scholarly journals Seasonal InSAR Displacements Documenting the Active Layer Freeze and Thaw Progression in Central-Western Spitsbergen, Svalbard

2021 ◽  
Vol 13 (15) ◽  
pp. 2977
Author(s):  
Line Rouyet ◽  
Lin Liu ◽  
Sarah Marie Strand ◽  
Hanne Hvidtfeldt Christiansen ◽  
Tom Rune Lauknes ◽  
...  
Keyword(s):  
Time Series ◽  
Active Layer ◽  
Composite Index ◽  
Ground Surface ◽  
Western Coast ◽  
Thermal Dynamics ◽  
Index Model ◽  
Synthetic Aperture Radar Interferometry ◽  
Freeze And Thaw ◽  
Ground Conditions

In permafrost areas, the active layer undergoes seasonal frost heave and thaw subsidence caused by ice formation and melting. The amplitude and timing of the ground displacement cycles depend on the climatic and ground conditions. Here we used Sentinel-1 Synthetic Aperture Radar Interferometry (InSAR) to document the seasonal displacement progression in three regions of Svalbard. We retrieved June–November 2017 time series and identified thaw subsidence maxima and their timing. InSAR measurements were compared with a composite index model based on ground surface temperature. Cyclic seasonal patterns are identified in all areas, but the timing of the displacement progression varies. The subsidence maxima occurred later on the warm western coast (Kapp Linné and Ny-Ålesund) compared to the colder interior (Adventdalen). The composite index model is generally able to explain the observed patterns. In Adventdalen, the model matches the InSAR time series at the location of the borehole. In Kapp Linné and Ny-Ålesund, larger deviations are found at the pixel-scale, but km or regional averaging improves the fit. The study highlights the potential for further development of regional InSAR products to represent the cyclic displacements in permafrost areas and infer the active layer thermal dynamics.

Seasonal patterns of coupled flow in the active layer at three sites in northwest North America

1997 ◽  
Vol 34 (5) ◽  
pp. 667-678 ◽  
Author(s):  
Kenneth M. Hinkel ◽  
Samuel I. Outcalt ◽  
Alan E. Taylor
Keyword(s):  
Time Series ◽  
Soil Water ◽  
Active Layer ◽  
Electric Potential ◽  
Soil Column ◽  
Ground Surface ◽  
Summer Precipitation ◽  
Solute Concentration ◽  
Conductive Heat ◽  
Coupled Flow

Vertical arrays of temperature and electric-potential probes were installed in the upper soil at sites along the Mackenzie River valley and on the North Slope of Alaska. Time series were obtained at subdiurnal frequencies throughout the year in the active layer and upper permafrost. If the data acquisition system is properly configured, the time series can be used to infer soil physiochemical processes. The electric potential develops primarily in response to soil water solute concentration gradients in the soil column, and is a crude surrogate of the soil water electrolytic conductivity. Summer precipitation can cause rapid penetration of the thaw front when percolating rainwater, warmed at the ground surface, carries sensible heat downward to the thawing front. Rates of warming at depth occur significantly faster than those typical of conductive heat transfer. In early winter, as the freezing front penetrates downward toward the permafrost table, ions are excluded from the ice and concentrated in the intermediate unfrozen zone. Nearly instantaneous warming of the active layer is triggered by spring snowmelt. At Happy Valley in northern Alaska, temperatures at the 29 cm depth rise from −7 to −3 °C in 1 h. For several hours during this event, the temperature at 29 cm is warmer than that at regions both above and below, producing a strong thermal inversion. Time series of electric potential, or a surrogate derived from electric potential, suggest rapid transport of meltwater from the snowpack to depth, probably through soil cracks. Serial events hasten active-layer warming by 1–2 weeks.

scholarly journals Freeze-Thaw Deformation Cycles and Temporal-Spatial Distribution of Permafrost along the Qinghai-Tibet Railway Using Multitrack InSAR Processing

