Characterization and monitoring of the snow cover is highly applicable for numerous problems in mountain and arctic environments, including avalanche hazard and hydrology assessments. Remote sensing techniques from space or air are conventionally used to map and monitor large areas. To bridge the gap between satellite and ground scales, we propose the use of UAV-borne GPR systems to optimize areal coverage, resolution and repeatability for snowpack information. We present an extensive study of the potential applications and limitations when using UAV-borne GPR for snowpack characterization. We discuss the operational constraints and demonstrate various examples conducted in different environments. We tested low (400 MHz) and high (1 GHz) frequency GPR systems on a commercial off-the-shelf UAV equipped with a radar altimeter and terrain following capabilities. GPR data were acquired at three field sites in central and western Norway. We demonstrate that data repeatability is satisfactory and that any measurement differences are due to aircraft positioning errors. We also tested data acquisition from various flight altitudes above the snow surface which led us to the conclusion that recording data between altitudes of 2 to 4 m above the surface is the best compromise between flight safety and data quality. Regarding flight speeds, if we focus on layer tracking and do not require high lateral resolution for discrete target mapping, data can be acquired at 2 m/s or more as long as flight safety is ensured. We recommend recording data along pre-determined flight paths, downslope starting from the highest elevation and following profiles parallel to the slope. Kinematic timelapse surveys recorded at a two-week interval highlighted the capabilities for thin layer detection. Centimeter thick melt-freeze crust layers are visible on GPR profiles and are correlated with observed layers in neighboring snowpits. Additional tests in wet snowpacks showed that the penetration depth was limited with the 1 GHz antenna due to the attenuation related to the presence of liquid water in the snowpack. The use of a lower frequency antenna (400 MHz) enabled sufficient penetration depth even though it caused a loss in resolution for mapping the upper layers of the snowpack. Overall, the UAV GPR surveys showed promising results towards recording highly repeatable snow height and snow layering data which can be helpful for avalanche forecasting and hydrology studies.

Ubinas is the most active volcano in Peru and has exhibited recurrent eruptive activity in recent decades, including eruptions in 2006–2009, 2013–2017, 2019, and 2023–2025. Here, we present a three-dimensional magnetotelluric (MT) study aimed at investigating the structure and dynamics of its magmatic–hydrothermal system. The MT model reveals an asymmetric, trans-crustal conductive architecture extending from the lower crust to the surface. At depths of 32–40 km below the surface, a deep conductive anomaly (1–5 Ω·m) is interpreted as a primitive basaltic–andesitic magma reservoir, consistent with independent petrological and seismic constraints. Above this reservoir, two overlying, nearly vertical conductors at approximately 14–25 km and 5–13 km depth (8–15 Ω·m) are interpreted as deep and intermediate-crustal magma reservoirs, respectively. The intermediate-crustal reservoir is consistent with a crystal-rich mush containing melt fractions generally below 30%, whereas the deeper basaltic–andesitic reservoir is consistent with higher melt fractions, locally exceeding 50%. At shallow levels, a conductor (<5 Ω·m) is interpreted as an active hydrothermal system, overlain by a clay-rich conductive cap that controls fluid circulation and discharge. The spatial distribution of seismicity supports pathways linking the deep magmatic reservoirs with the shallow hydrothermal system. The low-resistivity anomaly beneath the southeastern flank is consistent with intense fracturing and hydrothermal alteration, suggesting progressive mechanical weakening. These results support a vertically organized trans-crustal magmatic–hydrothermal system beneath Ubinas, providing an integrated framework for understanding magma transport, fluid circulation, and volcanic hazards in active Andean volcanic systems.

