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The versatility and cost efficiency of fibre-optic distributed acoustic sensing (DAS) technologies facilitate geophysical monitoring in environments that were previously inaccessible for instrumentation. Moreover, the spatio-temporal data density permitted by DAS naturally appeals to seismic array processing techniques, such as beamforming for source location. However, the measurement principle of DAS is inherently different from that of conventional seismometers, providing measurements of ground strain rather than ground motion, and so the suitability of traditional seismological methods requires in-depth evaluation. In this study, we evaluate the performance of a DAS array in the task of seismic beamforming, in comparison with a co-located nodal seismometer array. We find that, even though the nodal array achieves excellent performance in localising a regional ML 4.3 earthquake, the DAS array exhibits poor waveform coherence and consequently produces inadequate beamforming results that are dominated by the signatures of shallow scattered waves. We demonstrate that this behaviour is likely inherent to the DAS measurement principle, and so new strategies need to be adopted to tailor array processing techniques to this emerging measurement technology. One strategy demonstrated here is to convert the DAS strain rates to particle velocities by spatial integration using the nodal seismometer recordings as a reference, which dramatically improves waveform coherence and beamforming performance and warrants new types of “hybrid” array design that combine dense DAS arrays with sparse seismometer arrays.

The strength properties of fault rocks at shearing rates spanning the transition from crystal–plastic flow to frictional slip play a central role in determining the distribution of crustal stress, strain, and seismicity in tectonically active regions. We review experimental and microphysical modelling work, which is aimed at elucidating the processes that control the transition from pervasive ductile flow of fault rock to rate-and-state-dependent frictional (RSF) slip and to runaway rupture, carried out at Utrecht University in the past 2 decades or so. We address shear experiments on simulated gouges composed of calcite, halite–phyllosilicate mixtures, and phyllosilicate–quartz mixtures performed under laboratory conditions spanning the brittle–ductile transition. With increasing shear rate (or decreasing temperature), the results consistently show transitions from (1) stable velocity-strengthening (v-strengthening) behaviour, to potentially unstable v-weakening behaviour, and (2) back to v strengthening. Sample microstructures show that the first transition seen at low shear rates and/or high temperatures represents a switch from pervasive, fully ductile deformation to frictional sliding involving dilatant granular flow in localized shear bands where intergranular slip is incompletely accommodated by creep of individual mineral grains. A recent microphysical model, which treats fault rock deformation as controlled by competition between rate-sensitive (diffusional or crystal–plastic) deformation of individual grains and rate-insensitive sliding interactions between grains (granular flow), predicts both transitions well. Unlike classical RSF approaches, this model quantitatively reproduces a wide range of (transient) frictional behaviours using input parameters with direct physical meaning, with the latest progress focusing on incorporation of dynamic weakening processes characterizing co-seismic fault rupture. When implemented in numerical codes for crustal fault slip, the model offers a single unified framework for understanding slip patch nucleation and growth to critical (seismogenic) dimensions, as well as for simulating the entire seismic cycle.

Human subsurface activities induce significant hazard by (re-)activating slip on faults, which are ubiquitous in geological reservoirs. Laboratory and field (decametric-scale) fluid injection experiments provide insights into the response of faults subjected to fluid pressure perturbations, but assessing the long-term stability of fault slip remains challenging. Numerical models offer means to investigate a range of fluid injection scenarios and fault zone complexities and require frictional parameters (and their uncertainties) constrained by experiments as an input. In this contribution, we propose a robust approach to extract relevant microphysical parameters that govern the deformation behaviour of laboratory samples. We apply this Bayesian approach to the fluid injection experiment of Cappa et al. (2019) and examine the uncertainties and trade-offs between parameters. We then continue to analyse the field injection experiment reported by Cappa et al. (2019), from which we conclude that the fault-normal displacement is much larger than expected from the adopted microphysical model (the Chen–Niemeijer–Spiers model), indicating that fault structure and poro-elastic effects dominate the observed signal. This demonstrates the importance of using a microphysical model with physically meaningful constitutive parameters, as it clearly delineates scenarios where additional mechanisms need to be considered.

