Continuous Global Navigation Satellite System Research Articles

Detecting Transient Uplift at the Active Volcano Ol Doinyo Lengai in Tanzania With the TZVOLCANO Network

AbstractOver the last 7 years, geodetic data have detected periods of uplift and subsidence of the active volcano Ol Doinyo Lengai in Tanzania. Although numerous eruptions of the volcano have occurred historically, a systematic investigation of transient deformation using continuous Global Navigation Satellite System (GNSS) data has not been undertaken. We use the Targeted Projection Operator (TPO) to assess 7 years of continuous GNSS data from the TZVOLCANO network for transient signals and find rapid uplift spanning March 2022–December 2022 and then steady‐state uplift through August 2023. We conduct a nonlinear inversion of the GNSS velocities associated with the transient signal using dMODELS and find consistency with an inflating spheroidal source located 2.3 ± 0.6 km beneath the crater. Prior to March 2022, geodetic data indicated quiescence just below Ol Doinyo Lengai, thus detecting transient deformation with TPO allows for tracking changes in the magmatic system over time in the Natron Rift.

Detecting Transient Uplift at the Active Volcano Ol Doinyo Lengai in Tanzania With the TZVOLCANO Network

AbstractOver the last 7 years, geodetic data have detected periods of uplift and subsidence of the active volcano Ol Doinyo Lengai in Tanzania. Although numerous eruptions of the volcano have occurred historically, a systematic investigation of transient deformation using continuous Global Navigation Satellite System (GNSS) data has not been undertaken. We use the Targeted Projection Operator (TPO) to assess 7 years of continuous GNSS data from the TZVOLCANO network for transient signals and find rapid uplift spanning March 2022–December 2022 and then steady‐state uplift through August 2023. We conduct a nonlinear inversion of the GNSS velocities associated with the transient signal using dMODELS and find consistency with an inflating spheroidal source located 2.3 ± 0.6 km beneath the crater. Prior to March 2022, geodetic data indicated quiescence just below Ol Doinyo Lengai, thus detecting transient deformation with TPO allows for tracking changes in the magmatic system over time in the Natron Rift.

Numerical experiment toward simultaneous estimation of the spatiotemporal evolution of interseismic fault slips and block motions in southwest Japan

Interseismic strain around southwest Japan can be attributed to slip phenomena on the plate interface and processes inside the continental plate, such as block motions and inland fault slips. Although many crustal deformation analyses have been carried out, the simultaneous estimation of these phenomena and comprehensive discussion regarding the effect on the total strain budget remain topics to be investigated. In this study, we conducted numerical experiment to evaluate the possibility of simultaneously monitoring the spatiotemporal evolution of interseismic fault slips and block motions based on state-space modeling. We aimed to estimate fault slips and block motions using the time series of dense continuous Global Navigation Satellite System sites covering southwest Japan, encompassing 25 years from 1996 onward. We calculated synthetic block motions of the forearc region, monotonically increasing back slips on block boundary faults, and long-term slow slip events in the Tokai region, Kii Channel, and Bungo Channel. Subsequently, we generated the expected synthetic displacement time-series at GNSS stations. Applying Kalman filtering, we successfully estimated the spatiotemporal evolution of block motions, cumulative back slips, multiple slow slip events occurring in different regions. Although the contributions of fault slips and block motions showed slight trade-off, main characteristics of the slip distributions and the direction of block motions were well-recovered. We recovered slow slip events with slips of 5–10 cm or larger. We investigated the estimation uncertainty and separation precision of the unknown parameters using the covariance matrix estimated by Kalman filtering. Focusing on the structure of the non-diagonal component of the covariance matrix, we evaluated the complex effects of site and subfault locations on the estimated slip spatial distribution bias. For instance, the extent of the correlation between subfaults suggested that the three slow slip regions have different tendency of the uncertainties of slip areas, extending toward landside, seaward, or both of them. Our framework enables the comprehensive evaluation of the contributions and uncertainties of various deformation sources covering the entire subduction zone.Graphical abstract

Strain accumulation in the Mentawai Forearc Sliver, Indonesia, inferred from continuous GNSS-derived strain rate

