阿根廷-智利科帕休火山单站多参数地震监测(2018-2023 年)

IF 4.6 Q2 MATERIALS SCIENCE, BIOMATERIALS
J. A. Casas, G. Badi, T. D. Mikesell, Sebastián García, D. Draganov
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引用次数: 0

摘要

有关火山时间演变的知识对于准确了解正在发生的物理动态过程和适当评估近期最可能发生的火山情况至关重要。利用在阿根廷-智利国际边界上最危险的火山之一--科帕休火山地区记录的地震数据,我们获得了一些信息,有助于更好地解释火山爆发之前、期间和之后发生的过程。我们采用单站方法来评估科帕休火山机械性能和内部结构的变化。因此,我们获得了有关火山系统结构改变、摩擦和断裂以及刚度变化的信息。我们的结果表明,所评估的地震参数的时间变化与在地表观察到的火山现象(即炽热和火山灰排放)相关。考虑到所分析的地震参数对物理过程的敏感性,以及之前为该地区开发的模型,我们提出了一个物理模型来解释 2018-2023 年期间在科帕休发生的喷发事件。该模型可用于评估未来情景,这对负责科帕休火山实时监测的机构提高循证决策的质量至关重要。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Single-Station Multiparametric Seismic Monitoring of Copahue Volcano, Argentina–Chile (2018–2023)
Knowledge about the temporal evolution of a volcano is fundamental for an accurate understanding of the occurring physical dynamic processes and an appropriate assessment of the most probable near-future volcanic scenarios. Using seismic data recorded in the area of one of the most hazardous volcanoes along the Argentina–Chile, international border—Copahue volcano, we obtain information for an improved interpretation of the processes that occurred before, during, and after eruptive events. We use a single-station methodology to assess variations in the mechanical properties and internal structure of the Copahue volcano. Thus, we obtain information about structural alterations, friction and fractures, and variations in rigidity in the volcanic system. Our results show that the time variations of the evaluated seismic parameters correlate to the volcanic phenomena observed on the surface, that is, incandescence and ash emissions. Accounting for the physical processes, to which the analyzed seismic parameters are sensitive, and previous models developed for the area, we propose a physical model explaining the eruptive events that occurred at Copahue in the period 2018–2023. This model can potentially be used for the assessment of future scenarios, which is of fundamental importance for the institutions in charge of the real-time monitoring of Copahue volcano to improve the quality of their evidence-based decisions.
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来源期刊
ACS Applied Bio Materials
ACS Applied Bio Materials Chemistry-Chemistry (all)
CiteScore
9.40
自引率
2.10%
发文量
464
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