| 摘要: | 地震災害的防治，其首要步驟在於地震震災的評估，在傳統地震災害潛勢評估皆應用衰減模式作為評估的依據。而局部場址特性對最大地動值有相當大的影響，因此建立衰減模式時必須考慮測站的場址特性，以增進評估的可靠度。因此，本研究之目的將利用地震記錄，分析測站觀測值與參考衰減模式的系統誤差，建立台灣地區測站場址特性的衰減模式修正函數。 本研究使用Chien(2001)的衰減公式，得到各測站初步預估值，此為第一階段的計算結果。第二階段分析時則將其對各測站觀測值的系統偏差量作校正分析。與地震規模及震源距離之關係做比較，分析結果呈現此誤差殘值與兩者之關聯性不高，顯示對於系統誤差量的修正以測站場址特性之影響為主，則建立各測站場址特性的修正函數，此為第二階段迴歸分析之目的。將各測站的初步預估值與觀測值作迴歸分析，其間之關係式為ln(PGVObs) =C0+C1×ln(PGVpre)，則可得到各測站的修正係數C0、C1 值，如此即可修正測站場址特性所造成之誤差，得到可靠的地動速度極值。 但當地震發生時，中央氣象局能即時接收到資料，進而快速推估震源參數，故能利用這些地震記錄來修正該地震的震源特性對於地表地動值所造成之影響，藉以修正二階段所預測出來各測站之地表最大速度值，將可更準確地推估台灣地區地震發生後之地表PGV分佈。 整體而言，經由上述所採用的兩種方式計算所得預估值與觀測值已有較佳之相似性，因此可做為早期地震災害潛勢評估之依據之一；當大地震發生時，將可由地震速報系統於短時間內估算PGV分佈圖，協助救災指揮系統作緊急應變之參考，運用得宜應可達到減災之目的。 The prevention of the earthquake disaster, its primary step lies in the assessment of the earthquake calamity. Earthquake disaster forecast of the traditional manner use to do most of the application of attenuation models. As a result, we can better understand the attenuation characteristics in Taiwan and can reliably predict the peak amplitude for strong ground motion when an earthquake occurs. However, Local site characteristics on the value of the largest earthquake has considerable influence, the decay mode set up stations must be taken into account characteristics of the site in order to enhance the reliability of assessment. So, it is necessary to consider the site effects in attenuation relationship of PGV, and the result of predicted in seismic hazard will make best. Generally, site effect is one of the important factors for predicting ground motion. Therefore, the purpose of this study will use seismic records and PGV attenuation relationships between the errors, set up the Site corrections of the attenuation relationships in Taiwan region. First step, we got the first PGA of each site by attenuation relationship of PGV following Chien(2001), which used more than 3000 seismic records from 59 earthquake events to study the attenuation relationship of PGV. Second step, the TSMIP and TREIRS site correction C0 and C1, can be simplified by fallowing the law : ln(PGVObs)=C0+C1×ln(PGVpre), where PGVObs is the observed PGV value, PGVpre is the predicted PGV value obtained by the attenuation relationship laws. The selection criteria are ML > 4.5 and focal depth < 35 km. All data of site are well recorded by the TREIRS system and TSMIP system. The results agree reasonably well with the surface geology from published maps. Generally, the attenuation relationship and site corrections represent a statistically average effect. But, every event possesses its own characteristics, such as the source. Therefore, we used TREIRS system data from 80 telemetered strong-motion stations to estimated the peak ground motions PDTS at TSMIP sites: PDTS= fTS(f(ML,R),C0,C1)× fRTD(R,D0,D1), where PDTS is the predicted PGV value obtained by the attenuation relationship, R is the ratio by observed value at the TREIRS system station and the predicted value by the attenuation relationship with site correction at the TREIRS system station, D0 and D1 are coefficient to correct the amplification by TSMIP system station. With the attenuation relationship and the site corrections data base, we have embarked on a practical but yet important problem of predicting the PGV values as soon as a large earthquake happens in Taiwan. The only input this extreme values prediction calculation system needs is the TREIRS system solution. We expect that the predicted PGV maps will be useful in earthquake emergency response operations. |
