Spatiotemporal filtering of regional GNSS network’s position time series with missing data using principle component analysis

The existing spatiotemporal analysis methods suppose that the involved time series are complete and have the same data interval. However missing data inevitably occur in the position time series of Global Navigation Satellite Systems networks for many reasons. In this paper, we develop a modified principal component analysis to extract the Common Mode Error (CME) from the incomplete position time series. The principle of the proposed method is that a time series can be reproduced from its principle components. The method is equivalent to the method of Dong et al. (J Geophys Res 111:3405–3421, 2006) in case of no missing data in the time series and to the extended ‘stacking’ approach under the assumption of a uniformly spatial response. The new method is first applied to extract the CME from the position time series of the Crustal Movement Observation Network of China (CMONOC) over the period of 1999–2009 where the missing data occur in all stations with the different gaps. The results show that the CMEs are significant in CMONOC. The size of the first principle components for the North, East and Up coordinates are as large as 40, 41 and 37 % of total principle components and their spatial responses are not uniform. The minimum amplitudes of the first eigenvectors are only 41, 15 and 29 % for the North, East and Up coordinate components, respectively. The extracted CMEs of our method are close to the data filling method, and the Root Mean Squared error (RMS) values computed from the differences of maximum CMEs between two methods are only 0.31, 0.52 and 1.55 mm for North, East and Up coordinates, respectively. The RMS of the position time series is greatly reduced after filtering out the CMEs. The accuracies of the reconstructed missing data using the two methods are also comparable. To further comprehensively test the efficiency of our method, the repeated experiments are then carried out by randomly deleting different percentages of data at some stations. The results show that the CMEs can be extracted with high accuracy at the non missing-data epochs. And at the missing-data epochs, the accuracy of extracted CMEs has a strong dependence on the number of stations with missing data.     

任楼矿井72煤层断层构造分形特征研究

利用分形理论,对安徽皖北任搂煤矿72煤层断层分形特征进行了研究,计算了不同构造分区的维数。研究发现构造复杂性不同及断裂性质的不同其分形维数也有所不同,构造简单,断层分维数小,而构造复杂区,断层分为数相对较大;剪切断裂带具有较低的分维值,张扭性断裂带分维值较高。     

Identification of buried sinkholes using refraction tomography at Ft. Campbell Army Airfield,Kentucky

Karst aquifers are highly susceptible to contamination, with numerous points of entry for contaminants through recharge features such as sinkholes, swallow holes and solutionally enlarged fractures. These recharge features may be filled or obscured at the surface, requiring the use of geophysical or remote sensing techniques for their identification. This study uses seismic refraction data collected at the Ft. Campbell Army Airfield (CAAF), Kentucky, USA, to test the hypothesis that refraction tomography is a useful tool for imaging bedrock depressions beneath thick overburden (greater than 20 m of unconsolidated sediment). Southeast of the main taxiway of CAAF seismic velocity tomograms imaged a bedrock low, possibly a closed depression, at a depth of 25 m that had been earlier identified through delay-time analysis of the same refraction data. Tomography suggests the bedrock low is about 250-m wide by 10-m deep at its widest point. High rates of contaminant vapor extraction over the western extension of this feature suggest a high concentration of contaminants above, and within, this filled bedrock low, the base of which may contain solutionally enlarged fractures (i.e. karst conduits) that could funnel these contaminants to the upper or lower bedrock aquifers. This study thus demonstrates the viability of seismic refraction tomography as a tool for identification of filled sinkholes and bedrock depressions in karst areas.     

Constraints from melt inclusions and their host olivines on the petrogenesis of Oligocene-Early Miocene Xindian basalts, Chifeng area, North China Craton

