• ALGAE
• /
• v.20 no.2
• /
• pp.113-120
• /
• 2005

The freshwater blooms mainly blue-green algal blooms occur frequently in the lower Naktong River in summer, which provoke many socio-economical problems; therefore, the early detection of bloom events are demanding through the quantitative and qualitative analyses of blue green algal species. The in vivo fluorescence properties of cultured strains of Microcystis aeruginosa, M. viridis, M. wesenbergii, M. ichthyoblabe, Anabaena cylindrica, A. flos-aquae, and Synedra sp. were investigated. Wild phytoplankton communities of the lower Naktong River were also monitored at four stations in terms of their standing stocks, biomass and fluorescence properties compared with its absorption spectram. The 77K fluorescence emission spectra of each cultured strains normalized at 620 nm was very specific and enabled to detect of blue green algal biomass qualitatively and quantitatively. The relative chlorophyll a concentration determined by chlorophyll fluorescence analysis method showed significant relationship with chlorophyll a concentration determined by solvent extraction method ($R^2$ = 0.906), and the blue-green algal cell number determined by microscopic observation ($R^2$ = 0.588), which gives insight into applications to early detection of blue green algal bloom.

• Journal of Wetlands Research
• /
• v.26 no.3
• /
• pp.245-253
• /
• 2024

Blue-green algal bloom, or harmful algal bloom has a negative impact on the aquatic ecosystem and purified water supply system due to oxygen depletion in the water body, odor, and secretion of toxic substances in the freshwater ecosystem. This Blue-green algal bloom is expected to increase in intensity and frequency due to the increase in algae's residence time in the water body after the construction of the Nakdong River weir, as well as the increase in surface temperature due to climate change. In this study, in order to respond to the expected increase in green algae phenomenon, an algal bloom forecast system based on hydro-meteorological factors was presented for preemptive response before issuing a algal bloom warning. Through polyserial correlation analysis, the preceding influence periods of temperature and discharge according to the algal bloom forecast level were derived. Using the decision tree classification, a machine learning technique, Classification models for the algal bloom forecast levels based on temperature and discharge of the preceding period were derived. And a algal bloom forecast system based on hydro-meteorological factors was derived based on the results of the decision tree classification models. The proposed algae forecast system based on hydro-meteorological factors can be used as basic research for preemptive response before blue-green algal blooms.

• Korean Journal of Ecology and Environment
• /
• v.38 no.2 s.112
• /
• pp.217-224
• /
• 2005

This study was aimed to analyze the long-term fluctuation of water quality and phytoplankton dynamics of Paldang reservoir in Korea and to assess the relationship between algal bloom patterns and hydrological, limnological data. Diatoms in Paldang reservoir occurred continuously through the year. Blue- green algae occurred during the summer season (from June to Sept.), and the highest count was observed in July. Occurrence pattern of green algae was similar to that of blue-green algae. The rest of algae contained a lot of Cryptomonas spp. whose concentration was high from May to Aug. Dominant algal genera (>>7,000 cells $mL^{-1}$) in Paldang reservoir were Aulacoseira, Cyclotella, Microcystis, and Cryptomonas spp. Microcystis and Anabaena occurred during the summer season. Many different green algal genera were found in Paldang reservoir but their abundances were very low. There were some significant correlations (r>0.3, p<0.05) between algal taxa and water quality; diatoms and water temperature, TP:blue-green algae and water temperature, pH, DO saturation, COD, TP; green algae and water temperature, pH, DO saturation, COD, SS, TP. Furthermore, algal genera and water quality was significantly correlated (r>0.3, p<0.05) ; Aulacoseira and TN, TP; Anabaena and water temperature, DO saturation, COD, TP : Microcystisand water temperature, pH, DO saturation, TP; Coelastrum and COD, SS; Scenedesmus and water temperature, COD, TN, TP; Cryptomonas and DO saturation, TN. In Paldang reservoir, the water temperature had relatively big effect on blue-green algal bloom that was also dependant upon its hydrologic condition.

• Korean Journal of Ecology and Environment
• /
• v.47 no.1
• /
• pp.1-12
• /
• 2014

Some blue-green algal species such as those in the genus Anabaena causing severe algal blooms can produce akinetes, resting spores, in aquatic ecosystems. Germinated akinetes staying in the sediment as "seed banks" grow into vegetative cells under favorable conditions of light intensity, nutrient, and temperature. Therefore, akinete plays an important role in forming the nuisance bloom. However, little information is available in the ecological study of akinetes compared to that of vegetative cells in Korea. This review reports ecological and physiological characteristics of akinetes, especially of the blue-green algal genus Anabaena. We also suggest the feasible area of akinetes in the freshwater ecosystems. We expect that the suggested studies associated with akinetes will contribute to further understanding the life cycle and ecology of Anabaena and other algae.

• Journal of Environmental Science International
• /
• v.9 no.3
• /
• pp.267-273
• /
• 2000

In order to understand the impact for decomposition of blue-green algae Microcystis on water quality, the algae were cultivated with collection of natural population during approximately one month, when water-bloom of Microcystis dominated at August 31, 1999 in the lower part of the Okchon Stream. The enrichment of inorganic NㆍP nutrients didn't in algal assay and the effect of Microcystis on water duality was assessed from the variation of nutrients by algal senescence. Microcystis population seemed to play a temporary role of sink for nutrients in the water body. Initial algal density of Microcystis was 2.3×10/sup 6/ cells/㎖. When Microcystis population died out under light condition, algal NㆍP nutrients between 9∼12 days affected to increase of biomass after reuse by other algal growth as soon as release to the ambient water. However, cellular nutrients under dark condition were almost moved into the water during algal cultivation. NH₄, NO₃ and SRP concentration were highly increased with 160, 17 and 79 folds, respectively relative to the early. As a result, the senescence of Microcystis population seemed to be an important biological factor in which cause more eutrophy and increase of explosive algal development by a lot of nutrients transfer to water body. There are significantly observed an effort of reduce for production of inner organic matters such a phytoplankton as well as load pollutants from watershed in side of the water quality management of reservoir.

