Interferometric Synthetic Aperture Radar Observations Research Articles

Fault Kinematics of the 2023 Mw 6.0 Jishishan Earthquake, China, Characterized by Interferometric Synthetic Aperture Radar Observations

Characterizing the coseismic slip behaviors of earthquakes could offer a better understanding of regional crustal deformation and future seismic potential assessments. On 18 December 2023, an Mw 6.0 earthquake occurred on the Lajishan–Jishishan fault system (LJFS) in the northeastern Tibetan Plateau, causing serious damage and casualties. The seismogenic fault hosting this earthquake is not well constrained, as no surface rupture was identified in the field. To address this issue, in this study, we use Interferometric Synthetic Aperture Radar (InSAR) data to investigate the coseismic surface deformation of this earthquake and invert both ascending and descending line-of-sight observations to probe the seismogenic fault and its slip characteristics. The InSAR observations show up to ~6 cm surface uplift caused by the Jishishan earthquake, which is consistent with the thrust-dominated focal mechanism. A Bayesian-based dislocation modeling indicates that two fault models, with eastern and western dip orientations, could reasonably fit the InSAR observations. By calculating the coseismic Coulomb failure stress changes (∆CFS) induced by both fault models, we find that the east-dipping fault scenario could reasonably explain the aftershock distributions under the framework of stress triggering, while the west-dipping fault scenario produced a negative ∆CFS in the region of dense aftershocks. Integrating regional geological structures, we suggest that the seismogenic fault of the Jishishan earthquake, which strikes NNE with a dip of 56° to the east, may be either the Jishishan western margin fault or a secondary buried branch. The optimal finite-fault slip modeling shows that the coseismic slip was dominated by reverse slip and confined to a depth range between ~5 and 15 km. The released seismic moment is 1.61 × 1018 N·m, which is equivalent to an Mw 6.07 earthquake. While the Jishishan earthquake ruptured a fault segment of approximately 20 km, it only released a small part of the seismic moment that was accumulated along the 220 km long Lajishan–Jishishan fault system. The remaining segments of the Lajishan–Jishishan fault system still have the capability to generate moderate-to-large earthquakes in the future.

Coseismic deformation and interseismic strain accumulation of the 2024 MS 7.1 Wushi earthquake in Xinjiang, China

On January 23, 2024, a magnitude 7.1 earthquake occurred in Wushi County, Aksu Prefecture, Xinjiang, China. The epicenter was at the Maidan Fault, which is known for its left-lateral strike-slip and thrust properties in the Tianshan seismic zone. In this study, we used Interferometric Synthetic Aperture Radar (InSAR) and Global Navigation Satellite System (GNSS) observations to investigate the characteristics and mechanisms of both the coseismic and interseismic deformation. The main findings are as follows: 1) The InSAR coseismic deformation displays clear thrust characteristics, with a maximum relative displacement of ∼0.8 m along the line of sight. This indicates a thrust-type earthquake. 2) The majority of the slip during the earthquake occurred within a 60 km × 40 km area, with depths ranging from 4 to 26 km. The maximum slip of the fault was about 2.3 m, corresponding to a moment magnitude of 7.0. 3) The seismogenic faults mainly exhibit thrust-type movement characteristics during the interseismic period and have a clearly defined locked state. The earthquake rupture depth aligns with the depth of locking during interseismic periods. 4) Before the earthquake, the seismogenic structure experienced compressive deformation in a north-south direction and the epicenter occurred at the edge of the high-strain area, as indicated by the GNSS strain rate.

Double-Vergent Plate Boundary Faults and Triggered Coseismic Rupture of the 2022 Chihshang Doublet Earthquake Occurred in Eastern Taiwan

Abstract The earthquake doublet of Mw 6.5 and 6.9 occurred along the west-dipping Central Range fault (CRF) adjacent to the east-dipping creep segment of the Longitudinal Valley fault in eastern Taiwan on 17–18 September 2022. The faulting model derived from the Interferometric Synthetic Aperture Radar and Global Positioning System observation suggests that the west-dipping CRF rupture is responsible for the two mainshocks. Meanwhile, the two major earthquakes resulted in ∼100 km of fault slip along the double-convergent plate boundary faults near the Longitudinal Valley in eastern Taiwan. The 2022 Chihshang earthquake sequence filled the seismic gap of the CRF located between the 2006 ML 6.1 Taitung earthquake and the 2013 ML 6.1 Ruisui earthquake. Finally, the 2022 Chihshang earthquake sequence increased the Coulomb failure stress in the southernmost segment of the CRF, which may cause a higher seismic potential in the future.

