• Ocean and Polar Research
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• v.34 no.2
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• pp.253-264
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• 2012

In the northwestern Pacific, spawning of the common squid, Todarodes pacificus, occurs at continental shelf and slope areas of 100-500 m, and the optimum temperature for the spawning and survival of paralarvae is assumed to be $18-23^{\circ}C$. To predict the spawning ground of Todarodes pacificus under future climate conditions, we simulated the present and future ocean circulations, using an East Asia regional ocean model (Modular Ocean Model, MOM version3), projected by two different global climate models (MPI_echam5, MIROC_hires), under an IPCC SRES A1B emission scenario. Mean climate states for 1990-1999 and 2030-2039 from 20th and 21th Century Climate Change model simulation (from the IPCC 4th Assessment Report) were used as surface conditions for simulations, and we examined changes in spawning ground between the 1990s and 2030s. The results revealed that the distribution of spawning ground in the 2030s in both climate models shifted northward in the East China Sea and East Sea, for both autumn and winter populations, compared to that of the 1990s. Also, the spawning area (with $1/6^{\circ}{\times}1/6^{\circ}$ grid) in the 2030s of the autumn and winter populations will decline by 11.6% (MPI_echam5) to 30.8% (MIROC_hires) and 3.0% (MPI_echam5) to 18.2% (MIROC_hires), respectively, from those of the 1990s.

• Proceedings of the Korea Water Resources Association Conference
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• 2011.05a
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• pp.273-277
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• 2011

오늘날 기후변화는 기후 시스템을 구성하는 대기, 해양, 생물, 빙하, 육지 등의 다양한 구성요소에 작용하여 자연 생태계와 인간의 사회 및 경제 시스템에 커다란 영향을 미친다. 특히 최근 인간의 활동에 의해 야기된 기후변화는 극치적인 기후 현상의 빈도와 강도에 영향을 미칠 뿐만 아니라, 기후변화 현상은 수환경 시스템, 하천 생태계와 유역관리 등의 다양한 분야에 걸쳐 심각한 문제를 발생시킨다. 이에 따른 수자원의 효율적인 관리와 안정적인 물공급에 어려움을 증대시킬 것으로 전망되며, 현재 이것은 각 분야별로 해결해야 할 범지구적 문제로 인식되고 있다. 기후변화를 탐지하고 예측하기 위해서는 SRES 배출시나리오를 이용한 미래의 기후변화 장기시나리오가 필요한데, 이를 위한 기본적인 도구로 전지구기후모형(Global Climate Models, GCMs)이 있다. 기후변화에 따른 지역적 차원의 수자원에의 영향 분석을 위해서는 GCMs의 결과를 바탕으로 지역 규모에서의 기후 자료로 변환하는 규모내림(downscaling) 기법을 이용한다. 본 연구는 기후변화 분석의 가장 기본이라 할 수 있는 국내에 적합한 GCM의 선정 및 우리나라의 시공간적 기상패턴의 정밀한 구현을 위한 규모내림기법의 적용을 통하여 실시하였다. 현재 뿐 아니라 미래 90년간 (2011년 ~ 2100년)의 기상 자료를 생산하고 이를 SWAT 모형에 적용하였다. 이러한 GCMs-규모내림-SWAT 모형으로 이어지는 시나리오 기반의 기후변화에 대한 낙동강 유역의 유출 분석은 기후변화 연구에 기술적 방법론의 제시와 함께 앞으로 타 유역에의 적용을 통하여 보다 정량적이고 신뢰성 있는 전국 단위의 기후변화에 따른 유출 분석연구의 기초가 될 수 있을 것이라 기대한다.

