• Journal of the Korean Association of Geographic Information Studies
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• v.14 no.3
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• pp.188-202
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• 2011

Due to emissions of greenhouse gases caused by increased use of fossil fuels, the climate change has been detected and this phenomenon would affect even larger changes in temperature and precipitation of South Korea. Especially, the increase of temperature by climate change can affect the amount and pattern of snowfall. Accordingly, we tried to predict future snowfall and the snowfall pattern changes by using the downscaled GCM (general circulation model) scenarios. Causes of snow varies greatly, but the information provided by GCM are maximum / minimum temperature, rainfall, solar radiation. In this study, the possibility of snow was focused on correlation between minimum temperatures and future precipitation. First, we collected the newest fresh snow depth offered by KMA (Korea meteorological administration), then we estimate the temperature of snow falling conditions. These estimated temperature conditions were distributed spatially and regionally by IDW (Inverse Distance Weight) interpolation. Finally, the distributed temperature conditions (or boundaries) were applied to GCM, and the future snowfall was predicted. The results showed a wide range of variation for each scenario. Our models predict that snowfall will decrease in the study region. This may be caused by global warming. Temperature rise caused by global warming highlights the effectiveness of these mechanisms that concerned with the temporal and spatial changes in snow, and would affect the spring water resources.

• International Journal of Highway Engineering
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• v.15 no.2
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• pp.19-27
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• 2013

PURPOSES : This study aims to investigate the snow-melt effects of an underground electric heater's snow-melt system via a field performance test, for evaluating the suitability of the system for use on a concrete pavement. The study also investigates the effectiveness of dynamic measures for clearing snow after snowfall events. METHODS : In order to check the field applicability, in November 2010, specimens were prepared from materials used for constructing concrete pavements, and underground electric heating meshes (HOT-mesh) were buried at depths of 50 mm and 100 mm at the site of the Incheon International Airport Construction Research Institute. Further, an automatic heating control system, including a motion sensor and pavement-temperature-controlled sensor, were installed at the site; the former sensor was intended for determining snow-melt effects of the heating control system for different snowfall intensities. Pavement snow-melt effects on snowy days from December 2010 to January 2011 were examined by managing the electric heating meshes and the heating control system. In addition, data on pavement temperature changes resulting from the use of the heating meshes and heating control system and on the dependence of the correlation between the outdoor air temperature and the time taken for the required temperature rise on the depth of the heating meshes were collected and analyzed. RESULTS : The effects of the heating control system's preheat temperature and the hot meshes buried at depths of 50 mm and 100 mm on the melting of snow for snowfalls of different intensities have been verified. From the study of the time taken for the specimen's surface temperature to increase from the preheat temperature ($0^{\circ}C$) to the reference temperature ($5{\sim}8^{\circ}C$) for different snowfall intensities, the correlation between the burial depth and outdoor air temperature has been determined to be as follows: Time=15.10+1.141Depth-6.465Temp CONCLUSIONS : The following measures are suggested. For the effective use of the electric heating mesh, it should be located under a slab it may be put to practical use by positioning it under a slab. From the management aspect, the heating control system should be adjusted according to weather conditions, that is, the snowfall intensity.

• Journal of Korean Society of Forest Science
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• v.106 no.1
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• pp.63-69
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• 2017

This study aimed to investigate orographic precipitation and green dam (water conservation function) characteristics in a deciduous forest watershed in the region of Mt. Ungseok, Sancheong, Gyeongnam, South Korea. The rainfall and runoff of the watershed were monitored for six years (2011~2016) at the weather station and at the weir of the watershed, respectively. During the study period, the rainfall in the watershed (mountainous area) was larger than that of the meteorological station (flat area) nearest to the watershed. Besides, compared to the normal year (1981~2010), the rainfall has increased and the seasonal distribution of rainfall of the mountainous area has changed. These changes might have been caused by climate change. The runoff ratio was highest in spring, followed by winter, summer and fall, whilst the runoff was highest in summer, followed by spring, fall and winter. This difference seems to be due to the melting of snow in dry spring and intensive rainfall in summer. The total runoff in the watershed was calculated as $10,143.8ton{\cdot}ha{\cdot}yr^{-1}$.

• Korean Journal of Soil Science and Fertilizer
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• v.32 no.1
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• pp.31-38
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• 1999

Rainfall factor. R, and soil factor, K were estimated to use the Revised Universal Soil Loss Equation (RUSLE) to predict the amount of soil erosion from a land on slope in Kangwon-do, Korea. The average of R factor was 405 with a range from 251 to 601. The R factor differed among regions. The R factor at Taegwalryung, in the highland region, was 409 and those at Inje and Hongchon, in the mid mountainous regions, ranged from 310 to 493. The R factors at Wonju and Chuncheon, in the plain regions, ranged from 505 to 601. The R factors at Sokcho, Kangnung and Samchok, in the east coastal region, which ranged from 251 to 368, were lowee than those in the western part of the Taebaeg Mountains. The R factor during the winter including the effect of winter freezing and thawing was 12 to 30% of the annual average value in the east coastal and highland regions, while that in the western part of Taebaeg Mountains was lower than 7%. The average of K factor in the surface soil was 0.21 with a range from 0.06 to 0.42. The K factors of Odae and Weoljeong serieses were the lowest, while that of Imog was the highest. The average of K factor in the subsoil was 0.28 with a range from 0.07 to 0.45. The K factor of the subsoil was 1.3 times higher than that of top soil. The average of K factor in he soil including the effect of the gravel covering and percolation was 0.18 with a range from 0.03 to 0.33. In contrast. the K factor excluding the effect of the gravel covering was lower than this. The average of K factor in the frozen subsoil was 0.33, which was 1.6 times higher than that of the non frozen subsoil.