Probabilistic spatial prediction of categorical data using elliptical copulas

This study uses elliptical copulas and transition probabilities for uncertainty modeling of categorical spatial data. It begins by discussing the expressions of the cumulative distribution function and probability density function of two major elliptical copulas: Gaussian copula and t copula. The basic form of spatial copula discriminant function is then derived based on Bayes’ theorem, which consists of three parts: the prior probability, the conditional marginal densities, and the conditional copula density. Finally, three kinds of parameter estimation methods are discussed, including maximum likelihood estimation, inference functions for margins and canonical maximum likelihood (CML). To avoid making assumptions on the form of marginal distributions, the CML approach is adopted in the real-world case study. Results show that the occurrence probability maps generated by these two elliptical copulas are similar to each other. However, the prediction map interpolated by Gaussian copula has a relatively higher classification accuracy than t copula.     

基于多源数据的云南人口空间分布模拟研究

人口数据精度是提高地震灾情速判准确度的关键之一。本文基于多源数据融合思路,以云南第6次人口普查数据为基础,把居民地作为人口分布指示因子,利用GIS软件工具,分析了人口分布与地貌形态、坡度、地形起伏度以及土地利用之间的关系,构建了人口影响因子的权重系数,并采用城乡人口-面积统一模型对人口统计数据进行了网格化空间模拟及精度检验。以2013年3月3日云南洱源5.5级地震为例,通过多种估算方法对灾区人口进行了计算及对比分析,结果表明,多源数据融合法生成的千米网格人口与实际人口的相关性均在0.89以上,人口数据精度符合实际,可为灾情速判提供可靠的数据基础。     

Bootstrap approaches for spatial data

Generation of replicates of the available data enables the researchers to solve different statistical problems, such as the estimation of standard errors, the inference of parameters or even the approximation of distribution functions. With this aim, Bootstrap approaches are suggested in the current work, specifically designed for their application to spatial data, as they take into account the dependence structure of the underlying random process. The key idea is to construct nonparametric distribution estimators, adapted to the spatial setting, which are distribution functions themselves, associated to discrete or continuous random variables. Then, the Bootstrap samples are obtained by drawing at random from the estimated distribution. Consistency of the suggested approaches will be proved by assuming stationarity from the random process or by relaxing the latter hypothesis to admit a deterministic trend. Numerical studies for simulated data and a real data set, obtained from environmental monitoring, are included to illustrate the application of the proposed Bootstrap methods.     

基于GRAIL重力数据的月球深部断裂识别和空间分布研究

月球深部断裂是研究月球早期应力场演化和动力机制的一类重要构造.本文基于GRAIL月球重力数据计算了全月布格重力梯度,在此基础上对月球深部断裂进行了全球绘制,共识别月球深部断裂226条.计算了断裂的长度和走向等基本参数,断裂总长度达到37137 km,平均长度为164 km.统计月球深部断裂在不同范围内的分布情况,发现多数断裂分布在月球的中低纬度地区,且北半球的断裂多于南半球.此外,大型月海集中区所在的纬向带断裂分布最多,断裂经向分布最多的区域为风暴洋的西侧.从全球尺度和不同经纬度带绘制断裂走向玫瑰花图,总体上月球全球尺度上的深部断裂表现出NE-SW和NW-SE的优势走向,不同经度带断裂的优势走向变化不明显,但在纬度带上有显著的变化.南北半球的中纬度带和高纬度带具有相同的优势走向,分别为NE-SW和NW-SE、E-W,在低纬度带的优势走向有所差异,分别是南半球的NE-SW和NW-SE以及北半球的N-S.

