Geodetic Observations Research Articles

Linking 3D Long‐Term Slow‐Slip Cycle Models With Rupture Dynamics: The Nucleation of the 2014 Mw 7.3 Guerrero, Mexico Earthquake

AbstractSlow slip events (SSEs) have been observed in spatial and temporal proximity to megathrust earthquakes in various subduction zones, including the 2014 Mw 7.3 Guerrero, Mexico earthquake which was preceded by a Mw 7.6 SSE. However, the underlying physics connecting SSEs to earthquakes remains elusive. Here, we link 3D slow‐slip cycle models with dynamic rupture simulations across the geometrically complex flat‐slab Cocos plate boundary. Our physics‐based models reproduce key regional geodetic and teleseismic fault slip observations on timescales from decades to seconds. We find that accelerating SSE fronts transiently increase shear stress at the down‐dip end of the seismogenic zone, modulated by the complex geometry beneath the Guerrero segment. The shear stresses cast by the migrating fronts of the 2014 Mw 7.6 SSE are significantly larger than those during the three previous episodic SSEs that occurred along the same portion of the megathrust. We show that the SSE transient stresses are large enough to nucleate earthquake dynamic rupture and affect rupture dynamics. However, additional frictional asperities in the seismogenic part of the megathrust are required to explain the observed complexities in the coseismic energy release and static surface displacements of the Guerrero earthquake. We conclude that it is crucial to jointly analyze the long‐ and short‐term interactions and complexities of SSEs and megathrust earthquakes across several (a)seismic cycles accounting for megathrust geometry. Our study has important implications for identifying earthquake precursors and understanding the link between transient and sudden megathrust faulting processes.

Three-dimensional VP, VS, and VP/VS imaging based on AI microseismic detection reveals the mechanism of induced earthquakes in the Xiluodu Reservoir Area, China

The Xiluodu Reservoir (XLD), the third hydropower station developed downstream of the Jinsha River, is currently the fourth largest hydropower station worldwide. The reservoir has been impounded for 10 years, and numerous earthquakes have occurred, thus indicating an increased seismic risk. In existing studies, the deep tectonics and fine-scale structure in the reservoir area have not been sufficiently explained. Thus, the mechanism underlying reservoir-induced seismicity in this area remains unclear. In this study, we utilized a microseismic catalogue compiled based on the LOC-FLOW workflow (Li et al., 2023), alongside long-term observation data from a dense seismic array in the Jinsha River downstream, to obtain high-precision 3D VP, VS and VP/VS structures, as well as refined seismic relocations in the XLD Reservoir area. Additionally, we incorporated petrological, geomagnetic, gravity, crustal density, geodetic observation and numerical simulation data, which demonstrate that seismicity in the reservoir head area and near the Manao Fault is influenced by fluids. Moreover, the two M4 earthquakes that occurred east of the Lianfeng Fault are indicative of tectonic activity. Of these earthquakes, the Tianba earthquake cluster in the reservoir head area is located in a high-VP/VS zone, while a low-VS anomaly channel is observed here, which suggests that large amounts of fluid infiltrated along the fault, increasing the pore pressure and reducing the effective stress on the fault. The Wuji earthquake cluster in the head area is also located in a low-VP/VS zone, which indicates a low porosity and possibly undrained conditions. Thus, the earthquakes in this area are the result of coupled elastic stress-pore water pressure interactions.

Minimum-variance-based outlier detection method using forward-search model error in geodetic networks

Abstract. Geodetic observations are crucial for monitoring landslides, crustal movements, and volcanic activity. They are often integrated with data from interdisciplinary studies, including paleo-seismological, geological, and interferometric synthetic aperture radar observations, to analyze earthquake hazards. However, outliers in geodetic observations can significantly impact the accuracy of estimation results if not reliably identified. Therefore, assessing the outlier detection model's reliability is imperative to ensure accurate interpretations. Conventional and robust methods are based on the additive bias model, which may cause type-I and type-II errors. However, outliers can be regarded as additional unknown parameters in the Gauss–Markov model. It is based on modeling the outliers as unknown parameters, considering as many combinations as possible of outliers selected from the observation set. In addition, this method is expected to be more effective than conventional methods as it is based on the principle of minimal variance and eliminates the interdependence of decisions made in iterations. The primary purpose of this study is to seek an efficient outlier detection model in the geodetic networks. The efficiency of the proposed model was measured and compared with the robust and conventional methods by the mean success rate (MSR) indicator of different types and magnitudes of outliers. Thereby, this model enhances the MSR by almost 40 %–45 % compared to the Baarda and Danish (with the variance unknown case) method for multiple outliers. Besides, the proposed model is 20 %–30 % more successful than the others in the low-controllability observations of the leveling network.

