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  • 學位論文

台灣即時強地動觀測於地震預警之應用

The application of real-time strong-motion observations on the earthquake early warning in Taiwan

指導教授 : 王乾盈 辛在勤
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摘要


本研究以中央氣象局即時強地動觀測系統為骨幹,發展台灣地震預 警作業所需之相關研究。地震預警作業包含強震的即時觀測、振動參數 的合理預估以及預警訊息的快速傳遞等3 個部分,本研究把重點放在觀測 地震學的研究範疇,首先在即時強地動觀測系統的架構下,分別根據區 域預警以及現地預警模式,進行地震參數測報的評估;然後蒐集中央氣 象局自由場強震站所收錄到116 個中大型地震的強震記錄,採取2 階段迴 歸分析的方法,建立台灣地區地振動參數的經驗預估模式,並根據即時 作業情形,規劃3 種振動圖層的製作流程;最後則將研究結果綜合應用於 台灣地區地震預警作業之規劃,並實際以近年來7 個顯著地震進行實例評 估。 歸納主要研究成果如下:(一)、利用虛擬的區域觀測子網,針對島 內或近海規模大於4.5 的地震,可以將地震反應時間縮短在20 秒以內,平 均為18.8±3.8 秒,對於距離震央約60 公里以外的地區開始具有預警能 力;(二)、參考現地預警模式,探討以P 波垂直向位移振幅及頻率做為 預警發布依據的可行性,結果發現P 波位移振幅0.1 公分可設定為判斷台 灣島內或近海區域是否發生規模6 以上地震的門檻,並獲得1 組利用P 波 頻率相關參數推估地震規模之經驗公式;(三)、利用迴歸分析方法,建 立台灣地區地振動參數的經驗預估公式,所預估參數包括最大地動加速 度值PGA、最大地動速度值PGV、週期0.3 秒、1.0 秒和3.0 秒之反應譜 加速度值Sa,以及頻率0.5、1.0、2.0、3.0、4.0、5.0、6.0、7.0、8.0、9.0 及10.0Hz 的加速度峰值;(四)、根據即時作業情形,本研究規劃3 種 振動圖層的製作流程,以分別提供速報及預警階段緊急應變之依據,根 據評估,針對規模5 以上地震,大部分預估振動圖層的相關係數可以達到 0.8 以上,平均格點的放大率則大都集中在0.5 至1.5 倍之間;(五)、根 據區域預警模式實際運作結果以及P 波預警模式資料分析統計,在中央氣象局即時強地動觀測系統的架構下,配合地振動參數經驗預估模式, 建立台灣地區的預警作業架構;根據2002 年後7 個規模大於6 地震的實 例評估,反應時間幾乎都可以縮短在15 秒以內,針對島內地震,甚至可 以在10 秒內發出強震發生的訊息,除了2003 年12 月10 日成功地震,對 於陸地部分,其預警的空白區可以縮小在30 公里的範圍以內。

並列摘要


Based on the real-time strong-motion monitoring system implemented by Central Weather Bureau (CWB), we developed and evaluated the earthquake early warning (EEW) application in Taiwan. In the study, we mainly concentrated our attention upon two essential parts of EEW, which one is rapid determination of earthquake parameters, and the other is accurate prediction of peak ground motions. On determining earthquake parameters, in order to shorten the earthquake response time, a virtual sub-network approach is utilized at first. Under the practical experiment since 2001, for monitoring inland or near offshore earthquakes with magnitude greater than 4.5, the response time can be shorten as 18.8±3.8 sec averagely. Therefore, it can provide early warning before S-wave arrival for metropolitan areas located 60 km away from the epicenter. For the sake of further reducing the area of so-called blind-zone which cannot provide early warning, we also attempted to utilize vertical displacement records of P-wave as a basis to issue warnings. As results, we found that the amplitude 0.1 cm can be used as a criterion to judge if an earthquake above magnitude 6.0 is occurring in Taiwan Island. Furthermore, we also derived a set of frequency-based formulas simultaneously, which can be used to estimate earthquake magnitude rapidly. As regards the prediction of peak ground motions, we use two-step linear regression analysis to derive various parametric equations. The parameters include peak ground acceleration (PGA), peak ground velocity (PGV), 0.3 sec, 1.0 sec, 3.0 sec spectral acceleration (Sa) and filtered PGA etc.. According to the earthquake early warning and rapid reporting stages respectively, we developed three algorithms creating “ShakeMaps” based on these predictive equations. In comparison with actual maps resulted from observed strong-motion data, the predictive results had high similarity, the correlation coefficients are almost above 0.8 and the average magnifications of grids are between 0.5 to 1.5. To combine the research results, and under the framework of real-time strong-motion observational network, we designed an earthquake early warning algorithm which is suitable for Taiwan Island. According to the experiment on 7 magnitude-above-6.0 earthquakes took place after 2002, the averaged response times is within 15 sec. Except for the Chengkung earthquake of 2003, the processing time for inland earthquakes can be shorten beneath 10 sec further, and the radius of blind-zone is reduced to 30 km.

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被引用紀錄


黃煒婷(2009)。台灣地區Pd衰減關係式之分析及於地震預警之運用〔碩士論文,國立臺灣大學〕。華藝線上圖書館。https://doi.org/10.6342/NTU.2009.01282
Kuo, Z. P. (2013). 地震預警系統與牙齒咬合壓力分佈監測系統 [master's thesis, National Taipei University of Technology]. Airiti Library. https://www.airitilibrary.com/Article/Detail?DocID=U0006-3007201309272900
許喬筑(2015)。台灣宜蘭地區地震預警系統之測站效應〔碩士論文,國立中央大學〕。華藝線上圖書館。https://www.airitilibrary.com/Article/Detail?DocID=U0031-0412201512062164

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