The Mentawai Forearc Sliver (MFS) is characterized by oblique deformation formed as slip partitioned between normal and parallel trench plate convergence. The surge of great earthquakes from 2004 to 2012 along the adjacent Sunda trench left a large unbroken segment known as the Mentawai Seismic Gap. Here, we adopted continuous Global Navigation Satellite System (GNSS) observation data to identify the present regional crustal deformation using geodetic strain rates. The principal strain rate, dilatation rate, and maximum shear strain rate are about 0.13 microstrain/yr, 0.2 microstrain/yr, and 0.1 microstrain/yr, respectively, with the range of its uncertainties between 0.01 and 0.04 microstrain/yr. The dilatation and maximum shear strain rates reveal the spatial coverage of strike-slip duplex and backthrust tectonics along the Mentawai Forearc Sliver.

Overview and Analysis of Ground Subsidence along China’s Urban Subway Network Based on Synthetic Aperture Radar Interferometry

Deformation along a subway rail network is related to the safe operation of the subway and the stability of construction facilities on the surface, making long-term deformation monitoring imperative. Long-term monitoring of surface deformation along the subway network and statistical analysis of the overall deformation situation are lacking in China. Therefore, targeting 35 Chinese cities whose subway mileage exceeds 50 km, we extracted their surface deformation along subway networks between 2018 and 2022, using spaceborne synthetic aperture radar (SAR) interferometry (InSAR) technology and Sentinel-1 satellite data. We verified the results with the continuous global navigation satellite system (GNSS) stations’ data and found that the root mean square error (RMSE) of the InSAR results was 3.75 mm/year. Statistical analysis showed that ground subsidence along the subways was more prominent in Beijing, Tianjin, and other areas in the North China Plain, namely Kunming (which is dominated by karst landforms), as well as Shanghai, Guangzhou, Qingdao, and other coastal cities. In addition, an analysis revealed that the severity of surface subsidence correlated positively with a city’s gross domestic product (GDP) with a Pearson correlation of 0.787, since the higher the GDP, the more frequent the construction and maintenance of subway, and the more commuters there are, which in turn exacerbates the disturbance to the surface. Additionally, the type of land cover also affects the ground deformation. Our findings provide a reference for constructing, operating, and maintaining the urban subway systems in China.

GNSS and Sentinel-1 InSAR Integrated Long-Term Subsidence Monitoring in Quetta and Mastung Districts, Balochistan, Pakistan

Land subsidence (LS) is a global phenomenon that has affected several urban centres around the world such as Jakarta (Indonesia), Mexico City (Mexico), Xi’an (China), and Iron County (US). It has mainly been attributed to anthropogenic activities such as groundwater exploitation, especially in unconsolidated aquifer systems rich in highly compressible clay and silt. The platy clay minerals rearrange into horizontal stacks after dewatering, leading to a volume change due to overburden. In this study, land subsidence is investigated in the Quetta and Mastung districts, Balochistan, Pakistan, by employing Small Baseline Subset (SBAS) Interferometric Synthetic Aperture Radar (InSAR), Global Navigation Satellite System (GNSS), and groundwater level (GWL) variations. This study represents the first attempt in Pakistan to measure the long-term land subsidence by fusing GNSS and InSAR data for improved validity. InSAR data from the Sentinel-1 satellite in the Ascending (195 scenes) and Descending (183 scenes) tracks were used to analyse LS from December 2015 to December 2022. High-accuracy Trimble NetRS GNSS receivers were used in five locations from October 2006 to December 2022. An average subsidence ranging from 3.2 cm/y to 16 cm/y was recorded in the valley mainly due to the GWL decline and clay-rich sediments, which are prone to compaction due to dewatering. An accumulative LS of 2 m was recorded by the permanent GNSS station in central Quetta from October 2008 to January 2023 (14.2 years). An acceleration in the subsidence from 12 cm/y to 16.6 cm/y after 2016 was recorded by the continuous GNSS. Additionally, the InSAR and GNSS values were compared for validation, resulting in a good correlation between both techniques. A GWL decline ranging from 1.7 m to 6 m was recorded by the piezometers in Quetta during the period 1987–2022. Large- and small-scale fissures were observed in the study area during the surveys. These fissures are responsible for damage to the city’s infrastructure and aquifer contamination. The subsidence profile also agrees with the subsurface lithology. Our assessment concludes that Quetta may be the fastest-sinking metropolitan city in Pakistan. The overexploitation of groundwater and the population explosion may be the main contributing factors for the land subsidence.

