Integrated Geophysical and Geochemical Detection of the Active Moxi Fault at the Southeastern Margin of the Qinghai‒Tibet Plateau

Integrated Geophysical and Geochemical Detection of the Active Moxi Fault at the Southeastern Margin of the Qinghai‒Tibet Plateau | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Integrated Geophysical and Geochemical Detection of the Active Moxi Fault at the Southeastern Margin of the Qinghai‒Tibet Plateau Chao Tan, Ye Kuang, Xiujun Dong, Ruiqing Xiao, Kejia Wei This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9258880/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 5 You are reading this latest preprint version Abstract Active faults in mountain-gorge regions with thick overburden, such as the southeastern Tibetan Plateau, pose severe seismic risks to populated areas and critical infrastructure, yet their detection remains technically challenging due to complex topography and limited subsurface imaging capabilities. The 2022 Ms 6.8 earthquake along the Moxi Fault—the southeastern segment of the Xianshuihe Fault Zone—highlights the urgent need for precise fault characterization to inform post-earthquake reconstruction and seismic hazard assessment. Existing studies often rely on single geophysical or geological methods, which fail to fully resolve deep-shallow structural coupling, geochemical evidence of fluid activity, and quantitative kinematic parameters of active faults in these settings, leaving critical gaps in understanding fault behavior and hazard potential. This study aimed to address these gaps by developing an integrated detection framework combining geological-geomorphological survey, multi-method geophysics, and soil gas geochemistry to finely characterize the geometry, kinematics, and late Quaternary activity of the Moxi Fault. We employed high-resolution UAV remote sensing and field mapping to identify fault geomorphology, complemented by shallow seismic reflection, high-density resistivity, microtremor survey, and ground-penetrating radar for deep-shallow structural imaging, alongside high-density soil CO₂ and radon measurements to trace fault-related fluid pathways. Our results reveal that the Moxi Fault is a steeply west-dipping (75°–80°) left-lateral strike-slip fault with a 50–60 m wide damage zone, exhibiting a measured left-lateral displacement of 39.5 ± 0.5 m and a vertical throw of ~ 3 m. Radiocarbon dating (6379 ± 120 to 7856 ± 40 year BP) confirms late Holocene activity, with a slip rate of 5.3 ± 0.2 mm/yr, consistent with the regional Xianshuihe Fault Zone slip rate (4–6 mm/yr). The integrated geophysical and geochemical approach effectively overcomes topographic interference, with soil CO₂ and radon anomalies spatially correlating with the fault zone, verifying its role as a deep fluid conduit. These findings demonstrate that the integrated framework successfully resolves the structural and kinematic details of the Moxi Fault, achieving the study’s goal of precise active fault characterization in mountain-gorge regions with thick overburden. This work provides critical data for post-earthquake reconstruction and seismic hazard assessment in the region, and offers a transferable technical reference for active fault detection in similar tectonically active mountain-gorge settings worldwide. Moxi Fault integrated geophysics and geochemistry active fault detection thick overburden mountain–gorge region thick overburden Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 1. Introduction The Qinghai–Tibet Plateau, formed by the ongoing collision between the Indian and Eurasian plates, represents one of the most tectonically active regions on Earth (e.g., Yin & Harrison, 2000 ; Tapponnier et al., 2001). This collisional process has generated a complex network of large-scale strike-slip faults, which accommodate crustal deformation and frequently trigger destructive earthquakes that threaten populated areas and critical infrastructure across the plateau and its margins. Understanding the geometry, kinematics, and activity of these faults is therefore essential for mitigating seismic hazard and supporting sustainable development in the region. Against this broad tectonic backdrop, the Xianshuihe Fault Zone stands out as a key left-lateral strike-slip system that accommodates significant crustal motion in the southeastern Tibetan Plateau (e.g., Wen et al., 2008; Li et al., 2019). The Moxi Fault, located at the southeastern tip of the Xianshuihe Fault Zone, has long been recognized as a major seismogenic structure. On September 5, 2022, a destructive Ms 6.8 earthquake ruptured the Moxi Fault, causing extensive damage and highlighting the urgent need for precise characterization of its fault geometry, slip behavior, and late Quaternary activity. This event also underscores the critical gap in our ability to detect and characterize active faults in mountain-gorge regions with thick overburden, where complex topography and thick sediment cover obscure direct observations of fault geometry and activity. Mountain-gorge regions with thick overburden, such as the area surrounding the Moxi Fault, present unique technical challenges for active fault detection (e.g., Zhang et al., 2021; Liu et al., 2022). Steep topography, dense vegetation, and thick colluvial or alluvial deposits limit the effectiveness of traditional geological mapping and single geophysical methods, which often fail to resolve the deep-shallow structural coupling of fault zones or provide quantitative constraints on slip rates and recurrence intervals. While previous studies have applied individual geophysical techniques (e.g., shallow seismic reflection, electrical resistivity tomography) to image fault structures in similar settings, few have integrated multiple methods with geochemical observations to achieve a comprehensive understanding of fault architecture and fluid activity. Active faults act as channels and release windows for deep fluid migration, and their structural activity can modify underground gas migration paths, leading to measurable surface soil gas geochemical anomalies (e.g., CO₂, Rn, δ¹³C) (Xu et al., 2022 ). These geochemical signatures provide an independent constraint on fault location, complementing geophysical methods and offering a valuable tool for verifying fault zone continuity and fluid connectivity—information that is critical for understanding fault mechanics and seismic hazard potential. This motivated the integration of soil gas geochemical sampling alongside geophysical surveys in the present study. Despite the importance of the Moxi Fault and the 2022 earthquake, critical knowledge gaps remain in our understanding of its structure and activity. First, the precise geometry of the fault (e.g., dip angle, damage zone width) and its kinematic behavior (e.g., slip partitioning between strike-slip and dip-slip components) are not fully resolved. Second, quantitative constraints on late Quaternary slip rates and recurrence intervals are lacking, limiting our ability to assess long-term seismic hazard. Third, there is a lack of integrated geochemical evidence to verify the fault’s role as a conduit for deep fluid flow, which is critical for understanding fault mechanics and earthquake nucleation processes. These gaps hinder accurate seismic hazard assessment and post-earthquake reconstruction efforts in the region. This study aimed to address these knowledge gaps by developing an integrated detection framework combining geological-geomorphological survey, multi-method geophysics, and soil gas geochemistry to finely characterize the geometry, kinematics, and late Quaternary activity of the Moxi Fault. Specifically, we used high-resolution UAV remote sensing and field mapping to identify fault-related geomorphic features, complemented by shallow seismic reflection, high-density resistivity, microtremor survey, and ground-penetrating radar to image the deep-shallow structure of the fault zone, alongside high-density soil CO₂ and radon measurements to trace fault-related fluid pathways. Our preliminary results reveal that the Moxi Fault is a steeply west-dipping (75°–80°) left-lateral strike-slip fault with a 50–60 m wide damage zone, exhibiting a measured left-lateral displacement of 39.5 ± 0.5 m and a vertical throw of ~ 3 m, with a late Holocene slip rate of 5.3 ± 0.2 mm/yr. This integrated approach represents a novel contribution to the field, as it overcomes the technical challenges of mountain-gorge regions with thick overburden and provides a comprehensive dataset for seismic hazard assessment, offering a transferable technical reference for active fault detection in similar tectonically active settings worldwide. 2. Geological and Geomorphic Setting of the Study Area 2.1 Tectonic and Fault Framework The Xianshuihe Fault Zone is located at the eastern margin of the Qinghai‒Tibet Plateau and the central part of the North‒South Seismic Belt, stretching approximately 450 km along the north-northwest (NNW)‒south-southeast (SSE) strike direction and comprising several segments with distinct tectonic characteristics (Allen et al., 1991 ; Wen et al., 1989, 2000). The Moxi Fault, which is the southeastern segment of the Xianshuihe Fault Zone, extends from Kangding to Shimian with a relatively simple geometric configuration and is a major seismogenic fault in the southeastern part of the Qinghai‒Tibet Plateau (Sichuan Bureau of Geology and Mineral Resources, 1982; Tang et al., 1983; Shi et al., 1992 ; Liu et al., 1993; Xu et al., 2005; Ai et al., 2019; Ma et al., 2020). The fault is dominated by left-lateral strike-slip motion with a minor vertical slip component, and its activity is closely related to distal stress transmission from the northeastward subduction of the Indian Plate beneath the Eurasian Plate (Ma et al., 2020; Yi et al., 2023). 2.2 Topography and Geomorphology The study area is located in the mid–low mountain area of western Sichuan, a transitional zone between the Qinghai‒Tibet Plateau and the Chengdu Plain, with well-developed river valleys and gullies. The topography is characterized by mountain dominance interspersed with valley plains, thereby sloping from the high northwest to the low southeast. The elevation ranges from ~ 1870 m (Moxi River valley, the lowest point) to ~ 3500 m (Qipengzi Ridge, the highest point), with a relative elevation difference of ~ 1630 m. Valley plains are formed primarily via fluvial erosion–accumulation processes, and the macroscopic geomorphic features are significantly controlled by the tectonic activity of the Moxi Fault (Zhao et al., 2008; Chen et al., 2011). 2.3 Quaternary Deposits Quaternary deposits in the study area are notably influenced by glacial–interglacial climate changes and exhibit distinct vertical and horizontal zonation features (Li et al., 1991; Lu & Zhong, 1996). From high-altitude areas to the Dadu River valley, the deposits are dominated by moraines, glaciofluvial deposits, and alluvial‒diluvial deposits with varying thicknesses. Glaciofluvial deposits (thickness: ~100 m) are widely distributed across the Moxi Platform; these deposits comprise well-bedded gravel and sand layers and serve as important carriers for recording fault displacement (Chen et al., 2011). In the study area, the shallow surface is covered by heterogeneous boulder soil (pluvial–alluvial origin) and terrace fine sand–silt deposits, with thicknesses ranging from 5 to 25 m, thereby forming a thick overburden layer that obscures shallow fault traces (Zhao et al., 2008). 3. Geological and Geomorphic Survey Observations High-resolution unmanned aerial vehicle (UAV) remote sensing interpretation (spatial resolution: 0.1 m) and field seismogeological tracing surveys were conducted to identify the macroscopic distribution, geometric configuration, and kinematic characteristics of the Moxi Fault. UAV remote sensing data were processed to generate digital elevation models (DEMs) and orthophoto maps, which were used to interpret microgeomorphic features related to fault activity (e.g., fault troughs, slope breaks, displaced gullies, and sag ponds). Field surveys were conducted, thereby focusing on verifying remote sensing interpretations, measuring fault displacement, and collecting samples for geochronological dating, with a particular focus on Yuejinping and Buziba village, which are key areas with well-preserved fault-related geomorphic features. The Moxi Fault cuts obliquely through the hillside from north to south in the Yuejinping area, thereby forming a fault trough valley with a length of ~ 350 m and a width of 30–50 m. This area encompasses an alluvial platform formed from the late Pleistocene to the early Holocene, and trench excavation by Chen et al. (2011) confirmed that the surface rupture of the 1786 Kangding earthquake passed through this site, resulting in a cumulative displacement of 36 m. Although surface rupture features are obscured by anthropogenic modification, well-preserved fault sag ponds can still be identified. Field measurements and remote sensing model analysis revealed a 39.5 ± 0.5 m left-lateral displacement of a long abandoned gully on the platform surface, representing the cumulative strike-slip displacement of the Moxi Fault since the formation of the platform (Chen et al., 2011). Buziba village is located on the northern side of the Moxi Platform and is covered by Moxi River terrace deposits (bedded fine sand and silt). High-resolution UAV remote sensing and field surveys revealed clear 3 m-high slope breaks in the Buziba area, which result from the vertical slip component of the Moxi Fault, and the fault was observed to cut through the terrace deposits from north to south with obvious tectonic geomorphic features. Trench excavation was conducted in Buziba, which revealed that colluvial wedges formed because of seismic activity. In addition, several small faults offset the ground surface. The ¹⁴C ages of the glacial deposits at the bottom ranged from 6379 to 7856 year BP, which are generally consistent with the results (7420 ± 90 to 7430 ± 300 year BP) reported by Li et al. (1991). A radiocarbon (¹⁴C) age of 732 ± 30 year BP was obtained from layer U2, which is essentially consistent with the age of 1490 ± 70 year BP reported by Wen et al. (2001). On the basis of the dating data, the middle–late Holocene was identified as the active period of the Moxi Fault. The left-lateral displacement of the abandoned gully in Yuejinping and the vertical slope break in Buziba directly confirm the left-lateral strike-slip nature of the vertical slip component of the Moxi Fault, which is consistent with the results of previous regional studies (Chen et al., 2011; Ma et al., 2020). The cumulative left-lateral displacement of 39.5 ± 0.5 m is the most refined quantitative geomorphic displacement value for the Moxi Fault to date, which provides a key basis for calculating the slip rate of the fault combined with geochronological dating. 