Seasonal Subsidence Research Articles

Soil Characteristics and Response Mechanism of the Microbial Community in a Coal–Grain Compound Area with High Groundwater Levels

Coal mining has led to escalating ecological and environmental issues in significant coal and grain production areas, posing a severe danger to food security. This study examines the disturbance patterns of soil factors and microbial communities in coal and grain production areas, and attempts to understand the impact of subsidence and water accumulation stress on soil characteristics and microbial communities in coal mining subsidence areas with high subsidence levels. Five specific regions of Zhao Gu Yi Mine, situated in Henan Province and under the ownership of Jiaozuo Coal Group, were chosen. Aside from the control group (CK), the study blocks situated in the coal mining subsidence zones consisted of perennial subsidence ponding (PSP), seasonal subsidence ponding (SSP), the neutral zone (NZ), and the horizontal deformation zone (HDZ). The soil nutrient indices and the stoichiometric properties of soil C, N, and P were assessed on the surface of each block. The organization of the soil microbial community was identified using high-throughput sequencing. The findings indicate that: 1. Substantial disparities exist in soil properties and microbial community structure between the subsidence and non-subsidence zones. The levels of soil organic mater (SOM), total nitrogen (TN), total phosphorus (TP), available nitrogen (AN), and available phosphorus (AP) all decrease to different extents in the subsidence area. Additionally, the coal mining subsidence waterlogged area exhibits higher levels compared to the coal mining subsidence non-waterlogged area. Conversely, the soil water content (SWC), C/N ratio, C/P ratio, and N/P ratio all increase to varying degrees. 2. Regarding the composition of the community, the presence of Proteobacteria is considerably greater in the non-water-logged area of coal mining subsidence (NZ, HDZ) compared to the water-logged area and control group (p < 0.05). The prevalence of Firmicutes in the subsidence water area was substantially greater compared to both the subsidence non-waterlogged area and the control group (p < 0.05). The prevalence of Gemmatimonadota is markedly greater in the waterlogged area of mining subsidence compared to the non-waterlogged area and CK (p < 0.05). The Ascomycota population reached its highest value in the neutral zone (NZ), which was significantly greater than the values observed in the seasonal subsidence ponding (SSP) and perennial subsidence ponding (PSP) regions (p < 0.05). On the other hand, the Rozellomycota population had its highest value in the SSP region, which was significantly greater than the values observed in the other regions (p < 0.05). 3. The abundance and variety of soil bacteria and fungi, as well as their important populations, are associated with different levels of soil characteristics. The primary elements that influence the alteration of microbial communities are soil nutrients and soil water content. The presence of coal mine subsidence and water accumulation has a notable impact on the properties of the soil in the surrounding area. This study offers a scientific foundation for reclaiming land affected by subsidence caused by coal mining in regions where coal and grain production are the dominant industries.

Research on collaborative management technology of deep multi-coal seam mining and pre-reclamation in coal-grain composite area

Subterranean coal mining results in the occurrence of surface subsidence, soil degradation, and damage to agricultural lands, which is especially severe in regions with high groundwater levels. The collaborative reclamation scheme combining surface pre-reclamation and underground mining layout optimization can effectively control the problem of damage to farmlands. Hence, it is imperative to study the collaborative management technology. The research area for this study is Jiulishan Mine, located in coal-grain composite areas with a high groundwater table. Initially, a combined UAV and USV measuring system was utilized to acquire spatial data of the proposed reclamation area. Furthermore, we examined the evolution features of the subsidence ponding related to various mining methods using FLAC3D numerical modeling. Ultimately, the ArcGIS spatial analysis module was utilized to model and calculate the reclamation volume and rate for each plan. Our findings indicate that: (1) The extent of damage caused by shallow coal seam mining includes an area of 50.67 hm2 for farmland damaged area (FDA), 31.49 hm2 for seasonal subsidence ponding (SSP), and 23.51 hm2 for perennial subsidence ponding (PSP). Additionally, the boundary subsidence values for each damaged area are 0.8 m, 1.6 m, and 2.8 m, respectively. (2) Through the optimization of deep coal seam mining designs, the spatial configuration of the subsidence basin is successfully altered, creating the necessary condition for the development of a dynamic pre-reclamation plan. (3) The reclamation rate of the optimized pre-reclamation (PR) scheme is significantly higher, ranging from 40 % to 44 %, compared to the reclamation rate of 24 % of the traditional reclamation (TR). The choice of a suitable land reclamation and ecological restoration strategy was determined by optimizing mining plans and considering the characteristics of the subsidence area. This offers empirical evidence and specialized assistance for the ecological rehabilitation of coal-grain composite areas with high groundwater levels.