Dominance of transient rheology in far-field postseismic deformation following the 2012 Mw 7.8 Haida Gwaii and 2013 Mw 7.5 Craig earthquakes

The Mw 7.8 2012 Haida Gwaii earthquake and the Mw 7.5 2013 Craig earthquake occurred along the Queen Charlotte transpressive margin, two months and 340 km apart. On and near Vancouver Island, hundreds of kilometres southeast of the two events, many continuous Global Navigation Satellite Systems sites underwent no discernable coseismic motion but up to 1 cm southeast postseismic motion (away from epicenters) which lasted for only 2 – 3 years. To resolve the postseismic signal of the two earthquakes, we used a minimum of four years of measurements before the Haida Gwaii earthquake to remove the longer-term motion of these sites that reflect mainly the locking of the Cascadia megathrust. To study the geodynamic process that governed the observed far-field postseismic motion, in particular its short duration, we employ a model of an elastic lithosphere with thickness 20 km and rigidity (μE) 32 GPa overlying Burgers-viscoelastic mantle layers in a self-gravitating spherical Earth which captures the regionally integrated effect of Earth rheology despite the complex and controversial tectonics of the study area. We find that the short-lived far-field postseismic motion was controlled entirely by the transient rheology. The observations can be explained by a steady-state (Maxwell) viscosity ηM of the upper mantle no lower than 1×1019 Pa s with a transient (Kelvin) viscosity ηK of about 6×1017 Pa s (Kelvin relaxation time τK ∼1.2 years) extending to large depths such as > 400 km. The far-field postseismic deformation is the result of the elastic plate serving as a stress guide but resisted by the asthenospheric mantle undergoing transient creep. The lithosphere-asthenosphere coupling is quantified by a “plate Kelvin response time” τKE=ηK/μE. Rheological parameters can be scaled to other values, but as long as τK and τKE stay unchanged, the far-field deformation results remain the same. Our observations presented a unique opportunity to quantify the effect of the transient rheology separately from that of the steady-state rheology.

Versatile Modeling Of Deformation (VMOD) Inversion Framework: Application to 20 Years of Observations at Westdahl Volcano and Fisher Caldera, Alaska, US

AbstractWe developed an open source, extensible Python‐based framework, that we call the Versatile Modeling Of Deformation (VMOD), for forward and inverse modeling of crustal deformation sources. VMOD abstracts from specific source model implementations, data types and inversion methods. We implement the most common geodetic source models which can be combined to model and analyze multi‐source deformation. VMOD supports Global Navigation Satellite System (GNSS), InSAR, electronic distance measurement, Leveling and tilt data. To infer source characteristics from observations, VMOD implements non‐linear least squares and Markov Chain Monte‐Carlo Bayesian inversions, including joint inversions using different sources of data. VMOD's structure allows for easy integration of new geodetic models, data types, and inversion strategies. We benchmark the forward models against other published results and the inversion approaches against other implementations. We apply VMOD to analyze deformation at Unimak Island, Alaska, observed with continuous and campaign GNSS, and ascending and descending InSAR time series generated from Sentinel‐1 satellite radar acquisitions. These data show an inflation pattern at Westdahl volcano and subsidence at Fisher Caldera. We use VMOD to test a range of source models by jointly inverting the GNSS and InSAR data sets. Our final model simultaneously constrains the parameters of two sources. Our results reveal a depressurizing spheroid under Fisher Caldera ∼4–6 km deep, contracting at a rate of ∼2–3 Mm3/yr, and a pressurizing spherical source underneath Westdahl volcano ∼6–8 km deep, inflating at ∼5 Mm3/yr. This and past applications of VMOD to volcanic unrest benefit from an extensible framework which supports jointly inversions of data sets for parameters of easily composable multi‐source models.