4. Geophysical Exploration Methods and Optimization 4.1 Geophysical Methods and Instrument Configuration Four geophysical methods were selected on the basis of the geological and topographic characteristics of the study area, with instrument configurations following mature technical specifications. Table 1 Instrument configuration and optimized parameters of geophysical exploration methods Method Instrument Configuration Optimized Sampling Spacing Detection Depth Uncertainty Range Parameter Optimization Basis Shallow seismic Seismic source: hammer; geophone: 40-Hz vertical geophone; recorder: DZQ-8B seismograph 5 m 0–300 m ± 1–5 m DZ/T 0370–2021; adjusted for thick boulder soil overburden High-density electrical Electrode array: Wenner–Schlumberger; recorder: E60D electrical prospecting instrument 5 m 0–200 m ± 2 m DZ/T 0370–2021; optimized for fluid-filled fracture zones Microtremor Seismograph: Summit X One (Germany); geophone: SN4-2 Hz low-frequency geophone 10 m 0–250 m ± 2–3 m Field tests (5/10/20 m): a 10-m spacing balances resolution and depth; a 5-m spacing causes data redundancy GPR Main unit: LTD-2600 (CETC); antenna: 100 MHz 20 cm 0–30 m ± 0.5 m Field tests (10/20/50 cm): a 20-cm spacing captures shallow fault displacement; a 50-cm spacing causes the loss of fine structures 4.2 Parameter Optimization for Complex Terrains To adapt to the complex geological conditions of the high mountain–gorge region with thick overburden, the sampling point spacing of microtremor exploration and GPR surveys was optimized through field comparative tests (from large to small spacings) to balance detection accuracy and efficiency. Notably, experimental design principles (e.g., controlled variable tests, gradient spacing settings, and sample size justification) were strictly followed to ensure the robustness of optimization results, as detailed in the Methods section. ① Microtremor exploration: Comparative tests with spacings of 5, 10, and 20 m were conducted to quantify the trade-off between data redundancy, anomaly resolution, and field efficiency. A 5-m spacing generated redundant data with low information efficiency, as closely spaced points added limited new structural details while doubling the field workload. A 20-m spacing resulted in the loss of key fault anomaly details, particularly subtle step-like variations in fault zone geometry, due to undersampling of the subsurface structural gradient. In contrast, a 10-m spacing accurately captured deep fault anomalies (e.g., low-velocity zone boundaries) while maintaining acceptable field work efficiency (≈ 8 km of survey lines per day). Hence, a spacing of 10 m was adopted for formal microtremor surveys, as this spacing achieved the optimal balance between resolution and efficiency required for characterizing fault structures in thick overburden. ② GPR: Comparative tests with spacings of 10, 20, and 50 cm were performed to optimize shallow subsurface imaging. A 50-cm spacing caused an excessive data volume (≈ 5 GB per 100 m of profile) and slow field acquisition, leading to logistical inefficiencies and increased processing costs. A 20-cm spacing failed to resolve shallow fine fault features (e.g., sub-centimeter scale stratum offsets), as the sampling interval exceeded the vertical resolution limit of GPR for shallow deposits. A 20-cm spacing achieved centimeter-level resolution for shallow stratum displacement and accurately revealed fault breakpoints, enabling clear identification of fault zone architecture and secondary fractures. Hence, a spacing of 20 cm was selected for formal GPR surveys, as this spacing provided the necessary detail to characterize shallow fault structures in mountain–gorge regions while maintaining practical data acquisition and processing workflows. 4.3 Geophysical Profile Layout A total of 8 geophysical exploration profiles were deployed along the strike of the Moxi Fault, perpendicular to the fault strike, to ensure the effective detection of fault structural features. To provide readers with key context for understanding the performance of the proposed integrated fault detection framework, three representative profiles (HT02, HT04, and HT07) fully covered by the four geophysical methods (shallow seismic reflection, high-density resistivity, microtremor exploration, and ground-penetrating radar) were selected for detailed analysis, with their specific characteristics described as follows: Profile HT02 (northern part): This ~ 1.2 km-long profile is located in the northern segment of the Moxi Fault, traversing a boulder soil area dominated by thick colluvial deposits and steep topography. It crosses a fault segment where surface ruptures are partially obscured by anthropogenic modification, making it ideal for testing the framework’s ability to detect buried fault structures in densely covered terrains. Profile HT04 (central part): Extending ~ 1.5 km in the central study area, this profile passes through a terrace fine sand–silt area (a typical fluvial sedimentary environment with relatively flat topography). It intersects the fault at a location with evident vertical slip components, enabling evaluation of the framework’s capacity to resolve both strike-slip and dip-slip fault features. Profile HT07 (southern part): Stretching ~ 1.0 km in the southern segment, this profile cuts across a weathered granite area with exposed bedrock and thin overburden. It targets a fault segment where geomorphic markers (e.g., displaced gullies) are well-preserved, allowing for direct comparison between geophysical anomalies and field-observed fault traces. Collectively, these three profiles cover distinct geological and geomorphic units, fully reflecting the adaptability of the integrated geophysical methods to complex mountain–gorge terrains with thick overburden, and providing a comprehensive basis for evaluating the framework’s performance in fault detection. 5. Geophysical Interpretation Criteria and Results 5.1 Unified Interpretation Criteria for Geophysical Methods To ensure the objectivity and reproducibility of geophysical interpretation, clear and quantitative interpretation criteria were established for each method on the basis of the geological characteristics of the study area and the literature (Table 2 ), with all threshold values verified by field tests and presurveys. Table 2 Quantitative interpretation criteria for fault identification with geophysical methods Method Core Interpretation Criteria (Quantitative Thresholds) Literature Basis/Field Calibration Shallow seismic 1. Discontinuity of stratigraphic reflection events; 2. amplitude decrease of > 30% in the fault zone; 3. dominant frequency reduction (80–200 Hz → 20–80 Hz); 4. high-frequency component (> 150 Hz) attenuation of > 80% DZ/T 0370–2021; Yuejinping Fault outcrop High-density electrical 1. Linear low-resistivity anomaly zone; 2. abrupt resistivity change at the same depth; 3. discontinuity of the top high-resistivity layer of the bedrock DZ/T 0370–2021; Buziba area Microtremor 1. Linear low-apparent shear wave velocity anomaly zone; 2. dispersion curve inflection/discontinuity; 3. velocity gradient zone (width: 5–15 m; velocity difference: 2–3× the normal area) Rein et al. ( 2024 ); Qipengzi Ridge GPR 1. Vertical/horizontal displacement of reflected wave groups; 2. abrupt termination of continuous wave groups; 3. waveform distortion and energy attenuation (> 50%) Wang et al. ( 2024 ); shallow fault outcrop 5.2 Geophysical Interpretation Results for the Representative Profiles The raw geophysical data were processed using professional commercial software, with explicit parameter settings specified to ensure full reproducibility: Shallow seismic reflection data: Processed in Reflex-W using standard default workflows (band-pass filtering, static correction, normal moveout correction) with no specialized parameter adjustments, which is widely accepted for shallow seismic imaging in mountain-gorge regions with thick overburden. High-density electrical resistivity data: Processed in Res2dinv with default robust inversion parameters (5% data error tolerance, L1-norm regularization), consistent with common practices for fault zone characterization in complex terrains. Microtremor data: Processed in Surfer using default kriging gridding and contouring parameters, which are standard for visualizing spatial variations in shear wave velocity ratios. Ground-penetrating radar (GPR) data: Processed in RADAN with default migration and automatic gain control settings, optimized for resolving shallow subsurface stratigraphic and fault-related features in thick overburden. The key objective observations of profiles HT02, HT04, and HT07 are summarized as follows (Figs. 4 –15): ① Profile HT02 (boulder soil overburden, 5–10 m): No continuous seismic reflection interface is observed at depths of 0–10 m; a linear low-resistivity anomaly (180–250 Ω·m) is identified at depths of 140–180 m, accompanied by a low-apparent shear wave velocity zone (200–250 m/s) at the same depth range; a wedge-shaped chaotic GPR reflection is detected at 160 m. ② Profile HT04 (fine sand-silt overburden, 15–25 m): A clear seismic reflection interruption is present at depths of 70–80 m; a linear low-resistivity anomaly (200–300 Ω·m) is observed at depths of 60–90 m, corresponding to a low-apparent shear wave velocity zone (180–220 m/s) at the same depth range; a vertical GPR wave group displacement of 1.5 m is identified at depths of 70–80 m. ③ Profile HT07 (weathered granite overburden, 5–15 m): A seismic reflection dislocation is detected at depths of 90–110 m (bedrock layer); no obvious electrical anomaly is observed (only resistivity fluctuations of 300–500 Ω·m); a low-apparent shear wave velocity zone (220–250 m/s) is present at depths of 90–110 m, coinciding with an abrupt termination of the GPR wave group at the same depth range. 5.3 Interpretation and Discussion of the Geophysical Results On the basis of the objective observations and geological-geomorphic constraints, geophysical anomalies were interpreted as fault-related features. The complementary advantages of the four methods were evaluated by quantifying their resolution capabilities and uncertainty budgets, with the results summarized below: ① Profile HT02 (boulder soil overburden): Shallow seismic reflection failed to characterize the shallow fault structure due to strong velocity heterogeneity from boulder soil, introducing a positional uncertainty of ± 5 m. In contrast, the high-density electrical method (resolution: ±2 m) and GPR technology (resolution: ±0.5 m) compensated for this deficiency by resolving the upper breakpoint and confirming its surface outcrop, providing precise spatial constraints on the fault’s shallow structure. ② Profile HT04 (fine sand-silt overburden): Microtremor exploration yielded ambiguous fault core positioning due to minimal stiffness contrasts between interbedded fine sand and silt layers, resulting in a positional uncertainty of ± 3 m. The shallow seismic method (resolution: ±1 m) accurately located the fault core and delivered quantitative displacement data, including a 1.5-m vertical GPR wave group displacement at 70–80 m depth, which constrained the fault’s vertical slip component with sub-meter precision. ③ Profile HT07 (weathered granite overburden): The high-density electrical method failed to resolve the fault due to uneven weathering of the granite bedrock, which created resistivity fluctuations (300–500 Ω·m) that masked the fault-related anomaly. Microtremor and shallow seismic exploration could only penetrate the shallow weathered layer (≤ 15 m depth), but they confirmed the fault’s truncation of the deep bedrock at 90–110 m depth, with a positional uncertainty of ± 2 m for the bedrock-fault intersection. 5.4 Comprehensive Geophysical Characterization of the Moxi Fault On the basis of multimethod complementary interpretation (detailed in Figs. 4 –15 and Table S1), the geometric characteristics of the Moxi Fault are summarized as follows: A. Fracture zone width: 50–60 m (averaged from three representative profiles (HT02, HT04, and HT07); this range reflects lithological heterogeneity across the study area, as visualized in the geophysical cross-sections of Figs. 8, 11, and 14. B. Fault plane dip: Steep westward dipping, with an apparent dip angle of 75–80° (consistent across all three profiles, as quantified by shallow seismic and microtremor velocity profiles in Figs. 7, 10, and 13). C. Upper breakpoint: Outcrops at the surface (verified by GPR reflection profiles in all three study profiles, as illustrated in Figs. 9, 12, and 15). D. Vertical connectivity: Cuts through shallow overburden and deep bedrock (confirmed by microtremor shear wave velocity and shallow seismic reflection data, as shown in Figs. 6 –7, 10–11, and 13–14). E. Spatial consistency: The geophysically inferred fault location is entirely consistent with the geomorphic fault location identified in Section 3 , with an overall absolute error of ± 2–5 m (quantified by comparing fault positions in geophysical profiles and UAV DEMs, as documented in Table S2). The ¹⁴C dating results for the glaciofluvial deposits in the study area (6379 ± 120 to 7856 ± 40 year BP) are essentially consistent with the ¹⁴C ages (7420 ± 90 to 7430 ± 300 year BP) reported by Li et al. (1991). Combined with dating data from layer U2 (732 ± 30 year BP), these results constrain the active period of the Moxi Fault to the middle–late Holocene, as visualized in the trench stratigraphy and dating plot (Fig. 3 ). 6. Geochemical Exploration: Methods, Results and Verification 6.1 Soil Gas Sampling and Measurement Methods In this study, soil gas was measured along the three geophysical profiles (HT02, HT04, HT07) to provide independent geochemical validation for the geophysically inferred fault location, with sampling points aligned with geophysical survey points to ensure spatial comparability. The instrument configuration, calibration protocols, and sampling parameters are summarized in Table 3 . Radon (Rn) measurement: A RAD7 radon detector was employed for Rn concentration measurements. Daily calibration was performed using a ²²⁶Ra standard source (100 ± 5 Bq) to ensure measurement stability, and zero drift correction was implemented every 50 consecutive sampling points to mitigate instrumental drift. This calibration regime resulted in a quantitative measurement error of ± 5% for Rn concentrations. Sampling was conducted at 5-m intervals along all three profiles to maintain consistent spatial resolution with geophysical surveys. Carbon dioxide (CO₂) measurement: An LI-840A infrared gas analyzer was used to measure CO₂ concentrations. Weekly calibration was carried out using three standard CO₂ gas mixtures (0 ppm, 5000 ppm, and 10000 ppm) to establish a linear response curve, and the linear error was controlled to < 2% throughout the measurement period. This calibration workflow yielded a measurement error of ± 2% for CO₂ concentrations. Sampling was performed at 5-m intervals, matching the spacing of Rn sampling to ensure spatial consistency across all soil gas datasets. Table 3 Instrument configuration, calibration and sampling parameters of geochemical exploration Index Instrument Model Calibration Procedure Sampling Spacing Measurement Error Rn RAD7 radon detector Daily calibration with a ²²⁶Ra standard source (100 ± 5 Bq); zero drift correction every 50 points 5 m ± 5% CO₂ LI-840A infrared analyzer Weekly calibration with 0/5000/10000 ppm standard CO₂ gas; linear error < 2% 5 m ± 2% 6.2 Soil Gas Geochemical Anomaly Characteristics Soil gas CO₂ and Rn were measured along profiles HT02, HT04 and HT07, with background values calculated as the 95% confidence intervals of nonanomaly points. The quantitative geochemical anomaly characteristics are listed in Table 4 and shown in Figs. 7–8. Table 4 Quantitative geochemical anomaly characteristics of the three profiles Profile CO₂ Background Value CO₂ Anomaly Range CO₂ Peak Value Rn Background Value Rn Anomaly Range Rn Peak Value HT02 500–1000 ppm 140–180 m 20000 ppm 5–10 Bq/L 140–180 m 20 Bq/L HT04 500–1000 ppm 60–90 m 25000 ppm 5–10 Bq/L 70–80 m 18 Bq/L HT07 500–1000 ppm 90–110 m 18000 ppm 5–10 Bq/L 90–120 m 15 Bq/L 6.3 Mechanistic Interpretation of Geochemical Anomalies A. Profile HT02: The fault fracture zone is a fluid-filled high-permeability zone (pore water saturation: 60–70%), with complete overlap of CO₂ and Rn anomalies across the 140–180 m segment. Building on these observations and previous studies of deep fluid migration along active faults (e.g., Xu et al., 2022 ; Li et al., 2020), we infer that Rn (produced by radioactive decay of deep bedrock elements; Shen et al., 2018) and CO₂ (derived from deep crustal fluid sources; Wang et al., 2019) migrate upward along the fault channel and accumulate at the surface. This complete anomaly overlap confirms that the fault acts as a core fluid release window, consistent with our geophysical evidence of deep-shallow fault connectivity. B. Profile HT04: The fault fracture zone exhibits high porosity (30–40%) favorable for gas accumulation, with the highest CO₂ peak (25000 ppm) among all profiles; CO₂ anomalies span a 30 m-wide zone, while Rn anomalies are concentrated in the fault core (70–80 m), resulting in partial anomaly overlap. Combining established differences in gas diffusion properties (Rn has lower diffusivity than CO₂ in porous media; Zhang et al., 2021), we speculate that the partial overlap arises from preferential trapping of Rn in the high-porosity fault core, while CO₂ diffuses more broadly into the surrounding fine sand-silt layer. C. Profile HT07: Located on the Qipengzi Ridge (a dry fracture zone with limited groundwater, confirmed by field surveys), CO₂ shows the lowest peak value (18000 ppm) and rapid diffusion, while Rn exhibits a larger anomaly range; core anomaly overlap is observed at 90–110 m. Consistent with gas diffusion behavior in arid, low-moisture environments (Liu et al., 2022), the rapid diffusion of CO₂ and relatively extensive diffusion of Rn lead to core anomaly overlap. This observation confirms the fault’s fluid release function even in arid, low-groundwater conditions, aligning with our geophysical detection of fault continuity through bedrock. Overall, the variable anomaly overlap patterns across the three profiles reflect differences in fault zone permeability, lithology, and hydrological conditions, and collectively validate the fault’s role as a deep fluid conduit—providing independent geochemical support for our integrated geophysical characterization of the Moxi Fault. 