Comparison of Machine Learning Models in Simulating Glacier Mass Balance: Insights from Maritime and Continental Glaciers in High Mountain Asia

Accurately simulating glacier mass balance (GMB) data is crucial for assessing the impacts of climate change on glacier dynamics. Since physical models often face challenges in comprehensively accounting for factors influencing glacial melt and uncertainties in inputs, machine learning (ML) offers a viable alternative due to its robust flexibility and nonlinear fitting capability. However, the effectiveness of ML in modeling GMB data across diverse glacier types within High Mountain Asia has not yet been thoroughly explored. This study addresses this research gap by evaluating ML models used for the simulation of annual glacier-wide GMB data, with a specific focus on comparing maritime glaciers in the Niyang River basin and continental glaciers in the Manas River basin. For this purpose, meteorological predictive factors derived from monthly ERA5-Land datasets, and topographical predictive factors obtained from the Randolph Glacier Inventory, along with target GMB data rooted in geodetic mass balance observations, were employed to drive four selective ML models: the random forest model, the gradient boosting decision tree (GBDT) model, the deep neural network model, and the ordinary least-square linear regression model. The results highlighted that ML models generally exhibit superior performance in the simulation of GMB data for continental glaciers compared to maritime ones. Moreover, among the four ML models, the GBDT model was found to consistently exhibit superior performance with coefficient of determination (R2) values of 0.72 and 0.67 and root mean squared error (RMSE) values of 0.21 m w.e. and 0.30 m w.e. for glaciers within Manas and Niyang river basins, respectively. Furthermore, this study reveals that topographical and climatic factors differentially influence GMB simulations in maritime and continental glaciers, providing key insights into glacier dynamics in response to climate change. In summary, ML, particularly the GBDT model, demonstrates significant potential in GMB simulation. Moreover, the application of ML can enhance the accuracy of GMB modeling, providing a promising approach to assess the impacts of climate change on glacier dynamics.

Representation and interpretation about underwater sound speed gradient field in the GNSS-A observation

SUMMARY The Global Navigation Satellite System—Acoustic ranging combination technique (GNSS-A) is a seafloor geodetic observation technique that achieves an accuracy of centimetres by combining high-rate GNSS data with acoustic ranging. The technique determines the seafloor position by acoustic ranging between the sea surface and multiple seafloor stations, using GNSS data from the sea surface station. Here, the gradient state of the underwater sound speed structure (SSS) is a significant source of error. The open-source software GARPOS can reduce the effect from underwater gradient structures by retrieving the underwater disturbance as a parameter projected onto the sea surface and seafloor. To evaluate the effects of underwater disturbances, a quantitative comparison of the model parameters is necessary. In this study, we developed a representation method to evaluate features of the ocean field. Here, the expression method was described in the order of a formulation and an interpretation in the case of a 2-D cross-section and extension to the case of an actual 3-D field. This method makes it possible to evaluate SSS states in the GNSS-A observations. As an example, we showed the correlation between the anomaly of the expressed ocean state and the anomaly of the seafloor station position, showing that this expression method is an effective index for correcting bias errors. Additionally, we used the data from sites located in the Kuroshio area, a strong current near Japan, to show that the ocean state can be quantitatively interpreted using this expression method.

Sensitivity of GNSS‐Derived Estimates of Terrestrial Water Storage to Assumed Earth Structure

AbstractGeodetic methods can monitor changes in terrestrial water storage (TWS) across large regions in near real‐time. Here, we investigate the effect of assumed Earth structure on TWS estimates derived from Global Navigation Satellite System (GNSS) displacement time series. Through a series of synthetic tests, we systematically explore how the spatial wavelength of water load affects the error of TWS estimates. Large loads (e.g., >1,000 km) are well recovered regardless of the assumed Earth model. For small loads (e.g., <10 km), however, errors can exceed 75% when an incorrect model for the Earth is chosen. As a case study, we consider the sensitivity of seasonal TWS estimates within mountainous watersheds of the western U.S., finding estimates that differ by over 13% for a collection of common global and regional structural models. Errors in the recovered water load generally scale with the total weight of the load; thus, long‐term changes in storage can produce significant uplift (subsidence), enhancing errors. We demonstrate that regions experiencing systematic and large‐scale variations in water storage, such as the Greenland ice sheet, exhibit significant differences in predicted displacement (over 20 mm) depending on the choice of Earth model. Since the discrepancies exceed GNSS observational precision, an appropriate Earth model must be adopted when inverting GNSS observations for mass changes in these regions. Furthermore, regions with large‐scale mass changes that can be quantified using independent data (e.g., altimetry, gravity) present opportunities to use geodetic observations to refine structural properties of seismologically derived models for the Earth's interior structure.