Toward long-term monitoring of regional permafrost thaw with satellite interferometric synthetic aperture radar

Abstract. Active-layer thickness (ALT) is estimated for a study area in northern Alaska's continuous-permafrost zone using satellite data from Sentinel-1 (radar) and ICESat-2 (lidar) for the period 2017 to 2022. Synthetic aperture radar (SAR) interferograms were generated using the Short Baseline Subset (SBAS) approach. Displacement time series over the thaw season (June–September) are fit well with a linear model (root mean square error (RMSE) scatter is less than 7 mm) and show maximum seasonal subsidence of 20–60 mm. ICESat-2 products were used to validate the interferometric synthetic aperture radar (InSAR) displacement time series. ALT was estimated from measured subsidence using a widely used model exploiting the volume difference between ice and water, reaching a maximum depth in our study area of 1.5 m. Estimated ALT is in good agreement with in situ and other remotely sensed data but is sensitive to assumed thaw season onset, indicating the need for reliable surface temperature data. Our results suggest the feasibility of long-term permafrost monitoring with satellite InSAR. However, the C-band (∼55 mm center wavelength) Sentinel radar is sensitive to vegetation cover and, in our studies, was not successful for similar monitoring in the heavily treed discontinuous-permafrost zone of central Alaska.

Revealing the Ground Deformation and Its Mechanism in the Heihe River Basin by Interferometric Synthetic Aperture Radar and Optical Images.

The Heihe River Basin (HRB), located on the northeast margin of the Qilian Mountains, is China's second largest inland river basin. It is a typical oasis-type agricultural area in northwest China's arid and semiarid areas. It is important to monitor and investigate the spatiotemporal distribution characteristics and mechanisms of surface deformation in HRB for the ecology of inland river basins. In recent years, research on HRB has mainly focused on hydrology, meteorology, geology, or biology. Few studies have conducted wide-area monitoring and mechanism analysis of the surface stability of HRB. In this study, an improved interferometric point target analysis InSAR (IPTA-InSAR) technique is used to process 101 Sentinel-1 SAR images from two adjacent track frames covering the HRB from 2019 to 2020. The wide-area deformation of the HRB is obtained first for this period. The results show that most of the surface around the HRB is relatively stable. There are six areas with an extensive deformation range and magnitude in the plain oasis area. The maximum deformation rate is more than 50 mm/year. The maximum seasonal subsidence and uplift along the satellites' line-of-sight (LOS) direction can be up to -70 mm and 60 mm, respectively. Moreover, we use the Google Earth Engine platform to process the multisource optical images and analyze the deformation areas. The remote sensing indicators of the deformation areas, such as the normalized difference vegetation index (NDVI), soil moisture (SMMI), and precipitation, are obtained during the InSAR monitoring period. We combine these integrated remote sensing results with soil type and precipitation to analyze the surface deformations of the HRB. The spatiotemporal relationships between soil moisture, vegetation cover, and surface deformation of the HRB are revealed. The results will provide data support and reference for the healthy and sustainable development of the inland river basin economic zone.