2021 ◽  
Vol 13 (23) ◽  
pp. 4744
Author(s):  
Jing Wang ◽  
Chao Wang ◽  
Hong Zhang ◽  
Yixian Tang ◽  
Wei Duan ◽  
...  
Keyword(s):  
Time Series ◽  
Large Scale ◽  
Surface Deformation ◽  
Anthropogenic Activities ◽  
Composite Index ◽  
Buffer Zone ◽  
Absolute Error ◽  
Tibet Plateau ◽  
Permafrost Region ◽  
Index Model

The Qinghai-Tibet Railway (QTR) is the railway with the highest elevation and longest distance in the world, spanning more than 1142 km from Golmud to Lhasa across the continuous permafrost region. Due to climate change and anthropogenic activities, geological disasters such as subsidence and thermal melt collapse have occurred in the QTR embankment. To conduct the large-scale permafrost monitoring and geohazard investigation along the QTR, we collected 585 Sentinel-1A images based on the composite index model using the multitrack time-series interferometry synthetic aperture radar (MTS-InSAR) method to retrieve the surface deformation over a 3.15 × 105 km2 area along the QTR. Meanwhile, a new method for permafrost distribution mapping based on InSAR time series deformation was proposed. Finally, the seasonal deformation map and a new map of permafrost distribution along the QTR from Golmud to Lhasa were obtained. The results showed that the estimated seasonal deformation range of the 10 km buffer zone along the QTR was −50–10 mm, and the LOS deformation rate ranged from −30 to 15 mm/yr. In addition, the deformation results were validated by leveling measurements, and the range of absolute error was between 0.1 and 4.62 mm. Most of the QTR was relatively stable. Some geohazard-prone sections were detected and analyzed along the QTR. The permafrost distribution results were mostly consistent with the simulated results of Zou’s method, based on the temperature at the top of permafrost (TTOP) model. This study reveals recent deformation characteristics of the QTR, and has significant scientific implications and applicational value for ensuring the safe operation of the QTR. Moreover, our method, based on InSAR results, provides new insights for permafrost classification on the Qinghai-Tibet Plateau (QTP).

scholarly journals GlobSim (v1.0): deriving meteorological time series for point locations from multiple global reanalyses

2019 ◽  
Vol 12 (11) ◽  
pp. 4661-4679 ◽  
Author(s):  
Bin Cao ◽  
Xiaojing Quan ◽  
Nicholas Brown ◽  
Emilie Stewart-Jones ◽  
Stephan Gruber
Keyword(s):  
Time Series ◽  
Land Surface ◽  
Ground Surface ◽  
Reanalysis Data ◽  
Meteorological Variables ◽  
Ensemble Simulations ◽  
Driving Time ◽  
Wide Range ◽  
Global Coverage ◽  
Uncertain Input

Abstract. Simulations of land-surface processes and phenomena often require driving time series of meteorological variables. Corresponding observations, however, are unavailable in most locations, even more so, when considering the duration, continuity and data quality required. Atmospheric reanalyses provide global coverage of relevant meteorological variables, but their use is largely restricted to grid-based studies. This is because technical challenges limit the ease with which reanalysis data can be applied to models at the site scale. We present the software toolkit GlobSim, which automates the downloading, interpolation and scaling of different reanalyses – currently ERA5, ERA-Interim, JRA-55 and MERRA-2 – to produce meteorological time series for user-defined point locations. The resulting data have consistent structure and units to efficiently support ensemble simulation. The utility of GlobSim is demonstrated using an application in permafrost research. We perform ensemble simulations of ground-surface temperature for 10 terrain types in a remote tundra area in northern Canada and compare the results with observations. Simulation results reproduced seasonal cycles and variation between terrain types well, demonstrating that GlobSim can support efficient land-surface simulations. Ensemble means often yielded better accuracy than individual simulations and ensemble ranges additionally provide indications of uncertainty arising from uncertain input. By improving the usability of reanalyses for research requiring time series of climate variables for point locations, GlobSim can enable a wide range of simulation studies and model evaluations that previously were impeded by technical hurdles in obtaining suitable data.

scholarly journals Research on forest terrain roughness as a source of dynamic action on the vehicle