• Journal of Korean Society on Water Environment
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• v.25 no.6
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• pp.821-831
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• 2009

The study was aimed to assess the expected impact of climate change on the water cycle and soil losses in Daecheong Reservoir watershed, Korea using the Soil and Water Assessment Tool (SWAT) that was validated for the watershed in a previous study. Future climate data including precipitation, temperature and humidity generated by introducing a regional climate model (Mesoscale Model Version 5, MM5) to dynamically downscale global circulation model (European Centre Hamburg Model Version 4, ECHAM4) were used to simulate the hydrological responses and soil erosion processes in the future 100 years (2001~2100) under the Special Report on Emissions Scenario (SRES) A1B. The results indicated that the climate change may increase in the amount of surface runoff and thereby sediment load to the reservoir. Spatially, the impact was relatively more significant in the subbasin Bocheongcheon because of its lower occupation rate of forest land compared to other subbasins. Seasonally, the increase of surface runoff and soil losses was more significant during late summer and fall season when both flood control and turbidity flow control are necessary for the reservoir and downstream. The occurrence of extreme turbidity flow events during these period is more vulnerable to reservoir operation because the suspended solids that remained water column can be resuspended by vertical mixing during winter turnover period. The study results provide useful information for the development of adaptive management strategy for the reservoir to cope with the expected impact of future climate change.

• Journal of Korean Society on Water Environment
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• v.31 no.3
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• pp.241-252
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• 2015

Runoff behaviors by five bias correction methods were analyzed, which were Change Factor methods using past observed and estimated data by the estimation scenario with average annual calibration factor (CF_Y) or with average monthly calibration factor (CF_M), Quantile Mapping methods using past observed and estimated data considering cumulative distribution function for entire estimated data period (QM_E) or for dry and rainy season (QM_P), and Integrated method of CF_M+QM_E(CQ). The peak flow by CF_M and QM_P were twice as large as the measured peak flow, it was concluded that QM_P method has large uncertainty in monthly runoff estimation since the maximum precipitation by QM_P provided much difference to the other methods. The CQ method provided the precipitation amount, distribution, and frequency of the smallest differences to the observed data, compared to the other four methods. And the CQ method provided the rainfall-runoff behavior corresponding to the carbon dioxide emission scenario of SRES A1B. Climate change scenario with bias correction still contained uncertainty in accurate climate data generation. Therefore it is required to consider the trend of observed precipitation and the characteristics of bias correction methods so that the generated precipitation can be used properly in water resource management plan establishment.

• Journal of The Korean Society of Agricultural Engineers
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• v.51 no.4
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• pp.7-13
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• 2009

The paddy irrigation demand for Nakdong river basin in Korea due to the climate change have been analyzed using regional climate model outputs. High-resolution (27 ${\times}$ 27 km) climate data for SRES A2 scenario produced by the Meteorological Research Institute (METRI), South Korea, and the observed baseline climatology dataset (1971-2000) were used. The outputs from the ECHO-G GCM model were dynamically downscaled using the MM5 regional model by METRI. Maps showing the predicted spatial variations of changes in climate parameters and paddy irrigation requirements have been produced using the geographic information system. The results of this study showed that the average growing season temperature will increase steadily by 1.5 $^{\circ}C$ (2020s A2), 3.2 $^{\circ}C$ (2050s A2) and 5.2 $^{\circ}C$ (2080s A2) from the baseline (1971-2000) 19.8 $^{\circ}C$. The average growing season rainfall will change by -3.4 % (2020s A2), 0.0 % (2050s A2) and +16.5 % (2080s A2) from the baseline value 886 mm. Assuming paddy area and cropping pattern remain unchanged the average volumetric irrigation demands were predicted to increase by 5.3 % (2020s A2), 8.1 % (2050s A2) and 2.2 % (2080s A2) from the baseline value 1.159 ${\times}$ $10^6\; m^3$. These projections are different from the previous study by Chung (2009) which used a different GCM and downscaling method and projected decreasing irrigation demands. This indicates that one should be careful in interpreting the results of similar studies.

