• Ocean and Polar Research
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• v.39 no.1
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• pp.35-43
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• 2017

Concentrations of dissolved organic carbon (DOC), dissolved organic nitrogen (DON), dissolved organic phosphate (DOP), and colored dissolved organic matter (CDOM) were measured in the coastal sea off inland aqua farms in northeastern Jeju Island in summer 2015. The highest concentrations of DOC, DON, and DOP were revealed in the surface water off Hado-ri where the lowest salinity conditions prevailed (31.6). The concentrations of DOC, DON, and DOP in the surface water were lower in the inner stations (SH1-1, 1-2, and 1-3) near the aqua farms of the Haengwon-ri than in the outer stations. The concentrations of DOC, DON, and DOP negatively correlated with salinity. These results indicate that the contribution of dissolved organic matter (DOM) from the aqua farms seems to be not significant. On the other hand, the higher concentrations of DON and DOP in the inner stations of Hado-ri (HD 1-1) seem to be attributed to excrement of migrating birds. The three components of CDOM (T, M, and C peaks) showed no relationship with salinity, perhaps due to various in situ productions by marine organisms and decomposition by ultraviolet radiation. The observed lower C:M ratio, an indicator of terrestrial source, and the higher biological index (BIX) of CDOM in the station off Hado-ri indicate that DOM is produced mainly by biological activity. Based on the higher humification index (HIX) of CDOM and the higher DOC:DON ratio off Haengwon-ri, refractory DOM in the inland aqua farms is likely transported to the coastal sea.

• Ocean and Polar Research
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• v.40 no.2
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• pp.77-85
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• 2018

We observed the concentrations of Dissolved Organic Carbon (DOC) and Colored Dissolved Organic Matter (CDOM) in coastal seawater and groundwater around a volcanic island, Jeju, Korea. The sampling of surface seawater and coastal groundwater was conducted in Woljeongri, Pyoseon, and Kwakgi beaches, in three sampling campaigns (June, July, and October 2016). The concentrations of DOC in groundwater were relatively higher in June and October than in July. Salinity and DOC concentrations in the coastal groundwater of Woljeongri and Pyoseon beaches did not show a marked relationship, whereas those in Kwakgi beach showed a good positive correlation (July: $R^2=0.64$, P < 0.01; October: $R^2=0.95$, P < 0.01). In addition, the concentrations of CDOM (C and M peaks) in the groundwater of Woljeongri and Pyoseon beaches, where saline groundwater discharge dominates, were relatively higher than those of Kwakgi beach, where fresh groundwater discharge dominates. The relatively higher DOC concentrations in the coastal groundwater of Woljeongri and Pyoseon, with higher CDOM concentrations, seem to be mainly from anthropogenic sources such as local pollution sources (i.e., aquaculture wastewater or domestic sewage). In order to understand the behavior of DOC in the coastal groundwater of a volcanic island, extensive studies are necessary in the future over a larger-area and greater time-scales using various isotopic tracers.

• Korean Journal of Remote Sensing
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• v.28 no.4
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• pp.421-434
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• 2012

Colored Dissolved Organic Matter (CDOM) is one of the important components of optical properties of seawater to determine ecosystem dynamics in a given marine area. The optical characteristics of CDOM may depend on the various ecosystem and environmental variables in the sea and those variables may vary region to region. Therefore, the retrieval algorithm for determining light absorption coefficient of CDOM ($a_{CDOM}$) using satellite remote sensing reflectance ($R_{rs}$) developed from other region may not be directly applicable to the other region, and it must be validated using an in-situ ground-truth observation. We have tested 6 known CDOM algorithms (three Semi-analytical and three Empirical CDOM algorithms) developed from other regions of the world ocean with laboratory determined in-situ values for the East Sea using field data collected during seven oceanographic cruises in the period of 2009~2011. Our field measurements extended from the coastal waters to the open oceanic type CASE-1 Waters. Our study showed that Quasi-Analytical Algorithm (QAA_v5) derived $a_{CDOM}$(412) appears to match in-situ $a_{CDOM}$(412) values statistically. Semi-analytical algorithms appeared to underestimate and empirical ones overestimated $a_{CDOM}$ in the East Sea. $a_{CDOM}$(412) value was found to be relatively high in the relatively high satellite derived-chlorophyll-a area. $a_{CDOM}$(412) value appears to be influenced by the amount of chlorophyll-a in seawater. The outcome of this work may be referenced to develop $a_{CDOM}$ algorithm for the new Korean Geostationary Ocean Color Imager (GOCI).