     

Determination and integration of appropriate spatial scales for river basin modelling

Appropriate spatial scales of dominant variables are determined and integrated into an appropriate model scale. This is done in the context of the impact of climate change on flooding in the River Meuse in Western Europe. The objective is achieved by using observed elevation, soil type, land use type and daily precipitation data from several sources and employing different relationships between scales, variable statistics and outputs. The appropriate spatial scale of a key variable is assumed to be equal to a fraction of the spatial correlation length of that variable. This fraction was determined on the basis of relationships between statistics and scale and an accepted error in the estimation of the statistic of 10%. This procedure resulted in an appropriate spatial scale for precipitation of about 20 km in an earlier study. The application to river basin variables revealed appropriate spatial scales for elevation, soil and land use of respectively 0·1, 5·3 and 3·3 km. The appropriate model scale is determined by multiplying the appropriate variable scales with their associated weights. The weights are based on SCS curve number method relationships between the peak discharge and some specific parameters like slope and curve number. The values of these parameters are dependent on the scale of each key variable. The resulting appropriate model scale is about 10 km, implying 225–250 model cells in an appropriate model of the Meuse basin meant to assess the impact of climate change on river flooding. The usefulness of the appropriateness procedure is in its ability to assess the appropriate scales of the individual key variables before model construction and integrate them in a balanced way into an appropriate model scale. Another use of the procedure is that it provides a framework for decisions about the reduction or expansion of data networks and needs. Copyright © 2003 John Wiley & Sons, Ltd.     

A universal kriging approach for spatial functional data

In a wide range of scientific fields the outputs coming from certain measurements often come in form of curves. In this paper we give a solution to the problem of spatial prediction of non-stationary functional data. We propose a new predictor by extending the classical universal kriging predictor for univariate data to the context of functional data. Using an approach similar to that used in univariate geostatistics we obtain a matrix system for estimating the weights of each functional variable on the prediction. The proposed methodology is validated by analyzing a real dataset corresponding to temperature curves obtained in several weather stations of Canada.     

Geostatistical integration of near-surface geophysical data

Accurate statics calculation and near‐surface related noise removal require a detailed knowledge of the near‐surface velocity field. Conventional seismic surveys currently are not designed to provide this information, and 3D high‐resolution reflection/refraction acquisition is not feasible for large survey areas. Satellite images and vibrator plate attributes are dense low‐cost data, which can be used in spatially extrapolating velocities from sparse uphole data by geostatistics. We tested this approach in two different areas of Saudi Arabia and found that the optimal recipe depends on the local geology.     

An Approach for Passive Removal of Residual LNAPL from Groundwater

Light nonaqueous phase liquids (LNAPLs) are a problematic challenge for obtaining site closure or no further action remediation sites. The source of the LNAPLs varies from leaking underground petroleum storage tanks, to manufacturing facilities where oil leaks create LNAPL accumulations beneath factory floors. Active recovery using pumping or periodic vacuum recovery from wells or sumps is used for remediation, but usually has disappointing results when LNAPL reaccumulates to thicknesses exceeding the 0.01-foot action level recognized by many states. This paper presents a simple passive approach for recovering persistent LNAPL using nonwoven hydrophobic oil absorbing cloth. The method used laboratory trials to assess physical properties of the cloth. Parameters observed and assessed included sorptive capacity and rate, buoyancy, and LNAPL wicking. It was determined that the cloth could be rolled and secured with cable ties for placement in the wells/sumps. Two placement designs were developed, one where rolled sorbent freely floated on the well/sump fluid surface and a second where the sorbent roll was placed in the fluid column at a fixed depth. Sorbents were then used at two manufacturing facilities where LNAPLs persisted for decades. In both instances, many wells/sumps were reduced to thicknesses below the action level in less than 2 months. In most wells, LNAPL did not reaccumulate. Where it did reaccumulate, it was less than 50% of the original thickness. Using laboratory-derived recovery rates, cloth sorbents could be sized to minimize placement/recovery frequency while effectively recovering LNAPL.     

Probabilistic characterization of cyclic shear modulus reduction for normally to moderately over-consolidated clays

Evaluation of the cyclic shear modulus of soils is a crucial but challenging task for many geotechnical earthquake engineering and soil dynamic issues. Improper determination of this property unnecessarily drives up design and maintenance costs or even leads to the construction of unsafe structures. Due to the complexities involved in the direct measurement, empirical curves for estimating the cyclic shear modulus have been commonly adopted in practice for simplicity and economical considerations. However, a systematic and robust approach for formulating a reliable model and empirical curve for cyclic shear modulus prediction for clayey soils is still lacking. In this study, the Bayesian model class selection approach is utilized to identify the most significant soil parameters affecting the normalized cyclic shear modulus and a reliable predictive model for normally to moderately over-consolidated clays is proposed. Results show that the predictability and reliability of the proposed model out performs the well-known empirical models. Finally, a new design chart is established for practical usage.     

