New-type urbanization in China: Predicted trends and investment demand for 2015–2030

The future development of new-type urbanization has drawn great attention from both the government and public alike. In this context, the present study had three related research aims. Firstly, it sought to predict the urbanization and population dynamics in China at both national and provincial levels for the period of 2015 to 2030. Secondly, on this basis, it sought to examine the spatial variation of urbanization given the predicted national urbanization rate of 70.12%. Thirdly, it sought to estimate and evaluate the national and provincial demands of investment in the development of new-type urbanization. The main conclusions from this study were as follows: (1) The population size and urbanization rate will reach 1.445 billion and 70.12%, respectively, from 2015 to 2030. (2) The demographic dividend will vanish when the population pressure reaches its maximum. During this period, there will be 70.16 million urban population born. The suburban population that becomes urbanized will be 316.7 million, and thus the net increase in urban population will reach 386 million. (3) Although the urbanization rate of every Chinese province will increase during 2015–2030, it will do so unequally, while differences in urbanization quality among provinces will also be substantial. In some provinces, moreover, the urbanization quality is not compatible with their eco-social development. (4) A total of 4,105,380 billion yuan is required to fund new-type urbanization and the investment demand for each province varies greatly; for example, Guangdong province requires the most funding, amounting to approximately 148 times that required by Tibet, the province in least need of funding. In the final part of this study, policy suggestions concerning the investment of the new-type urbanization are put forward and discussed.     

Statistical properties of aftershock rate decay: Implications for the assessment of continuing activity

Aftershock rates seem to follow a power law decay, but the assessment of the aftershock frequency immediately after an earthquake, as well as during the evolution of a seismic excitation remains a demand for the imminent seismic hazard. The purpose of this work is to study the temporal distribution of triggered earthquakes in short time scales following a strong event, and thus a multiple seismic sequence was chosen for this purpose. Statistical models are applied to the 1981 Corinth Gulf sequence, comprising three strong (M = 6.7, M = 6.5, and M = 6.3) events between 24 February and 4 March. The non-homogeneous Poisson process outperforms the simple Poisson process in order to model the aftershock sequence, whereas the Weibull process is more appropriate to capture the features of the short-term behavior, but not the most proper for describing the seismicity in long term. The aftershock data defines a smooth curve of the declining rate and a long-tail theoretical model is more appropriate to fit the data than a rapidly declining exponential function, as supported by the quantitative results derived from the survival function. An autoregressive model is also applied to the seismic sequence, shedding more light on the stationarity of the time series.     

Numerical analysis for random temperature fields of embankment in cold regions

The stochastic finite element equations for random temperature are obtained using the first-order per-turbation technique taking into account the random thermal properties and boundary condition, based on heat transfer variational principle. The local average method for 2-D is used to discretize random fields. Then, the random temperature fields of embankment in cold regions are investigated on condi-tion that the thermal properties and boundary condition are taken as random fields, respectively, by using the program, which is written by the methods. The expected value of temperature field and the standard deviation of the temperature field of embankment in cold regions are obtained and analyzed.     

Power law relating 10.7 cm flux to sunspot number

To investigate the relation between observations of the 10.7 cm flux and the international sunspot number so that a physical unit may be ascribed to historical records, both polynomial and power law models are developed giving the radio flux as a function of sunspot number and vice versa. Bayesian data analysis is used to estimate the model parameters and to discriminate between the models. The effect on the parameter uncertainty and on the relative evidence of normalizing the measure of fit is investigated. The power law giving flux as a function of sunspot number is found to be the most plausible model and may be used to estimate the radio flux from historical sunspot observations.     

Comparison of two creep degradation modeling approaches for soft structured soils

The creep degradation is a common phenomenon for soft structured clays. In this paper, the creep degradation behavior for soft structured clays is first studied by combining intrinsic creep behavior and the structure indicator. A creep-implicit model and a creep-explicit model corresponding to a stress-based and a creep-based structure indicators are developed, respectively, under one-dimensional condition. Parameters determination for both models is straightforward from oedometer tests. Coupled with consolidation theory, both models are used to simulate oedometer tests with different structural levels and load durations on three clays. The predictive ability of the two models on creep behavior, creep degradation behavior and evolution of structure indicator is analyzed. The relationship between the two structure indicators is discussed based on experimental results. The comparison between experimental and numerical results demonstrates that both models can accurately describe the creep degradation behavior of soft structured clay under one-dimensional loading.     

Expectation Maximization algorithm and its minimal detectable outliers

Minimal Detectable Biases (MDBs) or Minimal Detectable Outliers for the Expectation Maximization (EM) algorithm based on the variance-inflation and the mean-shift model are determined for an example. A Monte Carlo method is applied with no outlier and with one, two and three randomly chosen outliers. The outliers introduced are recovered and the corresponding MDBs are almost independent from the number of outliers. The results are compared to the MDB derived earlier by the author. This MDB approximately agrees with the MDB for one outlier of the EM algorithm. The MDBs for two and three outliers are considerably larger than MDBs of the EM algorithm.     

