The northeastern margin is a natural experimental field for studying crustal extrusion and expansion mechanisms. The accurate crustal deformation pattern is a key point in the analysis of regional ...deformation mechanisms and seismic hazard research and judgment. In this paper, the present-day GPS velocity field on the northeastern margin of the Tibetan Plateau was obtained from encrypted GPS observations around the Haiyuan–Liupanshan fault zone, combined with GPS observations on the northeastern margin of the Tibetan Plateau from 2010 to 2020. Firstly, we divided the study area into three relatively independent blocks: the ORDOS block, Alxa block, and Lanzhou block; secondly, the accurate fault distribution of the Haiyuan–Liupanshan fault zone was taken into account to obtain the optimal inversion model; finally, using the block and fault back-slip dislocation model, the inversion obtained the slip rate distribution, locking depth, and slip deficit rate of each fault. The results indicate that the Laohushan Fault and Haiyuan Fault are dominated by the left-lateral strike-slip, while the Liupanshan Fault is dominated by the thrust dip-slip, and the Guguan–Baoji Fault has both left-lateral strike-slip and thrust dip-slip components. The maximum locking depths of the Laohushan Fault, Haiyuan Fault, Liupanshan Fault, and Guguan–Baoji Fault are 5 km, 13 km, 15 km, and 10 km, respectively, and the locking of the Haiyuan Fault is strong in the middle section and weak in the eastern and western section. The Haiyuan Fault is still in the post-earthquake stress adjustment stage. The slip deficit rate decays from 3.6 mm/yr to 1.8 mm/yr from west to east along the fault zone. Combined with geological and historical seismic data, the results suggest that the mid-long-term seismic risk in the Liupanshan Fault is high.
Full text
Available for:
IZUM, KILJ, NUK, PILJ, PNG, SAZU, UL, UM, UPUK
The Crustal Movement Observation Network of China (CMONOC) has begun receiving BeiDou Navigation Satellite System (BDS) observations since 2015, and accumulated more than 2.5 years of data. BDS ...observations has been widely applied in many fields, and long-term continuous data provide a new strategy for the study of crustal deformation in China. This paper focuses on the evaluation of BDS positioning performance and its potential application on crustal deformation in CMONOC. According to the comparative analysis on multipath delay (MPD) and signal to noise ratio (SNR) between BDS and GPS data, the data quality of BDS is at the same level with GPS measurements in COMONC. The spatial distribution of BDS positioning accuracy evaluated as the root mean square (RMS) of daily residual position time series on horizontal component is latitude-dependent, declining with the increasing of station latitude, while the vertical one is randomly distributed in China. The mean RMS of BDS position residual time series is 7 mm and 22 mm on horizontal and vertical components, respectively, and annual periodicity in position time series can be identified by BDS data. In view of the accuracy of BDS positioning, there are no systematic differences between GPS and BDS results. Based on time series analysis with data volume being 2.5 years, the noise characteristics of BDS daily position time series is time-correlated and corresponding noise is white plus flicker noise model, and the derived mean RMS of the BDS velocities is 1.2, 1.5, and 4.1 mm/year on north, east, and up components, respectively. The imperfect performance of BDS positioning relative to GPS is likely attributed to the relatively low accuracy of BDS ephemeris, and the sparse amount of MEO satellites distribution in the BDS constellation. It is expectable to study crustal deformation in CMONOC by BDS with the gradual maturity of its constellation and the accumulation of observations.
