Volcanic passive margins constitute more than half of the global length of passive margins,with seaward-dipping reflectors(SDRs)being a hallmark feature of their ocean-continent transition zones.During the development of volcanic passive margins,significant amounts of mantle-derived magmas participate in the continental rifting process,representing a critical phase in the evolution of the crust-mantle system,which is crucial for understanding the Earth's internal dynamics.However,the specific mechanisms governing the transition from continental to oceanic crust and the precise delineation of the continent-ocean boundary remain contentious issues within the scientific community.This study focuses on two pairs of selected conjugate volcanic passive margins:the Uruguay-Namibia margins in the South Atlantic and the Laxmi Basin margins off western India.By analyzing multi-channel seismic reflection profiles,magnetic anomalies,free-air gravity anomalies,Bouguer gravity anomalies,and vertical gravity gradients,we conducted a detailed analysis of the structure and gravity-magnetic characteristics of the ocean-continent transition zone.Our findings reveal that,although the crustal structures of the conjugate margins display asymmetric development along the spreading center,their gravity and magnetic anomaly patterns exhibit axial symmetry from the ocean-continent transition zone to the spreading center.Both seismic and gravity-magnetic anomaly data indicate that the crustal structure,density,material composition,and magma upwelling mechanisms of the outer SDRs differ from those of typical oceanic crust.We propose that following the maturation of the outer SDRs,there was a significant shift in the magma upwelling pattern,with the transition from continental to oceanic crust occurring within adjacent thickened crustal regions.
The traditional ground-penetrating radar (GPR) imaging methods face challenges such as artifact interference, obscured target signals due to background clutter, and difficulties in detecting weak-reflective targets. To address these issues, this paper proposes a probabilistic grid-based imaging (PGI) method for GPR. This approach discretizes the detection area into 2D grid units, acquires target feature points through phase-based angle estimation and two-way travel time analysis from GPR profile data, and maps them to corresponding grids. Subsequently, by utilizing Bayesian theory to update network weights, we construct a probability distribution model that characterizes underground structures, thereby obtaining PGI imaging results. Both simulation experiments and real road tests demonstrate that compared with traditional methods, the proposed PGI method can effectively suppress artifacts, distinguish subsurface targets, enhance abilityanti-interference ability, achieve higher imaging resolution and facilitate radar profile interpretation later.
This paper proposes a method to recover time-varying gravity signals by using relative orbit determination technology between satellites in giant constellations. This study focuses on two relative orbit determination observation modes and conducts a closed-loop simulation experiment with three constellation configurations: A (2 orbital planes, 400 satellites), B (20 orbital planes, 400 satellites) and C (20 orbital planes, 4000 satellites), for recovering the time-varying gravity signal for the HIS (Hydrology, Ice, Solid Earth). The performance was analyzed for seismic and land water monitoring, and compared with the results from the GRACE/Bender observation modes. The closed-loop simulation accounts for error sources like observation noise, tidal model errors and de-aliasing model errors, with relative orbit determination accuracy for giant constellations set to 1 mm. The recovery accuracy of HIS signals across four 7-day periods (before and after the 2004 Sumatra earthquake) was compared for different configurations. The results show the following: (i) Relative orbit determination technique significantly improves the recovery accuracy of middle-to-high-degree (high-frequency) time-varying gravity signals compared to absolute orbit determination. The C constellation demonstrates the largest improvement, with accuracy enhancements of up to 5 similar to 7 times. (ii) The accuracy of the recovered time-varying gravity signal using relative orbit determination in the C constellation is superior to that of GRACE in the degree range of 10 to 50, and about 2 times better than GRACE at degree 20. It also compares favorably with Bender at low degrees. (iii) Spatial domain analysis shows that relative orbit determination in constellation C effectively recovers HIS signals up to degree 30. It can also monitor time-varying gravity signals caused by large earthquakes (such as the Sumatra earthquake), and monitor hydrological and glacial signals in multiple regions, with precision superior to GRACE but slightly inferior to Bender. The research demonstrates that a giant satellite constellation has significant potential for monitoring changes in Earth's gravity field using relative orbit determination, and can be a valuable technical approach for future geoscientific applications in giant satellite constellation missions.
