Description du sujet de thèse

Slip dynamics along the creeping segment of the Haiyuan fault (Gansu, China), from the analysis of InSAR, seismological and strainmeter observations

Context and scientific objectives :
Monitoring ground deformation along active fault systems is essential for unraveling earthquake physics and improving seismic hazard assessment. In the past twenty years, the densification of seismological and geodetic networks (GNSS, strainmeters) in fault zones, as well as the advent of spatial imagery for geodesy (optical, for image correlation, or radar, for interferometry or InSAR), have made it possible to improve the accuracy of slip and strain measurements and develop new concepts and models of earthquake cycles along active faults (e.g. Bürgmann 2018). Episodic and slow, aseismic strain transients on faults, both in subduction zones and along major continental faults (e.g. Ide et al., 2007) have hence been revealed, with a complex interplay between slow aseismic events and rapid, devastating earthquakes. In particular, geodetic observations have shown that, while earthquakes may trigger aseismic slip on faults, slow slip may also contribute to the nucleation of large earthquakes (Bouchon et al., 2021). The observation of the dynamics of slow slip is thus a window into the physics of fault slip in general, hence a way to expand our understanding of the physics of earthquakes.
Capturing this dynamics remains a challenge, due to limitations in the detection capability of our geodetic techniques. However, recent advances in instrumentation and seismo-geodetic time series analysis now allow to further investigate such dynamics. In particular, it has recently been proposed that slow slip is governed by a rich dynamics of small intermingled slip events, merged into detectable slip events with characteristic times ranging from minutes to months or years (e.g. Jolivet et al., 2015, Frank, et al., 2018, Jolivet & Frank, 2020). This PhD will specifically focus on the analysis of InSAR time series analysis to characterize fault slip behavior, which has demonstrated its ability to detect spatio-temporal slip changes, especially since the generation of Sentinel-1 satellites (e.g. Aslan et al., 2020, Dalaison et al., 2021, Li et al., 2023). Our primary target will be the Haiyuan fault in China, a strike-slip fault exhibiting both seismic and aseismic (« creep ») slip (e.g. Cavalié et al., 2008, Jolivet et al., 2012, 2013, Daout et al., 2016, Ou et al., 2022). The work will be part of a French ANR project « X-strain » (see details below) in whih new, high accuracy, low cost, optical strainmeters, able to measure all components of the strain tensor, will be conceived and installed along the creeping section of the Haiyuan fault. InSAR data in the end will thus be analyzed together with these strainmeters data, as well as local seismicity and GNSS data from our Chinese partners. Integrating this continuous data flow into state-of-the art fault model should provide a new insight into the understanding of transient slip and slow earthquakes and their associated hazard.

Study area and approach :
The Haiyuan fault (Gansu province, China) is a left-lateral fault at the northeastern boundary of the Tibetan plateau (Gaudemer et al., 1995). As the San Andreas fault in California or the North Anatolian fault in Turkey, the fault exhibits a dual behavior, with both locked segments prone to major earthquakes and segments with aseismic slip. It has been extensively studied by InSAR to characterize in space but also in time its creep behavior since 1990. These previous InSAR studies showed that creep is spatially co-located with a micro-to-moderate seismicity zone (Figure 1), and unsteady in time with transient events interacting with the local seismic events (Jolivet et al., 2013). The 35-km-long creeping segment of the fault (Figure 1), at the junction between the M~8 1920 earthquake and a major seismic gap mature for a rupture (Jolivet et al. 2012), is specifically targeted in this project, and continuously monitored by our Chinese partners by GNSS and seismology due to its potential impact on the regional seismic hazard.
The PhD student will use high resolution time series of radar images acquired by the Sentinel-1 satellites over a seven-year period (2015-2022), processed by the ForM@Ter FLATSIM service (Thollard et al., 2021), and additional series from our own processing based on a small baseline subset approach, and a Kalman filter designed to allow automatic updates of the displacement time series after each new acquisition (Dalaison & Jolivet 2020). This will provide fine constraints on the creep velocities, how they vary spatially along the fault, and why, exploring potential controlling factors such as fault geometry and lithology. Subtle temporal fluctuations in creep velocities, likely associated with small loading perturbations, will be searched for. InSAR time series will be confronted to data from strainmeters when available (5 to 8 will be installed around the creeping segment) and cGNSS time series, to derive evolutive strain maps through a transdimensional Bayesian method (Pagani et al., 2021). They will also be jointly analyzed with indirect observations of creep and state of stress on the fault by seismology (based on template matching, relative relocation techniques and machine learning to assess the seismic activity and detect potential tremor activities related to aseismic slip at depth, Gardonio et al. 2018, Rouet-Leduc et al. 2020). Non-tectonic (eg hydrological) and tectonic signal separation (e.g. Lemrabet et al., 2023), and integrated, multi-data fault modeling to locate transients at depth with associated uncertainties will also be performed to explore a broad range of potential physical models.