Estimating the recurrence intervals and magnitudes of earthquakes for a given fault is essential for seismic hazard assessment but often challenging due to the long recurrence times of large earthquakes. Fault network geometry (i.e. spatial arrangement between faults) plays a key role in modulating stress interactions and, consequently, earthquake recurrence and magnitude. Here, we investigate these effects of fault network geometry using earthquake cycle models to generate numerous earthquakes on two different networks of normal faults in Italy: the Central Apennines, characterised by a wide network of faults offset across strike, and the Southern Apennines, a narrow fault network where faults are predominantly arranged along strike. For each region, we ran an earthquake cycle simulation on systems of seven normal faults generating approximately 150 earthquakes. In the Central Apennines, co-seismic stress transfer between faults promotes more heterogeneous stress, more partial ruptures, greater Mw variability and less periodic behaviour of large earthquakes (coefficient of variation of recurrence time, CV 0.1–0.9). In contrast, faults in the Southern Apennines experience more homogeneous stress loading, leading to a higher proportion of full-fault ruptures with more regular recurrence intervals (CV 0–0.4). In both fault networks, high long-term slip rate amplifies the effects of fault interactions: faults with higher long-term slip rate are more sensitive to positive stress perturbations from nearby faults compared to slower-moving faults. These results highlight that incorporating stress interactions from fault network geometry into seismic hazard models is particularly important for networks of faults offset across strike, where rupture behaviour is more variable.

Multiple lines of evidence indicate that the 2023 Mw 7.8 Turkey earthquake started on a splay fault, then branched bilaterally onto the nearby East Anatolian Fault (EAF). This rupture pattern includes one feature deemed implausible, called backward rupture branching: rupture propagating from the splay fault onto the SW EAF segment through a sharp corner (with an acute angle between the two faults). To understand this feature, we perform 2.5-D dynamic rupture simulations considering a large set of possible scenarios. We find that both subshear and supershear ruptures on the splay fault can trigger bilateral ruptures on the EAF, which themselves can be either subshear, supershear, or a mixture of the two. In most cases, rupture on the SW segment of the EAF starts after rupture onset on its NE segment: the SW rupture is triggered by the NE rupture. Only when the EAF has initial stresses very close to failure, its SW segment can be directly triggered by the initial splay-fault rupture, earlier than the activation of the NE segment. These results advance our understanding of the mechanisms of multi-segment rupture and the complexity of rupture processes, paving the way for a more accurate assessment of earthquake hazards.

On November 11, 2019, a Mw 4.9 earthquake hit the region close to Montelimar (lower Rhône Valley, France), on the eastern margin of the Massif Central close to the external part of the Alps. Occuring in a moderate seismicity area, this earthquake is remarkable for its very shallow focal depth (between 1 and 3 km), its magnitude, and the moderate to large damages it produced in several villages. InSAR interferograms indicated a shallow rupture about 4 km long reaching the surface and the reactivation of the ancient NE-SW La Rouviere normal fault in reverse faulting in agreement with the present-day E-W compressional tectonics. The peculiarity of this earthquake together with a poor coverage of the epicentral region by permanent seismological and geodetic stations triggered the mobilisation of the French post-seismic unit and the broad French scientific community from various institutions, with the deployment of geophysical instruments (seismological and geodesic stations), geological field surveys, and field evaluation of the intensity of the earthquake. Within 7 days after the mainshock, 47 seismological stations were deployed in the epicentral area to improve the Le Teil aftershocks locations relative to the French permanent seismological network (RESIF), monitor the temporal and spatial evolution of microearthquakes close to the fault plane and temporal evolution of the seismic response of 3 damaged historical buildings, and to study suspected site effects and their influence in the distribution of seismic damage. This seismological dataset, completed by data owned by different institutions, was integrated in a homogeneous archive and distributed through FDSN web services by the RESIF data center. This dataset, together with observations of surface rupture evidences, geologic, geodetic and satellite data, will help to unravel the causes and rupture mechanism of this earthquake, and contribute to account in seismic hazard assessment for earthquakes along the major regional Cévenne fault system in a context of present-day compressional tectonics.

On November 11, 2019, a M w 4.9 earthquake hit the region close to Montelimar (lower Rhône Valley, France), on the eastern margin of the Massif Central close to the external part of the Alps. Occuring in a moderate seismicity area, this earthquake is remarkable for its very shallow focal depth (between 1 and 3 km), its magnitude, and the moderate to large damages it produced in several villages. InSAR interferograms indicated a shallow rupture about 4 km long reaching the surface and the reactivation of the ancient NE–SW La Rouvière normal fault in reverse faulting in agreement with the present-day E–W compressional tectonics. The peculiarity of this earthquake together with a poor coverage of the epicentral region by permanent seismological and geodetic stations triggered the mobilisation of the French post-seismic unit and the broad French scientific community from various institutions, with the deployment of geophysical instruments (seismological and geodesic stations), geological field surveys, and field evaluation of the intensity of the earthquake. Within 7 days after the mainshock, 47 seismological stations were deployed in the epicentral area to improve the Le Teil aftershocks locations relative to the French permanent seismological network (RESIF), monitor the temporal and spatial evolution of microearthquakes close to the fault plane and temporal evolution of the seismic response of 3 damaged historical buildings, and to study suspected site effects and their influence in the distribution of seismic damage. This seismological dataset, completed by data owned by different institutions, was integrated in a homogeneous archive and distributed through FDSN web services by the RESIF data center. This dataset, together with observations of surface rupture evidences, geologic, geodetic and satellite data, will help to unravel the causes and rupture mechanism of this earthquake, and contribute to account in seismic hazard assessment for earthquakes along the major regional Cévenne fault system in a context of present-day compressional tectonics.