To investigate the accumulation characteristics of gas hydrates in the Shenhu Area of the South China Sea from a multi-property perspective,we performed a joint interpretation of marine Controlled-Source Electromagnetic (CSEM) and multi-channel seismic data. The four stratigraphic interfaces identified from the 2D constrained inversion resistivity profiles of two marine CSEM lines correlate well with seismic interfaces T1-T4. A deeply-rooted high-resistivity anomaly zone, extending upward over 3 km in width, couples with chaotic seismic reflections. This correlation confirms the development of mud diapirs and indicates a high thermal maturity of deep source rocks, thereby establishing a foundation for thermogenic gas supply. The CSEM resistivity profiles demonstrate significant advantages in delineating gas migration pathways and reservoir boundaries. They reveal that fault systems control the vertical transport of thermogenic gas,directly influencing the spatial distribution of gas hydrate and free gas. This underscores the effectiveness of integrated seismic-electromagnetic interpretation in analyzing the reservoir transport system. Furthermore,the inverted resistivity values are consistent with drilling results: intervals within the gas hydrate stability zone exhibit high-resistivity anomalies (approximately 5 similar to 10 Omega m),whereas sections without hydrate show no such anomalies. The saturation distribution profile, obtained through joint seismic-CSEM inversion, clearly delineates the saturation characteristics of gas hydrate and free gas. The average saturations at wells W02 and W07 are 0.35 and 0.34,respectively,which deviate by less than 10% from the mean log-derived saturation values (0.32 and 0.33). The integration of marine CSEM and multi-channel seismic data significantly enhances the understanding of gas migration and reservoir systems, thereby contributing to reduced drilling risks.
The establishment and maintenance of the high-precision International Celestial Reference Frame (ICRF) and International Terrestrial Reference Frame (ITRF), as well as the accurate transformation between them, rely on a precisely defined celestial reference pole (reference axis). The celestial intermediate pole (CIP) is currently adopted by the IERS 2010 conventions as the celestial reference pole. In the Geocentric Celestial Reference System (GCRS), the third axis-denoted as C3-is derived through frame bias, precession, and nutation models. In the International Terrestrial Reference System (ITRS), the third axis-denoted as T3-is determined via polar motion calculations. Theoretically, C3 and T3 represent the same vector, collectively referred to as the celestial reference axis. However, due to modeling errors in precession, nutation and polar motion, C3 and T3 do not exactly coincide. Based on the transformation model between GCRS and ITRS provided by IERS 2010, this study proposes a new kinematic equation of Earth ' s rotation. This equation incorporates the polar motion of Earth ' s rotation axis, as well as the polar motion and nutation of the celestial reference axis. Therefore, the new formulation enables the definition of a more accurate celestial reference pole in the future. For instance, areasonable definition of the free pole motion of the celestial reference axis makes its free nutation zero. Additionally, the Earth rotation kinematic equation is used to derive the polar motion corresponding to the IAU2000AR06 nutation model. The nutation-induced effect on polar motion is approximately 3 mas-around 100 times larger than the libration effect-which has not yet been considered in existing polar motion models.
Accurate crustal velocity modeling from Ocean Bottom Seismometer (OBS) data requires precise travel-time measurements, which may be affected by spatial offsets between seismic sources and OBS profiles. In this study, we quantitatively assess the influence of seismic source offsets on first-arrival travel times and crustal structure modeling accuracy, with application and validation using field data from the 2021 Joint Arctic Scientific Middle-ocean ridge Insight Expedition (JASMInE) conducted along the Gakkel Ridge in the Arctic Ocean. The results show that for the typical crustal structure of the Gakkel Ridge, when the seismic source offset is less than 4 km and the source-receiver offset exceeds 6 km, the induced travel-time error (Delta t) remains below 120 ms-within acceptable limits for reliable crustal forward and inverse modeling. Statistical analysis of the JASMInE dataset indicates an average seismic source offset of 2.5 +/- 1.5 km. The impact of this offset is primarily confined to source-receiver offset <6 km, where arrivals are dominated by direct water-layer and are generally excluded from crustal modeling. In magmatic centers where the crust thickens to 7.5 km, source-receiver offsets >10 km is recommended to minimize the travel-time errors. Travel-time errors due to seafloor variations are <50 ms (equivalent to similar to 0.175 km Moho depth variation), whereas combined effects of seafloor and lateral crustal variations near magmatic centers can reach 140 ms, corresponding to <0.5 km Moho depth uncertainties. Overall, the uncertainties remain within a reasonable range. These results validate the robustness of the JASMInE-derived 2D crustal velocity model and offer quantitative guidance for seismic source deployment and data interpretation in polar challenging environment.
