Seismic Advances in Process Geomorphology

One of the pillars of geomorphology is the study of geomorphic processes and their drivers, dynamics, and impacts. Like all activity that transfers energy to Earth's surface, a wide range of geomorphic process types create seismic waves that can be measured with standard seismic instruments. Seismic signals provide continuous high-resolution coverage with a spatial footprint that can vary from local to global, and in recent years, efforts to exploit these signals for information about surface processes have increased dramatically, coalescing into the emerging field of environmental seismology. The application of seismic methods has the potential to drive advances in our understanding of the occurrence, timing, and triggering of geomorphic events, the dynamics of geomorphic processes, fluvial bedload transport, and integrative geomorphic system monitoring. As new seismic applications move from development to proof of concept to routine application, integration between geomorphologists and seismologists is key for continued progress. ▪ Geomorphic activity on Earth's surface produces seismic signals that can be measured with standard seismic instruments. ▪ Seismic methods are driving advances in our understanding of the occurrence, triggering, and internal dynamics of a range of geomorphic processes. ▪ Dedicated seismic-based observatories offer the potential to comprehensively characterize geomorphic activity and its impacts across a landscape. ▪ Collaboration between seismologists and geomorphologists is fostering the development of new applications, models, and analysis techniques for geomorphic seismology. Expected final online publication date for the Annual Review of Earth and Planetary Sciences, Volume 50 is May 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

Passive imaging of collisional orogens: a review of a decade of geophysical studies in the Pyrénées

This contribution reviews the challenges of imaging collisional orogens, focusing on the example of the Pyrenean domain. Indeed, important progresses have been accomplished regarding our understanding of the architecture of this mountain range over the last decades, thanks to the development of innovative passive imaging techniques, relying on a more thorough exploitation of the information in seismic signals, as well as new seismic acquisitions. New tomographic images provide evidence for continental subduction of Iberian crust beneath the western and central Pyrénées, but not beneath the eastern Pyrénées. Relics of a Cretaceous hyper-extended and segmented rift are found within the North Pyrenean Zone, where the imaged crust is thinner (10–25 km). This zone of thinned crust coincides with a band of positive Bouguer anomalies that is absent in the Eastern Pyrénées. Overall, the new tomographic images provide further support to the idea that the Pyrénées result from the inversion of hyperextended segmented rift systems.

A Numerical Investigation of the Characteristics of Seismic Signals Induced by Rockfalls

This study proposes a numerical coupling approach to simulate seismic signals of rockfalls and conducts a parametric analysis to explore the characteristics of the seismic signals generated by rockfalls. To validate the approach, three field rockfall tests were selected for comparison. The rockfall velocity, duration, seismic frequency, Husid plot, Arias intensity, and spectrogram of the seismic signals were compared. We found that friction between rocks and the ground affects rock falling behavior. In addition, the local damping and Rayleigh damping assignments in the numerical model have strong effects on the simulation results. The volume of the falling rock and the falling speed of the rock affect the Arias intensity. The coupling approach proposed could be extended and can potentially be used as a useful tool in rockfall hazard estimations.

Application of an improved particle filter for random seismic noise suppression

Random noise is inevitable during seismic prospecting. Seismic signals, which are variable in time and space, are damaged by conventional random noise suppression methods, and this limits the accuracy in seismic data imaging. In this paper, an improved particle filtering strategy based on the firefly algorithm is proposed to suppress seismic noise. To address particle degradation problems during the particle filter resampling process, this method introduces a firefly algorithm that moves the particles distributed at the tail of the probability to the high-likelihood area, thereby improving the particle quality and performance of the algorithm. Finally, this method allows the particles to carry adequate seismic information, thereby enhancing the accuracy of the estimation. Synthetic and field experiments indicate that this method can effectively suppress random seismic noise.