Geodetic signature of a weak Lithosphere-Asthenosphere Boundary in postseismic deformation of large subduction earthquakes

The rheology of the seismically imaged Lithosphere-Asthenosphere Boundary (LAB) is an important new question in plate tectonics. If the LAB is associated with ponding of partial melts as inferred from many seismic studies, it should have a low viscosity that minimizes resistance to plate motion and subduction. Here, we propose that recently observed postseismic enhanced landward motion (ELM) in coastal areas outside the rupture zone of large subduction earthquakes provides the first geodetic evidence for a low-viscosity LAB beneath subducting oceanic lithosphere. Using three-dimensional viscoelastic finite element models, we demonstrate that a low-viscosity LAB readily leads to postseismic ELM over broad coastal areas far beyond the rupture zone. If the LAB thickness is assumed to be 10 km, key spatiotemporal characteristics of the observed ELM can be well explained by an LAB viscosity of 5 × 1016 Pa s, orders of magnitude lower than typical asthenospheric viscosities. A thicker LAB such as 20 km with a higher viscosity may also explain the postseismic ELM but is incompatible with existing, albeit limited, near-field vertical deformation observations. The small thickness and the low viscosity of the model LAB are consistent with inferences from seismological observations and support the notion of ponding melts. Our preliminary weak-LAB models also predict diagnostic deformation features that can be tested by future onshore and offshore geodetic observations. Whether a weak LAB is ubiquitously present before and after plate subduction and how its presence and spatial heterogeneity impact postseismic and plate-scale deformation are important research targets for future investigations.

Lithospheric Rheology and Crustal Deformation Across the Northeastern Tibet and Their Implications for Plateau Growth

AbstractUnderstanding lithospheric rheology is crucial in investigating tectonic evolution of intra‐continental tectonic boundary. Here, we use geodetic observations to infer lithospheric rheology across the northeastern Tibet based on a 2D viscoelastic model. Our findings reveal a lower‐crust viscosity of <1022 Pa·s underneath its margins, lower than those estimated underneath its vicinities. By comparing deformation patterns and lithospheric rheology here with those observed in the eastern Tibet, we propose that lateral variations in lower‐crust viscosity control deformation patterns and topographic gradients along the Tibet margins. The presence of low viscosity lower‐crust can lead to the development of contrasting topographic gradients and shape the plateau's geomorphology and deformation characteristics during outward growth of the Tibet. We here emphasize the subtle variations in the lower‐crust rheology between deforming blocks and the corresponding mountain ranges, which play an important role in orogeny along the intracontinental convergence boundary.

Connecting Land and Sea Vertical Datums: A Data Evaluation for Developing Australia’s AUSHYDROID Model

Land and sea vertical datums have traditionally been separate reference levels, due to the different methodologies and observations used in their derivations. However, the need for a seamless connection of these datums has become important due to a wide range of applications in the coastal zone. This study evaluates existing methods, oceanographic and geodetic models and observations for the development of an operational model of coastal heights called AUSHYDROID. We use a complex study area in north west Australia to gain a new insight into how accurately the separation between the lowest astronomical tide (LAT) and a reference ellipsoid can be estimated from existing models, which could form the basis of a national AUSHYDROID model for Australia. Our results are the first attempt to use this combination of existing data in this location, suggesting that ellipsoidal heights of LAT can be estimated to an accuracy of ∼0.2 m at the coast, with the combination of DTU18MSS and FES2014b having the lowest RMS of 0.125 m. However, in some complex coastline areas such as bays and estuaries, the differences increase to >0.5 m so that additional tide gauge observations with GNSS levelling connections and improved models are needed in these regions.