Spatio-temporal evolution of land subsidence and susceptibility zonation of associated ground fissures in the urban area of loess plateau: a case in Xianyang city, China

For over 50 years, the Xianyang city on the Chinese loess plateau, has been deeply affected by land subsidence and its associated ground fissures. In this study, 67 Sentinel-1A images from 2015 to 2022 were analysed to obtain the spatio-temporal evolution of land subsidence. Subsidence centers identified in Yunyang town and Luqiao town exhibit annual subsidence rates of −31 mm/a and −26.7 mm/a, respectively, culminating in total subsidence of −258 mm in Yunyang town and −139 mm in Luqiao town. Moreover, time series analysis revealed that both towns exhibit pronounced seasonal subsidence patterns. It is believed that human cultivation and groundwater overuse, combined with the effects of active faults, have led to uneven land subsidence. Then, the gradient of land subsidence and its potential relation to ground fissure hazards were evaluated. The results highlight a strong spatial correlation between high subsidence gradient areas and dense ground fissure distribution. Therefore, we proposed for the first time to introduce the land subsidence gradient factors for the susceptibility mapping of ground fissures using the artificial neural network algorithm. The susceptibility zonation results show that integrating the gradient factor can improve the rationality of the susceptibility evaluation. The above understanding provides valuable support for disaster prevention and mitigation in urban areas affected by land subsidence and ground fissures in loess regions.

Seasonal Subsidence and Heave Recorded by Borehole Extensometers in Houston

Seasonal ground movements, particularly subsidence and heave, present a great challenge for the design of roadways, parking lots, underground utility lines, and buried culverts. The US Geological Survey has been operating 13 deep borehole extensometers in Houston, Texas, for land subsidence monitoring since the 1970s and the early 1980s. The half-century extensometer datasets provide direct and continuous measurements of seasonal ground movements in the vertical direction. The Houston global positioning system (GPS) network (HoustonNet) provides independent measures for the timely evaluation of extensometer data. According to this study, shallow expansive soils can induce up to 4 cm (peak-to-trough) seasonal subsidence and heave, and deep sediments can further produce up to 2 cm seasonal subsidence and heave. The latter is primarily caused by the seasonal fluctuations of hydraulic heads in the lower Chicot and upper-Evangeline aquifers, varying considerably over time and space. The results from this study are important for determining potential vertical movement (PVM) for the design of pavements and shallow foundations and for the optimization of groundwater management in the Houston region.

Sentinel-1 InSAR and GPS-Integrated Long-Term and Seasonal Subsidence Monitoring in Houston, Texas, USA

For approximately 100 years, the Houston region has been adversely impacted by land subsidence associated with excessive groundwater withdrawals. The rapidly growing population in the Houston region means the ongoing subsidence must be vigilantly monitored. Interferometric synthetic aperture radar (InSAR) has become a powerful tool for remotely mapping land-surface deformation over time and space. However, the humid weather and the heavy vegetation have significantly degraded the performance of InSAR techniques in the Houston region. This study introduced an approach integrating GPS and Sentinel-1 InSAR datasets for mapping long-term (2015–2019) and short-term (inter-annual, seasonal) subsidence within the greater Houston region. The root-mean-square (RMS) of the detrended InSAR-displacement time series is able to achieve a subcentimeter level, and the uncertainty (95% confidence interval) of the InSAR-derived subsidence rates is able to achieve a couple of millimeters per year for 5-year or longer datasets. The InSAR mapping results suggest the occurrence of moderate ongoing subsidence (~1 cm/year) in nothwestern Austin County, northern Waller County, western Liberty County, and the city of Mont Belvieu in Champers County. Subsidence in these areas was not recognized in previous GPS-based investigations. The InSAR mapping results also suggest that previous GPS-based investigations overestimated the ongoing subsidence in southwestern Montgomery County, but underestimated the ongoing subsidence in the northeastern portion of the county. We also compared the InSAR- and GPS-derived seasonal ground movements (subsidence and heave). The amplitudes of the seasonal signals from both datasets are comparable, below 4 mm within non-subsiding areas and over 6 mm in subsiding (>1 cm/year) areas. This study indicates that groundwater-level changes in the Evangeline aquifer are the primary reason for ongoing long-term and seasonal subsidence in the Houston region. The former is dominated by inelastic deformation, and the latter is dominated by elastic deformation. Both could cause infrastructure damage. This study demonstrated the potential of employing the GPS- and InSAR-integrated method (GInSAR) for near-real-time subsidence monitoring in the greater Houston region. The near-real-time monitoring would also provide timely information for understanding the dynamic of groundwater storage and improving both long-term and short-term groundwater resource management.

