyze the relationship between the two factors. The water temperature was lowest at the point where the Yeongcheon Lake inflow occurs at Imha Lake. It was highest at the point where the outflow occurs to Angye Lake. The pH was also highest at the outflow point, but in the case of DO, it was highest at the midpoint between the inflow and outflow. The main cyanobacteria that emerged during the study period were Oscillatorialimosa, Microcysti saeruginosa and Aphanizomenon flos-aquae. As a result of correlation analysis, the water temperature, inflow, COD loading, TOC loading at the inflow point of the Yeongcheon Lake were the items that were related to the harmful cyanobacteria. The data mining analysis indicated that the TP loading and harmful cyanobacteria in the inflow point of the Yeongcheon Lake were influential on the detrimental cyanobacteria in the Yeongcheon Lake outflow point. When the TP loading was less than 39.0 kg/day at the inflow site, it was expected that the amount of harmful cyanobacteria could be maintained below 10,000 cells/mL.

• Journal of Korean Society on Water Environment
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• v.40 no.1
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• pp.1-10
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• 2024

Algal blooms occur seasonally in the eutrophicated rivers or reservoirs, and some harmful cyanobacteria species produce toxic substances, which are directly or indirectly harmful to the ecosystem and terrestrial animals. So, the monitoring and control of harmful cyanobacteria occurrence and toxins residual in the aquasystem are important to preserve the water environment and secure public health. In this study, the four harmful cyanobacteria occurrences and toxic substance concentrations of two agricultural reservoirs in the southern part of Gyeonggi Province were investigated from August to October 2022. Among four harmful cyanobacteria (Microcystis sp., Anabaena sp., Oscillatoria sp., Aphanizomenon sp.), three kinds of cyanobacteria except Oscillatoria sp. were observed, and Microcystis sp. was the dominant cyanobacteria except for Anabaena sp. dominant result of a sample collected on October at reservoir B. The cell density of cyanobacteria was influenced by season and weather due to the length of daytime and concentrations of organic carbon and nitrogen. Three kinds of microcystin and anatoxin-a were quantitatively analyzed as total (in the cell body and water) and extracellular (in water) concentrations. The maximum total concentrations of anatoxin-a, microcystin-LR, microcystin-RR, and microcystin-YR were 0.1291 ㎍/L, 0.2776 ㎍/L, 0.3721 ㎍/L, and 0.0306 ㎍/L, respectively, in reservoir A and 0.3274 ㎍/L, 0.1495 ㎍/L, 0.2037 ㎍/L, and 0.0153 ㎍/L, respectively, in reservoir B.

• Journal of Korean Society on Water Environment
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• v.39 no.6
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• pp.451-464
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• 2023

Harmful cyanobacterial monitoring is time-consuming and requires skilled professionals. Recently, Phycocyanin, the accessory pigment unique to freshwater cyanobacteria, has been proposed as an indicator for the presence of cyanobacteria, with the advantage of rapid and simple measurement. The purpose of this research was to evaluate the correlation between the harmful cyanobacterial cell density and the concentration of phycocyanin and to consider how to use the real-time water quality monitoring system for algae bloom monitoring. In the downstream of the Nakdong River, Microcystis spp. showed maximum cell density (99 %) in harmful cyanobacteria (four target genera). A strong correlation between phycocyanin(measured in the laboratory) concentrations and harmful cyanobacterial cell density was observed (r = 0.90, p < 0.001), while a weaker relationship (r = 0.65, p < 0.001) resulted between chlorophyll a concentration and harmful cyanobacterial cell density. As a result of comparing the phycocyanin concentration (measured in submersible fluorescence sensor) and harmful cyanobacterial cell density, the error range increased as the number of cyanobacteria cells increased. Before opening the estuary bank, the diurnal variations of phycocyanin concentrations did not mix by depth, and in the case of the surface layer, a pattern of increase and decrease over time was shown. This study is the result of analysis when Microcystis spp. is dominant in downstream of Nakdong River in summer, therefore the correlation between the harmful cyanobacteria density and phycocyanin concentrations should be more generalized through spatio-temporal expansion.

