Initiation of large-volume silicic centers in the Yellowstone hotspot track: insights from H<Subscript>2</Subscript>O- and F-rich quartz-hosted rhyolitic melt inclusions in the Arbon Valley Tuff of the Snake River Plain

During the onset of caldera cluster volcanism at a new location in the Snake River Plain (SRP), there is an increase in basalt fluxing into the crust and diverse silicic volcanic products are generated. The SRP contains abundant and compositionally diverse hot, dry, and often low-δ¹⁸O silicic volcanic rocks produced through time during the formation of individual caldera clusters, but more H₂O-rich eruptive products are rare. We report analyses of quartz-hosted melt inclusions from pumice clasts from the upper and lower Arbon Valley Tuff (AVT) to gain insight into the initiation of caldera cluster volcanism. The AVT, a voluminous, caldera-forming rhyolite, represents the commencement of volcanism (10.44 Ma) at the Picabo volcanic field of the Yellowstone hotspot track. This is a normal δ¹⁸O rhyolite consisting of early and late erupted members (lower and upper AVT, respectively) with extremely radiogenic Sr isotopes and unradiogenic Nd isotopes, requiring that ~50 % of the mass of these elements is derived from melts of Archean upper crust. Our data reveal distinctive features of the early erupted lower AVT melt including: variable F concentrations up to 1.4 wt%, homogenous and low Cl concentrations (~0.08 wt%), H₂O contents ranging from 2.3 to 6.4 wt%, CO₂ contents ranging from 79 to 410 ppm, and enrichment of incompatible elements compared to the late erupted AVT, subsequent Picabo rhyolites, SRP rhyolites, and melt inclusions from other metaluminous rhyolites (e.g., Bishop Tuff, Mesa Falls Tuff). We couple melt inclusion data with Ti measurements and cathodoluminescence (CL) imaging of the host quartz phenocrysts to elucidate the petrogenetic evolution of the AVT rhyolitic magma. We observe complex and multistage CL zoning patterns, the most critical being multiple truncations indicative of several dissolution–reprecipitation episodes with bright CL cores (higher Ti) and occasional bright CL rims (higher Ti). We interpret the high H₂O, F, F/Cl, and incompatible trace element concentrations in the context of a model involving melting of Archean crust and mixing of the crustal melt with basaltic differentiates, followed by multiple stages of fractional crystallization, remelting, and melt extraction. This multistage process, which we refer to as distillation, is further supported by the complex CL zoning patterns in quartz. We interpret new Δ¹⁸O(Qz-Mt) isotope measurements, demonstrating a 0.4 ‰ or ~180 °C temperature difference, and strong Sr isotopic and chemical differences between the upper and lower AVT to represent two separate eruptions. Similarities between the AVT and the first caldera-forming eruptions of other caldera clusters in the SRP (Yellowstone, Heise and Bruneau Jarbidge) suggest that the more evolved, lower-temperature, more H₂O-rich rhyolites of the SRP are important in the initiation of a caldera cluster during the onset of plume impingement.     

基于部分最小二乘岭估计的粗差定值定位

在利用部分最小二乘原理进行粗差定值定位时,模型的法方程矩阵可能存在病态性,使得到的粗差定值定位结果不可靠。文中针对观测数据包含多个粗差且法方程病态问题,利用岭估计处理病态问题,建立部分最小二乘岭估计的粗差定值定位方法,给出粗差搜索步骤,利用迭代算法实现多个粗差的定值和定位。通过模拟算例分析部分最小二乘法、部分最小二乘岭估计在粗差搜索方面的效果,从另一个角度探讨粗差处理方法,推广现有的误差理论,证明文中方法的有效性。     

太湖地区HJ-1卫星CCD数据反演气溶胶及大气校正

针对HJ-1卫星CCD数据,利用改进的暗像元法反演气溶胶光学厚度(AOD),再利用反演的AOD对其进行大气校正。将反演的气溶胶与地基太阳光度计数据进行对比验证,发现当反演的AOD值大于0.2时,反演值与地基观测值的相关系数为0.964,符合MODIS业务化反演AOD的精度要求。再将反演得到的气溶胶带入6S辐射传输模型中,对HJ-1卫星CCD数据进行大气校正实验。结果表明,该方法能有效提高HJ-1卫星CCD数据大气校正的精度,更好地复原地物的真实光谱信息。     