• Ocean and Polar Research
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• v.45 no.3
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• pp.103-111
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• 2023

To evaluate the impact of effluents from land-based fish farms on the coastal ocean of Wando, Korea, we analyzed inorganic nutrients, particulate organic carbon (POC), dissolved organic carbon (DOC), and colored dissolved organic matter (CDOM) in the effluent and influent of land-based fish farms during the summer (July) of 2021. The average concentrations of nutrients (Dissolved inorganic nitrogen, phosphorus, and silicate; DIN, DIP, and DSi, respectively) in the effluents of this study area were 17±3.7 μM, 1.4±0.7 μM, and 14±1.6 μM, respectively. The average concentrations of POC and DOC were 37±22 μM and 81±13 μM, respectively, with POC accounting for about 30% for total organic carbon in effluents. The Reduced Dissolved Inorganic Nitrogen/Total Dissolved Inorganic Nitrogen ratio (0.7), potential short-period index, indicates that the discharge of nutrients excreted by the fish and unconsumed feed into coastal water results in such nutrients being deposited and accumulated in the sediment. Subsequently, this continuous accumulation triggers the release of ammonium ions during organic matter decomposition, and the ammonium-enriched waters that encroach on fish farms as influent seem to be due to the diffusion of high concentrations of ammonium from bottom sediment. Furthermore, we used fluorescence indices to examine the characteristics of organic matter sources, obtaining mean values of 1.54±0.19, 1.06±0.06, and 1.56±0.06 for the humification index, biological index, and fluorescence index, respectively, in the effluent. These results indicate that the organic matters had an autochthonous origin that resulted from microbial decomposition, and such organic matters were rapidly generated and removed by biological activity, likely supplied from the sediment. Our results suggest that the effluent from land-based fish farms could be a potential source of deoxygenation occurrence in coastal areas.

• Journal of the korean society of oceanography
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• v.37 no.3
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• pp.154-159
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• 2002

Satellite remote sensing technology for ocean observation has evolved considerably in these last twenty years. Ocean color is one of the most important parameters of ocean satellite measurements. This paper describes a remote sensing of ocean color data project - Asian I-Lac Project; it also introduces several case studies using satellite images in the Asian waters. The Asian waters are related to about 30 Asian countries, representing about 60% of the world population. The project aims at generating long-term time series images (planned for 10 years from 1996 to 2006) by combining several ocean color satellite data, i.e., ADEOS-I OCTS and SeaWiFS, and some other sensors. Some typical parameters that could be measured include Chlorophyll- a (Chl-a), Colored Dissolved Organic Matter (CDOM), and Suspended Material (SSM). Reprocessed OCTS images display spatial variation of Chl-a, CDOM, and SSM in the Asian waters; a short term variability of phytoplankton blooms was observed in the Gulf of Oman in November 1996 by analyzing OCTS and NOAA sea surface temperature (SST)； Chl-a concentrations derived from OCTS and SeaWiFS have also been evaluated in coastal areas of the Taiwan Strait, the Gulf of Thailand, the northeast Arabian Sea, and the Japan Sea. The data system provides scientists with capability of testing or developing ocean color algorithms, and transferring images for their research. We have also analyzed availability of OCTS images. The results demonstrate the potential of long-term time series of satellite ocean color data for research in marine biology, and ocean studies. The case studies show multiple applications of satellite images on monitoring of coastal environments in the Asian Waters.

