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황보종구,홍준혁,Hwang-Bo, Jong Gu,Hong, Jun Hyuk 한국수자원학회 2022 한국수자원학회논문집 Vol.55 No.10
The water level of the dam reservoir is an important data in the operation of the dam. reservoir storage can be calculated by using water levels or prepared for disasters such as drought and floods. However, the water level is measured near the dam, making it difficult to represent a reservoir with a large area, and there is a high possibility that the water surface will be distorted due to discharge. Furthermore, the results of the survey showed that the water level of the reservoir is irregular rather than constant, and the water level of the reservoir is repeatedly falling and rising by section. In order to calculate such a complex and irregular representative water level, the water level observation density of the reservoir must be increased. In this study, we tried to derive the optimum water level observation density for Hwacheon Dam. A reasonable water level measurement density was derived by investigating the water level elevation of the reservoir and statistically analyzing it. The observation density may vary depending on the size of the reservoir, so the same analysis was conducted on the Goesan Dam and Boseonggang Dam. According to the results, four Hwacheon dams, three Goesan dams, and seven Boseong River dams are needed for observation density.
미래 기후변화로 인해 발생하는 항공기 결항 및 경제적 손실 전망
이호용(Hoyong Lee ),김경훈(Kyunghun Kim),황보종구(Jong Gu Hwang-Bo),김수전(Soojun Kim) 한국방재학회 2022 한국방재학회논문집 Vol.22 No.5
항공운송산업은 국내⋅외 관광뿐만 아니라 항공물류의 발달로 수요가 증가함으로 생활에서 중요한 역할을 하고 있다. 하지만기후변화로 인한 극한기상이 빈번하게 발생하여 항공기의 운항에 막대한 악영향을 주고 있다. 기후변화로 인한 극한기상은더 심각해질 것으로 예상되는 만큼 결항에 대한 피해 대책이 필요하다. 따라서 본 연구에서는 국내선을 운영하는 13개의공항과 6개의 항공사를 대상으로 미래의 결항 횟수와 그에 따른 경제적 손실을 산정하였다. 이를 위해 SSP (Shared Socioeconomic Pathways) 시나리오를 이용하여 공간적 축소기법과 시간적 축소기법을 적용하였다. 공간적 축소는 머신러닝을 활용하였고, 시간적 축소는 최근린 방법과 유전자 알고리즘을 이용하였다. 그 결과 시나리오에 따라 강우강도는 먼 미래(2081~2100년도)에2.02배에서 3.54배 증가하였고, 풍속은 최소 1.16배에서 최대 1.24배의 증가하는 것으로 나타났다. 이에 따라 항공기 결항기준에 따른 결항의 경제적 손실은 최대 약 8.29배의 증가가 발생하는 것을 확인할 수 있었다. 이를 통해서 항공 산업에서의기후변화에 대한 대비 및 대응 대책의 필요성을 제시하고자 하였다. The aviation industry plays an important role in daily life because of the increase of demand attributable to the development of air logistics as well as domestic and foreign tourism. However, the higher frequency of extreme weather caused by climate change has a large adverse effect on the operation of aircraft. As this effect is expected to increase, measures to reduce flight cancellation are needed. Therefore, in this study, the number of future flight cancellations and related economic losses were calculated for 1 3 domestic airports and six domestic airlines. To calculate the future climate of the airports, we used the recently released Shared Socioeconomic Pathways (SSP) climate change scenario. Then, we applied machine learning and the nearest neighbor with genetic algorithm method for spatial and temporal downscaling, respectively. The calculated results were applied to aircraft cancellation criteria and a damage estimation formula. Depending on the scenario, rainfall intensity increased by 2.02 to 3.54 times and wind speed increased by 1.16 to 1.24 times during 2100 to 2081. Economic losses from aircraft cancellations attributable to future climate increased by up to approximately 8.29 times. The results of this study highlight the necessity of preparing for and responding to climate change within the airline industry.