Kristel Chanard

Long-term deformation of the Earth’s surface inferred from Global Navigation Satellite Systems (GNSS) station position time series plays a central role in high-precision geodetic and geophysical applications, such as terrestrial reference frame realization, crustal deformation and strain rate estimation, or vertical land motion estimates for improved sea level change assessment. GNSS station position time series contain stochastic variations, often referred to as noise, that exhibit spatial correlations over distances of thousands of kilometers. The impact of these spatial correlations on the uncertainty of longterm station velocity estimates, however, remains poorly modeled and is therefore largely neglected. To address this limitation, we build on recent advances in the characterization and modeling of the spatio-temporal correlations of the noise in GNSS station position time series. We develop a multi-scale spatio-temporal noise correlation model and use it to derive the full covariance matrix of errors in a global station velocity field. Our results show that the spatio-temporally correlated noise induces significant and non-trivial correlations across station velocity errors, which depend not only on the distance between stations but also on the temporal overlap of the station position time series. Accounting for these spatial correlations could significantly improve the detection and uncertainty assessment of subtle long-term deformation signals. Plain Language Summary Position time series of Global Navigation Satellite Systems (GNSS) stations provide essential information about the long-term deformation of the Earth’s surface. However, the detection of subtle long-term deformation signals is limited by the presence of time-correlated noise in GNSS station position time series. Part of this noise has a largescale spatial structure, meaning that stations separated by large distances can experience similar noise patterns. This is usually ignored when estimating long-term deformation rates and their associated uncertainties. In this study, we describe how to model and account for spatially correlated noise in GNSS station position time series. This leads to more realistic uncertainty estimates for GNSS-derived long-term deformation and can benefit a variety of high-precision geodetic and geophysical applications.

Déformation saisonnière de la Terre sous l’effet des variations hydrologiques : impact sur la sismicité: Cette thèse a pour objectif de modéliser les déformations saisonnières de la Terre associées aux redistributions de masses d’eau de l’hydrosphère. Pour cela, nous tirons profit de la mesure des déplacements saisonniers du sol par Global positioning system (GPS) et de l’estimation des variations spatio-temporelles de l’hydrosphère déduite du champs de gravité terrestre mesuré par la mission Gravity and recovery climate experiment (GRACE). Ces données ouvrent la voie à des modèles précis de la déformation saisonnière, discutés dans le chapitre 1, qui auront des implications importantes pour la définition des référentiels terrestres, l’identification d’évènements tectoniques de glissement de période comparable ou encore pour la compréhension du lien entre déformation et sismicité saisonnière. Dans le chapitre 2, nous montrons que les déformations saisonnières mesurées en Himalaya sont expliquées par la réponse de la Terre à la charge saisonnière de GRACE qui produit des déplacements de surface cohérents au premier ordre avec les observations horizontales et verticales simultanément à condition d’utiliser un modèle de Terre réaliste, sphérique et stratifié. Nous étendons ensuite le modèle à l’échelle globale dans le chapitre 3, et comparons les déplacements induits par la charge saisonnière à 195 stations GPS, en tenant compte des contributions de degré-1 dans le signal GRACE (Swenson et al., 2008). Alors que la composante verticale est raisonnablement prédite, les composantes horizontales sont systématiquement sous-estimées et leur phase est mal reproduite. Nous montrons que ce désaccord entre modèle et observations horizontales à l’échelle mondiale peut être associé au premier ordre à une contribution de degré-1 sous-estimée, et non à la grande résolution spatiale de GRACE. Nous proposons de l’estimer à posteriori grâce à une transformation d’Helmert, représentant le mouvement du géocentre ainsi qu’une partie de la déformation de degré-1. La corrélation entre modèle et données horizontales est nettement améliorée, sans que les prédictions verticales soient affectées. Au second ordre, nous montrons que les variations de volume dans le manteau terrestre liées aux changements de phase des minéraux qui le composent peuvent jouer un rôle dans la déformation saisonnière. Enfin, nous montrons qu’il est possible d’utiliser la déformation saisonnière pour déterminer une borne inférieure de la viscosité transitoire de l’asthénosphère, paramètre clé des modèles de déformation postsimique. Afin de tester l’hypothèse d’un impact des charges saisonnières sur la sismicité, nous examinons les variations de contrainte liées aux chargements saisonniers de surface. Nous menons également des expériences de déformation triaxiale sur des grès de Fontainebleau, saturés en eau soumis à des paliers de contrainte simulant un chargement tectonique, ainsi qu’à des oscillations sinusoïdales de la pression de pore simulant les marées ou l’hydrologie continentale. Nos observations expérimentales, détaillées dans le chapitre 4 suggèrent que les chargements périodiques de faible amplitude peuvent jouer un rôle important dans la longue phase de nucléation des séismes.