Mixed layer depth front and subduction of low potential vorticity water under seasonal forcings in an idealized OGCM

The mixed layer depth (MLD) front and subduction under seasonal variability are investigated using an idealized ocean general circulation model (OGCM) with simple seasonal forcings. A sharp MLD front develops and subduction occurs at the front from late winter to early spring. The position of the MLD front agrees with the curve where \({\rm D}T_{\rm s}/{\rm D}t = \partial T_{\rm s} /\partial t + {\user2{u}}_{\rm g} \cdot \nabla T_{\rm s} = 0\) is satisfied (t is time, \({\user2{u}}_{\rm g}\) is the upper-ocean geostrophic velocity, \(T_{\rm s}\) is the sea surface temperature (SST), and \(\nabla\) is the horizontal gradient operator), indicating that thick mixed-layer water is subducted there parallel to the SST contour. This is a generalization of the past result that the MLD front coincides with the curve \({\user2{u}}_{\rm g} \cdot \nabla T_{\rm s} = 0\) when the forcing is steady. Irreversible subduction at the MLD front is limited to about 1 month, where the beginning of the irreversible subduction period agrees with the first coincidence of the MLD front and \({\rm D}T_{\rm s}/{\rm D}t =0\) in late winter, and the end of the period roughly corresponds to the disappearance of the MLD front in early spring. Subduction volume at the MLD front during this period is similar to that during 1 year in the steady-forcing model. Since the cooling of the deep mixed-layer water occurs only in winter and SST can not fully catch up with the seasonally varying reference temperature of restoring, the cooling rate of SST is reduced and the zonal gradient of the SST in the northwestern subtropical gyre is a little altered in the seasonal-forcing case. These effects result in slightly lower densities of subducted water and the eastward shift of the MLD front.     

Was the M<Subscript>w</Subscript> 7.5 1952 Kern County,California, earthquake induced (or triggered)?

Several recent studies have presented evidence that significant induced earthquakes occurred in a number of oil-producing regions during the early and mid-twentieth century related to either production or wastewater injection. We consider whether the 21 July 1952 M_w 7.5 Kern County earthquake might have been induced by production in the Wheeler Ridge oil field. The mainshock, which was not preceded by any significant foreshocks, occurred 98 days after the initial production of oil in Eocene strata at depths reaching 3 km, within ~1 km of the White Wolf fault (WWF). Based on this spatial and temporal proximity, we explore a potential causal relationship between the earthquake and oil production. While production would have normally be expected to have reduced pore pressure, inhibiting failure on the WWF, we present an analytical model based on industry stratigraphic data and best estimates of parameters whereby an impermeable splay fault adjacent to the main WWF could plausibly have blocked direct pore pressure effects, allowing the poroelastic stress change associated with production to destabilize the WWF, promoting initial failure. This proof-of-concept model can also account for the 98-day delay between the onset of production and the earthquake. While the earthquake clearly released stored tectonic stress, any initial perturbation on or near a major fault system can trigger a larger rupture. Our proposed mechanism provides an explanation for why significant earthquakes are not commonly induced by production in proximity to major faults.     

Mechanisms controlling the temporal variation of the sea ice edge in the Southern Ocean

This paper examines the mechanism controlling the short time-scale variation of sea ice cover over the Southern Ocean. Sea ice concentration and ice velocity datasets derived from images of the Defense Meteorological Satellite Program (DMSP) Special Sensor Microwave Imager (SSM/I) are employed to reveal this mechanism. The contribution of both dynamic and thermodynamic processes to the change in ice edge location is examined by comparing the meridional velocity of ice edge displacement and sea ice drift. In the winter expansion phase, the thermodynamic process of new ice production off the ice edge plays an important role in daily advances of ice cover, whereas daily retreats are mostly due to southward ice drift. On the other hand, both advance and retreat of ice edges in the spring contraction phase are mostly caused by the dynamic process of the ice drift. Based on the above mechanism and the linear relation between the degree of ice production at the ice edge and northward wind speed, the seasonal advance of ice cover can be roughly reproduced using the meridional velocity of ice drift at the ice edge.     

Remote Sensing of Eupatorium Adenophorum Spreng Based on HJ-A Satellite Data

In the southwest of China, one of the greatest threats to local ecosystem is the area expansion of an invasive species, i.e., Eupatorium adenophorum Spreng (EAS). In this study, the remote-sensing technology was used to detect and map the spatial distribution of EAS in Guizhou Province, China. A series of vegetation indices, including normalized difference vegetation index (NDVI), simple ratio index (SRI) and atmospherically resistant vegetation index (ARVI), were used to identify EAS from HJ-A Chninese satellite data. According to the analysis results of fieldworks from March 21 to 22, 2009, it was found that the vegetation index of {1.9589 ≤ SRI ≤ 4.1095}∩{0.2359 ≤ ARVI ≤ 0.5193} was the optimal remote-sensing parameter for identifying EAS from HJ-A data. According to the spatial distribution of EAS estimated from HJ-A data, it was found that EAS was rather more in southwest of Guizhou Province than in northeast. EAS became sparse from southwest to northeast gradually, and the central Guizhou Province was the ecological corridor linking EAS in southwest to that in northeast. By comparison with validated data collected by the government of Guizhou Province, it was found that the uncertainty of remote-sensing method was 18.52%, 29.31%, 8.77% and 9.46% in grassland, forest, farmland and others respectively, and the mean uncertainty was 13.29%. Owing to the lower height of EAS than many plants in forest, the uncertainty of EAS was the greatest in forest than that in grassland, farmland and so on.