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The movement and deformation of the Earth’s crust and upper mantle provide critical insights into the evolution of earthquake processes and future earthquake potentials. Crustal deformation can be modeled by dislocation models that represent earthquake faults in the crust as defects in a continuum medium. In this study, we propose a physics-informed deep learning approach to model crustal deformation due to earthquakes. Neural networks can represent continuous displacement fields in arbitrary geometrical structures and mechanical properties of rocks by incorporating governing equations and boundary conditions into a loss function. The polar coordinate system is introduced to accurately model the displacement discontinuity on a fault as a boundary condition. We illustrate the validity and usefulness of this approach through example problems with strike-slip faults. This approach has a potential advantage over conventional approaches in that it could be straightforwardly extended to high dimensional, anelastic, nonlinear, and inverse problems. Modeling crustal deformation is critical for understanding of tectonic processes and earthquake potentials. Here, the authors propose a deep learning approach that can be extended in a straightforward manner to complex crustal structures and inverse problems.

Periodic ocean tides continually provide a cyclic load on Earth's surface, the response to which can be exploited to provide new insights into Earth's interior structure. We used geodetic observations of surface displacements induced by ocean tidal loads to constrain a depth-dependent model for the crust and uppermost mantle that provides independent estimates of density and elastic moduli below the western United States and nearby offshore regions. Our observations require strong gradients in both density and elastic shear moduli at the top and bottom of the asthenosphere but no discrete structural discontinuity at a depth of 220 kilometers. The model indicates that the asthenosphere has a low-density anomaly of ~50 kilograms per cubic meter; a temperature anomaly of ~300°C can simultaneously explain this density anomaly and inferred colocated minima in elastic moduli.

Analysis of the postseismic deformation of the moment magnitude 8.6 Indian Ocean earthquake in 2012 reveals that the asthenospheric layer must be thin and of low viscosity, constraining the structure of oceanic upper-mantle rheology. Mantle rheology after the Indian Ocean earthquake Yan Hu et al . use observations of postseismic deformation following the 2012 Indian Ocean earthquake to constrain the structure of oceanic mantle rheology. In the first three years after this event, most GPS stations in the region underwent horizontal northeastward displacement in a similar direction to the coseismic offsets. However, a few stations close to the rupture area, which had experienced up to four centimetres of coseismic subsidence, rose by nearly seven centimetres after the earthquake. The authors use a three-dimensional viscoelastic finite-element model of post-earthquake deformation to show that a relatively thin low-viscosity asthenospheric layer beneath the elastic oceanic lithosphere is required to fit the data. Also in this issue of Nature , Sylvain Barbot and colleagues report on transient deformation in the aftermath of this earthquake, as recorded by continuous geodetic stations in the region. The concept of a weak asthenospheric layer underlying Earth’s mobile tectonic plates is fundamental to our understanding of mantle convection and plate tectonics. However, little is known about the mechanical properties of the asthenosphere (the part of the upper mantle below the lithosphere) underlying the oceanic crust, which covers about 60 per cent of Earth’s surface. Great earthquakes cause large coseismic crustal deformation in areas hundreds of kilometres away from and below the rupture area. Subsequent relaxation of the earthquake-induced stresses in the viscoelastic upper mantle leads to prolonged postseismic crustal deformation that may last several decades and can be recorded with geodetic methods 1 , 2 , 3 . The observed postseismic deformation helps us to understand the rheological properties of the upper mantle, but so far such measurements have been limited to continental-plate boundary zones. Here we consider the postseismic deformation of the very large (moment magnitude 8.6) 2012 Indian Ocean earthquake 4 , 5 , 6 to provide by far the most direct constraint on the structure of oceanic mantle rheology. In the first three years after the Indian Ocean earthquake, 37 continuous Global Navigation Satellite Systems stations in the region underwent horizontal northeastward displacements of up to 17 centimetres in a direction similar to that of the coseismic offsets. However, a few stations close to the rupture area that had experienced subsidence of up to about 4 centimetres during the earthquake rose by nearly 7 centimetres after the earthquake. Our three-dimensional viscoelastic finite-element models of the post-earthquake deformation show that a thin (30–200 kilometres), low-viscosity (having a steady-state Maxwell viscosity of (0.5–10) × 10 18 pascal seconds) asthenospheric layer beneath the elastic oceanic lithosphere is required to produce the observed postseismic uplift.