La Soufrière de Guadeloupe volcano exhibits microseismic activity dominated by volcano‐tectonic repeaters, mainly occurring in swarms clustered in a sub‐vertical conduit beneath the Tarissan acid lake (TAS) at depths less than 800 m. Following the April 2018 earthquake (Mlv 4.1), which likely damaged the dome, swarms intensified and show seasonal modulation with more events in October–November. We analyze 5 years of daily seismicity, GNSS‐derived deformation, and hydrological data to investigate controls on this modulation. We enhance groundwater level resolution by modeling TAS level from daily rainfall. To isolate local seasonal deformation, we compute Global Navigation Satellite Systems (GNSS) baselines and derive regional strain time series. Using Multichannel Singular Spectrum Analysis, we identify annual and sub‐annual oscillations in seismicity, groundwater, and vertical strain, highlighting hydrological forcing. Elastic deformation from surface load cannot explain observed strain or stress at depth. In contrast, a poroelastic model calibrated with GNSS strain and lake‐level variations shows pore pressure fluctuations modulate Coulomb stresses by several kPa at microseismic depths. Stress amplitude and phase match seismicity peaks, supporting pore pressure as the main driver of seasonal modulation. Effective elastic moduli from geodetic data are an order of magnitude lower than laboratory rock values, consistent with a fractured dome. Our multi‐parameter time series analysis separates hydrologically driven background seismicity from residual signals, potentially linked to thermoelastic effects or magmatic fluid migration, offering a framework to detect departures from external forcing and improve monitoring of hydrothermal unrest and phreatic eruption precursors.

Monitoring essential climate variables such as Sea level rise, Earth’s Energy Imbalance, and ice-mass changes relies critically on space-geodetic observations of surface deformation and variations of the gravity field. In particular, satellite geodesy provides decades-long, globally consistent records that are fundamental for quantifying climate-driven surface mass redistribution. However, these observations integrate both mass changes from the oceans, atmosphere, cryosphere and continental hydrology and the associated solid Earth response. Isolating climate variables from geodetic data therefore requires models that reflect the solid Earth response across timescales relevant to contemporary variability.Yet, a critical assumption underlies much of current space-geodetic standard processing: the solid Earth response to surface mass variations is treated as purely elastic, i.e. instantaneous and fully recoverable. However, there is a growing body of evidence from laboratory rock mechanics experiments and geophysical observations suggesting that the Earth’s mantle exhibits a time-dependent, recoverable anelastic response across intermediate timescales that could significantly affect geodetic at decadal to centennial timescales.Here, we exploit several decades of Satellite Laser Ranging (SLR) observations towards passive spherical satellites to constrain key parameters governing the time-dependent mantle anelasticity. Owing to long-term measurements and sensitivity to low-degree gravity field variations, including solid Earth tides (C20, C30) and the pole tide (C21/S21), SLR observations are particularly well suited to probing deep Earth mantle rheology over decadal timescales.We combine analytical orbit perturbation theory with the Hill-Clohessy-Wiltshire equations to quantify the sensitivity of the SLR observables to rheology and to choose an optimal parametrization. We then numerically estimate the solid Earth transient rheological properties from the SLR time series using an anelasticity framework consistent with seismic attenuation theory. Our results are compared with independent rheological constraints and yield a new set of frequency-dependent Love numbers that capture the Earth’s mantle transient rheology across decadal timescales. We further show that accounting for this transient rheology by incorporating the corresponding frequency-dependent Love numbers into the modeling of solid Earth tides, pole tide and surface loading-induced deformation, introduces systematic differences in climate-relevant geodetic time-series, including satellite altimetry sea level rise estimates and ocean mass trends derived from satellite gravimetry.More broadly, our results show that as space geodetic records become longer, data processing cannot rely solely on an elastic solid Earth assumption. Instead, it must account for solid Earth transient rheology and the fact that geodetic observables will increasingly depend on the cumulative loading history, strengthening the need for interdisciplinary geodetic, geophysical and climate studies.

