• Journal of the Society of Disaster Information
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• v.13 no.3
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• pp.340-347
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• 2017

This study deducted institutional improvement factors for respond of heavy snowfall disaster and performed AHP analysis for choosing the priority. The result of Analysis, establishment of plan concerned heavy snowfall respond was represented most important factor(Importance : 0.461), this is meaningful establishment of plan is more important than facilities, sources, policies for building system of heavy snowfall respond. Establishment of plan concerned respond was represented most important element(Comprehensive Importance : 0.175) in plan for heavy snowfall respond, it is suggested that establishment of respond plan of heavy snowfall has to need for improving law and institution about heavy snowfall. The result of this study will be useful when the central or local government establish institutional improvement plan for respond of heavy snowfall disaster.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.2
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• pp.125-136
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• 2018

Heavy snowfall disasters are the third most serious natural disasters, after typhoon and heavy rainfall disasters, in terms of economic disaster damage in South Korea. The average annual economic damage of heavy snowfall disasters was approximately eighty-eight billion won during the period of 2005-2014. In spite of significant economic damage, there have been few economic studies regarding heavy snowfall disasters in South Korea. The objective of this research is to identify the association between economic damage of heavy snowfall disasters and damage effect factors of snowfall amounts, snowfall days, population densities, and non-urban area ratios using a regression analysis model. Economic damage data sets of heavy snowfall disasters during the period of 2005-2014 were obtained from the Natural Disaster Yearbook published by the Ministry of Public Safety and Security. Weather-related data sets, such as snowfall amounts and snowfall days were collected from the Korea Meteorological Administration. Demographic and urban data sets, including population densities and non-urban area ratios, were provided by the Local Government Yearbook. Outcomes of this study can assist with heavy snowfall disaster management policies of South Korea.

• Journal of Korea Planning Association
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• v.53 no.6
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• pp.117-130
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• 2018

Heavy snow is a natural disaster that causes serious economic damage. Since snowfall has been increasing recently, there is a need for measures against heavy snowfall. In order to make a policy decision on heavy snowfall, it is necessary to estimate the precise amount of damage by heavy snowfall. The direct damage of the heavy snow is severe, however the indirect damage caused by the road congestion and the urban dysfunction is also serious. Therefore, it is necessary to estimate indirect damage of snowfall. The purpose of this study is to estimate the effects on the regional economy from the limitation in traffic logistics caused by heavy snow using the transport demand model and inoperability input-output Model. The result shows that the amount of production loss caused by the heavy snow is KRW 2,460 billion per year and if the period of snowfall removal is shortened by one day or two days, it could be reduced to KRW 1,219 or 2,787 billion in production loss.

• Journal of the Society of Disaster Information
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• v.14 no.2
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• pp.154-164
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• 2018

Purpose: Recent climate change makes weather-related disasters such as summer storms, heavy rains, winter snowfall disasters, and extreme cold temperature increase in trend. Heavy snowfall disasters requires speedy response due to various effects to traffic flows, buildings, and infrastructure. Heavy snowfall disaster response of South Korea is insufficient, even though heavy snowfall disasters affect urban safety. There have been lack of policy studies for heavy snowfall disasters. Method: This research analyzes case studies and explores implications using Information system technologies to snow removal vehicles and equipments for speedy snow removal during the heavy snowfall disasters. Results: Information system technology attachment to snow removal equipments can identify locations of snow removal vehicles and equipments for emergency period to support snow removal of adjacent jurisdictions. Conclusion: Case studies of this research can be further used for efficient application of snow removal tools of local governments.

• Journal of the Society of Disaster Information
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• v.16 no.1
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• pp.21-33
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• 2020

Purpose: The objective of this research is to classify snowfall area types with consideration of past regional snowfall characteristics and times for the effective local snow removal response systems of 229 local government districts. Method: This research first collected snowfall data of South Korea meteorological stations, and classified regional types using successive snowfall time. This research finally produced GIS maps using regional type information of snowfalls by applying GIS analysis methods. Result: This research provides five types of snowfall regions including 'frequent heavy snowfall regions', 'frequent light snowfall regions', 'rare heavy snowfall regions', 'average snowfall regions', and 'rare light snowfall regions' based on analysis results. Conclusion: Results of this research can be used as basic information for regional demand estimations of snow removal equipments, materials, vehicles, and personnel for the efficient snow removal response systems.