6.4 Geochemical Validation and Alternative Explanation This subsection aimed to validate the spatial coupling between soil gas geochemical anomalies and the geophysically identified Moxi Fault zones, and to rule out non-tectonic alternative explanations by providing independent geochemical evidence for the fault’s role as a deep fluid release window. Soil gas CO₂ and Rn were measured along three representative profiles (HT02, HT04, HT07), with sampling points aligned to geophysical survey sites to ensure spatial comparability. Geochemical anomaly intervals and core positions were compared against geophysical anomaly zones (shallow seismic dislocation, high-density electrical low-resistivity zone, microtremor low-wave velocity zone, and GPR wave group displacement). Three potential non-tectonic alternative explanations (carbonate dissolution, seasonal variability, anthropogenic activity) were systematically evaluated and ruled out (Table 5 ), following established protocols for geochemical fault tracing (e.g., Xu et al., 2022 ; Liu et al., 2022). Table 5 Alternative explanations for the geochemical anomalies and ruling basis Alternative Explanation Ruling Basis Carbonate dissolution No carbonate outcrops in the study area; dissolution CO₂ exhibits a δ¹³C value close to + 0‰~+5‰ Seasonal variability Sampling was completed during the same season (autumn 2023); no rainfall occurred during sampling Anthropogenic activity Sampling points are located far from human settlements (> 500 m); no agricultural/industrial activity occurs in the area All three geochemical profiles exhibited high spatial coincidence between soil CO₂-Rn anomalies and geophysically identified fault zones, with anomaly intervals and core positions consistent with geophysical anomaly zones (shallow seismic dislocation, high-density low electrical resistivity, microtremor low wave velocity, and GPR wave group displacement). This spatial coupling verifies that the geophysically inferred anomaly zones constitute the active fracture zones of the Moxi Fault and confirms that the fault functions as a deep fluid release window. Notably, fault structural activity yields interconnected fracture networks that serve as migration channels for deep crust-mantle fluids (CO₂ and Rn; Wang et al., 2019), causing the concentrated enrichment of these gases in the surface soil above the fault zone and the formation of detectable geochemical anomalies. Alternative explanations for geochemical anomalies were ruled out (Table 5 ), confirming that the anomalies are related to the fault rather than other factors: No carbonate outcrops exist in the study area; dissolution-derived CO₂ exhibits a δ¹³C value close to 0‰ (± 3‰; Li et al., 2023), which was not observed in our samples; sampling was completed during the same season (autumn 2023); no rainfall occurred during sampling ( 500 m from human settlements, with no agricultural or industrial activity in the area, excluding anthropogenic gas sources. The geochemical results also demonstrated the applicability of soil CO₂/Rn measurements for hidden fault tracing in high mountain–gorge regions with thick overburden (Xu et al., 2022 ). Notably, even when shallow fault traces are obscured by heterogeneous overburden, soil gas geochemistry can effectively reveal fault locations by capturing deep fluid release signals, thus providing a reliable geochemical verification method for geophysical detection results. 7. Comprehensive Discussion 7.1 Integrated Detection Framework for Active Faults in Complex Terrains This study addresses the technical bottlenecks associated with the detection of active faults in high mountain – gorge regions with thick overburden by integrating geological–geomorphic surveys, optimized multimethod geophysics, and soil gas geochemistry and provides a deep–shallow coupling and geochemical verification integrated detection framework. The core of this framework is method complementarity and parameter optimization: ① Geological–geomorphic surveys (UAV + field tracing): These surveys provide the macroscopic fault distribution and kinematic characteristics and can be used to determine the layout of geophysical and geochemical profiles; ② Deep geophysical detection (shallow seismic + 10 m-spacing microtremor exploration): The deep fault structure (dip angle, fracture zone width, and vertical connectivity) can be characterized, and the shallow heterogeneous overburden is penetrated; ③ Shallow geophysical detection (high-density electrical + 20 cm-spacing GPR surveys): Shallow fault breakpoints and surface displacement features can be identified, thereby compensating for the deficiency of deep detection in shallow fault characterization; ④ Soil gas geochemistry (5 m-spacing CO₂/Rn measurements): Geophysically identified fault zones can be verified, the fluid release characteristics of the fault can be characterized, and multiple solutions for geophysical interpretation can be circumvented. This framework overcomes the inherent limitations of single detection methods and increases the resolution and reliability of active fault characterization in complex terrains. The optimized parameters (10-m microtremor spacing, 20-cm GPR spacing, and 5 m soil gas spacing) are suitable for high mountain – gorge regions with thick overburden and can be adjusted according to the specific geological conditions of various study areas, thereby providing a reproducible technical reference for active fault investigations in tectonically similar regions with complex topography and thick overburden. 7.2 Late Quaternary Activity Parameters of the Moxi Fault: Slip Rate and Active Period 7.2.1 Calculation of the Late Holocene Slip Rate The late Holocene slip rate of the Moxi Fault can be calculated on the basis of the cumulative left-lateral displacement (39.5 ± 0.5 m) measured in the Yuejinping area and the ¹⁴C dating results (6379 ± 120 to 7856 ± 40 year BP) for the glaciofluvial deposits hosting the displaced gully. The ¹⁴C dating results are consistent with the ¹⁴C ages of glaciofluvial deposits in the study area obtained by Li et al. (1991) (7420 ± 90 to 7430 ± 300 year BP), thus verifying the reliability of the age constraints. The calculated late Holocene slip rate of the Moxi Fault is 5.3 ± 0.2 mm/yr, which is consistent with the overall slip rate of the Xianshuihe Fault Zone (4–6 mm/yr) reported in previous studies (Wen, 2000; Bai et al., 2021 ). This consistency verifies that the Moxi Fault is a tectonically consistent segment of the Xianshuihe Fault Zone and that its activity is controlled by the regional tectonic stress field. 7.2.2 Constraints on the Active Period Combined with our in-situ ¹⁴C dating results (6379 ± 120 to 7856 ± 40 year BP) and the geomorphic characteristics of the displaced gully (formed during the middle–late Holocene), we constrain the active period of the Moxi Fault to the middle–late Holocene (since ~ 7856 year BP). This result refines the previous constraint of the latest occurrence of intense fault activity to the middle Holocene (Chen et al., 2011), providing a more precise time scale for regional tectonic evolution and paleoseismic reconstruction. Summary: By narrowing the active period to ~ 7.8 ka, this study improves the temporal resolution of Moxi Fault activity, enabling more accurate assessments of long-term seismic hazard and regional tectonic processes. The positive correlation between the calculated slip rate (5.3 ± 0.2 mm/yr) and the fracture zone width (50–60 m) of the Moxi Fault aligns with the empirical relationship between the slip rate and fracture zone width for active strike-slip faults proposed by Allen et al. ( 1991 ). This alignment verifies the applicability of this empirical relationship to the Moxi Fault and the Xianshuihe Fault Zone under the tectonic conditions of the southeastern Qinghai–Tibet Plateau. Summary: This validation of the slip rate-fracture width relationship in a high mountain-gorge setting extends the empirical framework to complex terrains, offering a valuable reference for characterizing active strike-slip faults in similar tectonic settings globally. 7.3 Tectonic Significance: Fault Occurrence and Regional Stress Field Coupling The Moxi fault exhibits a steep westward dip angle of 75–80°, which is consistent with the NE–SW-trending principal compressive stress field in the southeastern part of the Qinghai‒Tibet Plateau (horizontal stress: 8–12 MPa) observed by regional global positioning system (GPS) measurements (Ma et al., 2020). According to the Coulomb failure criterion, the optimal dip angle range for left-lateral strike-slip faults under horizontal principal compressive stress is 70–85°, and the dip angle of the Moxi Fault occurs exactly within this range, which indicates that its occurrence and geometric characteristics are the product of distal stress transmission from the northeastward subduction of the Indian Plate beneath the Eurasian Plate. These results supplement the evidence for the chain of plate collision → regional stress field → fault occurrence and activity in the southeastern part of the Qinghai‒Tibet Plateau and verify that the active strike-slip faults in this area constitute the primary tectonic response to the Indo–Eurasian collision. The high dip angle of the Moxi Fault also suggests that the fault exhibits a large seismogenic depth and the potential to generate strong earthquakes, providing an important tectonic basis for regional seismic hazard assessment. 7.4 Limitations and Prospects This study presents an effective integrated detection framework for active faults in high mountain – gorge regions with thick overburden but exhibits the following two main limitations: (1) the geochemical analysis focuses only on soil CO₂ and Rn, with no analysis of other trace gases (e.g., He and CH₄) that can further constrain fluid sources; (2) the slip rate calculation is based on geomorphic displacement and ¹⁴C dating. Future research should aim to (1) expand the scope of geochemical analysis to include multiple trace gases and isotopes (e.g., ³He/⁴He) to accurately constrain the source and migration pathway of deep fluids and (2) apply the integrated detection framework to more active fault segments in the Xianshuihe Fault Zone to establish a regional active fault parameter database and improve the scientific basis for seismic hazard assessment in the southeastern part of the Qinghai‒Tibet Plateau. 8. Conclusions This study establishes an integrated detection framework that combines geological-geomorphic surveys, optimized multi-method geophysics, and soil gas geochemistry to characterize the Moxi Fault—the seismogenic fault of the 2022 Ms 6.8 earthquake in the southeastern Qinghai–Tibet Plateau—overcoming key technical barriers to active fault detection in high mountain–gorge terrains with thick overburden. The core findings are summarized as follows: A. Geometric and kinematic characteristics: The Moxi Fault is a steep west-dipping (apparent dip: 75–80°) left-lateral strike-slip fault with a 50–60 m-wide fracture zone and a surface-exposed upper breakpoint. Field measurements reveal a 39.5 ± 0.5 m left-lateral displacement and ~ 3 m vertical relief, confirming its dominant left-lateral strike-slip nature with a minor vertical slip component. B. Optimized geophysical detection system: A complementary geophysical system (shallow seismic surveys, high-density electrical method, 10-m spacing microtremor surveys, 20-cm spacing GPR surveys) is established with quantitative interpretation criteria. This system enables deep-shallow coupling characterization: shallow seismic and microtremor exploration excel at deep fault detection, while high-density electrical methods and GPR can effectively identify shallow breakpoints. C. Geochemical verification of fault activity: Three 5-m spacing soil CO₂/Rn profiles show high spatial coincidence between geochemical anomalies and geophysically identified fault zones, verifying that the fault acts as a deep fluid release window. High-concentration CO₂ anomalies indicate deep fluid release, demonstrating the applicability of soil CO₂/Rn measurements for hidden fault tracing in thick overburden terrains. D. Late Quaternary activity parameters: On the basis of ¹⁴C dating (6379 ± 120 to 7856 ± 40 year BP) and geomorphic displacement, the fault’s active period is constrained to the middle–late Holocene, with a late Holocene slip rate of 5.3 ± 0.2 mm/yr. This rate aligns with the Xianshuihe Fault Zone’s regional slip rate (4–6 mm/yr) and validates the empirical slip rate-fracture zone width relationship (Allen et al., 1991 ) in the study area. E. Tectonic significance: The 75–80° west dip angle is consistent with the NE–SW principal compressive stress field in the southeastern Qinghai–Tibet Plateau, confirming that fault occurrence and activity are driven by the northeastward subduction of the Indian Plate beneath the Eurasian Plate. These results strengthen evidence for the coupled plate collision–regional stress field–fault response chain in the eastern Tibetan Plateau. Beyond these site-specific findings, the integrated deep-shallow coupling and geochemical verification framework provide high-precision tectonic data for the Moxi Fault, directly supporting post-disaster reconstruction and seismic risk assessment in the 2022 Ms 6.8 earthquake epicenter area. More broadly, this framework offers a transferable technical reference for active fault investigations in tectonically similar regions worldwide—characterized by complex topography and thick surface deposits—filling a critical methodological gap in high mountain–gorge terrain fault detection. Future work could expand this framework to incorporate multi-isotope geochemical tracing and apply it to additional segments of the Xianshuihe Fault Zone to refine regional seismic hazard models. Declarations Conflict of Interest: The authors declare that they have no conflicts of interest. Funding: This work was supported by the Science and Technology Innovation Projects of the Sichuan Provincial Bureau of Geology and Mineral Resources Exploration and Development (Nos. SCDKZCKJXM-2021063 and SCDZ-KJXM202402). Author Contribution Chao Tan was primarily responsible for the overall text editing and conceptual organization of the manuscript.Ye Kuang is Corresponding authors, and Ruiqing Xiao conducted geophysical surveys and relevant research.Xiujun Dong undertook the revision and critical review of the paper.Kejia Wei performed field investigations pertaining to geochemical studies. References Allen, C. R., Luo, Z., Qian, H., Wen, X., Zhou, H., & Huang, W. (1991). Field study of a highly active fault zone: The XSF of southwestern China. Geological Society of America Bulletin, 103, 1178–1199. Ai Y F, Zhang J.Geophysical analysis on the tectonic difference between northern and southern segmengts of xianshuihe fault zone[J].Acta seismologica sinica,41(3):329-342. Bekaert D V, Turner S J, Broadley M W, Barnes J D, Halldórsson S A, Labidi J, Wade J, Walowski K J, Barry P H. 2021. Subduction-driven volatile recycling: A global mass balance. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-9258880","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":625573648,"identity":"b8db5899-94e8-4eb1-8d43-589f9065734c","order_by":0,"name":"Chao Tan","email":"","orcid":"","institution":"Chengdu University of Technology","correspondingAuthor":false,"prefix":"","firstName":"Chao","middleName":"","lastName":"Tan","suffix":""},{"id":625573649,"identity":"af462957-8065-4a4f-b4a9-4992f6ef8379","order_by":1,"name":"Ye Kuang","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA1klEQVRIiWNgGAWjYBACNvbm459//rOR42dvPkCcFj6eY2nMDGxpxpI9xxKI0yInkWMG1HI40eBGjgGRDpNIS3tcwJOWwHAj5+ONNwx2croNhLTwPD5uPEPCJo+x5+1myzkMycZmBwhpYU9LkOAxSCtmZs/dJs3DcCBxG0EtDDkGEjwJhxPbGHKeEamFI8dMmufA4cQejhw2IrXwHEs2nNmQZizBc8zYco4BEX6Rb28++OBjg42c/fHmhzfeVNjJEdSCAoDhQIpyiBZSdYyCUTAKRsGIAADVjEJUvptJ1QAAAABJRU5ErkJggg==","orcid":"","institution":"The First Geological Brigade of Sichuan Province","correspondingAuthor":true,"prefix":"","firstName":"Ye","middleName":"","lastName":"Kuang","suffix":""},{"id":625573650,"identity":"9b2ad10c-5402-466f-8dd1-60401dccb5f1","order_by":2,"name":"Xiujun Dong","email":"","orcid":"","institution":"Chengdu University of Technology","correspondingAuthor":false,"prefix":"","firstName":"Xiujun","middleName":"","lastName":"Dong","suffix":""},{"id":625573651,"identity":"79f136b7-edcb-4947-be16-2216ad50b7d4","order_by":3,"name":"Ruiqing Xiao","email":"","orcid":"","institution":"The First Geological Brigade of Sichuan Province","correspondingAuthor":false,"prefix":"","firstName":"Ruiqing","middleName":"","lastName":"Xiao","suffix":""},{"id":625573653,"identity":"01120b5e-0601-4e2d-81e1-32192b022107","order_by":4,"name":"Kejia Wei","email":"","orcid":"","institution":"The First Geological Brigade of Sichuan Province","correspondingAuthor":false,"prefix":"","firstName":"Kejia","middleName":"","lastName":"Wei","suffix":""}],"badges":[],"createdAt":"2026-03-29 12:53:35","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-9258880/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9258880/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":107317279,"identity":"a59fb985-7a88-40e1-be7d-9cb9f701be39","added_by":"auto","created_at":"2026-04-20 09:58:16","extension":"jpeg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":268495,"visible":true,"origin":"","legend":"\u003cp\u003eLocation of the study area and distribution of surrounding active faults\u003c/p\u003e","description":"","filename":"floatimage1.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-9258880/v1/186e7e5f7d827a39d7344aef.jpeg"},{"id":107317323,"identity":"d830866c-6bcb-446f-9fbf-1e6b7049658d","added_by":"auto","created_at":"2026-04-20 09:58:22","extension":"jpeg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":633861,"visible":true,"origin":"","legend":"\u003cp\u003eGeological and geomorphic features of the Moxi Fault. (a) Displaced abandoned gully in Yuejinping village (shooting angle: S); (b) slope break in Buziba village (shooting angle: NW)\u003c/p\u003e","description":"","filename":"floatimage2.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-9258880/v1/872611482620e3ec4d5ba8a4.jpeg"},{"id":107317312,"identity":"670bc5f8-2fa5-4e1c-8925-dccc577915e5","added_by":"auto","created_at":"2026-04-20 09:58:22","extension":"jpeg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":92871,"visible":true,"origin":"","legend":"\u003cp\u003eInterpretation of the southern wall of the exploration trough in Buziba village\u003c/p\u003e","description":"","filename":"floatimage3.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-9258880/v1/ad88f96f3f886c3211ef2ea7.jpeg"},{"id":107317297,"identity":"40c99884-4cbd-43a5-9561-ec2aa3a6ed1d","added_by":"auto","created_at":"2026-04-20 09:58:21","extension":"jpeg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":114317,"visible":true,"origin":"","legend":"\u003cp\u003eSchematic illustration of the location of the geophysical and geochemical prospecting profiles in the study area\u003c/p\u003e","description":"","filename":"floatimage4.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-9258880/v1/2f50bd5ba6954e25a693e2a2.jpeg"},{"id":107317539,"identity":"722c0ca4-4168-4737-98a3-4ae676d13bde","added_by":"auto","created_at":"2026-04-20 09:58:38","extension":"jpeg","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":340701,"visible":true,"origin":"","legend":"\u003cp\u003eFrom left to right: Shallow seismic profile, high‑density electrical resistivity profile, and microtremor profile (a: profile 2, b: profile 4, c: profile 7)\u003c/p\u003e","description":"","filename":"floatimage5.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-9258880/v1/5ceee78f1fedcc5885a3a453.jpeg"},{"id":107317271,"identity":"d62ebae0-9d4c-4d6a-a925-ae108d5a0ce3","added_by":"auto","created_at":"2026-04-20 09:58:16","extension":"jpeg","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":387653,"visible":true,"origin":"","legend":"\u003cp\u003eGround-penetrating radar (GPR) profiles (a: profile 2, b: profile 4, c: profile 7)\u003c/p\u003e","description":"","filename":"floatimage6.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-9258880/v1/037148ba9701b249692f63d6.jpeg"},{"id":107317269,"identity":"e54e3b27-e9db-4744-8d7c-b6e578b45574","added_by":"auto","created_at":"2026-04-20 09:58:15","extension":"jpeg","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":496931,"visible":true,"origin":"","legend":"\u003cp\u003e8 Merged soil CO₂ and Rn anomaly maps for profiles HT02, HT04 and HT07\u003c/p\u003e","description":"","filename":"floatimage7.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-9258880/v1/54bd0ae73ee323534cdad0ff.jpeg"},{"id":107487222,"identity":"98c2df76-b36c-4c12-932f-c51839c1a187","added_by":"auto","created_at":"2026-04-22 02:40:06","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2805408,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9258880/v1/20ffdccb-fa7f-4a2c-bf49-acd3c835c9cb.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Integrated Geophysical and Geochemical Detection of the Active Moxi Fault at the Southeastern Margin of the Qinghai‒Tibet Plateau","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eThe Qinghai\u0026ndash;Tibet Plateau, formed by the ongoing collision between the Indian and Eurasian plates, represents one of the most tectonically active regions on Earth (e.g., Yin \u0026amp; Harrison, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2000\u003c/span\u003e; Tapponnier et al., 2001). This collisional process has generated a complex network of large-scale strike-slip faults, which accommodate crustal deformation and frequently trigger destructive earthquakes that threaten populated areas and critical infrastructure across the plateau and its margins. Understanding the geometry, kinematics, and activity of these faults is therefore essential for mitigating seismic hazard and supporting sustainable development in the region.\u003c/p\u003e \u003cp\u003eAgainst this broad tectonic backdrop, the Xianshuihe Fault Zone stands out as a key left-lateral strike-slip system that accommodates significant crustal motion in the southeastern Tibetan Plateau (e.g., Wen et al., 2008; Li et al., 2019). The Moxi Fault, located at the southeastern tip of the Xianshuihe Fault Zone, has long been recognized as a major seismogenic structure. On September 5, 2022, a destructive Ms 6.8 earthquake ruptured the Moxi Fault, causing extensive damage and highlighting the urgent need for precise characterization of its fault geometry, slip behavior, and late Quaternary activity. This event also underscores the critical gap in our ability to detect and characterize active faults in mountain-gorge regions with thick overburden, where complex topography and thick sediment cover obscure direct observations of fault geometry and activity.\u003c/p\u003e \u003cp\u003eMountain-gorge regions with thick overburden, such as the area surrounding the Moxi Fault, present unique technical challenges for active fault detection (e.g., Zhang et al., 2021; Liu et al., 2022). Steep topography, dense vegetation, and thick colluvial or alluvial deposits limit the effectiveness of traditional geological mapping and single geophysical methods, which often fail to resolve the deep-shallow structural coupling of fault zones or provide quantitative constraints on slip rates and recurrence intervals. While previous studies have applied individual geophysical techniques (e.g., shallow seismic reflection, electrical resistivity tomography) to image fault structures in similar settings, few have integrated multiple methods with geochemical observations to achieve a comprehensive understanding of fault architecture and fluid activity.\u003c/p\u003e \u003cp\u003eActive faults act as channels and release windows for deep fluid migration, and their structural activity can modify underground gas migration paths, leading to measurable surface soil gas geochemical anomalies (e.g., CO₂, Rn, δ\u0026sup1;\u0026sup3;C) (Xu et al., \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). These geochemical signatures provide an independent constraint on fault location, complementing geophysical methods and offering a valuable tool for verifying fault zone continuity and fluid connectivity\u0026mdash;information that is critical for understanding fault mechanics and seismic hazard potential. This motivated the integration of soil gas geochemical sampling alongside geophysical surveys in the present study.\u003c/p\u003e \u003cp\u003eDespite the importance of the Moxi Fault and the 2022 earthquake, critical knowledge gaps remain in our understanding of its structure and activity. First, the precise geometry of the fault (e.g., dip angle, damage zone width) and its kinematic behavior (e.g., slip partitioning between strike-slip and dip-slip components) are not fully resolved. Second, quantitative constraints on late Quaternary slip rates and recurrence intervals are lacking, limiting our ability to assess long-term seismic hazard. Third, there is a lack of integrated geochemical evidence to verify the fault\u0026rsquo;s role as a conduit for deep fluid flow, which is critical for understanding fault mechanics and earthquake nucleation processes. These gaps hinder accurate seismic hazard assessment and post-earthquake reconstruction efforts in the region.\u003c/p\u003e \u003cp\u003eThis study aimed to address these knowledge gaps by developing an integrated detection framework combining geological-geomorphological survey, multi-method geophysics, and soil gas geochemistry to finely characterize the geometry, kinematics, and late Quaternary activity of the Moxi Fault. Specifically, we used high-resolution UAV remote sensing and field mapping to identify fault-related geomorphic features, complemented by shallow seismic reflection, high-density resistivity, microtremor survey, and ground-penetrating radar to image the deep-shallow structure of the fault zone, alongside high-density soil CO₂ and radon measurements to trace fault-related fluid pathways. Our preliminary results reveal that the Moxi Fault is a steeply west-dipping (75\u0026deg;\u0026ndash;80\u0026deg;) left-lateral strike-slip fault with a 50\u0026ndash;60 m wide damage zone, exhibiting a measured left-lateral displacement of 39.5\u0026thinsp;\u0026plusmn;\u0026thinsp;0.5 m and a vertical throw of ~\u0026thinsp;3 m, with a late Holocene slip rate of 5.3\u0026thinsp;\u0026plusmn;\u0026thinsp;0.2 mm/yr. This integrated approach represents a novel contribution to the field, as it overcomes the technical challenges of mountain-gorge regions with thick overburden and provides a comprehensive dataset for seismic hazard assessment, offering a transferable technical reference for active fault detection in similar tectonically active settings worldwide.\u003c/p\u003e"},{"header":"2. Geological and Geomorphic Setting of the Study Area","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1 Tectonic and Fault Framework\u003c/h2\u003e \u003cp\u003eThe Xianshuihe Fault Zone is located at the eastern margin of the Qinghai‒Tibet Plateau and the central part of the North‒South Seismic Belt, stretching approximately 450 km along the north-northwest (NNW)‒south-southeast (SSE) strike direction and comprising several segments with distinct tectonic characteristics (Allen et al., \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1991\u003c/span\u003e; Wen et al., 1989, 2000). The Moxi Fault, which is the southeastern segment of the Xianshuihe Fault Zone, extends from Kangding to Shimian with a relatively simple geometric configuration and is a major seismogenic fault in the southeastern part of the Qinghai‒Tibet Plateau (Sichuan Bureau of Geology and Mineral Resources, 1982; Tang et al., 1983; Shi et al., \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e1992\u003c/span\u003e; Liu et al., 1993; Xu et al., 2005; Ai et al., 2019; Ma et al., 2020). The fault is dominated by left-lateral strike-slip motion with a minor vertical slip component, and its activity is closely related to distal stress transmission from the northeastward subduction of the Indian Plate beneath the Eurasian Plate (Ma et al., 2020; Yi et al., 2023).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2 Topography and Geomorphology\u003c/h2\u003e \u003cp\u003eThe study area is located in the mid\u0026ndash;low mountain area of western Sichuan, a transitional zone between the Qinghai‒Tibet Plateau and the Chengdu Plain, with well-developed river valleys and gullies.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe topography is characterized by mountain dominance interspersed with valley plains, thereby sloping from the high northwest to the low southeast. The elevation ranges from ~\u0026thinsp;1870 m (Moxi River valley, the lowest point) to ~\u0026thinsp;3500 m (Qipengzi Ridge, the highest point), with a relative elevation difference of ~\u0026thinsp;1630 m. Valley plains are formed primarily via fluvial erosion\u0026ndash;accumulation processes, and the macroscopic geomorphic features are significantly controlled by the tectonic activity of the Moxi Fault (Zhao et al., 2008; Chen et al., 2011).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.3 Quaternary Deposits\u003c/h2\u003e \u003cp\u003eQuaternary deposits in the study area are notably influenced by glacial\u0026ndash;interglacial climate changes and exhibit distinct vertical and horizontal zonation features (Li et al., 1991; Lu \u0026amp; Zhong, 1996). From high-altitude areas to the Dadu River valley, the deposits are dominated by moraines, glaciofluvial deposits, and alluvial‒diluvial deposits with varying thicknesses. Glaciofluvial deposits (thickness: ~100 m) are widely distributed across the Moxi Platform; these deposits comprise well-bedded gravel and sand layers and serve as important carriers for recording fault displacement (Chen et al., 2011). In the study area, the shallow surface is covered by heterogeneous boulder soil (pluvial\u0026ndash;alluvial origin) and terrace fine sand\u0026ndash;silt deposits, with thicknesses ranging from 5 to 25 m, thereby forming a thick overburden layer that obscures shallow fault traces (Zhao et al., 2008).