THE EFFECT OF SEASONAL VARIATION ON GNSS ZENITH TROPOSPHERIC DELAY

Abstract. The Global Navigation Satellite System (GNSS) signal experiences delays caused by the atmosphere, leading to the lengthening of the geometric path of the ray, commonly referred to as tropospheric delay. This delay is a significant source of error in GNSS positioning, contributing to a bias in the height component of several centimeters, even when meteorological data are simultaneously recorded and used in tropospheric models. In this study, considering seasonal variations, we investigated the impact of tropospheric delay on the GNSS height component. GNSS stations, part of the Turkish RTK CORS Network known as TUSAGA-Active (Turkish National Permanent GNSS Network Active), covered different heights over the 2014–2019 period. Daily coordinates of GNSS stations and tropospheric zenith delay were obtained through the GAMIT/GLOBK software solution.In the study, temperature, pressure, and relative humidity data of meteorological stations at different heights were converted to mean sea level. By using these values, interpolation estimates were made for the continuous GNSS stations in the same region with the IDW method. The most significant delay in GNSS signals occurs in July and August. This effect, which causes periodic changes in the zenith delay, varies inversely with the station's height. With the increase in the amount of water vapor in the atmosphere in parallel with the rise in the temperature in the summer months, it is seen that the stations at a low height are more exposed to the tropospheric effect than the stations at higher heights. In addition, GNSS stations' reduced meteorological values (temperature, pressure and relative humidity) show that the zenith delay values changed directly proportional to the temperature and inversely proportional to the pressure and relative humidity.

Drought‐Induced Vertical Displacements and Water Loss in the Po River Basin (Northern Italy) From GNSS Measurements

AbstractWe study vertical ground displacement time series from Global Navigation Satellite System (GNSS) stations to measure deformation associated with hydrological drought in the Po river basin. Focusing on interannual trend changes, rather than seasonal (annual) components, we found a clear spatially correlated deformation signal that is temporally (anti)correlated with changes in the Po river level and the SPEI‐12 drought index, with stations moving upward during periods of river/index level decrease and vice versa. In the 2021–2022 time span, which culminated in the most severe drought of the last two centuries, we estimate the amount and spatial distribution of water loss in the basin and its surroundings. Excluding the seasonal signals, between January 2021 and August 2022, the GNSS stations underwent uplift, up to 7 mm, which corresponds to ∼70 Gtons of water loss. Compared to Global Land Data Assimilation System and Gravity Recovery and Climate Experiment estimates, GNSS results show a similar temporal evolution of water content but a more heterogeneous distribution of values. We show that continuous GNSS networks provide an effective way to monitor multiannual trend changes in water storage even in small water basins and serve as a reliable indicator of drought severity.

Traceable frequency measurements with counters

Received signals from Global Navigation Satellite Systems (GNSS) are nowadays widely used by industry laboratories for ensuring metrological traceability for their respective range of calibration services in the field of time and frequency. Usually, a local frequency standard is steered by continuous GNSS signal reception providing at its output stable and accurate reference signals for the laboratory measurement equipment, in general for synthesizers and counters. Reception of GNSS signals is surely an adequate and practical tool for the purpose, however further steps are needed to establish traceability in a strict metrological sense. Based on already available guidelines and publications, this paper is a contribution to the discussion how metrological traceability to internationally accepted standards can be established in a calibration laboratory. We restrict the discussion to equipment in common use which may not necessarily be of the highest sophistication. In this spirit, we develop a detailed scheme for an uncertainty budget comprising all links of the traceability chain from the device under test to the SI second, the scale-unit of Coordinated Universal Time. Then we go through and apply this scheme step by step to a demonstration setup for frequency measurements with a counter with varying operational parameters. In this framework, a novel approach to distinguish between components of statistical measurement uncertainty is introduced. Furthermore, the limiting uncertainty contributions are discussed and based on a suitable set of parameters an expression for the best measurement capability is given. With this scheme at hand a user may develop an uncertainty budget adapted to his own setup, especially if acceptance from a national accreditation body is sought.

The Alaska Makushin Volcano 2016–2018 inflation and its potential relation to the 2020 earthquake swarm, from GNSS observations

Makushin volcano on Unalaska Island along the Aleutian Chain in Alaska experienced a period of unrest from 2016 to 2020, including 2016–2018 surface inflation observed by 5 continuous Global Navigation Satellite System stations, and an earthquake swarm in the second half of 2020 consisting of hundreds of earthquakes, including two greater than M4. A Bayesian inversion of the geodetic data applied to a range of analytical source models suggests that the observed deformation pattern can be explained by an inflating pressure point source located 2 km east of the summit at a depth of approximately 5 km below sea level, with a chamber volume increase of approximately 0.004 km3. A stress change analysis suggests that the 2016–2018 magma intrusion may have played a role in advancing the 2020 seismicity anomaly by modulating the regional stress field. Our study highlights the importance of stress transfer between magmatic and tectonic processes and the potential for using this information to better understand and mitigate the risk of volcanic eruptions.

