• 설비공학논문집
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• 제11권1호
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• pp.38-47
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• 1999

An improved one-dimensional modeling of snow melting was obtained by considering both the effect of heat capacity and the decreasing influence of porosity. Using the improved model, the effects of initial snow temperature, initial snow density and the heat flux on the snow melting were investigated. It is found that the drainage starting time is delayed and the drainage rate becomes smaller with lower initial snow temperature. ResuIts also show that the drainage starts at the same time when an initial snow density is over a certain value. Melting efficiency increases linearly with an increasing initial snow temperature. With increasing the initial density of the snow and the amount of heat supplied, the melting efficiency increases, then converges to a constant value.

• 설비공학논문집
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• 제12권6호
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• pp.599-608
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• 2000

One dimensional numerical modeling was carried out for the melting behavior of dry snow and the unsaturated flow when heat was supplied from the bottom surface. Discrepancy between the previous experimental data and the present numerical results is substantially reduced by considering the density change of water permeation layer due to the infiltration of meltwater. In the parametric study for effective thermal conductivity, it was found that the effect of this parameter to the behavior of snow melting is minor. Sensitivity analysis showed that the melting time is most sensitive to changes in supplied heat flux, snow temperature, and bulk density, whereas snow bulk density and residual saturation have a significant effect on the height of water permeation layer in snow.

• Wind and Structures
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• 제23권6호
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• pp.523-542
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• 2016

Snowdrift formation on roofs should be considered in snowy and windy areas to ensure the safety of buildings. Presently, the prediction of snowdrifts on roofs relies heavily on field measurements, wind tunnel tests and numerical simulations. In this paper, a new snowdrift modeling method by using CFD (Computational Fluid Dynamics) coupled with DEM (Discrete Element Method) is presented, including material parameters and particle size, collision parameters, particle numbers and input modes, boundary conditions of CFD, simulation time and inlet velocity, and coupling calculation process. Not only is the two-way coupling between wind and snow particles which includes the transient changes in snow surface topography, but also the cohesion and collision between snow particles are taken into account. The numerical method is applied to simulate the snowdrift on a typical stepped flat roof. The feasibility of using coupled CFD with DEM to study snowdrift is verified by comparing the simulation results with field measurement results on the snow depth distribution of the lower roof.

• 대한원격탐사학회지
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• 제29권3호
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• pp.315-324
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• 2013

Spatial information of snow cover and depth distribution is a key component for snowmelt runoff modeling. Wide snow cover areas can be extracted from NOAA AVHRR or Terra MODIS satellite images. In this study eight sets of annual snow cover data (1997-2006) in two mountainous watersheds (A: Chungju-Dam and B: Soyanggang-Dam) were extracted using NOAA AVHRR images. The distribution of snow depth within the Snow Cover Area (SCA) was generated using snowfall data from ground meteorological observation stations. Snow depletion characteristics for the two watersheds were analyzed snow distribution time series data. The decreased pattern of SCA can be expressed as a logarithmic function; the determination coefficients were 0.62 and 0.68 for the A and B watersheds, respectively. The SCA decreased over 70% within 10 days from the time of maximum SCA.

• 대기
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• 제25권1호
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• pp.155-167
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• 2015

A dynamical seasonal prediction system for boreal winter utilizing cryospheric information was developed. Using the Community Atmospheric Model, version3, (CAM3) as a modeling system, newly developed snow depth initialization method and sea ice concentration treatment were implemented to the seasonal prediction system. Daily snow depth analysis field was scaled in order to prevent climate drift problem before initializing model's snow fields and distributed to the model snow-depth layers. To maximize predictability gain from land surface, we applied one-month-long training procedure to the prediction system, which adjusts soil moisture and soil temperature to the imposed snow depth. The sea ice concentration over the Arctic region for prediction period was prescribed with an anomaly-persistent method that considers seasonality of sea ice. Ensemble hindcast experiments starting at 1st of November for the period 1999~2000 were performed and the predictability gain from the imposed cryospheric informations were tested. Large potential predictability gain from the snow information was obtained over large part of high-latitude and of mid-latitude land as a result of strengthened land-atmosphere interaction in the modeling system. Large-scale atmospheric circulation responses associated with the sea ice concentration anomalies were main contributor to the predictability gain.