\u003c/p\u003e \u003c/div\u003e"},{"header":"3. Geological and Geomorphic Survey Observations","content":"\u003cp\u003eHigh-resolution unmanned aerial vehicle (UAV) remote sensing interpretation (spatial resolution: 0.1 m) and field seismogeological tracing surveys were conducted to identify the macroscopic distribution, geometric configuration, and kinematic characteristics of the Moxi Fault. UAV remote sensing data were processed to generate digital elevation models (DEMs) and orthophoto maps, which were used to interpret microgeomorphic features related to fault activity (e.g., fault troughs, slope breaks, displaced gullies, and sag ponds). Field surveys were conducted, thereby focusing on verifying remote sensing interpretations, measuring fault displacement, and collecting samples for geochronological dating, with a particular focus on Yuejinping and Buziba village, which are key areas with well-preserved fault-related geomorphic features.\u003c/p\u003e \u003cp\u003eThe Moxi Fault cuts obliquely through the hillside from north to south in the Yuejinping area, thereby forming a fault trough valley with a length of ~\u0026thinsp;350 m and a width of 30\u0026ndash;50 m. This area encompasses an alluvial platform formed from the late Pleistocene to the early Holocene, and trench excavation by Chen et al. (2011) confirmed that the surface rupture of the 1786 Kangding earthquake passed through this site, resulting in a cumulative displacement of 36 m. Although surface rupture features are obscured by anthropogenic modification, well-preserved fault sag ponds can still be identified. Field measurements and remote sensing model analysis revealed a 39.5\u0026thinsp;\u0026plusmn;\u0026thinsp;0.5 m left-lateral displacement of a long abandoned gully on the platform surface, representing the cumulative strike-slip displacement of the Moxi Fault since the formation of the platform (Chen et al., 2011).\u003c/p\u003e \u003cp\u003eBuziba village is located on the northern side of the Moxi Platform and is covered by Moxi River terrace deposits (bedded fine sand and silt). High-resolution UAV remote sensing and field surveys revealed clear 3 m-high slope breaks in the Buziba area, which result from the vertical slip component of the Moxi Fault, and the fault was observed to cut through the terrace deposits from north to south with obvious tectonic geomorphic features.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eTrench excavation was conducted in Buziba, which revealed that colluvial wedges formed because of seismic activity. In addition, several small faults offset the ground surface. The \u0026sup1;⁴C ages of the glacial deposits at the bottom ranged from 6379 to 7856\u0026nbsp;year BP, which are generally consistent with the results (7420\u0026thinsp;\u0026plusmn;\u0026thinsp;90 to 7430\u0026thinsp;\u0026plusmn;\u0026thinsp;300\u0026nbsp;year BP) reported by Li et al. (1991). A radiocarbon (\u0026sup1;⁴C) age of 732\u0026thinsp;\u0026plusmn;\u0026thinsp;30\u0026nbsp;year BP was obtained from layer U2, which is essentially consistent with the age of 1490\u0026thinsp;\u0026plusmn;\u0026thinsp;70\u0026nbsp;year BP reported by Wen et al. (2001). On the basis of the dating data, the middle\u0026ndash;late Holocene was identified as the active period of the Moxi Fault.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe left-lateral displacement of the abandoned gully in Yuejinping and the vertical slope break in Buziba directly confirm the left-lateral strike-slip nature of the vertical slip component of the Moxi Fault, which is consistent with the results of previous regional studies (Chen et al., 2011; Ma et al., 2020). The cumulative left-lateral displacement of 39.5\u0026thinsp;\u0026plusmn;\u0026thinsp;0.5 m is the most refined quantitative geomorphic displacement value for the Moxi Fault to date, which provides a key basis for calculating the slip rate of the fault combined with geochronological dating.\u003c/p\u003e"},{"header":"4. Geophysical Exploration Methods and Optimization","content":"\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003e4.1 Geophysical Methods and Instrument Configuration\u003c/h2\u003e \u003cp\u003eFour geophysical methods were selected on the basis of the geological and topographic characteristics of the study area, with instrument configurations following mature technical specifications.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eInstrument configuration and optimized parameters of geophysical exploration methods\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMethod\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eInstrument Configuration\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eOptimized Sampling Spacing\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eDetection Depth\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eUncertainty Range\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eParameter Optimization Basis\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eShallow seismic\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSeismic source: hammer; geophone: 40-Hz vertical geophone; recorder: DZQ-8B seismograph\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5 m\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0\u0026ndash;300 m\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026plusmn;\u0026thinsp;1\u0026ndash;5 m\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eDZ/T 0370\u0026ndash;2021; adjusted for thick boulder soil overburden\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHigh-density electrical\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eElectrode array: Wenner\u0026ndash;Schlumberger; recorder: E60D electrical prospecting instrument\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5 m\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0\u0026ndash;200 m\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026plusmn;\u0026thinsp;2 m\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eDZ/T 0370\u0026ndash;2021; optimized for fluid-filled fracture zones\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMicrotremor\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSeismograph: Summit X One (Germany); geophone: SN4-2 Hz low-frequency geophone\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10 m\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0\u0026ndash;250 m\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026plusmn;\u0026thinsp;2\u0026ndash;3 m\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eField tests (5/10/20 m): a 10-m spacing balances resolution and depth; a 5-m spacing causes data redundancy\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGPR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMain unit: LTD-2600 (CETC); antenna: 100 MHz\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e20 cm\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0\u0026ndash;30 m\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026plusmn;\u0026thinsp;0.5 m\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eField tests (10/20/50 cm): a 20-cm spacing captures shallow fault displacement; a 50-cm spacing causes the loss of fine structures\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003e4.2 Parameter Optimization for Complex Terrains\u003c/h2\u003e \u003cp\u003eTo adapt to the complex geological conditions of the high mountain\u0026ndash;gorge region with thick overburden, the sampling point spacing of microtremor exploration and GPR surveys was optimized through field comparative tests (from large to small spacings) to balance detection accuracy and efficiency. Notably, experimental design principles (e.g., controlled variable tests, gradient spacing settings, and sample size justification) were strictly followed to ensure the robustness of optimization results, as detailed in the Methods section.\u003c/p\u003e \u003cp\u003e① Microtremor exploration: Comparative tests with spacings of 5, 10, and 20 m were conducted to quantify the trade-off between data redundancy, anomaly resolution, and field efficiency. A 5-m spacing generated redundant data with low information efficiency, as closely spaced points added limited new structural details while doubling the field workload. A 20-m spacing resulted in the loss of key fault anomaly details, particularly subtle step-like variations in fault zone geometry, due to undersampling of the subsurface structural gradient. In contrast, a 10-m spacing accurately captured deep fault anomalies (e.g., low-velocity zone boundaries) while maintaining acceptable field work efficiency (\u0026asymp;\u0026thinsp;8 km of survey lines per day). Hence, a spacing of 10 m was adopted for formal microtremor surveys, as this spacing achieved the optimal balance between resolution and efficiency required for characterizing fault structures in thick overburden.\u003c/p\u003e \u003cp\u003e② GPR: Comparative tests with spacings of 10, 20, and 50 cm were performed to optimize shallow subsurface imaging. A 50-cm spacing caused an excessive data volume (\u0026asymp;\u0026thinsp;5 GB per 100 m of profile) and slow field acquisition, leading to logistical inefficiencies and increased processing costs. A 20-cm spacing failed to resolve shallow fine fault features (e.g., sub-centimeter scale stratum offsets), as the sampling interval exceeded the vertical resolution limit of GPR for shallow deposits. A 20-cm spacing achieved centimeter-level resolution for shallow stratum displacement and accurately revealed fault breakpoints, enabling clear identification of fault zone architecture and secondary fractures. Hence, a spacing of 20 cm was selected for formal GPR surveys, as this spacing provided the necessary detail to characterize shallow fault structures in mountain\u0026ndash;gorge regions while maintaining practical data acquisition and processing workflows.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003e4.3 Geophysical Profile Layout\u003c/h2\u003e \u003cp\u003eA total of 8 geophysical exploration profiles were deployed along the strike of the Moxi Fault, perpendicular to the fault strike, to ensure the effective detection of fault structural features.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eTo provide readers with key context for understanding the performance of the proposed integrated fault detection framework, three representative profiles (HT02, HT04, and HT07) fully covered by the four geophysical methods (shallow seismic reflection, high-density resistivity, microtremor exploration, and ground-penetrating radar) were selected for detailed analysis, with their specific characteristics described as follows:\u003c/p\u003e \u003cp\u003eProfile HT02 (northern part): This\u0026thinsp;~\u0026thinsp;1.2 km-long profile is located in the northern segment of the Moxi Fault, traversing a boulder soil area dominated by thick colluvial deposits and steep topography. It crosses a fault segment where surface ruptures are partially obscured by anthropogenic modification, making it ideal for testing the framework\u0026rsquo;s ability to detect buried fault structures in densely covered terrains.\u003c/p\u003e \u003cp\u003eProfile HT04 (central part): Extending\u0026thinsp;~\u0026thinsp;1.5 km in the central study area, this profile passes through a terrace fine sand\u0026ndash;silt area (a typical fluvial sedimentary environment with relatively flat topography). It intersects the fault at a location with evident vertical slip components, enabling evaluation of the framework\u0026rsquo;s capacity to resolve both strike-slip and dip-slip fault features.\u003c/p\u003e \u003cp\u003eProfile HT07 (southern part): Stretching\u0026thinsp;~\u0026thinsp;1.0 km in the southern segment, this profile cuts across a weathered granite area with exposed bedrock and thin overburden. It targets a fault segment where geomorphic markers (e.g., displaced gullies) are well-preserved, allowing for direct comparison between geophysical anomalies and field-observed fault traces.\u003c/p\u003e \u003cp\u003eCollectively, these three profiles cover distinct geological and geomorphic units, fully reflecting the adaptability of the integrated geophysical methods to complex mountain\u0026ndash;gorge terrains with thick overburden, and providing a comprehensive basis for evaluating the framework\u0026rsquo;s performance in fault detection.\u003c/p\u003e \u003c/div\u003e"},{"header":"5. Geophysical Interpretation Criteria and Results","content":"\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003e5.1 Unified Interpretation Criteria for Geophysical Methods\u003c/h2\u003e \u003cp\u003eTo ensure the objectivity and reproducibility of geophysical interpretation, clear and quantitative interpretation criteria were established for each method on the basis of the geological characteristics of the study area and the literature (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e), with all threshold values verified by field tests and presurveys.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eQuantitative interpretation criteria for fault identification with geophysical methods\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMethod\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCore Interpretation Criteria (Quantitative Thresholds)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLiterature Basis/Field Calibration\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eShallow seismic\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1. Discontinuity of stratigraphic reflection events; 2. amplitude decrease of \u0026gt;\u0026thinsp;30% in the fault zone; 3. dominant frequency reduction (80\u0026ndash;200 Hz \u0026rarr; 20\u0026ndash;80 Hz); 4. high-frequency component (\u0026gt;\u0026thinsp;150 Hz) attenuation of \u0026gt;\u0026thinsp;80%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eDZ/T 0370\u0026ndash;2021; Yuejinping Fault outcrop\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHigh-density electrical\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1. Linear low-resistivity anomaly zone; 2. abrupt resistivity change at the same depth; 3. discontinuity of the top high-resistivity layer of the bedrock\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eDZ/T 0370\u0026ndash;2021; Buziba area\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMicrotremor\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1. Linear low-apparent shear wave velocity anomaly zone; 2. dispersion curve inflection/discontinuity; 3. velocity gradient zone (width: 5\u0026ndash;15 m; velocity difference: 2\u0026ndash;3\u0026times; the normal area)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRein et al. (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2024\u003c/span\u003e); Qipengzi Ridge\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGPR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1. Vertical/horizontal displacement of reflected wave groups; 2. abrupt termination of continuous wave groups; 3. waveform distortion and energy attenuation (\u0026gt;\u0026thinsp;50%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eWang et al. (\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2024\u003c/span\u003e); shallow fault outcrop\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003e5.2 Geophysical Interpretation Results for the Representative Profiles\u003c/h2\u003e \u003cp\u003eThe raw geophysical data were processed using professional commercial software, with explicit parameter settings specified to ensure full reproducibility:\u003c/p\u003e \u003cp\u003eShallow seismic reflection data: Processed in Reflex-W using standard default workflows (band-pass filtering, static correction, normal moveout correction) with no specialized parameter adjustments, which is widely accepted for shallow seismic imaging in mountain-gorge regions with thick overburden.\u003c/p\u003e \u003cp\u003eHigh-density electrical resistivity data: Processed in Res2dinv with default robust inversion parameters (5% data error tolerance, L1-norm regularization), consistent with common practices for fault zone characterization in complex terrains.