The geochemical characteristics of melt inclusions and their host olivines provide important information on the processes that create magmas and the nature of their mantle and crustal source regions. We report chemical compositions of melt inclusions, their host olivines and bulk rocks of Xindian basalts in Chifeng area, North China Craton. Compositions of both bulk rocks and melt inclusions are tholeiitic. Based on petrographic observations and compositional variation of melt inclusions, the crystallizing sequence of Xindian basalts is as follows: olivine (at MgO > ~5.5 wt%), plagioclase (beginning at MgO = ~5.5 wt%), clinopyroxene and ilmenite (at MgO < 5.0 wt%). High Ni contents and Fe/Mn ratios, and low Ca and Mn contents in olivine phenocrysts, combining with low CaO contents of relatively high MgO melt inclusions (MgO > 6 wt%), indicate that Xindian basalts are possibly derived from a pyroxenite source rather than a peridotite source. In the CS-MS-A diagram, all the high MgO melt inclusions (MgO > 6.0 wt%) project in the field between garnet + clinopyroxene + liquid and garnet + clinopyroxene + orthopyroxene + liquid near 3.0 GPa, further suggesting that residual minerals are mainly garnet and clinopyroxene, with possible presence of orthopyroxene, but without olivine. Modeling calculations using MELTS show that the water content of Xindian basalts is 0.3–0.7 wt% at MgO = 8.13 wt%. Using 20–25 % of partial melting estimated by moderately incompatible element ratios, the water content in the source of Xindian basalts is inferred to be ≥450 ppm, much higher than 6–85 ppm in dry lithospheric mantle. The melting depth is inferred to be ~3.0 GPa, much deeper than that of tholeiitic lavas (<2.0 GPa), assuming a peridotite source with a normal mantle potential temperature. Such melting depth is virtually equal to the thickness of lithosphere beneath Chifeng area (~100 km), suggesting that Xindian basalts are derived from the asthenospheric mantle, if the lithospheric lid effect model is assumed.     

Comparison of spectral and spatial methods for a Moho recovery from gravity and vertical gravity-gradient data

In global studies investigating the Earth’s lithospheric structure, the spectral expressions for the gravimetric forward and inverse modeling of the global gravitational and crustal structure models are preferably used, because of their numerical efficiency. In regional studies, the applied numerical schemes typically utilize the expressions in spatial form. Since the gravity-gradient observations have a more localized support than the gravity measurements, the gravity-gradient data (such as products from the Gravity field and steady-state Ocean Circulation Explorer - GOCE - gravity-gradiometry satellite mission) could preferably be used in regional studies, because of reducing significantly the spatial data-coverage required for a regional inversion or interpretation. In this study, we investigate this aspect in context of a regional Moho recovery. In particular, we compare the numerical performance of solving the Vening Meinesz-Moritz’s (VMM) inverse problem of isostasy in spectral and spatial domains from the gravity and (vertical) gravity-gradient data. We demonstrate that the VMM spectral solutions from the gravity and gravity-gradient data are (almost) the same, while the VMM spatial solutions differ from the corresponding spectral solutions, especially when using the gravity-gradient data. The validation of the VMM solutions, however, reveals that the VMM spatial solution from the gravity-gradient data has a slightly better agreement with seismic models. A more detailed numerical analysis shows that the VMM spatial solution formulated for the gravity gradient is very sensitive to horizontal spatial variations of the vertical gravity gradient, especially in vicinity of the computation point. Consequently, this solution provides better results in regions with a relatively well-known crustal structure, while suppressing errors caused by crustal model uncertainties from distant zones. Based on these findings we argue that the gravity-gradient data are more suitable than the gravity data for a regional Moho recovery.     

Reconstruction of paleocoastlines for the northwestern South China Sea since the Last Glacial Maximum

The range of relative sea level rise in the northwestern South China Sea since the Last Glacial Maximum was over 100 m. As a result, lowland regions including the Northeast Vietnam coast, Beibu Gulf, and South China coast experienced an evolution from land to sea. Based on the principle of reconstructing paleogeography and using recent digital elevation model, relative sea level curves, and sediment accumulation data, this paper presents a series of paleogeographic scenarios back to 20 cal. ka BP for the northwestern South China Sea. The scenarios demonstrate the entire process of coastline changes for the area of interest. During the late glacial period from 20 to 15 cal. ka BP, coastline slowly retreated, causing a land loss of only 1×10⁴ km², and thus the land-sea distribution remained nearly unchanged. Later in 15–10 cal. ka BP coastline rapidly retreated and area of land loss was up to 24×10⁴km², causing lowlands around Northeast Vietnam and South China soon to be underwater. Coastline retreat continued quite rapidly during the early Holocene. From 10 to 6 cal. ka BP land area had decreased by 9×10⁴km², and during that process the Qiongzhou Strait completely opened up. Since the mid Holocene, main controls on coastline change are from vertical crustal movements and sedimentation. Transgression was surpassed by regression, resulting in a land accretion of about 10×10⁴km². Supported by Key Laboratory of Marginal Sea Geology, Chinese Academy of Sciences (Grant No. MSGL0711), the Guangdong Natural Science Foundation (Grant No. 04001309) and Open Fund of the Key Laboratory of Marine Geology and Environment, Chinese Academy of Sciences (Grant No. MGE2007KG04)     