Precise orbit determination of BeiDou constellation: method comparison

Chinese BeiDou navigation satellite system is in official service as a regional constellation with five geostationary earth orbit (GEO) satellites, five inclined geosynchronous satellite orbit (IGSO) satellites and four medium earth orbit (MEO) satellites. There are mainly two methods for precise orbit determination of the BeiDou constellation found in the current literatures. One is the independent single-system method, where only BeiDou observations are used without help from other GNSS systems. The other is the two-step GPS-assisted method where in the first step, GPS data are used to resolve some common parameters, such as station coordinates, receiver clocks and zenith tropospheric delay parameters, which are then introduced as known quantities in BeiDou processing in the second step. We conduct a thorough performance comparison between the two methods. Observations from the BeiDou experimental tracking stations and the IGS Multi-GNSS Experiment network from January 1 to March 31, 2013, are processed with the Positioning and Navigation Data Analyst (PANDA) software. The results show that for BeiDou IGSO and MEO satellites, the two-step GPS-assisted method outperforms the independent single-system method in both internal orbit overlap precision and external satellite laser ranging validation. For BeiDou GEO satellites, the two methods show close performances. Zenith tropospheric delays estimated from the first method are very close to those estimated from GPS precise point positioning in the second method, with differences of several millimeters. Satellite clock estimates from the two methods show similar performances when assessing the stability of the BeiDou on board clocks.     

Recursive algorithm for fast GNSS orbit fitting

Gaussian elimination is an efficient and numerically stable algorithm for estimating parameters and their precision. However, before estimating the parameters, it is often prudent to perform statistical tests to achieve the best fitting model. We use Gaussian elimination to select the best fitting model among candidate models. A succinct relationship between the weighted sum of squared residuals and the previous one is revealed by a volume formula. For quick parameter estimation and determination of weighted sum of squared residuals, a recursive elimination algorithm is proposed in the context of Gaussian elimination. In order to improve the model selection efficiency, the parameter estimation and the determination of the weighted sum of squared residuals are carried out in parallel using the proposed recursive elimination algorithm in which the improvement at each recursive stage is judged by the Bayesian information criterion. Ultimately, the computational complexity and numerical stability of the recursive elimination proposed are briefly discussed, and a GNSS orbit interpolation example is used to verify the results. It shows that the proposed recursive elimination algorithm inherits the numerical stability of the Gaussian elimination, and this algorithm can be used to examine the gain from the newly introduced parameter, dynamically assess the fitting model, and fix the optimal model efficiently. The optimal fitting model with the lowest information is very close to the real situation verified by checkpoints.     

A new method for specular and diffuse pseudorange multipath error extraction using wavelet analysis

Multipath remains one of the major challenges in Global Navigation Satellite System (GNSS) positioning because it is considered the dominant source of ranging errors, which can be classified into specular and diffuse types. We present a new method using wavelets to extract the pseudorange multipath in the time domain and breaking it down into the two components. The main idea is an analysis-reconstruction approach based on application of both continuous wavelet transform (CWT) and discrete wavelet transform (DWT). The proposed procedure involves the use of L1 code-minus-carrier (CMC) observable where higher-frequency terms are isolated as residuals. CMC residuals are analyzed by applying the CWT, and we propose the scalogram as a technique for discerning time–frequency variations of the multipath signal. Unlike Fourier transform, the potential of the CWT scalogram for examining the non-stationary and multifrequency nature of the multipath is confirmed as it simultaneously allows fine detection and time localization of the most representative frequencies of the signal. This interpretation of the CWT scalogram is relevant when choosing the levels of reconstruction with DWT, allowing accurate time domain extraction of both the specular and diffuse multipath. The performance and robustness of the method and its boundary applicability are assessed. The experiment was carried out using a receiver of Campania GNSS Network. The results are given in which specular multipath error is achieved using DWT level 7 approximation component and diffuse multipath error is achieved using DWT level 6 denoised detail component.     

