Malgorzata Chmiel

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Chmiel

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Malgorzata

ORCID

0000-0002-5573-9801

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Publications 1 - 6 of 6

Seismic Velocity Response to Atmospheric Pressure Using Time-Lapse Passive Seismic Interferometry
Gradon, Chloé; Brenguier, Florent; Stammeijer, Johannes; et al. (2021)
Bulletin of the Seismological Society of America
Seismic velocities in the shallow crust down to a few kilometers depth show a remarkable sensitivity to stress perturbations due to the presence of compliant pores, cracks, fractures, and faults. Monitoring temporal changes of seismic velocities can thus provide key insights on dynamic processes affecting the shallow crust such as those related to the atmosphere (rainfall, barometric pressure, and temperature) and those with deeper tectonic and volcanic origins. In this work, we investigate the specific response of the near surface down to 300 m depth to atmospheric pressure variations. We conduct a four month passive seismic monitoring experiment in the desert of Oman using continuous noise recorded at geophones located within five wells. The results show a clear, direct correlation between seismic velocities and barometric pressure variations for monthly transients. At a longer, seasonal temporal scale, seismic velocities are stable, whereas atmospheric pressure shows a clear positive trend. We use the undrained coupled poroelastic theory to model these observations and find that the lack of seasonal velocity changes can be partly explained by the atmospheric pressure that diffuses into the pores with a strong hydraulic diffusivity likely higher than 100 m2=s consistent with the local geology referring to carbonates. Finally, the comparison between the modeled and observed velocity changes leads to estimate a velocity-stress sensitivity on the order of 6:3 x 10-7 Pa-1 which is consistent with previous studies. Using this result for calibration, we find that a sudden step-change drop of velocity of 0.015% occurring in the beginning of October 2019 and corresponding to a stress perturbation likely larger than 240 Pa affected the entire studied area. This small change could be related to a perturbation at greater depth associated with variations in the production rates within the underlying reservoir. © Seismological Society of America
Connecting beamforming and kernel-based noise source inversion
Bowden, Daniel; Sager, Korbinian; Fichtner, Andreas; et al. (2021)
Geophysical Journal International
Beamforming and backprojection methods offer a data-driven approach to image noise sources, but provide no opportunity to account for prior information or iterate through an inversion framework. In contrast, recent methods have been developed to locate ambient noise sources based on cross-correlations between stations and the construction of finite-frequency kernels, allowing for inversions over multiple iterations. These kernel-based approaches show great promise, both in mathematical rigour and in results, but are less physically intuitive and interpretable. Here we show that these apparently two different classes of methods, beamforming and kernel-based inversion, are achieving exactly the same result in certain circumstances. This paper begins with a description of a relatively simple beamforming or backprojection algorithm, and walks through a series of modifications or enhancements. By including a rigorously defined physical model for the distribution of noise sources and therefore synthetic correlation functions, we come to a framework resembling the kernel-based iterative approaches. Given the equivalence of these approaches, both communities can benefit from bridging the gap. For example, inversion frameworks can benefit from the numerous image enhancement tools developed by the beamforming community. Additionally, full-waveform inversion schemes that require a window selection for the comparisons of misfits can more effectively target particular sources through a windowing in a beamform slowness domain, or might directly use beamform heatmaps for the calculation of misfits. We discuss a number of such possibilities for the enhancement of both classes of methods, testing with synthetic models where possible.
Seismic Constraints on Damage Growth Within an Unstable Hanging Glacier
Chmiel, Malgorzata; Walter, Fabian Thomas; Pralong, Antoine; et al. (2023)
Geophysical Research Letters
Forecasting hanging glacier instabilities remain challenging as sensing technology focusing on the ice surface fails to detect englacial damage leading to large-scale failure. Here, we combine icequake cluster analysis with coda wave interferometry constraining damage growth on Switzerland's Eiger hanging glacier before a 15,000 m3 break-off event. The method focuses on icequake migration within clusters rather than previously proposed “event counting.” Results show that one cluster originated from the glacier front and migrated by 13.9(±1.2) m within 5 weeks before the break-off event. The corresponding crevasse extension separates unstable and stable ice masses. We use the measured source displacement for damage parametrization and find a 90% agreement between an analytical model based on damage mechanics and frontal flow velocities measured with an interferometric radar. Our analysis provides observational constraints for damage growth, which to date is primarily a theoretical concept for modeling englacial fractures.
Detecting the impact of climate change on alpine mass movements in observational records from the European Alps