The miniSLR: a low-budget, high-performance satellite laser ranging ground station

Satellite Laser Ranging (SLR) is an established technique providing very accurate position measurements of satellites in Earth orbit. However, despite decades of development, it remains a complex and expensive technology, which impedes its further growth to new applications and users. The miniSLR implements a complete SLR system within a small, transportable enclosure. Through this design, costs of ownership can be reduced significantly, and the process of establishing a new SLR site is greatly simplified. A number of novel technical solutions have been implemented to achieve a good laser ranging performance despite the small size and simplified design. Data from the initial six months of test operation have been used to generate a first estimation of the system performance. The data include measurements to many of the important SLR satellites, such as Lageos, Etalon and most of the geodetic and Earth observation missions in LEO. It is shown that the miniSLR achieves sub-centimetre accuracy, comparable with conventional SLR systems. The miniSLR is an engineering station in the International Laser Ranging Service and supplies data to the community. Continuous efforts are undertaken to further improve the system operation and stability.

РЕЗУЛЬТАТЫ МОНИТОРИНГА ДЕФОРМАЦИОННЫХ ПРОЦЕССОВ МЕТОДАМИ ВЫСОКОТОЧНОЙ ГЕОДЕЗИИ И РАДАРНОЙ ИНТЕРФЕРОМЕТРИИ НА ГЕОДИНАМИЧЕСКОМ ПОЛИГОНЕ ЗАПОЛЯРНОГО НЕФТЕГАЗОКОНДЕНСАТНОГО МЕСТОРОЖДЕНИЯ

To obtain information on the presence and magnitude of deformation processes during the development of the Polar oil and gas condensate field, an integrated method of surveying and geodetic works was applied, including: 4 high-precision geodetic satellite observations at all points of the field's observation network to determine global rock movements expressed by changes in the coordinates of points of the geodynamic polygon; 4 high-precision leveling of a local section of a geodynamic polygon to determine vertical movements of rocks in the area of a geo-dynamically active zone; 4 application of the radar interferometry method of stable reflectors to the oil and gas production region with a large number of man-made objects. In this paper, a comparative analysis of the anthropogenic impact of field development (based on accumulated maps of reservoir pressure selection and drop) on modern deformations of the Earth's surface (based on the results of satellite observations and radar inter-ferometry) is performed.

Most expedient mine surveying analysis and geodetic method for tracking the stability of the tailings dam position

This article examines the issues of mine surveying and geodetic observations of the stability of the position of the tailings dam of the Almalyk Mining and Metallurgical Combine (AMMC) in Uzbekistan. For these purposes, a geodetic network was created on the principle of geodetic serifs, including the course of polygonometry of the 1st category. To determine the stability of the position and condition of the dam of the combined tailing dump in order to improve the accuracy, observations were made using satellite technologies and classical methods. From the work performed, it was concluded that when determining the coordinates of points, it is convenient to use the method of geodetic serifs. It allows simultaneous measurements of both the main course and lateral points, which significantly reduces time for making field measurements. In addition, in the case of short sides of triangles, the method of linear serifs is most appropriate, since it allows you to obtain more accurate values of the angles of triangles in comparison with angular measurements, which in the end result significantly increases the accuracy of determining the coordinates of points.

Unraveling Earthquake Clusters Composing the 2014 Alto Tiberina Earthquake Swarm via Unsupervised Learning

AbstractEarthquake swarms represent a particular mode of seismicity, not directly related to the occurrence of large earthquakes (e.g., aftershocks) but rather driven by external forcing such as aseismic deformation or fluid migration in fault systems. Sometimes their occurrence overlaps with observable geodetic signals in space and time, indicating a direct link. However, the low resolution of geodetic observations tends to obscure the small scale spatial and temporal dynamics of swarms. In this work, we automatically extract clusters of seismicity related to the 2014 Alto Tiberina swarm sequence (Italy) using an unsupervised clustering approach that exploits space and time information of the seismicity. The quantitative characterization of each cluster indicates that the overall swarm is composed of spatially and temporally confined (sub) swarms each of which could potentially be driven by small‐scale aseismic deformation process. This observation aligns with similar findings during slow slip events in subduction zones.