Variations in surface temperature and groundwater pressure within aquifer systems generate internal thermoelastic and poroelastic strain in the shallow subsurface, producing surface deformation and crustal stress perturbations. We develop a general mathematical framework to compute surface displacements and stresses at depth driven by internal strain, accounting for realistic mechanical properties of the Earth, including depth-dependent layering and lateral heterogeneities. We show that variations in surface temperature induce deformation below layers affected by internal strain and surface horizontal displacements that scale with the Young’s modulus of the shallow layers where internal strain occurs. Because these layers generally have weak elastic moduli across continental regions (soils, weathered rock, etc.), long-wavelength thermoelastic horizontal deformation is predicted to be negligible. In contrast, vertical displacements driven by thermal expansion within shallow weak layers are expected to reach the millimeter level, implying that thermoelastic effects should be considered when interpreting GNSS signals, in particular at the annual timescale.At regional scale, lateral contrasts in elastic properties, such as transitions from bedrock to sedimentary basins or across fault damage zones, can produce annual thermoelastic horizontal displacements up to a few mm. The associated annual thermoelastic stress perturbations at depths of a few km may reach several kPa, locally exceeding stresses induced by seasonal hydrological loading, suggesting a potential contribution of surface temperature forcing observed seasonal modulation of seismicity. Over longer timescales, progressive climate-driven warming may also cause non-negligible stress perturbations in intraplate regions. Using the same formalism, we investigate deformation and stresses induced by poroelastic pressure variations in aquifer systems. We show that for 10 m variations of the water table, vertical displacements of a few mm to a few cm are expected and lateral variations of elastic properties can generate horizontal deformation of a few mm and crustal stress perturbations of several kPa.

The Kerguelen Islands (49°S, 69°E), a volcanic archipelago in the southern Indian Ocean, have experienced substantial environmental change over recent decades, including significant retreat of the Cook ice cap. The rapid ice loss is expected to induce measurable crustal deformation.In this study, we use the complete archive of Sentinel-1 SAR imagery acquired since 2015 to examine the present-day deformation field of the Kerguelen Islands. Our small-baseline InSAR time-series analysis reveals a broad ~ 100 km-wide pattern of crustal uplift centered on the Cook ice cap, reaching up to ~ 6 mm/yr. To investigate the physical processes driving this uplift, we combine observed change in ice elevation inferred from multiple Digital Elevation Model over the 2015-2025 period with local estimates of shallow elastic properties derived from seismic experiments. Using a layered Cartesian elastic Earth model, we predict the surface deformation resulting from present-day unloading of the Cook ice cap, and compare model predictions to the InSAR-derived deformation field.We then explore time-dependent deformation scenarios by considering viscoelastic deformation of the solid Earth induced by a range of plausible ice-loss histories over recent decades, and show that recent ice melting in the Kerguelen island can be used to place constraints on the rheology of the Earth’s upper mantle at decadal timescales. Finally, given the volcanic setting of the Kerguelen Islands, we also investigate whether magmatic sources could contribute to the observed long-wavelength uplift pattern.Overall, this work highlights the potential of InSAR observations in remote subpolar environments to quantify ice-driven deformation and to infer solid Earth rheological properties on decadal timescales.