Assessment of shallow landslides from Hurricane Mitch in central America using a physically based model

Shallow landslides induced by heavy rainfall events represent one of the most disastrous hazards in mountainous regions because of their high frequency and rapid mobility. Recent advancements in the availability and accessibility of remote sensing data, including topography, land cover and precipitation products, allow landslide hazard assessment to be considered at larger spatial scales. A theoretical framework for a landslide forecasting system was prototyped in this study using several remotely sensed and surface parameters. The applied physical model SLope-Infiltration-Distributed Equilibrium (SLIDE) takes into account some simplified hypotheses on water infiltration and defines a direct relation between factor of safety and the rainfall depth on an infinite slope. This prototype model is applied to a case study in Honduras during Hurricane Mitch in 1998. Two study areas were selected where a high density of shallow landslides occurred, covering approximately 1,200 km². The results were quantitatively evaluated using landslide inventory data compiled by the United States Geological Survey (USGS) following Hurricane Mitch’s landfall. The agreement between the SLIDE modeling results and landslide observations demonstrates good predictive skill and suggests that this framework could serve as a potential tool for the future early landslide warning systems. Results show that within the two study areas, the values of rates of successful estimation of slope failure locations reached as high as 78 and 75%, while the error indices were 35 and 49%. Despite positive model performance, the SLIDE model is limited by several assumptions including using general parameter calibration rather than in situ tests and neglecting geologic information. Advantages and limitations of this physically based model are discussed with respect to future applications of landslide assessment and prediction over large scales.     

A coupling of mixed and continuous Galerkin finite element methods for poroelasticity I: the continuous in time case

In this paper, we formulate a finite element procedure for approximating the coupled fluid and mechanics in Biot’s consolidation model of poroelasticity. Here, we approximate the pressure by a mixed finite element method and the displacements by a Galerkin method. Theoretical convergence error estimates are derived in a continuous in-time setting for a strictly positive constrained specific storage coefficient. Of particular interest is the case when the lowest-order Raviart–Thomas approximating space or cell-centered finite differences are used in the mixed formulation, and continuous piecewise linear approximations are used for displacements. This approach appears to be the one most frequently applied to existing reservoir engineering simulators.     

Rapid estimation of maximum and minimum void ratios of granular soils

Maximum and minimum void ratios (e_max and e_min) of granular soils are commonly used as indicators of many engineering properties. However, few methods, apart from laboratory tests, are available to provide a rapid estimation of both e_max and e_min. In this study, we present a theoretical model to map the densest and the loosest packing configurations of granular soils onto the void space. A corresponding numerical procedure that can predict both e_max and e_min of granular soils with arbitrary grain size distributions is proposed. The capacity of the proposed method is evaluated by predicting the maximum and minimum void ratios of medium to fine mixed graded sands with different contents of fines. The influence of the grain size distribution, characterized quantitatively by uniformity parameter and the fractal dimension, on e_max and e_min is discussed using the proposed method. Moreover, application of this method in understanding the controlling mechanism for the void ratio change during grain crushing is presented.

     

Stabilization of Expansive Clays Using Granulated Blast Furnace Slag (GBFS) and GBFS-Cement

Expansive clays undergo swelling when subjected to water. This can cause damage, especially to light weight structures, water conveyance canals, lined reservoirs, highways, and airport runways unless appropriate measures are taken. In this study, granulated blast furnace slag (GBFS) and GBFS-cement (GBFSC) were utilized to overcome or to limit the expansion of an artificially prepared expansive soil sample (sample A). GBFS and GBFSC were added to sample A in proportions of 5–25% by weight. The effects of these stabilizers on grain size distribution, Atterberg limits, swelling percentage and rate of swell of soil samples were determined. GBFS and GBFSC were shown to successfully decreasing the total amount of swell while increasing the rate of swell.