• Korean Journal of Environmental Biology
• /
• v.31 no.4
• /
• pp.233-242
• /
• 2013

Cyanobacteria (blue-green algae) are not only the first oxygenic organisms on earth but also the foremost primary producers in aquatic environment. Massive growth of cyanobacteria, in eutrophic waters, usually changes the water colour to green and is called as algal (cyanobacterial) bloom or green tide. Cyanobacterial blooms are a result of high levels of primary production by certain species such as Microcystis sp., Anabaena sp., Oscillatoria sp., Aphanizomenon sp. and Phormidium sp. These cyanobacterial species can produce hepatotoxins or neurotoxins as well as malodorous compounds like geosmin and 2-methylisoborneol (MIB). In order to solve the nationwide problem of hazardous cyanobacterial blooms in Korea, the following technically and strategically sound approaches need to be developed. 1) As a long-term strategy, reduction of the nutrients such as phosphorus and nitrogen in our water bodies to below permitted levels. 2) As a short term strategy, field application of combination of already established bloom remediation techniques. 3) Development of emerging convergence technologies based on information and communication technology (ICT), environmental technology (ET) and biotechnology (BT). 4) Finally, strengthening education and creating awareness among students, public and industry for effective reduction of pollution discharge. Considering their ecological roles, a complete elimination of cyanobacteria is not desirable. Hence a holistic approach mentioned above in combination to addressing the issue from a social perspective with cooperation from public, government, industry, academic and research institutions is more pragmatic and desirable management strategy.

• Journal of Korean Society on Water Environment
• /
• v.31 no.2
• /
• pp.159-165
• /
• 2015

The organic matter sources of phytoplankton and related environmental factors influencing algal bloom in Paldang reservoir were studied using nitrogen and carbon isotope ratio(${\delta}^{15}N$, ${\delta}^{13}C$). Phytoplankton samples for stable isotope analysis were collected from four points in reservoir using a plankton net. Physicochemical water quality, algal taxa and hydrological data were collected from published monitoring material. Phytoplankton samples were analyzed by IRMS. CN ratio of each sample was very similar to that of phytoplankton from literature cited. ${\delta}^{15}N$ of each sample was decreased during July. Mixing and dilution of nitrogen sources due to increment of influx by concentrated rainfall were considered as the main reason for the decline of ${\delta}^{15}N$. Based on analyzed ${\delta}^{15}N$ value of each sample, nitrogen source of Bughan river sample was presumed to come from soil. The nitrogen sources of Namhan river and Kyeongan stream samples seemed to be sewage or animal waste. Low ${\delta}^{15}N$ value in August (2012) seemed to be influenced by isotope fractionation due to the blooming of nitrogen-fixation blue-green algae (Anabaena spp.). Variation in ${\delta}^{15}N$ values particularly by blue-green algal bloom was considered the important factor for estimating the organic matter sources of phytoplankton.

• Korean Journal of Ecology and Environment
• /
• v.49 no.4
• /
• pp.320-333
• /
• 2016

This study was carried out to elucidate the development of unprecedented water-bloom caused by a single species of colonial green algae Eudorina elegans in the upstream area of the Seungchon weir located in the Yeongsan River from late April to May 2013. The Yeongsan River is typically regulated system and the waterbody is seriously enriched by both external and internal sources of nutrients. Seasonal algal outbreaks were highly probable due to various potential factors, such as the excessive nutrients contained in treated wastewater, slow current, high irradiation and temperature, in diatom (winter), green algae (spring) and bluegreen algae (summer). Spring green-tide was attributed to E. elegans with level up to $1,000mg\;m^{-3}$(>$50{\times}10^4cells\;mL^{-1}$). The bloom was exploded in the initial period of the algal development and after then gradually diminished with transporting to the downstream by the intermittent rainfall, resulting in rapid expansion of the distribution range. Although the pulsed-flows by the weir manipulation was applied to control algal bloom, they were not the countermeasures to solve the underlying problem, but rather there still was a remaining problem related to the impact of pulsed-flows on the downstream. The green-tide of E. elegans in this particular region of the Yeongsan River revealed the blooming characteristics of a colonial motile microalga, and fate of vanishing away by the succeeding episodic events of mesoscale rainfall. We believe that the results of the present study contribute to limno-ecological understanding of the green-tide caused by blue-green algae in the four major rivers, Korea.

• Korean Journal of Ecology and Environment
• /
• v.34 no.2 s.94
• /
• pp.90-97
• /
• 2001

The seasonal changes in phytoplankton standing crops, species composition, dominant species, species diversity and physico-chemical characteristics in Woopo and Mokpo swamps were studied from January to December, 1998. Phytoplankton of a total 353 taxa were identified, the composition of phytoplankton community was characetrized by green algae and diatoms and quantity composition of standing crops was dominated by green alga Oscillatoria sp. was especially prominent. The standing crops varied from 108 cells/ml and 118 cells/ml to 19,178 cells and 38,393 cells/ml in Woopo and Mokpo swamps, respectively. The maximum algal density was observed in November, Micractinium pusillum and Oscillatoria sp. usually contributed 83.2% to total cell numbers in Woopo swamp. However, the maximum density occurred in May when Oscillatoria sp. formed bloom in Mokpo swamp. The low species diversity of the phytoplankton coincided with maximum standing crops of the filamentous blue-green alga Oscillatoria sp. and green alga Micractinium pusillum in May and November.

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