环境噪声级
地质学
噪音(视频)
环境科学
地震噪声
地震学
计算机科学
地貌学
声音(地理)
图像(数学)
人工智能
作者
Hui Liu,Jing Li,Rong Hu,Haoran Meng,Hang Lyu
摘要
Abstract Seasonal frozen ground freeze–thaw cycles in cold regions are essential indicators of climate change, infrastructure, and ecosystems in the near-surface critical zone (CZ). As a noninvasive geophysical method, the ambient noise seismic method estimates the relative velocity variations (dv/v) based on coda waves or ballistic waves, providing new insights into the seasonal frozen ground changes in the soil properties and hydrology data, such as soil moisture content (SMC), temperature, and groundwater level. However, obtaining stable dv/v with high temporal and spatial resolution is challenging. In this work, we combine the 1D linear three-component seismic array and hydrological sensor to conduct seasonal frozen ground freeze–thaw monitoring experiments. Besides the conventional dv/v information, we calculate surface-wave dispersion curve variations (dc/c), which are more sensitive to SMC and can characterize the daily air temperature variations. Meanwhile, the horizontal-to-vertical spectral ratio (HVSR) amplitude and seismic signal peak frequency also show highly consistent changes to the freeze–thaw processes. All the results demonstrate that the different ambient noise seismic information (dc/c, HVSR, and peak frequency) provide robust observations for hydrogeological monitoring, such as air temperature, SMC, and groundwater level changes during seasonal freeze–thaw processes.
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