Sea level rise projections up to 2150 in the northern Mediterranean coasts

Vertical land movements (VLM) play a crucial role in affecting the sea level rise along the coasts. They need to be estimated and included in the analysis for more accurate Sea Level (SL) projections. Here we focus on the Mediterranean basin characterized by spatially variable rates of VLM that affect the future SL along the coasts. To estimate the VLM rates we used geodetic data from continuous global navigation satellite system stations with time series longer than 4.5 years in the 1996–2023 interval, belonging to Euro-Mediterranean networks and located within 5 km from the coast. Revised SL projections up to the year 2150 are provided at 265 points on a geographical grid and at the locations of 51 tide gauges of the Permanent Service for Mean Sea Level, by including the estimated VLM in the SL projections released by the Intergovernmental Panel on Climate Change (IPCC) in the AR6 Report. Results show that the IPCC projections underestimate future SL along the coasts of the Mediterranean Sea since the effects of tectonics and other local factors were not properly considered. Here we show that revised SL projections at 2100, when compared to the IPCC, show a maximum and minimum differences of 1094 ± 103 mm and −773 ± 106 mm, respectively, with an average value that exceeds by about 80 mm that of the IPCC in the reference Shared Socio-economic Pathways and different global warming levels. Finally, the projections indicate that about 19.000 km2 of the considered Mediterranean coasts will be more exposed to risk of inundation for the next decades, leading to enhanced impacts on the environment, human activities and infrastructures, thus suggesting the need for concrete actions to support vulnerable populations to adapt to the expected SL rise and coastal hazards by the end of this century.

A ∼200-year relative sea-level reconstruction from the Wellington region (New Zealand) reveals insights into vertical land movement trends

The sea-level rise threat to New Zealand's coastal cities is regionally exacerbated due to spatially varying vertical land movement (VLM). At Wellington, the capital city, situated adjacent to a major active plate boundary, strong regional spatial and temporal variability of VLM is indicated by the relatively short (∼25 year-long) continuous Global Navigation Satellite Systems (GNSS) network, but until now longer records of VLM have been lacking. Here, a ∼ 200-year-long relative sea-level reconstruction is presented from Pāuatahanui salt marsh in the northern Wellington region. The foraminifera-based relative sea-level reconstruction indicates that ∼1 ± 0.45 m of sudden uplift occurred during the 1855CE Mw 8.2 Wairarapa earthquake. Following this, Pāuatahanui has experienced a mean rate of relative sea-level rise (1855CE to present) of 1.5 ± 0.6 mm/yr, or 2.4 ± 0.8 mm/yr since the start of the twentieth century, consistent with ongoing subsidence in concert with climate-driven sea-level rise. Further acceleration to >3 mm/yr since the 1990s (with 4 mm/yr also possible if the full 95% confidence range is taken into consideration) is consistent with the globally documented acceleration in sea-level rise, although low model precision hampers confidence in this interpretation. This record is the first of its kind from a tectonically complex setting in New Zealand, shedding light on the effects of the historically significant 1855 earthquake, and fills a gap between millennial-scale and contemporary records of VLM with important implications for future sea-level projections in the region.

Seasonally hydrological load and background seismicity in the intraplate collision zone, the Longmen Shan, China

