Seismica

Seismicity and Surface Deformation in Kamanjab Inlier, Northern Namibia

2025-07-15T13:52:00-04:00

The last two decades have seen the onset of felt earthquakes, including occasionally damaging events, in the Kamanjab Inlier, a block of Paleoproterozoic crystalline basement in northern Namibia. The Geological Survey of Namibia (GSN) and the Council for Geoscience, South Africa (CGS) deployed a temporary network of 10 seismic stations within the Kamanjab Inlier from June to September 2018 and cataloged ~1500 events. We used a neural network-based earthquake phase detector, EQTransformer, to enhance the published GSN catalog to >9000 detections. The double-difference earthquake relocation of ~4500 events reveals two distinct major and three minor spatial clusters that we interpret as local discrete faults that intersect the NE-dipping seismogenic fault of the 4 April 2021 Mw 5.4 earthquake, which is the largest instrumentally recorded earthquake in Namibia to date. We name the Mw 5.4 host fault "Anker Fault" and constrain its orientation using Sentinel 1 Interferometric Satellite Aperture Radar (InSAR) to image surface uplift and subsidence patterns. Given the sudden onset of the 2018 seismic activity and the absence of dams, mineral or energy exploration projects nearby, we eliminated the possibility of anthropogenic triggering. We suggest that the proximal cause for 2018 seismicity is shallow groundwater migration, possibly associated with nearby hot springs and modulated by tidal forces. The Kamanjab Inlier area has shown an increase in the number and magnitude of earthquakes from 2018 to 2021, which could pose a seismic hazard in the future. Our study introduces an earthquake detection and relocation workflow that can be adopted for regions with limited instrumentation.

Depth-varying azimuthal anisotropy and mantle flow in the Patagonian slab window

2025-07-22T06:35:16-04:00

Subduction of spreading ridges forms slab windows which perturb the local structure and dynamics of the upper mantle. Slab windows may alter the pattern of mantle flow and serve as portals for the exchange of mantle material between upper mantle reservoirs that are otherwise separated by the boundary of the subducting slab. Here, we use Rayleigh waves to derive an azimuthally anisotropic regional seismic velocity model for the Patagonian slab window and use the anisotropy model to infer patterns of upper mantle flow and deformation. Anisotropic fast directions are primarily trench-parallel in the upper ~40 km of the mantle throughout the region, likely reflecting the history of subduction and compression along the South American margin. At greater depths sensed by long-period Rayleigh waves, fast directions within the youngest part of the slab window are consistent with cross-basin mantle flow between the Atlantic and Pacific, as previously suggested by shear wave splits. Overall, the anisotropic velocity model reveals complex, depth-dependent patterns of mantle deformation and flow within the Patagonian slab window.

The 1804 Alborán seismic series: Search for the source using seismic scenarios and static stress interactions

2025-03-28T18:36:26-04:00

Linking historical earthquakes with the faults that caused them is crucial for seismic hazard assessment. Historical documentation describing the effects of an earthquake is a useful information source, from which we can compile the observed intensity field of the earthquake. In this work, we use intensity data from the catastrophic 1804 Alborán earthquake (south of Iberia) along with intensity simulations and coseismic stress transfer analysis to search for this earthquake's seismic source. We build intensity simulations for each fault proposed as a potential source, and compare these simulations with the intensity field. We also propose the possibility of the Alborán 1804 earthquake triggering the Dalías earthquake (European macroseismic intensity (IEMS-98) IX), which occurred seven months after, and analyze stress transfer between the possible sources of both earthquakes. Our results point to a conjunct rupture of the northern Al-Idrissi Fault segment and the North–South Faults as the most likely source for the Alborán earthquake.