• Journal of Korean Society on Water Environment
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• v.39 no.1
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• pp.20-29
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• 2023

This study analyzed the relationship between harmful cyanobacterial abundance and environmental factors in order to figure out the causes of the recent increase of cyanobacteria in Lake Dukdong from 2019 to 2021. Lake Dukdong, which is used as a drinking water source for Gyeongju City, has an algae alert system in place. Lake Dukdong has maintained good water quality, but algae alert level 1 (over 1,000 cells/mL) has been issued in recent years. As a result of Pearson correlation analysis (from May to Oct.), the cell density of Microcystis and Aphanizomenon, which form part of the most harmful cyanobacteria genus, were significantly positively correlated with the water temperature and water storage volume. T-test was performed to compare the data from 2016-2018 and 2019-2021 (from May to Oct.). The average density of harmful cyanobacteria cells increased about six-fold from 54 to 344 cells/mL. There were significant differences in water temperature, pH, total nitrogen (TN), total phosphorus (TP), TN/TP ratio, water storage volume, and cyanobacterial cell density. Water temperature increased from 19.2 to 22.8 ℃. TP concentration increased from 0.017 to 0.028 mg/L. The main cause of the recent increase of harmful cyanobacteria in Lake Dukdong is thought to be the increase in water temperature, TP concentration, and water storage volume from 2019 and 2021, resulting in more favorable conditions for cyanobacterial growth.

• Journal of Korean Society on Water Environment
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• v.27 no.4
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• pp.491-498
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• 2011

We investigated the ranges of total cellular microcystins content of cyanobacterial blooms collected in Korean lakes and rivers from 2005 to 2009. The amount and composition of microcystins of Korean cyanobacteria varied depending on the sampling water bodies and dominant cyanobacterial genera. Toxic cyanobacterial cell numbers equivalent to $1{\mu}g$ MCYSTs/L using total cellular microcystin content of Korean cyanobacteria were in the range of 2,348 to 66,980,638 cells/mL. Only four samples among forty nine samples showed less cell numbers than current criterion of Harmful Algae Alert System, 5,000 cells/mL indicating current criterion do not reflect properly the microcystins content of Korean cyanobacteria. Anabaena and Aphanizomenon spp. showed three to six times higher cell numbers equivalent to $1{\mu}g$ MCYSTs/L than Microcystis spp. To propose criteria of Harmful Algae Alert System for Korean toxic cyanobacteria, we calculated about 50% selective geometrical means of cyanobacterial cell numbers equivalent to $1{\mu}g$ MCYSTs/L in order of toxic content. The proposed criteria for Microcystis, Oscillatoria, Anabaena, and Aphanizomenon spp., are 10,000, 20,000, 40,000, and 80,000 cells/mL, respectively.

• Journal of Korea Water Resources Association
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• v.54 no.spc1
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• pp.1167-1181
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• 2021

In relation to the algae bloom, four types of blue-green algae that emit toxic substances are designated and managed as harmful Cyanobacteria, and prediction information using a physical model is being also published. However, as algae are living organisms, it is difficult to predict according to physical dynamics, and not easy to consider the effects of numerous factors such as weather, hydraulic, hydrology, and water quality. Therefore, a lot of researches on algal bloom prediction using machine learning have been recently conducted. In this study, the characteristic importance of water quality factors affecting the occurrence of Cyanobacteria harmful algal blooms (CyanoHABs) were analyzed using the random forest (RF) model for Bohyeonsan Dam and Yeongcheon Dam located in Yeongcheon-si, Gyeongsangbuk-do and also predicted the occurrence of harmful blue-green algae using the machine learning and deep learning models and evaluated their accuracy. The water temperature and total nitrogen (T-N) were found to be high in common, and the occurrence prediction of CyanoHABs using artificial neural network (ANN) also predicted the actual values closely, confirming that it can be used for the reservoirs that require the prediction of harmful cyanobacteria for algal management in the future.

• Journal of The Korean Society of Agricultural Engineers
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• v.58 no.2
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• pp.53-63
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• 2016

Monitoring of cyanobacteria bloom in reservoir systems is important for water managers responsible of water supply system. Cyanobacteria affect the taste and smell of water and pose considerable filtration problems at water use places. Harmful cyanobacteria bloom in reservoir have significant economic impacts. We develop a new method for estimating the cyanobacteria bloom using Landsat TM and ETM+ data. Developed model was calibrated and cross-validated with existing in situ measurements from Daecheong Reservoir's Water Quality Monitoring Program and Algae Alarm System. Measurements data of three stations taken from 2004 to 2012 were matched with radiometrically converted reflectance data from the Landsat TM and ETM+ sensor. Stepwise multiple linear regression was used to select wavelengths in the Landsat TM and ETM+ bands 1, 2 and 4 that were most significant for predicting cyanobacteria cell number and bio-volume. Based on statistical analysis, the linear models were that included visible band ratios slightly outperformed single band models. The final monitoring models captured the extents of cyanobacteria blooms throughout the 2004-2012 study period. The results serve as an added broad area monitoring tool for water resource managers and present new insight into the initiation and propagation of cyanobacteria blooms in Daecheong reservoir.