Induced seismicity related to fluid injection in the upper crust is a major concern in the context of geothermal energy production. For exploited high-temperature geothermal systems in tectonically and volcanically active areas, such as Krafla caldera in NE Iceland, understanding the processes that trigger seismicity and changes in the local stress field can be difficult to unravel. We observe a link between anthropogenic activity and changes in the local stress field, since the appearance of a strike-slip cluster coincides with changes in the seismic anisotropy around an injection well during an injection interruption period. By analyzing the shear-wave splitting phenomenon, 90[Formula: see text] flips of the fast S-wave polarization and a decrease in the time delays between the fast and the slow S-wave component is observed, starting within hours after an injection stop, coinciding with a sharp increase of strike-slip events in the vicinity of the well. When the injection restarts, the seismic quiescence and increase of time delays may suggest a resumption of the previous state. The changes in seismicity patterns and variations of the seismic anisotropy might be linked to changes in the pore pressure and a possible activation of a shear-fault due to anthropogenic activity.

Understanding volcanic activity remains a challenging task. So far, several conceptual geodetic models have been proposed to describe the inter-eruptive period, typically invoking either progressive rock damage or increasing overpressure within the magmatic (or gas) reservoir. Here, we adopted a combined seismo-geodetic framework to investigate volcanic unrest and to model surface deformation at the Campi Flegrei (CF) volcano, Italy. The CF caldera is one of the most active hydrothermal systems in the Mediterranean region and has experienced notable unrest episodes. Since 2005 a monotonic uplift phenomenon has been observed, accompanied by unsteadily accelerating seismicity (Bevilacqua et al., 2022). Subsurface rocks sustain large strains and exhibit high shear and tensile strength (Vanorio & Kanitpanyacharoen, 2015). Consequently, seismicity reaches magnitude ~ 4.0 only upon relatively large uplifts ~70–80 cm during the 1980s unrest and >1 m during the recent episode), contrary to what is generally observed for calderas exhibiting much lower deformation levels (Hill et al., 2003).The caprock above the seismogenic zone is characterized by a fibril-rich matrix that enhances ductility and resistance to fracturing (Vanorio & Kanitpanyacharoen, 2015). However, changes in pore pressure and/or chemical alteration may ultimately induce mechanical failure and modify the structural properties of subsurface rocks. In addition, increased magma pressure within the reservoir can weaken the volcanic edifice, leading to reductions in elastic moduli (Carrier et al., 2015; Olivier et al., 2019). In recent years, a quasi-elastic behavior and a stress memory effect of the upper crust of the CF caldera under increasing stress suggest a progressive mechanical weakening (Bevilacqua et al., 2024; Kilburn et al., 2017, 2023). Seismic tomography indicates that most of the observed seismicity is associated with a pressurized gas reservoir (De Landro et al., 2025), while advanced big-data-based earthquake locations exclude shallow magma migration (Tan et al., 2025). Furthermore, recent petrological and geochemical studies identified a weak layer that plays a key role in overpressure accumulation, driving both deformation and seismicity (Buono et al., 2025). The initiation and growth of a volcano-tectonic fault have also been hypothesized (Giordano et al., 2025).In our study, we tracked the evolution of subsurface elastic properties by monitoring temporal changes in relative seismic wave velocities (δv/v) thanks to the coda wave interferometry of continuous ambient noise at local seismic stations. A progressive decrease in δv/v is detected in the area where we observe the highest concentration of seismicity and that we attribute to the rock-weakening tracked by the earthquake occurrences. By incorporating time-dependent elastic moduli changes in the geodetic inversion of surface displacement recorded by a local GPS network (De Martino et al, 2021), we retrieved a refined time evolution of reservoir overpressure. Our results suggest the active contribution of elastic properties of geomaterials in controlling the volcanic dynamics.