ScarpLearn: an automatic scarp height measurement of normal fault scarps using convolutional neural networks

2025-04-01T13:57:39-04:00

Geomorphic markers such as displaced surfaces, offset rivers or scarps are witnesses to the neotectonic activity of the faults.
The characterization (such as fault detailed surface trace, the scarp height, etc.) of these geomorphological markers is currently a time-consuming step with expert-dependent results, often qualitative and with uncertainties that are difficult to estimate. To overcome those issues, we present a proof of concept study for the use of deep learning in morphotectonics, specifically on fault markers. We developed a Bayesian supervised machine learning method using one-dimentional (1D) convolutional neural networks (CNN) trained on a database of simulated topographic profiles across normal fault scarps, called ScarpLearn. From a topographic profile, ScarpLearn is able to automatically give the cumulative scarp height with an uncertainty. We have developed two versions: one designed for more generalized cases involving profiles with multiple fault scarp (ScarpLearn), and another specifically trained to handle profiles featuring a single fault scarp (ScarpLearn_1F). We apply ScarpLearn for the characterization of active normal faults in extensional settings such as the Trans-Mexican Volcanic Belt and Malawi Rift system. From those specific case studies, we explore the progress (computation time, accuracy, uncertainties) that machine learning methods bring to the field of morphotectonics, as well as the current limits (such as
bias). Our results show that we are able to develop a CNN model that is estimating scarp heights on topographic profiles from 5m resolution digital elevation model. We compared the results obtained with ScarpLearn and other non deep-learning methods. ScarpLearn achieves similar accuracy while being much faster and having smaller uncertainties. We invite readers to use and to extend our study: codes to build the synthetic scarp database and for the CNN model ScarpLearn are available at: https://gricad-gitlab.univ-grenoble-alpes.fr/poussel/scarplearn.

Alaska Upper Crustal Velocities Revealed by Air-to-Ground Coupled Waves From the 2022 Hunga Tonga-Hunga Ha’apai Eruption

2025-07-08T12:54:53-04:00

Pressure changes in the atmosphere couple to the solid earth, producing ground motions that contain information about local crustal elastic parameters. This type of air-to-ground coupled wave was observed globally following the largest explosion of the instrumental age, the climactic eruption of the Hunga Tonga-Hunga Ha’apai volcano on 15^th January, 2022. We utilize this unprecedented source, along with the presence of colocated seismometers, infrasound sensors, and barometers in Alaska, to examine coupling and reveal elastic parameters beneath the stations. We derive coupling spectra by forming seismic--to--pressure amplitude ratios as a function of frequency, and identify passbands of high coherence between the pressure and seismic records. By relating coupling spectra in high-coherence bands to elastic parameters, we estimate mean shear wave velocities under stations to a depth encompassing much of the upper crust. Our velocity estimates from low-frequency coupling exhibit good agreement with a previously existing tomographic velocity model from Berg et al. (2020), while estimates from high-frequency coupling show considerable scatter when compared to proxy V_s30, even though the overall values are reasonable. In addition to providing velocity estimates, our results also indicate that, for the broadband pressure signals from the Hunga Tonga-Hunga Ha’apai eruption, microseismic noise exerts a strong effect on the frequency bands where coupling is observed, and that the air-to-ground coupled waves exhibit significant complexity not necessarily described by theory. Our results show that coupling observations provide a simple forward observation of mean seismic velocities beneath seismoacoustic stations, without the need to resort to complex inversion schemes. It is remarkable that pressure waves generated thousands of kilometers away are able to reveal the seismic velocity structure of Alaska to several kilometers depth.

Investigating the D" Reflector Beneath the Indian Ocean with Source Arrays

2025-07-08T12:54:55-04:00

We used seismic P-wave reflections to search for the discontinuity at the top of the D" region beneath the Indian Ocean. Due to a lack of seismic receiver arrays to target this region, we build source arrays using earthquakes in Indonesia and taking advantage of the long-running history of GEOSCOPE stations located in the western Indian Ocean and Antarctica, as well as three additional stations (Seychelles and Antarctica). Despite restricting the earthquake depth range, source-array stacks were difficult to interpret due to complications arising from differing earthquake depths, violating the plane wave assumption. Therefore, we use a source-array scatter imaging method, that does not rely on travel-times calculated for a plane wave. Using this technique in conjunction with source normalization, we found evidence for a D" P-wave reflector for several stations with reflector depths varying between 230-160 km above the CMB South of Australia and 190 to 270 km above the CMB beneath the Indian Ocean, where the depth of the reflector in the north of our study area is consistent with previously imaged D" depths using S-waves and agrees with receiver array data. We suggest that earlier imaged subducted lithosphere in this region is responsible for our D" reflections.