On November 11, 2019, a M\\(_{\\mathrm{w}}\\) 4.9 earthquake hit the region close to Montelimar (lower Rhône Valley, France), on the eastern margin of the Massif Central close to the external part of the Alps. Occuring in a moderate seismicity area, this earthquake is remarkable for its very shallow focal depth (between 1 and 3 km), its magnitude, and the moderate to large damages it produced in several villages. InSAR interferograms indicated a shallow rupture about 4 km long reaching the surface and the reactivation of the ancient NE–SW La Rouvière normal fault in reverse faulting in agreement with the present-day E–W compressional tectonics. The peculiarity of this earthquake together with a poor coverage of the epicentral region by permanent seismological and geodetic stations triggered the mobilisation of the French post-seismic unit and the broad French scientific community from various institutions, with the deployment of geophysical instruments (seismological and geodesic stations), geological field surveys, and field evaluation of the intensity of the earthquake. Within 7 days after the mainshock, 47 seismological stations were deployed in the epicentral area to improve the Le Teil aftershocks locations relative to the French permanent seismological network (RESIF), monitor the temporal and spatial evolution of microearthquakes close to the fault plane and temporal evolution of the seismic response of 3 damaged historical buildings, and to study suspected site effects and their influence in the distribution of seismic damage. This seismological dataset, completed by data owned by different institutions, was integrated in a homogeneous archive and distributed through FDSN web services by the RESIF data center. This dataset, together with observations of surface rupture evidences, geologic, geodetic and satellite data, will help to unravel the causes and rupture mechanism of this earthquake, and contribute to account in seismic hazard assessment for earthquakes along the major regional Cévenne fault system in a context of present-day compressional tectonics.

Dendrometry is the main non-invasive macroscopic technique commonly used in plant physiology and ecophysysiology studies. Over the years several types of dendrometric techniques have been developed, each with their respective strengths and drawbacks. Automatic and continuous monitoring solutions are being developed, but are still limited, particularly for non-invasive monitoring of large-diameter trunks. In this study, we propose a new type of automated dendrometer based on distributed fibre-optic sensing that continuously measures the change in stem circumference, is non-invasive, and has no upper limit on the trunk diameter on which it can be installed. We perform a three-month validation experiment during which we deploy a fibre-optic cable at three localities around the trunks of two specimens of Brachychiton. We verify the accuracy of this new method through comparison against a conventional point-dendrometer, and we observe a consistent time lag between the various measurement locations that varies with the meteorological conditions. Finally, we discuss the feasibility of the fibre-based dendrometer in the context of existing dendrometric techniques and practical experimental considerations.

Distributed Acoustic Sensing (DAS) that transforms city-wide fiber-optic cables into a large-scale strain sensing array has shown the potential to revolutionize urban traffic monitoring by providing a fine-grained, scalable, and low-maintenance monitoring solution. However, the real-world application of DAS is hindered by challenges such as noise contamination and interference among closely traveling cars. In response, we introduce a self-supervised U-Net model that can suppress background noise and compress car-induced DAS signals into high-resolution pulses through spatial deconvolution. Our work extends recent research by introducing three key advancements. Firstly, we perform a comprehensive resolution analysis of DAS-recorded traffic signals, laying a theoretical foundation for our approach. Secondly, we incorporate space-domain vehicle wavelets into our U-Net model, enabling consistent high-resolution outputs regardless of vehicle speed variations. Finally, we employ L-2 norm regularization in the loss function, enhancing our model's sensitivity to weaker signals from vehicles in remote traffic lanes. We evaluate the effectiveness and robustness of our method through field recordings under different traffic conditions and various driving speeds. Our results show that our method can enhance the spatial-temporal resolution and better resolve closely traveling cars. The spatial deconvolution U-Net model also enables the characterization of large-size vehicles to identify axle numbers and estimate the vehicle length. Monitoring large-size vehicles also benefits imaging deep earth by leveraging the surface waves induced by the dynamic vehicle-road interaction.