SUMMARY Hydrological modulation of background seismicity provides a way to understand the seismogenic process and interaction mechanism between the hydrosphere and lithosphere. To elucidate the hydrological modulation of background seismicity in the Longmen Shan, the monthly spatio-temporal distribution of terrestrial water storage (TWS) variations is inverted from the seasonal term of continuous GNSS (Global Navigation Satellite System) data and compared with monthly precipitation. In the Longmen Shan, monthly TWS variations are in phase with precipitation variations in the northern area but lag precipitation variation by 2 months in the southern area. The annual amplitude of the inverted TWS is about 0.2 m, which is consistent with the amplitude of precipitation. To investigate the stress perturbations in the crustal interior induced by the hydrological load, monthly Coulomb failure stress (CFS) variation caused by TWS and precipitation load is calculated on a simplified fault model of the Longmen Shan, respectively. The maximum CFS variations of TWS and precipitation are about 2.4 kPa. To obtain the background seismicity, different earthquake declustering methods are employed on a two-decade earthquake catalogue (M ≥ 2.5). The declustered results are subjected to null hypothesis tests, including assessing whether the earthquake distribution follows a homogeneous Poisson distribution in time or exhibits a temporally homogeneous, spatially heterogeneous Poisson distribution in space and time. The only declustered catalogue derived by the epidemic type aftershock sequence model pass all the tests. Furthermore, the monthly CFS variation and its rate caused by TWS and precipitation are compared with the monthly background seismic events. Notably, a correlation is observed between CFS variation rate due to precipitation and background seismicity. This correlation suggests the presence of long-term hydrological modulation of seasonal background seismicity in the Longmen Shan.

Ground Deformation Monitoring for Subway Structure Safety Based on GNSS

Ground deformation poses a serious threat to the safety of subway structures. Consequently, intelligent and efficient automated safety monitoring of ground deformation along the subway has become urgent. Traditional engineering observation methods have the disadvantages of difficulties with datum selection, non-automation, and poor reliability. A ground deformation monitoring system for subway structure safety based on the Global Navigation Satellite System (GNSS) was established and validated through experimental comparisons with traditional precision leveling in this study. Based on the GNSS monitoring points, the continuous kinematic observation GNSS data of ground deformation along the subway line were obtained; a joint robust local mean decomposition (RLMD)–singular value decomposition (SVD) noise-reduction processing method for GNSS signals was proposed to realize the real-time and high-precision monitoring of ground deformation. The results show that the proposed combined noise-reduction method can reduce the maximum noise amplitude by 86%. When compared with the accuracy of the traditional precision leveling method, it was determined that the vertical positioning accuracy of the deformation monitoring system is greater than 2.7 mm, the horizontal positioning accuracy is greater than 1.3 mm, and the measurement error is less than 1.5 mm. The deformation monitoring system has the advantages of convenience, automation, and high accuracy and can be applied to ground deformation monitoring for subway structures.

Active subduction and strain partitioning in western Myanmar revealed by a dense survey GNSS network

The active tectonics of the Myanmar (formerly Burma) microplate in central Myanmar are caused by the oblique collision between the Sunda and Eurasia plates to the east and the Indian plate to the west. The kinematics of this plate boundary zone remain a subject of controversy, due in part to limited geodetic and seismic observations in the region. Here, we report 41 new and 67 updated survey-mode and continuous Global Navigation Satellite System (GNSS) velocities spanning central and western Myanmar, between 15 – 23°N and 93 – 98°E. For the first time, our network allows us to directly observe the occurrence of active convergence along the central Rakhine coast in a manner consistent with active subduction and kinematic coupling of the megathrust, at a rate of 15 – 20 mm/yr. The data also establish a nearly constant strike-slip rate of 20 – 23 mm/yr along the entire length of the Sagaing fault. Using an elastic block-modeling approach, we examine several proposed models for the partitioning of oblique convergence into strike-slip and thrust motion across the Indo-Myanmar Ranges and the Myanmar Central Basin. We find evidence for shortening perpendicular to local topography throughout the Indo-Myanmar Ranges, indicating active convergence and nearly complete strain partitioning between thrust and transform faults north of 19°N, and estimate a rate of moment-deficit accumulation along the megathrust of 0.8−1.5×1019 N m/yr, equivalent to one MW 9.0 earthquake every 250 to 450 years, assuming all elastic strain is released seismically. We also find that a relatively small set of major active crustal faults can explain much of the data, though the data cannot resolve smaller faults that may be active at rates lower than a few mm/yr. Our results have important implications for earthquake and tsunami preparedness across the region, and indicate areas for future study where the geodetic observations remain ambiguous about ongoing fault activity and seismic hazard, particularly within the densely populated Ayeyarwady Delta region and along the southern Rakhine coast.