2017 ◽  
Vol 63 (No. 8) ◽  
pp. 363-369
Author(s):  
Mikleš Milan ◽  
Helexa Milan ◽  
Mikleš Juraj
Keyword(s):  
Correlation Function ◽  
Spectral Density ◽  
Power Spectral Density ◽  
Ground Surface ◽  
Operating Conditions ◽  
Mobile Object ◽  
Object A ◽  
Power Spectral ◽  
Gneiss Granite ◽  
Ground Conditions

The issue of terrain conditions is very complex and its description is approached from different perspectives and with different objectives. Because it consists of the gathering of basic information for a mobile object, a wheeled forestry tractor, the terrain-vehicle approach was taken as the basis. Ground conditions are part of the operating conditions of wheeled forestry tractors. Uneven ground can be regarded as a source of vibration in the vehicle – towing truck. In this respect, given the random shape of the surface roughness, the solution to vibrations leads to a terrain correlation analysis in order to obtain a correlation function and power spectral density of the ground surface. Scanning of the ground micro-profile was performed using a device for quick terrain scanning, which from the mechanical aspect consists of a towing vehicle and a measuring carriage. Correlation function and power spectral density are the evaluation based on ground micro-profile measurements and the results of calculations. Measurements of forest terrain (road) micro-profile were done in the area of Little Fatra and Little Carpathians in Slovakia. In geological terms, the measurements were done in an area with the occurrence of gneiss, granite, limestone and flysch. No measurements were performed in a sandy area.

Geotechnical Lessons Learned From Nineteen Railway Trenchless Crossings During Construction of a Transmission Pipeline

2020 ◽  
Author(s):  
Jack Park ◽  
Lisa Wheeler ◽  
Katherine Johnston ◽  
Mike Statters
Keyword(s):  
Ground Surface ◽  
Leading Edge ◽  
Lessons Learned ◽  
Ground Movement ◽  
Financial Loss ◽  
Canadian Prairies ◽  
Soil Plug ◽  
Ground Conditions ◽  
Transmission Pipeline ◽  
Movement Monitoring

Abstract When new pipelines are constructed, they often cross existing major infrastructure, such as railways. To reduce potential service disruption, it is a common practice to complete these crossings using trenchless technologies. Without proper methods and oversight in planning and construction, there may be serious safety and financial implications to the operators of the railways and the public due to unacceptable settlement or heave. If movement tolerances are exceeded, the schedule and financial loss to the railway operators could be in the millions of dollars per day. Recent construction of a new pipeline across the Canadian prairies implemented ground movement monitoring plans at 19 trenchless railway crossings in order to reduce the potential for impact to the track and railway operations. The specifics of the plan varied for each site and were based on the expected ground conditions, as well as permit requirements from the various railway operators, but typically included ground movement monitoring surveys, observation of the cuttings, recommendations for a soil plug at the leading edge of the bore casing, and frequent communication with both the railway operators and the contractors. For all crossings, the expected soil and groundwater conditions were obtained from pre-construction boreholes and confirmed during excavation of the bore bays. Based on the expected ground conditions, appropriate soil plug lengths, if required, were recommended. In general, fine-grained clay/silt-dominated soils needed minimal to no soil plug in order to minimize the potential for ground heave, while coarser-grained sand-dominated soils needed a longer soil plug in order to reduce the potential for “flowing soil” which would cause over excavation along the bore path. Prior to boring, surface monitoring points were established along the tracks to monitor for changes in the ground surface elevation. Additional subsurface points were installed for crossings where the potential for over excavation was higher. These monitoring points were surveyed before, throughout, and following completion of construction, and the frequency of the surveys was increased when the movement was nearing or exceeding specified tolerances. The effort to monitor and reduce the potential for ground movement was a coordinated effort between the geotechnical engineers, railway operators, and construction contractors. The purpose of this paper is to present the lessons learned from the 19 trenchless railway crossings, including the challenges and successes. Recommendations for ground movement monitoring are also provided to help guide railway operators, design and geotechnical engineers, and contractors during the construction of future trenchless pipeline crossings of railway infrastructure.

scholarly journals Advanced radar-interpretation of InSAR time series for mapping and characterization of geological processes