Fire as a Major Factor in Dynamics of Tree-Growth and Stable δ13C and δ18O Variations in Larch in the Permafrost Zone

Wildfires are one of the most important environmental factors controlling forest ecosystem physiology and the carbon balance in the permafrost zone of North Siberia. We investigated tree-ring width (TRW) and stable isotope chronologies in tree-ring cellulose (δ13CCell, δ18OCell) of Larix Gmelinii (Rupr.) Rupr. from a wet (WS) and a dry (DS) site. These sites are characterized by different fire histories (fire in 1852 at the wet and 1896 at the dry sites, respectively). TRW and δ18OCell are identified to be the most sensitive parameters in the changing tree growth conditions after fire. The differences in the soil seasonal thermal regime of sites after fires are shown in the relationship between the studied parameters. The δ13CCell values in tree rings from the two sites are positively correlated independently of the fire impact. This fact indicates that δ13CCell chronologies might be more adequate for climatic reconstruction in the region due to the climate signal consistency. Relationships of δ18OCell values between the two sites are still significantly positive 60 years after the fire impact. Dendroclimatic analysis indicates significant changes in tree-ring growth and isotopic ratio responses to climate due to the increased demand of water for trees during the post-fire period (deeper seasonal subsidence of permafrost).

Permafrost thaw sensitivity prediction using surficial geology, topography, and remote-sensing imagery: a data-driven neural network approach

Seasonal or degradational thaw subsidence of permafrost terrain affects the landscape, hydrology, and sustainability of permafrost as an engineering substrate. We perform permafrost thaw sensitivity prediction via supervised classification of a feature set consisting of geological, topographic, and multispectral variables over continuous permafrost near Rankin Inlet, Nunavut, Canada. We build a reference classification of thaw sensitivity using process-based categorization of seasonal subsidence as measured from differential interferometric synthetic aperture radar whereby categories of thaw sensitivity are reflective of ground ice conditions. Classification is performed using a neural network trained on both dispersed and parcel-based reference data. For Low, Medium, High, and Very High thaw sensitivity categories, generalized classification accuracy is 70.8% for 20.6 km2 of dispersed training data. In all cases, the majority classes of Low and Medium thaw sensitivity are predicted with higher accuracy and more certainty, while the minority classes of High and Very High thaw sensitivity are underpredicted. Minority classes can be combined to improve accuracy at the expense of a reduced level of discrimination. The two-class problem can be classified with an accuracy of 81.8%, thereby effectively distinguishing between stable and unstable ground. The method is applicable to similar Low-Arctic permafrost terrain with geological and topographical controls on thaw sensitivity. However, generalized accuracy is reduced for parcel-based training, indicating that reference samples are not totally representative for inference beyond the parcel, and any deployment of the network to other geographical regions would benefit from full or partial retraining with local data.

Spatially characterizing land surface deformation and permafrost active layer thickness for Donnelly installation of Alaska using DInSAR and MODIS data