Temporary slip speed increases with durations of 1–3 h were identified during short-term slow slip events in records of borehole and laser strainmeters in the Tokai region, Japan. They were found by searching for peaks of correlation coefficients between stacked strain data and ramp functions with rise times of 1 and 2 h. Although many of the strain steps were considered due to noise, some strain steps occurred with simultaneous activation of the deep tectonic tremors and shared source areas with the tremors. From 2016 to 2022, we observed five strain steps with simultaneous activation of tectonic tremors and coincidence of source locations with the tremors. Those strain steps occurred during short-term slow slip events and were temporary slip speed increases of the slow slip events. Those strain steps seemed to be related to successive occurrences with source migration of short-term slow slip events. The detrended strain steps corresponded to plate boundary slip events of moment magnitude around 5, which was consistent with the scaling law of slow earthquakes. Graphical Abstract

The Great Sumatran Fault system in Indonesia is a major right‐lateral trench‐parallel system that can be divided into several segments, most of which have ruptured within the last century. This study focuses on the northern portion of the fault system which contains a 200‐km‐long segment that has not experienced a major earthquake in at least 170 years. In 2005, we established the Aceh GPS Network for the Sumatran Fault System (AGNeSS) across this segment. AGNeSS observes large displacements which include significant postseismic deformation from recent large megathrust earthquakes as well as interseismic deformation due to continued elastic loading of both the megathrust and the strike slip system. We parameterize the displacements due to afterslip on the megathrust using a model based on a rate‐ and state‐dependent friction formalism. Using this approach, we are able to separate afterslip from other contributions. We remove predicted deformation due to afterslip from the observations, and use these corrected time series to infer the depth of shallow aseismic creep and deeper locked segments for the Great Sumatran Fault. In the northern portion of this fault segment, we infer aseismic creep down to 7.3 ± 4.8 km depth at a rate of 2.0 ± 0.6 cm/year. In the southwestern portion of the segment, we estimate a locking depth of 14.8 ± 3.4 km with a downdip slip rate of 1.6 ± 0.6 cm/year. This portion of the fault is capable of producing a magnitude 7.0 earthquake. Key Points Infer spatial variation in fault coupling Infer aseismic creep

Land subsidence significantly threatens vulnerable coastal environments. This study aims to explore how Semarang’s government, local communities, and researchers address land subsidence and its role in exacerbating flood risk, against the backdrop of ongoing efforts within flood risk governance. Employing an integrated mixed-methods approach, the research combined quantitative geospatial analysis (InSAR and land cover change detection) with qualitative socio-political and governance analysis (interviews, FGDs, field observations). Findings show high subsidence rates in Semarang. Line of sight displacement measurements revealed a continuous downward trend from late 2014 to mid-2023, with rates varying from −8.8 to −10.1 cm/year in Karangroto and Sembungharjo. Built-up areas concurrently expanded from 21,512 hectares in 2017 to 23,755 hectares in 2023, largely displacing cropland and tree cover. Groundwater extraction was identified as the dominant driver, alongside urbanization and geological factors. A critical disconnect emerged: community views focused on flooding, often overlooking subsidence’s fundamental role as an exacerbating factor. The study concluded that multi-level collaboration, improved risk communication, and sustainable land management are critical for enhancing urban coastal resilience against dual threats of subsidence and flooding. These insights offer guidance for similar rapidly developing coastal cities.

We analyze geodetic observation data associated with the 2011 Tohoku Earthquake to estimate coseismic and early postseismic fault slip distribution on the Pacific plate interface. The maximum slip and the moment magnitude of the main shock are about 60 m and M w 9.0, respectively. The location of the main slip patch is complementary to the source region of large earthquakes at least for those which have occurred during the last 100 years, and the maximum slip was corresponded to a release of stress accumulation for about 700 years Source regions of the 1936, 1938, and 1978 earthquakes are considered to have been re-ruptured in the 2011 main shock, where the slip amount was significantly smaller than the main patch.

