• Proceedings of the Korea Water Resources Association Conference
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• 2018.05a
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• pp.43-43
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• 2018

수생태계는 다른 여러 생태계 중에서 가장 위험에 처해있으며, 기후변화로 인한 수온, 수문 수질의 변화는 수생태계와 담수 생물다양성에 가장 큰 영향을 미치는 요인 중 하나이다. 본 연구에서는 생물 생태학적으로 변화하는 세계적인 물 관리 패러다임에 따라 한강유역에서의 미래 수생태계 평가를 수행하였다. 본 연구의 목적은 수생태 건강성 관측자료와 수질자료, SWAT 모형을 이용하여 미래 기후변화에 따른 한강유역의 수생태를 평가하는 것이다. 본 연구에서 선정한 수생태계 건강성 조사자료로 국립환경과학원에서 8년간(2008년~2015년) 봄과 가을 2차례에 걸쳐 모니터링 한 부착돌말류(TDI), 저서형 대형무척추동물(BMI), 어류(FAI)에 대한 수생태 등급자료 및 해당 지점에 대한 수온 및 수질자료를 이용하였다. 수집한 결과를 DB(T-N, $NH_4N$, $NO_3N$, T-P, PO4P)에 대한 수생태 등급의 상관성을 분석하고 수온 수질인자에 따른 수생태 등급을 나타내어 미래 기후변화에 따른 수생태 건강성 평가 및 예측을 실시하고자 하였다. Soil and Water Assessment Tool (SWAT) 모형은 유역의 신뢰성 있는 유역 수문, 수질 모의 및 기후변화 영향평가를 위하여 활용되었다. SWAT 모형을 이용하여 한강유역의 다목적댐(3개), 발전용댐(1개), 다기능보(3개) 운영을 고려하였고, 237개의 표준유역으로 분할한 뒤 수문 및 수질 모의를 수행하였다. 모형의 적용성 평가를 위해 댐 및 보의 유입량, 증발산량, 토양수분, 지하수위, SS, T-N, T-P에 대하여 보정(2005~2009) 및 검증(2010~2015)을 수행하였다. 기후변화에 따른 수문, 수질 및 수생태 평가를 위해 기상청의 HadGEM3-RA RCP 4.5와 8.5 시나리오를 적용하였으며, 기준년(1975-2005)년에 대해 2020s(2010-2039), 2050s(2040-2069), 2080s(2070-2099)의 수생태를 평가하였다.

• Proceedings of the Korea Water Resources Association Conference
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• 2022.05a
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• pp.94-94
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• 2022

본류와 지류가 만나는 하천 합류부에서 발생하는 복잡한 흐름 구조는 하상변동에 영향을 주며, 본류와 다른 특성을 보이는 지류의 유입은 수질과 수생태계에도 영향을 준다. 합류부는 하천 변화의 다양성을 보이기 때문에 하천 관리 측면에서 중요한 구간으로, 흐름 및 혼합 특성 이해가 중요하다. 합류부에서의 흐름 및 혼합은 본류와 지류의 유량비, 밀도차, 단차, 합류각, 하도형상 등의 영향으로 그 양상이 달라지며, 흐름장 및 두 수체에 의한 이송물질의 혼합이 이루어졌다고 간주하는 혼합거리는 지류가 본류에 미치는 영향 범위 분석을 위한 중요한 매개변수이다. 본 연구에서는 합류부 흐름에 미치는 주요 인자 중 유량비와 밀도차가 합류부 흐름 및 혼합에 미치는 영향을 수치해석을 통해 분석하고, 조건의 변화에 따른 혼합거리를 예측해 보고자 한다. 본 연구의 대상 지역인 낙동강-황강 합류부는 다기능보와 댐의 운영에 따라 유입 유량 및 유량비가 조절되며, 여름철에는 황강의 수온이 낙동강보다 평균 4℃ 이상 낮으며, 9℃(지류 20℃; 본류 29℃) 이상의 수온차가 발생하기도 한다. 이 경우 밀도비는 0.998로 밀도류가 발생할 수 있는데, 밀도류가 발생할 경우 수표면과 저층이 분리되어 흐르기 때문에 동일 유량 조건에서도 혼합 양상은 달라진다. 밀도류가 발생하기 위해서는 수표면과 저층이 분리되는 성층이 발달해야 하는데, 이는 유속 또는 유량의 범위에 따라 성층의 발달 여부가 달라질 수 있다. 이러한 현장 조건을 반영한 수치해석을 통해 다양한 유량 조건(유량비)에서 밀도의 차이(수온차)가 합류부의 흐름 및 혼합에 미치는 영향을 분석해 보고자 하며, 합류부에서 밀도차에 의한 흐름의 변화 조건을 무차원수(Richardson number, Densimetric Froude number 등)를 통해 정량화해보고자 한다. 이는 지류가 본류에 미치는 영향의 정도와 범위를 파악함으로써 하천 관리를 위한 관측망 및 현장 조사의 범위 선정의 기초자료 마련뿐 아니라 본류의 수온 변화가 발생할 수 있는 범위의 파악을 통해 수생태계에 미치는 영향 파악을 위한 기초자료로 활용될 수 있을 것으로 기대된다.