Active thickness estimation and failure simulation of translational landslide using multi-orbit InSAR observations: A case study of the Xiongba landslide

The active thickness of the translational landslides plays a pivotal role in evaluating its hazards and simulating its instability. Existing techniques have difficulties in estimating the accurate active thickness due to the limitations of observation conditions and imaging geometry, leading to deviations in failure simulations. To overcome these challenges, this study proposes an enhanced method that utilizes multi-orbit Interferometric Synthetic Aperture Radar (InSAR) observations to estimate the active thickness of the translational landslides and subsequently conduct more accurate instability simulations. The method involves integrating multi-orbit InSAR imaging parameters with the spatial geometry of the landslide to establish a slope coordinate system. This system enables the projection of one-dimensional InSAR Line Of Sight (LOS) displacements onto the three-dimensional displacements of the landslide. Subsequently, the active thickness is estimated by combining InSAR three-dimensional displacements with the mass conservation method. Finally, the estimated thickness is incorporated into the geological model construction to simulate the dynamic movement of the landslide. The method was applied to the Xiongba translational landslide in Gongga County, Tibet Autonomous Region, China. The results show that the deformation is mainly concentrated at its forefront, with maximum three-dimensional deformation rates of 4.7 m/a, 2.3 m/a, and 1.24 m/a. The landslide encompasses an estimated area of around 5.33 square kilometers, and its active thickness varies from 0 to 106.59 m. The maximum displacement distance reaches 1469.76 m, with a peak velocity of 60.37 m/s. The proposed method provides scientific support for assessing, analyzing, and preventing landslide disasters.

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

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

InSAR, Gravity, and Geomagnetic Observations Suggest the 2020 Mw 6.5 Stanley Earthquake Occurred on a Blind Strike-Slip and a Normal Fault

ABSTRACT The 2020 Mw 6.5 Stanley earthquake occurred in western North America and is the largest earthquake in Idaho state in the past ∼40 yr. The hypocenter is located at the western margin of the Centennial Tectonic Belt (CTB), which is a subprovince of the Basin and Range and characterized by a series of normal faults. In this study, the coseismic Interferometric Synthetic Aperture Radar observations, geophysical data, and aftershocks are jointly collected to estimate the seismogenic fault of the 2020 Stanley earthquake. The best-fitting fault models suggest the earthquake occurred on two blind faults. Slip on the main, west-dipping, seismogenic fault was sinistral and on the second fault predominantly normal slip with a minor component of right-lateral strike slip. Geophysical observations including gravity and geomagnetic data are consistent with the fault interpretations. The Coulomb failure stress (CFS) change indicates that the rupture of the main seismogenic fault had a positive triggering effect on the slip of the second fault and may have increased the rupture risk of the Sawtooth fault. Moreover, a potential seismic hazard risk zone with a notably low occurrence of aftershocks is found in the west of the central segment of the main seismogenic fault.

Land subsidence in Beijing: response to the joint influence of the South-to-North Water Diversion Project and ecological water replenishment, observed by satellite radar interferometry