The seismic hazard from the Lembang Fault, Indonesia, derived from InSAR and GNSS data

Abstract. A growing number of large cities are located near poorly understood faults that have not generated a significant earthquake in recent history. The Lembang Fault is one such fault located near the city of Bandung in West Java, Indonesia. The slip rate on this fault is debated, with estimates ranging from 6 to 1.95–3.45 mm yr−1, derived from a GNSS (global navigation satellite system) campaign and geological measurements respectively. In this paper we measure the surface deformation across the Bandung region and resolve the slip rate across the Lembang Fault using radar interferometry (InSAR – interferometric synthetic aperture radar) analysis of 6 years of Sentinel-1 satellite data and continuous GNSS measurements across the fault. Our slip rate estimate for the fault is 4.7 mm yr−1, with the shallow portions of the fault creeping at 2.2 mm yr−1. Previous studies estimated the return period of large earthquakes on the fault to be between 170–670 years. Assuming simplified fault geometries and a reasonable estimate of the seismogenic depth we derive an estimated moment deficit equivalent to magnitude 6.6–7.0 earthquakes, indicating that the fault poses a very real hazard to the local population. Using the Global Earthquake Model OpenQuake engine we calculate ground motions for these two earthquake scenarios and estimate that 1.9–2.7 million people within the Bandung metropolitan region would be exposed to ground shaking greater than 0.3 g. This study highlights the importance of identifying active faults, understanding their past activity, and measuring the current strain rates of smaller crustal active faults located near large cities in seismic zones.

GNSS-Constrained Rupture Kinematics of the 2022 Mw 6.7 Luding, China, Earthquake: Directivity Pulse during the Asymmetrical Bilateral Rupture

Abstract Impulse motion characterized by a large amplitude in the fault-normal direction can be observed at near-fault strong motion sites during strike-slip earthquakes. The large pulse, which always causes high intensity and stronger damage to structures close to faults, is usually attributed to the directivity effect of rupture propagating along strike and the proximity to the fault. We present an analysis of such a large directivity pulse captured by the near-fault high-rate Global Navigation Satellite System (GNSS) during the 2022 Mw 6.7 Luding, China, earthquake—the largest event ever observed by space geodesy on the seismically active Xianshuihe fault in the eastern Tibetan Plateau. We invert the displacement waveforms and offsets derived from the continuous and campaign GNSS for the rupture kinematics. The inferred slip model reveals a rupture zone of 30 km in length above 15 km depth along the Moxi segment, yielding a seismic moment of 1.1×1019 N·m and a source duration of 13 s. The high-rate GNSS (hrGNSS) waveforms suggest an asymmetric bilateral rupture: most slips with long rise time are concentrated on the southern part of the ruptured fault, whereas a short-duration pulse-like slip rate with low final slip propagates during the northward rupture. We found that the directivity pulse observed by the nearest hrGNSS site is controlled primarily by the sharp pulse-like slip rate and rapid rupture velocity approximating the local S-wave velocity. Along with additional local amplification, this large directivity pulse may be responsible for the heavy damage in Moxi town close to the northern ruptured fault.

Detecting outliers in GNSS position time series using machine learning techniques

The Global Navigation Satellite System (GNSS) position time series is applied in studies that require high-precision positioning, such as monitoring tectonic movements and Earth deformation. Outliers in GNSS position time series can significantly impact the accuracy of station positioning and movement parameters, leading to distorted data analysis outcomes. This study investigates the effectiveness of three machine learning techniques, including-Isolation Forest, One-Class Support Vector Machines (O-C SVM), and Local Outlier Factor (LOF) for outlier detection in GNSS position time series, with a specific focus on the SYNT model where outliers account for a substantial proportion (15%). Through comprehensive analysis, our results highlight the exceptional performance of the Isolation Forest method. It demonstrates remarkable accuracy in identifying outliers, effectively detecting the majority of them, and achieving an area under the ROC curve close to 1. In contrast, the LOF method performs less effectively in outlier detection, while the O-C SVM method displays relatively higher accuracy in identifying normal data points. These findings emphasize the significant advantages of leveraging machine learning approaches in processing continuous GNSS measurement data. By effectively identifying and handling outliers, these techniques enhance the accuracy and reliability of data analysis in GNSS position time series, ultimately establishing their superiority in the field of data analysis.