Field geological studies highlighted the heterogeneous structure of fault zones from the meter- to millimeter scale, but such internal variability is not generally resolved by seismological techniques due to spatial resolution limits. The near-surface velocity structure of the Vado di Corno seismogenic fault zone was quantified at different length scales, from laboratory measurements of ultrasonic velocities (few centimeters rock samples, 1 MHz source) to high-resolution first-arrival seismic tomography (spatial resolution to a few meters). The fault zone juxtaposed structural units with contrasting ultrasonic velocities. The fault core cataclastic units were slower compared to damage zone units. A negative correlation between ultrasonic velocity and porosity was observed, with dispersion in fault core units related to varying degree of textural maturity and pore space sealing by calcite. Low-velocity outliers in the damage zone were instead linked to microfracture networks with local cataclasis and partial calcite sealing. P-wave high-resolution seismic tomography imaged distinct fault-bounded rock bodies, matching the geometry and size of field-mapped structural units. At this length scale, relatively fast fault core units and low-strain damage zones contrasted with a very slow intensely fractured high-strain damage zone. The discrepancy between higher ultrasonic velocities and lower tomography-derived ones was reconciled through an effective medium approach considering the effect of meso-scale fractures in each unit. This revealed a heterogeneous fault zone velocity structure with different scaling among structural units. Lastly, the persistence of a thick compliant high-strain damage zone at shallow depth may significantly affect fault zone mechanics and the distribution of near-surface deformations.

Krafla, one of the five central volcanoes of the Northern Volcanic Zone in NE-Iceland, last erupted during the Krafla Fires in the 70s and 80s. During the same period, a geothermal power plant was built within Krafla caldera, first operated in 1978. Both scientific and industrial interest led to an increase of knowledge of the complex system through systematic exploration with a wide variety of geophysical methods including seismic and electromagnetics coupled with borehole information.Among them, a local seismic network operated by Landsvirkjun and Iceland GeoSurvey, comprising 12 permanent broadband stations, has been continuously recording seismic data since 2013. We supplemented this network in June 2022 with a dense network of 98 nodes, resulting in two arrays, one large-scale, the other small-scale, operating in parallel.Here we present multi-scale 3-D velocity models for P-, S- and surface waves, independently derived for both networks through local earthquake and ambient noise tomographies. These models offer a glimpse into the subsurface structures of the volcanic system by utilizing various types of waves that are responsive to distinct rock/fluid properties and depths. The relocated and clustered seismic activity, documented by both permanent and temporary networks, underscores active structures pinpointed through tomography. With this we hope to strengthen the understanding of the connected volcanic and geothermal systems. Indeed, both the seismicity and strong velocity anomalies are located at similar depths as the magma batch that was drilled into with the IDDP1.

Despite the existence of various hydrological and geophysical methods for characterizing the vadose zone and groundwater, it remains challenging to implement cost-effective, accurate, and efficient techniques for their long-term monitoring with high spatial resolution. A growing number of recent studies suggest that seismological methods based on continuous seismic noise recording can potentially address these difficulties. This study presents an original laboratory experiment aimed at assessing the sensitivity of passive seismic interferometry imaging (PII) to controlled fluctuations in water content. To achieve this, we used the recording of the seismic noise generated by a continuous seismic source to reconstruct ballistic surface Rayleigh waves propagating in the [200-500] Hz range within a 1-m scale sandbox. Multiple controlled cycles of water imbibition and drainage at the base of the sandbox produce significant variations in the seismic wavefield and especially in dominant surface waves. The large relative velocity variations (-35%), measured in Rayleigh waves with a fine temporal resolution, match the water pressure measurements conducted within the sandbox. The observations are well predicted by an original theoretical approach combining a Biot-Gassmann-Wood poroelastic model that incorporates effective pressure fluctuations and the frequency-dependent sensitivity kernels of Rayleigh waves. These results confirm the potential of the PII method in monitoring saturation changes in the vadose zone as well as the substantial effect of effective pressure fluctuations, at least when Rayleigh waves dominate ballistic arrivals.