Crustal response to water loads and expansion of triggered seismicity around the Xiluodu Reservoir, Southwest China

<p>The transition to low-carbon energy generation requires a diverse portfolio of energy sources. Large hydropower stations play a crucial role in providing eco-friendly energy but can lead to crustal deformation and seismic activity due to reservoir impoundment and discharge. The mechanism behind how impoundment-induced deformation influences reservoir-triggered seismicity remains unclear. We investigate this at the world��s 4<sup>th</sup> largest hydropower station in Xiluodu, China, using interdisciplinary analyses of relocated earthquakes, geodetic data, and numerical simulations. Geodetic observations confirm both a linear elastic response to hydrologic loading and the transition towards a relaxed and flexural response. Notably, approximately 81% of the earthquakes since impoundment occurred within ~15 km of the subsidence center. These events temporally relate to rapid hydrologic loading/unloading periods, with their spatiotemporal outward migration potentially caused by viscous relaxation of load stresses in the lower crust and upper mantle. The reservoir-induced flexural deformation and subsequent viscous relaxation may control the distribution and expansion of triggered seismicity. This research highlights the urgent need to enhance geohazard monitoring efforts around the subsidence center and emphasizes the vital importance of carefully considering this factor during the construction of large reservoirs to mitigate potential seismic risks.</p>

Organizational and technological features of geodetic observations of earth surface deformations

The article examines a complex of organizational, technological and economic measures to ensure observations of deformations of the earth's surface. The authors provide an overview of issues of improving the safety of buildings located in seismically active and landslide zones of the Russian Federation, and offer recommendations for improving monitoring methods. The need for careful consideration of the geodynamic factor during the construction and operation of not only especially critical unique objects, but also mass housing construction projects is substantiated. To study geodynamic processes occurring in the territories of populated areas or in the territories of large industrial enterprises and engineering structures, it is proposed to create specialized observation systems - geodynamic polygons. The authors propose an organizational and technological scheme for observations at the geodynamic site. Research methods for making organizational and technological decisions are discussed. Effective organization of work will allow us to study abnormal vertical and horizontal movements and prevent possible damage to infrastructure. The authors of the article also discuss and justify recommendations for performing and processing geodetic observations of deformations of the earth's surface.

An iterative and shrinking generalized ridge regression for ill-conditioned geodetic observation equations

An iterative and shrinking generalized ridge regression for ill-conditioned geodetic observation equations

A Bayesian Source Model for the 2022 Mw6.6 Luding Earthquake, Sichuan Province, China, Constrained by GPS and InSAR Observations

Until the Mw 6.6 Luding earthquake ruptured the Moxi section of the Xianshuihe fault (XSHF) on 5 September 2022, the region had not experienced an Mw >6 earthquake since instrumental records began. We used Global Positioning System (GPS) and Sentinel-1 interferometric synthetic aperture radar (InSAR) observations to image the coseismic deformation and constrain the location and geometry of the seismogenic fault using a Bayesian method We then present a distributed slip model of the 2022 Mw6.6 Luding earthquake, a left-lateral strike-slip earthquake that occurred on the Moxi section of the Xianshuihe fault in the southwest Sichuan basin, China. Two tracks (T26 and T135) of the InSAR data captured a part of the coseismic surface deformation with the line-of-sight displacements range from ∼−0.16 m to ~0.14 m in the ascending track and from ~−0.12 m to ~0.10 m in the descending track. The inverted best-fitting fault model shows a pure sinistral strike-slip motion on a west-dipping fault plane with a strike of 164.3°. We adopt a variational Bayesian approach and account for the uncertainties in the fault geometry to retrieve the distributed slip model. The inverted result shows that the maximum slip of ~1.82 m occurred at a depth of 5.3 km, with the major slip concentrated within depths ranging from 0.9–11 km. The InSAR-determined moment is 1.3 × 1019 Nm, with a shear modulus of 30 GPa, equivalent to Mw 6.7. The published coseismic slip models of the 2022 Luding earthquake show apparent differences despite the use of similar geodetic or seismic observations. These variations underscore the uncertainty associated with routinely performed source inversions and their interpretations for the underlying fault model.

