地表组合粗糙度不确定性引起的SAR反演土壤水分的不确定性分析

地表粗糙度的不确定性是引起SAR土壤水分反演结果不确定性的主要因素,现有研究大多着重于研究单个粗糙度参数（主要是相关长度）的不确定性,直接研究地表组合粗糙度不确定性的较少。本文使用偏度、峰度和四分位距3个指标来量化不确定性,通过在组合粗糙度中加入不同量级高斯噪声进行随机扰动的方法,研究组合粗糙度不确定性在反演过程中的传递,并对反演土壤水分的不确定性进行定量分析。进一步研究反演土壤水分的均方根误差对组合粗糙度不同比例误差范围的响应特征,得到满足反演精度要求的组合粗糙度误差控制范围。样区的实验分析结果表明：组合粗糙度高斯噪声标准差在0-0.045之间时,峰度取值从-0.1984到1.2501,偏度取值从0.0191到0.6791,四分位距取值从0.0018到0.0167,3个量化指标都随组合粗糙度高斯噪声量级的增大而增大,土壤水分反演值有集中在众数附近的趋势,土壤水分低估倾向比高估倾向更明显;本文提出的组合粗糙度误差控制范围可满足反演精度要求,误差控制范围与入射角负相关。     

电子探针快速自动定量矿石中矿物的方法研究

利用电子探针、能谱仪、扫描电镜和计算机等一整套仪器,对组成矿石样品中有用矿物的含量进行定量统计。既能准确识别矿物又能精确统计各矿物在矿样中的面积百分含量(面积法)。     

Selection of regional historical rainfall time series as input to urban drainage simulations at ungauged locations

It has become established practice during the past 20 years to use high-resolution historical rainfall time series as input to hydrological model packages for detailed simulation of urban drainage systems. However, sufficiently long rain series are rarely available from the exact catchment in question and simulations are hence often based on available rain series from other locations. Extreme rainfall properties of importance to the performance of urban storm drainage systems vary significantly even in regions with only minor physiographic differences. Part of this variation can be explained by regional variations of the mean annual rainfall and the remaining statistical residue can be interpreted as statistical uncertainty.In Denmark, more than 75 high-resolution rain gauges are installed across a total area of 43,000 m. About 40 gauges had sufficiently long records to be included in a comprehensive national investigation where newly developed statistical regionalisation procedures were used to model the regional variation of extreme rainfalls. On this basis, a spreadsheet model was made available for estimation of extreme design rainfalls and the associated uncertainty at any location in the country. Statistics were furthermore computed to classify historical rainfall time series according to the developed regional model, and this makes it possible to assess the uncertainty related with using different historical rain series for simulations at ungauged locations.This research indicates that use of historical point rainfall data at ungauged locations introduces a significant uncertainty that is largely overlooked in today's practice. The engineering recommendation is to select historical rain series based on an evaluation of the local physiographic characteristics (e.g., the mean annual rainfall) and a (pre-defined) desired safety level of the simulations.     

Controlled Fracture Growth by Blasting While Protecting Damages to Remaining Rock

Summary. Conventional blasting causes cracks and fractures in the rock. Controlled blasting techniques produce the macrocrack in a desired direction and eliminate microcrack in the remaining rock. Macrocrack development in desired direction is required for extraction of dimensional stone and at the same time there is need to reduce microcrack development in the block and remaining rock. To achieve the objectives, experimental work in the quarries was carried out for separating marble block from the in situ strata as practiced in some of the Indian mines by using detonating cord of 30 to 50 g/m by varying hole spacing, hole diameter, air cushioning, water and sand filled blast-holes. Blasthole notching was carried out. Further, tests were carried out by using various liners inside the blasthole to determine the damages in the extracted block and remaining rock. The designed experimental work was undertaken and rock samples were collected by coring before and after blasting for quantification of microcrack in the rock. P-wave velocity and microscopic studies were conducted for quantification of damages. Experiments were also conducted at laboratory scale for the quantification of damages in single circular and notched holes with variation of stemming and liners. The P-wave velocity close to hole always reduces after blast and in case of NG-based charge and detonating cord it decreases up to 1/3^rd. With PVC pipe and paper tube liners decrease is negligible. Thus, by using notched hole with paper tube, decrease in P-wave is minimum indicating least damage.     

GIS空间数据不确定性与质量控制的研究现状

GIS空间数据不确定性和质量控制的研究是GIS基础理论问题研究中的一个重要内容。文中具体介绍了对该问题研究的几个阶段，对目前这一理论问题的研究现状作了简要介绍，并对GIS数据质量控制的策略提出一些看法。     

中国南方中及晚奥陶世岩相古地理

中国南方是指西至金沙江一元江断裂、西北至龙门山断裂、北至城口-房县-襄樊-广济断裂、东北至郯城-庐江断裂、东至黄海和东海、南至南海的中国南方的广大地区，面积约200万km^2。在露头剖面和钻井剖面的地层学和岩石学研究所取得的各种定量及定性资料的基础上，采用单因素分析综合作图法，编制出了中国南方中奥陶统胡乐阶(庙坡阶)和}韩江阶(宝塔阶)以及上奥陶统石口阶(临湘阶)和五峰阶的各种单因素图以及相应的各世的岩相古地理图。在这些古地理图中，有7个主要的古地理单元，即滇西台地、康滇陆、扬子台地、斜坡、江南盆地、东南台地和华夏陆。前5个古地理单元属康滇古地理体系，后两个古地理单元属华夏古地理体系。这些古地理图的最大特征是定量，即每个古地理单元的划分和确定都有确切的定量的单因素图和数据为依据。这种定量的岩相古地理图在我国南方中及晚奥陶世还是首次出现。这种定量岩相古地理图在古地理学中是个重大的进展，对石油、天然气以及其他沉积矿产的预测和勘探有重要的指导作用。最后，对两个古地理体系和7个主要古地理单元在整个寒武纪和奥陶纪各期或世的历史演化进行了较详细的探讨。     