Potential field geophysical data are frequently used to image geological features in volcanic systems/areas (faults, lithological contacts, alteration zones, geothermal systems, magmatic reservoirs). However, although crucial, it can prove challenging to accurately simulate data in such regions due to the major influence of strong topographic variations. To accurately account for topography with reasonable computational cost, we develop a numerical tool for the modeling and inversion of these data. The method consists of a numerical integration scheme of the integral equations predicting gravity and magnetic data on deformable hexahedral elements. The integrals are evaluated using high-order Gaussian quadrature. Physical properties of the subsurface are defined on discrete grid points, allowing to model discontinuities in the parameters not only at the surface, but also along surfaces within the models, enabling to represent faults, lithological contacts or cavities. Our method uses non-conformal meshes with automatic local refinements in regions with rapidly varying surface topography and in the vicinity of measurement points. In particular, we have developed a local and self-adaptive iterative refinement scheme based on a local convergence criterion of the numerical integration, allowing to reduce the effect of solution singularities close to observation points. The accuracy of our method is tested by comparing our model predictions with results obtained from the tomofast code (https://doi.org/10.5194/gmd-17-2325-2024) using a fine reference discretization of the topography with rectangular prisms. These tests were performed for the modeling of the gravity and magnetic effects of topography over the geothermal system of Krafla, Iceland for the case of ground-based and airborne data. Our modeling tool will ultimately be used for the independent or joint inversion of potential field data to make use of their different sensitivities in terms of physical parameters and also lateral and depth resolutions.

Elastic full-waveform inversion (FWI) is appealing for an enhanced integration of wave physics propagation and the resulting improved characterization of the subsurface due to the reconstruction of P- and S-wave velocity models. While the high computational cost of elastic FWI can be controlled using adequate numerical methods, the increase in the nonlinearity of elastic FWI calls for dedicated strategies to design initial P- and S-wave velocity models and access low-frequency data. We believe that the recent surge in ocean-bottom sensor acquisition is an opportunity to develop such strategies. The seismic ambient noise recorded by an array of receivers can be stacked to reconstruct interstation Green's functions that can be further used as low-frequency input data for elastic FWI to generate low-resolution P- and S-wave velocity models. We illustrate two applications of this strategy at two different scales: the first for near-surface imaging in a landslide context, the second for the reconstruction of a high-resolution S-wave velocity model at the Alps scale. In both cases, the seismic ambient noise Green's functions are efficiently matched, and accurate velocity models are built.

Facing the societal issues related to water resources management, the development of ambient noise-based seismology for monitoring fluids in the subsurface is promising but still challenging (1). In this study, we propose a seismological monitoring of shallow groundwater with high spatial resolution, by applying ambient noise interferometry techniques. On a glacio-alluvial plain containing a shallow aquifer near Grenoble (France), we installed a dense array of 50 seismic nodes settled during five days. A pumping test was performed in a borehole during the experiment, inducing a fast and heterogeneous response of the aquifer. We estimated relative changes in surface wave velocity (dV/V) from autocorrelations of ambient noise recorded by the 50 sensors. During the pumping phase, dV/V increases by more than 10% near the borehole, indicating a significant decrease in pore pressure. Mapping the seismological response to pumping suggests a high channelization of the hydrogeological paths. Poroelastic modeling combined with active seismic campaigns improves the interpretation of observations (2), paving the way to a high-resolution time-lapse 3D mapping of the water dome and potential fluxes.References1 - Gaubert‐Bastide, T., Garambois, S., Bordes, C., Voisin, C., Oxarango, L., Brito, D., & Roux, P. (2022). High‐resolution monitoring of controlled water table variations from dense seismic‐noise acquisitions. Water Resources Research, 58(8), e2021WR030680.2 - Voisin, C., Garambois, S., Massey, C., & Brossier, R. (2016). Seismic noise monitoring of the water table in a deep-seated, slow-moving landslide. Interpretation, 4(3), SJ67-SJ76.

