• Proceedings of the Korea Water Resources Association Conference
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• 2010.05a
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• pp.957-961
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• 2010

Multivariate statistical approaches to classify sampling sites with measuring their similarity by water quality data. For empirical study, data of two years at the 9 sampling sites with the combination of 2 depth levels and 7 important variables related to water quality is collected in reservoir. The similarity among sampling sites is measured with Euclidean distances of water quality related variables and they are classified by hierarchical clustering method. The clustered sites are discussed with principal component variables in the view of the geographical characteristics of them and reducing the number of measuring sites. Nine sampling sites are clustered as follows; One cluster of 5, 6, and 7 sampling sites shows the characteristic of low water depth and main stream of water. The sites of 2 and 4 are clustered into the same group by characteristics of hydraulics which come from that of main stream. But their changing pattern of water quality looks like different since the site of 2 is near to dam. The sampling sites of 3, 8, and 9 are individually positioned due to the different tributary.

• Journal of Environmental Science International
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• v.25 no.11
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• pp.1511-1519
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• 2016

Jeju Island relies on subterranean water for over 98% of its water resources, and it is therefore necessary to continue to perform studies on drought due to climate changes. In this study, the representative standardized precipitation index (SPI) is classified by various criteria, and the spatial characteristics and applicability of drought in Jeju Island are evaluated from the results. As the result of calculating SPI of 4 weather stations (SPI 3, 6, 9, 12), SPI 12 was found to be relatively simple compared to SPI 6. Also, it was verified that the fluctuation of SPI was greater fot short-term data, and that long-term data was relatively more useful for judging extreme drought. Cluster analysis was performed using the K-means technique, with two variables extracted as the result of factor analysis, and the clustering was terminated with seven-time repeated calculations, and eventually two clusters were formed.

• Journal of Marine Bioscience and Biotechnology
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• v.8 no.2
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• pp.54-66
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• 2016

Productivity of Saccharina japonica was evaluated by water layers in Gijang and Wando sea area to find the suitable farming areas for mass production of biomass. For this, S. japonica was cultivated at various depths (0.5, 1, 2, 3 m), respectively. As the result, the growths in Gijang were 225.1-261.5 cm in length, 18.5-21.3 cm in widths, 396.0-537.7 g in weights, 14.3-17.8 kg/cluster in biomass, and those in Wando were 332.0-435.7 cm in lengths, 24.6-32.5 cm in widths, 766.0-1,232.9 g in weights, 16.4-24.3 kg/cluster in biomass. It showed that the growths of blades in Wando were faster than those in Gijang. The growth rates of blades by the depths were faster at 0.5-1 m depth from January to June. After June, however, as the growth rates of blades were lower than the shedding rates of blades, it showed that the growth of S. japonica decreased at all depth conditions except 2 m depth. Productivity of S. japonica was better in Wando which is lower in the water temperature and nutrients than Gijang.

• Ocean and Polar Research
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• v.26 no.1
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• pp.65-75
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• 2004

In order to understand the water masses and their distribution in the eastern Yellow Sea from winter to spring, a cluster analysis was applied to the temperature and salinity data of Korea Oceanographic Data Center from 1970 to 1990. From December to April, Yellow Sea Cold Water (YSCW) dominates the eastern Yellow Sea, whereas Eastern Yellow Sea Mixed Water (MW) and Yellow Sea Warm Water (YSWW) are found in the southern part of the eastern Yellow Sea. MW appears at the frontal region around $34^{\circ}N$ between YSCW in the north and YSWW in the south. On the other hand, Tshushima Warm Water (TWW) is found around Jeju Island and the South Sea of Korea. These water masses are relatively well-mixed throughout the water column due to the winter monsoon. However, the water column begins to be stratified in spring due to increased solar heating, the diminishing winds and fresh water discharge, and the water masses in June may be separated into surface, intermediate and bottom layers of the water column. YSWW advances northwestward from December to February and retreats southeastward from February to April. This suggests a periodic movement of water masses in the southern part of the eastern Yellow Sea from winter to spring. YSWW may continue to move eastward with the prevailing eastward current to the South Sea from April to June. Also, the front relaxes in June, but the mixed water advances to the north, increasing salinity. The salinity is also higher in the nearshore region than offshore. This indicates an influx of oceanic water to the north in the nearshore region of the eastern Yellow Sea in spring in the form of mixed water.