• Journal of Environmental Impact Assessment
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• v.20 no.2
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• pp.107-121
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• 2011

To assess the impact of climate change on water quality in an impounded river basin, this study estimated future air temperature and rainfall in the years of 2020, 2050 and 2080 by statistically downscaling the simulation results from two GCM models combined with two emission scenarios (A2 and B1). Both scenarios were selected from the Special Report on Emission Scenarios (SRES) suggested by IPCC. The A2 scenario represents an extreme condition whereas the B1 scenario represents a clean and energy efficient condition which is similar to that of study basin. With the results of estimated climate factors and land use data, the discharge and the concentrations of BOD, TN and TP in the Andong dam basins were simulated using the SWAT model. The change in BOD concentration for the B1 emission scenario was greater than the A2 scenario in the annual increase range and the pollution level. The concentration of TN was decreased during March? June which is drought period and increased again afterward. In contrast to TN, the concentration of TP was generally decreased. The change in TP concentration was greater for the B1 scenario than the A2 scenario.

• Journal of Korean Society on Water Environment
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• v.30 no.2
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• pp.212-219
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• 2014

In this study, a land pollutant load calculation method in TMDLs was improved to consider climate change scenarios. In order to evaluate the new method, future change in rainfall patterns was predicted by using SRES A1B climate change scenarios and then post-processing methods such as change factor (CF) and quantile mapping (QM) were applied to correct the bias between the predicted and the observed rainfall patterns. Also, future land pollutant loads were estimated by using both the bias corrected rainfall patterns and the enhanced method. For the results of bias correction, both methods (CF and QM) predicted the temporal trend of the past rainfall patterns and QM method showed future daily average precipitation in the range of 1.1~7.5 mm and CF showed it in the range of 1.3~6.8 mm from 2014 to 2100. Also, in the result of the estimation of future land pollutant loads using the enhanced method (2020, 2040, 2100), TN loads were in the range of 4316.6~6138.6 kg/day and TP loads were in the range of 457.0~716.5 kg/day. However, each result of TN and TP loads in 2020, 2040, 2100 was the same with the original method. The enhanced method in this study will be useful to predict land pollutant loads under the influence of climate change because it can reflect future change in rainfall patterns. Also, it is expected that the results of this study are used as a base data of TMDLs in case of applying for climate change scenarios.

• Advances in aircraft and spacecraft science
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• v.3 no.2
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• pp.113-148
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• 2016

In a whole variety of higher order plate theories existing in the literature no consideration is given to the transverse normal strain / deformation effects on flexural response when these higher order theories are applied to shear flexible composite plates in view of minimizing the number of unknown variables. The objective of this study is to carry out cylindrical bending of simply supported laminated composite and sandwich plates using sinusoidal shear and normal deformation plate theory. The most important feature of the present theory is that it includes the effects of transverse normal strain/deformation. The displacement field of the presented theory is built upon classical plate theory and uses sine and cosine functions in terms of thickness coordinate to include the effects of shear deformation and transverse normal strain. The theory accounts for realistic variation of the transverse shear stress through the thickness and satisfies the shear stress free conditions at the top and bottom surfaces of the plate without using the problem dependent shear correction factor. Governing equations and boundary conditions of the theory are obtained using the principle of minimum potential energy. The accuracy of the proposed theory is examined for several configurations of laminates under various static loadings. Some problems are presented for the first time in this paper which can become the base for future research. For the comparison purpose, the numerical results are also generated by using higher order shear deformation theory of Reddy, first-order shear deformation plate theory of Mindlin and classical plate theory. The numerical results show that the present theory provides displacements and stresses very accurately as compared to those obtained by using other theories.

