• Journal of Korean Society of Water and Wastewater
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• v.32 no.6
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• pp.573-581
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• 2018

The purpose of this study is to evaluate the fixed wing type domestic UAV for monitoring of algae bloom in aquatic environment. The UAV used in this study is operated automatically in-flight using an automatic navigation device, and flies along a path targeting preconfigured GPS coordinates of desired measurement sites input by a flight path controller. The sensors used in this study were Sequoia multi-spectral cameras. The photographed images were processed using orthomosaics, georeferenced digital surface models, and 3D mapping software such as Pix4D. In this study, NDVI(Normalized distribution vegetation index) was used for estimating the concentration of chlorophyll-a in river. Based on the NDVI analysis, the distribution areas of chlorophyll-a could be analyzed. The UAV image was compared with a airborne image at a similar time and place. UAV images were found to be effective for monitoring of chlorophyll-a in river.

• Journal of Environmental Science International
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• v.26 no.5
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• pp.685-689
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• 2017

Aquatic plants serve the crucial function of helping to balance water reservoir ecosystem, as they filter and remove major minerals required for algal growth such as nitrogen, ammonia, and nitrates. Aquatic plants provide food, shade, and protection for the aquatic biome in and around the reservoir. Thus, it is important to accurately determine the existence and areal extent of the aquatic plants. In the present study drone-based facilities were used for this purpose. In the Muncheon water reservoir, Gyeongbuk, the Normalized Difference Vegetation Index (NDVI) and Surface Algal Bloom Index (SABI) were used to determine the existence status of the aquatic plants. The data so obtained exhibited reasonable accuracy; drone-based facilities can be used in future to identify the areal extent of aquatic plants.

• Fisheries and Aquatic Sciences
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• v.11 no.1
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• pp.50-60
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• 2008

Harmful algal blooms (HABs) of Cochlodinium polykrikoides frequently occur around the South Sea of Korea, causing. economic losses in coastal breeding grounds. HAB outbreak scale usually changes each year depending on physical, biological and environmental conditions. Relatively large-scale HABs occurred in 1995, 1997, 1999, 2001, 2002 and 2003 with respect to spatial scale, duration and maximum density. Considering HAB scale and temperature distributions around the South Sea, we found that low coastal temperatures in August correspond to enormous HAB outbreaks. Cold waters created by coastal upwellings around the southeastern coast of Korea also corresponded to these outbreaks. Serial oceanographic investigations in August in the South Sea revealed that sea surface temperature anomalies had distinctively negative values when large-scale HAB outbreaks appeared. With regard to temperature differences between the surface and the 30-m layer, there was a tendency for large-scale outbreaks when temperature gradients around the seasonal thermocline weakened.

• Korean Journal of Ecology and Environment
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• v.46 no.1
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• pp.1-9
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• 2013

Algal blooms in potable water supplies are becoming an increasingly prevalent and serious water quality problem around the world. In addition to precipitating taste and odor problems, blooms damage the environment, and some classes like cyanobacteria (blue-green algae) release toxins that can threaten human health, even causing death. There is a recognized need in the water industry for models that can accurately forecast in real-time algal bloom events for planning and mitigation purposes. In this study, using data for an interconnected system of rivers and reservoirs operated by a New Jersey water utility, various ANN models, including both discrete prediction and classification models, were developed and tested for forecasting counts of three different algal classes for one-week and two-weeks ahead periods. Predictor model inputs included physical, meteorological, chemical, and biological variables, and two different temporal schemes for processing inputs relative to the prediction event were used. Despite relatively limited historical data, the discrete prediction ANN models generally performed well during validation, achieving relatively high correlation coefficients, and often predicting the formation and dissipation of high algae count periods. The ANN classification models also performed well, with average classification percentages averaging 94 percent accuracy. Despite relatively limited data events, this study demonstrates that with adequate data collection, both in terms of the number of historical events and availability of important predictor variables, ANNs can provide accurate real-time forecasts of algal population counts, as well as foster increased understanding of important cause and effect relationships, which can be used to both improve monitoring programs and forecasting efforts.

• Journal of Korean Society on Water Environment
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• v.30 no.5
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• pp.539-548
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• 2014

This study was carried out to investigate algal community structures and their correlations with environmental factors on five weir areas in the Nakdong River, South Korea. Water qualities, hydrodynamics, meteorological conditions and algal species compositions were observed in studied sites from May 2010 to Dec. 2013. Results showed that average total phosphorus concentration of 2013 was decreased by 52.4% in comparing with that from 2010 to 2011. Chlorophyll.a concentrations were positive significant with water temperature, pH, total phosphorus and total nitrogen, but is not significant with turbidity and suspended solids. Seasonal successions of algae were observed that Stephanodiscus sp. was dominant species with 65.3% of dominant frequency in studied site. Large algal biomass of the low temperature-adapted diatoms were observed during temperature range of $4{\sim}9^{\circ}C$, but large cyanobacterial biomass mainly during high temperature period ranged from $22^{\circ}C$ to $32^{\circ}C$. Microcystis sp. dominated during high water temperature in summer. The yearly correlations of algal biomass with accumulated solar radiations were not significant but seasonal correlations of summer from June to August were significant with correlation coefficient 0.33 (p<0.05). There were not significant correlations between turbidities and algal biomass. Turbidity and suspended solids concentrations were not significant correlation with algal biomass. According to the results, algal communities had strong correlation with water temperature and had partially correlation with solar radiation. For an effective management of algal blooms, water managers should survey with more long-term monitoring of various environmental factors and algal communities.

