Measuring Anatolian plate velocity and strain with Sentinel-1 InSAR and GNSS data: implications for fault locking, seismic hazard, and crustal dynamics

2020 ◽  
Author(s):  
Jonathan Weiss ◽  
Richard Walters ◽  
Tim Wright ◽  
Yu Morishita ◽  
Milan Lazecky ◽  
...  
Keyword(s):  
Strain Rate ◽  
Large Scale ◽  
Surface Deformation ◽  
Active Regions ◽  
Earthquake Hazard ◽  
Ground Level ◽  
Surface Velocity ◽  
Strain Accumulation ◽  
Spatial Coverage ◽  
Gnss Data

<p>Geodetic measurements of small rates of interseismic crustal motion made at high spatial resolutions and over large areas are crucial for understanding the earthquake cycle, characterizing spatial variations in lithosphere rheology and fault frictional properties, illuminating the mechanics of large-scale continental deformation, and improving earthquake hazard models. The densification of Global Navigation Satellite System (GNSS) networks has provided an unprecedented view of the kinematics of deforming regions. However, large gaps in spatial coverage still hamper our ability to fully characterize patterns of surface deformation. Interferometric synthetic aperture radar (InSAR), and the Sentinel-1 (S-1) satellites in particular, have the potential to overcome this obstacle by providing spatially continuous measurements of surface motions, without instruments on the ground, with precision approaching that obtained from GNSS, and at a resolution of a few tens of meters. In order to manage and process the large data volumes produced by S-1, we have developed open-source, automated workflows to efficiently generate interferograms and line-of-sight (LOS) velocity fields. These outputs are valuable for a range of applications, from earthquake rapid-response to investigating human-induced ground-level changes. In this talk, we demonstrate our ability to measure plate-scale interseismic deformation using data from the first ~5 years of the S-1 mission. We estimate LOS velocities for the Anatolian microplate, an area encompassing ~800,000 km<sup>2</sup> and including the highly seismogenic North Anatolian Fault Zone (NAFZ). By combining S-1 InSAR and GNSS data, we create high-resolution surface velocity and strain rate fields for the region, which illuminate horizontal deformation patterns dominated by the westward motion of Anatolia relative to Eurasia, localized strain accumulation along the NAFZ, and rapid vertical signals associated with groundwater extraction. Relatively low levels of strain characterize other active regions including the East and Central Anatolian Fault Zones and the Western Anatolian Extensional Province. We find that GNSS data alone are insufficient for characterizing key details of the strain rate field that are critical for understanding the relationship between strain accumulation and release in earthquakes. We highlight two important results stemming from our work including probabilistic estimates of the recurrence times of earthquakes of varying magnitudes for the region and a new NAFZ locking distribution that shows close correspondence to the surface rupture extents of large 20<sup>th</sup> century earthquakes.</p>

Estimation of active layer thickness from modeling and InSAR deformation data at QTP

2020 ◽  
Author(s):  
Rongxing Li ◽  
Tong Hao ◽  
Ping Lu ◽  
Gang Qiao ◽  
Lemin Chen ◽  
...  
Keyword(s):  
Layer Thickness ◽  
Active Layer ◽  
Large Scale ◽  
Surface Deformation ◽  
Remote Sensing Data ◽  
Field Measurements ◽  
Active Layer Thickness ◽  
Quality Of Data ◽  
Spatial Coverage ◽  
Sbas Insar

<p>In context of global warming, permafrost, as an important component of cryosphere in the Qinghai-Tibetan Plateau (QTP) that is located in middle and low latitudes with a high radiation intensity of high Asia mountains, is particularly sensitive to climate changes. The active layer thickness (ALT) in a permafrost area is an important index to indicate its stability. Traditional methods for measuring ALT in QTP mainly rely on ground-based field surveys and accordingly are extremely time- consuming and labor-intensive. The field works provide a good quality of data at a single site, however, such measurements are limited in spatial coverage and difficult for multi-temporal acquisitions. In addition, the harsh environment in QTP is not suitable for large-scale field measurements. In this study, the ALT of permafrost in QTP is estimated using modelling and remote sensing data. Particularly, the surface deformation on permafrost, as detected by the long-term InSAR technique, is considered as an input to the inversion model of ALT. The time-series deformation results over an experimental permafrost area were obtained by the SBAS-InSAR technique. Then, combined with the soil characteristics of soil moisture and soil thermal conductivity in the Stefan model, the melting thickness was estimated. Finally, the resulting ALT was tested and verified against a set of in-situ borehole measurements of depth-temperature.</p>

