SEISMOLOGICAL ASPECTS OF THE 1989-1990 ERUPTION AT REDOUBT VOLCANO, ALASKA - THE MATERIALS FAILURE FORECAST METHOD (FFM) WITH RSAM AND SSAM SEISMIC DATA
SEISMOLOGICAL ASPECTS OF THE 1989-1990 ERUPTION AT REDOUBT VOLCANO, ALASKA - THE MATERIALS FAILURE FORECAST METHOD (FFM) WITH RSAM AND SSAM SEISMIC DATA
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DOI：
10.1016/0377-0273(94)90048-5
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发表时间：
1994-08-01
影响因子：
2.9
通讯作者：
VOIGHT, B
中科院分区：
文献类型：
--
作者：
CORNELIUS, RR;VOIGHT, B
阿拉斯加火山观测站利用实时地震振幅测量（RSAM）和地震频谱振幅测量（SSAM）系统，对1989年12月至1990年4月阿拉斯加里道特火山喷发期间的地震活动进行了跟踪。数据由地震仪输出的绝对振幅的10分钟平均值组成。这些数据已被用来测试在事后的材料失效预测方法（FFM），它试图定义喷发的时间与一个时间序列的变化率可测量的事件前加速的偶发现象。该方法的实际应用强调反速率图，无论是从背景中出现的信号的早期检测，并为事件预测。喷发窗口是由图形或数值外推的反向速率趋势和交叉的数据包络线，反映数据的分散性和一致性，与经验的临界率附近的时间epursion.Before圆顶破坏喷发的1月2日，速率变化有足够的一致性，持续时间和强度的定性或定量的FFM预测分析，使用RSAM或SSAM。信噪比都很高的RSAM或SSAM的数据集，和FFM分析可以提供有用的支持决策。1月2日之后，与一个快速连续的圆顶倒塌喷发，信号强度减弱和RSAM的信噪比下降。RSAM上最明显的模式反映了噪声而不是信号，完全基于RSAM的预测会产生误导。通过消除被排除的频率中的噪声，对于2Hz附近的带状频率，SSAM通常产生增强的信噪比。1月2日之后，只有SSAM表现出适合FFM分析的信噪比。反向SSAM图可能是早期检测的间接长期地震活动的信息。将FFM方法与选定频率的频谱幅度相结合的前景提供了相当大的希望。
Seismic activity during the December 1989 to April 1990 eruption of Redoubt Volcano, Alaska, has been tracked by the Alaska Volcano Observatory using Real-time Seismic Amplitude Measurement (RSAM) and Seismic Spectral Amplitude Measurement (SSAM) systems with up to five stations. Data consist of 10-minute averages of the absolute amplitudes of seismometer output. These data have been used to test in hindsight the Materials Failure Forecast Method (FFM), which attempts to define the time of eruption with a time series for precursory phenomena whose rate of change accelerates measurably before events. Practical application of the method emphasizes inverse-rate plots, both for early detection of signal emergent from background, and for event forecasting. Eruption windows are determined by graphical or numerical extrapolation of the inverse-rate trend and by intersection of a data envelope, reflecting data scatter and consistency, with an empirical critical rate near the time of eruption.Prior to the dome-destroying eruption of January 2, rate changes were of sufficient consistency, duration, and intensity for a qualitative or quantitative FFM predictive analysis, using either RSAM or SSAM. Signal-to-noise ratio was high for both RSAM or SSAM data sets, and FFM analyses could have provided useful support for decision making.Following January 2, in association with a rapid succession of dome-collapse eruptions, signal strength diminished and RSAM signal-to-noise ratio declined. The most distinct patterns on RSAM reflected noise rather than signal, and forecasting exclusively based for RSAM would have been misleading. By eliminating the noise in excluded frequencies, an enhanced signal-to-noise ratio was generally produced by SSAM for banded frequencies near 2 Hz. After January 2, only SSAM exhibited signal-to-noise ratios suitable for FFM analysis. Inverse-SSAM plots could have been informative for early detection of precursory long-period seismicity. The prospect of combining the FFM approach with spectral amplitudes in selected frequencies offers considerable promise.