ABSTRACT The South-to-North Water Diversion Project Middle Route (SNWD-MR) annually diverts hundreds of millions of cubic meters of water from the Danjiangkou Reservoir to Beijing, significantly impacting the regional groundwater cycle. To conserve water resources, the government has implemented ecological water replenishment (EWR) in some water systems. This study aimed to study the coupled process of groundwater dynamics and land subsidence (LS) in Yongding River (YDR) basin (Beijing section) following the implementation of the SNWD-MR and EWR. First, an Interferometric Synthetic Aperture Radar (InSAR) time series technique was used to detect spatial and temporal distributions of surface displacement between 2015 and 2020 based on satellite images from Sentinel-1A/B. The results indicated a predominant LS deceleration trend during the InSAR observation period. The area with subsidence velocity below 20 mm/yr decreased significantly by 18.6% after SNWD-MR and EWR (from 2016 to 2020). Then, groundwater level fluctuations during the InSAR observation period were analyzed using groundwater measurement well data. Over 60% of these wells showed a rebound in groundwater levels after the implementation of SNWD-MR and EWR. The polynomial distribution lag model (PDL) revealed the association between LS and groundwater level changes, depicting both short- and long-term lag effect. The results showed significant spatial and temporal heterogeneity on the short- and long-term response between groundwater level change and regional subsidence. In addition, we calculated the differential subsidence slope based on the InSAR-derived LS and analyzed its impact on the river slope after SNWD-MR and EWR. The results show that two sections with significant severe differential subsidence slope occur between 0 and 14,000 m and between 54,000 and 78,000 m along the YDR. The slope change caused by LS may reduce the conveyance capacity of surface canals, and more attention should be paid in those two sections. These findings have an important scientific significance for management strategy for LS control against the background of SNWD-MR and EWR.

Excess Ground Ice Profiles in Continuous Permafrost Mapped From InSAR Subsidence

AbstractExcess ground ice formation and melt drive surface heave and settlement, and are critical components of the water balance in Arctic soils. Despite the importance of excess ice for the geomorphology, hydrology and biogeochemistry of permafrost landscapes, we lack fine‐scale estimates of excess ice profiles. Here, we introduce a Bayesian inversion method based on remotely sensed subsidence. It retrieves near‐surface excess ice profiles by probing the ice content at increasing depths as the thaw front deepens over summer. Ice profiles estimated from Sentinel‐1 interferometric synthetic aperture radar (InSAR) subsidence observations at 80 m resolution were spatially associated with the surficial geology in two Alaskan regions. In most geological units, the estimated profiles were ice poor in the central and, to a lesser extent, the upper active layer. In a warm summer, units with ice‐rich permafrost had elevated inferred ice contents at the base of the active layer and the (previous years') upper permafrost. The posterior uncertainty and accuracy varied with depth. In simulations, they were best (≲0.1) in the central active layer, deteriorating (≳0.2) toward the surface and permafrost. At two sites in the Brooks Foothills, Alaska, the estimates compared favorably to coring‐derived profiles down to 35 cm, while the increase in excess ice below the long‐term active layer thickness of 40 cm was only reproduced in a warm year. Pan‐Arctic InSAR observations enable novel observational constraints on the susceptibility of permafrost landscapes to terrain instability and on the controls, drivers and consequences of ground ice formation and loss.

Slow slip event displacement on 2018 offshore Boso Peninsula detected by Sentinel-1 InSAR time-series analysis with numerical weather model assistance

SUMMARY The south-eastern offshore of the Boso Peninsula in Japan periodically experiences short-term slow slip events (SSEs) every few years. On 2018 June, an SSE occurred with the maximum surface horizontal displacement reaching up to 4.7 cm by according to the operational global navigation satellite system (GNSS) network. This study performed a time-series analysis of interferometric synthetic aperture radar (InSAR) with Sentinel-1 SAR images to investigate detailed spatial pattern of surface displacements caused by the SSE. With the assistance of an atmospheric delay correction with a regional numerical weather model output, the InSAR time-series analysis successfully captured displacement signals in three paths, whose maximum amplitudes in line-of-sight directions were 1.46, 1.86 and −0.80 cm. A checkerboard test revealed that the resolution of the slip inversion was higher when InSAR was used than that using GNSS, especially in and around the inland. The slip inversion with the actual displacement data derived from the InSAR time-series analysis was performed with the L-curve optimization, showing that the estimated slip area was concentrated offshore south-eastward from the Boso Peninsula with the maximum slip of 5 cm and the estimated moment magnitude of 6.4. As similar to previous SSEs in the Boso Peninsula, a seismic swarm simultaneously occurred in the downdip area adjacent to the estimated slip with the SSE occurrence, suggesting a different friction characteristics between them. This study demonstrates usefulnesses of the InSAR observation for capturing detailed spatial characteristics of small-displacement events like SSEs and of the hybrid use of the externally derived delay correction with the time-series analysis to improve the displacement detection accuracy.

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

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

Research on the Surface Deformation, Fault Rupture, and Coseismic Geohazard of the 2022 Luding Mw 6.8 Earthquake.