• Proceedings of the Korea Water Resources Association Conference
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• 2010.05a
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• pp.938-942
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• 2010

현재 기후변화가 심화되면서 기상변동성이 커지고 이에 따라 사막화 현상의 심화, 엘니뇨(El Nino), 라니냐(La Nina), 태풍, 집중호우 등의 이상기후 현상이 전 지구상에 걸쳐 광역적으로 나타나고 있는 실정이다. 이러한 기후변화는 앞서 말한 것과 같이 여러 기후인자들을 변화시켜 수자원의 양적변화 등 지속가능한 수자원 개발 관리에 큰 영향을 미치므로 이에 대한 연구가 국내외에서 활발히 진행되고 있다. 대표적으로 여러 가지 2CO2 시나리오에 대한 대기 순환 모형의 적용 결과를 이용하여, 이러한 기후변화가 수문순환에 영향을 미치는 기후인자인 기온, 강수량, 습도 및 풍속, 그리고 물의 수량 및 수질 등에 미치는 영향을 분석하고, 이를 기반으로 기후변화와 관련된 환경 및 수자원의 정책 개발에 대한 연구들이 주로 수행되고 있다. 국내 역시 기후 변화와 관련된 연구들이 수행되고는 있으나, 기후변화와 연계된 유량과 수질 예측에 대한 연구가 절실히 요구되고 있는 실정이다. 따라서 본 연구에서는 IPCC의 배출 시나리오(Special Report on Emissions Scenarios, 이하 SRES) 중 인구증가율이 높고 경제발달과 기술변화가 느리고 환경에 무관심한 극한현상을 나타내는 A2 시나리오와 청정 및 자원 효율적인 기술 등 급격히 발전하고 조사대상 유역특성과 유사한 B1 시나리오를 선정하고, 이에 대한 유역의 기온과 강우량을 GCM을 적용하여 모의하였다. 또한 향후의 기후변화가 유출 수질(BOD, TN, TP)에 미치는 영향을 2020년, 2050년, 2080년에 대하여 평가하기 위하여 GIS 기반의 유역 모형인 SWAT을 대상모형으로 선정하였다. 신뢰성 평가를 위해 현재 상태에서의 모의를 검 보정 하여 실제 A2, B1 기후변화 시나리오에 따른 기온 및 강우량 변화 등에 대한 영향을 평가하여 보았다.

• Proceedings of the Korea Water Resources Association Conference
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• 2010.05a
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• pp.1605-1609
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• 2010

CGCM3.1 SRES B1 시나리오의 2D 변수들을 입력값으로 인공신경망 모형을 이용한 스케일 상세화기법으로 강부식(2009)은 소양강댐 유역의 월 누적강수 경향분석을 실시하였다. 원시 GCM 시나리오를 스케일 상세화 시키기 위한 기법의 하나로 인공신경망 모형을 사용할 수 있는데, 이 경우 GCM에서 모의되는 강수플럭스, 해면기압, 지표면 근처에서의 일 평균온도, 지표면 근처에서의 일평균온도, 지표면으로부터 발생하는 잠열플럭스 등과 같은 22개의 변수를 잠재적인 예측인자로 사용하여 신경망을 구성하게 된다. 입력변수세트의 구성은 인공신경망의 계산 효율을 좌우하는 중요한 요소라 할 수 있다. 본 연구에서는 변수의 물리적 특성을 고려하여 순차적인 변수선택을 통한 신경망 입력변수 세트를 구성하고 입력세트 간의 학습성과 비교를 통하여, 최적 입력변수 선정 및 신경망의 학습효과를 높일 수 있는 방법에 대해 연구하였다. 물리적 상관성이 높다고 판단되는 GCM_Prec, huss, ps를 입력변수로 하여 순차적인 케이스를 학습해본 결과 huss와 ps를 입력변수로 하는 케이스에 대해서 적은 오차와 높은 상관성을 보였다, 또한, 신경망의 학습 효과를 높이기 위해 홍수기와 비홍수기로 구분하여 학습한 결과 홍수기와 비홍수기로 구분하여 신경망을 구성하였을 경우가 향상된 모의값을 나타내었다. 기후변화모의자료는 CCCma(Canadian Center for Climate Modeling and Analysis)에서 제공되는 CGCM3.1/T63 20C3M 시나리오를 사용하였으며, 관측값으로는 AWS에서 제공된 일 누적강수를 사용하였다. 인공신경망의 학습기간은 1997년부터 2000년이며, 검증기간은 2001년부터 2004년으로 구성하였다.