• 한국물환경학회지
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• 제28권6호
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• pp.819-832
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• 2012

HSPF model based on BASINS was applied for the Hwaseong Reservoir watershed (HRW) to evaluate the feasibility of water quality management. The watershed was divided into 45 sub-basins considering various watershed environment. Streamflow was calibrated based on the measured meteorological data, discharge data of treatment plants and observed streamflow data for 2010 year. Then the model was calibrated against the field measurements of water qualities, including BOD, T-N and T-P. In most cases, there were reasonable agreements between observed and predicted data. The validated model was used to analyze the characterization of pollutant load from study area. As a result, Non-point source pollutant loads during the rainy season was about 66~78% of total loads. In rainy-season, water quality parameters depended on precipitation and pollutant loads patterns, but their concentration were not necessarily high during the rainy season, and showed a decreasing trend with increasing water flow. As another result of evaluation for load duration curves, in order to improve water qualities to the satisfactory level, the watershed managements considering both time-variant and pollution sources must be required in the HRW. Overall, it was found that the model could be used conveniently to assess watershed characteristics and pollutant loads in watershed scale.

• 한국지구과학회지
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• 제26권3호
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• pp.268-275
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• 2005

대표적인 엘니뇨 지수인 태평양 Nino 해역의 표층 수온을 예측하기 위해 비선형 통계모델 중의 하나인 신경망 기법을 적용하였다. 신경망 모델 학습 과정의 입력 자료로 1951년부터 1993년까지의 태평양 해역$(120^{\circ}\;E,\;20^{\circ}\;S-20^{\circ}\;N)$ NCEP/NCAR의 재분석 표층 수온 편차의 경험적 직교함수 7개 주모드를 사용하였고, 그 중 1994년부터 2003년까지의 10년 결과를 분석하였다. 모든 해역에서의 9개월까지의 신경망 모델의 예측력은 비교적 우수하였으며, 특히 1997년과 1998년의 강한 엘니뇨의 발달 및 소멸도 잘 예측함을 확인할 수 있었다. 해역별로는 Nino3 지역의 예측성능이 가장 높았으며, 9개월 이후부터는 그 예측력이 급격히 감소하였다. 한편 지역적인 영향이 커 예측력이 낮은 동태평양 연안의 Nino1+2 지역은 9개월 이후에도 예측력의 감소가 관찰되지 않았다.

• Advances in environmental research
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• 제7권2호
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• pp.121-138
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• 2018

Depending on the increased energy needs, a large number of dams have been built around the world. These dams have significant impacts on river ecology and climate change. When the climate change scenarios are examined, it is stated that the annual average temperature in Turkey will increase by 2.5-4 degrees in the future years, the south of the country will be opposed to the severe drought threat, and the northern regions will have a flood risk. In particular, it can be predicted that many dams and dam lakes built in the North of Turkey may increase the impact of climate change. In this study, the effects of the dams constructed in Çoruh basin on climate change are examined. Environmental and ecological problems of dam reservoirs have been examined. As a result of the data received from meteorological stations, it was determined that temperature and rainfall changes in the region. In this direction, solution proposal is presented.

• 방사성폐기물학회지
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• 제21권2호
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• pp.183-191
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• 2023

The potential impact of hypothetical accidents that occur during the immediate and deferred dismantling of the Kori Unit 1 steam generator has been comprehensively evaluated. The evaluation includes determining the inventory of radionuclides in the Steam Generator based on surface contamination measurements, assuming a rate of release for each accident scenario, and applying external and internal exposure dose coefficients to assess the effects of radionuclides on human health. The evaluation also includes calculating the atmospheric dispersion factor using the PAVAN code and analyzing three years of meteorological data from Kori NPP to determine the degree of diffusion of radionuclides in the atmosphere. Overall, the effective dose for residents living in the Exclusion Area Boundary (EAB) of Kori NPP is predicted, an it is found that the maximum level of the dose is 0.034% compared to the annual dose limit of 1 mSv for the general public. This implies that the potential impact of hypothetical accidents on human health discussed above is within acceptable limits.

• 대기
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• 제28권1호
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• pp.37-51
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• 2018

In this study, we investigate the performance of Global Seasonal Forecasting System version 5 (GloSea5) in Korea Meteorological Administration on the relationship between El $Ni{\tilde{n}}o$ and East Asian climate for the period of 1991~2010. It is found that the GloSea5 has a great prediction skill of El $Ni{\tilde{n}}o$ whose anomaly correlation coefficients of $Ni{\tilde{n}}o$ indices are over 0.96 during winter. The eastern Pacific (EP) El $Ni{\tilde{n}}o$ and the central Pacific (CP) El $Ni{\tilde{n}}o$ are considered and we analyze for EP El $Ni{\tilde{n}}o$, which is well simulated in GloSea5. The analysis period is divided into the developing phase of El $Ni{\tilde{n}}o$ summer (JJA(0)), mature phase of El $Ni{\tilde{n}}o$ winter (D(0)JF(1)), and decaying phase of El $Ni{\tilde{n}}o$ summer (JJA(1)). The GloSea5 simulates the relationship between precipitation and temperature in East Asia and the prediction skill for the East Asian precipitation and temperature varies depending on the El $Ni{\tilde{n}}o$ phase. While the precipitation and temperature are simulated well over the equatorial western Pacific region, there are biases in mid-latitude region during the JJA(0) and JJA(1). Because the low level pressure, wind, and vertical stream function are simulated weakly toward mid-latitude region, though they are similar with observation in low-latitude region. During the D(0)JF(1), the precipitation and temperature patterns analogize with observation in most regions, but there is temperature bias in inland over East Asia. The reason is that the GloSea5 poorly predicts the weakening of Siberian high, even though the shift of Aleutian low is predicted. Overall, the predictability of precipitation and temperature related to El $Ni{\tilde{n}}o$ in the GloSea5 is considered to be better in D(0)JF(1) than JJA(0) and JJA(1) and better in ocean than in inland region.