Mapping tectonic strain in the central Alpine-Himalayan Belt with Sentinel-1 InSAR and GNSS observations

2021 ◽  
Author(s):  
Chris Rollins ◽  
Tim Wright ◽  
Jonathan Weiss ◽  
Andrew Hooper ◽  
Richard Walters ◽  
...  
Keyword(s):  
High Resolution ◽  
Seismic Hazard ◽  
Strain Rate ◽  
Crustal Deformation ◽  
Large Scale ◽  
Surface Deformation ◽  
Processing System ◽  
Temporal Sampling ◽  
Himalayan Belt ◽  
Automated Processing

<p>Geodetic measurements of crustal deformation provide crucial constraints on a region’s tectonics, geodynamics and seismic hazard. However, such geodetic constraints have traditionally been hampered by poor spatial and/or temporal sampling, which can result in ambiguities about how the lithosphere accommodates strain in space and time, and therefore where and how often earthquakes might occur. High-resolution surface deformation maps address this limitation by imaging (rather than presuming or modelling) where and how deformation takes place. These maps are now within reach for the Alpine-Himalayan Belt thanks to the COMET-LiCSAR InSAR processing system, which performs large-scale automated processing and time-series analysis of Sentinel-1 InSAR data. Expanding from our work focused on Anatolia, we are combining LiCSAR products with GNSS data to generate high-resolution maps of tectonic strain rates across the central Alpine-Himalayan Belt. Then, assuming that the buildup rate of seismic moment (deficit) from this geodetically-derived strain is balanced over the long term by the rate of moment release in earthquakes, we pair these strain rate maps with seismic catalogs to estimate the recurrence intervals of large, moderate and small earthquakes throughout the region. We also use arguments from dislocation modeling to identify two key signatures of a locked fault in a strain rate field, allowing us to convert the strain maps to “effective fault maps” and assess the contribution of individual fault systems to crustal deformation and seismic hazard. Finally, we address how to expand these approaches to the Alpine-Himalaya Belt as a whole.</p>

scholarly journals Crustal strain-rate fields estimated from GNSS data with a Bayesian approach and its correlation to seismic activity in Mainland China

2021 ◽  
pp. 229003
Author(s):  
Ziyao Xiong ◽  
Jiancang Zhuang ◽  
Shiyong Zhou ◽  
Mitsuhiro Matsu'ura ◽  
Ming Hao ◽  
...  
Keyword(s):  
Strain Rate ◽  
Bayesian Approach ◽  
Seismic Activity ◽  
Mainland China ◽  
Crustal Strain ◽  
Gnss Data

scholarly journals Elucidating the Onset of Plasticity in Sliding Contacts Using Differential Computational Orientation Tomography

2021 ◽  
Vol 69 (3) ◽  
Author(s):  
S. J. Eder ◽  
P. G. Grützmacher ◽  
M. Rodríguez Ripoll ◽  
J. F. Belak
Keyword(s):  
Grain Boundary ◽  
Large Scale ◽  
Surface Deformation ◽  
Boundary Migration ◽  
Material Design ◽  
Lattice Rotation ◽  
Time Resolved ◽  
Near Surface ◽  
Color Saturation ◽  
Dynamics Simulations

Abstract Depending on the mechanical and thermal energy introduced to a dry sliding interface, the near-surface regions of the mated bodies may undergo plastic deformation. In this work, we use large-scale molecular dynamics simulations to generate “differential computational orientation tomographs” (dCOT) and thus highlight changes to the microstructure near tribological FCC alloy surfaces, allowing us to detect subtle differences in lattice orientation and small distances in grain boundary migration. The analysis approach compares computationally generated orientation tomographs with their undeformed counterparts via a simple image analysis filter. We use our visualization method to discuss the acting microstructural mechanisms in a load- and time-resolved fashion, focusing on sliding conditions that lead to twinning, partial lattice rotation, and grain boundary-dominated processes. Extracting and laterally averaging the color saturation value of the generated tomographs allows us to produce quantitative time- and depth-resolved maps that give a good overview of the progress and severity of near-surface deformation. Corresponding maps of the lateral standard deviation in the color saturation show evidence of homogenization processes occurring in the tribologically loaded microstructure, frequently leading to the formation of a well-defined separation between deformed and undeformed regions. When integrated into a computational materials engineering framework, our approach could help optimize material design for tribological and other deformation problems. Graphic Abstract .

scholarly journals Reservoir-Induced Land Deformation: Case Study from the Grand Ethiopian Renaissance Dam