民房震害预测专家评定统计模型的探讨

本文针对专家评定意见有一定伸缩性的特点,将专家意见表示为评定论域上的模糊子集,利用可能性相加原理,对专家意见进行了统计分析,得出综合性的意见。结果表明,利用伸缩性提供的丰富信息,可以较好地总结专家意见。基于几种模型的仿真可靠性分析结果,本文推荐可靠性最高的模型作为城市平房震害预测统计手段。     

Conditioning mean steady state flow on hydraulic head and conductivity through geostatistical inversion

Nonlocal moment equations allow one to render deterministically optimum predictions of flow in randomly heterogeneous media and to assess predictive uncertainty conditional on measured values of medium properties. We present a geostatistical inverse algorithm for steady-state flow that makes it possible to further condition such predictions and assessments on measured values of hydraulic head (and/or flux). Our algorithm is based on recursive finite-element approximations of exact first and second conditional moment equations. Hydraulic conductivity is parameterized via universal kriging based on unknown values at pilot points and (optionally) measured values at other discrete locations. Optimum unbiased inverse estimates of natural log hydraulic conductivity, head and flux are obtained by minimizing a residual criterion using the Levenberg-Marquardt algorithm. We illustrate the method for superimposed mean uniform and convergent flows in a bounded two-dimensional domain. Our examples illustrate how conductivity and head data act separately or jointly to reduce parameter estimation errors and model predictive uncertainty.This work is supported in part by NSF/ITR Grant EAR-0110289. The first author was additionally supported by scholarships from CONACYT and Instituto de Investigaciones Electricas of Mexico. Additional support was provided by the European Commission under Contract EVK1-CT-1999-00041 (W-SAHaRA-Stochastic Analysis of Well Head Protection and Risk Assessment).     

Another look at the conceptual fundamentals of porous media upscaling

We suggest a critical look at the epistemic foundations of the porous media upscaling problem that focuses on conceptual processes at work and not merely on form manipulations. We explore the way in which critical aspects of scientific methodology make their appearance in the upscaling context, thus generating useful effective parameters in practice. The fons et origo of our approach is a conceptual blending of knowledge states that requires the revision of the traditional method of scientific argument underlying most upscaling techniques. By contrast to previous techniques, the scientific reasoning of the proposed upscaling approach is based on a stochastic model that involves teleologic solutions and stochastic logic integration principles. The syllogistic form of the approach has important advantages over the traditional reasoning scheme of porous media upscaling, such as: it allows the rigorous derivation of the joint probability distributions of hydraulic gradients and conductivities across space; it imposes no restriction on the functional form of the effective parameters or the shape of the probability laws governing the random media (non-Gaussian distributions, multiple-point statistics and non-linear models are automatically incorporated); it relies on sound methodological principles rather than being ad hoc; and it offers the rational means for integrating the multifarious core knowledge bases and uncertain site-specific information sources about the subsurface system. Previous upscaling results are derived as special cases of the proposed upscaling approach under limited conditions of porous media flow, a fact that further demonstrates the generalization power of the approach. Our hope is that looking at the upscaling problem in this novel way will direct further attention to the methodological exploration of the problem at the length and the detail that it deserves.I would like to thank Drs. A. Kolovos and D.T. Hristopulos for their valuable comments. The work was supported by grants from the Army Research Office (Grant no. DAAG55–98–1-0289) and the National Institute of Environmental Health Sciences (P42-ES05948 & P30-ES10126).     

A BME solution of the inverse problem for saturated groundwater flow

In most real-world hydrogeologic situations, natural heterogeneity and measurement errors introduce major sources of uncertainty in the solution of the inverse problem. The Bayesian Maximum Entropy (BME) method of modern geostatistics offers an efficient solution to the inverse problem by first assimilating various physical knowledge bases (hydrologic laws, water table elevation data, uncertain hydraulic resistivity measurements, etc.) and then producing robust estimates of the subsurface variables across space. We present specific methods for implementing the BME conceptual framework to solve an inverse problem involving Darcys law for subsurface flow. We illustrate one of these methods in the case of a synthetic one-dimensional case study concerned with the estimation of hydraulic resistivity conditioned on soft data and hydraulic head measurements. The BME framework processes the physical knowledge contained in Darcys law and generates accurate estimates of hydraulic resistivity across space. The optimal distribution of hard and soft data needed to minimize the associated estimation error at a specified sampling cost is determined. This work was supported by grants from the National Institute of Environmental Health Sciences (Grant no. 5 P42 ES05948 and P30ES10126), the National Aeronautics and Space Administration (Grant no. 60-00RFQ041), the Army Research Office (Grant no. DAAG55-98-1-0289), and the National Science Foundation under Agreement No. DMS-0112069.