Data-domain least-squares reverse time migration is an imaging method based on optimization theory that performs iterative optimization. In recent years, many researchers have continuously optimized the least-squares reverse time migration method, with the hybrid conjugate gradient method being the mainstream optimization algorithm for solving least-squares reverse time migration. However, the least-squares reverse time migration based on this method still suffers from issues such as slow convergence speed, leading to poor stability throughout the computational process. To address the above problems, this paper proposes a method that uses the Gauss-Newton direction as a guide and employs a weighted combination of dual conjugate parameters to improve the convergence stability of least-squares reverse time migration. The improved method dynamically weights and combines two gradient parameters, leveraging the fast convergence of the quasi-Newton algorithm and the stable convergence of the hybrid conjugate gradient method. Through testing on models and real data, compared with conventional methods, the proposed algorithm achieves better imaging results under the same number of iterations, while also demonstrating good stability and high computational efficiency.
In recent years, machine learning methods have made significant advances in laboratory earthquake prediction, opening up new directions for research into natural earthquake forecasting. However, most current studies primarily employ single shallow or deep learning models to fit the complex nonlinear relationship between acoustic emission data and fault instability states. This approach has certain limitations in fully capturing data complexity and enhancing model generalization. To address these challenges, this paper systematically compares the performance of Multi-Layer Perceptron (MLP) and Multi-Layer Perceptron with Bootstrap Aggregation (MLP-Bagging) models in the task of inferring the time to failure (TTF) of laboratory faults. The training and testing datasets are evaluated using multiple performance metrics, including mean absolute error (MAE), root mean square error (RMSE), mean squared error (MSE) and coefficient of determination (R-2), enabling a comprehensive analysis of the fitting and generalization capabilities of both models. The results show that the MLP-Bagging model consistently outperforms the single MLP model across all statistical metrics, exhibiting lower prediction errors and higher R(2 )values on both the training and test sets. This finding is further validated in ensemble learning frameworks using LSTM + CNN as base learners. The Bagging ensemble strategy increases data diversity through bootstrap sampling and effectively reduces inference variance via model averaging, thereby significantly improving model stability and generalization. Although the inference accuracy of the models still requires improvement in regions near fault instability, ensemble learning methods provide a more robust and reliable approach for inferring fault instability states in laboratory settings. These results offer important reference value for related research areas, such as earthquake prediction.
The fluctuation characteristics of the geomagnetic field are crucial for understanding the internal geophysical processes and monitoring changes and predicting future trends in the geomagnetic field. Given the complexity of geomagnetic field fluctuations, this study analyzed the fluctuation characteristics of the hourly mean time series from the geomagnetic D, H and Z components recorded by 68 fixed stations across Chinese mainland in 2023 using the multifractal detrended fluctuation analysis (MF-DFA). The results revealed that geomagnetic field fluctuations over Chinese mainland exhibited significant multifractal characteristics. The fluctuation function displayed three scale intervals, demonstrating multiscale properties and the invariance characteristics of scale interval segmentation. The spatial variations of the generalized Hurst index at small and medium time scales further validated the multiscale nature of geomagnetic field time series. The differences in long-term memory properties among different geomagnetic components at medium time scales may be attributed to their differential responses to various geomagnetic activities. The spatial similarity between the multiple fractal spectrum width and the generalized Hurst index at medium time scale suggested that persistence enhanced the multiscale inhomogeneity of temporal amplitude fluctuations. The fluctuation amplitude in the D and Z components was pronounced, while the fluctuations in the H component remained relatively uniform. Geomagnetic field fluctuations exhibited distinct spatial heterogeneity. The D component exhibited a longitudinal effect, while the H and Z components displayed pronounced latitudinal effects. This indicated that the dipole geomagnetic field exerted a dominant control over regional geomagnetic field fluctuations.