References :
Aslan, G., Lasserre, C., Cakir, Z., Ergintav, S., Özarpaci, S., Dogan, U., Bilham, R., and Renard, F. (2019), Shallow creep along the 1999 Izmit earthquake rupture (Turkey) from GPS and high temporal resolution interferometric synthetic aperture radar data (2011–2017). Journal of Geophysical Research: Solid Earth, 124(2):2218–2236
Bouchon, et al. (2021). The nucleation of the Izmit and Düzce earthquakes: some mechanical logic on where and how ruptures began. Geophysical Journal International, 225(3), 1510-1517.
Bürgmann, R. (2018). The geophysics, geology and mechanics of slow fault slip, Earth Planet. Sci. Lett., 495, 112–134.
Cavalié, O., C. Lasserre, M.-P. Doin, G. Peltzer, J. Sun, X. Xu, Z.-K. Shen (2008), Measurement of interseismic strain across the Haiyuan fault (Gansu, China), by InSAR, Earth and Planetary Science Letters, Volume 275, Issues 3–4
Dalaison, M., R. Jolivet, E. M. van Risjingen & S. Michel (2021), The interplay between seismic and aseismic slip along the Chaman fault illuminated by InSAR, JGR - Solid Earth, Vol. 126
Daout, S., R. Jolivet, C. Lasserre, M.-P. Doin, S. Barbot, P. Tapponnier, G. Peltzer, A. Socquet, Sun Jianbao (2016), Along strike variations of the partitioning of convergence across the Haiyuan fault system detected by InSAR, Geophys. J. Int., 205 (1), 536-547
Frank W.B., B. Rousset, C. Lasserre, M. Campillo (2018), Revealing the cascade of slow transients behind a large slow slip event, Science Advances, 4 (5), doi : 10.1126/sciadv.aat0661
Gaudemer, Y., et al. (1995). Partitioning of crustal slip between linked, active faults in the eastern Qilian Shan, and evidence for a major seismic gap, the 'Tianzhu gap', on the western Haiyuan Fault, Gansu (China). Geophys. J. Int., 120(3), 599-645.
Gardonio, B., Jolivet, R., Calais, E., & Leclère, H. (2018). The April 2017 Mw6. 5 Botswana earthquake: An intraplate event triggered by deep fluids. Geophys. Res. Lett., 45(17), 8886-8896.
Ide, S., Beroza, G. C., Shelly, D. R., & Uchide, T. (2007). A scaling law for slow earthquakes. Nature, 447 (7140), 76.
Jolivet, R., Lasserre, C., Doin, M. P., Guillaso, S., Peltzer, G., Dailu, R., ... & Xu, X. (2012). Shallow creep on the Haiyuan fault (Gansu, China) revealed by SAR interferometry. J. Geophys. Res.: Solid Earth, 117(B6).
Jolivet, R., C. Lasserre, et al. (2013). Spatiotemporal evolution of aseismic slip along the haiyuan fault, china: Implications for fault frictional properties, Earth Planet. Sci. Lett., 377, 23–33.
Jolivet, R., T. Candela, C. Lasserre, F. Renard, Y. Klinger, M.-P. Doin (2015), The burst-like behavior of aseismic slip on a rough fault : the creeping segment of the Haiyuan fault, China, Bull. Seism. Soc. Am., v. 105, p. 480-488, First published on December 30, 2014, doi:10.1785/0120140237
Jolivet, R & Frank, W. B. (2020). The transient and intermittent nature of slow slip. AGU Advances, 1, e2019AV000126.
Lemrabet, L., M.-P. Doin, C. Lasserre, P. Durand and the FLATSIM team (2023), Referencing of Continental-Scale InSAR-Derived Velocity Fields: Case Study of the Eastern Tibetan Plateau, J. Geophys. Res.: Solid Earth, in revision.
Li, Y., Bürgmann, R., & Taira, T. (2023). Spatiotemporal variations of surface deformation, shallow creep rate, and slip partitioning between the San Andreas and southern Calaveras Fault. Journal of Geophysical Research: Solid Earth, 128, e2022JB02536
Ou, Q., Daout, S., Weiss, J. R., Shen, L., Lazecký, M., Wright, T. J., & Parsons, B. E. (2022). Large-scale interseismic strain mapping of the NE Tibetan Plateau from Sentinel-1 interferometry. Journal of Geophysical Research: Solid Earth, 127, e2022JB024176
Pagani, C., Bodin, T., Métois, M., & Lasserre, C. (2021). Bayesian estimation of surface strain rates from Global Navigation Satellite System Measurements: Application to the Southwestern United States. Journal of Geophysical Research: Solid Earth, 126, e2021JB021905
Rouet-Leduc, B., R. Jolivet, M. Dalaison, P. A. Johnson & C. Hulbert (2020), Autonomous extraction of millimeter-scale deformation in InSAR time series using deep learning, Nature Communications, Vol. 12, 6480
Thollard, F., Clesse, D., Doin, M.-P., Donadieu, J., Durand, P., Grandin, R., Lasserre, C., Laurent, C., Deschamps-Ostanciaux, E., Pathier, E., Pointal, E., Proy, C., Specht, B. (2021), FLATSIM: The ForM@Ter LArge-Scale Multi-Temporal Sentinel-1 InterferoMetry Service. Remote Sens., 13, 3734