The degradation of permafrost in the Earth's cold regions due to climate warming and human activities is of increasing concern because of its impact on ecosystems and land management, thus, monitoring the degradation becomes critical. This study aimed to demonstrate a method in which Sentinel-1 DInSAR and MODIS data were combined to estimate and map seasonal and long-term land surface deformation (subsidence/uplifting) and permafrost active layer thickness (ALT) in Donnelly Training Area (DTA) in Alaska. The coherence (similarity) between the paired SAR images was analyzed for their applicability. A sensitivity analysis and accuracy assessment of the estimates were conducted to account for their quality. Results showed that the estimated seasonal subsidence mainly occurring in June and July was in the range of 0 to −0.43 m, while the estimated uplifting mainly happening from September to May of next year was as great as +0.34 m. Moreover, the estimated long-term (2015 to 2018) subsidence and uplifting were mostly distributed in the southern and northern parts of DTA, respectively. The spatially variable time delays led to the ALT estimates greater along the east river and in the west and south parts, and smaller in the north parts. At the significance level of 0.05, the coherence estimates of the paired images were significantly different from zero and compared with the referenced predictions from a widely used annual prediction model, the average residual of the ALT estimates did not significantly differ from zero at the significance level of 0.05. The spatial distributions of the uncertainties for the seasonal surface deformation estimates were similar to those of the input uncertainties from the estimates of model coefficients, the phase change, the modelling error, and the image pairs. Thus, the DInSAR image based method coupled with MODIS data offered the potential of mapping and monitoring the dynamics of permafrost environment for the cold regions such as DTA in which collecting field observations is difficult and costly. This study also enhanced understanding spatiotemporal variability of permafrost deformation in DTA and provided guidelines for developing a near real-time monitoring system of the permafrost environment.

Landform mapping, elevation modelling, and thaw subsidence estimation for permafrost terrain using a consumer-grade remotely-piloted aircraft

We assess performance of a small consumer-grade remotely-piloted aircraft (RPA) for landform mapping, elevation modelling, and thaw subsidence estimation in continuous permafrost terrain. We acquired RPA imagery near Rankin Inlet, Nunavut, to construct orthomosaics and digital elevation models (DEMs) that we use to interpret geomorphology and surficial geology. We estimate seasonal thaw subsidence using DEM differences. To quantify accuracy, RPA DEMs are compared with a satellite-based reference elevation. Subsidence estimates are compared with measurements from differential interferometric synthetic aperture radar (DInSAR). We find that RPA images are very effective for mapping periglacial landforms and surficial geology with the chosen flight specifications. The DEMs exhibit vertical mean absolute error of approximately 1 cm at ground control points. Away from control points, relative vertical accuracy is approximately 3 cm. Comparison to the reference elevation results in survey-wide vertical mean absolute errors of 33–66 cm with high variability and spatial autocorrelation of elevation discrepancy. There is local agreement between DEM differences, DInSAR, and on-the-ground measurements of seasonal subsidence. Results suggest that small RPA may be applicable for mapping thaw subsidence on the order of a few centimetres near control points. However, DEM differences are influenced by vegetation and are contaminated by spatially-variable artefacts, preventing reliable survey-wide RPA estimation of seasonal thaw subsidence.

Apportioning deformation among depth intervals in an aquifer system using InSAR and head data

Land surface subsidence due to excessive groundwater pumping is an increasing concern in California, USA. Interferometric Synthetic Aperture Radar (InSAR) is a remote sensing technique for measuring centimeter-to-millimeter surface deformation at 10–100 m spatial resolution. Here, a data-driven approach that attributes deformation to individual depth intervals within an aquifer system by integrating head data acquired from each of three screened intervals in a monitoring well with InSAR surface deformation measurements was developed. The study area was the Colusa Basin in northern Central Valley. To reconstruct the surface deformation history over the study area, 13 ALOS-PALSAR scenes acquired between 2006 and 2010 were processed. Up to ~3-cm year−1 long-term subsidence and up to ~6 cm seasonal subsidence were observed using the InSAR technique. The technique developed in this paper integrates the InSAR-observed seasonal deformation rate and the co-located head measurements in multiple depth intervals to estimate the elastic skeletal storage coefficient, the time delay between the head change and the observed deformation, and subsequently the deformation of each depth interval. This technique can be implemented when hydraulic head measurements within each depth interval are not correlated with each other. Using this approach, the depth interval that contributed the most to the total subsidence, as well as storage parameters for all intervals, are estimated. The technique can be used for identification of the depth interval within the aquifer system responsible for deformation.