2011 ◽  
Vol 11 (3) ◽  
pp. 865-881 ◽  
Author(s):  
F. Cigna ◽  
C. Del Ventisette ◽  
V. Liguori ◽  
N. Casagli
Keyword(s):  
Time Series ◽  
Field Surveys ◽  
Synthetic Aperture Radar Interferometry ◽  
Geological Processes ◽  
Multi Temporal ◽  
Under Sampling ◽  
Temporal Measures

Abstract. We present a new post-processing methodology for the analysis of InSAR (Synthetic Aperture Radar Interferometry) multi-temporal measures, based on the temporal under-sampling of displacement time series, the identification of potential changes occurring during the monitoring period and, eventually, the classification of different deformation behaviours. The potentials of this approach for the analysis of geological processes were tested on the case study of Naro (Italy), specifically selected due to its geological setting and related ground instability of unknown causes that occurred in February 2005. The time series analysis of past (ERS1/2 descending data; 1992–2000) and current (RADARSAT-1 ascending data; 2003–2007) ground movements highlighted significant displacement rates (up to 6 mm yr−1) in 2003–2007, followed by a post-event stabilization. The deformational behaviours of instable areas involved in the 2005 event were also detected, clarifying typology and kinematics of ground instability. The urban sectors affected and unaffected by the event were finally mapped, consequently re-defining and enlarging the influenced area previously detected by field observations. Through the integration of InSAR data and conventional field surveys (i.e. geological, geomorphologic and geostructural campaigns), the causes of instability were finally attributed to tectonics.

Fluctuation complexity of agent-based financial time series model by stochastic Potts system

2015 ◽  
Vol 26 (11) ◽  
pp. 1550123 ◽  
Author(s):  
Weijia Hong ◽  
Jun Wang
Keyword(s):  
Time Series ◽  
Dynamic System ◽  
Financial Time Series ◽  
Composite Index ◽  
Time Series Model ◽  
Agent Based ◽  
Financial Time ◽  
System A ◽  
Challenging Tasks ◽  
Financial Research

Financial market is a complex evolved dynamic system with high volatilities and noises, and the modeling and analyzing of financial time series are regarded as the rather challenging tasks in financial research. In this work, by applying the Potts dynamic system, a random agent-based financial time series model is developed in an attempt to uncover the empirical laws in finance, where the Potts model is introduced to imitate the trading interactions among the investing agents. Based on the computer simulation in conjunction with the statistical analysis and the nonlinear analysis, we present numerical research to investigate the fluctuation behaviors of the proposed time series model. Furthermore, in order to get a robust conclusion, we consider the daily returns of Shanghai Composite Index and Shenzhen Component Index, and the comparison analysis of return behaviors between the simulation data and the actual data is exhibited.

scholarly journals A Hypothesis Test Method for Detecting Multifractal Scaling, Applied to Bitcoin Prices

2020 ◽  
Vol 13 (5) ◽  
pp. 104
Author(s):  
Chuxuan Jiang ◽  
Priya Dev ◽  
Ross A. Maller
Keyword(s):  
Time Series ◽  
Heavy Tails ◽  
Financial Time Series ◽  
Hypothesis Test ◽  
Composite Index ◽  
Test Method ◽  
Scaling Functions ◽  
Financial Time ◽  
Nasdaq Composite Index ◽  
Multifractal Scaling

Multifractal processes reproduce some of the stylised features observed in financial time series, namely heavy tails found in asset returns distributions, and long-memory found in volatility. Multifractal scaling cannot be assumed, it should be established; however, this is not a straightforward task, particularly in the presence of heavy tails. We develop an empirical hypothesis test to identify whether a time series is likely to exhibit multifractal scaling in the presence of heavy tails. The test is constructed by comparing estimated scaling functions of financial time series to simulated scaling functions of both an iid Student t-distributed process and a Brownian Motion in Multifractal Time (BMMT), a multifractal processes constructed in Mandelbrot et al. (1997). Concavity measures of the respective scaling functions are estimated, and it is observed that the concavity measures form different distributions which allow us to construct a hypothesis test. We apply this method to test for multifractal scaling across several financial time series including Bitcoin. We observe that multifractal scaling cannot be ruled out for Bitcoin or the Nasdaq Composite Index, both technology driven assets.

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