Can land subsidence be monitored with ambient seismic auto-correlations?

Laura Ermert,Marine Denolle, Enrique Cabral Cano,Estelle Chaussard, Dario Solano Rojas

crossref(2021)

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摘要
<p>Mexico City has been undergoing rapid subsidence for more than 100 years due to groundwater extraction. During the 2010s, rates surpassing 30 centimeters/year were observed by satellite geodetic measurements. Not only does this subsidence pose grave challenges for buildings, urban infrastructure, and water management, but it also changes the seismic response of the affected subsurface layers and thereby alters the seismic hazard in the metropolis that has seen devastating site effects both in the 1985 Michoacan and 2017 Puebla earthquake. We use data and numerical modeling of ambient noise auto-correlations to gain a better insight into the subsidence process through ambient noise techniques.</p><p>We establish a baseline for the long-term and seasonal variations of seismic velocity near the basin from long-term recordings of the Geoscope station UNM, located at the Universidad Nacional Aut&#243;noma de M&#233;xico in the geotechnical hill zone. We further study temporary recordings from the MASE array (MASE (2007): Meso America Subduction Experiment. Caltech. Dataset. doi:10.7909/C3RN35SP) to see how subsidence and other factors may influence seismic velocity in the geotechnical hill, transition, and lake zones.</p><p>We find that seasonal oscillations and a strong, rapid velocity drop coincident with the 2017 Puebla earthquake overlay a multi-year increasing trend in seismic velocity. We cautiously interpret the multi-year increase as a long-term effect of subsidence. We further study the temporal correlations of seismic velocity changes with other environmental time series like precipitation, and model auto-correlations in order to improve our understanding of their composition and sensitivity.</p>
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