2021 ◽  
Vol 13 (5) ◽  
pp. 874
Author(s):  
Yu Chen ◽  
Mohamed Ahmed ◽  
Natthachet Tangdamrongsub ◽  
Dorina Murgulet
Keyword(s):  
Land Surface ◽  
Large Scale ◽  
Surface Deformation ◽  
Vertical Displacement ◽  
Nile River ◽  
Reservoir Volume ◽  
Novel Approach ◽  
Land Deformation ◽  
Large Scale Land ◽  
The Impact

The Nile River stretches from south to north throughout the Nile River Basin (NRB) in Northeast Africa. Ethiopia, where the Blue Nile originates, has begun the construction of the Grand Ethiopian Renaissance Dam (GERD), which will be used to generate electricity. However, the impact of the GERD on land deformation caused by significant water relocation has not been rigorously considered in the scientific research. In this study, we develop a novel approach for predicting large-scale land deformation induced by the construction of the GERD reservoir. We also investigate the limitations of using the Gravity Recovery and Climate Experiment Follow On (GRACE-FO) mission to detect GERD-induced land deformation. We simulated three land deformation scenarios related to filling the expected reservoir volume, 70 km3, using 5-, 10-, and 15-year filling scenarios. The results indicated: (i) trends in downward vertical displacement estimated at −17.79 ± 0.02, −8.90 ± 0.09, and −5.94 ± 0.05 mm/year, for the 5-, 10-, and 15-year filling scenarios, respectively; (ii) the western (eastern) parts of the GERD reservoir are estimated to move toward the reservoir’s center by +0.98 ± 0.01 (−0.98 ± 0.01), +0.48 ± 0.00 (−0.48 ± 0.00), and +0.33 ± 0.00 (−0.33 ± 0.00) mm/year, under the 5-, 10- and 15-year filling strategies, respectively; (iii) the northern part of the GERD reservoir is moving southward by +1.28 ± 0.02, +0.64 ± 0.01, and +0.43 ± 0.00 mm/year, while the southern part is moving northward by −3.75 ± 0.04, −1.87 ± 0.02, and −1.25 ± 0.01 mm/year, during the three examined scenarios, respectively; and (iv) the GRACE-FO mission can only detect 15% of the large-scale land deformation produced by the GERD reservoir. Methods and results demonstrated in this study provide insights into possible impacts of reservoir impoundment on land surface deformation, which can be adopted into the GERD project or similar future dam construction plans.

scholarly journals Deterministic and Empirical Approach for Millimeter-Wave Complex Outdoor Smart Parking Solution Deployments

Sensors ◽  
2021 ◽  
Vol 21 (12) ◽  
pp. 4112
Author(s):  
Fidel Alejandro Rodríguez-Corbo ◽  
Leyre Azpilicueta ◽  
Mikel Celaya-Echarri ◽  
Peio Lopez-Iturri ◽  
Ana V. Alejos ◽  
...  
Keyword(s):  
Large Scale ◽  
Radio Channel ◽  
Path Loss ◽  
Ground Level ◽  
Directional Antennas ◽  
Scale Parameters ◽  
Parking Lot ◽  
Smart Parking ◽  
Wireless Communications Systems

The characterization of different vegetation/vehicle densities and their corresponding effects on large-scale channel parameters such as path loss can provide important information during the deployment of wireless communications systems under outdoor conditions. In this work, a deterministic analysis based on ray-launching (RL) simulation and empirical measurements for vehicle-to-infrastructure (V2I) communications for outdoor parking environments and smart parking solutions is presented. The study was carried out at a frequency of 28 GHz using directional antennas, with the transmitter raised above ground level under realistic use case conditions. Different radio channel impairments were weighed in, considering the progressive effect of first, the density of an incremental obstructed barrier of trees, and the effect of different parked vehicle densities within the parking lot. On the basis of these scenarios, large-scale parameters and temporal dispersion characteristics were obtained, and the effect of vegetation/vehicle density changes was assessed. The characterization of propagation impairments that different vegetation/vehicle densities can impose onto the wireless radio channel in the millimeter frequency range was performed. Finally, the results obtained in this research can aid communication deployment in outdoor parking conditions.

scholarly journals Atmospheric Circulation Effects on Wind Speed Variability at Turbine Height

2007 ◽  
Vol 46 (4) ◽  
pp. 445-456 ◽  
Author(s):  
Katherine Klink
Keyword(s):  
Wind Speed ◽  
Pressure Gradient ◽  
Large Scale ◽  
Ground Level ◽  
The Arctic ◽  
Circulation Index ◽  
Regression Equations ◽  
Change Models ◽  
Wind Speeds ◽  
The North