• 한국농공학회논문집
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• 제64권6호
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• pp.35-41
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• 2022

Heavy snow damage can be prevented in advance with an appropriate security system. To develop the security system, we developed a model that predicts snow depth after a few hours when the snow depth is observed, and utilized it to calculate a failure probability with various types of greenhouses and observed snow depth data. We compared the Markov chain model and Bayesian long short-term memory models with varying input data. Markov chain model showed the worst performance, and the models that used only past snow depth data outperformed the models that used other weather data with snow depth (temperature, humidity, wind speed). Also, the models that utilized 1-hour past data outperformed the models that utilized 3-hour data and 6-hour data. Finally, the Bayesian LSTM model that uses 1-hour snow depth data was selected to predict snow depth. We compared the selected model and the shifting method, which uses present data as future data without prediction, and the model outperformed the shifting method when predicting data after 11-24 hours.

• Water Engineering Research
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• 제1권1호
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• pp.25-37
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• 2000

This study presents some results of a preliminary study for the coupled precipitation and river flow prediction system. The model system in based on three numerical models, Mesoscale Atmospheric Simulation model for generating atmospheric variables. Soil-Plant-Snow model for computing interactions within soil-canopy-snow system as well as the energy and water exchange between the atmosphere and underlying surfaces, and TOPMODEL for simulating stream flow, subsurface flow, and water tabled depth in an watershed. The selected study area is the 2,703 $\alpha_4$ $\km_2$ Soyang River basin with outlet at Soyang dam site. In addition to providing the results of rainfall and stream flow predictions, some results of DEM and GIS application are presented. It is obvious that the accurate river flow predictions are highly dependant on the accurate predictation predictions.

• 자원환경지질
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• 제54권1호
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• pp.61-67
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• 2021

고체상의 눈 또는 얼음의 안정동위원소 값은 과거의 기후를 복원하고 동위원소 수문분리의 단성분으로 기여율을 계산하는 데에 사용되어 왔다. 융해와 냉동이 일어나면서 눈 또는 얼음과 액체상의 물 사이의 동위원소 분별작용이 일어나는데, 융해는 상대적으로 현장, 실험 및 모델연구를 통해 연구결과가 제시되어 있지만, 냉동에 대해서는 알려진 것이 많지 않다. 본 논평에서는 평형 냉동이 발생할 때 물의 두 안정동위원소인 산소, 수소의 선형관계 및 레일리분별과정을 통해 냉동에 의한 동위원소 분별과정을 고찰하였다. 해양에서 증발한 수증기에 의해 응축된 눈은 기울기 8을 가지는 지구천수선을 따라 움직이지만, 냉동 및 융해가 발생하게 되면 기울기 19.5/3.1~6.3을 가지는 선형관계를 나타내게 된다. 평형냉동 동안 레일리분별과정에 의해 액체상인 물은 열린 계와 닫힌계에서 같은 동위원소변동을 보여 주었다. 눈 또는 얼음이 제거되는 열린 계에서는 남아있는 물의 안정동위원소와 분별계수만큼의 차이를 가지면서 높은 값을 나타내었다. 닫힌 계에서는 초기 액체상의 물의 동위원소 값으로 눈 또는 얼음은 수렴하였다. 냉동에 의한 눈 또는 얼음의 동위원소변동과정은 고기후 연구 및 수문분리의 정확도를 증가시킬 것으로 기대된다.

• 한국습지학회지
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• 제10권1호
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• pp.1-9
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• 2008

본 연구에서는 융설을 고려할 수 있는 물수지 모형인 WASMOD(Water And Snow MODeling system)에 대하여 기술하였으며, 소양강댐 상류유역에 적용하여 장기 월 유출량을 산정하였다. WASMOD의 장점은 입력자료의 구축이 간단하며 사용자가 쉽게 운영할 수 있다는 점이다. 모형의 매개변수를 최적화하기 위해 자동추적법인 VA05A를 이용하였으며, 관측 월 유출 수문곡선과 모의 월 수문곡선을 비교하였다. 관측 유출량과 계산 유출량간의 상관계수가 0.89이상으로, 이를 통해 WASMOD의 국내 유역에 적용가능성을 확인할 수 있었다.

• 아태비즈니스연구
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• 제13권1호
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• pp.317-333
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• 2022

Purpose - The purpose of this study is to investigate the interrelationships between visitor motivations, attitude, and behavioral intention toward the Harbin International Ice and Snow Festival, China. It is also to test moderating roles of gender and past travel experience between these factors. Design/methodology/approach - Data was collected from potential Chinese visitors, after which 420 usable surveys were processed. Findings - To investigate our hypotheses, we used descriptive, confirmatory factor analysis, and structural equation modeling. We found that aesthetic attractiveness, purchase of local products, and involvement had positive effects on attitude toward the festival. Attitude toward the festival had a significant effect on behavioral intention to visit. Finally, it was also found that gender and past travel experience significantly moderated the interrelationships between these factors. Research implications or Originality - Theoretical and managerial implications, as well as, suggestions for future research are discussed.