• Spatial Information Research
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• v.22 no.2
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• pp.63-71
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• 2014

Ocean leisure sports have recently emerged as one of so-called blue ocean industries. They are sensitive to diverse environmental conditions such as current, temperature, and salinity, which can increase needs of forecasting data as well as in-situ observations for the ocean. In this context, a Web-based geovisualization system for coastal information produced by model forecasts was implemented for use in supporting various ocean activities. First, FVCOM(Finite Volume Coastal Ocean Model) was selected as a forecasting model, and its data was preprocessed by a spatial interpolation and sampling library. The interpolated raster data for water surface elevation, temperature, and salinity were stored in image files, and the vector data for currents including speed and direction were imported into a distributed DBMS(Database Management System). Web services in REST(Representational State Transfer) API(Application Programming Interface) were composed using Spring Framework and integrated with desktop and mobile applications developed on the basis of hybrid structure, which can realize a cross-platform environment for geovisualization.

• Proceedings of the Korea Water Resources Association Conference
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• 2017.05a
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• pp.141-141
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• 2017

본 연구에서는 대하천의 8개의 수질인자(수온, 용존산소, 수소이온농도, 전기전도도, 총질소, 총인, 탁도, 클로로필-a)를 예측할 수 있는 인공신경망모델을 개발하였다. 인공신경망모델(ANN)은 수질데이터가 가지는 불확실성 및 비정상성, 복잡한 상호관련성에 효과적으로 대응할 수 있는 데이터기반 모델이다. 데이터기반 모델의 특성상 예측정확도를 높이기 위해서 양질의 입력데이터를 구성하는 것이 가장 중요하다. 때문에 각각의 수질인자뿐만 아니라 기상학적 인자 또한 예측을 위한 입력자료로 사용하였으며, 요인분석 및 층화표층추출법을 적용하여 입력데이터를 구성하였고 앙상블기법을 이용하여 추가적으로 예측의 정확도를 향상시켰다. 개발된 모델을 이용하여 지천유입이 있는 북한강의 수질자료를 예측한 결과 탁도를 제외한 7개의 수질인자 모두 0.85 이상의 설명력을 보였으며, 실측값과 예보값을 비교해본 결과 평균적으로 10% 미만의 에러값을 나타냈다. 요인분석을 통하여 연관성있는 인자를 입력인자로 추가한 경우 향상된 결과값을 보였주었으며, 앙상블기법을 적용한 결과 정확도 면에서 큰 향상을 보여주었다.

• Journal of Internet Computing and Services
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• v.24 no.1
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• pp.61-69
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• 2023

Recently, as the fishery resources are depleted, expectations for productivity improvement by 'rearing fishery' in land farms are greatly rising. In the case of land farms, unlike ocean environments, it is easy to control and manage environmental and breeding factors, and has the advantage of being able to adjust production according to the production plan. On the other hand, unlike in the natural environment, there is a disadvantage in that operation costs may significantly increase due to the artificial management for fish growth. Therefore, profit maximization can be pursued by efficiently operating the farm in accordance with the planned target shipment. In order to operate such an efficient farm and nurture fish, an accurate growth prediction model according to the target fish species is absolutely required. Most of the growth prediction models are mainly numerical results based on statistical analysis using farm data. In this paper, we present a growth prediction model from a stochastic point of view to overcome the difficulties in securing data and the difficulty in providing quantitative expected values for inaccuracies that existing growth prediction models from a statistical point of view may have. For a stochastic approach, modeling is performed by introducing a Gaussian process regression method based on water temperature, which is the most important factor in positive growth. From the corresponding results, it is expected that it will be able to provide reference values for more efficient farm operation by simultaneously providing the average value of the predicted growth value at a specific point in time and the confidence interval for that value.

• Korean Journal of Ecology and Environment
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• v.35 no.2 s.98
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• pp.79-91
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• 2002

A time variable modeling study was performed for seasonal variations of vertical temperature profiles in the Okjung Lake located in upstream of the Sumjin River. Based on the model structure of the US Army Corps of Engineer's CE-QUAL-W2, the lake was divided into 3 branches, 50 longitudinal segments and 49 vertical layers and vertical profiles of water temperature and current velocity were simulated over one year. The model results were calibrated and verified against vertical profiles of water temperature measured every month from March 1998 to February 1999 at 5 different locations. The model results showed a good agreement with the field measurements. The hydrologic balance during this period was validated by comparing the simulated values of surface elevation level with the measured data. There was some discrepancy in July data between the model results and the fleld measurements. This could be attributed partially to the inadequacy of the model to the highly hydrodynamic nature of water body and partially to the lack of accuracy in local atmospheric temperature data during summer monsoon period. The model results have shown that there was no seasonal over-turn in most part of the Okjung Lake, where water temperature maintained above $4^{\circ}C$ over one year. In the upstream shal-low area (depth<20 meter), however, temperature at surface layer fell below $4^{\circ}C$ and water was frozen such that slight over-turn would occur during winter period. From this study, we concluded that the Okjung Lake is oligomictic. This conclusionis significantly different from the general pattern that the lakes located from $20^{\circ}C$ to $40^{\circ}C$ latitude would be warm monomictic. From the examination of simulated current velocity distribution, it was found that the upstream inflows would infiltrate into mesolimnion of the lake during hydrodynamic summer monsoon periods due to the thermal density of water.