• Environmental Engineering Research
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• v.22 no.1
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• pp.1-11
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• 2017

One of the most threatening consequences of eutrophic freshwater reservoirs is algal blooming which typically occur after the long a mega drought or/and irregular rainfall under influence of climate change. The long-term experiences of chemical treatment are known as a most practical effort to reduce health concerns from human exposure of harmful cyanobacteria as well as to preserve ultimate freshwater resources. Even though these conventional chemical treatment methods do not completely solve the algal residue problem in water treatment plant or directly in the water bodies, they still have big advantages as fast and efficient removal process of cyanobacteria due to cheaper, easier to manage. This review summarizes their chemical treatment scenarios of the representative coagulants, pre-oxidants and algaecides composed to chemical compounds which immediately may help to manage severe cyanobacteria blooms in the summer seasons.

• Journal of Korean Society on Water Environment
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• v.40 no.3
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• pp.121-129
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• 2024

Harmful cyanobacterial blooms (HCBs) are caused by the rapid proliferation of cyanobacteria and are believed to be exacerbated by climate change. However, the extent to which HCBs will be stimulated in the future due to increased temperature remains uncertain. This study aims to predict the future occurrence of cyanobacteria in the Nakdong River, which has the highest incidence of HCBs in South Korea, based on temperature rise scenarios. Representative Concentration Pathways (RCPs) were used as the basis for these scenarios. Data-driven model simulations were conducted, and out of the four machine learning techniques tested (multiple linear regression, support vector regressor, decision tree, and random forest), the random forest model was selected for its relatively high prediction accuracy. The random forest model was used to predict the occurrence of cyanobacteria. The results of boxplot and time-series analyses showed that under the worst-case scenario (RCP8.5 (2100)), where temperature increases significantly, cyanobacterial abundance across all study areas was greatly stimulated. The study also found that the frequencies of HCB occurrences exceeding certain thresholds (100,000 and 1,000,000 cells/mL) increased under both the best-case scenario (RCP2.6 (2050)) and worst-case scenario (RCP8.5 (2100)). These findings suggest that the frequency of HCB occurrences surpassing a certain threshold level can serve as a useful diagnostic indicator of vulnerability to temperature increases caused by climate change. Additionally, this study highlights that water bodies currently susceptible to HCBs are likely to become even more vulnerable with climate change compared to those that are currently less susceptible.

• Journal of Korean Society on Water Environment
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• v.32 no.3
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• pp.261-270
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• 2016

We analyzed cyanobacterial community including akinete, resting cell, and benthic cyanobacteria in sediment of Bukhan, Namhan-River, Paldang-Lake, and Kyeongan-Stream and compared the physicochemical factors for water and pore water. We also performed cyanobacteria growth potential test through incubating sediment. As a result of physicochemical analysis, the concentrations of nutrients were similar for each depth of Bukhan-River. For Namhan-River and Lake Paldang sites, the concentrations of TP and DTN in bottom and deep water had higher levels. DTN in water body composed of NO3-N(73%) while DTN in pore water composed of NH3-N(77.8%). Benthic cyanobacteria in the sediment such as Oscillatoria tenuis, O. limosa, Phormidium tenue, Pseudanabaena limnetica, and Lyngbya sp. were dominant (between 0.0∼243.3×10³ cells/g, w/w). Cell densities of cyanobacteria in sediment depth of 0∼2 cm in most sites were higher compared to those in other depths. The cell density of cyanobacteria in sediment correlated with pH, conductivity, BOD5, TP, DTP, and chl. a. Increased phytoplankton and organic matters were found to be able to inhibit the growth of benthic cyanobacteria. Results of cyanobacteria growth potential test after incubating sediment revealed that harmful cyanobacteria (Anabaena, Aphanizomenon, Microcystis, and Oscillatoria) appeared at 7 days post culturing. Base on these results, the methods used in this study are considered to be able to determine the appearance of harmful cyanobacteria.