An Mw 6.8 earthquake occurred in Luding County, Ganzi Tibetan Autonomous Prefecture, Sichuan Province, on 5 September 2022. This seismic event triggered numerous coseismic geohazards in the seismic zone. In this study, the ascending- and descending-track synthetic aperture radar (SAR) images observed by the Sentinel-1A satellite are utilized to extract the coseismic surface deformation of the Luding earthquake. Subsequently, a faulting model is estimated based on the elastic dislocation theory, under the constraint of the InSAR observation. Additionally, the POT technique was employed to detect coseismic geohazards. High-spatial-resolution optical remote sensing images served to validate the reliability of the detection results. The coseismic interferometric synthetic aperture radar (InSAR) deformation field indicated a maximum deformation of ~190 mm and ~140 mm along the ascending and descending tracks, respectively. The estimated best-fitting faulting model suggests that the optimal seismogenic fault strike and dip angles are 169.3° and 70°, respectively. The fault slip predominantly exhibits left-lateral strike-slip characteristics and is concentrated at depths of 3-12 km. The estimated maximum fault slip was 2.67 m, occurring at a depth of 7 km. The pixel offset tracking (POT) result derived from the pre- and post-earthquake SAR images found a total of 245 medium- to large-scale coseismic geohazards, with a verification rate from optical images exceeding 64%. The distribution of these geohazards is notably dense within the significant fault rupture segment. Geohazards on the fault hanging wall are densely packed, whereas landslides along the Dadu River's fault footwall are also notably frequent.

Interseismic kinematics along the Tuolaishan-Lenglongling fault determined by Sentinel-1 InSAR observations

Current study of interseismic fault slip behavior constrained by Interferometric Synthetic Aperture Radar (InSAR) derived line-of-sight (LOS) velocities has been favored. However, we found that the fault slip rate inferred by the spatially dense two-dimensional (2-D) horizontal velocities can be more robust than that estimated by LOS velocities. Here, we obtain the LOS velocity maps across the Qilian-Haiyuan fault (QL-HYF) zone through time series analysis of Sentinel-1 A/B data (2015–2020). Combining the GPS observations, we calculate the interseismic 3-D velocity map. Based on a genetic optimization algorithm, we investigate the fault motion at depth on the Lenglongling (LLL) and Tuolaishan (TLS) segments. We show the spatial variation of the strike-slip rate (4.1– 5.5 mm/yr), dip-slip rate (0– 1.7 mm/yr), crustal compression shortening rate (1.2– 3 mm/yr) and locking depth (7.9– 17.1 km) along the TLSF. These parameters are 3.4– 5.6 mm/yr, 0– 0.8 mm/yr, 1.9– 4 mm/yr and 13.3– 23 km along the LLLF, respectively. Based on the inferred strike-slip rate (∼3.4 mm/yr) and locking depth (∼13.3 km) on the main fault of the 2022 Menyuan earthquake, the estimated interseismic accumulated seismic moment (1.44×1019 N m) since the 1540 M7.2 paleoearthquake can produce an Mw6.74 earthquake, in agreement with the moment magnitude (∼Mw6.7) caused by the coseismic rupture. This suggests that there is a good correspondence between inter- and co-seismic kinematics, and the fault with low interseismic slip rate remains have the potential to generate large earthquake.

Geodetic source models of the 2016–2022 Menyuan Earthquake sequence (Northeastern Tibet) inferred from InSAR and optical observations

SUMMARY We study the 2016 January 21 (${{{M}}}_{\rm{w}}$ 5.9) and 2022 January 8 (${{{M}}}_{\rm{w}}$ 6.7) earthquake sequence that struck the Menyuan region in northwest China's Qinghai province. These two earthquakes are destructive events that occurred around/on the Lenglongling fault (LLLF). Here, we derive the line-of-sight displacement fields of the two earthquakes using Interferometric Synthetic Aperture Radar (InSAR) measurements of Sentinel-1 SAR data, and map the range and horizontal offset fields of the 2022 event using Sentinel-1 amplitude images and Planet-Lab optical images. Based on the offset maps, we determine the detailed surface rupture trace of the 2022 event. We perform slip inversions for the two earthquakes on triangle fault patches whose size increases with depth. Results show that the western branch segment of the 2022 event has a ∼0.5-m normal dip-slip motion. This result contradicts previous inferences on dip-slip sense of this branch segment. We identify a left-stepping fault structure with a ∼5-km step width in the transition zone between the Tuolaishan fault (TLSF) and LLLF, which may serve as a kinematic barrier to prevent further propagation of seismic rupture along the TLSF. Stress calculation shows that a stress drop of ∼0.4 bar produced by the 2016 event on a ∼5-km long LLLF segment may act as a negative stress barrier to suppress rupture propagation of the 2022 event toward the southeast of the LLLF.

