• Proceedings of the Korean Society of Disaster Information Conference
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• 2017.11a
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• pp.362-363
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• 2017

최근 기후변화에 따라 여름철 태풍, 호우와 겨울철 대설, 한파 등의 기상재난이 증가하고 있다. 대설재난은 교통, 건물, 시설물 등에 다양한 피해를 발생시키기 때문에 신속한 대처가 필요하다. 대설재난이 도시안전에 영향을 주고 있으나 우리나라의 대설재난 대처는 미흡하고, 정책 연구도 부족한 상황이다. 본 연구는 대설재난이 발생할 때 신속한 도로 제설을 위하여 제설차량과 장비에 GPS 기술을 활용한 사례를 분석하고, 시사점을 도출한다. 도로 제설장비에 GPS 장비를 부착하면 긴급 상황시 제설차량과 장비의 위치를 파악하여 인근지역의 도로 제설을 응원할 수 있다. 본 연구의 사례 분석은 향후 지자체 제설장비의 효율적 이용을 위해 활용될 수 있다.

• 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 Korea Water Resources Association
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• v.53 no.4
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• pp.259-271
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• 2020

In Korea, snow damage has happened in the region with little snowfalls in history. Also, accidental damage was caused by heavy snow leads and the public interest on heavy snow has been increased. Therefore, policy about the Natural Disaster Reduction Comprehensive Plan has been changed to include the mitigation measures of snow damage. However, since heavy snow damage was not frequent, studies on snowfall have not been conducted on different points. The characteristics of snow data commonly are not the same as the rainfall data. Some southern coastal areas in Korea are snowless during the year. Therefore, a joint probability distribution was suggested to analyze the snow data with many 0s in a previous research and fitness from the joint probability distribution was higher than the conventional methods. In this study, snow frequency analysis was implemented using the joint probability distribution and compared to the design codes. The results were compared to the design codes. The results of this study can be used as the basic data to develop a procedure for the snow frequency analysis in the future.

• Korean Journal of Agricultural and Forest Meteorology
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• v.22 no.2
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• pp.92-101
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• 2020

To prevent and mitigate damage to farms due to heavy snowfall, snow weight information should be provided in addition to snow depth. This study reviews four formulae regarding snow density and weight used in extant studies and applies them in Suwon area to estimate snow weight in Korea. We investigated the observed snow depth of 94 meteorological stations and automatic weather stations (AWS) data over the past 30 years (1988-2017). Based on the spatial distribution of snow depth by area in Korea, much of the fresh snow cover, due to heavy snowfall, occurred in Jeollabuk-do and Gangwon-do. Record snowfalls occurred in Gyeongsangbuk-do and Gangwon-do. However, the most recent heavy snowfall in winter occurred in Gyeonggi-do, Gyeongsangbuk-do, and Jeollanam-do. This implies that even if the snow depth is high, there is no significant damage unless the snow weight is high. The estimation of snow weight in Suwon area yielded different results based on the calculation method of snow density. In general, high snow depth is associated with heavy snow weight. However, maximum snow weight and maximum snow depth do not necessarily occur on the same day. The result of this study can be utilized to estimate the snow weight at other locations in Korea and to carry out snow weight prediction based on a numerical model. Snow weight information is expected to aid in establishing standards for greenhouse design and to reduce the economic losses incurred by farms.

• Disaster Prevention Review
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• v.17 no.5
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• pp.18-28
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• 2015

• Water for future
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• v.51 no.9
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• pp.46-52
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• 2018

• Water for future
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• v.55 no.10
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• pp.72-79
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• 2022

• Water for future
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• v.57 no.1
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• pp.6-15
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• 2024

• Proceedings of the Korea Water Resources Association Conference
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• 2016.05a
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• pp.205-205
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• 2016

우리나라의 겨울철 자연재해 중 대설에 의한 피해가 발생하는 빈도가 증가하고 있는 가운데 그 피해를 예측하고 대비하기 위한 연구들이 다수 진행되고 있다. 강설은 일단위로 측정하며, 매일 새롭게 내린 강설의 양인 최심신적설과 기존에 녹지 않고 쌓여 있던 깊이까지를 고려한 최심적설로 구분된다. 우리나라의 경우에는 갑작스럽게 내린 폭설에 의한 피해가 대부분이므로 최심신적설량을 예측하는 것이 매우 중요하다. 이에 본 연구에서는 다중회귀분석을 이용해 우리나라의 최심신적설량을 추정하기 위한 식을 개발하였다. 다중회귀분석을 위한 독립변수로는 해당 일에 예측된 강수량, 일평균기온, 일최고기온, 일최저기온을 사용하였으며, 강수량과 일평균기온의 상호작용을 고려할 수 있도록 모형을 구성하였다. 모형의 개발에는 전국 74개 기상관측소의 최심신적설 자료를 관측소 단위로 전체 자료의 2/3을 무작위로 추출하여 이용하였으며, 추출되지 않고 남은 1/3의 자료를 이용해 모형에 대한 검증을 실시하였다. 그 결과 상호작용항이 포함되지 않은 다중선형회귀모형에 비해 상호작용을 고려한 다중회귀모형의 예측력이 훨씬 우수하게 나타났다. 강수량과 기온이 정확하게 예측된다면 개발된 추정식을 이용해 간편하게 최심신적설량을 예측할 수 있어, 폭설에 대한 대비에 활용할 수 있을 것으로 판단된다.

• Water for future
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• v.57 no.1
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• pp.16-22
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• 2024