• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.11 no.1
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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.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.12 no.6
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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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• v.23 no.6
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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.

• Korean Journal of Remote Sensing
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• v.29 no.3
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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.

• Atmosphere
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• v.25 no.1
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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.

• Journal of The Korean Society of Agricultural Engineers
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• v.64 no.6
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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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• v.1 no.1
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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.

• Economic and Environmental Geology
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• v.54 no.1
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• pp.61-67
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• 2021

Isotopic compositions of snow or ice have been used to reconstruct paleoclimate and to calculate contribution to streamwater using isotopic hydrograph separation as an end member. During freezing and melting of snow or ice, isotopic fractionation occurs between snow or ice and liquid water. Isotopic evolution during melting process has been studied by field, melting experiments and modeling works, but that during freezing has not been well studied. In this review, isotopic fractionation during equilibrium freezing is discussed using the linear relationship between two stable water isotopes (oxygen and hydrogen) and the Rayleigh fractionation. Snow, evaporated from nearby ocean and condensated, follows the Global Meteoric Water Line (slope of 8), but the melting and freezing of snow affect the linear relationship (slope of 19.5/3.1~6.3). The isotopic evolution of liquid water by freezing observed in the open system during Rayleigh fractionation is also seen in the closed system. The isotopic evolution of snow or ice in the open system where the snow or ice is continuously removed becomes more enriched than the residual liquid water by the fractionation factor. The isotopic evolution of snow or ice in the closed system eventually equals the original isotopic compositions of liquid water. It is expected the understanding of isotopic evolution of snow or ice by freezing to increase the accuracy of the paleoclimate studies and hydrograph separation.

• Journal of Wetlands Research
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• v.10 no.1
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• pp.1-9
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• 2008

This study describes the WASMOD, water balance model which can consider the snowmelting. The pilot study basin is the Soyang River basin with outlet at Soyang Dam Site and compute long-term monthly streamflow, The advantage of the WASMOD is that the input data is simple and the user can operate easily. To optimize for the parameters of the model, the WASMOD used VA05A of automatic fitting technique. The observed and simulated monthly streamflow hydrographs were compared. The model performance on corrleation coefficient between the observed and the simulated streamflow for the verification periods was above 0.89. It was shown that the WASMOD reproduces the observed monthly streamflow hydrographs very well. This evidence suggests that the WASMOD might be appropriate for the simulation of monthly streamflow

• Asia-Pacific Journal of Business
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• v.13 no.1
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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.