• Proceedings of the Korea Water Resources Association Conference
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• 2021.06a
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• pp.85-85
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• 2021

CDOM(Colored or Chromophoric Dissolved Organic Matter)은 바다, 호수 및 강에서 담수, 오수, 퇴적물 등으로부터 공급된 유기물질의 일종으로 가시광선에서 빛을 흡수하는 성질을 가지며, 2016년부터 환경부에서 선정한 하천, 호수 등 방류수의 수질오염 표준인 TOC(Total Organic Carbon)를 간접 추정할 수 있는 매개변수가 될 수 있다. 따라서, 본 연구에서는 백제보 상류 23 km 구간을 대상으로 2개년(2016~2017) 중 7일의 초분광영상 자료를 활용하여 내륙지역의 CDOM에 대한 적정 반사도 밴드값(R_rs)과 CDOM을 추정하는 알고리즘을 개발하고자 한다. CDOM은 흡수계수(α_CDOM)를 통해 간접 추정되며, 흡수계수의 기준 파장값(λ)은 연구별로 350 nm, 375 nm, 400 nm, 412 nm 및 440 nm 등 다르게 나타난다. 초분광영상은 AsaFENIX 초분광 센서에서 관측된 380~970 nm까지 4 nm 간격, 127개 대역의 분광해상도와 2 m의 공간해상도를 가진 영상을 활용하였으며, 자료의 연속성을 위해 smoothing 기법을 활용하여 가공하였다. 추정 알고리즘은 Random forest를 활용하였으며, 70%의 trainning과 30%의 test로 구분하여 적용하였다. 산출된 CDOM은 결정계수(R²), Nash-Sutcliffe efficiency(NSE)를 이용하여 실측 CDOM과 비교하였다. 흡수계수별 CDOM의 산정 결과 α_CDOM(350 nm)의 trainning, test에서 각각 R²가 0.71, 0.74, NSE가 0.25, 0.49로 가장 높았으며, 적정 반사도 밴드값은 R_rs(466), R_rs(493), R_rs(548), R_rs(641)를 사용하였을 때 trainning, test에서 각각 R²가 0.93, 0.90, NSE가 0.85, 0.69로 가장 높게 나타났다.

• Proceedings of the Korea Water Resources Association Conference
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• 2022.05a
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• pp.46-46
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• 2022

유기물의 복잡한 혼합물인 CDOM(Colored or Chromophoric Dissolved Organic Matter)은 하천 내 BOD(Biological Oxygen Demand), COD(Chemical Oxygen Demand) 및 유기 오염물질과 상당한 관련이 있다. CDOM은 가시광선 영역에서 빛을 흡수하는 성질을 가지고 있으며, 최근 원격감지 기술로 CDOM을 모니터링하기 위한 연구가 진행되고 있다. 본 연구에서는 백제보 상류 23km 구간에서 3년(2016~2018) 중 13일의 초분광영상을 활용하여 머신러닝 기반 CDOM을 추정 알고리즘을 개발하고자 한다. 초분광영상은 400~970 nm의 범위의 4 nm 간격 127개 대역의 분광해상도와 2 m의 공간해상도를 가진 항공기 탑재 AsiaFENIX 초분광 센서를 통해 수집하였으며 CDOM은 Millipore polycarbonate filter (𝚽47, 0.2 ㎛)에서 여과된 CDOM 샘플 자료를 200~800 nm의 흡수계수 스펙트럼으로 추출하여 사용하였다. CDOM 값은 전체기간 동안 2.0~11.0 m^-1의 값 분포를 보였으며 5 m^-1이상의 고농도 구간 자료개수가 전체 153개 샘플자료 중 21개로 불균형하다. 따라서 ADASYN(Adaptive Synthesis Sampling Approach)의 oversampling 방법으로 생성된 합성 데이터를 사용하여 원본 데이터의 소수계층 데이터 불균형을 해결하고 모델 예측 성능을 개선하고자 하였다. 생성된 합성 데이터를 입력변수로 하여 ANN(Artificial Neural Netowk)을 활용한 CDOM 예측 알고리즘을 구축하였다. ADASYN 기법을 통한 합성 데이터는 관측된 데이터의 불균형을 해결하여 기계학습 모델의 CDOM 탐지 성능을 향상시킬 수 있으며, 저수지 내 유기 오염물질 관리를 위한 설계를 지원하는데 사용할 수 있을 것으로 판단된다.