• 대한원격탐사학회지
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• 제35권6_3호
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• pp.1221-1233
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• 2019

화산재 누적에 따라 발생할 수 있는 각 분야별 피해를 산정하는 것은 화산재 재해를 대비하는 측면에서 매우 중요하다. 본 연구에서는 기존 연구에서 제시된 공간정보 기반의 국내 화산재 피해 분야에 대하여 아소산 화산재 모의 확산 시나리오를 적용하여 각 분야에서 발생할 수 있는 화산재 피해의 정도를 나타냈다. 이를 위하여 기존의 사례 연구를 통하여 제시된 국내 화산재 피해 분야와 관련된 공간정보 자료를 수집하고 가공함으로써 화산재 피해 기반자료를 생성하였다. 수집된 두 개의 아소산 화산 모의 분화 시나리오를 활용하여 중첩분석을 통해 분야별 피해를 나타냈다. 그 결과 각 분화 시나리오에 대하여 162개, 134개 시군구에서 강회 피해 최소 기준인 0.01 mm 이상의 강회량에 따라 피해가 발생할 것으로 예상되었다. 가장 강회량이 많은 행정구역(시나리오 190805-강원, 경북; 시나리오 190811-춘천, 홍천)을 선정하여 발생 가능한 분야별 피해의 정도를 수집 가공한 공간정보 자료를 활용하여 서로 비교하였다.

• 환경영향평가
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• 제9권4호
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• pp.323-338
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• 2000

A Korean air dispersion modeling software, AirMaster, was developed on a basis of dispersion theories adopted in U.S. EPA's ISC3 (Industrial Source Complex - version 3) model to assess the air quality impact from the stacks. Key characteristics of AirMaster are as follows: 1) The building downwash effect can be easily simulated; 2) The screen, long term, and short term models can be run independently; 3) The input data to run the model such as meteorological and terrain data are supplied automatically from the databases in AirMaster; and 4) The modeling procedure is easy and simple under the GUI window environment. In order to validate AirMaster, comparisons with ISC3 model and Indianapolis tracer experiment were carried out. It was shown that AirMaster was identical to ISCST3 and ISCLT3 models in predicting the 1 hr to annual concentrations from the stack under various stack emission and meteorological conditions. The 1 hr concentrations predicted by AirMaster also showed a good agreement with the Indianapolis tracer measurements.

• 한국태양에너지학회 논문집
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• 제31권6호
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• pp.8-22
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• 2011

Investigations on modeling methods of a CFD wind resource prediction program, WindSim for a ccurate predictions of wind speeds were performed with the field measurements. Meteorological Masts having heights of 40m and 50m were installed at two different sites in complex terrain. The wind speeds and direction were monitored from sensors installed on the masts and recorded for one year. Modeling parameters of WindSim input variables for accurate predictions of wind speeds were investigated by performing cross predictions of wind speeds at the masts using the measured data. Four parameters that most affect the wind speed prediction in WindSim including the size of a topographical map, cell sizes in x and y direction, height distribution factors, and the roughness lengths were studied to find out more suitable input parameters for better wind speed predictions. The parameters were then applied to WindSim to predict the wind speed of another location in complex terrain in Korea for validation. The predicted annual wind speeds were compared with the averaged measured data for one year from meteorological masts installed for this study, and the errors were within 6.9%. The results of the proposed practical study are believed to be very useful to give guidelines to wind engineers for more accurate prediction results and time-saving in predicting wind speed of complex terrain that will be used to predict annual energy production of a virtual wind farm in complex terrain.

• 설비공학논문집
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• 제18권1호
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• pp.87-94
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• 2006

In this paper, we investigated a feasibility of applying highest and lowest temperatures of the next day forecasted from a meteorological observatory to operation of an air-conditioning system with thermal storage. First we investigated specific characteristics of the time series of forecasted temperatures and errors in Osaka from 1994 to 1996. Since the forecast error is not always small, it might be difficult to use the forecasted data without correction for the sizing and the control of the thermal storage system. On the other hand, the autocorrelation functions of the forecast errors decrease relatively slowly during high summer season when cooling thermal storage is required. Since the values of the autocorrelation function; for one day are larger than 0.4, not small, the forecast errors can be predicted by proper statistical analysis. Thus, the forecasted values of the highest temperatures for the next day were improved by using the stochastic time series models.

• 상하수도학회지
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• 제14권3호
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• pp.281-290
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• 2000

This study investigates the prediction of daily water supply, which is a necessary for the efficient management of water distribution system. ANFIS, namely artificial intelligence, is a neural network into which fuzzy information is inputted and then processed. In this study, daily water supply was predicted through an application of network-based fuzzy inference system(ANFIS) for daily water supply prediction. This study was investigated methods for predicting water supply based on data about the amount of water which supplied in Kwangju city. For variables choice, four analyses of input data were conducted: correlation analysis, autocorrelation analysis, partial autocorrelation analysis, and cross-correlation analysis. Input variables were (a) the amount of water supply, (b) the mean temperature, and (c) the population of the area supplied with water. Variables were combined in an integrated model. Data of the amount of daily water supply only was modelled and its validity was verified in the case that the meteorological office of weather forecast is not always reliable. Proposed models include accidental cases such as a suspension of water supply. The maximum error rate between the estimation of the model and the actual measurement was 18.46% and the average error was lower than 2.36%. The model is expected to be a real-time estimation of the operational control of water works and water/drain pipes.