Since the 2004 Sumatra–Andaman earthquake ( M w 9.2), the northwestern part of the Sumatran island has been a high seismicity region. To evaluate the seismic hazard along the Great Sumatran fault (GSF), we installed the Aceh GNSS network for the Sumatran fault system (AGNeSS) in March 2005. The AGNeSS observed co-seismic offsets due to the April 11, 2012 Indian Ocean earthquake ( M w 8.6), which is the largest intraplate earthquake recorded in history. The largest offset at the AGNeSS site was approximately 14.9 cm. Two M w 6.1 earthquakes occurred within AGNeSS in 2013, one on January 21 and the other on July 2. We estimated the fault parameters of the two events using a Markov chain Monte Carlo method. The estimated fault parameter of the first event was a right-lateral strike-slip where the strike was oriented in approximately the same direction as the surface trace of the GSF. The estimated peak value of the probability density function for the static stress drop was approximately 0.7 MPa. On the other hand, the co-seismic displacement fields of the second event from nearby GNSS sites clearly showed a left-lateral motion on a northeast–southwest trending fault plane and supported the contention that the July 2 event broke at the conjugate fault of the GSF. We also calculated the Coulomb failure function ΔCFF caused by the first event to evaluate its effect on the second event. The results showed that the July 2 event was likely brought 0.1 MPa closer to failure by the January 21 event.

Lombok Island was hit by a series of earthquakes in July and August 2018 with magnitude 6 class. This series of earthquakes resulted in fatalities and material losses that even reached Sumbawa Island to the east of Lombok Island. The earthquake was triggered by Flores back arc thrust resulting in ground deformation. Ground deformation can be identified by satellite-based remote sensing method. The Sentinel-1A and Sentinel-1B satellites are two satellites carrying C-band SAR sensors with a temporal resolution of 12 days each for the same orbit, and the difference in time between the two is 6 days. Therefore, ground deformation related to seismo-tectonic or volcanic activities can be identified by interfering two SAR images (interferometric synthetic aperture radar or InSAR) at least in 6 days. By utilizing Sentinel Application Platform (SNAP) a free open source software (FOSS) and combining with other InSAR software, an interferogram that represents line of sight displacement (LOS) between ground and satellite can be generated. Line of sight displacement can then be interpreted as ground deformation signals. It is shown that the series of Lombok earthquake cause an uplift up to 70cm and subsidence up to 25cm. This deformation affects areas around epicentre. A field survey was conducted to obtain information directly and it was seen that the ground deformation that was identified with the InSAR technique were consistent with the findings in the field. This shows the advantages of remote sensing in terms of ability to cover a wide area in a short time.

Jakarta as a home for more than 10 millions habitant facing complex environmental problems due to physical development that cause physical deformation. Physical deformation issues such as decreasing environmental carrying capacity, land cover changes and land subsidence have occurred. Recent studies shows that the long of shoreline changes in a span of 13 years from 2002 to 2015 around 14 km due to land reclamation in Jakarta bay. Previous studies also concluded that Jakarta suffer a sinking phenomena due to its rapid subsidence rate, approximately 260 mm year in northern part of Jakarta. During the 2007 to 2011, the land subsidence phenomena in Jakarta was observed by InSAR based on ALOS-PALSAR data and found that the subsided areas only occurred in certain areas, mainly in Pluit and Cengkareng regions, with a subsidence of approximately 70 cm for 4 years. Land subsidence is generally related to geological subsidence i.e. sediment consolidation due to its own weight and tectonic movements; or related to human activities such as withdrawal of ground water and geothermal fluid, oil and gas extraction from underground reservoirs, and collapse of underground mines. The amount of subsidence or uplift can be estimated from the number of concentric fringes that appear in the interferogram. This research utilizes Synthetic Aperture Radar (SAR) data observed from ALOS-2 (L-band) and Sentinel-1 (C-band) satellites. By interfering two single look complex (SLC) images from different observation epoch, it is found that the subsided area that has been identified before continues to subside. This occurs especially in Pluit region and has been revealed by interfering ALOS-2 data up to year 2016. The deformation in this area is approximately 12 cm from November 2015 to September 2016. The process of land reclamation also clearly identified by Sentinel-1 image by series data processing in Sentinels Application Platform (SNAP) software.