The 2015 M(W)7.8 Nepal earthquake significantly altered the seismic activity in the Himalayan region, highlighting the crucial role of coseismic and postseismic stress adjustments in earthquake triggering. Observations show that seismic activity near the rupture zone increased dramatically between 2015 (after the event) and 2017, while the 2025 M(W)7.1 Dingri earthquake region, located farther away from the 2015 rupture area, exhibited continuously enhanced seismicity over the subsequent 10 years compared to the pre-earthquake period, suggesting that postseismic stress adjustments may play an important role in triggering earthquakes. This study employs a regional three-dimensional (3D) viscoelastic finite element model constrained by long-term GNSS observations to systematically analyze the spatiotemporal evolution of stress fields induced by coseismic rupture, postseismic afterslip and viscoelastic relaxation from lower crust and upper mantle. The results indicate that the coseismic event induced substantial Coulomb stress perturbations of up to 15 MPa on the Main Himalayan Thrust (MHT), while postseismic processes (e.g., afterslip and viscoelastic relaxation) contributed to long-term stress adjustments, with a maximum cumulative Coulomb stress reduction of 3.7 MPa over 10 years within the postseismic afterslip zone on the MHT. Furthermore, the model results reveal the impact of postseismic stress adjustments on the seismic hazard of active crustal faults in the Himalayan region, showing that major faults near the up-dip and down-dip portions of the rupture zone experienced varying degrees of stress loading, indicating potential possibility of seismic hazards. For example, this Nepal earthquake and its M(W)7.3 aftershock contributed similar to 18 kPa of coseismic Coulomb stress accumulation in the 2025 M(W)7.1 Dingri earthquake region, followed by gradual postseismic stress increases, indicating its triggering effects on subsequent seismicity in adjacent regions. This study gains insights into the tectonic stress evolution of the Himalayan region and helps seismic hazard assessments, emphasizing the importance of postseismic stress evolution in the earthquake cycle.
Finite source geometric, kinematic, and dynamic parameters of large earthquakes (M > 6) are difficult to retrieve in real-time, yet they are essential for understanding complex rupture processes and accurately assessing disaster risk. The Finite-Fault Rupture Detector (FinDer) algorithm rapidly estimates key line source parameters-centroid, length, and strike-from the spatial distribution of near-source high-frequencyseismic records. Using the 12 May 2008 Wenchuan MS 8.0 earthquake as a case study, we reevaluate FinDer ' s real-time performance and, on the basis of its output, propose a method for simultaneously deriving effective rupture direction and rupture velocity. We further test the usefulness of these parameters for Earthquake Early Warning (EEW). The results show that FinDer continuously updates the line source parameters during rupture and converges to a stable solution approximately 100 s after origin time: rupture length 290 km, magnitude MFD 8.0, strike 50 degrees, epicenter 103.25 degrees E/31.09 degrees N, centroid 104.51 degrees E/32.08 degrees N, predominant rupture direction 49 degrees, and apparent rupture velocity 2.8 km center dot s(-1). This velocity represents the effective near-surface energy-propagation speed and explains the similar to 20 s pseudo-supershear phase observed in the early rupture. The time history of rupture direction clearly reveals a dominant southeastward propagation between 20 s and 30 s, followed by northeastward propagation after 30 s. EEW scenario analyses indicate that accounting for rupture directivity improves Peak Ground Acceleration (PGA) predictions at some stations and yields, on average, an additional similar to 4 s of warning time for stations located in high-intensity areas.
