• Journal of the Society of Disaster Information
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• v.16 no.4
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• pp.670-681
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• 2020

Purpose: This study aims to derive a PGV prediction equation and to enhance the application of the Onsite EEW technology which has developed through previous studies. Method: The prediction equation for the Onsite EEW derived from earthquake data M≥3.0 and MMI≥II over the past four years. Local seismic risk is estimated using M and PGV deduced from P wave properties. Result: The improved PGV prediction equation estimated the MMI with an average accuracy of 94.8% and the 𝜏_c : Pd method also showed valid performance for alerting local seismic risks. Conclusion: Onsite EEW technology is successfully applied to Korea, and becomes to reduce the blind zone to about 14km.

• Journal of the Society of Disaster Information
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• v.16 no.1
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• pp.133-143
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• 2020

Purpose: This study aims to derive a predictive empirical equation for PGV prediction from P-wave using earthquake records in Korea and to verify the reliability of Onsite EEW. Method: The noise of P wave is removed from the observations of 627 seismic events in Korea to derive an empirical equation with PGV on the base rock, and reliability of Onsite alarms is verified from comparing PGV's predictions and observations through simulation using the empirical equation. Result: P-waves were extracted using the Filter Picker from earthquake observation records that eliminated noises, a linear regression with PGV was used to derive a predictive empirical equation for Onsite EEW. Through the on-site warning simulation we could get a success rate of 80% within the MMI±1 error range above MMI IV or higher. Conclusion: Through this study, the design feasibility and performance of Onsite EEWS using domestic earthquake records were verified. In order to increase validity, additional medium-sized seismic observations from abroad are required, the mis-detection of P waves is controlled, and the effect of seismic amplification on the surface is required.

• Proceedings of the Korea Water Resources Association Conference
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• 2011.05a
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• pp.258-258
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• 2011

지구 온난화에 따른 기후변화는 예측하기 힘든 패턴으로 특정지역의 강우빈도와 강수량을 증가시키고, 과거 관측되지 않았던 홍수 수위를 기록하는 등의 이상기후 현상으로 나타나고 있다. 기후변화의 눈으로 봤을 때 2010년은 전 세계적으로 많은 홍수, 지진, 산사태 등의 자연재해를 야기 시켰고, 이는 수자원의 활용과 관리 측면 뿐만 아니라 사회, 경제적 영향 및 자연재해로 확장되어 인류의 생활에 큰 영향으로 다가왔다. 이처럼 예기치 못한 기후변화에 대응하기 위해서는 수자원 정책이나, 장기발전계획 뿐만 아니라 발생된 기후 상황을 검토하고, 그 지역에서 발생된 강수량, 수위, 유량 등에 대한 기초 자료에 대한 분석이 선행되어야 할 것으로 판단된다. 본 연구에서는 2010년에 섬진강 유역의 최상류에서 하류에 이르는 덕치 외 12개 수위관측소를 대상 지점으로 선정하여 각 지점에 대한 현장조사를 실시하고, 수위모니터링을 비롯한 강수량, 방류량 등의 기본 자료를 수집하여 과거 자료와 비교검토 하였다. 그리고 저 평수기와 홍수기에 하천의 수위 및 유량을 현장에서 직접 실측하여 섬진강 상류에서 하류에 이르는 유출특성을 분석하였다. 그 결과 2010년 섬진강 유역에서는 지점에 따라 관측 개시일이 다르지만 1990년부터 관측이 개시된 구례와 송정 지점을 비롯하여 관측 이래 최고수위에 해당하는 호우가 발생되었음을 확인 할 수 있었다. 또한 2010년에 발생한 섬진강 유역의 지점별 상류에서 하류까지의 첨두유량을 분석 및 제시하였다. 이는 기존에 추정에 의해서 제시되었던 고수위 부분의 유량을 실측함으로써 고수위에 대한 수위-유량관계곡선식을 새롭게 제시하고, 홍수 주의보와 경보수위를 검토할 수 있는 기회가 되었다. 아울러 본 자료는 추후 발생 가능한 홍수에 좀 더 신속하게 대응할 수 있는 기초가 될 수 있을 것으로 기대한다.

• Korean Journal of Agricultural and Forest Meteorology
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• v.19 no.3
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• pp.130-139
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• 2017

The crop damage caused by strong wind was predicted using the wind speed data available from Korean Meteorological Administration (KMA). Wind speed data measured at 19 automatic weather stations in 2012 were compared with wind data available from the KMA's digital forecast. Linear regression equations were derived using the maximum value of wind speed measurements for the three-hour period prior to a given hour and the digital forecasts at the three-hour interval. Estimates of daily maximum wind speed were obtained from the regression equation finding the greatest value among the maximum wind speed at the three-hour interval. The estimation error for the daily maximum wind speed was expressed using normal distribution and Weibull distribution probability density function. The daily maximum wind speed was compared with the critical wind speed that could cause crop damage to determine the level of stages for wind damage, e.g., "watch" or "warning." Spatial interpolation of the regression coefficient for the maximum wind speed, the standard deviation of the estimation error at the automated weather stations, the parameters of Weibull distribution was performed. These interpolated values at the four synoptic weather stations including Suncheon, Namwon, Imsil, and Jangsu were used to estimate the daily maximum wind speed in 2012. The wind damage risk was determined using the critical wind speed of 10m/s under the assumption that the fruit of a pear variety Mansamgil would begin to drop at 10 m/s. The results indicated that the Weibull distribution was more effective than the normal distribution for the estimation error probability distribution for assessing wind damage risk.