Seismic Ambient Noise Analyses Reveal Changing Temperature and Water Signals to 10s of Meters Depth in the Critical Zone
Seismic Ambient Noise Analyses Reveal Changing Temperature and Water Signals to 10s of Meters Depth in the Critical Zone
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DOI：
10.1029/2020jf005823
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发表时间：
2021-01
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影响因子：
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通讯作者：
David Oakley;B. Forsythe;X. Gu;A. Nyblade;S. Brantley
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作者：
David Oakley;B. Forsythe;X. Gu;A. Nyblade;S. Brantley
关键地带维持着陆地生命，但我们几乎没有工具可以有效地探索地下最初几米以外的区域。通过对部署在萨斯奎汉纳页岩山临界区观测站（SHCZO）森林覆盖的页岩山子流域中密集分布的地震仪的高频环境地震噪声进行分析，我们发现可以检测到深度从0.1 m到数十m的地震速度的时间变化。这些变化是由地表变化驱动的。采用移动窗口互谱（MWCS）方法，在10个不同的频带中以每小时的分辨率测量尾波的地震速度变化。我们观察到一个昼夜信号，一个季节信号和一个基于气象事件的信号。将这些信号与大量仪表集水区的降水、井水位、土壤湿度、土壤温度、气温、潜热通量和气压的时间序列测量值进行比较。大多数的速度变化可以解释为温度的变化，导致热弹性应变传播到深度。但是，在大雨事件后观察到的地震速度时间序列中的一些双重极小值部分归因于水渗透的影响。这些结果表明，高频环境噪声数据在某些位置可用于检测从0.1米到0.100米或更大深度的临界区的变化，每小时的分辨率。但是，这些数据的解释需要多个环境数据集，以反卷积地下临界区的热弹性和水文效应之间的复杂的相互关系。
The critical zone sustains terrestrial life, but we have few tools to explore it efficiently beyond the first few meters of the subsurface. Using analyses of high‐frequency ambient seismic noise from densely spaced seismometers deployed in the forested Shale Hills subcatchment of the Susquehanna Shale Hills Critical Zone Observatory (SSHCZO), we show that temporal changes in seismic velocities at depths from ∼1 m to tens of m can be detected. These changes are driven by variations at the land surface. The Moving‐Window Cross‐Spectral (MWCS) method was employed to measure seismic‐velocity changes in coda waves at hourly resolution in 10 different frequency bands. We observed a diurnal signal, a seasonal signal, and a meteorological‐event‐based signal. These signals were compared to time‐series measurements of precipitation, well water levels, soil moisture, soil temperature, air temperature, latent heat flux, and air pressure in the heavily instrumented catchment. Most of the velocity changes can be explained by variations in temperature that result in thermoelastic strains that propagate to depth. But some double minima in seismic velocity time‐series observed after large rain events were attributed in part to the effects of water infiltration. These results show that high‐frequency ambient noise data may in some locations be used to detect changes in the critical zone from ∼1 to ∼100 m or greater depth with hourly resolution. But interpretation of such data requires multiple environmental data sets to deconvolve the complex interrelationships among thermoelastic and hydrological effects in the subsurface critical zone.