Subsurface deformation monitoring with InSAR and elastic inversion modeling in west Texas

Recent Interferometric Synthetic Aperture Radar (InSAR) observations depict centimeter-level surface uplift/subsidence signals in west Texas that correlate spatially and temporally with increased fluid extraction and injection activities over the past decade. Linear subsidence features from InSAR data near the Pecos area, that align well with maximum horizontal stress orientations and recent clusters of seismic events, suggest fault motion is also associated with this deformation. In this study, we investigate the relationship between observed surface displacement and inferred subsurface fault slip and reservoir compaction/inflation by inversely solving a combined model of elastic dislocation (Okada, 1985, 1992) and poroelastic reservoir compaction/inflation model (Geertsma, 1973).Our geomechanical analysis coupled with InSAR observations are consistent with the idea that both fault slip and reservoir inflation/compaction are occurring associated with fluid injection and withdrawal in the Pecos area. Numerical results show that the linear surface displacement patterns can be accurately reproduced using clusters of finite slip on multiple elastic dislocations in the subsurface, but also matching the broader areal subsidence and uplift signals requires the addition of poroelastic subsurface inflation and depletion. The inverted areal reservoir pressure distribution correlates well with known injection and withdrawal operations in the area. The best-fit surface deformation locates most fault slips patches at depths of 1–3 km, which is shallower than most reported earthquakes in this area. The difference in the estimation of depth suggests there could be aseismic fault slippages.

Insight into the 1 December 2016 Mw 6.2 Juliaca Earthquake, Southern Peru, by InSAR Observations and Field Investigation

On 1 December 2016, an Mw 6.2 earthquake characterized by normal faulting occurred in the highlands of the central Andes in southern Peru, marking the region’s largest shallow event. The occurrence of the earthquake provides a significant chance to gain insight into the regional tectonic deformation and the seismogenic mechanism of the shallow normal-faulting earthquake, as well as the regional potential seismic risk. Here, we first utilize Sentinel-1A interferometric synthetic aperture radar (InSAR) data to extract the coseismic and postseismic deformation associated with this earthquake and then determine the detailed coseismic slip and postseismic afterslip distribution of this event. Coseismic modeling results indicate that the coseismic rupture is mainly characterized by normal faulting with some dextral strike-slip components. Most coseismic slip is confined to a depth range of 2–12 km, indicating an obvious slip deficit area in the shallow fault part. Further postseismic modeling reveals that the majority of afterslip is concentrated at depths of 0 to 5.4 km. The relatively shallow postseismic afterslip makes up for the coseismic slip deficit area to some extent. Through a joint analysis of the inversions, seismic data, and regional geology and geomorphology, we infer that the occurrence of this 2016 normal-faulting event is a result of regional gravitational collapse. In addition, we investigate the relationship between the 2016 earthquake and great historical earthquakes near the subduction zone of the central Andes and find that the 2016 event is likely promoted in advance by these events through our calculations of the coseismic and postseismic Coulomb stress changes. Finally, we should pay more attention to the nearby Falla Huaytacucho-Condoroma fault and the western segment of the Vilcanota Fault because of their relatively high stress loading.