Krafla, one of five central volcanoes of the Northern Volcanic Zone in Iceland, is utilized for geothermal energy production. Due to scientific and industrial interests, the volcano and its geothermal system have been imaged and monitored with various geophysical methods over the last decades leading to a better knowledge of its complex geological setting. Nonetheless, the unexpected encounter of magma at relatively shallow depths during drilling of the IDDP-1 well in 2009 proved that imaging small-scale structures remains challenging in such heterogeneous geological settings. With data from a local permanent 12 station seismic network owned by Landsvirkjun and operated by Iceland GeoSurvey since 2013, and a dense temporary network of 98 seismic nodes deployed for one month in 2022 in the center of Krafla caldera, we conducted a multi-scale analysis based on local earthquake tomography. This analysis enables us to identify small-scale velocity structures and improve earthquake locations. The newly obtained high-resolution 3D models for P- and S-wave velocities offer a glimpse into the subsurface structure of the volcanic system with both wave types being responsive to distinct rock/fluid properties. The relocated seismic activity highlights active structures pinpointed through the tomography, in particular the seismogenic zone at the boundary of high to low Vp/Vs ${V}_{p}/{V}_{s}$ ratios, close to where magma was repeatedly encountered. By comparing the newly obtained high-resolution velocity models with available well log data, such as formation temperature, we aim to enhance the understanding of the interconnected volcanic and geothermal systems in areas lacking in situ measurements.

Harmali & egrave;re is an active landslide located in a mountainous region of southern France where the presence of a thick layer of clays provides favourable conditions for the development of slowly moving landslides. However, at Harmali & egrave;re, the alternation of sudden reactivation and quiet episodes suggests that specific structural and geomechanical properties control its kinematics. In order to shed light on its subsurface properties, we deployed for one month a dense network of seismic nodes within the landslide and recorded active-source and ambient noise seismic data. These data sets have been first independently processed with dedicated interferometry-based processing and inversion workflows to reconstruct P-wave (active sources) and S-wave (seismic noise) velocity models. Full wave-equation tomography is then performed to improve the reliability and resolution of the obtained elastic model by iteratively fitting the virtual gathers obtained by cross-correlation of the ambient-noise recordings. As opposed to conventional ambient-noise tomography, the approach fully accounts for topography and 3-D elastic heterogeneities. The obtained high-resolution 3-D models are then qualitatively interpreted in terms of landslide properties and geological lithologies, that can influence landslide kinematics.

T & ecirc;te Rousse glacier is a small polythermal glacier in the Mont-Blanc massif (French Alps) that released a large outburst flood in 1892 when a water-filled intraglacial cavity suddenly drained. A new water-filled cavity was detected again in the central part of the glacier by a geophysical campaign in 2007. It has been pumped three times since to avoid another catastrophic flood. The volume of water in this central reservoir has decreased recently but recent geophysical surveys suggested that significant volumes of water could be stored in the upper part of the glacier. Here, we describe a seismic tremor signal detected in May 2022 probably generated by a water-filled reservoir within the glacier. The tremor started on 15 May a few days after temperature first increased above 0 degrees C. Tremor amplitude was stronger in the evening and is correlated with water level measured in a crevasse about 230 m downglacier. The time delay between temperature and tremor or water level is consistent with the time needed for water to infiltrate within the snow and into the glacier. We used different methods to locate this signal both from amplitude decay and from P and S waves arrival times. Both methods provide a similar location near the northern boundary of the glacier. Ground penetrating radar surveys performed in May 2024 have since detected a water-filled reservoir near this location. These results validate our interpretation of this seismic tremor being produced by changes in water-level in this reservoir.