Full text
Available for:
IZUM, KILJ, NUK, PILJ, PNG, SAZU, UL, UM, UPUK
The southeastern margin of the Tibetan Plateau is one of the most significant deforming regions in China, and even the world, leading to an urgent need to assess the potential earthquake hazard along ...its complex geological structures. The moment deficit estimate is a well-established way of assessing earthquake hazards in seismic zones. In this study, we derive an improved crustal deformation field for the southeastern margin of the Tibetan Plateau by using a new Global Positioning System (GPS) dataset that includes both the published and latest observations from the Crustal Movement Observation Network of China from 1998 to 2020. We employ the new GPS velocities to estimate two-dimensional strain rates in the southeastern Tibetan Plateau, including the derivatives of maximum shear strain rates. The geodetic strain rates are used to calculate the geodetic moment accumulation rates, which are then compared with the seismic moment release derived from historical earthquakes over the past hundreds of years at 14 seismic zones. Our results reveal that the crustal strain accumulation is substantially released by earthquakes occurring in the Xianshuihe, Xiaojiang, and Chuxiong–Jianshui zones. For the remaining seismogenic zones, the geodetic moment rates are found to be remarkably higher than the seismic rates, with ratios of around 2.1–7.8. In the Litang–Muli, Ganzi–Yushu, Songpan–Longmenshan, western Yunnan, and Anninghe zones, the seismic moment rate deficits are estimated to be 3.6 × 10
17
Nm/year, 15.5 × 10
17
Nm/year, 20.2 × 10
17
Nm/year, 11.0 × 10
17
Nm/year, and 21.8 × 10
17
Nm/year, respectively, indicating a possible high level of seismic hazard in the future. However, aseismic processes such as creep and ductile deformation might modulate a large proportion of the total strain accumulation in the northwestern Yunnan zone, possibly accounting for the discrepancies between the estimated geodetic and seismic moments and thus making the assessment of earthquake potential quite vague. This study demonstrates that insightful comparison of geodetic and seismic moments could be beneficial for assessing earthquake hazards on the southeastern margin of the Tibetan Plateau.
Full text
Available for:
DOBA, EMUNI, FIS, FZAB, GEOZS, GIS, IJS, IMTLJ, IZUM, KILJ, KISLJ, MFDPS, NLZOH, NUK, OILJ, PILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, UILJ, UKNU, UL, UM, UPUK, VKSCE, ZAGLJ
We analyzed daily displacement time series from 34 continuous GPS stations in Nepal and 5 continuous GPS stations in South Tibet, China, and extracted the first 4.8 years of postseismic motion after ...the 2015 Mw7.8 Gorkha earthquake. With the longer duration GPS observations, we find that postseismic displacements mainly exhibit southward and uplift motion. To study the postseismic afterslip and viscoelastic relaxation, we built a 3-D spherical finite-element model (FEM) with heterogeneous material properties and surface topography across the Himalayan range, accounting for the strong variations in material properties and surface elevation along the central Himalayan arc. On the basis of the FEM, we reveal that the predicted viscoelastic relaxation of cm level moves southward to the north of the Gorkha earthquake rupture, but in an opposite direction to the observed postseismic deformation in the south; the postseismic deformation excluding viscoelastic relaxation is well explained by afterslip downdip of the coseismic rupture. The afterslip is dominant during 4.8 years after the 2015 Mw7.8 Gorkha earthquake; the contribution by the viscoelastic relaxation gradually increases slightly. The lack of slip on a shallow portion and western segment of the MHT during and after the 2015 Gorkha earthquake implies continued seismic hazard in the future.
We installed 10 continuous Global Positioning System (GPS) stations on the northeast margin of the Tibetan Plateau at the end of 2012, in order to qualitatively investigate strain accumulation across ...the Liupanshan Fault (LPSF). We integrated our newly built stations with 48 other existing GPS stations to provide new insights into three-dimensional tectonic deformation. We employed white plus flicker noise model as a statistical model to obtain realistic velocities and corresponding uncertainties in the ITRF2014 and Ordos-fixed reference frame. The total velocity decrease from northwest to southeast in the Longxi Block (LXB) was 5.3 mm/yr within the range of 200 km west of the LPSF on the horizontal component. The first-order characteristic of the vertical crustal deformation was uplift for the northeastern margin of the Tibetan Plateau. The uplift rates in the LXB and the Ordos Block (ORB) were 1.0 and 2.0 mm/yr, respectively. We adopted an improved spherical wavelet algorithm to invert for multiscale strain rates and rotation rates. Multiscale strain rates showed a complex crustal deformation pattern. A significant clockwise rotation of about 30 nradians/yr (10−9 radians/year) was identified around the Dingxi. Localized strain accumulation was determined around the intersectional region between the Haiyuan Fault (HYF) and the LPSF. The deformation pattern across the LFPS was similar to that of the Longmengshan Fault (LMSF) before the 2008 Wenchuan MS 8.0 earthquake. Furthermore, according to the distributed second invariant of strain rates at different spatial scale, strain partitioning has already spatially localized along the Xiaokou–Liupanshan–Longxian–Baoji fault belt (XLLBF). The tectonic deformation and localized strain buildup together with seismicity imply a high probability for a potential earthquake in this zone.