Seasonal and Interannual Ground-Surface Displacement in Intact and Disturbed Tundra along the Dalton Highway on the North Slope, Alaska

Spatiotemporal variation in ground-surface displacement caused by ground freeze–thaw and thermokarst is critical information to understand changes in the permafrost ecosystem. Measurement of ground displacement, especially in the disturbed ground underlain by ice-rich permafrost, is important to estimate the rate of permafrost and carbon loss. We conducted high-precision global navigation satellite system (GNSS) positioning surveys to measure the surface displacements of tundra in northern Alaska, together with maximum thaw depth (TD) and surface moisture measurements from 2017 to 2019. The measurements were performed along two to three 60–200 m transects per site with 1–5 m intervals at the three areas. The average seasonal thaw settlement (STS) at intact tundra sites ranged 5.8–14.3 cm with a standard deviation range of 2.1–3.3 cm. At the disturbed locations, averages and variations in STS and the maximum thaw depth were largest in all observed years and among all sites. The largest seasonal and interannual subsidence (44 and 56 cm/year, respectively) were recorded at points near troughs of degraded ice-wedge polygons or thermokarst lakes. Weak or moderate correlation between STS and TD found at the intact sites became obscure as the thermokarst disturbance progressed, leading to higher uncertainty in the prediction of TD from STS.

Small-Baseline Approach for Monitoring the Freezing and Thawing Deformation of Permafrost on the Beiluhe Basin, Tibetan Plateau Using TerraSAR-X and Sentinel-1 Data.

The dynamic changes of the thawing and freezing processes of the active layer cause seasonal subsidence and uplift over a large area on the Qinghai–Tibet Plateau due to ongoing climate warming. To analyze and investigate the seasonal freeze–thaw process of the active layer, we employ the new small baseline subset (NSBAS) technique based on a piecewise displacement model, including seasonal deformation, as well as linear and residual deformation trends, to retrieve the surface deformation of the Beiluhe basin. We collect 35 Sentinel-1 images with a 12 days revisit time and 9 TerraSAR-X images with less-than two month revisit time from 2018 to 2019 to analyze the type of the amplitude of seasonal oscillation of different ground targets on the Beiluhe basin in detail. The Sentinel-1 results show that the amplitude of seasonal deformation is between −62.50 mm and 11.50 mm, and the linear deformation rate ranges from −24.50 mm/yr to 5.00 mm/yr (2018–2019) in the study area. The deformation trends in the Qinghai–Tibet Railway (QTR) and Qinghai–Tibet Highway (QTH) regions are stable, ranging from −18.00 mm to 6 mm. The InSAR results of Sentinel-1 and TerraSAR-X data show that seasonal deformation trends are consistent, exhibiting good correlations 0.78 and 0.84, and the seasonal and linear deformation rates of different ground targets are clearly different on the Beiluhe basin. Additionally, there are different time lags between the maximum freezing uplift or thawing subsidence and the maximum or minimum temperature for the different ground target areas. The deformation values of the alpine meadow and floodplain areas are higher compared with the alpine desert and barren areas, and the time lags of the freezing and thawing periods based on the Sentinel-1 results are longest in the alpine desert area, that is, 86 days and 65 days, respectively. Our research has important reference significance for the seasonal dynamic monitoring of different types of seasonal deformation and the extensive investigations of permafrost in Qinghai Tibet Plateau.

Inference of the impact of wildfire on permafrost and active layer thickness in a discontinuous permafrost region using the remotely sensed active layer thickness (ReSALT) algorithm

The Yukon–Kuskokwim (YK) Delta is a region of discontinuous permafrost in the subarctic of southwestern Alaska. Many wildfires have occurred in the YK Delta between 1971–2015, impacting vegetation cover, surface soil moisture, and the active layer. Herein, we demonstrate that the remotely sensed active layer thickness (ReSALT) algorithm can resolve the post-fire active layer dynamics of tundra permafrost. We generated a stack of Advanced Land Observing Satellite Phased Array type L-band Synthetic Aperture Radar interferograms over a study region in the YK Delta spanning 2007–2010. We applied ReSALT to this stack of interferograms to measure seasonal subsidence associated with the freezing and thawing of the active layer and subsidence trends associated with wildfire. We isolated two wildfire-induced subsidence signatures, associated with the active layer and the permafrost layer. We demonstrate that InSAR is sensitive to increases in active layer thickness following wildfire, which recovers to pre-fire values after approximately 25 years. Simultaneously, we show that fire gradually thins the permafrost layer by 4 m, which recovers to pre-fire thickness after 70 years.

