The study uses a regional climate model to check future changes in extreme climate, to calculate extreme indexes presented by STARDEX, and to analyze the trends to predict the continuity and changes in the spatial distribution of extreme climate in the future. An analysis of extreme climate indices showed that they are likely to increase in the Seoul metropolitan area, in Gyeonggi-do, in Yongdong in Gangwon-do, and in the southern shore region of Korea. It is, however, forecasted to diminish in the central inland region. The analysis also showed that the average temperature in Korea will increase because of climate change. On the other hand, an analysis of extreme rainfall indexes showed that the trend of heavy rainfall threshold is 0.229 in Seogwipo, the greatest five-day rainfall is 5.692 in Seogwipo, and the longest dry period is 0.099 in Sokcho. Of extreme temperature indexes, the trend of Hotdays threshold is 0.777 in Incheon and the longest heat wave is 0.162 in Uljin. The Coldnight threshold is 0.075 in Inje and -0.193 in Tongyeong, according to the analysis.
The standardized precipitation index (SPI) was developed based on the fact that if precipitation decreases, a relative shortage of water would occur compared to the required water demand, resulting in drought. However, similar to other drought indexes, the relative standard distribution of the time series of precipitation or runoff is calculated. The analysis suggests that relatively high-rainfall areas occur with no actual occurrence. Hence, modified drought analysis techniques are required to mitigate this phenomenon. Therefore, in this paper, a gamma distribution, calculated for the time series of points in the SPI calculation process, was expanded nationwide, and the drought index was calculated by applying it to the standard regular distribution after the calculation. In addition, the modified SPI (M-SPI) was verified for its effectiveness using the extreme drought and drought duration in areas where there was limited water supply in the past. Consequently, the SPI recognized drought only in 1995, 2001, and 2014, while the drought duration in 2010 and 2014 remained underestimated as a result of the comparison with the year of limited water supply and the results of the SPI and M-SPI. However, the M-SPI determined droughts in 1995, 1996, 2001, and 2010. In the case of Yeosu, although the SPI did not recognize two extreme droughts, M-SPI successfully recognized one extreme drought. In the case of Goheung, both the drought indexes recognized extreme drought.
Recent disasters have caused a great deal of personal and social damage. In addition to the work of preventing disasters by examining subsequent damage, it is important to manage disasters in real time. Therefore, a variety of measures are prepared to utilize empirical disaster information to manage ongoing disasters. However, the current system available to disaster managers is insufficient. In this study, we discuss the necessity of a visualization system for safety data code operation in rapid disaster situation management. This system should address safety operations according to the type of disaster, so those involved in situation management can easily grasp appropriate data. The purpose of this project is to establish a visualization system that can reduce the damage of future disasters by utilizing planned rapid situation management. Through this study, we propose a prototype of an information visualization system that assesses and provides task analysis and requirements for the responding disaster officer. It will be possible to establish such a practical disaster safety information system through the use of practical trials, an operation plan, and an improvement plan.
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