Seismo-electromagnetic (SE) signals are created in fluid-saturated porous media by electrokinetic conversions at the pore scale. Two of these signals are frequently investigated: the first is a co-seismic wavefield, bounded to the propagating seismic waves, and the second is an electromagnetic (EM) wave created when a seismic wave passes through the interface between two porous media. Led by the effectiveness of SE phenomena in detecting thin layers (i.e., layers with thicknesses smaller than the seismic wavelength), many authors studied how a thin layer, or a combination of thin layers, can alter SE signals. In this context, the present work brings new experimental and numerical data as a means to further investigate the relation between the layer thickness and the EM interface-generated response. Particularly, we have noticed that the effect of layer thinning on the EM interface-generated waves is similar to what is observed for seismic waves, but with a maximum signal enhancing, due only to thickness, occurring when a layer has a thickness that is equal to half the wavelength of the P-wave impinging on the layer. We have also explored the effect of the pore-fluid electric conductivity on SE signals, since this parameter plays an important role on the SE fields. The fact that the EM interface-generated wave is very sensitive to contrasts of fluid conductivity, whereas seismic waves (and therefore the co-seismic) are, in effect, insensitive, is an appealing characteristic of SE exploration. By comparing experiments with simulations we have accessed the effect of fluid conductivity on SE wavefields, complementing previous studies with a quantitative analysis of the dependency of SE signals on this physical property. Moreover, we have evaluated the ability of the electrokinetic theory adopted in this study to predict our experimental data, and showed that it performs well in terms of waveform and amplitude behavior for all fluid conductivities considered.

Despite the availability of various geophysical techniques for characterizing the fluids in geological reservoirs, implementing cost-effective, accurate, and efficient methods for long-term monitoring with high spatial resolution remains challenging. Recent studies increasingly suggest that seismological methods based on continuous seismic noise recordings could help address these challenges. This study presents a novel laboratory experiment designed to evaluate the sensitivity of passive seismic interferometry (PII) imaging to controlled variations in water content. To do so, we utilized seismic noise generated by a continuous seismic source to reconstruct ballistic surface Rayleigh waves propagating in the [200-500] Hz frequency range within a 1-meter sandbox. Multiple controlled cycles of water imbibition and drainage at the sandbox base result in significant changes in the seismic wavefield, particularly in the dominant surface waves. The large relative velocity variations (δv/v) measured in Rayleigh waves with fine temporal resolution closely match pressure measurements made within the sandbox. These observations are well explained by an original theoretical model combining the Biot-Gassmann-Wood poroelastic framework, which accounts for effective pressure fluctuations, with the frequency-dependent sensitivity kernels of Rayleigh waves. The results confirm the potential of the PII method for monitoring saturation changes in reservoirs and highlight the substantial impact of effective pressure fluctuations.

Download This Paper Open PDF in Browser Add Paper to My Library Share: Permalink Using these links will ensure access to this page indefinitely Copy URL Copy DOI

Groundwater plays a critical role in sustaining ecosystems, agriculture, and human activities. Effective groundwater monitoring is essential for assessing aquifer health and managing water resources. This abstract provides a comprehensive overview of the emerging approach of utilizing ambient seismic noise for groundwater monitoring. Ambient seismic noise, generated by natural and anthropogenic sources, has proven to be a valuable source of information for characterizing subsurface properties. This technique leverages the continuous and ubiquitous nature of seismic signals, providing a non-invasive and cost-effective means to monitor changes in groundwater levels and properties. The methodology involves analyzing the variations in seismic noise patterns collected by a network of sensors deployed in proximity to the groundwater monitoring area. Changes in subsurface conditions, such as water table fluctuations or alterations in aquifer properties, induce measurable variations in seismic velocity and attenuation. By employing advanced signal processing techniques, researchers can extract valuable information about groundwater dynamics, recharge rates, and aquifer characteristics. This abstract discusses key advantages of ambient seismic noise-based groundwater monitoring, including its ability to offer real-time data, continuous monitoring capabilities, and the potential for early detection of groundwater-related anomalies. Furthermore, the method's non-intrusive nature minimizes environmental impact and reduces the need for extensive drilling or intrusive measurements. The challenges and limitations associated with this approach are also addressed, highlighting the need for further research to optimize data processing techniques, improve resolution, and enhance the method's applicability across diverse geological settings. As the field of ambient seismic noise-based groundwater monitoring continues to evolve, this abstract underscores its potential as a valuable tool for enhancing our understanding of subsurface hydrological processes and advancing sustainable water resource management practices. The integration of ambient seismic noise into existing groundwater monitoring frameworks holds promise for revolutionizing how we assess and manage this vital component of the Earth's water cycle.

