首页> 外文期刊>Journal of geophysical research. Solid earth: JGR >Self-Potential Ambient Noise and Spectral Relationship With Urbanization, Seismicity, and Strain Rate Revealed via the Taiwan Geoelectric Monitoring Network
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Self-Potential Ambient Noise and Spectral Relationship With Urbanization, Seismicity, and Strain Rate Revealed via the Taiwan Geoelectric Monitoring Network

机译:通过台湾地电气监测网络揭示了与城市化,地震性和应变率的自势环境噪声和光谱关系

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摘要

Geoelectric self-potential (SP) signals are sensitive to natural and anthropogenic factors. The SP spectral characteristics under the different factors in Taiwan were investigated, and the SP spectral scalings were correlated with urbanization level, seismicity, and crustal deformation. The ambient SP noise models were first established by estimating the probability density functions of the spectrograms at each frequency. The effects of the natural and anthropogenic factors on the SP signals are understood by comparing the SP noise models under various conditions, such as precipitation, urbanization, and electric trains. Results show that the SP signals in areas of high industrialization and human activity and areas close to train stations behave as white noises and exhibit a distinct spectral ripple at frequencies around 1 Hz. On the other hand, the SP spectral power law parameters, Gutenberg-Richter b values, and dilation strain rates were estimated by using the SP, earthquake catalog, and GPS data, respectively, during 2012-2017. By investigating the correlations of the SP spectral parameters with the Gutenberg-Richter b value, dilation strain rates, and urbanization level, the SP optimal frequency band is found between 0.006 and 1 Hz due to the high correlation between the SP and seismicity data and between the SP and dilation data and the low correlation between the SP and urbanization data. Hence, this study may help the filtering and screening of the SP data and facilitate the understanding of the mechano-electric behavior in the crust.
机译:电气电位(SP)信号对天然和人为因素敏感。研究了台湾不同因素下的SP光谱特性,SP光谱凝固与城市化水平,地震性和地壳变形相关。首先通过估计每个频率的谱图的概率密度函数来建立环境SP噪声模型。通过比较各种条件下的SP噪声模型,例如降水,城市化和电动火车,可以理解天然和人为的因素对SP信号的影响。结果表明,高工业化和人类活动领域的SP信号以及靠近火车站的区域表现为白色噪音,并在1Hz左右的频率下表现出不同的光谱纹波。另一方面,通过使用SP,地震目录和GPS数据在2012-2017期间,估计SP光谱功率法参数,古龄堡 - RICHTER B值和扩张应变率。通过研究SP光谱参数与古腾堡 - RICHTER B值,扩张应变率和城市化水平的相关性,由于SP和地震性数据之间的高相关性,SP最佳频带在0.006和1 Hz之间找到了0.006和1 Hz SP和扩张数据和SP与城市化数据之间的低相关性。因此,本研究可以帮助滤波和筛选SP数据并促进地壳中的机械电动行为的理解。

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