Estimating geodynamic model parameters from geodetic observations using a particle method

SUMMARY Bayesian-based data assimilation methods integrate observational data into geophysical forward models to obtain the temporal evolution of an improved state vector, including its uncertainties. We explore the potential of a variant, a particle method, to estimate mechanical parameters of the overriding plate during the interseismic period. Here we assimilate vertical surface displacements into an elementary flexural model to estimate the elastic thickness of the overriding plate, and the locations and magnitudes of line loads acting on the overriding plate to produce flexure. Assimilation of synthetic observations sampled from a different forward model than is used in the particle method, reveal that synthetic seafloor data within 150 km from the trench are required to properly constrain parameters for long wavelength solutions of the upper plate (i.e. wavelength ∼500 km). Assimilation of synthetic observations sampled from the same flexural model used in the particle method shows remarkable convergence towards the true parameters with synthetic on-land data only for short to intermediate wavelength solutions (i.e. wavelengths between ∼100 and 300 km). In real-data assimilation experiments we assign representation errors due to discrepancies between our incorrect or incomplete physical model and the data. When assimilating continental data prior to the 2011 Mw Tohoku-Oki earthquake (1997–2000), an unrealistically low effective elastic plate thickness for Tohoku of ∼5–7 km is estimated. Our synthetic experiments suggest that improvements to the physical forward model, such as the inclusion of a slab, a megathrust interface and viscoelasticity of the mantle, including accurate seafloor data, and additional geodetic observations, may refine our estimates of the effective elastic plate thickness. Overall, we demonstrate the potential of using the particle method to constrain geodynamic parameters by providing constraints on parameters and corresponding uncertainty values. Using the particle method, we provide insights into the data network sensitivity and identify parameter trade-offs.

Developing Iran's empirical zenith wet delay model (IR-ZWD)

The presence of water vapor in the lower atmosphere can introduce errors in satellite-based geodetic observations. Accurate modeling of this part of atmospheric delay is particularly challenging due to the considerable variations of water vapor. Therefore, constructing a reasonable model to predict Zenith Wet Delay (ZWD) can improve the accuracy of geodetic observations and positioning techniques. In this study, we aim at constructing a regional ZWD model for Iran and nearby regions (called the IR-ZWD model) using base functions with local support. The mode is based on the five-year outputs of the Empirical Reanalysis Fifth generation (ERA5) data with the spatial resolution of about 0.25° from 2017 to 2021. The B-spline base functions are used to effectively represent local spatial changes in the spectral domain and to decrease the number of unknown parameters. A B-spline model with the order and surface resolution of about 3 and 5 (scalar values) is found to be efficient, which has an equivalent spatial resolution of ∼0.5°. Temporal variations are accounted for by applying a constant term, along with periodic components with annual, semi-annual, 3-, and 4-monthly periods. Our results demonstrate that the proposed model has a mean Root Mean Squared Error (RMSE) of about 0.035 m within Iran, which represents an improvement of approximately 12.5% compared to the commonly used global empirical models such as GPT3w, GTrop, and HGPT2. The correlation coefficient value of 0.55 is found between IR-ZWD and ERA5 data, which is about 10% higher than that of, e.g., GPT3w and GTrop. The IR-ZWD model is also evaluated against five radiosonde stations and ZWD from the Jason-3 satellite mission. In both cases, the results indicate that IR-ZWD can reduce the RMSE and MAE values of about 10%, and it improves the correlation coefficient value about 9%.

Physics‐Informed Neural Networks for Fault Slip Monitoring: Simulation, Frictional Parameter Estimation, and Prediction on Slow Slip Events in a Spring‐Slider System

AbstractThe episodic transient fault slips called slow slip events (SSEs) have been observed in many subduction zones. These slips often occur in regions adjacent to the seismogenic zone during the interseismic period, making monitoring SSEs significant for understanding large earthquakes. Various fault slip behaviors, including SSEs and earthquakes, can be explained by the spatial heterogeneity of frictional properties on the fault. Therefore, estimating frictional properties from geodetic observations and physics‐based models is crucial for fault slip monitoring. In this study, we propose a Physics‐Informed Neural Network (PINN)‐based new approach to simulate fault slip evolutions, estimate frictional parameters from observation data, and predict subsequent fault slips. PINNs, which integrate physical laws and observation data, represent the solution of physics‐based differential equations. As a first step, we validate the effectiveness of the PINN‐based approach using a simple single‐degree‐of‐freedom spring‐slider system to model SSEs. As a forward problem, we successfully reproduced the temporal evolution of SSEs using PINNs and obtained implications on how to choose the appropriate collocation points by analyzing the residuals of physics‐based differential equations. As an inverse problem, we estimated the frictional parameters from synthetic observation data and demonstrated the ability to obtain accurate values regardless of the choice of first‐guess values. Furthermore, we discussed the potential of the predictability of the subsequent fault slips using limited observation data, taking into account uncertainties. Our results indicate the significant potential of PINNs for fault slip monitoring.