Fast Identification of Volcanic Tremor and Lahar Signals during the 2009 Redoubt Eruption Using Permutation Entropy and Supervised Machine Learning

Despite their usefulness for volcano monitoring, emergent seismic signals, such as volcanic tremor or signals generated by lahars, are difficult to identify with confidence in a timely fashion. Machine-learning algorithms offer an objective alternative to traditional methods of identifying such volcanoseismic signals, because they are able to handle quickly large amounts of data, while requiring little input from the user. In this work, we combine permutation entropy and centroid as well as dominant frequency with supervised machine learning to evaluate their potential in identifying volcanic tremor and lahar signals recorded during the 2009 Redoubt volcano eruption. The particular dataset was chosen for the reason that the properties and occurrence times of the volcanoseismic signals during the eruption are well known from previous studies. We find that the selected features can effectively discriminate both types of signals against the seismic background, especially for stations that are near the source. Results show that the identification success rate for volcanic tremor reaches up to 96%, whereas this rate becomes up to 91% for lahar signals. The calculation of the features as well as the application of the machine-learning algorithms is fast, allowing their implementation in the operational environment of a volcano observatory during a volcanic crisis. Finally, the proposed methodology can potentially be used to objectively identify other emergent seismic signals such as tectonic tremor along subduction zones, glacial tremor, or seismic signals generated during landslides.

Resonances of the InSight Seismometer on Mars

ABSTRACT The Interior Exploration using Seismic Investigations, Geodesy and Heat Transport (InSight) seismometer was deployed to the surface of Mars in December 2018–February 2019. The specific deployment conditions, which are very different from those of a standard broadband instrument on the Earth, result in resonances caused by different parts of the sensor assembly (SA) that are recorded by the seismometer. Here, we present and characterize the resonances known to be present in the SA and their causes to aid interpretation of the seismic signals observed on Mars. Briefly, there are resonances in the SA at about 2.9, 5.3, 9.5, 12, 14, 23–28, and 51 Hz. We discuss various methods and tests that were used to characterize these resonances, and provide evidence for some of them in data collected on Mars. In addition to their relevance for the high frequency analysis of seismic data from InSight, specifically for phase measurements near the resonant frequencies, the tests and observations described here are also of potential use in the further development of planetary seismometers, for example, for Mars, the Moon, or Europa.

Magma pressure discharge induces very long period seismicity

Volcano seismicity is one of the key parameters to understand magma dynamics of erupting volcanoes. However, the physical process at the origin of the resulting complex and broadband seismic signals remains unclear. Syn-eruptive very long period (VLP) seismic signals have been explained in terms of the sudden expansion of gas pockets rising in the liquid melt. Their origin is linked to a magma dynamics which triggers the explosive process occurring before the explosive onset. We provide evidence based on acoustic, thermal, and ground deformation data to demonstrate that VLP signals at Stromboli are generated at the top of the magma column mainly after the explosion onset. We show that VLP amplitude and duration scale with the eruptive flux which induces a decompression of 103–104 Pa involving the uppermost ~ 250 m of the feeding conduit. The seismic VLP source represents the final stage of a ~ 200 s long charge and discharge mechanism the magma column has to release excess gas accumulated at the base of a denser and degassed magma mush. The position of the VLP seismic source coincides with the centroid of the shallow mush plug and tracks elevation changes of the magma free surface.

On Dam Failure Induced Seismic Signals Using Laboratory Tests and on Breach Morphology due to Overtopping by Modeling

Dam models were constructed in an indoor flume to test dam breach failure processes to study the seismic signals induced. A simple dam breach model was also proposed to estimate hydrographs for dam breach floods. The test results showed that when the retrogressive erosion due to seepage of the dam continues, it will eventually reach the crest at the upstream side of the dam, and then trigger overtopping and breaching. The seismic signals corresponding to the failure events during retrogressive erosion and overtopping of the dam models were evaluated. Characteristics of the seismic signals were analyzed by Hilbert–Huang transform. Based on the characteristics of the seismic signals, we found four types of mass movement during the retrogressive erosion process, i.e., the single, intermittent, and successive slides and fall. There were precursor seismic signals found caused by cracking immediately before the sliding events of the dam. Furthermore, the dam breach modeling results coincided well with the test results and the field observations. From the test and modeling results, we confirmed that the overtopping discharge and the lateral sliding masses of the dam are also among the important factors influencing the evolution of the breach. In addition, the widening rate of the breach decreases with decreased discharge. The proposed dam breach model can be a useful tool for dam breach warning and hazard reduction.