• Journal of Environmental Science International
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• v.16 no.12
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• pp.1411-1424
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• 2007

Long-term trends and distribution patterns of water quality were investigated in the Asan coastal areas of Yellow Sea, Korea from 1975 to 2005. Water samples were collected at 3 stations and physicochemical parameters were analyzed including water temperature, salinity, suspended solids(SS), chemical oxygen demand(COD), dissolved oxygen(DO) and nutrients. Spatial distribution patterns were not clear among stations but the seasonal variations were distinct except COD, SS and nitrate. The trend analysis by principal component analysis(PCA) during twenty years revealed the significant variations in water quality in the study area, Annual water qualities were clearly discriminated into 4 clusters by PCA; year cluster 1988-1991, 1994-1997, and 1992-1993/1998-2005. By this multi-variate analysis we can summarize the annual trends as the followings; salinity, suspended solids and dissolved oxygen tended to increase from late 1980's, increased pH and COD from 1992, and decreased salinity and increased nitrogen and COD from 1990 due to the runoff frow agricultural lands causing eutrophication.

• Proceedings of the Korea Water Resources Association Conference
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• 2004.05b
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• pp.937-941
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• 2004

삽교호유역에 위치한 19개 수질관측지점에서 측정된 월별수질자료를 이용하여 수질관측지점을 2개에서 7개의 수질특성으로 분류하였으며, 그에 따른 수질요인분석을 실시하였다. 군집분석결과 삽교호유역의 각 하천은 개개의 수질특성을 보이고 있으며, 삽교호, 삽교천, 무한천 및 곡교천의 4개 그룹으로 나눌 수가 있었다. 수질분석결과에 의하면 삽교호에서는 부유물질의 농도가 다른 하천보다 높았는데 이는 하천으로부터 유입되는 풍부한 영양염에 의한 식물플랑크톤의 생물량 증가에 따른 것으로 사료된다. 또한 곡교천의 수질은 다른 하천에 비해 생화학적산소요구량은 $3.5\~4.8$배, 화학적산소요구량은 $1.7\~2.5$배 높았으며, 전반적으로 삽교호 유역의 수질은 부영양상대를 훨씬 초과하였다. 요인분석결과 삽교천과 무한천은 농경지와 주거지에 의한 수질요인이 지배적이었고, 곡교천은 천안도시지역으로부터 유입되는 과다한 유기물유입과 상류에 위치한 하수 처리장의 영향을 복합적으로 받고 있는 것으로 사료된다. 삽교호의 수질은 삽교천과 무한천 및 곡교천에서 높은 부하를 보인 인자가 주된 오염요인으로 나타났다.

• The Korean Journal of Ecology
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• v.21 no.3
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• pp.283-290
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• 1998

The vegetation pattern of Mt. Odae based on the soil humidity gradient showed 3 types: (1) the forest of Pinus densiflora under the mesic or xeric conditions of the low altitudinal area, (2) the forest of Acer including A. mono, A. pseudo-sieboldianum and Tilia amurensis under the submesic or subxeric conditions and (3) the forest of Quercus including Q. mongolica of the higher elevational area and Q. variabilis of the lower elevational area under the xeric condition. Water content, organic matter and total nitrogen of soil were relatively low in Pinus densiflora and Quercus variabilis communities while they were relatively high in Betula platyphylla var. japonica and Quercus mongolica communities. According to the result of cluster analysis based on similarity indices of the communities, the proposed successional sere in the forest vegetation of Mt. Odae was as follows. P. densiflora community $\longrightarrow$ P. densiflore + Q. mongolica community $\longrightarrow$ Q. mongolica + A. pseudo-sieboldianum community. P. densiflora community $\longrightarrow$ P. densiflora + Q. variabilis community $\longrightarrow$ Q. variabilis community $\longrightarrow$ Q. mongolica + Q. variabilis community $\longrightarrow$ Q. mongolica + A. pseudo-sieboldianum community.