Identifying poromechanism and spatially varying parameters of aquifer compaction in Choushui River alluvial fan, Taiwan

Subsidence occurs in many alluvial depositional environments, causing substantial socio-economic losses. Thick aquifers with interbedding or lens-structured clay can contribute significantly to compaction. The poromechanism of aquifer compaction is usually complicated, and its spatial variation is poorly understood, inhibiting our ability to fully explain the region-wide nature of groundwater-exploitation-induced land subsidence. In this study, we explore the poromechanism of aquifer deformation in the Choushui River alluvial fan, Taiwan. Groundwater level and multi-layer compaction data were collected for analyses. Elastic, plastic, and viscous characteristics all appear in the deformation data to various extents. A visco-elasto-plastic (VEP) model composed of a visco-elastic set and a visco-plastic set in series, which are associated with different viscous dampers, is proposed to model the deformation. Compared with existing models, the proposed model is superior in terms of simulating compaction as well as its applicability and versatility. The proposed VEP model is applied to observation wells in the proximal, middle, and distal fans of the Choushui River alluvial fan to explore the spatial variation in the poromechanical properties. The results show that the Young's modulus of the elastic spring increases with depth and with the distance from the distal fan to the proximal fan. The Young's modulus of the plastic element decreases with depth. The system response factor of the visco-plastic set decreases with depth and with the distance from the distal fan to the proximal fan. Aquifer recovery incapability increases with depth. Both the trend and dynamic fluctuations in compaction for the Choushui River alluvial fan are well captured by the proposed VEP model, which is essential for assessing long-term land and water resource management and evaluating potential short-term threats to infrastructure caused by seasonal subsidence.

GPS Interferometric Reflectometry Reveals Cyclic Elevation Changes in Thaw and Freezing Seasons in a Permafrost Area (Barrow, Alaska)

AbstractGround surface over permafrost area undergoes seasonal subsidence and uplift caused by the annual thawing and freezing of the active layer. Applying the Global Positioning System (GPS) interferometric reflectometry technique to the signal‐to‐noise ratio data collected by a continuously operating GPS station in a permafrost area in Barrow, we retrieve the daily surface elevation changes on snow‐free days over a decade (2007–2016). Among these years, 2016 had the longest snow‐free season, offering the longest and most complete records of elevation changes. Use this year as an example, we show that the ground subsided in thaw season and then uplifted from September to early November (freezing season) with an amplitude of 5.1 ± 0.2 cm. We also develop a composite model that includes both thaw and freeze indices to characterize the cyclic movements. Our composite model effectively explains the observed cyclic elevation changes and could be used in other permafrost studies.

Thaw Subsidence of a Yedoma Landscape in Northern Siberia, Measured In Situ and Estimated from TerraSAR-X Interferometry

In permafrost areas, seasonal freeze-thaw cycles result in upward and downward movements of the ground. For some permafrost areas, long-term downward movements were reported during the last decade. We measured seasonal and multi-year ground movements in a yedoma region of the Lena River Delta, Siberia, in 2013–2017, using reference rods installed deep in the permafrost. The seasonal subsidence was 1.7 ± 1.5 cm in the cold summer of 2013 and 4.8 ± 2 cm in the warm summer of 2014. Furthermore, we measured a pronounced multi-year net subsidence of 9.3 ± 5.7 cm from spring 2013 to the end of summer 2017. Importantly, we observed a high spatial variability of subsidence of up to 6 cm across a sub-meter horizontal scale. In summer 2013, we accompanied our field measurements with Differential Synthetic Aperture Radar Interferometry (DInSAR) on repeat-pass TerraSAR-X (TSX) data from the summer of 2013 to detect summer thaw subsidence over the same study area. Interferometry was strongly affected by a fast phase coherence loss, atmospheric artifacts, and possibly the choice of reference point. A cumulative ground movement map, built from a continuous interferogram stack, did not reveal a subsidence on the upland but showed a distinct subsidence of up to 2 cm in most of the thermokarst basins. There, the spatial pattern of DInSAR-measured subsidence corresponded well with relative surface wetness identified with the near infra-red band of a high-resolution optical image. Our study suggests that (i) although X-band SAR has serious limitations for ground movement monitoring in permafrost landscapes, it can provide valuable information for specific environments like thermokarst basins, and (ii) due to the high sub-pixel spatial variability of ground movements, a validation scheme needs to be developed and implemented for future DInSAR studies in permafrost environments.