Abstract Mean monthly wind speed at 70 m above ground level is investigated for 11 sites in Minnesota for the period 1995–2003. Wind speeds at these sites show significant spatial and temporal coherence, with prolonged periods of above- and below-normal values that can persist for as long as 12 months. Monthly variation in wind speed primarily is determined by the north–south pressure gradient, which captures between 22% and 47% of the variability (depending on the site). Regression on wind speed residuals (pressure gradient effects removed) shows that an additional 6%–15% of the variation can be related to the Arctic Oscillation (AO) and Niño-3.4 sea surface temperature (SST) anomalies. Wind speeds showed little correspondence with variation in the Pacific–North American (PNA) circulation index. The effect of the strong El Niño of 1997/98 on the wind speed time series was investigated by recomputing the regression equations with this period excluded. The north–south pressure gradient remains the primary determinant of mean monthly 70-m wind speeds, but with 1997/98 removed the influence of the AO increases at nearly all stations while the importance of the Niño-3.4 SSTs generally decreases. Relationships with the PNA remain small. These results suggest that long-term patterns of low-frequency wind speed (and thus wind power) variability can be estimated using large-scale circulation features as represented by large-scale climatic datasets and by climate-change models.

Seeding metrics for image velocimetry performances in rivers

2021 ◽  
Author(s):  
Silvano Fortunato Dal Sasso ◽  
Alonso Pizarro ◽  
Sophie Pearce ◽  
Ian Maddock ◽  
Matthew T. Perks ◽  
...  
Keyword(s):  
Spatial Distribution ◽  
Optical Sensors ◽  
Large Scale ◽  
Surface Flow ◽  
Surface Velocity ◽  
Seeding Density ◽  
Earth System ◽  
Science Data ◽  
Image Velocimetry ◽  
Hydraulic Conditions

<p>Optical sensors coupled with image velocimetry techniques are becoming popular for river monitoring applications. In this context, new opportunities and challenges are growing for the research community aimed to: i) define standardized practices and methodologies; and ii) overcome some recognized uncertainty at the field scale. At this regard, the accuracy of image velocimetry techniques strongly depends on the occurrence and distribution of visible features on the water surface in consecutive frames. In a natural environment, the amount, spatial distribution and visibility of natural features on river surface are continuously challenging because of environmental factors and hydraulic conditions. The dimensionless seeding distribution index (SDI), recently introduced by Pizarro et al., 2020a,b and Dal Sasso et al., 2020, represents a metric based on seeding density and spatial distribution of tracers for identifying the best frame window (FW) during video footage. In this work, a methodology based on the SDI index was applied to different study cases with the Large Scale Particle Image Velocimetry (LSPIV) technique. Videos adopted are taken from the repository recently created by the COST Action Harmonious, which includes 13 case study across Europe and beyond for image velocimetry applications (Perks et al., 2020). The optimal frame window selection is based on two criteria: i) the maximization of the number of frames and ii) the minimization of SDI index. This methodology allowed an error reduction between 20 and 39% respect to the entire video configuration. This novel idea appears suitable for performing image velocimetry in natural settings where environmental and hydraulic conditions are extremely challenging and particularly useful for real-time observations from fixed river-gauged stations where an extended number of frames are usually recorded and analyzed.</p><p> </p><p><strong>References </strong></p><p>Dal Sasso S.F., Pizarro A., Manfreda S., Metrics for the Quantification of Seeding Characteristics to Enhance Image Velocimetry Performance in Rivers. Remote Sensing, 12, 1789 (doi: 10.3390/rs12111789), 2020.</p><p>Perks M. T., Dal Sasso S. F., Hauet A., Jamieson E., Le Coz J., Pearce S., …Manfreda S, Towards harmonisation of image velocimetry techniques for river surface velocity observations. Earth System Science Data, https://doi.org/10.5194/essd-12-1545-2020, 12(3), 1545 – 1559, 2020.</p><p>Pizarro A., Dal Sasso S.F., Manfreda S., Refining image-velocimetry performances for streamflow monitoring: Seeding metrics to errors minimisation, Hydrological Processes, (doi: 10.1002/hyp.13919), 1-9, 2020.</p><p>Pizarro A., Dal Sasso S.F., Perks M. and Manfreda S., Identifying the optimal spatial distribution of tracers for optical sensing of stream surface flow, Hydrology and Earth System Sciences, 24, 5173–5185, (10.5194/hess-24-5173-2020), 2020.</p>

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