The International Terrestrial Reference Frame (ITRF) is the foundation for Earth science and operational geodesy applications. It is built on international cooperation over more than three decades for the benefit of countries, regions and global geodesy. Substantial improvements have been constantly made in the data analysis strategy, at the level of both individual geodetic techniques, as well as the ITRF combination, with the aim to improve the ITRF accuracy and reliability. Motivated by a number of reasons that will be exposed in this paper, the ITRS Center decided to regularly (yearly) update the ITRF2020, with a first update (ITRF2020-u2023) released in December 2024, a second update (ITRF2020-u2024) released in September 2025 and a third update foreseen in 2026. Results of these updates will be presented and discussed, with a special focus on the uncertainty evaluation regarding the stability of the frame physical parameters (origin and scale), as well as Earth Rotation Parameters when adding extended data from the four techniques: VLBI, SLR, GNSS and DORIS. Future plans and perspectives regarding the ITRF2020 updates and consequences for the most demanding user needs conclude the presentation.

SUMMARY: Seasonal variations in Nepalese seismicity have been reported with varying degrees of confidence. We re-investigate these claims by analysing 20 yr of Nepalese seismicity before the 2015 Gorkha earthquake, as detected by the Nepalese national network, and focusing on earthquakes located along the eastern and central sections of the Nepalese Main Himalayan Thrust. Using several declustering techniques, we find no statistically robust evidence of seasonal seismicity in the studied record, regardless of magnitude threshold above completeness. This suggests that previously reported seasonality may be restricted to the western section of the Nepalese orogeny, may be an artefact, or may indicate that nucleation times of earthquakes are longer than the year. We also investigate potential annual variations in the Gutenberg–Richter b-value, given its recent observed modulation by transient stressing. Additionally, we use large-scale mass redistribution estimated from the monthly gravity field retrieved from the Gravity Recovery And Climate Experiment and Follow-On (GRACE/-FO) missions, to resolve stress variations at depth induced by transient surface loads. We find that the mean annual b-value peaks when seasonal Coulomb stress rates reach their minimum value at the height of the summer rainy season. When considering the combined effect of tectonic and seasonal loading, this corresponds to a recurring period of stress reversal, when Coulomb stress momentarily decreases. This suggests that periodic clamping of the Main Himalayan Thrust reduces the likelihood of earthquakes growing to larger magnitudes in accordance with hierarchical rupture models. The susceptibility of b-value to stress variations of roughly 0.1 points.kPa$^{-1}$ is consistent with recent estimates of b-value sensitivity to transient loading, although it remains high when compared to the stress-dependence associated with both static differential stress, and with long-term evolution during the seismic cycle. This discrepancy points to the large impact of stress transients on the dynamics of seismic rupture.

Groundwater overdraft in arid and semi-arid regions poses a significant threat to sustainable water resources. In Balochistan, Pakistan, a region with limited precipitation (

Monthly estimates of the Earth’s gravity field based on the GRACE/-FO missions have enabled decisive progress in the quantification and understanding of mass transfers in the Earth system. However, raw level 2 GRACE/-FO solutions are affected by large errors in the form of North-South stripes. Several filtering methods have been developed to isolate the gravity signal from these errors, based on either spatial covariance models of the signal and errors (gaussian filters, DDK filters), or on statistical decomposition techniques (PCA, ICA, SSA, M-SSA). This presentation introduces a new filtering method that relies on both the temporal and spatial structures of the signal and errors.In the temporal domain, a spectral analysis of the GRACE/-FO Stokes coefficient time series suggests that they may be modeled as the sum of:linear trends, seasonal (annual and semi-annual) variations, ~160-day periodic variations, temporally uncorrelated aperiodic variations (white noise), temporally correlated aperiodic variations that may be described by a power-law stochastic process. Assuming that the linear trends, seasonal variations, and time-correlated aperiodic variations reflect gravity signal, that this signal is spatially isotropic, while the ~160-day variations and white noise are errors, we construct a spatio-temporal Wiener filter of the GRACE/-FO level 2 solutions. We then compare the results of this Wiener filter with those from the DDK5 filter and Gauer et al. (2023)’s M-SSA filter. The advantages, drawbacks and prospects for improvement of the Wiener filter are finally discussed.