\u003c/p\u003e \u003cp\u003eMicrotremor data: Processed in Surfer using default kriging gridding and contouring parameters, which are standard for visualizing spatial variations in shear wave velocity ratios.\u003c/p\u003e \u003cp\u003eGround-penetrating radar (GPR) data: Processed in RADAN with default migration and automatic gain control settings, optimized for resolving shallow subsurface stratigraphic and fault-related features in thick overburden.\u003c/p\u003e \u003cp\u003eThe key objective observations of profiles HT02, HT04, and HT07 are summarized as follows (Figs.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e\u0026ndash;15):\u003c/p\u003e \u003cp\u003e① Profile HT02 (boulder soil overburden, 5\u0026ndash;10 m): No continuous seismic reflection interface is observed at depths of 0\u0026ndash;10 m; a linear low-resistivity anomaly (180\u0026ndash;250 Ω\u0026middot;m) is identified at depths of 140\u0026ndash;180 m, accompanied by a low-apparent shear wave velocity zone (200\u0026ndash;250 m/s) at the same depth range; a wedge-shaped chaotic GPR reflection is detected at 160 m.\u003c/p\u003e \u003cp\u003e② Profile HT04 (fine sand-silt overburden, 15\u0026ndash;25 m): A clear seismic reflection interruption is present at depths of 70\u0026ndash;80 m; a linear low-resistivity anomaly (200\u0026ndash;300 Ω\u0026middot;m) is observed at depths of 60\u0026ndash;90 m, corresponding to a low-apparent shear wave velocity zone (180\u0026ndash;220 m/s) at the same depth range; a vertical GPR wave group displacement of 1.5 m is identified at depths of 70\u0026ndash;80 m.\u003c/p\u003e \u003cp\u003e③ Profile HT07 (weathered granite overburden, 5\u0026ndash;15 m): A seismic reflection dislocation is detected at depths of 90\u0026ndash;110 m (bedrock layer); no obvious electrical anomaly is observed (only resistivity fluctuations of 300\u0026ndash;500 Ω\u0026middot;m); a low-apparent shear wave velocity zone (220\u0026ndash;250 m/s) is present at depths of 90\u0026ndash;110 m, coinciding with an abrupt termination of the GPR wave group at the same depth range.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003e5.3 Interpretation and Discussion of the Geophysical Results\u003c/h2\u003e \u003cp\u003eOn the basis of the objective observations and geological-geomorphic constraints, geophysical anomalies were interpreted as fault-related features. The complementary advantages of the four methods were evaluated by quantifying their resolution capabilities and uncertainty budgets, with the results summarized below:\u003c/p\u003e \u003cp\u003e① Profile HT02 (boulder soil overburden): Shallow seismic reflection failed to characterize the shallow fault structure due to strong velocity heterogeneity from boulder soil, introducing a positional uncertainty of \u0026plusmn;\u0026thinsp;5 m. In contrast, the high-density electrical method (resolution: \u0026plusmn;2 m) and GPR technology (resolution: \u0026plusmn;0.5 m) compensated for this deficiency by resolving the upper breakpoint and confirming its surface outcrop, providing precise spatial constraints on the fault\u0026rsquo;s shallow structure.\u003c/p\u003e \u003cp\u003e② Profile HT04 (fine sand-silt overburden): Microtremor exploration yielded ambiguous fault core positioning due to minimal stiffness contrasts between interbedded fine sand and silt layers, resulting in a positional uncertainty of \u0026plusmn;\u0026thinsp;3 m. The shallow seismic method (resolution: \u0026plusmn;1 m) accurately located the fault core and delivered quantitative displacement data, including a 1.5-m vertical GPR wave group displacement at 70\u0026ndash;80 m depth, which constrained the fault\u0026rsquo;s vertical slip component with sub-meter precision.\u003c/p\u003e \u003cp\u003e③ Profile HT07 (weathered granite overburden): The high-density electrical method failed to resolve the fault due to uneven weathering of the granite bedrock, which created resistivity fluctuations (300\u0026ndash;500 Ω\u0026middot;m) that masked the fault-related anomaly. Microtremor and shallow seismic exploration could only penetrate the shallow weathered layer (\u0026le;\u0026thinsp;15 m depth), but they confirmed the fault\u0026rsquo;s truncation of the deep bedrock at 90\u0026ndash;110 m depth, with a positional uncertainty of \u0026plusmn;\u0026thinsp;2 m for the bedrock-fault intersection.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003e5.4 Comprehensive Geophysical Characterization of the Moxi Fault\u003c/h2\u003e \u003cp\u003eOn the basis of multimethod complementary interpretation (detailed in Figs.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e\u0026ndash;15 and Table S1), the geometric characteristics of the Moxi Fault are summarized as follows:\u003c/p\u003e \u003cp\u003e \u003col\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eA. Fracture zone width: 50\u0026ndash;60 m (averaged from three representative profiles (HT02, HT04, and HT07); this range reflects lithological heterogeneity across the study area, as visualized in the geophysical cross-sections of Figs.\u0026nbsp;8, 11, and 14.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eB. Fault plane dip: Steep westward dipping, with an apparent dip angle of 75\u0026ndash;80\u0026deg; (consistent across all three profiles, as quantified by shallow seismic and microtremor velocity profiles in Figs.\u0026nbsp;7, 10, and 13).\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eC. Upper breakpoint: Outcrops at the surface (verified by GPR reflection profiles in all three study profiles, as illustrated in Figs.\u0026nbsp;9, 12, and 15).\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eD. Vertical connectivity: Cuts through shallow overburden and deep bedrock (confirmed by microtremor shear wave velocity and shallow seismic reflection data, as shown in Figs.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e\u0026ndash;7, 10\u0026ndash;11, and 13\u0026ndash;14). E. Spatial consistency: The geophysically inferred fault location is entirely consistent with the geomorphic fault location identified in Section \u003cspan refid=\"Sec6\" class=\"InternalRef\"\u003e3\u003c/span\u003e, with an overall absolute error of \u0026plusmn;\u0026thinsp;2\u0026ndash;5 m (quantified by comparing fault positions in geophysical profiles and UAV DEMs, as documented in Table S2).\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003c/ol\u003e \u003c/p\u003e \u003cp\u003eThe \u0026sup1;⁴C dating results for the glaciofluvial deposits in the study area (6379\u0026thinsp;\u0026plusmn;\u0026thinsp;120 to 7856\u0026thinsp;\u0026plusmn;\u0026thinsp;40\u0026nbsp;year BP) are essentially consistent with the \u0026sup1;⁴C ages (7420\u0026thinsp;\u0026plusmn;\u0026thinsp;90 to 7430\u0026thinsp;\u0026plusmn;\u0026thinsp;300\u0026nbsp;year BP) reported by Li et al. (1991). Combined with dating data from layer U2 (732\u0026thinsp;\u0026plusmn;\u0026thinsp;30\u0026nbsp;year BP), these results constrain the active period of the Moxi Fault to the middle\u0026ndash;late Holocene, as visualized in the trench stratigraphy and dating plot (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e"},{"header":"6. Geochemical Exploration: Methods, Results and Verification","content":"\u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003e6.1 Soil Gas Sampling and Measurement Methods\u003c/h2\u003e \u003cp\u003eIn this study, soil gas was measured along the three geophysical profiles (HT02, HT04, HT07) to provide independent geochemical validation for the geophysically inferred fault location, with sampling points aligned with geophysical survey points to ensure spatial comparability. The instrument configuration, calibration protocols, and sampling parameters are summarized in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e.\u003c/p\u003e \u003cp\u003eRadon (Rn) measurement: A RAD7 radon detector was employed for Rn concentration measurements. Daily calibration was performed using a \u0026sup2;\u0026sup2;⁶Ra standard source (100\u0026thinsp;\u0026plusmn;\u0026thinsp;5 Bq) to ensure measurement stability, and zero drift correction was implemented every 50 consecutive sampling points to mitigate instrumental drift. This calibration regime resulted in a quantitative measurement error of \u0026plusmn;\u0026thinsp;5% for Rn concentrations. Sampling was conducted at 5-m intervals along all three profiles to maintain consistent spatial resolution with geophysical surveys.\u003c/p\u003e \u003cp\u003eCarbon dioxide (CO₂) measurement: An LI-840A infrared gas analyzer was used to measure CO₂ concentrations. Weekly calibration was carried out using three standard CO₂ gas mixtures (0 ppm, 5000 ppm, and 10000 ppm) to establish a linear response curve, and the linear error was controlled to \u0026lt;\u0026thinsp;2% throughout the measurement period. This calibration workflow yielded a measurement error of \u0026plusmn;\u0026thinsp;2% for CO₂ concentrations. Sampling was performed at 5-m intervals, matching the spacing of Rn sampling to ensure spatial consistency across all soil gas datasets.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eInstrument configuration, calibration and sampling parameters of geochemical exploration\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIndex\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eInstrument Model\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCalibration Procedure\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSampling Spacing\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eMeasurement Error\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRn\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRAD7 radon detector\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eDaily calibration with a \u0026sup2;\u0026sup2;⁶Ra standard source (100\u0026thinsp;\u0026plusmn;\u0026thinsp;5 Bq); zero drift correction every 50 points\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5 m\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026plusmn;\u0026thinsp;5%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCO₂\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLI-840A infrared analyzer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eWeekly calibration with 0/5000/10000 ppm standard CO₂ gas; linear error\u0026thinsp;\u0026lt;\u0026thinsp;2%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5 m\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026plusmn;\u0026thinsp;2%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec18\" class=\"Section2\"\u003e \u003ch2\u003e6.2 Soil Gas Geochemical Anomaly Characteristics\u003c/h2\u003e \u003cp\u003eSoil gas CO₂ and Rn were measured along profiles HT02, HT04 and HT07, with background values calculated as the 95% confidence intervals of nonanomaly points. The quantitative geochemical anomaly characteristics are listed in Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e and shown in Figs.\u0026nbsp;7\u0026ndash;8.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eQuantitative geochemical anomaly characteristics of the three profiles\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eProfile\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCO₂ Background Value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCO₂ Anomaly Range\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCO₂ Peak Value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eRn Background Value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eRn Anomaly Range\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eRn Peak Value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHT02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e500\u0026ndash;1000 ppm\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e140\u0026ndash;180 m\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e20000 ppm\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5\u0026ndash;10 Bq/L\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e140\u0026ndash;180 m\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e20 Bq/L\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHT04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e500\u0026ndash;1000 ppm\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e60\u0026ndash;90 m\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e25000 ppm\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5\u0026ndash;10 Bq/L\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e70\u0026ndash;80 m\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e18 Bq/L\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHT07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e500\u0026ndash;1000 ppm\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e90\u0026ndash;110 m\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e18000 ppm\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5\u0026ndash;10 Bq/L\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e90\u0026ndash;120 m\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e15 Bq/L\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003e6.3 Mechanistic Interpretation of Geochemical Anomalies\u003c/b\u003e \u003c/p\u003e\u003cp\u003eA. Profile HT02: The fault fracture zone is a fluid-filled high-permeability zone (pore water saturation: 60\u0026ndash;70%), with complete overlap of CO₂ and Rn anomalies across the 140\u0026ndash;180 m segment. Building on these observations and previous studies of deep fluid migration along active faults (e.g., Xu et al., \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Li et al., 2020), we infer that Rn (produced by radioactive decay of deep bedrock elements; Shen et al., 2018) and CO₂ (derived from deep crustal fluid sources; Wang et al., 2019) migrate upward along the fault channel and accumulate at the surface. This complete anomaly overlap confirms that the fault acts as a core fluid release window, consistent with our geophysical evidence of deep-shallow fault connectivity.\u003c/p\u003e \u003cp\u003eB. Profile HT04: The fault fracture zone exhibits high porosity (30\u0026ndash;40%) favorable for gas accumulation, with the highest CO₂ peak (25000 ppm) among all profiles; CO₂ anomalies span a 30 m-wide zone, while Rn anomalies are concentrated in the fault core (70\u0026ndash;80 m), resulting in partial anomaly overlap. Combining established differences in gas diffusion properties (Rn has lower diffusivity than CO₂ in porous media; Zhang et al., 2021), we speculate that the partial overlap arises from preferential trapping of Rn in the high-porosity fault core, while CO₂ diffuses more broadly into the surrounding fine sand-silt layer.\u003c/p\u003e \u003cp\u003eC. Profile HT07: Located on the Qipengzi Ridge (a dry fracture zone with limited groundwater, confirmed by field surveys), CO₂ shows the lowest peak value (18000 ppm) and rapid diffusion, while Rn exhibits a larger anomaly range; core anomaly overlap is observed at 90\u0026ndash;110 m. Consistent with gas diffusion behavior in arid, low-moisture environments (Liu et al., 2022), the rapid diffusion of CO₂ and relatively extensive diffusion of Rn lead to core anomaly overlap. This observation confirms the fault\u0026rsquo;s fluid release function even in arid, low-groundwater conditions, aligning with our geophysical detection of fault continuity through bedrock.\u003c/p\u003e \u003cp\u003eOverall, the variable anomaly overlap patterns across the three profiles reflect differences in fault zone permeability, lithology, and hydrological conditions, and collectively validate the fault\u0026rsquo;s role as a deep fluid conduit\u0026mdash;providing independent geochemical support for our integrated geophysical characterization of the Moxi Fault.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec19\" class=\"Section2\"\u003e \u003ch2\u003e6.4 Geochemical Validation and Alternative Explanation\u003c/h2\u003e \u003cp\u003eThis subsection aimed to validate the spatial coupling between soil gas geochemical anomalies and the geophysically identified Moxi Fault zones, and to rule out non-tectonic alternative explanations by providing independent geochemical evidence for the fault\u0026rsquo;s role as a deep fluid release window.