• Journal of Environmental Impact Assessment
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• v.18 no.6
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• pp.401-409
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• 2009

Multivariate statistical approaches to classify sampling sites with measuring their similarity by water quality data and understand the characteristics of classified clusters have been discussed for the optimal water quality monitering network. For empirical study, data of two years (2005, 2006) at the 9 sampling sites with the combination of 2 depth levels and 7 important variables related to water quality is collected in Yongdam reservoir. The similarity among sampling sites is measured with Euclidean distances of water quality related variables and they are classified by hierarchical clustering method. The clustered sites are discussed with principal component variables in the view of the geographical characteristics of them and reducing the number of measuring sites. Nine sampling sites are clustered as follows; One cluster of 5, 6, and 7 sampling sites shows the characteristic of low water depth and main stream of water. The sites of 2 and 4 are clustered into the same group by characteristics of hydraulics which come from that of main stream. But their changing pattern of water quality looks like different since the site of 2 is near to dam. The sampling sites of 3, 8, and 9 are individually positioned due to the different tributary.

• Economic and Environmental Geology
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• v.36 no.6
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• pp.415-429
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• 2003

This study was objected to identify the difference of water quality and the characteristics of water contamination in adjacent bed-rock areas of Upper Hwajeonni and Guryongsan Formations in Miwon, Choongchungbuk-do, Korea. Water samples showed mainly (Ca, Mg)-$HCO_3$ type in Upper Hawjeonni Formation and (Ca, Mg)-$SO_4$ and (Ca, Mg)-$HCO_3$ types in Guryongsan Formation indicating the enrichment of $SO_4$ in major compositions. Groundwater quality could be divided into two groups based on the major weathering processes, implied by the ratio of bicarbonate to silica. Carbonate-silicate weathering predominates in Upper Hwajeonni Formation, and silicate weathering in Guryongsan Formation. Stream-water quality also appeared to be controlled by water-rock interaction. Cluster analysis identified three groups of groundwater and four groups of stream-water with distinctive geochemical characteristics. The results of factor analysis indicated that the levels of each chemical constituent in water samples derived from both natural weathering reactions and anthropogenic contamination sources. To delineate the pollution potential of water resources, Modified Pollution Index(M.P.I.) was developed. M.P.I. scores of water samples ranged from -0.08 to 0.18, with mostly positive along the rock quarry in Guryongsan Formation areas. M.P.I. scores appeared to be a useful predictor of metal contamination of water resources.

• Journal of Korea Water Resources Association
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• v.47 no.4
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• pp.385-396
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• 2014

Lately, more frequent typhoons cause extensive flood and wind damage throughout the summer season. In this respect, this study aims to develop a probabilistic clustering model that uses both typhoon genesis location and trajectories. The proposed model was applied to the 197 typhoon events that made landfall in the Korean peninsula from 1951 to 2012. We evaluate the performance of the proposed clustering model through a simulation study based on synthetic typhoon trajectories. The seven distinguished clusters for typhoons affecting Korean peninsula were identified. It was found that most of typhoon genesis originated from a remote position ($10^{\circ}{\sim}20^{\circ}N$, $120^{\circ}{\sim}150^{\circ}E$) near the Equator. Cluster, type B can be regarded as a major track due to the fact that its frequency is approximately about 25.4% out of 197 events and its direct association with strong positive rainfall anomalies.