Mapping and Analyses of Land Subsidence in Hengshui, China, Based on InSAR Observations

In this paper, we use interferometric synthetic aperture radar (InSAR) annual and time-series analysis of RADARSAT-2 SAR data, spanning from September 2011 to October 2022, to study the temporal–spatial characteristics of land subsidence in Hengshui, North China Plain. The data reveal two large-scale subsidence areas in Hengshui, individually located to the north of Hengshui city around the Hutuo River and to the east or south along the Fuyang, Suolu and Qingliang Rivers. The fastest subsidence arises after 2017, with the maximum rate exceeding 11 cm/year. We correlate the observed subsidence with the central table variation of groundwater depression, groundwater table variation of three confined aquifers, hydraulic head declines of three confined aquifers and the time-dependent total hydraulic head variation. We find a spatial consistency between land subsidence and groundwater depression or hydraulic head declines of three confined aquifers, and subsidence displacement and total hydraulic heads both manifest clear seasonal variability. This suggests that the subsidence is primarily caused by groundwater extraction for agricultural use. We also observe that the subsidence rates in Hengshui did not decrease but rather increased when the groundwater table significantly rose after September 2019. It is very likely that as a result of the occurrence of thick and widespread continuity of clay layers with high compressibility in the Quaternary deposit of Hengshui, a new preconsolidation head could be generated due to groundwater table drop, leading to the effective hydraulic head still existing in the aquitards even if the groundwater table rises in the aquifer systems.

Investigating Deformation Mechanism of Earth-Rock Dams with InSaR and Numerical Simulation: Application to Liuduzhai Reservoir Dam, China

Ground deformation is the direct manifestation of the earth-rock dam's hazard potential. Therefore, it is essential to monitor deformation for dam warning and security evaluation. The Liuduzhai Dam, a clay-core dam of a large reservoir in China, was reinforced with plastic concrete cut-off walls between 13 January 2009 and 29 May 2010, as it was subject to leakage and deformation. However, the deformation development and the mechanism of the dam are still unclear. In this study, the deformation fields before and after the reinforcement of the Liuduzhai Dam were yielded by using the Interferometric Synthetic Aperture Radar (InSAR) technique. Furthermore, a numerical simulation method was employed to obtain the dynamic seepage field of the dam during the InSAR observation period. The results indicated that the average deformation velocity and maximum deformation velocity are −11.7 mm/yr and −22.5 mm/yr, respectively, and the cumulative displacement exceeds 100 mm, which shows typical continuous growth characteristics in a time series. In contrast, the dam deformation tended to be stable after reinforcement, with the average deformation velocity and maximum deformation velocity being −0.4 mm/yr and −1.2 mm/yr, respectively, behaving as cyclical deformation time series. According to the results of InSAR and seepage analysis, it is shown that: (1) dynamic seepage was the main mechanism controlling dam deformation prior to reinforcement; (2) the concentrated load caused by construction and the rapid dissipation of pore water pressure caused by the sudden drop of the infiltration line were the reasons for the acceleration of deformation during and after construction; and (3) the plastic concrete cut-off walls effectively reduced the dynamic seepage field, while the water level fluctuations were the main driving factor of elastic deformation of the dam after reinforcement. This study provides a novel approach to investigating the deformation mechanism of earth-rock dams. Furthermore, it has been confirmed that InSAR can identify the seepage deformation of dams by detecting surface movements. It is recommended that InSAR deformation monitoring should be incorporated into future dam safety programs to provide detailed deformation signals. By analyzing the temporal and spatial characteristics of the deformation signal, we can identify areas where dam performance has degraded. This crucial information aids in conducting a comprehensive dam safety assessment.

Sensitivity Evaluation of Time Series InSAR Monitoring Results for Landslide Detection

Spaceborne interferometric synthetic aperture radar (InSAR) techniques are important for landslide detection and monitoring; however, several limitations and uncertainties, such as the unique north–south flying direction and side-look radar observing geometry, currently limit the ability of InSAR to credibly detect landslides, especially those related to high and steep slopes. Here, we conducted experimental and statistical analysis on the feasibility of time-series InSAR monitoring for steep slopes using ascending and descending SAR images. First, the theoretical (TGNSS), practical (PGNSS), and terrain (Hterrain) (T-P-H) indices for sensitivity evaluations of the slope displacement monitoring results from time-series InSAR were proposed for slope monitoring. Subsequently, two experimental and statistical studies were conducted for the cases with and without Global Navigation Satellite System (GNSS) monitoring data. Our experimental results of two high and steep open-pit mines showed that the defined theoretical and practical sensitivity indices can quantitatively evaluate the feasibility of ascending and descending InSAR observations in steep-slope deformation monitoring with GNSS data, and the terrain sensitivity index can qualitatively evaluate the feasibility of landslide monitoring results from ascending and descending Sentinel-1 satellite data without GNSS data. We further demonstrate the generalizability of these proposed indices using four landslide cases with both public GNSS and InSAR monitoring data and 119 landslide cases with only InSAR monitoring data. The statistical results indicated that greater indices correlated with higher reliability of the monitoring results, suggesting that these novel indices have wide suitability and applicability. This study can help to improve the practice of slope deformation monitoring using spaceborne InSAR, especially for high and steep slopes.