Jacquemart, Mylène; Weber, Samuel; Chiarle, Marta; et al. (2024)
Earth-Science Reviews
Anthropogenic climate change is rapidly altering high mountain environments, including changing the frequency, dynamic behavior, location, and magnitude of alpine mass movements. Here, we review three decades of scientific literature (∼1995 to early 2024) to assess to what degree observational records from the European Alps – as the region with the most comprehensive records – reveal these changes. We do this for the processes that are most common in this region, namely rockfall, rock avalanches, debris flows, ice avalanches, and snow avalanches. The systematic literature search and review yielded 335 publications, of which we omitted publications that did not focus primarily on observational records. The remaining 103 publications used observations from over 100 sites and 30 inventories to investigate the connection between climate change and mass movements. About one third of the relevant studies found a measurable impact of climate change on the investigated alpine mass movement processes (with the exception of large rock avalanches). The clearest climate-controlled trends are (i) increased rockfall frequency in high-alpine areas due to higher temperatures, (ii) fewer and smaller snow avalanches due to scarcer snow conditions at low and mid elevations, and (iii) a shift towards avalanches with more wet snow and fewer powder clouds. While there is (iv) despite a clear increase in debris-flow triggering precipitation, debris-flow activity has not been found to uniformly increase, though there is some evidence for increasing activity above treeline and at locations without historical precedence. The trends for (v) ice avalanches are spatially very variable with no clear direction. Ice temperatures are measurably increasing, but – despite a theoretical expectation – this has not impacted ice avalanche activity to date. The reviewed literature also reveals that quantifying the impact of climate change on these mass movements remains difficult in part due to the complexities of the natural system, but also because of limitations in the available datasets, confounding effects, and existing statistical processing techniques. Better assessments could be achieved if we would more broadly support the compilation and maintenance of large standardized data catalogs, bring together various dispersed datasets (in said catalogs), including from social and citizen science projects, invest in long-term natural observatories, and develop suitable processing techniques. Better observations will additionally support the development and performance of process-based models. If we can advance natural hazard research on these fronts, more quantitative predictions of future change are well within our reach.
Brief communication: Seismological analysis of flood dynamics and hydrologically triggered earthquake swarms associated with Storm Alex
Chmiel, Malgorzata; Godano, Maxime; Piantini, Marco; et al. (2022)
Natural Hazards and Earth System Sciences
On 2 October 2020, the Maritime Alps in southern France were struck by the devastating Storm Alex, which caused locally more than 600 mm of rain in less than 24 h. The extreme rainfall and flooding destroyed regional rain and stream gauges. That hinders our understanding of the spatial and temporal dynamics of rainfall-runoff processes during the storm. Here, we show that seismological observations from permanent seismic stations constrain these processes at a catchment scale. The analysis of seismic power, peak frequency, and the back azimuth provides us with the timing and velocity of the propagation of flash-flood waves associated with bedload-dominated phases of the flood on the Vesubie River. Moreover, the combined short-term average to long-term average ratio and template-matching earthquake detection reveal that 114 local earthquakes between local magnitude M-L = -0.5 and M-L = 2 were triggered by the hydrological loading and/or the resulting in situ underground pore pressure increase. This study shows the impact of Storm Alex on the Earth's surface and deep-layer processes and paves the way for future works that can reveal further details of these processes.
Phase-velocity inversion from data-based diffraction kernels: seismiv Michelson interferometer
Chmiel, Malgorzata; Roux, Philippe; Wathelet, Marc; et al. (2021)
Geophysical Journal International
We propose a new surface-wave tomography approach that benefits from densely sampled active-source arrays and brings together elements from active-source seismic-wave interferometry, full waveform inversion and dense-array processing. In analogy with optical interferometry, seismic Michelson interferometer uses seismic interference patterns given by the data-based diffraction kernels in an iterative inversion scheme to image a medium. Seismic Michelson interferometer requires no travel-time measurements and no spatial regularisation, and it accounts for bent rays. Furthermore, the method does not need computation of complex synthetic models, as it works as a data-driven inversion technique that makes it computationally very fast. In an automatic way, it provides high-resolution phase-velocity maps and their error estimation. Seismic Michelson interferometer can complete traditional surface-wave tomography studies, as its use can be easily extended from land active seismic data to the virtual source gathers of ambient-noise-based studies with dense arrays.

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Malgorzata Chmiel

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