Polythermal glaciers can trap considerable volumes of liquid water with the potential to generate devastating outburst floods. This study aims to identify water-filled subglacial reservoirs from ambient seismic noise collected by moderate-cost surveys. The horizontal-to-vertical spectral ratio technique is highly sensitive to impedance contrasts at interfaces, thus commonly used to estimate glacier thickness. Here, we focus on the inverse ratio, that is, the V/H spectral ratio (VHSR), whose high values indicate a low impedance volume beneath the surface, suggesting subglacial cavities. We analyze VHSR peaks from a seismic array of 60 nodes installed on the Tete-Rousse Glacier (Mont Blanc massif, French Alps); data were gathered over 15 days. Mapping the VHSR amplitude over the free surface reveals the main cavity locations and the basal areas affected by melting within the glacier. Results obtained in the field are supported by a conceptual model based on 3D finite-element simulations. Considerable volumes of liquid water may be trapped within cavities in polythermal glaciers. If these cavities rupture, the resulting outburst flood has the potential to cause devastation in populated mountain areas. With the aim of testing methods to locate such cavities, we installed 60 small 3-component seismic sensors on the Tete-Rousse Glacier (Mont Blanc massif, French Alps), which is known to contain such cavities. We used these sensors to test a detection method based on ambient seismic noise. For 3 weeks, the sensors recorded vibrations within the glacier. On a glacier without cavities, these vibrations ought to be predominantly in the horizontal direction. In the presence of a cavity, we expect the ice above the cavity to vibrate mostly vertically-like a bridge. In this paper, we highlight areas on the glacier where vertical vibrations were stronger than horizontal vibrations. These areas fit well with the locations of the main known cavities in this glacier, and with areas affected by basal melting. We supported our field observations with modeling based on 3D simulations, paving the way to a new method to locate water-filled cavities within glaciers. Spectral analysis from ambient seismic noise is complementary to other geophysical methods for investigating glaciers at depth Results suggest that the vertical-to-horizontal spectral ratio is a reliable proxy to locate subglacial cavities Experimental results were confirmed using a simplified numerical model

From seismic interferometry, we investigate the strain sensitivity to seismic velocity variations related to a seismic swarm activity that occurred in 2013 along the Alto Tiberina low angle normal fault. We compute daily auto-correlation functions of ambient noise recorded at seismic stations located in the vicinity of the fault over the course of 10 years. Using the stretching technique, we compute daily velocity variations smoothed over a period of 100 days with a time lapse approach. Through the application of an optimization procedure based on synthetic modeling, we separate the non-tectonic, thermoelastic and rain induced velocity variations, from the tectonic components. Consequently, we unravel a significant velocity drop of 0.033% coinciding with the swarm occurring at seismogenic depth (3-5 km). Additionally, the time evolution of the velocity changes shows a direct relationship with the strain rate rather than the strain indicating a non-linear behavior of the crust induced by aseismic slip. The deduced strain sensitivity, exhibiting an order of magnitude comparable to that observed within volcanic settings, confirms this non-linear behavior and suggests the presence of pressurized fluids at depth. The driving mechanism of seismic swarms is still unclear. Seismic swarms are bursts of small earthquakes without a clear triggering mainshock. Understanding the physical processes driving these sequences is crucial for earthquake hazard assessment. To that scope, we focus in this study on a small seismic swarm that occurred in 2013 in northern Apennines, Italy. We monitor the properties of crustal rocks using continuous recordings of ambient seismic noise recorded at seismic stations located in the vicinity of the Alto Tiberina low angle normal fault over the course of 10 years. With this approach, we demonstrate the ability to retrieve quantitative information about the fault's state and to indirectly infer that the triggering of the swarm is mainly related to the presence of fluids in the crust. Velocity variations from seismic coda wave interferometry Separation of thermoelastic and hydrological stress induced velocity variation from tectonic changes Seismic swarm triggered by aseismic slip favored by the presence of fluids