Optimization and Parametrical Investigation to Assess the Reconstitution of Different Types of Indian Sand Using Portable Travelling Pluviator

By using the air pluviation technique, it is aimed to achieve the desired relative density with uniform void ratio throughout the specimen in order to maintain the homogeneity and to avoid the spatial variability. Further, in order to achieve the maximum deposition intensity, a systematic optimization study has been carried out rigorously in a test tank to determine the diameter of the orifice to be employed for the sieve plates of different porosity and the number of sieve plates to be installed in the diffuser sieve sets. The study has been conducted with four different patterns of sieves with different porosity to achieve a wide range of relative densities for four different uniformly graded Indian sands. The dynamic penetrometer which is considered to be one of the cost effective instruments has been efficiently used to determine the soil resistance at various locations of the test tank for every given height of fall in order to check the uniformity of placement density throughout the sand bed. The study reveals that the sand beds of different relative densities could be achieved using different patterns of diffuser sieves at optimum sand flow rate without compromising the uniformity. The effect of height of fall as well as porosity of diffuser sieves on the relative density of different sands has been studied in detail. The deposition intensity and the relative density obtained from the present study are compared with the values available in the literature.     

Assessment and Prediction of Liquefaction Potential Using Different Artificial Neural Network Models: A Case Study

Soil liquefaction as a transformation of granular material from solid to liquid state is a type of ground failure commonly associated with moderate to large earthquakes and refers to the loss of strength in saturated, cohesionless soils due to the build-up of pore water pressures and reduction of the effective stress during dynamic loading. In this paper, assessment and prediction of liquefaction potential of soils subjected to earthquake using two different artificial neural network models based on mechanical and geotechnical related parameters (model A) and earthquake related parameters (model B) have been proposed. In model A the depth, unit weight, SPT-N value, shear wave velocity, soil type and fine contents and in model B the depth, stress reduction factor, cyclic stress ratio, cyclic resistance ratio, pore pressure, total and effective vertical stress were considered as network inputs. Among the numerous tested models, the 6-4-4-2-1 structure correspond to model A and 7-5-4-6-1 for model B due to minimum network root mean square errors were selected as optimized network architecture models in this study. The performance of the network models were controlled approved and evaluated using several statistical criteria, regression analysis as well as detailed comparison with known accepted procedures. The results represented that the model A satisfied almost all the employed criteria and showed better performance than model B. The sensitivity analysis in this study showed that depth, shear wave velocity and SPT-N value for model A and cyclic resistance ratio, cyclic stress ratio and effective vertical stress for model B are the three most effective parameters on liquefaction potential analysis. Moreover, the calculated absolute error for model A represented better performance than model B. The reasonable agreement of network output in comparison with the results from previously accepted methods indicate satisfactory network performance for prediction of liquefaction potential analysis.     

中国北方三流域河流—沙漠过渡带地表沉积物化学元素空间差异分析

通过对克里雅河、毛布拉格孔兑以及西拉木伦河三流域的河流-沙漠过渡带地表沉积物的7种常量氧化物以及15种微量元素进行因子分析,结果显示:三个流域之间或不同河段因子分析提取的公因子均可以概括为较稳定的铁锰矿物、较不稳定的长石类和方解石（白云石）类等硅酸盐矿物以及稳定的稀土元素和重矿物等类别;河流间因子分析结果表明,自西向东三个流域沿河地表沉积物的化学元素富集与迁移程度呈递增趋势,化学风化程度增强;流域内因子分析结果表明,自上游至下游,样点化学组成均愈变复杂,不同河段或不同河岸沉积物化学元素空间分布规律与其物源、地貌格局以及水分条件等因素有关;自河床至阶地,不同地貌单元地表沉积物化学元素呈相异的递变规律,这与在距离河道远近不同,物源、动力因素的分配不同有关。