• The Journal of the Korea institute of electronic communication sciences
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• v.16 no.2
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• pp.371-378
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• 2021

In this study, in order to analyze the spatial distribution of cold water occurred in the Southeast Sea of Korea, the K-means clustering method was used to analyze the ocean observatory buoy of Gori and Yangpo and GHTSST Level 4 from 2016 to 2018. The buoy data was used to identify the change in sea water temperature and the cold water occurrence at Gori and Yangpo in the Southeast Sea. As a result, the sea water temperature of Gori and Yangpo decreased equally at the cold water occurrence. Therefore, the reciprocal of the sea water temperature and the variance of SST were compared to see the changes of SST when the cold water occurs. When the reciprocal of the sea water temperature increases, the dispersion of SST also increases. Through this, it can be seen that there is a change in the water temperature distribution of SST in the sea when the cold water occurs. After that, K-means clustering was used to classify the cold water. After analyzing the optimal K value for clustering by using the Elbow method, it was possible to classify a region with cold water. Through this, it is estimated that the spatial distribution and diffusion range of the cold water, and it can be estimated and used in future studies to identify damage caused by the cold water and predict spatial spread.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.18 no.3
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• pp.111-121
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• 2013

Accurate prediction of sea water temperature has been emphasized to make precise local weather forecast and to understand change of ecosystem. The Yellow Sea, which has turbid water and strong tidal current, is an unique shallow marginal sea. It is essential to include the effects of the turbidity and the strong tidal mixing for the realistic simulation of temperature distribution in the Yellow Sea. Evaluation of ocean circulation model response to vertical mixing scheme and turbidity is primary objective of this study. Three-dimensional ocean circulation model(Regional Ocean Modeling System) was used to perform numerical simulations. Mellor- Yamada level 2.5 closure (M-Y) and K-Profile Parameterization (KPP) scheme were selected for vertical mixing parameterization in this study. Effect of Jerlov water type 1, 3 and 5 was also evaluated. The simulated temperature distribution was compared with the observed data by National Fisheries Research and Development Institute to estimate model's response to turbidity and vertical mixing schemes in the Yellow Sea. Simulations with M-Y vertical mixing scheme produced relatively stronger vertical mixing and warmer bottom temperature than the observation. KPP scheme produced weaker vertical mixing and did not well reproduce tidal mixing front along the coast. However, KPP scheme keeps bottom temperature closer to the observation. Consequently, numerical ocean circulation simulations with M-Y vertical mixing scheme tends to produce well mixed vertical temperature structure and that with KPP vertical mixing scheme tends to make stratified vertical temperature structure. When Jerlov water type is higher, sea surface temperature is high and sea bottom temperature is low because downward shortwave radiation is almost absorbed near the sea surface.

• Journal of Korea Water Resources Association
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• v.38 no.8 s.157
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• pp.655-664
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• 2005

A real-time monitoring and modeling system (RTMMS) for rainfall-induced turbidity flow, which is one of the major obstacles for sustainable use of reservoir water resources, is under development. As a prediction model for the RTMMS, a laterally integrated two-dimensional hydrodynamic and water quality model, CE-QUAL-W2 was tested by simulating the temperature stratification, density flow regimes, and temporal and spatial distributions of turbidity in a reservoir. The inflow water temperature and turbidity measured every hour during the flood season of 2004 were used as the boundary conditions. The monitoring data showed that inflow water temperature drop by 5 to $10^{\circ}C$ during rainfall events in summer, and consequently resulted in the development of density flow regimes such as plunge flow and interflow in the reservoir. The model showed relatively satisfactory performance in replicating the water temperature profiles and turbidity distributions, although considerable discrepancies were partially detected between observed and simulated results. The model was either very efficient in computation as the CPU run time to simulate the whole flood season took only 4 minutes with a Pentium 4(CPU 2.0GHz) desktop computer, which is essentially requited for real-time modeling of turbidity plume.

• Proceedings of the Korean Society of Coastal and Ocean Engineers Conference
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• 1995.10a
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• pp.146-151
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• 1995

원자력, 화력발전소 및 임해공업시설로부터 방출되는 냉각용 온수는 하천 또는 연안일대의 수계환경에 전반적인 수중온도의 상승과 가동 중단시 갑작스러운 수온 저하 등의 열균형 파괴를 가져온다. 따라서 여러가지 형태의 주위수에 영향을 받는 온배수의 이동 및 확산에 대한 정성, 정량적 예측을 위한 수치모델의 개발은 환경관리 및 생태계 보전 측면에서 매우 중요하다. (중략)