Full text
Available for:
IZUM, KILJ, NUK, PILJ, PNG, SAZU, UL, UM, UPUK
Global navigation satellite system (GNSS) signals are affected by refraction when traveling through the troposphere, which result in tropospheric delay. Generally, the tropospheric delay is estimated ...as an unknown parameter in GNSS data processing. With the increasing demand for GNSS real-time applications, high-precision tropospheric delay augmentation information is vital to speed up the convergence of PPP. In this research, we estimate the zenith tropospheric delay (ZTD) from 2018 to 2019 by static precise point positioning (PPP) using the fixed position mode; GNSS observations were obtained from the National Geomatics Center of China (NGCC). Firstly, ZTD outliers were detected, and data gaps were interpolated using the K-nearest neighbor algorithm (KNN). Secondly, The ZTD differences between the KNN and periodic model were employed as input datasets to train the long short-term memory (LSTM) neural network. Finally, LSTM forecasted ZTD differences and the ZTD periodic signals were combined to recover the final forecasted ZTD results. In addition, the forecasted ZTD results were applied in static PPP as a prior constraint to reduce PPP convergence time. Numerical results show that the average root-mean-square error (RMSE) of predicting ZTD is about 1 cm. The convergence time of the PPP which was corrected by the LSTM-ZTD predictions is reduced by 13.9, 22.6, and 30.7% in the summer, autumn, and winter, respectively, over GPT2-ZTD corrected PPP and unconstrained conventional PPP for different seasons.
Full text
Available for:
IZUM, KILJ, NUK, PILJ, PNG, SAZU, UL, UM, UPUK
The
M
w
7.8 Kaikōura, North Canterbury, New Zealand earthquake, which occurred on 14 November 2016 (local time), was one of the most complex continental earthquakes ever documented and among the ...largest instrumentally recorded events in New Zealand history. The epicenter was located at the southern termination of the Hikurangi margin, where the subducting Pacific Plate transfers into the dextral Alpine transform fault. In this work, we precisely estimate three-dimensional coseismic and postseismic displacements caused by this event from continuous global navigation satellite systems (GNSS) stations in New Zealand. The Kaikōura earthquake activated significant and diverse coseismic and postseismic deformation on a large spatial scale, located mainly in the southern part of the North Island and the northern part of the South Island. Station CMBL had the largest coseismic offsets and the most remarkable postseismic displacements. The accumulated postseismic displacements at this station reached 13, 7 and 29% of the coseismic values on the east, north and vertical components, respectively, in the first 1.5 years after the mainshock. Integrating our estimated coseismic displacements with previously published coseismic displacements, we inverted for the spatial distribution of coseismic slip and spatiotemporal evolution of postseismic slip. Our optimal coseismic model suggests that rupture occurred both on shallow crustal faults, and to some extent at the southern Hikurangi subduction interface. The GPS-inverted coseismic moment release is equivalent to an
M
w
7.9 event. The postseismic slip was not only significantly extended at the subduction interface, but also appeared on the Needles fault. The cumulative moment magnitude is
M
w
7.35 in the first 1.5 years after the event, and
M
w
7.35,
M
w
6.95 and
M
w
6.80 during the periods 0.0–0.5, 0.5–1.0 and 1.0–1.5 years, respectively, indicating rapid decay of the postseismic deformation. Comparing the spatial distribution of the postseismic to the coseismic slip, although their direction is similar, the discrepancy between their location is significant: the slip located along the shallow crustal faults activated the coseismic deformation, while the slip located on the deep subduction interface controlled the postseismic deformation.
Full text
Available for:
DOBA, EMUNI, FIS, FZAB, GEOZS, GIS, IJS, IMTLJ, IZUM, KILJ, KISLJ, MFDPS, NLZOH, NUK, OBVAL, OILJ, PILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, UILJ, UKNU, UL, UM, UPUK, VKSCE, ZAGLJ
In this article, barycentric interpolation collocation method (BICM) is presented to solve the fractional linear Fredholm-Volterra integro-differential equation (FVIDE). Firstly, the fractional order ...term of equation is transformed into the Riemann integral with Caputo definition, and this integral term is approximated by the Gauss quadrature formula. Secondly, the barycentric interpolation basis function is used to approximate the unknown function, and the matrix equation of BICM is obtained. Finally, several numerical examples are given to solve one-dimensional differential equation.
Full text
Available for:
DOBA, FZAB, GIS, IJS, IZUM, KILJ, NLZOH, NUK, OILJ, PILJ, PNG, SAZU, SBCE, SBMB, SIK, UILJ, UKNU, UL, UM, UPUK
PDF