Analysis of the fault slip, creep, and coupling characteristics of the Maomaoshan-Laohushan-Haiyuan Fault using InSAR and GNSS measurements

Line-of-sight Interferometric Synthetic Aperture Radar (InSAR) observations are affected by long-wavelength errors and the inaccurate estimation of vertical deformation, thereby restricting horizontal slip rate estimations for strike-slip faults, such as the Maomaoshan-Laohushan-Haiyuan Fault (MMS-LHS-HY). To overcome this limitation, herein, InSAR (2016–2022) and Global Navigation Satellite System (GNSS) observations were combined and the Least Squares Variance Component Estimation (LS-VCE) method was used to obtain the Three-Dimensional (3-D) deformation field of the Haiyuan fault zone; subsequently, the slip-rate and coupling distributions were inverted. The results showed that: (1) Compared with the GNSS and leveling deformation velocities, the residuals of the 3-D deformation field obtained using the LS-VCE method combined with the GNSS and InSAR observations reached an RMS of 1 mm/a, significantly better than the deformation field obtained without GNSS data. (2) Vertical deformation from InSAR observations led to over- or under-estimation of the fault strike-slip rate, with the maximum influence on the shallow creep rate of 2.1 mm/a. (3) Based on the 3-D deformation field, fault slip rate, locking depth, and fault creep characteristics obtained from the elastic dislocation and elastic block models were consistent with each other. (4) The strike-slip rate of the MMS-LHS-HY fault gradually decreased from west to east, whereas the thrust rate gradually increased in the same direction. (5) Based on the 3-D deformation field, the creep range of the LHS fault was ∼40 km, with the mean shallow creep rate reaching 2.5 ± 0.1 mm/a, notably larger than the creep rate obtained by ascending InSAR observation alone.

Soil moisture estimation from Sentinel-1 interferometric observations over arid regions

We present an experimental methodology based on interferometric synthetic aperture radar (InSAR) time series analysis that can provide surface (top 5 cm) soil moisture (SSM) estimations over sandy arid soils. A co-registered Single Look Complex (SLC) SAR stack as well as meteorological information are required as input of the proposed methodological workflow. The proposed methodology consists of five steps. In the first step, meteorological data are exploited to identify the snow/ice free SAR acquisition related to lowest SSM level. In the second step, interferometric (coherence and phase closure) observables over a spatial grid are calculated. In the third step, for each grid cell the ordering of SAR acquisitions according to the SSM is performed. The sorting is performed by starting from the SAR acquisition related to lowest SSM level and by exploiting coherence and backscattering information. In the fourth step, for each grid cell the coherence values due to SSM variations are calculated by exploiting the ordering of SAR acquisitions according to the SSM. In the fifth step, SSM is estimated by inverting an analytical interferometric model using coherence values due to SSM variations and phase closure information. The proposed method estimates SSM over arid regions by ordering SAR acquisitions based on SSM, by calculating coherence values due to SSM variations and by inverting an interferometric model.A case study over an arid region in California/Arizona is presented. The proposed workflow was applied in Sentinel-1 (C-band) VV-polarized InSAR observations. The estimated SSM results were assessed with independent SSM observations from a station of the International Soil Moisture Network (ISMN) (RMSE: 0.029 m3/m3 R: 0.78) and with ERA5-Land reanalysis model data (RMSE: 0.049 m3/m3 R: 0.62). In summary, the proposed methodology was able to provide accurate SSM estimations at high spatial resolution (∼250 m). A discussion of the benefits and the limitations of the proposed methodology highlighted the potential of interferometric observables for SSM estimation over arid regions.