Contexte de travail

Funding:
The PhD is fully funded by the ANR project «X-strain » (« Detecting transient strain along the Haiyuan fault, China », 2022-2026) gathering partners in Geosciences Montpellier (J. Chery is the PI of the project), LGL-TPE Lyon, LG-ENS Paris, IPGP, LAAS Toulouse, ESEO Angers, in collaboration with Chinese researchers from ITPCAS, Beijing.

Supervision and scientific team:
The PhD will be co-advised by Cécile Lasserre (LGL-TPE Lyon) and Romain Jolivet (LG-ENS Paris). Enrollment will be in the PHAST doctoral school of Université Lyon 1 but regular, possibly long visits at LG-ENS Paris are planned. The PhD student will be part of the "Surface and Lithosphere" group at LGLTPE. The PhD will also be integrated in the ANR X-strain project team and will work in close collaborations with other colleagues at ISTerre (M.P Doin), LGL-TPE (B. Gardonio, M. Métois, T. Bodin), LIRIS Lyon (C. Pothier) and ITES (B. Rousset, E. Neyrinck) for InSAR, seismological and strain data analysis.

Contraintes et risques

No constrain or risk identified.
Regular visits at LG-ENS Paris are planned.

Informations complémentaires

Required profile :
Interests in seismotectonics and geodetic time series processing and analysis are required. Skills in programming (python, UniX cluster environment), signal processing and/or data mining tools will be a plus. Communication and writing skills will be important to develop in order to present the work to the scientific community in the form of oral presentations, posters, and scientific