• Journal of the Korean association of regional geographers
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• v.14 no.2
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• pp.114-125
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• 2008

Colored dissolved organic matter(CDOM) is an important component of ocean color that can be used as an invaluable tool in water quality and ocean color studies. With the largest source of coastal CDOM appearing to be from freshwater discharge into the ocean, coastal predictive models will do much to refine our knowledge about major processes that control CDOM distributions in coastal waters and provide a better insight into the global carbon cycle. This study aims at developing a GIS-based watershed-scale predictive model of CDOM distributions in Neponset river watersheds that can be used to appraise our understanding of CDOM sources and distributions in coastal waters and predict the response of CDOM concentration to changes in land use patterns. Weighting factors are developed for CDOM freshwater sources after extensive groundtruthing from various landuse types in the watershed. This model makes use of a publicly available DEM(Digital elevation model) as the base data for analysis. Stream networks, discharge, and land use data are used from public repositories while sub- watershed delineation, pour-points, and land use parcels are generated using Spatial Analysis of ArcGIS 9.2 to estimate the CDOM loading from various sources to the lower tributaries of rivers. The Neponset Watershed in eastern Massachusetts is selected as the site for development of the model.

• Proceedings of the KSRS Conference
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• v.1
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• pp.82-85
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• 2006

The Geostationary Ocean Color Imager (GOCI) will be loaded in Communication, Ocean and Meteorological Satellite (COMS). To efficiently apply the GOCI data in the variety of fields, it is essential to develop the standard algorithm for estimating the concentration of ocean environmental components (, , and ). For developing the empirical algorithm, about 300 water samples and in situ measurements were collected from sea water around the Korean peninsula from 1998 to 2006. Two kinds of chlorophyll algorithms are developed by using statistical regression and fluorescence technique considering the bio-optical properties in Case-II waters. The single band algorithm for is derived by relationship between Rrs (555) and in situ concentration. The CDOM is estimated by absorption coefficient and ratio of Rrs(412)/Rrs(555). These standard algorithms will be programmed as a module of GOCI Data Processing System (GDPS) until 2008.

• Journal of Information Technology Services
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• v.11 no.sup
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• pp.177-189
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• 2012

We developed the ocean disaster detection system(OD2S) which copes with the occurrences of ocean disasters (e. g. the red and green tide, the oil spill, the typhoon, and the sea ice) by converging and integrating the ocean color remote sensing using the satellite and the information technology exploiting the mass data processing and the pattern recognitions. This system which is based on the cosine similarity detects the ocean disasters in real time. The existing ocean color sensors which are operated in the polar orbit platforms cannot conduct the real time observation of ocean environments because they support the low temporal resolutions of one observation a day. However, geostationary ocean color imager(GOCI), the first geostationary ocean color sensor in the world, produces the ocean color images(e. g. the chlorophyll, the colored dissolved organic matter(CDOM), and the total suspended solid(TSS)), with high temporal resolutions of hourly intervals up to eight observations a day. The evaluation demonstrated that the OD2S can detect the excessive concentration of chlorophyll, CDOM, and TSS. Based on these results, it is expected that OD2S detects the ocean disasters in real time.