\u003c/p\u003e \u003cp\u003eSoil gas CO₂ and Rn were measured along three representative profiles (HT02, HT04, HT07), with sampling points aligned to geophysical survey sites to ensure spatial comparability. Geochemical anomaly intervals and core positions were compared against geophysical anomaly zones (shallow seismic dislocation, high-density electrical low-resistivity zone, microtremor low-wave velocity zone, and GPR wave group displacement). Three potential non-tectonic alternative explanations (carbonate dissolution, seasonal variability, anthropogenic activity) were systematically evaluated and ruled out (Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e), following established protocols for geochemical fault tracing (e.g., Xu et al., \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Liu et al., 2022).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eAlternative explanations for the geochemical anomalies and ruling basis\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"2\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAlternative Explanation\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRuling Basis\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCarbonate dissolution\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo carbonate outcrops in the study area; dissolution CO₂ exhibits a δ\u0026sup1;\u0026sup3;C value close to +\u0026thinsp;0\u0026permil;~+5\u0026permil;\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSeasonal variability\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSampling was completed during the same season (autumn 2023); no rainfall occurred during sampling\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAnthropogenic activity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSampling points are located far from human settlements (\u0026gt;\u0026thinsp;500 m); no agricultural/industrial activity occurs in the area\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eAll three geochemical profiles exhibited high spatial coincidence between soil CO₂-Rn anomalies and geophysically identified fault zones, with anomaly intervals and core positions consistent with geophysical anomaly zones (shallow seismic dislocation, high-density low electrical resistivity, microtremor low wave velocity, and GPR wave group displacement). This spatial coupling verifies that the geophysically inferred anomaly zones constitute the active fracture zones of the Moxi Fault and confirms that the fault functions as a deep fluid release window. Notably, fault structural activity yields interconnected fracture networks that serve as migration channels for deep crust-mantle fluids (CO₂ and Rn; Wang et al., 2019), causing the concentrated enrichment of these gases in the surface soil above the fault zone and the formation of detectable geochemical anomalies.\u003c/p\u003e \u003cp\u003eAlternative explanations for geochemical anomalies were ruled out (Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e), confirming that the anomalies are related to the fault rather than other factors:\u003c/p\u003e \u003cp\u003eNo carbonate outcrops exist in the study area; dissolution-derived CO₂ exhibits a δ\u0026sup1;\u0026sup3;C value close to 0\u0026permil; (\u0026plusmn;\u0026thinsp;3\u0026permil;; Li et al., 2023), which was not observed in our samples; sampling was completed during the same season (autumn 2023); no rainfall occurred during sampling (\u0026lt;\u0026thinsp;5 mm), eliminating hydrological fluctuations that could alter gas concentrations; and sampling points were located\u0026thinsp;\u0026gt;\u0026thinsp;500 m from human settlements, with no agricultural or industrial activity in the area, excluding anthropogenic gas sources.\u003c/p\u003e \u003cp\u003eThe geochemical results also demonstrated the applicability of soil CO₂/Rn measurements for hidden fault tracing in high mountain\u0026ndash;gorge regions with thick overburden (Xu et al., \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Notably, even when shallow fault traces are obscured by heterogeneous overburden, soil gas geochemistry can effectively reveal fault locations by capturing deep fluid release signals, thus providing a reliable geochemical verification method for geophysical detection results.\u003c/p\u003e \u003c/div\u003e"},{"header":"7. Comprehensive Discussion","content":"\u003cdiv id=\"Sec21\" class=\"Section2\"\u003e \u003ch2\u003e7.1 Integrated Detection Framework for Active Faults in Complex Terrains\u003c/h2\u003e \u003cp\u003eThis study addresses the technical bottlenecks associated with the detection of active faults in high mountain\u003cb\u003e\u0026ndash;\u003c/b\u003egorge regions with thick overburden by integrating geological\u0026ndash;geomorphic surveys, optimized multimethod geophysics, and soil gas geochemistry and provides a deep\u0026ndash;shallow coupling and geochemical verification integrated detection framework.\u003c/p\u003e \u003cp\u003eThe core of this framework is method complementarity and parameter optimization:\u003c/p\u003e \u003cp\u003e① Geological\u0026ndash;geomorphic surveys (UAV\u0026thinsp;+\u0026thinsp;field tracing): These surveys provide the macroscopic fault distribution and kinematic characteristics and can be used to determine the layout of geophysical and geochemical profiles;\u003c/p\u003e \u003cp\u003e② Deep geophysical detection (shallow seismic\u0026thinsp;+\u0026thinsp;10 m-spacing microtremor exploration): The deep fault structure (dip angle, fracture zone width, and vertical connectivity) can be characterized, and the shallow heterogeneous overburden is penetrated;\u003c/p\u003e \u003cp\u003e③ Shallow geophysical detection (high-density electrical\u0026thinsp;+\u0026thinsp;20 cm-spacing GPR surveys): Shallow fault breakpoints and surface displacement features can be identified, thereby compensating for the deficiency of deep detection in shallow fault characterization;\u003c/p\u003e \u003cp\u003e④ Soil gas geochemistry (5 m-spacing CO₂/Rn measurements): Geophysically identified fault zones can be verified, the fluid release characteristics of the fault can be characterized, and multiple solutions for geophysical interpretation can be circumvented.\u003c/p\u003e \u003cp\u003eThis framework overcomes the inherent limitations of single detection methods and increases the resolution and reliability of active fault characterization in complex terrains. The optimized parameters (10-m microtremor spacing, 20-cm GPR spacing, and 5 m soil gas spacing) are suitable for high mountain\u003cb\u003e\u0026ndash;\u003c/b\u003egorge regions with thick overburden and can be adjusted according to the specific geological conditions of various study areas, thereby providing a reproducible technical reference for active fault investigations in tectonically similar regions with complex topography and thick overburden.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec22\" class=\"Section2\"\u003e \u003ch2\u003e7.2 Late Quaternary Activity Parameters of the Moxi Fault: Slip Rate and Active Period\u003c/h2\u003e \u003cdiv id=\"Sec23\" class=\"Section3\"\u003e \u003ch2\u003e7.2.1 Calculation of the Late Holocene Slip Rate\u003c/h2\u003e \u003cp\u003eThe late Holocene slip rate of the Moxi Fault can be calculated on the basis of the cumulative left-lateral displacement (39.5\u0026thinsp;\u0026plusmn;\u0026thinsp;0.5 m) measured in the Yuejinping area and the \u0026sup1;⁴C dating results (6379\u0026thinsp;\u0026plusmn;\u0026thinsp;120 to 7856\u0026thinsp;\u0026plusmn;\u0026thinsp;40\u0026nbsp;year BP) for the glaciofluvial deposits hosting the displaced gully. The \u0026sup1;⁴C dating results are consistent with the \u0026sup1;⁴C ages of glaciofluvial deposits in the study area obtained by Li et al. (1991) (7420\u0026thinsp;\u0026plusmn;\u0026thinsp;90 to 7430\u0026thinsp;\u0026plusmn;\u0026thinsp;300\u0026nbsp;year BP), thus verifying the reliability of the age constraints.\u003c/p\u003e \u003cp\u003eThe calculated late Holocene slip rate of the Moxi Fault is 5.3\u0026thinsp;\u0026plusmn;\u0026thinsp;0.2 mm/yr, which is consistent with the overall slip rate of the Xianshuihe Fault Zone (4\u0026ndash;6 mm/yr) reported in previous studies (Wen, 2000; Bai et al., \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). This consistency verifies that the Moxi Fault is a tectonically consistent segment of the Xianshuihe Fault Zone and that its activity is controlled by the regional tectonic stress field.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec24\" class=\"Section3\"\u003e \u003ch2\u003e7.2.2 Constraints on the Active Period\u003c/h2\u003e \u003cp\u003eCombined with our in-situ \u0026sup1;⁴C dating results (6379\u0026thinsp;\u0026plusmn;\u0026thinsp;120 to 7856\u0026thinsp;\u0026plusmn;\u0026thinsp;40\u0026nbsp;year BP) and the geomorphic characteristics of the displaced gully (formed during the middle\u0026ndash;late Holocene), we constrain the active period of the Moxi Fault to the middle\u0026ndash;late Holocene (since ~\u0026thinsp;7856\u0026nbsp;year BP). This result refines the previous constraint of the latest occurrence of intense fault activity to the middle Holocene (Chen et al., 2011), providing a more precise time scale for regional tectonic evolution and paleoseismic reconstruction. Summary: By narrowing the active period to ~\u0026thinsp;7.8 ka, this study improves the temporal resolution of Moxi Fault activity, enabling more accurate assessments of long-term seismic hazard and regional tectonic processes.\u003c/p\u003e \u003cp\u003eThe positive correlation between the calculated slip rate (5.3\u0026thinsp;\u0026plusmn;\u0026thinsp;0.2 mm/yr) and the fracture zone width (50\u0026ndash;60 m) of the Moxi Fault aligns with the empirical relationship between the slip rate and fracture zone width for active strike-slip faults proposed by Allen et al. (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1991\u003c/span\u003e). This alignment verifies the applicability of this empirical relationship to the Moxi Fault and the Xianshuihe Fault Zone under the tectonic conditions of the southeastern Qinghai\u0026ndash;Tibet Plateau. Summary: This validation of the slip rate-fracture width relationship in a high mountain-gorge setting extends the empirical framework to complex terrains, offering a valuable reference for characterizing active strike-slip faults in similar tectonic settings globally.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec25\" class=\"Section2\"\u003e \u003ch2\u003e7.3 Tectonic Significance: Fault Occurrence and Regional Stress Field Coupling\u003c/h2\u003e \u003cp\u003eThe Moxi fault exhibits a steep westward dip angle of 75\u0026ndash;80\u0026deg;, which is consistent with the NE\u0026ndash;SW-trending principal compressive stress field in the southeastern part of the Qinghai‒Tibet Plateau (horizontal stress: 8\u0026ndash;12 MPa) observed by regional global positioning system (GPS) measurements (Ma et al., 2020). According to the Coulomb failure criterion, the optimal dip angle range for left-lateral strike-slip faults under horizontal principal compressive stress is 70\u0026ndash;85\u0026deg;, and the dip angle of the Moxi Fault occurs exactly within this range, which indicates that its occurrence and geometric characteristics are the product of distal stress transmission from the northeastward subduction of the Indian Plate beneath the Eurasian Plate.\u003c/p\u003e \u003cp\u003eThese results supplement the evidence for the chain of plate collision \u0026rarr; regional stress field \u0026rarr; fault occurrence and activity in the southeastern part of the Qinghai‒Tibet Plateau and verify that the active strike-slip faults in this area constitute the primary tectonic response to the Indo\u0026ndash;Eurasian collision. The high dip angle of the Moxi Fault also suggests that the fault exhibits a large seismogenic depth and the potential to generate strong earthquakes, providing an important tectonic basis for regional seismic hazard assessment.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec26\" class=\"Section2\"\u003e \u003ch2\u003e7.4 Limitations and Prospects\u003c/h2\u003e \u003cp\u003eThis study presents an effective integrated detection framework for active faults in high mountain\u003cb\u003e\u0026ndash;\u003c/b\u003egorge regions with thick overburden but exhibits the following two main limitations: (1) the geochemical analysis focuses only on soil CO₂ and Rn, with no analysis of other trace gases (e.g., He and CH₄) that can further constrain fluid sources; (2) the slip rate calculation is based on geomorphic displacement and \u0026sup1;⁴C dating.\u003c/p\u003e \u003cp\u003eFuture research should aim to (1) expand the scope of geochemical analysis to include multiple trace gases and isotopes (e.g., \u0026sup3;He/⁴He) to accurately constrain the source and migration pathway of deep fluids and (2) apply the integrated detection framework to more active fault segments in the Xianshuihe Fault Zone to establish a regional active fault parameter database and improve the scientific basis for seismic hazard assessment in the southeastern part of the Qinghai‒Tibet Plateau.\u003c/p\u003e \u003c/div\u003e"},{"header":"8. Conclusions","content":"\u003cp\u003eThis study establishes an integrated detection framework that combines geological-geomorphic surveys, optimized multi-method geophysics, and soil gas geochemistry to characterize the Moxi Fault\u0026mdash;the seismogenic fault of the 2022 Ms 6.8 earthquake in the southeastern Qinghai\u0026ndash;Tibet Plateau\u0026mdash;overcoming key technical barriers to active fault detection in high mountain\u0026ndash;gorge terrains with thick overburden. The core findings are summarized as follows:\u003c/p\u003e\u003cp\u003eA. Geometric and kinematic characteristics: The Moxi Fault is a steep west-dipping (apparent dip: 75\u0026ndash;80\u0026deg;) left-lateral strike-slip fault with a 50\u0026ndash;60 m-wide fracture zone and a surface-exposed upper breakpoint. Field measurements reveal a 39.5\u0026thinsp;\u0026plusmn;\u0026thinsp;0.5 m left-lateral displacement and ~\u0026thinsp;3 m vertical relief, confirming its dominant left-lateral strike-slip nature with a minor vertical slip component.\u003c/p\u003e \u003cp\u003eB. Optimized geophysical detection system: A complementary geophysical system (shallow seismic surveys, high-density electrical method, 10-m spacing microtremor surveys, 20-cm spacing GPR surveys) is established with quantitative interpretation criteria. This system enables deep-shallow coupling characterization: shallow seismic and microtremor exploration excel at deep fault detection, while high-density electrical methods and GPR can effectively identify shallow breakpoints.\u003c/p\u003e \u003cp\u003eC. Geochemical verification of fault activity: Three 5-m spacing soil CO₂/Rn profiles show high spatial coincidence between geochemical anomalies and geophysically identified fault zones, verifying that the fault acts as a deep fluid release window. High-concentration CO₂ anomalies indicate deep fluid release, demonstrating the applicability of soil CO₂/Rn measurements for hidden fault tracing in thick overburden terrains.\u003c/p\u003e \u003cp\u003eD. Late Quaternary activity parameters: On the basis of \u0026sup1;⁴C dating (6379\u0026thinsp;\u0026plusmn;\u0026thinsp;120 to 7856\u0026thinsp;\u0026plusmn;\u0026thinsp;40\u0026nbsp;year BP) and geomorphic displacement, the fault\u0026rsquo;s active period is constrained to the middle\u0026ndash;late Holocene, with a late Holocene slip rate of 5.3\u0026thinsp;\u0026plusmn;\u0026thinsp;0.2 mm/yr. This rate aligns with the Xianshuihe Fault Zone\u0026rsquo;s regional slip rate (4\u0026ndash;6 mm/yr) and validates the empirical slip rate-fracture zone width relationship (Allen et al., \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1991\u003c/span\u003e) in the study area.