The Gakkel Ridge in the Arctic Ocean, characterized by its ultraslow spreading rate, remoteness from subduction zones and mantle plumes, and lack of transform faults, represents a unique natural laboratory for examining seafloor spreading processes. Yet, seismic investigations in this region have been severely constrained by perennial, dense ice floes. During the 12th and 14th Chinese National Arctic Research Expeditions, active-source seismic surveys were conducted across the 75 degrees E-100 degrees E segment of the Gakkel Ridge. A total of 43 and 19 Ocean Bottom Seismometers (OBSs) were deployed, respectively, employing large-volume airgun arrays as the seismic source. Exceptional OBS recovery rates of 98% and 100% were achieved, producing the highest-quality active-source seismic dataset obtained to date in the densely ice-covered environment. This study highlights the deployment of self-developed equipment and the application of innovative operational methodologies specifically tailored to ice-covered conditions. It further synthesizes critical experience gained in conducting seafloor seismic surveys under challenging Arctic settings and presents unprecedented data collected with maximum source energy. The results offer new constraints on the deep crustal structure of the Gakkel Ridge and provide crucial evidence to advance understanding of lithospheric accretion dynamics in ultraslow-spreading ridge systems.
The Arctic Ocean has become a new focus in global climate research and natural resource exploration, with acoustic detection serving as a key technique for acquiring sub-ice seafloor information. The short-period seismic ambient noise carries abundant sound-source information. Analyzing its characteristics not only aids in understanding the seafloor acoustic environment but also provides valuable insights for artificialseismic surveys. This study, utilizes seismic records collected by Chinese Ocean Bottom Seismometers (OBSs) during the 2021 Joint Arctic Scientific Middle-ocean ridge Insight Expedition at the 85 degrees E volcanic area of the Gakkel Ridge, first analyzes the characteristics and controlling factors of short-period seismic ambient noise (>0.5 Hz) in this region. Spectral analysis reveals that seismic records from the Gakkel Ridge exhibit higher noise levels than typical terrestrial noise models. Our results indicate that the seafloor topographic slope exerts a decisive effect on OBS records, and different OBS models lead to variations in recorded noise energy. Furthermore, frequent microearthquakes at the Gakkel Ridge considerably elevate local seismic ambient noise levels, while the thick sediment layers along the ridge axis likely contribute to the amplification of ambient noise energy.
Compared to traditional empirical models, machine learning-based ground motion models offer superior accuracy and reliability. However, the "black-box" nature of machine learning techniques limits the interpretability of these models, underscoring the need for interpretable machine learning-based approaches. In this study, we developed a vertical ground motion model for peak ground acceleration (PGA), peak ground velocity (PGV), and 5%-damped pseudo-spectral acceleration (PSA) (ranging from 0.01 s to 10 s) using the interpretable Neural Additive Models (NAMs) algorithm. The model was trained on 14,995 vertical ground motion records from 257 seismic events in the NGA-West2 database. We conducted a comprehensive evaluation of the model, including performance analysis, physical characterization, residual analysis, and interpretability analysis. The results demonstrate that the proposed model strikes an effective balance between accuracy and reliability while maintaining the physical characteristics of traditional models. Furthermore, the model offers excellent interpretability: the influence of input features on the model varies, with magnitude and rupture distance being the most significant contributors. Specifically, the impact of magnitude increases with its value, while the effect of rupture distance diminishes as it increases. In contrast, the depth to the top of the rupture and time-averaged shear-wave velocity in the top 30 meters of soil have relatively minor effects, which slightly decrease as their values rise. Moreover, the model enables interpretable analysis of the PSA spectrum for various ground motion input parameters, allowing for the identification of their respective impacts on the spectrum.
Borehole acoustic reflection imaging technology has been widely applied in hydrocarbon exploration.A detailed understanding of the radiation characteristics of borehole acoustic sources is crucial for imaging performance analysis and method optimization,particularly in formations with high porosity and permeability.This study,based on Biot-Rosenbaum theory,derives analytical expressions for the radiation directivity and wavefield energy flux of multipole sources in permeable porous media using the steepest descent method and the complex Poynting vector.A comprehensive parametric analysis is conducted to assess how poroelastic properties and source frequency influence the radiation behavior of different wave modes.Results reveal that a slow P-wave component emerges in permeable porous media and that increasing porosity and permeability substantially attenuate the radiation efficiency of multipole sources.Dipole radiation efficiency shifts toward lower frequencies,accompanied by broadened spectral responses.The SV-wave efficiency transitions from a dual-peak to a single low-frequency pattern.Although the SH-wave remains the dominant mode,its imaging capability degrades markedly under high-porosity and high-permeability conditions.A field reflection imaging case validates the theoretical predictions.These findings offer theoretical support for evaluating and interpreting the performance of acoustic imaging in permeable porous reservoirs.