Detection and analysis of LNAPL using the instantaneous amplitude and frequency of ground‐penetrating radar data

This paper reports the results of using the ground‐penetrating radar (GPR) method to detect light non‐aqueous phase liquids (LNAPL) floating on the water table in an area where the thickness of LNAPL present ranges from a few centimetres to several decimetres. To understand the GPR response in this context, GPR theoretical models are calculated using information from the literature and hydrogeological field data. The study revealed that in the case of LNAPL floating on the water table in a static condition, there is an increase in the reflection amplitude from the water table due to the decrease in the capillary fringe. Nevertheless the amplitude of reflection from the water table can discriminate the contaminated from the non‐contaminated zone. Apart from an analysis of the real traces, the analysis of some attributes of the complex trace, instantaneous amplitude, phase and frequency, are also good tools to detect hydrocarbons floating on the water table. Such attributes, depending on both the signal frequency and the hydrocarbon thickness, can also give information about the thickness of the hydrocarbon layer. It is concluded that analysing the lateral variations in signal amplitude of the real trace and in the amplitude, phase and instantaneous frequency of the complex signal permits the delimiting of the area polluted by the hydrocarbon.     

基于稀疏反演的OBS数据多次波压制方法

自由表面多次波压制是海底地震仪（Ocean Bottom Seismometer,OBS）数据处理和成像中的难点,OBS数据多次波能量强,周期长,严重影响深层一次反射波的处理和成像.不同于常规拖缆观测系统,OBS数据站点一般相隔较远,仅仅利用检波点稀疏的波场信息难以压制OBS数据中的自由表面多次波.本文采用拖缆数据与OBS数据联合,利用稀疏反演估计（Estimation of Primaries and Multiples by Sparse Inversion,EPSI）方法,研究了OBS数据自由表面多次波压制理论,分析了OBS多次波产生的机理,详细推导了拖缆数据与OBS数据联合预测OBS多次波的EPSI方法基本原理.通过利用拖缆数据的信息,实现了OBS检波点稀疏数据多次波的压制问题.EPSI方法通过稀疏反演直接估计一次反射波,避免了SRME（Surface Related Multiple Elimination）方法中自适应相减对有效信号的损害,保真了一次反射有效信号,理论模拟OBS数据验证了方法的有效性.     

Sequential analysis of hydrochemical data for watershed characterization

A methodology for characterizing the hydrogeology of watersheds using hydrochemical data that combine statistical, geochemical, and spatial techniques is presented. Surface water and ground water base flow and spring runoff samples (180 total) from a single watershed are first classified using hierarchical cluster analysis. The statistical clusters are analyzed for spatial coherence confirming that the clusters have a geological basis corresponding to topographic flowpaths and showing that the fractured rock aquifer behaves as an equivalent porous medium on the watershed scale. Then principal component analysis (PCA) is used to determine the sources of variation between parameters. PCA analysis shows that the variations within the dataset are related to variations in calcium, magnesium, SO4, and HCO3, which are derived from natural weathering reactions, and pH, NO3, and chlorine, which indicate anthropogenic impact. PHREEQC modeling is used to quantitatively describe the natural hydrochemical evolution for the watershed and aid in discrimination of samples that have an anthropogenic component. Finally, the seasonal changes in the water chemistry of individual sites were analyzed to better characterize the spatial variability of vertical hydraulic conductivity. The integrated result provides a method to characterize the hydrogeology of the watershed that fully utilizes traditional data.     

Probabilistic residual capacity assessment of mainshock-damaged multi-span simply supported concrete girder bridges subjected to aftershocks

Bulletin of Earthquake Engineering - Since post-mainshock events following a major earthquake are likely to occur, it is imperative to have an understanding of the functionality status of...     

