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Discussion on the Abnormally Low Active Fault Slip Rate of the M_S 8. 0 Wenchuan Earthquake

Based on the collection of active fault slip rate data of large intra-continental shallow thrust earthquakes occurring in the triangular seismic region of the East Asia continent,a preliminary analysis has been performed with results showing that the Wenchuan,Sichuan, China earthquake ( MS = 8. 0) of May 12,2008 occurred on the Longmenshan Mountain active fault with an abnormally low slip rate.     

Assessment of extreme drought and human interference on baseflow of the Yangtze River

Attention has been given to baseflow in large rivers, but up to now, no study on baseflow for the Yangtze River in combination with extreme drought and extensive human activities has been carried out. Discharge data in 2000–2005 and in the extreme drought years, 1978 and 2006, at stations along the main stream, lakes and distributaries of the Yangtze River were collected to analyse the features of baseflow in 2006 by using baseflow separation technique, HYSEP. It can be seen that the baseflow relative to the streamflow in 2006 was greater than those in other years. The variation of baseflow discharge in the Upper Yangtze River Stream (UYRS) was larger than that in the Mid‐Lower Yangtze River Stream (MLYRS). Human activities in MLYRS are more intensive than that in the UYRS and the baseflow discharge was greater. The baseflow is influenced by the extreme climate and human activities along the Yangtze River with the former being the dominant factor in 2006. The contribution of human interference to baseflow discharge was about 10% in 2006. Copyright © 2009 John Wiley & Sons, Ltd.     

大岗山库区主动震源探测系统性能及其影响因素

利用大岗山水库地震监测台网,在大岗山库区建立了主动震源探测系统。主动震源设备为10t精密控制机械震源,接收台站包括大岗山水库地震台网的8个固定台站、2个加密流动台站和1个震源接收台。本文介绍了大岗山库区主动震源探测系统的基本情况、震源与地基的耦合特征、系统的性能及其影响因素等,并通过初步数据处理获取了大岗山库区地壳波速的相对变化。     

Statistic inversion of multi-zone transition probability models for aquifer characterization in alluvial fans

Understanding the heterogeneity arising from the complex architecture of sedimentary sequences in alluvial fans is challenging. This paper develops a statistical inverse framework in a multi-zone transition probability approach for characterizing the heterogeneity in alluvial fans. An analytical solution of the transition probability matrix is used to define the statistical relationships among different hydrofacies and their mean lengths, integral scales, and volumetric proportions. A statistical inversion is conducted to identify the multi-zone transition probability models and estimate the optimal statistical parameters using the modified Gauss–Newton–Levenberg–Marquardt method. The Jacobian matrix is computed by the sensitivity equation method, which results in an accurate inverse solution with quantification of parameter uncertainty. We use the Chaobai River alluvial fan in the Beijing Plain, China, as an example for elucidating the methodology of alluvial fan characterization. The alluvial fan is divided into three sediment zones. In each zone, the explicit mathematical formulations of the transition probability models are constructed with optimized different integral scales and volumetric proportions. The hydrofacies distributions in the three zones are simulated sequentially by the multi-zone transition probability-based indicator simulations. The result of this study provides the heterogeneous structure of the alluvial fan for further study of flow and transport simulations.     

Nonlinear inversion of electrical resistivity imaging using pruning Bayesian neural networks

Conventional artificial neural networks used to solve electrical resistivity imaging (ERI) inversion problem suffer from overfitting and local minima. To solve these problems, we propose to use a pruning Bayesian neural network (PBNN) nonlinear inversion method and a sample design method based on the K-medoids clustering algorithm. In the sample design method, the training samples of the neural network are designed according to the prior information provided by the K-medoids clustering results; thus, the training process of the neural network is well guided. The proposed PBNN, based on Bayesian regularization, is used to select the hidden layer structure by assessing the effect of each hidden neuron to the inversion results. Then, the hyperparameter α _k , which is based on the generalized mean, is chosen to guide the pruning process according to the prior distribution of the training samples under the small-sample condition. The proposed algorithm is more efficient than other common adaptive regularization methods in geophysics. The inversion of synthetic data and field data suggests that the proposed method suppresses the noise in the neural network training stage and enhances the generalization. The inversion results with the proposed method are better than those of the BPNN, RBFNN, and RRBFNN inversion methods as well as the conventional least squares inversion.     

Measurement of aerosol effective density by single particle mass spectrometry

Single particle mass spectrometry has been widely used to determine the size and chemical compositions of atmospheric aerosols; however, it is still rarely used for the microphysical properties measurement. In this study, two methods were developed for determining aerosol effective density by a single particle aerosol mass spectrometer (SPAMS). Method I retrieved effective density through comparison between measured light scattering intensities and Mie theoretical modelled partial scattering cross section. Method II coupled a differential mobility analyzer (DMA) with SPAMS to simultaneously determine the electric mobility and vacuum aerodynamic diameter, and thus the effective density. Polystyrene latex spheres, ammonium sulfate and sodium nitrate were tested by these methods to help validate their effectiveness for determining the aerosol effective density. This study effectively extends SPAMS measurements to include particle size, chemical composition, light scattering, and effective density, and thus helps us better understand the environment and climate effects of aerosols.     

Implementation of Elastic Prestack Reverse-Time Migration Using an Efficient Finite-Difference Scheme

Elastic reverse-time migration (RTM) can reflect the underground elastic information more comprehensively than single-component Pwave migration. One of the most important requirements of elastic RTM is to solve wave equations. The imaging accuracy and efficiency of RTM depends heavily on the algorithms used for solving wave equations. In this paper, we propose an efficient staggered-grid finite-difference (SFD) scheme based on a sampling approximation method with adaptive variable difference operator lengths to implement elastic prestack RTM. Numerical dispersion analysis and wavefield extrapolation results show that the sampling approximation SFD scheme has greater accuracy than the conventional Taylor-series expansion SFD scheme. We also test the elastic RTM algorithm on theoretical models and a field data set, respectively. Experiments presented demonstrate that elastic RTM using the proposed SFD scheme can generate better images than that using the Taylor-series expansion SFD scheme, particularly for PS images. FurH. thermore, the application of adaptive variable difference operator lengths can effectively improve the computational efficiency of elastic RTM.     

Spatio-temporal Differences and Driving Forces of Air Quality in Chinese Cities

Deterioration of city air quality is the serious problem in the process of rapid urbanization and economic development in China. Taking 74 cities that have implemented the new Ambient Air Quality Standards (GB3095- 2012) since 2013 as examples, using statistical and ArcGIS spatial analysis method, the multi-scale temporal and spatial variations characteristics and the impact of social and economic factors on urban air quality variations, are analyzed in this paper. The main research conclusions are as follows:(1) Air quality in Chinese cities shows very significant seasonal variations, with higher air quality in summer and autumn, and lower air quality in spring and winter; (2) Seen from a daily pollution perspective, air pollution is very serious and will tend to be more serious in the future; (3) Seen from an hourly variation perspective, urban air quality is time coupled with social production and urban living; (4) The overall spatial pattern of urban air quality is high in the east and north and low in the west and south, but with an obvious trend towards regional integration. (5) Cities in different regions have different factors that cause air quality variations. In general, urbanization level and energy consumption per GDP are the common factors.