• Journal of the Korean Geographical Society
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• v.43 no.6
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• pp.843-857
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• 2008

This study analyzed distribution of natural disaster and trend of related climatic elements in mountainous region of Gangwon-do. In mountainous region of Gangwon-do, there have been 27 natural disasters of which heavy rainfall have the leading cause for the last 5 years(16 times in 2003-2007). It has been 9 natural disasters in Jinbu-myeon Pyeongchang-gun, the most frequent area. The mountainous region has been larger natural damage than its surrounding regions and there has been more damage at higher altitudes. While the heavy rainfall have caused damage over the northwest of mountains, most typhoons have damaged southern part of mountains. Most mountainous region suffers from strong wind but damage by snow is small. In mountainous region of Gangwon-do, annual precipitation, intensity of precipitation and heavy rainfall days have been increasing since 2000 and this tendency is significant in its intensity. However, annual snowfall, snowfall days and heavy snowfall days have been clearly decreasing since 2000. In case heavy rainfall accompanies strong wind, the damages are larger in mountainous region of Gangwon-do. Therefore it is important to be prepared for heavy rainfall and strong wind.

• Journal of Environmental Science International
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• v.16 no.12
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• pp.1439-1449
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• 2007

Heavy snowfall was occurred over the south-western part of the Korean Peninsula called as Honam Districts, on two days from 21 December 2005. The development mechanism of snowfall and its characteristics were analysed using observation and numerical data provided by Korea Meteorological Administration. In comparison with other years Arctic air mass developed and maintained during all December 2005 due to active planetary waves with three branches. And jet streams at lower and higher levels make easy development of snow convection cells. Especially thermal low induced by mesoscale heat and dynamic sources, also help the developments of convection cells in strong ascension. The understanding the relation between synoptic and mesoscale circumstance, therefore, is also important to predict the heavy snowfall and to prevent the disaster.

• Journal of the Society of Disaster Information
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• v.13 no.2
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• pp.199-212
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• 2017

Rapid roadway snow removal is significantly important due to difficult occurrence estimation of heavy snowfall disasters by global warming and climate change. Local governments of S. Korea have snow removal equipments and vehicles based on past experiences without considering snowfall and roadway characteristics. The objective of this research is to develop the demand estimation procedure for snow removal equipments and vehicles based on regional snowfall and roadway characteristics. This research first classifies regional snowfall characteristics using KMO's ten-year snowfall data. Second, roadway snow removal length is computed for local governments. Real possession data is compared with demand estimation of snow removal equipments & vehicles for each local government with roadway snow removal scenarios. Finally, required demands of snow removal equipments & vehicles are predicted by concerning regional snowfall amount and required snow removal hours. Results from this research are used for developing heavy snowfall disaster management policies for optimal demands and snow removal routes of 229 local governments.

• Journal of the Society of Disaster Information
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• v.11 no.1
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• pp.23-34
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• 2015

This Study analyzed heavy snow properties according to the area that was based by winter weather properties and the damage data by the heavy snow among each local government of Chungcheongbuk-do. The result of analysis, Jecheon-si and Boeun-gun are represented the highest dangerous regions by potential degree of risk by average amount of snowfall for 35 years. But, the potential degree of risk by maximum amount of snowfall for 35 years is different with it. Cheongju-si and Youngdong-gun, Goesan-gun, Boeun-gun are represented the highest dangerous regions. Examining the frequency of regions with potential danger factors according to the characteristics of heavy snowfall, Boeun-gun and Jecheon-si, Goesan-gun, Youngdong-gun, Cheongju-si is derived the highest dangerous regions in Chungcheongbuk-do.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.35 no.3
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• pp.545-556
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• 2015

This study is to project the future snowfall and to assess heavy snowfall vulnerable area in South Korea using ground measured snowfall data and RCP climate change scenarios. To identify the present spatio-temporal heavy snowfall distribution pattern of South Korea, the 40 years (1971~2010) snowfall data from 92 weather stations were used. The heavy snowfall days above 20 cm and areas has increased especially since 2000. The future snowfall was projected by HadGEM3-RA RCP 4.5 and 8.5 scenarios using the bias-corrected temperature and snow-water equivalent precipitation of each weather station. The maximum snowfall in baseline period (1984~2013) was 122 cm and the future maximum snow depth was projected 186.1 cm, 172.5 mm and 172.5 cm in 2020s (2011~2040), 2050s (2041~2070) and 2080s (2071~2099) for RCP 4.5 scenario, and 254.4 cm, 161.6 cm and 194.8 cm for RCP 8.5 scenario respectively. To analyze the future heavy snowfall vulnerable area, the present snow load design criteria for greenhouse (cm), cattleshed ($kg/m^2$), and building structure ($kN/m^2$) of each administrative district was applied. The 3 facilities located in present heavy snowfall areas were about two times vulnerable in the future and the areas were also extended.