\u003c/p\u003e \u003cp\u003eE. Tectonic significance: The 75\u0026ndash;80\u0026deg; west dip angle is consistent with the NE\u0026ndash;SW principal compressive stress field in the southeastern Qinghai\u0026ndash;Tibet Plateau, confirming that fault occurrence and activity are driven by the northeastward subduction of the Indian Plate beneath the Eurasian Plate. These results strengthen evidence for the coupled plate collision\u0026ndash;regional stress field\u0026ndash;fault response chain in the eastern Tibetan Plateau.\u003c/p\u003e\u003cp\u003eBeyond these site-specific findings, the integrated deep-shallow coupling and geochemical verification framework provide high-precision tectonic data for the Moxi Fault, directly supporting post-disaster reconstruction and seismic risk assessment in the 2022 Ms 6.8 earthquake epicenter area. More broadly, this framework offers a transferable technical reference for active fault investigations in tectonically similar regions worldwide\u0026mdash;characterized by complex topography and thick surface deposits\u0026mdash;filling a critical methodological gap in high mountain\u0026ndash;gorge terrain fault detection. Future work could expand this framework to incorporate multi-isotope geochemical tracing and apply it to additional segments of the Xianshuihe Fault Zone to refine regional seismic hazard models.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e \u003ch2\u003eConflict of Interest:\u003c/h2\u003e \u003cp\u003eThe authors declare that they have no conflicts of interest.\u003c/p\u003e \u003c/p\u003e\u003ch2\u003eFunding:\u003c/h2\u003e \u003cp\u003eThis work was supported by the Science and Technology Innovation Projects of the Sichuan Provincial Bureau of Geology and Mineral Resources Exploration and Development (Nos. SCDKZCKJXM-2021063 and SCDZ-KJXM202402).\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eChao Tan was primarily responsible for the overall text editing and conceptual organization of the manuscript.Ye Kuang is Corresponding authors, and Ruiqing Xiao conducted geophysical surveys and relevant research.Xiujun Dong undertook the revision and critical review of the paper.Kejia Wei performed field investigations pertaining to geochemical studies.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAllen, C. R., Luo, Z., Qian, H., Wen, X., Zhou, H., \u0026amp; Huang, W. (1991). Field study of a highly active fault zone: The XSF of southwestern China. Geological Society of America Bulletin, 103, 1178\u0026ndash;1199.\u003c/li\u003e\n\u003cli\u003eAi Y F, Zhang J.Geophysical analysis on the tectonic difference between northern and southern segmengts of xianshuihe fault zone[J].Acta seismologica sinica,41(3):329-342.\u003c/li\u003e\n\u003cli\u003eBekaert D V, Turner S J, Broadley M W, Barnes J D, Halld\u0026oacute;rsson S A, Labidi J, Wade J, Walowski K J, Barry P H. 2021. Subduction-driven volatile recycling: A global mass balance. Annu Rev Earth Planet Sci, 49: 37\u0026ndash;70\u003c/li\u003e\n\u003cli\u003eBai, M., Chevalier, M.-L., Leloup, P. H., Li, H., Pan, J., Replumaz, A., et al. (2021). Spatial slip rate distribution along the SE Xianshuihe fault, eastern Tibet, and earthquake hazard assessment. Tectonics, 40, e2021TC006985. https://doi. org/10.1029/2021TC006985\u003c/li\u003e\n\u003cli\u003eDeng, Q., Zhang, P., Ran, Y., Yang, X., Min, W., \u0026amp; Chu, Q. (2003). Basic characteristics of active tectonics of China. Science in China, 46, 356\u0026ndash;372. https://doi.org/10.1360/03ys9030\u003c/li\u003e\n\u003cli\u003eDeepak M. Maurya https://orcid.org/0000-0001-6236-0093 Mohamedharoon A. Shaikh https://orcid.org/0000-0002-5886-3007 Atul K. Patidar https://orcid.org/0000-0001-7203-0063\u003c/li\u003e\n\u003cli\u003eHe M X,Fang H,Wang X B, et al.2017.Deep conductivity characteristics of the southern xianshuihe fault zone[J].Chinese journal of geophysics, 60（6）:2414-2424.\u003c/li\u003e\n\u003cli\u003eLuo Y, Wang Y (2013) Topographic amplification effect of Wenchuan earthquake induced mountain slope vibration. Mountain Res 2:11\u003c/li\u003e\n\u003cli\u003eLi C L,Gao M T,Xu W J, et al.2016.Influence of strong earthquakes on the occurrence rate of major earthquakes and applications on xianshuihe fault. [J].Chinese journal of geophysics, 59(8):2833-2842.\u003c/li\u003e\n\u003cli\u003eLee C T, Jiang H, Dasgupta R, Torres M. 2019. A framework for understanding whole-Earth carbon cycling. In:Orcutt B N, Daniel I, Dasgupta R, eds. Deep Carbon: Past to Present. Cambridge: Cambridge University Press. 313\u0026minus;357\u003c/li\u003e\n\u003cli\u003eLiu Xingsong,Xu Huaiji,Shi Lanbin , et al. 1993.Study on activity feature and time of the faults in bedrock region-taking kangding-moxi fault segment as an example[J]. Seismology and geology, 15(2):123-130.\u003c/li\u003e\n\u003cli\u003eLu Ruren,Zhong Xianghao.1996.Block and burst of the water channels insiade hailuogou glacier. Glacial permafrost. 18:257-263.\u003c/li\u003e\n\u003cli\u003eLi Zhongwu,Chen Zhirong,Wang Minglong.1991.Classification and correlation of the quaternary glacial epoch in the hengduan mountains[J]. Geological review, 39(4):124-132.\u003c/li\u003e\n\u003cli\u003eLiang Mingjian. The Late Quaternary Activity Patterns of the Xianshuihe Fault [D]. Institute of Geology, China Earthquake Administration, 2019.DOI: 10.27489/d.cnki.gzdds.2019.000019.\u003c/li\u003e\n\u003cli\u003eMa Chao,Liu Yufa,Zhang Wei, et al.2020. Preliminary study on newly discovered seismic surface rupture zones in moxi section of xianshuihe fault[J]. earthquake research in sichuan, (4):8-13.\u003c/li\u003e\n\u003cli\u003eQidong Li1,Zhuojuan Xie(2024).Analysis of spatiotemporal variations in b‑values before the 6.8‑magnitude earthquake in Luding, Sichuan, China, on September 5, 2022 .Acta Geophysica (2024) 72:3957\u0026ndash;3974 https://doi.org/10.1007/s11600-024-01369-5\u003c/li\u003e\n\u003cli\u003eRein, N., Isken, M.P., Domigall, D., Ohrnberger, M., Hannemann, K., Kr\u0026uuml;ger, F., Korn, M., et al. Dahm, T. (2024)\u003c/li\u003e\n\u003cli\u003eCharacterizing shallow fault zones by integrating profile, borehole and array measurements of seismic data and distributed acoustic sensing. Near Surface Geophysics, 22, 298\u0026ndash;312. https://doi.org/10.1002/nsg.12293\u003c/li\u003e\n\u003cli\u003eRyckebusch, C. et al. (2025) Characterization of a heterogeneous limestone vadose zone based on a multimethod and multiscale geophysical approach. Near Surface Geophysics, 1\u0026ndash;17. https://doi.org/10.1002/nsg.70026\u003c/li\u003e\n\u003cli\u003eShi Lanbin,Lin Chuanyong,He Yongnian, et al.1992. Characteristics of fault rock and fault activity in kangding-moxi fault zone[J].Seismology and geology, 14(2):97-104,193-194.\u003c/li\u003e\n\u003cli\u003eTang W Q,Chen Z L,Liu Y P, et al.2005.Present-day tectonics activity in the intersection area of the xianshuihe fault and longmenshan fault on the eastern margin of the Qinghai-tibet plateau[J].Geological bulletin of china,24（12）：1169-1172.\u003c/li\u003e\n\u003cli\u003eWen Xueze, C.R.Allen,Luo Zhuoli, et al.1989.segmentation,geometric features,and their seismotectonic implication for the Holocene xianshuihe fault zone[J]. Acta seismologica sinica, 11(4)：362-372.\u003c/li\u003e\n\u003cli\u003eWen X Z.2000.Character of rupture segmentation of the xianshuihe -anninghe-zemuhe fault zone,western sichuan[J].Seismology and geology, 22(3)：239-249.\u003c/li\u003e\n\u003cli\u003eWang Y, Wang Y, Zhang P, Zhang J, Zhang B, Liu-Zeng J, Zhou R, Wang W, Zhang H, Li Z. 2022. Cenozoic tectonic evolution of regional fault systems in the SE Tibetan Plateau. Science China Earth Sciences, 65(4): 601\u0026ndash;623, https://doi.org/10.1007/s11430-021-9880-3\u003c/li\u003e\n\u003cli\u003eWang, P., Li, X., Min, X., Xu, S., Zhao, G. \u0026amp; Fan, D. (2024) Investigating soil layers with ground penetrating radar in the modern Yellow River Delta of China. Near Surface Geophysics, 22, 339\u0026ndash;357. https://doi.org/10.1002/nsg.12289\u003c/li\u003e\n\u003cli\u003eWei Kejia, Xiao Ruiqing, Kuang Ye, et al. Application of Comprehensive Detection in Active Fault Investigation\u0026mdash;Taking the Moxi Fault in the Southern Segment of the Xianshuihe Fault on the Southeastern Margin of the Qinghai-Tibet Plateau as an Example [J/OL]. Geological Bulletin, 1-10 [2025-04-08]. http://kns.cnki.net/kcms/detail/11.4648.p.20250102.1447.002.html.\u003c/li\u003e\n\u003cli\u003eXu X W,Zhang P Z,Wen X Z, et al.2005.Features of active tectonics and recurrence behaviors of strong earthquakes in the western Sichuan province and its adjacent regions[J].Seismology and geology, 27(3)：446-461.\u003c/li\u003e\n\u003cli\u003eXu S, Guan L, Zhang M, Zhong J, Liu W, Xie X, Liu C, Takahata N, Sano Y. 2022. Degassing of deep-sourced CO2 from Xianshuihe-Anninghe fault zones in the eastern Tibetan Plateau. Science China Earth Sciences, 65(1): 139\u0026ndash;155, https://doi.org/10.1007/s11430-021-9810-x\u003c/li\u003e\n\u003cli\u003eYin A, Harrison T M. 2000. Geologic evolution of the Himalayan-Tibetan orogen. Annu Rev Earth Planet Sci, 28: 211\u0026ndash;280\u003c/li\u003e\n\u003cli\u003eYi Guixi,Long Feng,Liang Mingjian, et al.2023.Seimogenic structure of the 5 september 2022 sichuan luding Ms6.8 earthquake sequence.chinese J.geophys.(in Chinese),66(4):1363-1384.\u003c/li\u003e\n\u003cli\u003eZhao Dejun,Wang Daoyong,Wu Dechao, et al. 2008.structural deformation and kinematics of the moxi fault in western sichuan[J].Sedimentary geology and Tethyan geology, 28(3):15-20.\u003c/li\u003e\n\u003cli\u003eChen Guihua, Min Wei, Song Fangmin, et al.2011. Preservation of Co-seismic Surface Rupture in Different Geomorphological Settings From the Study of the 1786 Moxi Earthquake[J]. seismology and geology, 33(4): 804-817.\u003c/li\u003e\n\u003cli\u003eZhou Rongjun, He Yulin, Yang Tao et al. 2001.Slip Rate and Strong Earthquake Rupture on the Moxi-Mianning Segment Along the Xianshuihe-Anninghe Fault Zone[J]. earthquake research in china, 17(3):253-262.\u003c/li\u003e\n\u003cli\u003eZhang, P. Z. (2013). A review on active tectonics and deep crustal processes of the Western Sichuan region, eastern margin of the Tibetan Plateau. Tectonophysics, 584, 7\u0026ndash;22. https://doi.org/10.1016/j.tecto.2012.02.021\u003c/li\u003e\n\u003cli\u003eZheng Rongying, Yu Zhongyuan, Chen Baixu, et al. 2022.Shallow Surface Structure of Seismogenic Fault of Luding,Sichuan MS6.8 Earthquake in 2022 [J]. J.of institute ofdisaster prevention, 24(4): 67-74.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":false,"email":"","identity":"studia-geophysica-et-geodaetica","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"","title":"Studia Geophysica et Geodaetica","twitterHandle":"","acdcEnabled":false,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"VoR Journals","inReviewEnabled":false,"inReviewRevisionsEnabled":false},"keywords":"Moxi Fault, integrated geophysics and geochemistry, active fault detection, thick overburden mountain–gorge region, thick overburden","lastPublishedDoi":"10.21203/rs.3.rs-9258880/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9258880/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eActive faults in mountain-gorge regions with thick overburden, such as the southeastern Tibetan Plateau, pose severe seismic risks to populated areas and critical infrastructure, yet their detection remains technically challenging due to complex topography and limited subsurface imaging capabilities. The 2022 Ms 6.8 earthquake along the Moxi Fault\u0026mdash;the southeastern segment of the Xianshuihe Fault Zone\u0026mdash;highlights the urgent need for precise fault characterization to inform post-earthquake reconstruction and seismic hazard assessment. Existing studies often rely on single geophysical or geological methods, which fail to fully resolve deep-shallow structural coupling, geochemical evidence of fluid activity, and quantitative kinematic parameters of active faults in these settings, leaving critical gaps in understanding fault behavior and hazard potential.\u003c/p\u003e \u003cp\u003eThis study aimed to address these gaps by developing an integrated detection framework combining geological-geomorphological survey, multi-method geophysics, and soil gas geochemistry to finely characterize the geometry, kinematics, and late Quaternary activity of the Moxi Fault. We employed high-resolution UAV remote sensing and field mapping to identify fault geomorphology, complemented by shallow seismic reflection, high-density resistivity, microtremor survey, and ground-penetrating radar for deep-shallow structural imaging, alongside high-density soil CO₂ and radon measurements to trace fault-related fluid pathways.\u003c/p\u003e \u003cp\u003eOur results reveal that the Moxi Fault is a steeply west-dipping (75\u0026deg;\u0026ndash;80\u0026deg;) left-lateral strike-slip fault with a 50\u0026ndash;60 m wide damage zone, exhibiting a measured left-lateral displacement of 39.5\u0026thinsp;\u0026plusmn;\u0026thinsp;0.5 m and a vertical throw of ~\u0026thinsp;3 m. Radiocarbon dating (6379\u0026thinsp;\u0026plusmn;\u0026thinsp;120 to 7856\u0026thinsp;\u0026plusmn;\u0026thinsp;40\u0026nbsp;year BP) confirms late Holocene activity, with a slip rate of 5.3\u0026thinsp;\u0026plusmn;\u0026thinsp;0.2 mm/yr, consistent with the regional Xianshuihe Fault Zone slip rate (4\u0026ndash;6 mm/yr). The integrated geophysical and geochemical approach effectively overcomes topographic interference, with soil CO₂ and radon anomalies spatially correlating with the fault zone, verifying its role as a deep fluid conduit.\u003c/p\u003e \u003cp\u003eThese findings demonstrate that the integrated framework successfully resolves the structural and kinematic details of the Moxi Fault, achieving the study\u0026rsquo;s goal of precise active fault characterization in mountain-gorge regions with thick overburden. This work provides critical data for post-earthquake reconstruction and seismic hazard assessment in the region, and offers a transferable technical reference for active fault detection in similar tectonically active mountain-gorge settings worldwide.\u003c/p\u003e","manuscriptTitle":"Integrated Geophysical and Geochemical Detection of the Active Moxi Fault at the Southeastern Margin of the Qinghai‒Tibet Plateau","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-04-20 09:57:11","doi":"10.21203/rs.3.rs-9258880/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"reviewerAgreed","content":"28229414030958685483561061767095094653","date":"2026-05-05T06:02:07+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-04-10T10:36:35+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-03-30T04:45:48+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-03-30T04:45:02+00:00","index":"","fulltext":""},{"type":"submitted","content":"Studia Geophysica et Geodaetica","date":"2026-03-29T12:49:08+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":false,"email":"","identity":"studia-geophysica-et-geodaetica","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"","title":"Studia Geophysica et Geodaetica","twitterHandle":"","acdcEnabled":false,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"VoR Journals","inReviewEnabled":false,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"cbfb7ff0-6ee3-4e85-a83a-76cb21963e63","owner":[],"postedDate":"April 20th, 2026","published":true,"recentEditorialEvents":[{"type":"reviewerAgreed","content":"28229414030958685483561061767095094653","date":"2026-05-05T06:02:07+00:00","index":21,"fulltext":""}],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-04-20T09:57:12+00:00","versionOfRecord":[],"versionCreatedAt":"2026-04-20 09:57:11","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9258880","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9258880","identity":"rs-9258880","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}