• Journal of Korean Society of Water and Wastewater
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• v.21 no.3
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• pp.265-272
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• 2007

This study uses the SWAT model to analyze the characteristics of long-term runoff at the Ssang-cheon Basin located in the city of Sokcho, which is located in the province of Gangwon. The study considers the effect of snow packing and snow melting in a runoff simulation. In this simulation, the study examines the need to introduce a snow pack and snow melt model to evaluate the water resources of the mountainous region of the Gangwon province. The findings of this study indicate that the runoff hydrograph that was produced approximates the true measured flow when the effect of the snow pack and snow melt are considered, compared to when they are not factored in. The analysis of the flow duration curve indicates that the stream flow largely increases when the effect of the snow pack and snow melt are considered. The wet stream flow was shown to increase by nearly 3% due to the melting effect, while the normal stream flow, low stream flow and drought stream flow were shown to increase by slightly more than 10%. Specifically, it was found that as the stream flow decreases, the effect of the snow pack and snow melt on the stream flow increases.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.32 no.6B
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• pp.355-361
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• 2012

Gwangdong Dam Watershed is affected by the increased discharge caused by the melting snow in the spring season. Therefore, simulation results obtained using hydrologic models have generally been inaccurate in relation to discharge without snow pack and melt modules. In this research, a grid based distributed rainfall runoff model (K-DRUM) was developed using a snow pack and melt module, and has been applied in the Gwangdong Dam Watershed to simulate the discharge for a four year period. A previous version of K-DRUM, which does not include a snow pack or melt module, was used to calculate the discharge in order to compare the snow melt effect. The simulation period lasted about 7 months from October of the previous year to April of this year using hourly precipitation and weather observed data. To evaluate the model performance, NSE, PBIAS and RSR statistics techniques were applied using the simulation results of the discharge. From the results of reliability evaluation, the K-DRUM model, which uses a snow pack and melt module, had a good applicability for the runoff simulation considering the snow melt effect in the spring.

• Proceedings of the KSR Conference
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• 2008.11b
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• pp.56-60
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• 2008

Increasing urban sprawl and climate changes have been causing unexpected high-intensity rainfall events. Thus there are needs to enhance conventional disaster management system for comprehensive actions to secure safety. Therefore long-term and comprehensive flood management plans need to be well established. Recently torrential snowfall are occurring frequently, causing have snow traffic jams on the road. To secure safety and on-time operation of the Bi-modal tram system, well-structured disaster management system capable of analyzing the urban flash flooding and snow pack melt/freezing due to unexpected rainfall event and snowfall are needed. To secure safety of the Bi-modal tram system due to torrential snowfall, the snow melt simulation capability was investigated. The snow accumulation and snow melt were measured to validate the SWMM snow melt component. It showed that there was a good agreement between measured snow melt data and the simulated ones. Therefore, the Bi-modal tram disaster management system will be able to predict snow melt reasonably well to secure safety of the Bi-modal tram system during the winter. The Bi-modal tram disaster management system can be used to identify top priority area for snow removal within the tram route in case of torrential snowfall to secure on-time operation of the tram. Also it can be used for detour route in the tram networks based on the disaster management system predicted data.

• Proceedings of the Korea Water Resources Association Conference
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• 2006.05a
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• pp.1876-1879
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• 2006

우리나라의 경우 약 70%가 산악지형이며, 특히 북동부 산악지대의 경우 겨울철에 내린 눈이 봄철까지 쌓여있는 경우가 많기 때문에 수자원의 양적측면의 평가는 겨울철 적설과 융설을 고려하는 것이 필요하다. 본 연구에서는 대표적인 장기유출모형인 SWAT모형을 이용하여 강원도 쌍천유역을 대상으로 적설 및 융설의 영향을 검토하였다. 융설모형을 고려하지 않는 경우에는 강수가 발생하면 그 즉시 유출이 발생하나, 융설모형을 적용하는 경우에는 강설 이후 기온이 상승하여 융설이 된 이후에 유출이 발생하게 된다. 즉, 강원도의 산악지역에서는 적설 및 융설모형의 적용여부에 따라 봄철 가뭄시기에 차이가 발생할 수 도 있다. 실측 유량과 모의를 통해 얻어진 유량을 비교한 결과, 적설 및 융설의 영향을 고려하지 않을 때 보다 고려할 경우가 실측유량과 더 유사한 패턴을 보였다. 유황분석 결과, 적설 및 융설의 영향을 고려하지 않을 때보다 고려할 경우에 하천의 유황이 다소 증가하였다.

• Journal of the Korean Society for Railway
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• v.11 no.5
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• pp.441-448
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• 2008

Increasing urban sprawl and climate changes have been causing unexpected high-intensity rainfall events. Thus there are needs to enhance conventional disaster management system for comprehensive actions to secure safety. Therefore long-term and comprehensive flood management plans need to be well established. Recently torrential snowfall are occurring frequently, causing have snow traffic jams on the road. To secure safety and on-time operation of the Bi-modal tram system, well-structured disaster management system capable of analyzing the show pack melt/freezing due to unexpected snowfall are needed. To secure safety of the Bi-modal tram system due to torrential snow-fall, the snow melt simulation capability was investigated. The snow accumulation and snow melt were measured to validate the SWMM snow melt component. It showed that there was a good agreement between measured snow melt data and the simulated ones. Therefore, the Bi-modal tram disaster management system will be able to predict snow melt reasonably well to secure safety of the Bi-modal tram system during the winter. The Bi-modal tram disaster management system can be used to identify top priority area for know removal within the tram route in case of torrential snowfall to secure on-time operation of the tram. Also it can be used for detour route in the tram networks based on the disaster management system prediction.