• Journal of Korea Water Resources Association
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• v.55 no.8
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• pp.577-588
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• 2022

This study aims to identify the limiting nutrient for algal growth in the Geum River and the significant pollutant sources from the tributaries affecting the water quality and to provide a management alternative for an improvement of water quality. An eight-year of daily data (2013~2020) were collected from the Water Environment Information System (water.nier.go.kr) and Water Resources Management Information System (wamis.go.kr). 14 water quality variables were analyzed at five water quality monitoring stations in the Geum River (WQ1-WQ5). In the Geum River, the water quality variables, especially Chl-a vary greatly in downstream of the river. In the open weir gate operation, TP (total phosphorus) and water temperature greatly influence the growth of algae in downstream of the river. A correlation analysis was used to identify the relationship between variables and investigate the factor affecting algal growth in the Geum River. At the downstream station (WQ5), TP and Temp have shown a strong correlation with Chl-a, indicating they significantly influence the algal bloom. The principal component analysis (PCA) was applied to identify and prioritize the major pollutant sources of the two major tributaries of the river, Gab-cheon and Miho-cheon. PCA identifies three major pollutant sources for Gab-cheon and Miho-cheon, respectively. For Gab-cheon, wastewater treatment plant, urban, and agricultural pollutions pollution are identified as significant pollutant sources. For Miho-cheon, agricultural, urban, and forest land are identified as major pollutant sources. PCA seems to be effective in identifying water pollutant sources for the Geum River and its tributaries in detail and thus can be used to develop water quality management strategies.

• 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.

• Korean Journal of Microbiology
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• v.42 no.1
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• pp.7-11
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• 2006

To see effect of marine rock powder and fungal culture supernatant, we analyzed the biodegradation rates of harmful marine dinoflagellate, Heterosigma akashiwo and Prorocentrum minimum for developing the effective control methodology of algal bloom. Relatively low removal rates were observed in the treatment of marine rock powder or buffer solution alone. However, the lysis of H. akashiwo and P. minimum was enhanced in the combined treatments of marine rock powder with fungal supernatant. The effective concentration and exposure time of fungal supernatant for the lysis of H. akashiwo and P. minimum were 5 ml/l and 30 minutes, respectively. These results suggest that the fungal supernatant may be a biocontrol agent for the control of algal blooms in seawater.

• Korean Journal of Ecology and Environment
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• v.51 no.1
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• pp.16-28
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• 2018

Although physiological and ecological characteristics of cyanobacteria have been studied extensively for decades, unknown areas still remain greater than the already known. Recently, the development of omics techniques based on molecular biology has made it possible to view the ecosystem from a new and holistic perspective. The molecular mechanism of toxin production is being widely investigated, by comparative genomics and the transcriptomic studies. Biological interaction between bacteria and cyanobacteria is also explored: how their interactions and genetic biodiversity change depending on seasons and environmental factors, and how these interactions finally affect each component of ecosystem. Bioinformatics techniques have combined with ecoinformatics and omics data, enabling us to understand the underlying complex mechanisms of ecosystems. Particularly omics started to provide a whole picture of biological responses, occurring from all layers of hierarchical processes from DNA to metabolites. The expectation is growing further that algal blooms could be controlled more effectively in the near future. And an important insight for the successful bloom control would come from a novel blueprint drawn by omics studies.

• Journal of environmental and Sanitary engineering
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• v.24 no.2
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• pp.40-48
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• 2009

Unusual bloom of toxic cyanobacteria in water bodies have drawn attention of environmentalists world over. Major bloom of Anabaena, Microcystis in water storage reservoir, rivers and lake leading to adverse health effects have been reported from Australia, England and many part of the world. These cyanobacterial cells can release intercellular matter like toxin in water and these intercellular matter can increase the concentration of organic matter. Cellysis can occur when algal cells meet the disinfectants like chlorine in water treatment plant and the resultant rising up of DOC(Dissolved Organic Carbon) or TOC(Total Organic Carbon) can increase the formation of disinfection by products. Disinfectants that kill microorganisms react with the organic or inorganic matter in raw water. In general disinfectants oxidize the matter in raw water and the resultant products can be harmful to human. There are always conflict about which is more important, disinfection or minimizing disinfection by products. The best treatment process for raw water is the process of the lowest disinfection by products and also the the lowest microorganism. In this study the cultured cells, Microcytis Aeruginosa(MA), Anabaena Flos-aquae(AF), Anabaena Cylindrica(AC), and the cells obtained in Daechung Dam(DC) whose dominant species was Anabaena Cylindrica were subjected to chlorination. Chlorination oxidizes inorganic and organic compounds and destruct live cells in raw water. Chloroform was analyzed for the cultured cells which were treated with $20mg/\ell$ dose of chlorine. In general chloroform is easily formed when dissolved organic matter react with chlorine. The cultured cells contributes the concentration of dissolved organic carbon and also that of total organic carbon which might be potent precusors of chloroform formed. The correlations of the concentration of chloroform, DOC and TOC were investigate in this study.