Monitoring the Response of Roads and Railways to Seasonal Soil Movement with Persistent Scatterers Interferometry over Six UK Sites

Road and rail networks provide critical support for society, yet they can be degraded by seasonal soil movements. Currently, few transport network operators monitor small-scale soil movement, but understanding the conditions contributing to infrastructure failure can improve network resilience. Persistent Scatterers Interferometry (PSI) is a remote sensing technique offering the potential for near real-time ground movement monitoring over wide areas. This study tests the use of PSI for monitoring the response of major roads, minor roads, and railways to ground movement across six study sites in England, using Sentinel 1 data in VV polarisation in ascending orbit. Some soils are more stable than others—a national soil map was used to quantify the relationships between infrastructure movement and major soil groups. Vertical movement of transport infrastructure is a function of engineering design, soil properties, and traffic loading. Roads and railways built on soil groups prone to seasonal water-logging (Ground-water Gley soils, Surface-water Gley soils, Pelosols, and Brown soils) demonstrated seasonal subsidence and heave, associated with an increased risk of infrastructure degradation. Roads and railways over Podzolic soils demonstrated relative stability. Railways on Peat soils exhibited the most extreme continual subsidence of up to 7.5 mm year−1. Limitations of this study include the short observation period (~13 months, due to satellite data availability) and the regional scale of the soil map—mapping units contain multiple soil types with different ground movement potentials. Future use of a higher resolution soil map over a longer period will advance this research. Nevertheless, this study demonstrates the viability of PSI as a technique for measuring both seasonal soil-related ground movement and the associated impacts on road and rail infrastructure.

Freeze/Thaw-Induced Deformation Monitoring and Assessment of the Slope in Permafrost Based on Terrestrial Laser Scanner and GNSS

Most previous studies of the Qinghai-Tibet engineering corridor (QTEC) have focused on the impacts of climate change on thaw-induced slope failures, whereas few have considered freeze-induced slope failures. Terrestrial laser scanning was used in combination with global navigation satellite systems to monitor three-dimensional surface changes between 2014 and 2015 on the slope of permafrost in the QTEC, which experienced two thawing periods and a freezing period. Soil temperature and moisture sensors were also deployed at 11 depths to reveal the hydrological–thermal dynamics of the active layer. We analyzed scanned surface changes in the slope based on comparisons of multi-temporal point cloud data to determine how the hydrological–thermal process affected active layer deformation during freeze–thaw cycles, thereby comprehensively quantifying the surface deformation. During the two thawing periods, the major structure of the slope exhibited subsidence trends, whereas the major structure of the slope had an uplift trend in the freezing period. The seasonal subsidence trend was caused by thaw settlement and the seasonal uplift trend was probably due to frost heaving. This occurred mainly because the active layer and the upper permafrost underwent a phase transition due to heat transfer. The ground movements occurred approximately in the soil temperature conduction direction between the top of the soil and the permafrost table. The elevation deformation range was mainly −0.20 m to 0.20 m. Surface volume increases with heaving after freezing could have compensated for the loss of thawing twice and still led to the upward swelling of the slope. Thus, this type of slope in permafrost is dominated by frost heave. Deformation characteristics of the slope will support enhanced decision making regarding the implementation of remote sensing and hydrological–thermal measurement technologies to monitor changes in the slopes in permafrost adjacent to engineering corridors, thereby improving the understanding and assessment of hazards.