• Korean Journal of Remote Sensing
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• v.23 no.6
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• pp.507-520
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• 2007

Satellite passive microwave(PM) sensors have been observing polar sea ice concentration(SIC), ice temperature, and snow depth since 1970s. Among them SIC is playing an important role in the various studies as it is considered the first factor for the monitoring of global climate and environment changes. Verification and correction of PM SIC is essential for this purpose. In this study, we calculated SIC from KOMPSAT-1 EOC images obtained from Arctic sea ice edges from July to August 2005 and compared with SSM/I SIC calculated from NASA Team(NT) algorithm. When we have no consideration of sea ice types, EOC and SSM/I NT SIC showed low correlation coefficient of 0.574. This is because there are differences in spatial resolution and observing time between two sensors, and the temporal and spatial variation of sea ice was high in summer Arctic ice edge. For the verification of SSM/I NT SIC according to sea ice types, we divided sea ice into land-fast ice, pack ice, and drift ice from EOC images, and compared them with SSM/I NT SIC corresponding to each ice type. The concentration of land-fast ice between EOC and SSM/I SIC were calculated very similarly to each other with the mean difference of 0.38%. This is because the temporal and spatial variation of land-fast ice is small, and the snow condition on the ice surface is relatively dry. In case of pack ice, there were lots of ice ridge and new ice that are known to be underestimated by NT algorithm. SSM/I NT SIC were lower than EOC SIC by 19.63% in average. In drift ice, SSM/I NT SIC showed 20.17% higher than EOC SIC in average. The sea ice with high concentration could be included inside the wide IFOV of SSM/I because the drift ice was located near the edge of pack ice. It is also suggested that SSM/I NT SIC overestimated the drift ice covered by wet snow.

• Proceedings of the Korea Water Resources Association Conference
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• 2007.05a
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• pp.1441-1444
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• 2007

It is now widely acknowledged that climate variability modifies the frequency spectrum of hydrological extreme events. Traditional hydrological frequency analysis methodologies are not devised to account for nonstationarity that arises due to variation in exogenous factors of the causal structure. We use Hierarchical Bayesian Analysis to consider the exogenous factors that can influence on the frequency of extreme floods. The sea surface temperatures, predicted GCM precipitation, climate indices and snow pack are considered as potential predictors of flood risk. The parameters of the model are estimated using a Markov Chain Monte Carlo (MCMC) algorithm. The predictors are compared in terms of the resulting posterior distributions of the parameters associated with estimated flood frequency distributions.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.19 no.6
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• pp.698-705
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• 2008

When electromagnetic waves propagate through atmosphere, waves are affected by various factors. Atmosphere normally consists of different molecular species, water vapours, rain, fog, snow and small suspended particles called aerosols. The distributions of atmosphere molecules, water vapours, rain rate, snowfall and aerosol are dependent on geometrical regions or environment. In order to predict propagation characteristics in atmospheric environment, statistical analysis of the relevant parameters such as temperature, humidity, atmospheric pressure, wind speed, areosol and rainfall is crucial. In this paper, we performed a long-term statistical analysis for the atmospheric parameters in domestic environments and analyzed the propagation characteristics through atmosphere based on that.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.12 no.1
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• pp.24-31
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• 2007

Global fates of polychlorinated biphenyl(PCB) were investigated with a fugacity based multimedia transport and fate model, Globe-POP(persistent organic pollutant). The accumulation of PCB was directly affected by the emission patterns of PCB into the atmosphere and surface areas of environmental compartments. Partition coefficients and reaction rates also influenced on the accumulation patterns of PCB. The emission patterns of PCB in 10 climate zones were consistent for the past 70 years, while the contribution of PCB in high-latitude zones to the globe has increased by cold condensation. Considering the amounts of emission and accumulation of PCB, the North temperature zone is regarded as an important source and sink of PCB. Meanwhile, in spite of no significant sources, POPs accumulate in Antarctic environments mainly due to extremely low temperature. Finally we suggested that a global water balance accounting for snow/ice should be incorporated into multimedia environmental models for high-latitude zones and polar regions with the seasonal snow pack and/or permanent ice caps. The modified model will be useful to evaluate the influence of climate change on the fate of POPs.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37C no.9
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• pp.811-820
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• 2012

GNSS signal is vulnerable to jamming signal because of well-known signal structure and weak signal power. For these reasons, the need for analysis of jamming effects and anti-jamming techniques of is increasing. In this paper, a GNSS signal generator is designed which includes a radio wave propagation model for six kind of tactical environments and a body masking model for the reception environment of a vehicle. The radio wave propagation model for downtown, rural, forest, coastline, waste land and snow or ice area is designed using two-ray model. The body masking model is designed the effect which the antenna is affected by the reception environment of a vehicle and radiation pattern from a user configuration. The performance of generated signals from the GNSS signal generator considering reception environment of a vehicle is evaluated by a commercial GPS L1 receiver(NordNav) in normal and jamming environment. Also, the generated GNSS signal is compared to a commercial GPS L1 H/W based RF signal generator(STR4500). The results show that the designed GNSS signal generator in a normal environment compared to the same navigation performance. In jamming environment, it is shown that the body masking effect and GNSS signal acquisition and tracking loss in compliance with the jamming signal are precisely working in the reception environment of a vehicle.