Abnormal pore pressure is a primary cause of drilling-related problems, and accurate pre-drilling prediction of formation pore pressure has become a critical technical component in deepwater oil and gas exploration and development. Prediction accuracy directly affects drilling safety and operational efficiency. Existing methods based on a single parameter (e.g., P-wave velocity) are insufficient to fully characterize the coupled effects among multiple geological parameters, resulting in limited predictive performance. To address this issue, this study proposes a multi-parameter collaborative pore pressure prediction model based on smooth threshold regression. Multiple parameters associated with formation pore pressure are incorporated into the model. First, an optimal feature set is identified using a hybrid feature selection strategy that combines the Lasso algorithm and bidirectional stepwise regression. Subsequently, pore pressure is predicted using the smooth threshold regression model. To remedy the absence of shear-wave data in logging records, a shear-wave prediction method based on an improved consolidation index is introduced. A case study in a hydrocarbon-generating overpressure zone in the Bohai Sea demonstrates that the proposed model achieves a mean absolute error of approximately 1.61 and a root mean square error of approximately 2.02 in the test well, with an average cross-validated coefficient of determination (R-2) of 0.9454. The model accurately identifies abnormally overpressured intervals and quantitatively estimates pore pressure, providing reliable technical support for drilling risk mitigation and reservoir evaluation.
The acquisition of high-precision GNSS vertical velocity fields constitutes a critical foundation for investigating tectonic processes. Refined modeling of non-tectonic deformations within GNSS time series is key to achieving high-precision tectonic deformation estimates. This paper utilizes GNSS observation data from 46 continuous GNSS stations and 176 campaign GNSS stations in the northeastern Tibetan Plateau margin from 2010 to 2022. Based on the differential response of soil and bedrock stations to environmental loads, non-tectonic deformation correction models are constructed for each type of station. Environmental loading datasets provided by GFZ and NASA are combined to evaluate the correction performance of different loading correction schemes on GNSS vertical time series, leading to the construction of an optimized non-tectonic deformation correction model. The results show that, after non-tectonic deformation correction, the root mean square (RMS) values of GNSS time series for 95% of the continuous stations and 83% of the campaign stations, indicating that this method effectively reduces the dispersion of the time series. The corrected time series were fitted with functions to extract a high-spatial-resolution vertical velocity field for the northeastern Tibetan Plateau margin, the results reveal the primary tectonic units and their internal vertical deformation characteristics. Marked spatial variation in vertical deformation is observed across the northeastern Tibetan Plateau margin, with the Liupanshan Fault Zone acting as a distinct boundary. The region to the west of the fault zone shows an overall slow subsidence, while the area to the east exhibits general uplift, with an average uplift rate of 1.2 mm & centerdot;a(-1). Notably, the Liupanshan Fault Zone shows significant local uplift, with a rate of up to 5 mm & centerdot;a(-1). The average subsidence rates in the Alxa block and the Qilian Mountains orogenic belt are -0.5 mm & centerdot;a(-1) and -1.2 mm & centerdot;a(-1), respectively. The Ordos block exhibits an average uplift rate of 1.0 mm & centerdot;a(-1). The Yinchuan Rift Basin shows the most significant subsidence, with an average rate of -1.8 mm & centerdot;a(-1).
Frequency-domain finite difference forward modeling is crucial for seismic inversion and imaging. However, the large memory requirements and extensive computations have long been major challenges in frequency-domain forward modeling. To address these difficulties, this paper proposes two improvements to the difference operator. First, the general optimization method of finite difference decomposition is employed to enhance the accuracy of the difference operator. Second, a stretched grid is introduced to reduce the computational burden of LU factorization of the impedance matrix by confining the sub-diagonals of the impedance matrix to both sides of the main diagonal. Based on these improvements, a Differential-Distance (DD) 21-point difference scheme tailored for rectangular grid sampling is developed. Dispersion analysis demonstrates that the DD 21-point difference scheme achieves higher accuracy compared to other methods, especially for large grid spacing ratio sampling. When the grid spacing ratio exceeds 1.5, the DD scheme requires only 2.13 grid points per wavelength to maintain the phase velocity error within 1%. Finally, through model testing and comparison with the Average-Derivative Method (ADM) and other comparable methods, the feasibility and efficiency of the DD 21-point difference scheme are thoroughly verified.