Field Tracer Test for the Design of LNAPL Source Zone Surfactant Flushing

A field tracer test was carried out in a light nonaqueous phase liquid (LNAPL) source zone using a well pattern consisting of one injection well surrounded by four extraction wells (5‐spot well pattern). Multilevel sampling was carried out in two observation wells located inside the test cell characterized by heterogeneous lithology. Tracer breakthrough curves showed relatively uniform flow within soil layers. A numerical flow and solute transport model was calibrated on hydraulic heads and tracer breakthrough curves. The model was used to estimate an average accessible porosity of 0.115 for the swept zone and an average longitudinal dispersivity of 0.55 m. The model was further used to optimize the relative effects of viscous forces versus capillary forces under realistic imposed hydraulic gradients and to establish optimal surfactant solution properties. Maximum capillary number (N_Ca) values between injection and extraction wells were obtained for an injection flow rate of 16 L/min, a total extraction flow rate of 20 L/min, and a surfactant solution with a viscosity of 0.005 Pa?s. The unconfined nature of the aquifer limited further flow rate or viscosity increases that would have led to unrealistic hydraulic gradients. An N_Ca range of 3.8 × 10^?4 to 7.6 × 10^?3 was obtained depending on the magnitude of the simulated LNAPL‐water interfacial tension reduction. Finally, surfactant and chase water slug sizing was optimized with a radial form of the simplified Ogata‐Banks analytical solution (Ogata and Banks 1961) so that injected concentrations could be maintained in the entire 5‐spot cell.     

Probabilistic assessment of aggregate risk for bisphenol A by integrating the currently available environmental data

Bisphenol A (BPA) is an endocrine disruptor widely used in the production of polycarbonate plastics and epoxy resins. Exposures to BPA have been associated with reproductive, developmental, and cardiovascular effects. In this study, the CalTOX model was used to assess the aggregate health risks on BPA by integrating the currently available BPA data in various environmental media in Taiwan. Local parameters such as chemical properties, local landscape data, and exposure factors were used as model inputs under the continuous source mode. A reference dose (RfD) of 50 μg/kg-day was adopted in this assessment. Monte Carlo simulation was used to simulate great variability of the environmental data. Our results show that an upper limit of 95 % confidence interval of aggregate exposures for the adults (19–64 years old) was 1.05 μg/kg-day, corresponding to a hazard index (HI) of 0.021. The chemical properties (BPA half-life in surface water), intake rates (fruit, vegetable, and fluid intake), and landscape data (average depth of surface waters and leaf wet density) are critical parameters. Finally, HI value would approach to 1 as BPA concentrations in ambient air, surface water, and sediment was greater than 20 ng/m³, 100 μg/L, and 3.3 mg/kg. The quality of the risk assessment on BPA can be further improved by reduction of uncertainty of the abovementioned critical parameters as well as considering additional BPA exposures from canned and packaged goods.     

Influence of spatial distribution of sensors and observation accuracy on the assimilation of distributed streamflow data in hydrological modelling

The aim of this study is to assess the influence of sensor locations and varying observation accuracy on the assimilation of distributed streamflow observations, also taking into account different structures of semi-distributed hydrological models. An ensemble Kalman filter is used to update a semi-distributed hydrological model as a response to measured streamflow. Various scenarios of sensor locations and observation accuracy are introduced. The methodology is tested on the Brue basin during five flood events. The results of this work demonstrate that the assimilation of streamflow observations at interior points of the basin can improve the hydrological models according to the particular location of the sensors and hydrological model structure. It is also found that appropriate definition of the observation accuracy can affect model performance and consequent flood forecasting. These findings can be used as criteria to develop methods for streamflow monitoring network design.     

Integrated spatial sampling modeling of geospatial data

Sampling is to, by efficient selection of samples, acquire the accurate information about the population (the research object) at less cost. Spatial sampling is a kind of sampling toward geospatial objects or features with spatial correlation. The differences between effi-cient sampling and completely universal survey lie in quality, time and cost. Sampling provides a kind of economical, prompt and accurate survey[13]. Efficient spatial sampling can be regarded as the optimization of the sampl…