Kinematic reconstruction of detachment faults is critical for understanding lithospheric extension mechanisms, yet the initial dip angles of these faults remain controversial. The classic Rolling-Hinge Model suggests that detachment faults have a steep initial dip angle (>45 degrees), but the dip angle gradually decreases during fault slip due to flexural rotation. While this model aligns with microseismic and paleomagnetic observations from oceanic core complexes, it conflicts with low-temperature thermochronological data (e.g., fission-track) from continental metamorphic core complexes. Such discrepancies may arise because active surface processes, including rapid erosion and topographic evolution, are considerably more pronounced in continental settings and can significantly alter the reconstruction of exhumation pathways. This study employs a 2D geodynamic numerical model (ASPECT) coupled with a surface process model (FastScape) to simulate MCCs formation and to quantitatively compare the cooling histories of detachment faults footwall under varying surface process intensities. The modelling results indicate that a relatively high surface erosion rate (e.g., bedrock erodibility coefficient ) leads to smaller differences in temperature-pressure information recorded by Kf >= 10(-4) m(0.2) & centerdot; a(-1) samples at varying horizontal distances from the detachment fault termination point. Consequently, an increased erosion rate causes the fault dip angle inferred from low-temperature thermochronological data of surface samples to be underestimated. Our models confirm that even if detachment faults undergo progressive rotation as predicted by the Rolling-Hinge Model, intense surface processes can obscure the thermochronological signatures of this rotation, resulting in reduced reliability of dip angles inferred from surface low-temperature thermochronological data. These findings reveal the mechanism by which surface processes interfere with reconstructions of rapid exhumation histories of MCCs across diverse extensional environments, provide new dynamic constraints for precise inversion of detachment fault kinematics, and suggest that the application of the Rolling-Hinge Model in continental settings requires modifications that account for the effects of surface processes.
The California Undercurrent Eddies (Cuddies) can carry heat, salt, and sediments to the interior of the eastern Pacific Ocean, which is an important mechanism for the California Current System to transport material and energy offshore. A subsurface submesoscale anticyclonic eddy was observed based on the multi-channel seismic data from cruise EW9415 in the Pacific Ocean off the southern coast of California, USA, from October 16 to 19, 1994. The overall reflection structure of the eddy is about 20 similar to 25 km in width, 240 similar to 300 m in thickness, and 240 similar to 540 m in depth. There is a weak reflection core area in the reflection structure, with a width of about 8 similar to 12 km and a depth of about 400 similar to 430 m. We interpreted it as a subsurface submesoscale anticyclonic eddy combined with a reanalysis of hydrological data. The reflection events on both sides of the eddy core are inclined in a opposite direction. The eddy core is slightly upturned on the nearshore side, where the reflection events are strong because of the limitation of the adjacent steep terrain. On the offshore side, the eddy core is nearly horizontal, the reflection event is weak, and the range of the high amplitude reflection area is significantly smaller than that of the nearshore side. The vertical asymmetry of the reflection structure of the eddy core indicates that the irregular topography and frictional torque affect the formation and development of the eddy jointly. The reflection seismic image of the cuddy is given for the first time by the seismic oceanography method in this work. The same eddy was captured on the repetitive observation section at a 20-hour interval. During the observation period, the eddy has a horizontal displacement along the offshore direction of the survey line, and the apparent translational speed is 0.042 m center dot s(-1). With further evolution, the eddy core changed from convex lenticular to nearly oval, the inclination of the reflection events in the strong reflection area becomes smaller, and the thickness increases. Dislocations of small events on the nearshore side were merged, with continuity enhanced. Some events on the offshore side are weakened or even disappeared. The morphological changes of the eddy could be caused by a certain degree of differences in the cross sections at different angles, and the further relaxation of its own morphology.
